Loren K. Mell, William Y. Song, Todd Pawlicki, and Arno J. Mundt
Image-guided radiation therapy (IGRT) consists of a panoply of technological applications with the common purpose of maximizing target and normal tissue localization for radiotherapy. The exact subset of applications that defines IGRT is somewhat controversial. Proposed definitions of IGRT have ranged from narrow (“external beam radiation therapy with positional verification using imaging prior to each treatment fraction”1) to broad (“any use of imaging to aid in decisions in the radiotherapy process”2), the former risking the exclusion of techniques as avant garde as adaptive four-dimensional (4D) positron emission tomography (PET), and the latter risking the inclusion of techniques as banal as a staging chest x-ray. The American College of Radiology and American Society of Radiation Oncology practice guideline defines IGRT as “a procedure that refines the delivery of therapeutic radiation by applying image-based target relocalization to allow proper patient repositioning for the purpose of ensuring accurate treatment and minimizing the volume of normal tissue exposed to ionizing radiation,”3 while Greco and Ling4defined IGRT more broadly as “the use of imaging for detection and diagnosis, delineation of target and organs at risk (OARs), determining biological attributes, dose distribution design, dose delivery assurance, and deciphering treatment response,” a so-called six-dimensional definition. For the purposes of this chapter, the authors also favor a broader perspective and define IGRT as the use of innovative imaging modalities to augment target and normal tissue localization for radiotherapy planning and delivery. This encompasses a wide range of imaging techniques used for delineation, adjusting for motion or positional uncertainty, and adapting treatment to response. Exploring IGRT in its many facets leaves one simultaneously awed by the pace and extent of technological achievements, yet daunted by the task of critically assessing their tangible benefits to patients.
RATIONALE FOR IMAGE-GUIDED RADIATION THERAPY
Increasing the accuracy and precision of radiotherapy delivery has always been a therapeutic goal. Inaccuracy refers to systematic errors that, on average, bias the treatment delivery with respect to the true target location. Systematic errors can originate, for example, from improper target delineation, poorly representative simulation, dissociation between skin marks and internal anatomy, or predictable organ motions (e.g., periodicity of a lung tumor). Imprecision, on the other hand, refers to stochastic (random) errors that introduce variance in the spatial location of treatment around the true target. Stochastic errors can originate, for example, from inevitable fluctuations in daily setup and from unpredictable target motions (e.g., uterine anteversion or retroversion). Insufficient compensation for these uncertainties leads to target underdosing and overdosing of nearby OARs, whereas overcompensation for uncertainties leads to unnecessary irradiation of normal tissue and constraints in treatment planning. This creates a tradeoff between tumor control probability (TCP) and normal tissue complication probability (NTCP) and emphasizes the role of minimizing uncertainties to enhance the therapeutic ratio of radiation.
Uncertainty in target delineation is a well-documented problem.5,6 Even among experts, reproducibly defining targets is a challenge, as both intra- and interobserver variation contribute to ambiguity in target localization, and existing guidelines for target delineation are predominantly based on qualitative judgments. Furthermore, while computed tomography (CT) and magnetic resonance imaging (MRI) have become standard for 3D planning, functional imaging techniques—particularly PET—have been increasingly incorporated into treatment planning7 to facilitate demarcation of tumor borders and characterize subregions of targets with different physiologic properties. Quantitative imaging can help raise consistency in target delineation, while automated segmentation and deformable image registration software are becoming increasingly available to facilitate and standardize treatment planning.
The use of conformal and hypofractionated radiotherapy techniques, with prolonged treatment times and steeper dose gradients, accentuates the effects of uncertainties related to target localization and the need for IGRT to compensate for them. Toxicity is often an important barrier to treatment intensification, including radiation dose escalation and intensive combined modality therapy. By mitigating toxicity, IGRT may permit implementation of more intensive, but isotoxic, treatment approaches. Furthermore, as therapies continue to improve tumor control, the importance of reducing late and chronic effects of radiotherapy becomes increasingly imperative to maximize patients’ quality of life. Determining the functional relation between IGRT, changes in tumor and OAR dose, and changes in clinical outcomes (e.g., TCP and NTCP models) are of critical importance in evaluating the effectiveness of IGRT techniques compared to standard approaches. There is a rapidly growing need for validated models to estimate the impact of IGRT on cumulative dose distributions and the corresponding effects of cumulative dose on TCP and NTCP.
Conventional radiotherapy techniques are limited due to motion and changes of both tumor and normal tissues occurring between (interfraction) or during (intrafraction) treatment. In many situations, the treatment model based on a static initial simulation is inadequate, necessitating adaptation of the initial plan. In particular, changes that occur in response to therapy could be indicative of a more or less favorable prognosis, in which case modifications to the treatment strategy could be considered. Theoretically, adaptive radiotherapy can take place either between fractions (offline) or while the patient is in the treatment position (online). Innovative strategies to monitor and optimize therapy throughout the treatment course, such as 4D PET-CT, in-room MRI, and fast online adaptive replanning, ideally will advance the quality of radiotherapy for current and future generations.
IMAGE-GUIDED TARGET AND NORMAL TISSUE DELINEATION
Positron Emission Tomography
PET has revolutionized the staging and treatment of cancer. PET scanning involves the systemic administration of a tracer labeled with a radioactive isotope, which emits positrons as it decays. The tracer accumulates in a region of interest and the emitted positron annihilates with a local negatron, releasing two 511 keV photons that propagate in 180 degrees opposite directions. The scanner is equipped with parallel mounted sensors that can detect and determine the spatial location of these annihilation events and, therefore, the regions of increased radiotracer accumulation. Most modern treatment planning systems offer tools to facilitate image registration and fusion with the planning CT to aid target delineation. Commercial software systems that incorporate deformable image registration can aid delineation by accommodating changes in patient anatomy and positioning between scans and segmenting target volumes based on quantitative methods (Fig. 11.1).6,8
FIGURE 11.1. Reductions in contour variability are observed with automatic contouring. Physician manual contours shown in blue, automatic contours modified by physicians shown in purple, and manual contours using Simultaneous Truth and Performance Level Estimation algorithm shown in brown.(From Stapleford LJ, Lawson JD, Perkins C, et al. Evaluation of automatic atlas-based lymph node segmentation for head-and-neck cancer. Int J Radiat Oncol Biol Phys 2010;77:959–966, with permission from Elsevier.)

FIGURE 11.2. Fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET-CT) scan in a patient with a right middle lobe lung carcinoma. On CT[MB15] (left), the limits of the tumor are obscured by postobstructive pneumonia and atelectasis. On the fused scan (right), the tumor is intensely FDG avid and more easily differentiated. (From Spratt DE, Diaz R, McElmurray J, et al. Impact of FDG PET/CT on delineation of the gross tumor volume for radiation planning in non-small-cell lung cancer. Clin Nucl Med 2010;35:237-243, with permission.)

F18-Fluorodeoxyglucose
The most widely used tracer is F18-fluorodeoxyglucose (18F-FDG), which is taken into cells by active transport, then phosphorylated by hexokinase, trapping the molecule intracellularly. 18F decays to 18O, and the molecule enters the glycolytic pathway, but the metabolism of FDG is slow relative to normal glucose, accounting for the high relative accumulation in metabolically active cells, including inflammatory tissue, neurons, brown fat, bone marrow, gastrointestinal (GI) epithelium, and tumors.9 Studies in many different types of cancer have found that FDG-PET improves staging,10–11,12,13,14 leading to more appropriate risk-adapted management. Other studies have found that increased FDG uptake within tumors prior to or following treatment confers an adverse prognosis,15,16,17 indicating subsets of patients suitable for alternative treatment strategies.
Multiple studies have investigated the role of FDG-PET in radiotherapy planning for lung cancer.18–23 FDG-PET imaging alters treatment volumes in approximately 40% to 60% of non–small cell lung cancer (NSCLC) patients19,21,23,24; it appears to aid targeting for mesothelioma as well.25 It is valuable both for detection of occult nodal involvement and for distinguishing tumor from atelectasis,19,26 which can be difficult to detect on CT alone (Fig. 11.2). Vanuytsel et al.21 found that FDG PET-CT altered treatment volumes in 45 of 73 (62%) lymph node–positive patients staged by mediastinoscopy; in 16 the volume was enlarged, and in 29 it was contracted. Results of the Radiation Therapy Oncology Group’s (RTOG) study RTOG-0515, a phase II trial with 52 NSCLC patients, were recently reported22; incorporation of FDG PET-CT led to alterations in nodal volumes in 51% of the 47 evaluable patients and in general led to smaller tumor gross tumor volumes (GTV) and mean lung dose. There is no definite consensus on how PET-guided volumes should be delineated, although PET does appear to improve interobserver target definitions.18 Yu et al.24 reported that the optimal standardized uptake value (SUV) threshold correlating with pathologic specimens was 31% ± 11%. However, recent studies in both phantoms and patients indicate that gradient-based methods may be a more accurate and consistent technique for target volume contouring.8,27
Studies of FDG PET in head and neck cancer (HNC) have similarly found that planning volumes are frequently altered after incorporating PET imaging.23,28–35 In a study of 40 HNC patients, Paulino et al.30 compared IMRT plans based on FDG PET to those based on CT. In 25% of patients, CT-based plans were suboptimal in covering the PET-delineated GTV. In a prospective analysis of 20 patients, Schwartz et al.32 found that IMRT plans could be optimized with FDG PET-CT to improve parotid and laryngeal sparing and allow dose escalation up to 81 Gy. A study from Memorial Sloan-Kettering Cancer Center found significant differences in target volumes drawn with and without PET or MRI guidance, indicating complementary information comes from multiple sources, including CT and physical examination, and is necessary to optimally tailor target delineation for each patient.33 GTVs delineated by FDG PET appear to be significantly smaller than those delineated on CT alone.33–35 Some concerns exist regarding the technical aspects of PET-guided radiation therapy (RT) in HNC, including difficulties in establishing optimal image registration36 and large variability in target definition.37 Recent studies indicate that automated techniques to guide delineation in HNC can improve consistency,6,38,39 however, target delineation is still highly dependent on both segmentation and reconstruction methods, emphasizing the importance of clarifying and standardizing methodologies across institutions.40,41
FDG PET for target delineation has been extensively studied in both esophageal14,42,43–47 and rectal48,49–52 cancers. Hong et al.44 studied 25 esophageal cancer patients undergoing FDG PET-CT for radiotherapy planning; PET influenced target delineation in 21 patients (84%), with changes classified as major in 9 (34%). However, Muijs et al.14 reviewed 30 studies spanning 1,222 patients and found no conclusive evidence supporting the necessity of PET for radiotherapy planning. It is clear that PET is helpful in determining lymph node status and detecting occult metastases, but whether it is superior to other modalities for GTV delineation remains unclear. If used to delineate GTV, a threshold of 2.5 for either absolute SUV or SUV relative to liver uptake has been proposed.47 As for rectal cancer, Braendengen et al.48 compared GTV delineation with MRI versus FDG PET-CT in 77 patients; PET-guided volumes were smaller than MRI volumes, but PET-guidance appeared to complement data from MRI and led to alteration of management in 15% of patients. Dynamic FDG PET-CT is also an emerging technique50 that could play a role in the future for image-guided target delineation for rectal and other cancers.
Researchers at Washington University have extensively studied FDG PET for cervical cancer.53–55 PET-guided targeting for cervical cancer patients with involved para-aortic lymph nodes can facilitate safe dose escalation to 60 Gy along with intensity-modulated radiation therapy (IMRT).53 Serial changes in cervical tumor volume during brachytherapy54 and external beam RT55 have been documented, but it is unclear yet how treatment should be adapted in the face of poor response. Lin et al.56 reported that FDG PET-based brachytherapy planning significantly optimized GTV coverage without increasing bladder or rectal dose. Liang et al.57 analyzed 10 patients treated with FDG PET-guided bone marrow–sparing IMRT for pelvic malignancies in a prospective trial. IMRT plans significantly reduced dose to active bone marrow, and this approach was feasible and well tolerated. Related work by Rose et al.58has indicated that dose to metabolically active bone marrow subregions identified by FDG PET is a significant predictor of hematologic toxicity.
Studies of FDG PET for radiation planning in other disease sites have found mixed results. It has potential utility in contouring lumpectomy cavities in breast cancer,59 involved nodal or involved field radiation therapy for lymphoma60,61 and GTV for pancreatic cancer,62 but less apparent utility in treating sarcoma.63 Application of FDG PET in central nervous system (CNS) tumors is limited by high background uptake of FDG by normal brain cells, whereas its utility in prostate cancer is limited by relatively lower uptake of FDG in tumor cells. Douglas et al.64 successfully used FDG PET in 40 patients for dose escalation in malignant glioma, however, no improvement in patient outcomes was observed. As discussed below, other PET tracers have been more extensively studied in these diseases.
FIGURE 11.3. Comparison of magnetic resonance imaging, L-(methyl-11C)methionine positron emission tomography (PET_, and O-(2-[18F]fluoroethyl)-L-tyrosine PET for a patient with grade III astrocytoma. (From Grosu AL, Astner ST, Riedel E, et al. An interindividual comparison of O-(2-[18F]fluoroethyl)-L-tyrosine (FET)- and L-[methyl-11C]methionine (MET)-PET in patients with brain gliomas and metastases. Int J Radiat Oncol Biol Phys 2011;81:1049–1058, with permission from Elsevier.)

Other Positron Emission Tomography Tracers
Although most studies to date have focused on FDG, many other radiotracers have been studied, including 18F-thymidine (FLT), 18F-misonidazole (MISO), 18F-azomycin arabinoside (FAZA), 18F-fluoroethyl-L-tyrosine (FET), 18F-choline, 11C-choline, 11C-methionine (MET), 11C-acetate, and 60Cu(II)-diacetyl-bis(N4-methylosemicarbazone) (60Cu-ATSM). 15O and 13N—labeled H2O, CO2, O2, or NH3—molecules have also been used to measure blood flow, apoptosis, or hypoxia with PET.65–67 New tracers are continually being developed and tested. For further discussion of novel molecular imaging applications, refer to several reviews.65,66–68,69
Background uptake of MET in neural tissue is low, making it useful for image-guided planning of brain tumors. Grosu et al.70 analyzed 39 patients with glioblastoma multiforme (GBM); in 29 patients (74%), MET uptake extended (up to 4.5 cm) beyond the tumor identified by MRI. MET also appears to improve GTV delineation for skull-base meningiomas.71 A limitation of MET PET, however, is the short half-life of 11C (20 minutes). FET leads to different GTV compared to MRI alone72 but appears to be comparable to MET (Fig. 11.3),73 with the advantage of a longer isotope half-life. Milker-Zabel et al.74 evaluated 68Ga-(0)-D-Phe (1)-Tyr (221)-octreotide (DOTATOC) PET in 26 meningiomas patients. This technique takes advantage of high expression of the somatostatin type 2 receptor, which binds DOTATOC. In 19 patients, DOTATOC PET significantly influenced target design. Gehler et al.75 found similar results, with DOTATOC PET-CT significantly influencing target volumes in 17 of 26 patients.
Several investigators have explored PET-guided RT using MISO76,77 and FAZA.78 The Trans-Tasman Radiation Oncology Group correlated hypoxia identified on MISO PET with outcomes in 45 stage III or IV HNC patients undergoing chemoradiotherapy, with or without the hypoxic cytotoxin tirapazamine.77 Baseline hypoxia and residual hypoxia (detected on MISO PET scans at week 4 or 5 of treatment) were correlated with higher rates of locoregional failure. Four of six patients with residual hypoxia recurred locally compared to 4 of 23 patients without residual hypoxia. 60Cu-ATSM has attracted attention for hypoxia imaging due to its potential biokinetic advantages and better resolution. 60Cu-ATSM PET-guided hypoxia imaging has been investigated in HNC and cervical cancer.79,80 In a pilot study in 14 cervical cancer patients, 60Cu-ATSM appeared to provide good prognostic discrimination; 5 of 5 patients with hypoxic tumors developed recurrence versus 3 of 9 with normoxic tumors.80
Both 11C-choline and 18F-choline have been studied in prostate cancer81,82; however, the utility of this approach in routine settings is unclear. SUV at 60% of the maximum value appears to correlate well with histopathologic specimens as a threshold for contouring dominant intraprostatic lesions.81 FLT PET has shown utility in some settings, such as esophageal cancer, where its positive predictive value for involved nodes may be higher than for FDG PET.51 In a study of five NSCLC patients undergoing serial baseline and on-treatment FLT PET, reductions in FLT uptake within both tumor and bone marrow were observed.83 However, its value for tumor and nodal delineation in rectal cancer and HNC appears more limited.84,85
In summary, a wide body of literature supports the utility of PET for image-guided treatment planning. Further research efforts are needed to standardize approaches and determine the impact of PET-guided planning on patient outcomes.
Magnetic Resonance Imaging
The utility of MRI in RT planning, particularly for CNS, HNC, and pelvic malignancies, is well known.86–94 In addition, MR simulators and MRI-only planning approaches are becoming more widely available (Fig. 11.4).95Increasingly, quantitative MRI techniques have been used to improve RT planning. For example, functional MRI (fMRI) has been used to reduce radiation dose to normal functioning brain during planning for CNS tumors.96–100Aoyama et al.99 evaluated the use of magnetoencephalography and anisotropic diffusion weighted MRI to plan 20 patients, 15 of whom had arteriovenous malformation (AVM). In 15 patients, targets were modified with significant reduction in the volume of sensitive regions receiving more than 15 Gy. Fast imaging employing steady-state acquisition can facilitate visualization of the trigeminal nerve during radiosurgery planning.101,102 The 1H MR spectroscopy (MRS) has also been used to guide planning in gliomas.103,104 Underdosing of 1H MRS-delineated metabolically active areas has been associated with worse outcomes in GBM.104
In patients with prostate cancer, van Lin et al.105 have reported the feasibility of escalating doses to 90 Gy to dominant intraprostatic lesions identified by 1H MRS. MR lymphography with intravenous ferumoxtran-10 has also been used to identify pathologic nodal involvement in prostate cancer (Fig. 11.5).106,107 In a study of 47 patients treated with salvage RT for rising postprostatectomy prostate-specific antigen (PSA), 79% were found to have at least one aberrant positive lymph node, including 10 of 18 (61%) with a PSA less than 1.0 ng/mL. MR lymphography may therefore be useful in helping to define nodal boost volumes in prostate cancer.
FIGURE 11.4. Integration of magnetic resonance (MR) imaging and radiotherapy, with trolley solution and specialized docking device for smooth transfer between MR and linear accelerator. (From Karlsson M, Karlsson MG, Nyholm T, et al. Dedicated magnetic resonance imaging in the radiotherapy clinic. Int J Radiat Oncol Biol Phys 2009;74:644–651, with permission from Elsevier.)

FIGURE 11.5. Fusion of magnetic resonance (MR) lymphography (upper right and left and lower left) and computed tomography (CT) (lower right). With the help of MR lymphography, the node identified on CT is identified as pathologic. (From Meijer HJ, van Lin EN, Debats OA, et al. High occurrence of aberrant lymph node spread on magnetic resonance lymphography in prostate cancer patients with a biochemical recurrence after radical prostatectomy. Int J Radiat Oncol Biol Phys 2012;82(4):1405–1410; with permission from Elsevier.)

FIGURE 11.6. Axial iterative decomposition of water and fat with echo asymmetry and least-squares estimation magnetic resonance imaging scans of the pelvis in a gynecologic cancer patient undergoing chemoradiotherapy. Scans were acquired at baseline (left), midtreatment (middle), and posttreatment (right) and show a steady increase in fraction of fat relative to water within the pelvic bones, indicated by conversion to progressively higher signal.

Dynamic contrast-enhanced (DCE) MRI has been investigated for RT planning in a variety of tumors including HNC, lung, rectal, and cervical cancers.108–110,111 Mayr et al.111 studied 102 cervical cancer patients treated with DCE MRI. Patients with a low total volume of tumor voxels with low DCE signal had significantly worse tumor control and disease-specific survival. Liang et al.112 used an MRI technique called iterative decomposition of water and fat with echo asymmetry and least-squares estimation to study fractional changes in fat content of pelvic bone marrow during pelvic chemoradiotherapy (Fig. 11.6). Conversion of bone marrow from low fat, high cellularity to high fat, low cellularity during RT is readily observed, enabling noninvasive quantitative methods to analyze the impact of local changes in radiation dose.
In summary, novel and quantitative or functional MRI techniques have been increasingly implemented for RT planning. Ongoing research is seeking to define the clinical benefits of MRI-based IGRT techniques.
Single Photon Emission Computed Tomography
Single photon emission computed tomography (SPECT) is a relatively inexpensive functional imaging technique, with a wide range of potential tracers. Although PET is generally more quantitatively accurate than SPECT in determining in vivo radioactivity distribution,69 SPECT tracers often have a longer half-lives and release less energy, leading to favorable dosimetry and utility for studying slower biological processes.69 Nonetheless, SPECT appears to have more limited utilization than PET in RT planning.7
Several studies of 111In-capromab pendetide radioimmunoscintigraphy (RIS) have found it useful in planning both external beam RT113,114–115 and brachytherapy116,117 for prostate cancer. Jani et al.114 reported that RIS influenced RT volumes and decision making in a significant proportion of patients undergoing postprostatectomy salvage RT. Of 54 evaluable patients, 18.5% had treatment plans altered by RIS, including 4 who were not offered RT based on the RIS findings. In a multivariate analysis of 107 patients (53 planned with RIS), RIS was associated with an improved 3-year biochemical failure-free survival (bFFS).115 A similar analysis of 82 patients undergoing RIS for salvage therapy, however, did not reveal a clear benefit of RIS.118 Ellis et al.116 treated 80 low-intermediate risk prostate cancer patients with RIS-assisted brachytherapy. Regions of the prostate showing increased RIS uptake were prescribed 150% of the standard dose. The overall 4-year biochemical failure-free survival was 97.4%.
Other applications of SPECT-guided treatment planning have been studied, including 123IMT (123I-alpha-methyl-L-tyrosine) SPECT for gliomas119–121 and meta-123iodo-benzylguanidine scans for neuroblastoma.122 Krengli et al.121 studied 21 patients with high-grade gliomas using fused 99mTc-MIBI SPECT and MRI. Similar to findings of Grosu et al.,119 target volumes were significantly augmented by SPECT, with an average increase of 33% over MRI alone, particularly in resected cases.
SPECT has also been used to guide normal tissue avoidance. In patients with NSCLC, Christian et al.123 used 99mTc SPECT to identify functional lung to avoid using inverse RT planning, and showed the V20 of functioning lung could be reduced without compromising target coverage. Roeske et al.124 used 99mTc SPECT to identify active bone marrow subregions to reduce hematologic toxicity in patients receiving pelvic chemoradiotherapy.
IN-ROOM IMAGE-GUIDED RADIOTHERAPY TECHNIQUES
Numerous studies have found that motion and setup errors for various disease sites can be quite substantial,125 leading to inaccurate or suboptimal treatment plans and potentially poorer tumor control.126–129,130 For example, in a study of 127 prostate cancer patients treated without daily prostate localization, de Crevoisier et al.130 found that significant rectal distension resulting in anterior displacement of the prostate at simulation was an independent risk factor for biochemical failure. Strategies to address motion have included wide margins, elaborate immobilization techniques, resimulation and replanning, and portal radiography. IGRT approaches take advantage of more frequent and sophisticated imaging to setup the patient and localize the target with greater accuracy, ostensibly improving treatment delivery and allowing reduction of margins.
This section will describe various IGRT technologies developed to address both interfraction and intrafraction motion. Particular attention is devoted to clinical applications of in-room IGRT technologies and data supporting their use. Although some of these technologies have been available for many years, others have only recently been introduced, yet appear to have been adopted rapidly by clinicians.131 Many others are still under development and have not yet been implemented clinically.
Ultrasound
Ultrasound (US) is one of the most common IGRT approaches in practice, particularly for prostate cancer.131 It involves emission of high-frequency sound waves to produce images of internal anatomy, consisting of a transducer encased in a probe applied to the skin surface, reflecting sound waves back as echoes when a change in impedance is encountered due to density differences between tissues. The time an echo takes to return is used to calculate the depth of the tissue interface. Image information is obtained along the beamline of the probe, with a complete image created by sweeping across the region of interest. Although three operational modes are available, B (brightness) mode is the primary one used. Readers interested in a more complete description are referred elsewhere.132
Several US products are currently available. All have a system to map the image coordinate system to both the linear accelerator (LINAC) coordinate system and the simulation images. This can be achieved either by tracking the position of a stereotactic arm or using an infrared imaging system to detect the probe position. The target location can be determined in the room prior to treatment, with the necessary shifts conducted to bring the anatomy into position. A widely used US system is the B-mode acquisition and targeting (BAT) transabdominal system (NOMOS, North American Scientific, Chatsworth, CA). The probe is registered to a stereotactic arm on the LINAC gantry, allowing its position to be tracked. Prior to treatment, transverse and sagittal images are generated and the target and normal tissue contours from the planning CT scan are overlaid on the US images. If the target is displaced, the CT structures are maneuvered on a touch screen and the necessary 3D couch shifts are calculated. Another system is SonArray (Varian Medical Systems, Palo Alto, CA), which combines US localization with an optical guidance system to track the position of the probe in the treatment room.133,134 A similar system is available from BrainLab (Heimstetten, Germany). The I-Beam system (Computerized Medical Systems Inc, St. Louis, MO) uses a machine vision pattern recognition technique to calibrate the probe relative to the gantry. Clarity (Elekta, Stockholm, Sweden) incorporates structure-based tissue matching and segmentation tools to facilitate contouring.
At experienced centers, the additional time required to implement US-based IGRT is reported to be 5 minutes or less.135,136 Additional time may be necessary, however, when the technology is first adopted or if moves need to be checked online by a physician. Increased skin-to-prostate distances, increased thickness of tissue anterior to the bladder, and less prostate gland present superior to the symphysis can reduce image quality.137 However, reproducibility and image quality are generally reported to be high for prostate localization.137–139 Probe-induced prostate motion is also a consideration, as displacements up to 1 cm have been observed,140 although generally the magnitude of displacements is 3 mm or less.133,135,138,140,141
Numerous investigators have compared US systems versus conventional setup techniques (i.e., external skin markers) for prostate localization.133–135,136,137,138,139,140,141–144,145 In a review of nine series, Kuban et al.145 reported that shifts from the initial setup were greatest in the anterior-posterior (AP) direction, with standard deviations in the AP, superior-inferior (SI), and right-left (RL) directions ranged from 2.7 to 6.4 mm, 2.8 to 7.3 mm, and 2.1 to 4.6 mm, respectively, with maximum values of 29.8, 30.3, and 34.9 mm, respectively. Several investigators have evaluated shifts in prostate patients undergoing daily portal imaging,138,140 removing the impact of patient setup uncertainty. In a study of 35 patients using BAT, Little et al.140 reported mean shifts of –1.3, –1.6, and –0.89 mm in the AP, SI, and RL directions, respectively. Trichter and Ennis138 reported that the margins necessary to encompass the prostate at the 95% confidence level using daily portal imaging alone (without US) were 9.2, 14.6, and 10.2 mm in the RL, SI, and AP directions, primarily due to organ motion rather than setup error.
Although US-based localization accounts for interfraction organ motion, it does not address intrafraction motion. However, the magnitude of such motion in patients with prostate cancer appears to be small. In a study of 20 patients undergoing pre- and posttherapy US, Huang et al.146 noted mean shifts of 0.2 ± 1.3 mm, 0.1 ± 1 mm, and 0.01 ± 0.4 mm, in the AP, SI, and RL directions, respectively. Trichter and Ennis138 similarly noted small mean intrafraction shifts using pre- and posttherapy US; however, large maximum shifts of 8.1, 20.4, and 8.3 mm in the AP, SI, and RL directions, respectively, were noted.
Several authors have compared prostate localization with CT136,145,147,148 and implanted fiducial markers (144,149,150). Lattanzi et al.136 found average disagreements between the modalities were small: –0.09 mm (AP), –0.03 mm (SI), and –0.16 mm (RL). O’Daniel et al.148 compared four target alignment techniques: skin marks, bony registration, US, and in-room CT. Direct alignment with US and CT provided better target coverage compared to the other methods. Scarbrough et al.150 compared US with fiducial markers in 40 patients and found that US was associated with significantly greater systematic and random errors than fiducials. Similarly, Gayou and Miften151 found that US was associated with a higher percentage of shifts greater than 5 mm compared to cone beam CT (CBCT).
Limited data exist regarding the impact of US IGRT on patient outcomes. Indirect support is garnered, however, from the excellent outcome of prostate cancer patients treated using daily US guidance.152,153–154 Kupelian et al.152reported on 100 patients undergoing short-course IMRT, using daily BAT. Margins around the target were 4 mm posteriorly, 8 mm laterally, and 5 mm in other directions. With a median follow-up of 66 months, the 5-year bFFS was 85%, with 5% of patients developing grade 2 or 3 rectal sequelae. Similarly, Zerini et al.153 treated 25 low- to intermediate-risk patients to 70 Gy in 30 fractions with daily BAT. With a mean follow-up of 45 months, one patient had biochemical relapse and no patients developed grade 3 or higher late rectal toxicity.
Jani et al.155 evaluated acute toxicity in patients treated with (n = 50) versus without (n = 49) daily BAT, reporting that patients treated using BAT experienced less rectal toxicity. They also separately analyzed late sequelae in patients treated with and without BAT.156 Although less toxicity was observed in patients treated with BAT, there was no significant correlation between BAT usage and toxicity on multivariate analysis. Bohrer et al.157 also reported that patients treated using BAT had less rectal toxicity compared to patients treated prior to BAT implementation. However, no differences in bladder toxicity or PSA control were seen between the two groups. US may also be useful in the postprostatectomy setting.158,159 Chinnaiyan et al.159 evaluated SonArray in six post-prostatectomy patients. The average shifts from the initial setup were 5 ± 4 mm, 3 ± 4 mm, and 3 ± 3 mm, in the AP, SI, and RL directions, respectively.
Fewer studies have reported on the utility of US in other tumor sites. US can be useful to confirm bladder volume and position in gynecologic patients undergoing pelvic RT, which is known to be volatile.160 In intracavitary brachytherapy planning, US is a valuable tool for both detection and prevention of perforations.161,162 Several investigators have also recently evaluated US-based IGRT to define and verify position of the lumpectomy boost cavity in breast cancer.163,164 Boda-Heggeman et al.165 used US guidance for frameless stereotactic radiosurgery (SRS) for liver metastases, using active breathing control to reduce tumor motion. Fuss et al.166 evaluated US-based IGRT in 62 patients with upper abdominal malignancies, predominantly pancreatic cancer. The mean shifts in the AP, SI, and RL directions were 6 ± 5.31 mm, 6 ± 6.7 mm, and 4.9 ± 4.35 mm, respectively. Meeks et al.167 performed US-guided extracranial SRS in 16 patients. Single-fraction doses ranging from 12.5 to 24.0 Gy were delivered without significant acute complications. US-guided extracranial SRS appears safe for treatment of GI malignancies as well.168–170For example, in a series of 10 gallbladder cancer patients treated to a median dose of 59 Gy with daily US localization, all but one experienced grade 2 or less acute toxicity.168
As newer IGRT approaches are introduced in the clinic, the future role of US remains unclear. Declining utilization was noted in a recent survey.131 Nonetheless, an advantage of US is that it does not involve additional ionizing radiation, making it likely that it will always play a role in clinical practice.
Video and Surface Imaging
Video-based techniques for patient positioning have been used for over 25 years. Connor et al.171 described a close-circuit television camera and monitor system plus a videodisc recorder, which reduced positional errors to less than 1 mm. The recorder stored a reference image of each treatment setup and was superimposed, in reverse color, on the live camera image. Investigators at the University of Chicago developed an online video “subtraction” setup system, consisting of wall- and ceiling-mounted charge-coupled device cameras linked to a computer equipped with a frame grabber.172,173 After optimal positioning, a reference image is obtained and, on subsequent days, is subtracted in real time from live video images. Subtraction images are displayed on an in-room monitor and used to interactively realign the patient. Milliken et al.172 reported high levels of accuracy in both 2D and 3D repositioning using this system. Johnson et al.173 performed a clinical study of this system in five HNC patients undergoing twice daily RT. Conventional setup was used in the morning, with the video used simply to record the final patient position. In the afternoon, patients were first aligned with conventional techniques and then live subtraction images were used for setup correction. Although the standard deviation of setup error using room lasers was σ = 3.9 mm, it was reduced by 56% (σ = 1.7 mm) using video setup. The entire process generally required approximately 1 minute.
Several investigators have evaluated video-based setup techniques in breast cancer patients. Baroni et al.174 developed a video system based on optoelectronics and close-range photogrammetry that captures in real time the position of markers on the patient that are used to monitor and adjust the patient position. Bert et al.175 investigated a commercial stereovision surface imaging system (AlignRT, Vision RT Ltd, London, UK) for setup of partial-breast irradiation patients, which uses close-range photogrammetry to generate a 3D image of the patient’s surface. The resultant image is compared to an image generated at simulation or of the patient’s external surface generated from a CT dataset. Phantom studies found that the system was capable of identifying translational shifts and rotations of less than 0.1 degree. The AlignRT system is currently being used clinically in the treatment of breast cancer patients undergoing adjuvant whole breast RT (Fig. 11.7).176
A novel use of the AlignRT system is in the setup and monitoring of patient positioning for those undergoing cranial SRS using minimal immobilization. Cerviño et al.177 used AlignRT to monitor positioning in patients immobilized with only a head mold that leaves the face exposed. Using anthropomorphic head phantoms and volunteers, the motion inside the head mold was small and could be accurately detected by real-time surface imaging. These investigators recently presented their initial experience using this approach in 23 patients undergoing SRS.178 The average setup time for both surface imaging and CBCT was 26 minutes, with surface imaging requiring on average 14 minutes. The mean time from initial setup on the table through the last delivery was 40 minutes. Overall, eight patients (35%) required repositioning during treatment. Others have similarly used video surface imaging in patients undergoing cranial radiosurgery.179
Li et al.180 and Djajaputra and Li181 developed a real-time video-guided IMRT approach in breast cancer patients using a camera capable of capturing full-frame 3D surface images through a single snapshot. Patient setup parameters are determined semiautomatically, and the IMRT leaf segments are modified in real time. Unlike other video approaches, this system compensates for changes in surface topology by modifying the treatment plan rather than adjusting the patient position. This system is also being applied to patients undergoing fractionated stereotactic RT.182
Overall, video and surface imaging approaches are among the least commonly used IGRT technologies in the clinic today, with only 3.2% of responding physicians reporting its use on a recent survey performed in the United States.131 As new commercial systems and new applications are introduced (e.g., real-time positioning monitoring for frameless radiosurgery), utilization of such technologies may increase in the future.
FIGURE 11.7. AlignRT for breast cancer. A: Alignment of patient surface to planning computed tomography using video cameras. B: Surface monitoring showing the region of interest of the breast in pink and the tolerance level displayed on the left in dark blue.

Planar Imaging
Planar imaging approaches, which include both megavoltage (MV) and kilovoltage (kV), are the most common in-room IGRT approaches used today. In a national survey from 2009, the percentage of respondents using megavolt- and kilovolt-planar systems were 63% and 58%, respectively.131 These systems were used in nearly all disease sites, particularly CNS tumors and prostate cancer (together with implanted fiducial markers). MV-planar systems were adopted earlier, with the majority of users (53%) having implemented them by 2004. The adoption of kilovolt-planar–based systems occurred later, with the majority of users (54%) having adopted them by 2006.
Electronic Portal Imaging Devices
Electronic portal imaging devices (EPIDs) provide a means of generating an electronic image of a treatment field with the patient on the treatment table. Similar to conventional portal imaging, EPIDs produce images using the therapeutic (MV) beam. However, EPIDs overcome many of the limitations of conventional port films, including delays due to image processing. Moreover, EPID images can be digitally processed for better visualization of the relevant anatomy and stored for offline review. Numerous EPIDs have been introduced including video-based, liquid ion chamber, and solid-state systems. Most commercial systems in use today are based on flat-panel amorphous silicon (aSi) detectors. With this method, a scintillator first converts x-rays to visible light. A photodiode array then converts the light to electrons, which in turn activate pixels in a layer of aSi. The pixels are then read out in successive rows, processed, and displayed on a computer screen for viewing. Clinical studies illustrating the benefits of EPID-based IGRT approaches initially appeared in the early 1990s,183–184,185 and since then it has been studied in many disease sites.186–192 Readers interested in an overview of EPID technologies are referred elsewhere.193,194
Concerns over increased workload and excess dose have increased interest in on offline EPID approaches. One approach is the so-called shrinking action level strategy.195 Initially, EPID images are obtained on a given number (Nmax) of consecutive days. The 3D setup deviation is calculated offline, and the length of the deviation vector is compared to a predetermined “action level.” If exceeded, a setup correction is performed at the next session. The feasibility of this approach was demonstrated in a multi-institutional prostate cancer trial.196 Favorable results have also been reported in lung cancer197 and HNC.198 An alternative approach is the “no action level” strategy, whereby the mean setup error over a fixed number of fractions is calculated and always corrected for.199
EPID is useful for prostate localization in conjunction with implanted seed markers.200,201 Pouliot et al.202 presented an overview of the prostate seed marker protocol developed at University of California–San Francisco (UCSF) using EPID. Prior to simulation, three gold markers were inserted (two laterally on each side of the prostate and one in the apex). A planning CT scan was performed, the location of each marker was contoured, and a digitally reconstructed radiograph (DRR) was generated. Prior to treatment, a lateral EPID image was obtained to assess SI and AP shifts, requiring approximately 0.02 Gy of dose. Comparison of the center of mass of the markers with their expected position on the DRR was used to evaluate the need for repositioning. If shifts were greater than 3 mm, the couch was adjusted. Most investigators report excellent marker visualization,200–201,202,203,204 particularly when gold markers are used with a minimum diameter of 0.9 mm.201 At least two gold markers are typically visible,203 and high reproducibility has been reported using this approach.204,205 Although marker migration is a potential concern, several investigators have reported minimal migration of implanted markers.200–201,202,203,204 Kupelian et al.206 evaluated seed marker position throughout the course of treatment in 56 prostate cancer patients. Of 2,037 alignments, the average directional variation of all intermarker distances was –0.31 ± 1.41 mm. Only two markers (1%) showed frequent changes in position, most likely caused by prostate deformation. Of note, others have reported marker movement in patients undergoing hormonal therapy as the prostate involutes.207
Limited data exist for EPID and implanted markers in other tumor sites.208 EPID has been compared with CBCT nongenitourinary (GU) sites, with some studies reporting superior setup accuracy with CBCT.209–211 Topolnjak et al.210 compared the two modalities in 20 breast cancer patients undergoing adjuvant RT, noting that EPID underestimated the bony anatomy setup error by 20% to 50%.
Several investigators have reported outcomes of patients treated with EPID-based IGRT. Nichol et al.212 treated 140 stage T1 or T2 prostate cancer patients to 75.6 Gy with daily EPID setup corrections based on bony anatomy. Overall, late grade 2 or higher GI and GU toxicities were noted in 2% and 1% of patients, respectively. Others have reported favorable results using EPID and the shrinking action level approach.213 Ost et al.214 compared acute GI and GU toxicity in 196 prostate cancer patients treated with postoperative salvage RT. Overall, patient position was corrected using EPID (prior to 2006, n = 116) or CBCT (after 2006, n = 80). Patients treated with CBCT verification had less grade 1 or 2 GU toxicity compared to those treated using EPID. No differences were seen in GI or high-grade GU toxicity between the two groups.
EPID has long been among the most common in-room IGRT technologies used clinically. In the national IGRT survey,131 EPID was the most commonly used IGRT technology across nearly all disease sites. With the proliferation of newer technologies, notably CBCT, however, its use may decrease in the future.
CyberKnife
CyberKnife (Accuray Inc, Sunnyvale, CA) consists of a compact X-band 6 MV linear accelerator coupled to a multijointed robotic manipulator with 6 degrees of freedom (Fig. 11.8).215 The current generation of CyberKnife technology consists of two precisely calibrated diagnostic x-ray tubes fixed to the ceiling of the treatment vault and two nearly orthogonal aSi flat-panel detectors. After coarse alignment, projected images from the cameras are automatically registered with the DRRs from the planning CT. Changes in target position are relayed to the robotic arm, which adjusts pointing of the treatment beam. During treatment, the robotic arm moves through a sequence of positions (nodes). At each node, a pair of images is obtained, the patient position is determined, and adjustments are made.
CyberKnife was initially based on tracking the skeletal anatomy of the skull and upper spine, limiting treatment to tumors of the brain, head and neck, and upper spine. Subsequently, the ability to track implanted fiducial markers was introduced, allowing treatment of lower spinal tumors with submillimeter precision.216 More recently, software has been developed that obviates the need for implanted fiducials in spine patients and enables respiratory tracking.
Several preclinical studies have been published reporting high levels of accuracy of CyberKnife. Murphy and Cox217 noted a mechanical accuracy of the beams of 0.7 mm with a calibration accuracy of plus or minus 0.5 mm along each axis. Yu et al.218 reported submillimeter accuracy in a phantom study using fiducial markers. Many clinical studies have described favorable outcomes for patients treated with CyberKnife, including adenoma,219,220schwannoma,221 glioma,222,223 brain metastases,224 meningioma,225 trigeminal neuralgia,226,227 AVM,228 and tumors abutting the optic nerves or chiasm.229,230
A provocative use of the CyberKnife is for pediatric brain tumors. CyberKnife avoids the need for a rigid head frame and, in select children, general anesthesia. Moreover, frameless treatment can be fractionated. Investigators at Baylor University reported promising results with the CyberKnife in infants231 and the general pediatric population.232 Giller et al.232 treated 21 children (median age, 6 years) with CNS tumors, with a median dose of 18.8 Gy primarily delivered in a single fraction. At a median follow-up of 18 months, 10 children had evidence of decreased tumor size or stable disease on follow-up imaging.
Many studies have focused on CyberKnife for spinal lesions (Table 11.1).233,234–237,238,239,240,241–244,245,246,247,248 Dodd et al.233 treated 51 patients with 55 benign intradural extramedullary spinal tumors, with a median dose of 19.6 Gy delivered primarily in 1 or 2 fractions. All patients with more than 2 years of follow-up had either stable or smaller tumors on repeat imaging. Most patients had stable or improved symptoms. One developed a spinal cord injury 8 months following treatment. Investigators at the University of Pittsburgh reported on 125 primarily malignant spinal lesions (115 patients) treated to a median dose of 14 Gy in 3 to 5 fractions (Fig. 11.9).238 At a median follow-up of 18 months, no patient developed new symptoms or had evidence of RT sequelae, despite the fact that 68% had received prior RT. Of 79 patients presenting with pain, 74 (94%) noted improvement. Others have reported similarly promising results in patients with benign and malignant spinal tumors.235–249
Recently, CyberKnife has been used to treat extracraniospinal sites.250–258 However, outcome data remain limited. King et al.252 treated 41 low-risk prostate cancer patients, prescribing 36.25 Gy in 5 fractions of 7.25 Gy. At a median follow-up of 33 months, two patients developed grade 3 GU toxicity and no patients developed grade 3 or higher GI toxicity. Less rectal toxicity was observed with an every-other-day approach versus 5 consecutive days (0% vs. 38%; P = .0035). At last follow-up, all patients remained biochemically controlled. Of 32 patients with 1-year minimum follow-up, 25 (78%) achieved a PSA nadir of 0.4 ng/mL or less.
Several investigators have explored the use of CyberKnife in patients with lung cancer.251,254 Nuyttens et al.251 treated 20 patients with lung tumors in whom fiducial markers had been implanted for tumor tracking. A system of light-emitting diodes placed on the patient’s abdomen was used to monitor the location of fiducials with respect to respiratory motion and provide feedback to the robotic arm of the CyberKnife for tracking. Four-dimensional CT simulation scans were acquired, and patients were treated with hypofractionated radiation (36 to 60 Gy in 3 fractions). With a median follow-up of 4 months, no local failures were observed.
FIGURE 11.8. CyberKnife radiosurgery system. Two amorphous silicon x-ray detectors are positioned orthogonally to the treatment couch. (From Gerszten PC, Ozhasoglu C, Burton SA, et al. Cyberknife frameless stereotactic radiosurgery for spinal lesions: clinical experience in 125 cases. Neurosurgery2004;55:89–99, with permission.)

FIGURE 11.9. X-ray with isodose lines of a treatment plan for a renal cell metastasis to C5 in a 70-year-old woman (arrow). The patient had severe pain that recurred after initial external beam irradiation. The tumor was treated with 14 Gy to the 80% isodose line in a single fraction (orange line). Notice the conformality of the isodose lines around the spinal cord. The patient had significant pain relief within 1 month of treatment. (From Gerszten PC, Ozhasoglu C, Burton SA, et al. Cyberknife frameless stereotactic radiosurgery for spinal lesions: clinical experience in 125 cases. Neurosurgery 2004;55:89–99, with permission.)

TABLE 11.1 OUTCOMES FROM SELECTED SERIES OF SPINAL TUMORS TREATED WITH CYBERKNIFE

Novalis
The Novalis system (BrainLab Inc, Westchester, IL) consists of a 6 MV linear accelerator equipped with a micro-multileaf collimator (MLC). Infrared camera and stereoscopic kilovoltage x-ray imaging technologies are used for patient positioning. Two 80 to 100 kV x-ray tubes mounted in the floor of the treatment room are used to acquire images of internal anatomy (e.g., the vertebral bodies), which are automatically compared with the DRRs from the planning CT scan. The cameras are used to detect the positions of sensors on the patient’s skin, which are automatically compared with their position at simulation to determine necessary couch shifts.
In an analysis of the positional accuracy of the Novalis system, simulated infrared marker shifts revealed that positioning errors of the planned isocenter were 0.6 ± 0.3, 0.5 ± 0.2, and 0.7 ± 0.2 mm along the lateral, longitudinal, and vertical axes, respectively.259 Simulated target shifts indicated that positioning errors of the planned isocenter were 0.6 ± 0.3, 0.7 ± 0.2, and 0.5 ± 0.2 mm along the three axes. Others studies have similarly reported submillimeter accuracy with the Novalis system.260
Various investigators have reported outcomes of patients with intracranial tumors and conditions treated with Novalis.261,262–268 In a series of 32 trigeminal neuralgia patients, Chen et al.261 found good-to-excellent pain relief in 78%. Pedroso et al.263 treated 44 cranial AVM patients to a median dose of 15 Gy in a single fraction. The obliteration rate was 53%. Three patients (7%) bled following treatment; however, none developed significant late sequelae.
Others have reported on the use of Novalis in spinal tumors.269–272 Investigators at Henry Ford Hospital treated 10 spinal metastases with external beam RT (25 Gy in 10 fractions) followed by a 6 to 8 Gy SRS boost on a Novalis unit (Fig. 11.10).271 All patients presenting with pain experienced significant relief. No acute or chronic sequelae were noted at a median follow-up of 6 months. These same investigators reported their experience with SRS alone (10 to 16 Gy) in 49 patients with 61 spinal metastases.272 Complete and partial pain relief was noted in 85% of patients. Others have reported similarly promising results in malignant and benign spinal tumors.269,270
The Novalis system is being increasingly used in other tumor sites.273–274,275–279 Ryu et al.277 treated 13 HNC tumors with either SRS (12 to 18 Gy in 1 fraction) or hypofractionated RT (30 to 36 Gy in 6 fractions). Six patients achieved a complete and three a partial response. Soete et al.278 reported short-term outcomes of prostate cancer patients treated with hypofractionated RT (56 Gy in 3.5 Gy daily fractions). Acute grade 2 rectal and bladder toxicity was noted in 12% and 29% of patients, respectively, with no grade 3 or higher toxicities. In a separate study, Soete et al.279 noted significant improvements in positioning of prostate cancer patients using Novalis compared to conventional setup techniques. Setup errors of 5 mm or more occurred in 2% to 14% of patient positionings, versus 28% to 53% with conventional positionings.
FIGURE 11.10. An intensity-modulated stereotactic spinal radiosurgery plan in a patient treated on a Novalis unit. The patient had multiple myeloma involving the seventh and eighth thoracic vertebral bodies. (From Ryu S, Yin FF, Rock J, et al. Image-guided and intensity-modulated radiosurgery for patients with spinal metastasis. Cancer 2003;97:2013–2018, with permission.)

FIGURE 11.11. The real-time tumor-tracking radiation therapy (RTRT) system. (From Harada T, Shirato H, Ogura S, et al. Real-time tumor-tracking radiation therapy for lung carcinoma by the aid of insertion of a gold marker using broncho-fiberoscopy. Cancer 2002;95:1720–1727, with permission.)

Real-Time Tumor Tracking
The real-time tumor-tracking radiation treatment (RTRT) system (Mitsubishi Electronics Co Ltd, Tokyo, Japan) consists of four sets of diagnostic x-ray tubes and imagers (Fig. 11.11).280 Each x-ray unit has a 1.5 MHU x-ray tube with a fixed collimator mounted in the floor with a corresponding imager mounted in the ceiling. During treatment, two of the four x-ray systems are selected to track an implanted fiducial marker using motion-tracking software.281The treatment beam is gated to irradiate when the position of the marker coincides with its planned position.
Phantom experiments demonstrate that the RTRT system is highly accurate, with geometric accuracy better than 1.5 mm for moving targets up to a speed of 40 mm per second. Dose due to the diagnostic x-ray monitoring ranges from 0.01% to 1% of the target dose measured in a chest phantom.280 A 4D RTRT system has also been developed.282
Investigators at Hokkaido University in Japan have presented a number of clinical studies using the RTRT system.280–293 In an early report, Shirato et al.280 described the treatment of 14 patients with a variety of tumors, including lung, bladder, prostate, liver and rectal cancers. All patients were treated with tight planning target volume (PTV) margins (<10 mm). At a median follow-up of 6 months, no local or marginal recurrences were noted. These investigators and others have explored the RTRT system in tumors of the lung,281,286,289–291 prostate,283,285 GI tract,287,293,294 and female genital tract.288,290 In a study of 18 lung cancer patients, Harada et al.281 placed gold markers via bronchofiberoscopy under video guidance. Markers were shown to be stable in 65% of tumors throughout treatment. All patients received 35 to 40 Gy in 4 fractions, with tight (5 mm) margins around the tumor. At a median follow-up of 9 months, all were locally controlled, with only one patient developing symptomatic pneumonitis.
Hashimoto et al.287 treated 20 GI patients (14 esophagus, 2 stomach, and 4 duodenum) with the RTRT system. Markers were placed either intraoperatively or via endoscopy and tight (5 mm) margins were used. At a median follow-up of 10 months, no grade 3 or higher late toxicities were noted. Ahn et al.294 used the RTRT system in three unresectable pancreatic cancer patients. All received intraoperative electrons and external beam RT. None developed grade 2 or higher acute toxicity. At a median follow-up of 3 months, three partial responses and one stable disease were noted. The RTRT system is discussed further in the section “Respiratory Gating” below.
University of Michigan System
Investigators at the University of Michigan developed an IGRT system for high-dose irradiation of intrahepatic tumors comprising a racetrack microtron and diagnostic x-ray tubes mounted on the floor and ceiling of the treatment room.295 An in-room shielded control booth allows direct visual contact of the patient during kilovoltage imaging. This system was designed for use in conjunction with an active breathing control (ABC) apparatus to reduce tumor motion due to respiration. In a feasibility study, daily orthogonal images were obtained under ABC and aligned to the planning CT, using the diaphragm for SI alignment and the vertebral bodies for LR and AP alignment.296 Overall, 171 of 262 (65%) fractions required repositioning. Setup errors were reduced from 3.8 mm (AP), 6.7 mm (SI), and 4.0 mm (RL) to 2.3 mm (AP), 3.5 mm (SI), and 2.1 mm (RL). Treatment time was 25 to 30 minutes, with breath holds of up to 35 seconds.
In a review of the 128 patients with unresectable intrahepatic tumors treated with high-dose conformal RT and hepatic artery floxuridine, Ben-Josef et al.297 reported a median survival of 15.8 months, which was significantly improved over historical controls. Grade 3 and 4 toxicities were noted in 21% and 9% of patients, respectively. However, outcomes of patients treated with or without online setup corrections were not compared, so the direct effect of IGRT on patient outcome is not clear.
FIGURE 11.12. The prototype gantry-mounted image-guided radiation therapy (IGRT) system developed by Takai et al. at Tohoku University in Japan. (From Takai Y, Mitsuya M, Nemoto K, et al. Development of a new linear accelerator mounted with dual x-ray flouroscopy using amorphous silicon flat panel x-ray sensors to detect a gold seed in a tumor at real treatment position [abstr]. Int J Radiat Oncol Biol Phys 2001;51[Suppl]:381, with permission.)

FIGURE 11.13. The integrated radiotherapy imaging system developed at Massachusetts General Hospital. (Courtesy of Steve Jiang, PhD.)

Prototype Gantry-Mounted Systems
Investigators at Tohoku University in Japan have modified a commercial linear accelerator to include x-ray generators (mounted on the gantry at plus or minus 45 degrees from the beam axis) opposite two sets of aSi flat panel sensors with images obtained at 15 frames per second (Fig. 11.12).298 In a subsequent study, Takai et al.299 used this system to image a gold seed on a rotating disc and a seed implanted in a metastatic lung tumor and reported excellent visualization of both. This system was combined with a dynamic MLC approach, potentially allowing tracking and continuously irradiating a moving target.
Inter- and intrafractional prostate organ motion has been evaluated using this system in eight patients with implanted gold markers.299 After alignment using skin marks, images were obtained and isocenter shifts were calculated. Images were also obtained prior to every field with corrections of intrafractional displacements greater than 1 mm. The mean magnitudes of interfractional displacements were 1.76, 3.14, and 3.78 mm in the LR, SI, and AP directions, respectively. Corresponding intrafractional displacements were 0.45, 1.08, and 1.45 mm, respectively. Of 214 fractions, 84 (39%) required intrafractional corrections.
An integrated radiotherapy imaging system (IRIS) comprising two gantry-mounted diagnostic x-ray units mounted on either side of the machine head opposite two aSi flat panel detectors has been developed at Massachusetts General Hospital (Fig. 11.13).300 The system co-rotates with the gantry, maintaining relative positions between the megavoltage and kilovoltage x-ray beams. It is also integrated with the pulsing of the LINAC to limit the amount of megavoltage noise during imaging. Each flat panel has an active area of 39.7 cm by 29.8 cm. To accommodate larger coverage for cone-beam CT acquisition (see “Volumetric Imaging” below), the panels are able to slide 13.2 cm along their long axes from their home position. Unlike commercially available systems, the dual-imager IRIS provides a stereoscopic view of the tumor, allowing assessment of the 3D trajectory of tumor motion. To date, no clinical studies have been published using this system.
Commercial Gantry-Mounted Systems
Two commercially gantry-mounted planar imaging systems are currently available: the Varian On-Board Imaging (OBI) system (Varian Medical Systems, Palo Alto, CA) and the Elekta Synergy (Elekta Oncology Systems, Norcross, GA). Both produce high-resolution diagnostic quality x-ray images of the patient in treatment position with considerably less dose than EPID. The Varian OBI system consists of an x-ray tube opposed to an aSi flat panel detector, both mounted to the LINAC gantry orthogonal to the treatment beam axis. The x-ray tube and aSi detector panel can be retracted from the imaging position via robotic arms (Fig. 11.14). The x-ray tube produces 40 to 150 kV x-rays with an image size of 40 by 30 cm2. Images are acquired at 7.5 frames per second at 0.195 mm per pixel and 15.0 frames per second at 0.390 mm per pixel.
Fox et al.301 presented an overview of OBI software and hardware and a performance evaluation of the automated image registration algorithm. In phantom verification tests, the registration algorithm was capable of detecting known translations and rotations with an accuracy of less than 1.4 mm for a 3D vector offset (0.4 mm, 1.1 mm, and 0.8 mm in the lateral, longitudinal, and vertical dimensions, respectively). Earlier work demonstrated that the isocenter stability of the LINAC with the OBI arms extended is less than 1 mm.302
The Elekta Synergy system consists of an x-ray tube opposed to an aSi flat panel detector, both mounted to the LINAC gantry orthogonal to the treatment beam axis. Similar to the Varian system, the x-ray tube and aSi detector panel can be retracted via mechanical arms. The x-ray tube produces 60 to 150 kV x-rays with an image size of 41 by 41 cm2. Modern day LINAC-based kilovolt imaging systems were originally developed by investigators at the William Beaumont Hospital (Fig. 11.15). A full description of their original system is provided by Jaffray et al.303
Commercial gantry kilovoltage planar systems are becoming increasing used clinically in the radiation oncology community.131 Lawson et al.304 presented their early clinical experience using the OBI system in 117 patients (2,088 sessions) with a wide variety of tumors. Overall, the great majority of alignments based on either bones or implanted fiducial markers were small; however, 10% of lateral, longitudinal, and vertical shifts were 0.8 cm or more, 0.6 cm, and 0.7 cm, respectively. Median vector shifts varied between anatomic sites: 0.42 cm (HNC), 0.40 cm (brain), 0.59 (prostate), and 0.73 cm (breast). Pisani et al.305 evaluated the accuracy of online setup errors using a kilovoltage and megavoltage dual-beam imaging system mounted on an Elekta SL-20 linear accelerator. Inter- and intraobserver variability was less with kilovoltage imaging in most cases.
Perkins et al.306 presented the outcome of 13 GI tumor patients undergoing IMRT and concomitant chemotherapy with daily online setup corrections based on bony landmarks or surgical clips using the OBI system. Of 276 fractions, average isocenter shifts were 0.30 ± 0.42 cm (vertical), 0.33 ± 0.34 cm (longitudinal), and 0.35 ± 0.39 cm (lateral). Maximum corresponding shifts were 4.0, 2.3, and 2.4 cm, respectively. Grade 2 or higher acute nausea and diarrhea were noted in five and two patients, respectively. At a median follow-up of 6 months, 21% had disease regression and 71% stable disease. Investigators at Karolinska University reported on OBI in prostate cancer patients with implanted gold markers.307 Shifts were determined by comparing daily orthogonal films of the patient on the treatment couch with reference DRRs at simulation, using a 2D matching algorithm with couch movements made remotely. The entire process added less than 1 minute to the treatment.
Others have presented their initial experiences using OBI in patients with prostate,308 pancreas,309,310 HNC,311,312 and gynecologic cancers.313–330 This system has also been used in patients undergoing SRS,314 stereotactic body RT (SBRT),315 and intracavitary brachytherapy.316 An intriguing use of OBI is the daily localization of select normal tissues. Willis et al.317 used daily OBI for verifying the location of kidneys in patients undergoing abdominal irradiation. In that study, kidneys were well visualized in 60% of the images. Ability to visualize the kidneys depended on multiple factors, including the relative anterior-posterior patient and kidney separation, axial profile of the kidneys, and relative contrast between the kidneys and surrounding structures.
FIGURE 11.14. The Varian On-Board Imaging (OBI) system. (From Fox T, Huntzinger C, Johnstone P, et al. Performance evaluation of an automated image registration algorithm using an integrated kilovoltage imaging and guidance system. J Appl Clin Med Phys 2006;7:97–104, with permission.)

FIGURE 11.15. A modified Elekta linear accelerator (LINAC) with dual kilovoltage and megavoltage imaging capability. (From Jaffray SA, Drake DG, Moreau M, et al. A radiographic and tomographic imaging system integrated into a medical linear accelerator for localization of bone and soft-tissue targets. Int J Radiat Oncol Biol Phys 1999;45:773–789, with permission from Elsevier.)

Volumetric Imaging
In the IGRT survey, 59% of practicing radiation oncologists reported using volumetric imaging approaches clinically, most commonly in HNC, lung, GI, and prostate cancers.131 Compared to other in-room IGRT approaches, volumetric IGRT technologies had been adopted more recently, with the majority of users having adopted them only since 2007.
Fusion of Computed Tomography and Linear Accelerator
The fusion of CT and LINAC (FOCAL) system comprises a Mitsubishi EXL-15DP linear accelerator (Mitsubishi Electric, Tokyo, Japan), a high-speed DX/I General Electric CT scanner (GE Medical Systems, Tokyo, Japan), and conventional x-ray simulator (Fig. 11.16). Developed at the National Defense Medical College in Japan, this system was designed primarily for stereotactic irradiation of lung tumors.318 The gantry axes of the LINAC, CT scanner, and simulator are all coaxial, and the table can be rotated in three directions, allowing imaging with the CT scanner and simulator and treatment with the LINAC. Accuracy of the matching of the LINAC isocenter with the CT image is 0.5 mm or less.
Uematsu et al.318–321 published a series of reports on the utility of FOCAL. Lung cancer patients are immobilized supine and instructed to perform shallow breathing, often with the aid of an oxygen mask. The position and motion of the lung tumor are first evaluated using planar x-rays. The table is then rotated to the CT and serial thin-slice scans are performed at 4 seconds per slice to ensure capturing of the full extent of tumor motion. The target volume is determined, the plan generated, and the table is rotated to the LINAC for treatment. Using this approach, Uematsu et al.319 treated 50 stage I or II lung cancer patients, primarily with 50 to 60 Gy in 5 to 10 fractions. At a median follow-up of 36 months, local control was 94%. No adverse sequelae were noted, apart from minor bone fractures and temporary pleural pain in two and six patients, respectively.
In a separate study, FOCAL was used to evaluate intrafraction tumor stability in 38 lung and 12 liver tumor patients.320 Overall, no intrafraction movements greater than 10 mm were noted, and 68% of lesions had clinically negligible changes in position (0 to 5 mm). The percentage of upper lung, lower lung, and liver tumors with 5 mm or less movements were 100%, 50%, and 25%, respectively. However, in addition to coaching all patients on shallow breathing, abdominal belts were used in select patients to further reduce motion.
FIGURE 11.16. Fusion of computed tomography (CT) and linear accelerator (LINAC) unit (top). The table is rotated to the x-ray simulator to monitor respiratory motion, then to the CT for scanning (middle), and finally to the LINAC for treatment (bottom). (From Uematsu M, Shioda A, Suda A, et al. Intrafractional tumor position stability during computed tomography (CT)-guided frameless stereotactic radiation therapy for lung or liver cancers with a fusion of CT and linear accelerator (FOCAL) unit. Int J Radiat Oncol Biol Phys 2000;48:443–448, with permission from Elsevier.)

Memorial Sloan-Kettering Cancer Center System
Investigators at Memorial Sloan-Kettering Cancer Center (MSKCC) have constructed a treatment system consisting of a conventional CT scanner (Phillips Medical Systems, Milpitas, CA) and a Clinac 2100EX linear accelerator (Varian Medical Systems, Palo Alto, CA).322,323 The CT scanner couch and LINAC table are aligned, permitting a smooth transfer to the LINAC after the CT is performed. In an initial report, Yenice et al.322 described the treatment of paraspinal patients with this system. Patients were first immobilized in a stereotactic body frame, using pressures points on select skeletal structures. A planning CT scan was then performed and an IMRT plan generated. A CT scan in the treatment room was then obtained and automatically registered using bony landmarks and surgical hardware to the planning CT scan. Prior to treatment, a second registration was performed using fiducial markers on the frame and patient. The entire process required approximately 60 to 85 minutes for the initial fraction. Overall 3D accuracy of the system was 1.3 ± 0.8 mm.
The outcome of 35 paraspinal tumor patients (14 primary, 21 metastatic) undergoing IMRT using the MSKCC system has been presented.323 Overall, 24 (68%) had received prior RT. A planning margin of 10 mm was used, except at the spinal cord interface where 5 mm was used. The median prescribed dose was 20 Gy in 5 fractions. At a median follow-up of 11 months, the 2-year local control for primary and metastatic tumors was 75% and 81%, respectively. Of 30 patients with more than 3 months follow-up, 90% experienced excellent palliation. No patient developed late RT-related sequelae. In their latest report focusing on previously irradiated patients,324 daily CT myelograms were performed to improve localization of the spinal cord and cauda equina.
Recently, investigators at MSKCC published a study of patients with extracranial metastases treated with either single fraction or hypofractionated SBRT regimens.325 The 3-year actuarial local progression-free survival for the entire group was 44%. However, lesions that were treated with high-dose single fraction sizes (≥24 Gy) had a local progression-free survival of 88%, compared to 21% in lesions treated with lower single fraction doses (<24 Gy) and 17% in those undergoing hypofractionated RT.
Computed Tomography on Rails
The initial CT-on-rails system was developed at the University of Yamanashi in Japan. It consists of a linear accelerator, a CT scanner, and a common treatment couch, with the LINAC and the CT gantries positioned at opposite ends of the patient couch.326 This system minimizes patient movement and displacement by moving the gantry of the CT scanner instead of the couch within the gantry. The basis of this system is the Smart Gantry system (GE Medical Systems, Tokyo, Japan), which comprises one middle and two side rails. The side rails ensure controlled horizontal gantry movement, whereas the middle rail guides the gantry forward and backward in the direction of scanning. Kuriyama et al.326 reported that the positional accuracy of the common couch was 0.2, 0.18, and 0.39 mm in the lateral, longitudinal, and vertical directions, respectively. The scan-position accuracy of the CT gantry was less than 0.4 mm in all three axes.
In a series of reports, Onishi et al.327,328 described the utility of the CT-on-rails system in patients with unresected lung cancer. Twenty-two stages I to IIIB patients were treated using voluntary breath hold and self-directed beam control. Patients were able to turn the beam on or off using a hand-held switch.327 Using fluoroscopy, a comfortable degree of breath hold was identified, which maintained tumor position. Tumor position was found to be highly reproducible, with average positional differences of 2.2, 1.4, and 1.3 mm in the SI, AP, and RL positions, respectively, between the daily and planning CT scans. In a separate report, they treated 35 stage I lung cancer patients with 60 Gy in 10 fractions.328 At a median follow-up of 13 months, 94% of tumors were locally controlled. Five patients developed mild (grade 1 or 2) late respiratory symptoms.
Recently, several investigators have published experiences using commercial CT-on-rails systems. Investigators at M.D. Anderson Cancer Center used Varian ExaCT Targeting System (Varian Medical Systems, Palo Alto, CA), which integrates a high-speed CT scanner on rails (GE Medical Systems, Milwaukee, WI) with a Varian dual-energy LINAC equipped with a 120 MLC.329,330 The couch base is rotated to position the patient for either treatment or scanning, without the need to transfer onto the CT couch. Court et al.331 reviewed the accuracy of this system and noted that the largest single uncertainty was the couch position on the CT side after a rotation (0.5 mm in the lateral direction). All other sources of uncertainty, including the difference in couch sag between the CT and LINAC, were less than 0.3 mm.
Chang et al.330 treated 15 patients with spine metastases with IMRT on a phase I clinical trial using ExaCT. All patients were immobilized in a stereotactic body frame and received 30 Gy in 5 fractions, with a maximum cord dose of 10 Gy. On average, the duration of the daily procedure was 1.5 hours. At a median follow-up of 9 months, no patient developed significant RT-related sequelae. These investigators reported the outcome of 63 patients with 74 spine lesions treated using CT-on-rails on the phase I trial and a subsequent phase II trial.332 At a median follow-up of 21.3 months, the 1-year local progression-free survival was 82%, with 52% of patients pain free at 12 months. No patient developed late grade 3 or higher neurologic sequelae. Favorable results have similarly been reported using this approach in patients with renal cell spine metastases333 and those undergoing reirradiation.334
Others have reported their experiences using the Siemens Primatom CT-on-rails (Siemens Oncology Systems, Concord, CA). This system consists of a Somatom CT scanner and a Primus linear accelerator in the same vault sharing a common table or couch (Fig. 11.17).335–338 As with other systems, the CT scanner is moved on a pair of horizontal rails. Wong et al.335 used Primatom to deliver the boost treatments in 108 prostate cancer patients undergoing IMRT. Overall, isocenter adjustments were common. The percentage of adjustments in the AP, SI, and LR directions were 54%, 27%, and 34%, respectively. Corresponding shifts of 1 cm or greater were noted in 15%, 4%, and 5% of patients, respectively.
Ma and Paskalev339 provided an excellent review of in-room CT systems and techniques. The future of such systems remains unclear given the increasing availability of other commercial volumetric imaging systems, including on-board CBCT and helical tomotherapy.340 However, the value and possible applications of high-quality in-room conventional CT images remains an interesting area for clinical research.
Megavoltage Systems
Early Megavoltage Computed Tomography Systems
The underlying principle of megavoltage CT (MVCT) is analogous to kilovoltage CT, namely an x-ray source and detectors are used to reconstruct 2D images into 3D datasets. The first MVCT system was developed in 1982, consisting of a modified 4 MV linear accelerator with a detector array mounted on the LINAC gantry.341 In addition to the appeal of using the megavoltage beam for imaging, MVCT has the added benefit of producing images free of the streaking artifacts common in kilovoltage CT, secondary to dental fillings or hip prostheses.
More recently, investigators at the University of Tokyo mounted a small detector on the gantry of a 6 MV LINAC in order to generate MVCT images in lung tumor patients undergoing SRS.342,343 All patients were instructed to maintain shallow breathing during planning and treatment to minimize organ motion. Moreover, at simulation, tumor motion was assessed by fluoroscopy, and, if greater than 1 cm, an oxygen mask and a belt compressing the chest and abdomen were used. Immediately prior to treatment, a MVCT was obtained on the treatment table and appropriate shifts are made. In a series of 14 patients treated with a median single fraction dose of 20 Gy using this approach, the overall local control was 95%. Moreover, although all patients with greater than 3 months follow-up had interstitial lung changes, only one developed symptomatic pneumonitis.
FIGURE 11.17. The Siemens Primatom computed tomography-on-rails system. (From Wong JR, Grimm L, Uematsu M, et al. Image-guided radiotherapy for prostate cancer by CT-linear accelerator combination: prostate movements and dosimetric considerations. Int J Radiat Oncol Biol Phys 2005;61:561–569, with permission from Elsevier.)

FIGURE 11.18. The helical Tomotherapy system. (From Tomsej M. The Tomotherapy Hi-Art System for sophisticated IMRT and IGRT with helical delivery: recent developments and clinical applications. Cancer Radiother 2006;10:288–295, with permission from Elsevier.)

FIGURE 11.19. Color wash showing dose distribution for a 20-year-old female patient treated with targeted total body irradiation using Tomotherapy. The target structure is skeletal bone. Relative sparing of the brain, oral cavity, thyroid, lungs, heart, soft tissue, and gastrointestinal tract is seen. (From Wong JYC, Rosenthal K, Liu A, et al. Image guided total marrow irradiation (TMI) using helical Tomotherapy in patients with multiple myeloma and acute leukemia undergoing hematopoietic cell transplantation. Int J Radiat Oncol Biol Phys 2009;73:273–279, with permission from Elsevier.)

Helical Tomotherapy
The Tomotherapy system (Tomotherapy Inc., Madison, WI) has a 6 MV LINAC and a detector array mounted opposite each other on a ring gantry that continuously rotates while the couch is translated through the gantry (Fig. 11.18).344,345 MVCT imaging on the Tomotherapy system is performed by reducing the nominal energy of the incident electron beam to 3.5 MeV.346 Three acquisition modes are available (fine, normal, and coarse).
Investigators at the University of Wisconsin evaluated Tomotherapy MVCT imaging for optimizing setup in eight dogs undergoing RT.347 Prior to treatment, a MVCT scan was obtained and aligned with the planning kilovoltage CT scan in the transverse and sagittal planes. MVCT images were of sufficient quality for verification of treatment setup in all eight animals, although soft tissue contrast was inferior to that of the kilovoltage CT scans. Both the primary tumor and adjacent bony landmarks were used for alignment. The entire process took approximately 5 to 12 minutes, including 3 minutes for image acquisition.
Mahan et al.348 reported on Tomotherapy for optimizing patient setup in eight patients undergoing reirradiation of spinal metastases. The mean retreatment dose was 28 Gy, with the maximum cord dose of 27% to 56% of the prescribed dose. Prior to treatment, MVCT images were acquired and autofused with the planning CT scan, allowing calculation of couch translations. The range of interfraction displacement was as great as 1.5 cm, with standard deviations of ± 4 mm (AP), ± 4.3 (SI), and ± 4.1 (RL). At a median follow-up of 15.2 months, all eight patients responded (two partial, six complete). None developed an in-field recurrence or significant late toxicity. Others have reported the value of daily setup verification using the Tomotherapy system in other sites, notably lung cancer.349,350
A concern with the use of the Tomotherapy system for daily setup verification is image quality. Although less of a concern when bony landmarks are used, this is important when alignment is based solely on soft tissues. Song et al.351 evaluated the feasibility of Tomotherapy for daily prostate localization. MVCT images were acquired and compared to the planning kilovoltage CT images in five patients. Of note, prostate volumes were smaller and more consistent on kilovoltage CT scans. Moreover, inter- and intraobserver contouring uncertainty was greater for MVCT. Daily alignment can be improved in prostate patients, however, with implanted fiducials, which are well visualized on the Tomotherapy system.352
Tomotherapy is a popular IGRT treatment approach, with multiple dosimetric studies supporting its potential benefits.353,354–360 Multiple investigators have reported favorable results using the Tomotherapy system for HNC361 and CNS,362 pediatric,363 GI,364 gynecologic,365 and GU366 tumors. An intriguing use of Tomotherapy is in the delivery of total marrow irradiation in place of total body irradiation in leukemia patients undergoing allogeneic stem cell transplantation (Fig. 11.19).367
Megavoltage Cone-Beam Computed Tomography Systems
Megavoltage CBCT imaging is accomplished by first generating a series of 2D projections around the patient with the megavoltage beam and a detector.368 A 3D dataset is then reconstructed using the Feldkamp algorithm,369 in a process analogous to conventional CT imaging, whereby an x-ray source and a detector are mounted on a rotating gantry. However, whereas a conventional CT system uses a 1D linear detector array, the CBCT system uses a 2D array.
Multiple investigators have evaluated the utility of megavoltage CBCT,370,371–373,374,375 with the largest published experience from UCSF.370,374,375–376 Pouliot et al.374 described patient alignment and dose verification using a 6-MV Primus linear accelerator (Siemens Oncology Systems, Concord, CA) operating in arc mode equipped with an aSi flat-panel EPID. Megavoltage CBCT scans were generated using an anthropomorphic head phantom, frozen sheep or pig cadaver heads, and HNC patients, requiring doses of 0.05 to 0.15 Gy. Acquisition and processing times were both on the order of 90 seconds. Megavoltage CBCT and conventional CT datasets were registered with millimeter and degree accuracy.
Morin et al.370 evaluated the potential benefits of megavoltage CBCT imaging in HNC, lung, and pelvic cancer patients treated on a prospective clinical trial. In a locally advanced HNC patient, megavoltage CBCT detected a misalignment of the vertebral bodies and spinal cord in the neck not seen on portal imaging (Fig. 11.20). Megavoltage CBCT has also been found to complement treatment planning in patients with implanted metallic objects.377
Outcomes of patients specifically undergoing megavoltage CBCT imaging during treatment are limited. Swamy et al.378 evaluated the use of dose-escalated IMRT treatment in 12 intact prostate cancer patients. Following implantation of fiducials, patients underwent megavoltage CBCT daily to localize the prostate. At a mean follow-up of 12.2 months, 92% of patients were biochemically controlled. Only one patient developed grade 2 proctitis following treatment; no grade 3 or higher toxicities were seen.
Kilovoltage Systems
Mobile Fluoroscopic C-Arm Systems
Several groups have reported on kilovoltage CBCT scanning using a mobile fluoroscopic C-arm imager.378–380 Swamy et al.378,380 modified a commercial mobile isocentric fluoroscopic C-arm (Power-Mobil, Siemens Medical Solutions, Erlangen, Germany), replacing the standard image intensifier with an aSi flat-panel detector. A projection set of 100 to 1,000 images are obtained while the C-arm rotates around the patient in a 180-degree arc. Similar to megavoltage CBCT imaging, kilovoltage CBCT images are reconstructed using the Feldkamp algorithm, modified due to the limited projection arc.381 Similar units have been developed at other centers.382
The feasibility of using kilovoltage CBCT imaging produced by a mobile C-arm system in patients with prostate and HNC to improve setup and target localization has been presented.378 Patients underwent kilovoltage CBCT imaging weekly and the images were assessed offline. Overall, the imaging procedure was performed in less than 5 minutes with less dose than conventional CT. Although spatial resolution was good, image quality was not ideal (e.g., differentiation of the prostate from the rectum in the area of the prostate-rectum interface was poor). In sites prone to respiratory-induced motion, image quality can be improved by correlating the CBCT acquisition with breathing.380
FIGURE 11.20. Comparison of a kilovoltage computed tomography (CT) scan (left) with a megavoltage cone-beam CT (right) of a head-and-neck cancer patient. The window level of both images was adjusted to provide the best soft-tissue contrast. (From Morin O, Gillis A, Chen J, et al. Megavoltage cone-beam CT: system description and clinical applications. Med Dosim 2006;31:51–61, with permission from Elsevier.)

Gantry-Mounted Cone-Beam Computed Tomography Systems
Most major linear accelerator vendors currently offer gantry-mounted kilovoltage CBCT solutions. The Elekta Synergy and Varian OBI systems consist of kilovoltage x-ray tubes mounted opposite flat panel detectors orthogonal to the treatment beam on retractable arms.383,384 In collaboration with investigators at the University of Heidelberg, Siemens is developing an “in-line” system that places the diagnostic x-ray tube at 180 degrees to the megavoltage source (Fig. 11.21).385,386 All three systems acquire kilovoltage projections during a 360-degree gantry rotation, which are reconstructed into a 3D dataset.387
The initial prototype (and its corresponding commercial counterpart) of the Elekta kilovoltage CBCT system has been presented in reports from William Beaumont Hospital.388,389 In a phantom study in prostate cancer, kilovoltage CBCT was found to achieve a setup accuracy of 1 mm or less in the LR, AP, and SI directions. Setup error was reduced in nearly all cases and was generally within ± 1.5 mm. The entire image-guided process required 23 to 35 minutes. Others have presented their experiences using the Elekta kilovoltage CBCT system.390–394 In 20 patients with various tumors, McBain et al.390 noted sufficient image quality in all patients, including those in whom full gantry rotations were not possible (extremity and breast tumor patients). In general, soft tissue delineation was sufficient to allow assessment of the target and normal tissues. However, prostate images were not sufficiently distinct to allow organ contouring, compensation for small (<3 mm) movements, or for verification of small PTV margins.
Guckenberger et al.391 compared the utility of the Elekta kilovoltage CBCT system with EPID in terms of setup accuracy in 24 patients with a variety of tumors. Kilovoltage CBCT was found to add little in the assessment of translational errors. Translational errors detected with either approach differed by less than 1 mm in 70.7% and less than 2 mm in 93.2% of measurements. However, CBCT was superior in the detection of rotational errors. Rotational errors greater than 2 degrees were noted in 3.7%, 26.4%, and 12.4% of pelvic cancers, thoracic cancers, and HNC, respectively. Such rotational errors led to poorer target coverage and increased normal tissue dose in cases with elongated targets in close proximity to normal tissues. Several authors have presented their experience using the Varian kilovoltage CBCT system in the treatment of a variety of tumors including neuroblastoma395 and bladder cancer.396
Thilmann et al.386 evaluated the utility of the in-line kilovoltage CBCT system developed in collaboration with Siemens. In a study of various tumor sites, bony landmarks were easily visualized on all images, allowing table shifts to be automatically calculated. Soft tissue contrast was acceptable except in one morbidly obese patient. Using an action level of 2 mm, setup corrections were performed in four of six patients. Approximately 10 to 12 minutes were required to perform imaging, reconstruction, analysis, and positional corrections.
No detailed clinical outcome studies are yet available in patients treated using kilovoltage CBCT for either setup or target localization. However, Groh et al.397 compared the performance of megavoltage and kilovoltage CBCT technologies. Megavoltage CBCT was found to offer an advantage in terms of simplicity of mechanical integration with a linear accelerator. In contrast, kilovoltage CBCT was found to be superior in terms of imaging of soft tissue structures and the signal-to-noise ratio per unit dose.
In the coming years, numerous advancements are expected in kilovoltage CBCT technology. One area of active research is digital tomosynthesis (DTS), a method of reconstructing 3D slices from 2D cone beam x-ray projections data acquired with limited source angulation (e.g., 40 degrees). Unlike conventional kilovoltage CBCT approaches, DTS requires less scan time and results in less radiation exposure to the patient. Investigators from Duke University recently illustrated the ability to generate high-quality images using the DTS approach in patients with prostate, HNC, and liver tumors.398
FIGURE 11.21. Comparison of a conventional computed tomography (CT) scan (left) with a kilovoltage cone-beam CT scan (right) obtained using a mobile fluoroscopic C-arm imager in a patient with prostate cancer. (From Sorensen SP, Chow PE, Kriminiski S, et al. Image-guided radiotherapy using a mobile kilovoltage x-ray device. Med Dosim 2006;31:40–50, with permission from Elsevier.)

Electromagnetic Localization Systems
Electromagnetic localization systems are typically based on a magnetic dipole source and one or more sensors to detect a magnetic field created by the dipole. The dipole source is excited by a radiofrequency (RF) signal that creates a magnetic field. Overall, the system operates such that when the RF signal is removed, a capacitor is discharged, resulting in an oscillating magnetic dipole. A transponder is an electric device used to wirelessly transmit and receive electrical signals. The dipole sources in clinical electromagnetic systems are generally referred to as transponders. Each transponder is similar in size to a gold fiducial marker. The transponders are permanently implanted within the tissue to be treated. To date, the only commercial system is supplied by Calypso Medical Technologies, Inc. (Seattle, WA). An excellent review of this technology and its clinical use in IGRT is given by Litzenberg.399 The benefits of electromagnetic tracking systems are: (a) transponders can be implanted directly into the target, (b) nonionizing radiation is used, and (c) real-time positional determination is possible during the treatment fraction.
Particular attention has been focused on the use of the Calypso system for prostate cancer patients undergoing definitive RT.400–404 Kupelian et al.400 reported a multi-institutional study of 35 patients undergoing prostate localization and continuous monitoring during treatment. An average initial displacement (from setup skin marks) exceeding 5 mm was seen in more than 75% of sessions analyzed. Displacement of 3 mm or move and 5 mm or more for 30 seconds or longer occurred during 41% and 15% of sessions, respectively. The percentage of fractions in an individual patient with displacements of 3 mm or more varied considerably (3% to 87%). In a study of 28 patients with implanted Calypso transponders, Rajendran et al.401 noted that the average number of treatment days with shifts beyond 0.5 cm in the vertical, longitudinal, and lateral directions were 62%, 35%, and 38%, respectively. No outcome comparisons have been performed of prostate cancer patients treated with and without the Calypso system; hence, the clinical importance of this intrafraction displacement remains unclear.
Less attention has been focused on the use of the Calypso system in other tumor sites. Shinohara et al.405 recently evaluated the potential of using the Calypso system in five patients with locally advanced pancreatic cancer. Overall, the markers were well tolerated, with minimal migration noted, except in one patient who expulsed a single transponder. The mean initial shifts (from the setup markers) were 4.5 mm, 6.4 mm, and 3.9 mm in the x, y, and zdirections, respectively. Mean intrafraction motion was significant in all directions: superior (7.2 mm), inferior (11.9 mm), anterior (4.9 mm), posterior (2.9 mm), left (2.2 mm), and right (3.1 mm).
Few in-room IGRT systems provide the ability to perform continuous monitoring of target position. Thus, particularly in sites in which intrafraction motion is a concern, the use of the Calypso system remains appealing.
Emerging In-Room Imaging Technologies
Increasing interest has focused on the combining treatment devices with advanced imaging modalities to create novel in-room IGRT platforms. These platforms can incorporate functional and high-resolution imaging to facilitate better setup and target delineation than is possible with CT-based techniques. Such technologies may provide the possibility for improved adaptive RT techniques in the future.
Magnetic Resonance–Linear Accelerator Systems
MRI provides superior soft-tissue resolution compared to CT. Because linear accelerators are the dominant radiation delivery device in developed radiotherapy programs, in-room MR-LINAC systems are being developed, but to date no commercial systems are available. An early proposal for an integrated MR-LINAC was from the University Medical Center Utrecht.406 This system was designed as a 1.5-T MRI scanner with diagnostic quality imaging integrated with a 6-MV LINAC. More recently, simultaneous MRI and megavoltage transmission images were acquired with the imaging systems without interfering with each other.407 The first operational prototype system reported in the literature was at the Cross Cancer Institute.408 This prototype used a fixed gantry 6-MV LINAC in conjunction with a 0.2-T MRI system and fully operational MRIs were acquired during LINAC beam-on. There are issues with MR-LINAC systems such as magnetic interference at the LINAC due to the MR fringe fields, beam losses with the electron gun and RF noise from MLC motors. However, these are active areas of research and do not appear to be insurmountable hurdles toward the clinical implementation of MR-LINAC systems.409–411
Magnetic Resonance–Cobalt Systems
Due to some of the technical issues limiting MR-LINAC systems, MR-cobalt systems have also been developed.412 MR-cobalt systems consist of one or more high-dose-rate cobalt sources, an MRI system, and MLCs for IMRT (the same issues exist with RF noise from MLC motors as for MR-LINAC systems). A commercial cobalt-MR system has been developed by ViewRay Inc. (Oakwood Village, OH) and utilizes a 0.35-T MR, 3 KCi cobalt sources and three double-focused MLCs (Fig. 11.22).
As with MR-LINAC systems, the dose distributions can be significantly affected by high magnetic fields. The effect is a significant increase in dose at tissue air boundaries, due to returning electrons in the presence of magnetic fields, known as the electron return effect. The magnitude of this effect depends on the strength of the magnetic field. It has been demonstrated that this effect is minimal for lower magnetic fields of about 0.2 T.413 Therefore, it is advantageous to use the lowest possible magnetic field strength while still obtaining MR images with sufficient spatial resolution.
On-Board Single-Photon Emission Computed Tomography Imaging Systems
SPECT imaging uses a radiotracer attached to a biologically active molecule, which is injected into the patient. The energy of γ-ray emission depends on the radionuclide used in the procedure. A gamma camera is used in SPECT imaging to create 3D images. The gamma camera collects γ-rays that are emitted from within the patient. An image of the radionuclide location within the patient is generated from the data collected by the gamma camera. The aspects making up the gamma camera are the collimator, detector crystal, photomultiplier tube array, and reconstruction algorithm such as filtered back projection or iterative reconstruction. SPECT uses collimation (e.g., lead block containing many tiny holes that is positioned between the patient and the detector) to permit only photons of essentially parallel trajectory to pass through the collimator and reach the detector. Given knowledge of the orientation of a collimator’s holes, the original path of a detected photon is linearly extrapolated and thus used in the reconstruction algorithm to create the 3D image. Simulation studies have been performed to determine the potential localization accuracy for on-board SPECT-LINAC systems. It was determined that conventional SPECT systems were too cumbersome, and realization of such a system would be better accomplished using a smaller gamma camera with a limited imaging region that would also be mobile to move it closer to the patient and to enhance the spatial resolution.414
Proton–Positron Emission Tomography Systems
PET, similar to SPECT, is an imaging technique in which a radionuclide is synthetically introduced into a molecule of potential biological relevance and administered to a patient. However, the physics of photon emission is different from that for SPECT. In PET, the photons emitted from the radiotracer are coincident, that is, nearly back to back. Locating the source of an annihilation event is a method known as coincident detection. PET systems have similar components as SPECT systems (e.g., detectors, photomultiplier tube, collimators, and a reconstruction algorithm), except that a PET camera is constructed so that opposing detectors are used. Each annihilation event is presumed to have occurred at some point along an imaginary line between the two. This information is registered in the reconstruction algorithm. Coincidence detection is a very efficient technique and contributes to PET’s superior sampling rates and sensitivity compared to SPECT.
During proton therapy, inelastic reactions between the treatment protons and nuclei of the tissues in the patient produce small amounts of short-lived positron-emitting isotopes. PET imaging has been suggested as a method to determine the geometric accuracy of the treatment delivery. The threshold of inelastic nuclear reactions leading to tissue positron activation is in the energy range of 15 to 20 MeV. The distal activity falloff is not exactly matched to the dose falloff at the end of the proton range. Nonetheless, a clinical study was completed to investigate proton-PET IGRT for offline proton treatment verification.415 This pilot study was followed by further development of this approach to include efficient analytical models to accurately predict the expected PET images based on the treatment plan.416 Furthermore, mobile PET scanners have been investigated to provide a low-cost solution for in-room PET imaging, which also has the advantage of increasing the imaging sensitivity partly due to lower biological washout.417
FIGURE 11.22. Viewray cobalt magnetic resonance system. (Courtesy of Timothy Sokolich.)

FIGURE 11.23. Tumor trajectories in 20 liver cancer patients, measured using a total of 49 implanted markers during cone-beam computed tomography acquisition: (A) Anterior-to-posterior, (B) Posterior-to-anterior, (C) Left-to-right, and (D) Right-to-left projection view. An average motion of up to 3.0 ± 0.4 cm was observed for a patient, in 1 fraction.

FOUR-DIMENSIONAL IMAGING AND MOTION MANAGEMENT
Respiratory Motion
Respiratory-induced organ motion presents a significant challenge. Particularly for tumors in the thorax and upper abdomen, movements can be greater than 3 cm if the motion is not actively controlled (Fig. 11.23).285,418 Respiratory motion can result in imaging artifacts on both the planning CT and the CBCT used for treatment guidance. If left uncorrected, this can lead to target delineation and beam placement uncertainties that compromise the overall effectiveness of the treatment. There are numerous ways to compensate for motion and minimize its impact on the treatment integrity, including 4D imaging, 4D target delineation, increased planning margins, voluntary breath-hold and shallow breathing, abdominal compression, respiratory gating, and real-time tumor tracking. Although most of these approaches have been in clinical use in various forms, each has pros and cons that need to be weighed for use in an individual clinic.
Four-Dimensional Imaging
Four-dimensional imaging refers to the acquisition of spatial motion information over time. This can be done with CT,419,420 PET,421 or MRI.422 All have all been successfully used for RT planning. Only 4D CT has seen widespread use in the past decade, although 4D PET is gaining more interest, especially used in combination with 4D CT.423,424 The need for 4D CT is nicely illustrated in Figure 11.24. As can be seen, without 4D imaging, significant and unpredictable artifacts can render tumor visualization difficult. Depending on the scanning speed relative to the tumor motion speed, artifacts appear in different ways.425 If the scan speed is much slower than the tumor speed, a smeared image is captured. If the scan speed is much faster, tumor position and shape are captured at an arbitrary breathing phase. If the scan and tumor speeds are comparable, which is the case in Figure 11.2 and in most currently available CT scanners, the tumor position and shape are heavily distorted. Based on an experiment and computer simulations, it was found that distortions along the axis of motion could result in either a lengthening or shortening of the target. In addition to shape distortion, the center of the imaged target can be displaced by as much as the amplitude of the motion.425
To overcome these problems, a respiratory-correlated or 4D CT is performed. The idea behind 4D CT is that at every position of interest along the patient’s long axis, images are oversampled and each image is tagged with breathing phase information (Fig. 11.25). The instantaneous breathing phase information can be obtained through the real-time position management (RPM) system,426 (GateCT, VisionRT, London, UK),427 spirometry,428 and pressure belts,429 among others. After the scan is done, images are sorted based on the corresponding breathing phase or amplitude signals. Many 3D CT sets are thus obtained, each corresponding to a particular breathing phase, and together they constitute a 4D CT set covering the whole breathing cycle. Four-dimensional CT decreases motion-induced artifacts and accurately assesses the extent of intrafraction motion. Downsides to 4D CT include the increased time for image acquisition and increased dose to the patient from multiple CT scans. An excellent review of 4D CT scanning was presented by Keall.430
Four-Dimensional Target Delineation and Planning
There are several approaches to internal target volume (ITV) delineation of moving lung tumors.431–437 Lagerwaard et al.432 used multiple “slow” CT scans to define the ITV, showing that this volume provided better target coverage than a free-breathing CT-derived ITV with isotropic margins. This method is old and limited, however, by the presence of motion-induced artifacts in 3D CT that hamper accurate target delineation. Breath-hold or forced shallow breathing during a 3D CT acquisition can theoretically minimize the motion-induced artifacts.433 However, such approaches may not be well tolerated in many patients, particularly those with poor pulmonary function. More sophisticated methods to improve target delineation are based on 4D CT imaging.
Various investigators have proposed numerous 4D CT-based techniques, which can largely be classified into four categories: (a) maximum intensity projection (MIP)-based ITV delineation,434–436 (b) using two extrema phases with a margin,434 (c) time-weighted mean tumor position with a margin,437 and (d) using all 10 phases to create composite volume.434,436 The MIP-based ITV technique is popular due to the simple and rapid construction of the ITV, based on a single 3D image. It has been shown to have good agreement with the “two extrema phases” and “all 10 phases” techniques.435 Wolthaus et al.437 have found, however, that the MIP-based ITV technique can overtreat normal tissues by up to 33% compared with a mean tumor position approach. In addition, Muirhead et al.436 have found that, although the MIP-based ITV technique is safe in most cases, compared with the all 10 phases technique as a gold standard, there are still special cases when the tumor is at or near the diaphragm, the MIP-based ITV technique would lead to underestimation of the actual ITV. This occurs because the tumor is similar in electron density with the diaphragm and other surrounding healthy tissues, such that when an MIP is generated, one cannot distinguish the borders between the overlapping tumor and its similar-density surroundings (Fig. 11.26). Therefore, the MIP-based ITV technique should not be entrusted in all situations, and the all 10 phases technique may be preferable in cases of doubt.
For liver cancers, the authors discourage the use of the MIP-base ITV technique, because the electron density of the liver tumor is generally lower than the surrounding normal liver tissue. Thus, the MIP image underestimates the ITV volume. The remedy for this is to use the minimum intensity projection (MinIP) instead. In terms of planning and dose calculations, the authors recommend using the average intensity projection images over a MIP, MinIP, or free-breathing CT images, due to the fact that it more closely represents the time-averaged anatomy of the patient than the other images. To be most accurate, 4D planning (Fig. 11.27) is desired (i.e., calculating dose on each 4D CT phase image and accumulating the dose using a deformable dose tracking technique).438,439 However, full implementation of the 4D planning approach is currently limited due to the computational resources needed to perform the increased number of dose calculations and deformable image registrations. If computational burden is not an issue, then a fully integrated 4D IMRT optimization based on the 4D CT phase images and 4D dose accumulations would be the best approach.440
The ways to treat a moving tumor can largely be classified into five categories441: (a) motion-encompassing, (b) respiratory gating, (c) breath-hold, (d) forced shallow breathing with abdominal compression, and (e) real-time tumor tracking. Motion-encompassing methods refer to treating the entire ITV, without intervention to minimize the treatment volume, in a patient’s natural breathing state. Once the ITV is delineated, the beam portal can be made large enough to adequately cover the volume during the planning stage. During treatment, it is necessary to monitor the patient to ensure that the patient breathes consistently without any drifts or sudden change in the amplitude. One should also be aware that presently most linear accelerator systems do not offer 4D imaging for patient setup (e.g., 4D CBCT).442,443 Therefore, adequate training to properly recognize the motion-induced blurring effects in 3D CBCT is critical to the image registration accuracy and the overall treatment effectiveness. Figure 11.28 illustrates blurring of the 3D CBCT images that can result due to breathing pattern (i.e., inspiration-to-expiration duration ratio).444
FIGURE 11.24. Computed tomography (CT) images of a spherical object in periodic motion in the axial direction. Top row: artifacts obtained in helical CT. Such artifacts depend on the relative phase between CT data acquisition and object motion. To evaluate different artifacts, CT scans were started at different phases. The right image shows the disconnected top and bottom of the sphere. Bottom row: On the left is a CT scan of the static object. The other images show three positions of the moving sphere as imaged by four-dimensional CT. Only small residual artifacts (on the surface) remain on the images at different positions of the motion cycle. (From Rietzel E, Pan T, Chen GT. Four-dimensional computed tomography image formation and clinical protocol. Med Phys 2005;32:874–889, with permission).

FIGURE 11.25. Data acquisition and processing in four-dimensional computed tomography (CT). The x-ray “on” duration during each step of data acquisition is greater than or equal to the average breathing cycle plus the duration of data acquisition for an image reconstruction. The dots on the respiratory signal trace represent the midscan time of the CT image reconstructions. Each dot represents four image reconstructions on a four-slice CT. There is an x-ray “off” period for table translation from one position to the next. (From Pan T, Lee TY, Rietzel E, et al. 4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT. Med Phys 2004;31:333–340, with permission.)

FIGURE 11.26. An example difference in the internal target volumes generated based on the maximum intensity projection (blue) and the 10-phase four-dimensional computed tomography (purple) images, when the tumor is adjacent to the diaphragmatic tissue of similar density. (From Muirhead R, McNee SG, Featherstone C, et al. Use of maximum intensity projections (MIPs) for target outlining in 4DCT radiotherapy planning. J Thoracic Oncol 2008;3:1433–1438, with permission.)

FIGURE 11.27. Dose–volume histograms for target volumes for two patients, showing three-dimensional and four-dimensional dose calculations. (From Starkschall G, Britton K, McAleer, et al. Potential dosimetric benefits of four-dimensional radiation treatment planning. Int J Radiat Oncol Biol Phys2009;73:1560–1565, with permission from Elsevier.)

FIGURE 11.28. Three-dimensional cone-beam computed tomography (3D CBCT) images of five simulated respiratory profiles. The ratio of time spent in inspiration to expiration is indicated on the bottom right corner of each 3D CBCT. (From Vergalasova I, Maurer J, Yin FF. Potential underestimation of the internal target volume (ITV) from free-breathing CBCT. Med Phys 2011;38:4689–4699, with permission.)

Respiratory Gating
There are two main approaches to respiratory gating—internal445,446 and external176,433,447—although a combination is also possible.448,449 Internal gating utilizes internal tumor motion surrogates such as implanted fiducial markers or marker-less imaging of internal anatomy, whereas external gating uses external respiratory surrogates such as markers placed on the surface of the patient’s abdomen, a compression belt, or spirometer signals.
The only internal gating system currently in clinical use is the RTRT system.281 Its major strength is its precise and real-time localization of the tumor position during treatment. Implanted markers are often good surrogates for tumor position, and marker migration is usually not an issue, particularly if multiple markers are used. Major weaknesses include its invasiveness and the high imaging dose required for fluoroscopic tracking.
The RPM system (Varian Medical Systems, Palo Alto, CA) can be viewed as representative of external gating systems. This system consists of a lightweight plastic block with two or six passive infrared reflective markers placed on the patient’s anterior abdominal surface and monitored by a charge-coupled–device video camera mounted on the treatment room wall. The surrogate signal is the abdominal surface motion. Both amplitude and phase gating are allowed. During treatment, a periodicity filter checks the regularity of the breathing waveform and disables the beam when the waveform becomes irregular, such as with patient motion or coughing, and re-enables the beam after establishing breathing is again regular. The RPM system is also used during simulation to acquire the patient’s geometry in the gating window and to set up the gating window.
Major strengths of external gating are that it is noninvasive, relatively easy to use, and well tolerated by patients. Moreover, it does not require any radiation dose for imaging. However, it should be noted that tracking the external marker is not equivalent to tracking the tumor, and blindly trusting the external surrogate can result in errors.448 In particular, the relation between the tumor motion and the surrogate signal may change over time, inter- and intrafractionally.
BrainLab (Westchester, IL) has a U.S. Food and Drug Administration–cleared respiratory gating device called ExacTrac Gating/Novalis Gating.449 This device uses external markers for gating the radiation beam, however, it uses x-ray imaging to determine the internal anatomy position and to verify its reproducibility during treatment. By updating the correlation between the internal and external signals in a reasonable frequency, x-ray exposure to the patient is minimized, while the external gating signal accuracy is maintained.
Breath-hold and deep inspiration breath-hold techniques450–453 are attractive options for patients who are capable of repeatedly holding for greater than 15 seconds due to reduced setup uncertainty (and hence, planning margins). The technique is useful for thoracic and upper abdominal targets as well as left-sided breast cancers, due to heart sparing. Setup reproducibility is challenging, due to the different levels of inspiration that are possible. Breathing coaching is helpful, and a monitoring device is essential. Any of the monitoring techniques involving internal and external signals (discussed earlier) can be used, including the spirometer,450 ABC device,450–452 RPM,449,450 and AlignRT surface tracking system.454
Forced shallow breathing in combination with abdominal compression devices is an effective technique for controlling the motion in upper abdominal tumors and inferior lung tumors.452,455–457 This was originally developed by Lax et al.455 and has since been replicated around the world. Eccles et al.456 has thoroughly analyzed the impact of the abdominal compression on the liver motion of 60 patients using cine MRI. They have found that more than 90% of patients showed reduction in motion along at least one direction and that more than 40% of patients showed greater than 3-mm motion reduction. However, this technique can be quite uncomfortable and even painful for some patients, and thus the level of compression should be balanced between patient comfort and a reasonable motion reduction (Fig. 11.29). Also, due to the difficulty in reproducibly positioning the abdominal compression device, couch indexed positioning and the subsequent imaging is essential at each treatment fraction. The technique is most appropriate for SBRT for early-stage lung and liver tumors without mediastinal involvement or nodal disease.
FIGURE 11.29. Examples of abdominal compression devices on the market: a plastic plate (left) and a pressure belt (right).

FIGURE 11.30. Flowchart of electromagnetically guided real-time dynamic multileaf collimator tracking. (From Keall PJ, Sawant A, Cho B, et al. Electromagnetic-guided dynamic multileaf collimator tracking enables motion management for intensity-modulated arc therapy. Int J Radiat Oncol Biol Phys2011;79:312–320, with permission from Elsevier.)

Tumor Tracking
Tumor tracking is perhaps the most ideal—and most technologically intense—strategy, as real-time tumor localization, fast processing and relay of information, and corresponding repositioning of the beam all need to be dynamically seamlessly integrated.458–473 Compared to the motion “freezing” methods, tumor tracking techniques are associated with higher delivery efficiency and less residual target motion. These factors may be particularly important to SBRT of thoracic and abdominal tumor sites, where a large dose is delivered during a single or a few relatively lengthy treatment sessions. However, there are a number of technical hurdles before this approach becomes clinically feasible, including treatment planning and the accurate response of the MLC to tumor positions measured in real time. The actual tumor movement as well as its relation to surrounding critical structures during the treatment cannot be known at the time of treatment planning. Therefore, planning can only be done based on some kind of average patient geometry information or at best on 4D CT simulation data, and an adaptive scheme must be used throughout the treatment course.
As mentioned earlier, tumor tracking is presently not in widespread clinical use. Most studies carried out so far are still at an investigational stage for linear accelerator–based approaches, except for a few specialized commercial systems.461,466 There are a number of ways one can obtain the real-time 3D position information of the tumor including: (a) marker-less imaging,445,446,472 (b) marker-guided imaging,281,462,463,467–469 and (c) using implantable magnetic transponders.465,470,473 Of these approaches, the use of implantable magnetic transponders is most promising due to lack of x-ray exposure, minimal system latency, and relative ease with which the system can be integrated in the clinical linear accelerator-based systems. The same argument in terms of x-ray exposure also applies to MRI-guided tumor tracking472; however, MRI implementation requires a whole new design to interface with linear accelerators. System latency is also a complex issue, due to the need to process the images and provide near real-time 3D tumor position information. Figure 11.30 illustrates a flowchart of a possible tumor tracking strategy with dynamic MLC (DMLC), based on the real-time 3D position information provided by the magnetic transponders (Calypso, Seattle, WA).
FIGURE 11.31. Tumor control probability (TCP) and rectum normal tissue complication probability (NTCP) curves for prostate cancer patients, from 50 to 100 Gy in 2-Gy per-fraction increments, for the three image-guided adaptive registration techniques: tattoo, bone, clinical target volume (CTV) registered, and CTV-registered with margin reduced to 5 mm. TCP curves are on the left and NTCP curves are on the right. Error bars are standard deviations. (From Song WY, Schaly B, Bauman G, et al. Image-guided adaptive radiation therapy (IGART): radiobiological and dose escalation considerations for localized carcinoma of the prostate. Med Phys 2005;32:2193–2220, with permission.)

ADAPTIVE RADIOTHERAPY
Radiation therapy has traditionally involved generating a static plan, based on a single snapshot of the patient’s anatomy, which is then delivered over a number of weeks. Modern IGRT technologies can transform this static process into a dynamic one, whereby plans are continuously altered throughout the treatment course or even during a single fraction. In many ways, altering the treatment plan during treatment is not new; for example, patients are often replanned due to weight loss or rapid tumor response. What is different is the speed and sophistication with which IGRT enables this process.
The term adaptive radiation therapy (ART) was first coined by Yan et al.474 in 1997. This was around the time that David Jaffray at the same institution (William Beaumont Hospital, Royal Oak, MI) was working on the integration of CBCT with a linear accelerator to enable in-room soft-tissue imaging before, during, or after treatment.475 Thus, the concept of ART was proposed based on the idea that advancements in in-room imaging technologies would make the process of target localization and definition more precise.
The optimal level of adaptation is a broad question, and it is unlikely that a global solution exists for all situations. An intriguing approach is to use the knowledge of patient setup and organ motion information to decide the prescribed “safe dose” (i.e., isotoxicity) to be delivered for each patient, rather than prescribing the same dose for all patients because normal tissue tolerance is usually what limits the prescription dose. Song et al.476 evaluated the maximum dose that can be delivered while keeping the same rectal NTCP level (i.e., iso-NTCP dose escalation) using various IGRT approaches (Fig. 11.31). It was found that the possible dose escalation levels were highly patient dependent, even if the same target localization approaches were used, and that image registration based on soft tissues provided the least discrepancy among patients.
This level of adaptation was proven to be clinically feasible.477,478 Their approach was as follows. Based on the planning CT simulation, an initial treatment plan is generated with a 1-cm CTV–PTV margin. Each of the first 4 days of therapy, daily EPID and CT scans are acquired immediately before or after treatment. Confidence-limited PTV margins are generated based on each patient’s setup inaccuracies and internal organ motion. Rectal and bladder constraints are used to determine the individual patient’s total dose, ranging from 70.2 to 79.2 Gy. Using this isotoxicity ART strategy, they found no statistically different rectal toxicity rates across the prescription dose ranges. This was the first clinical evidence that an individualized prescription is possible indicating benefits of image-guided ART.
Deutschmann et al.479 further used online aperture adaptation to reduce planning margins in 39 prostate cancer patients, after correcting for interfraction shifts based on implanted fiducials. They found that this approach was feasible, and correcting for intrafraction 6-degree rotations could allow reduced planning margins to 3 mm. Intrafraction motion based on pretreatment kilovoltage planar imaging versus last beam EPID images showed RL rotations up to 26.9 degrees (mean, 2.5 degrees) and 3D translations up to 10.2 mm (mean, 3.0 mm).
The need to adapt to changes in the patient anatomy (tumor(s) or normal tissues) is not limited to prostate cancer. Multiple investigators have reported significant morphologic changes in tumors or normal tissues in a wide variety of tumor sites, including HNC,480,481 lung cancer,482,483 and gynecologic tumors.484 Barker et al.480 noted a mean volume reduction of the GTV of 0.2 cm3/day in HNC patients treated on a CT-on-rails system. Of note, the parotid gland volume decreased by 0.19 cm3/day and the glands shifted medially, on average, by 3.1 mm. In seven lung cancer patients undergoing daily MVCT imaging, Ramsey et al.485 reported a mean GTV reduction of 31%. Kupelian et al.482 treated 10 NSCLC patients with the Tomotherapy system and observed an average decrease in GTV of 1.2% per day; five of six replanned cases demonstrated small increases in tumor dose delivery. Van de Bunt et al.484reported an average reduction in the GTV of 46% in 14 cervical cancers reimaged with MRI after the delivery of 30 Gy (Fig. 11.32).
Several investigators have reported that adapting to morphologic changes may improve treatment delivery. Ramsey et al.485 found that the lung V20 would be decreased from 23% to 17% by adapting to reductions in the GTV in lung cancer patients, corresponding to 17% less reduction in lung perfusion. Hansen et al.481 evaluated the impact of replanning in a cohort of 13 HNC patients with either significant weight loss or tumor response during IMRT (Fig. 11.33). Compared to replanning, not replanning significantly decreased dose to the target volume and increased doses to normal tissues (spinal cord and brainstem). The doses to 95% of the PTVGTV and the PTVCTV decreased by up to 6.3 Gy and 7.4 Gy, respectively.
FIGURE 11.32. Magnetic resonance images of a patient with a bulky cervical cancer obtained prior to the initiation of treatment (A: sagittal; C: axial) and following 30 Gy (B: sagittal; D: axial) illustrating significant regression of the primary tumor. (From Van de Bunt L, van der Heided UA, Ketelaars M, et al. Conventional, conformal and intensity modulated radiation therapy treatment planning of external beam radiotherapy for cervical cancer: the impact of tumor regression. Int J Radiat Oncol Biol Phys 2006;64:189–196, with permission from Elsevier.)

Adaptation could potentially be extended beyond morphologic changes. An intriguing idea is to adapt the plan to functional changes of the tumor. Current IGRT technologies do not generally allow in-room functional imaging, however, increasing data suggest that functional changes in tumors are correlated with outcome.17,486 For example, Wieder et al.486 examined changes in tumor 18FDG avidity in patients undergoing preoperative chemoradiotherapy for esophageal carcinoma (Fig. 11.34). In 27 patients undergoing midtreatment 18FDG PET, a decline in SUV greater than 30% was associated with improved 2-year overall survival and histopathologic response. Whether adapting the plan (e.g., intensifying treatment in patients with suboptimal metabolic changes) would improve patient outcomes remains unclear.
From a technical standpoint, a major concern is how exactly to adapt to changes in the tumor or normal tissues during treatment. Although it may be trivial to occasionally replan a limited number of patients offline, frequent replannings of many patients are labor and time intensive, especially if online replanning is necessary. New software tools, approaches, and fast and reliable computing are needed. This is currently an active area of research. Researchers at the University of California–San Diego have explored the potential to perform online replanning utilizing the vast computational capability of the graphics card technology (Fig. 11.35).487–495 Graphics processing unit (GPU) cards were originally developed for the gaming industry, where a fast display of large graphics data is necessary to enhance the quality of the gaming experience. By developing new algorithms with mathematical structures suitable for GPU parallelization, it is possible to dramatically improve the computational efficiency of the traditionally computationally intense tasks in RT such as dose calculations,487,491,493,495 inverse planning reoptimizations,489,493 CT reconstructions,490,494 and deformable image registrations for fast contour mapping.489 Of note, Gu et al.487,493 have shown that a full 3D-dose calculation based on finite-size pencil beam algorithm achieved a speed up of 200 to 400 times, taking less than 1 second for typical IMRT plans. Men et al.488,492 found that, for a typical nine-field prostate IMRT plan with 5-by-5 mm2 beamlet size and 2.5-by-2.5-by-2.5 mm3 voxel size, reoptimization would only take 2.8 seconds. Park et al.494 found that for a filtered back-projection reconstruction of a typical 3D CBCT, volume can be done in a real-time fashion (i.e., as soon as the scan is done), while Gu et al.489found that a daemons deformable image registration of a typical 3D CBCT volume can be completed in 7 to 11 seconds.
FIGURE 11.33. The benefit of replanning midway through treatment is illustrated in a patient with a T2N2C base of tongue carcinoma. A: The initial intensity modulated radiation therapy plan generated from the initial planning computed tomography (CT) scan. B: A second CT scan during treatment showing the isodose lines obtained without replanning. C: The same slice from the second CT scan, with isodose lines obtained by replanning. The second CT was obtained after 22 fractions and after a 12% weight loss from the start of treatment. The arrowdemonstrates the increased spinal cord dose without replanning. (From Hansen EK, Bucci MK, Quivey JM, et al. Repeat CT imaging and re-planning during the course of IMRT for head-and-neck cancer. Int J Radiat Oncol Biol Phys 2006;64:355–362, with permission from Elsevier.)

Another computational acceleration approach is the utilization of Cloud computing for RT applications, pioneered by Meng et al.496 and Wang et al.497 at Stanford University. Cloud computing is a recent advancement in supercomputing technology where the end user only needs Internet access and he or she requests computations to a large network of computers (nodes) that are not visible to the end user. The task is divided up and handled in a parallel computing manner, automatically. The larger the number of nodes used, the faster the computations. Because this system does not require the computers to be physically located near the user, and they can be accessed from anywhere with an Internet connection, the potential for their use in ART applications irrespective of the location of the clinic is tremendous. The technology is new and research in RT is in its infancy; but the potential benefits remain to be seen.
Even if computational issues are completely resolved and online replanning can be technically implemented, many questions still remain to be answered before various ART strategies can be introduced into clinical practice. For example, how often should new plans be generated? Once? Weekly? Daily? Another question is whether altering the target volume would adversely impact tumor control. In the study by Hansen et al.481, attempts were made to “maintain the size of the original GTV in the second plan without extending it beyond the skin contour or into adjacent normal structures,” ensuring irradiation of potential microscopic disease spread. Such concerns are quite reasonable in infiltrative tumors such as HNC, but may be less warranted in noninfiltrative tumors (e.g., bulky lymphadenopathy). Altering the target volume as the tumor responds in this situation should carry less risk. Moreover, it should reduce the risk of toxicity and allow the delivery of higher, more effective doses. The answer to these and other questions should be resolved through prospective clinical trials.
FIGURE 11.34. Coronal slices from fluorodeoxyglucose (FDG) positron emission tomographyscans in patients with histopathologically responding (A) and nonresponding (B) esophageal cancer. In the responding tumor, FDG uptake decreased to background levels 14 days after beginning chemoradiotherapy. At the same time point in the nonresponding tumor, FDG uptake is essentially unchanged. (From Wieder HA, Brucher BL, Zimmermann F, et al. Time course of tumor metabolic activity during chemoradiotherapy of esophageal squamous cell carcinoma and response to treatment. J Clin Oncol 2004;22:900–908. Reprinted with permission. © 2004 American Society of Clinical Oncology. All rights reserved.)

FIGURE 11.35. Super-Computing Online Replanning Environment (SCORE) for adaptive radiation therapy. A: SCORE workflow. B: Reoptimized dose distribution (left) and calculated dose-volume histograms (right) for a head and neck cancer patient undergoing SCORE simulation. The SCORE plan is generated then exported back to the treatment planning system for verification before treatment. (Courtesy of Xun Jia and Steve Jiang.)

CONCLUSIONS
Technological progress has been defined in economic terms as an increase in the efficiency of production. This is achieved by producing more output for a given set of inputs, or alternately, requiring fewer inputs to produce a given output. In medicine, technological progress might be defined similarly—as an increase in the efficiency of medical services—where improved patient outcomes (“outputs”) are achieved for less cost (“inputs”), and medical costs may include both economic resources and adverse events. When therapeutic outcomes are achieved for less toxicity, technological progress is tantamount to an increase in the therapeutic ratio. An ongoing challenge for the field of radiation oncology is to develop, test, and implement new technologies that meet this definition of progress.
REFERENCES
1. Advanced Technology Consortium. Image guided radiation therapy guidelines: ATC QA subcommittee report. ATC Credentialing and QA Committee Reports. Created October 18, 2009. Available at: http://atc.wustl.edu/credentialing/ATC_reports/IGRT_guidelines_18Oct09.pdf.
2. Balter J. Image guided radiation therapy (IGRT)—a perspective. American Association of Physicists in Medicine. Available at: http://www.aapm.org/meetings/06ss/documents/2006summerschoolIGRTintro_000.pdf.
3. ACR–ASTRO Practice Guideline For Image-Guided Radiation Therapy (IGRT). American College of Radiology. http://www.acr.org/SecondaryMainMenuCategories/quality_safety/guidelines/ro/IGRT.aspx.
4. Greco C, Ling CC. Broadening the scope of image-guided radiotherapy (IGRT). Acta Oncol 2008;47:1193–1200.
5. Young AV, Wortham A, Wernick I, et al. Atlas-based segmentation improves consistency and decreases time required for contouring postoperative endometrial cancer nodal volumes. Int J Radiat Oncol Biol Phys 2011;79:943–947.
6. Stapleford LJ, Lawson JD, Perkins C, et al. Evaluation of automatic atlas-based lymph node segmentation for head-and-neck cancer. Int J Radiat Oncol Biol Phys 2010;77:959–966.
7. Simpson DR, Lawson JD, Nath SK, Rose BS, Mundt AJ, Mell LK. Utilization of advanced imaging technologies for target delineation in radiation oncology. J Am Coll Radiol 2009;6:876-883.
8. Werner-Wasik M, Nelson AD, Choi W, et al. What is the best way to contour lung tumors on PET scans? Multiobserver validation of a gradient-based method using a NSCLC digital PET phantom. Int J Radiat Oncol Biol Phys2012;82(3):1164–1171.
9. Plathow C, Weber WA. Tumor cell metabolism imaging. J Nucl Med 2008;49(Suppl 2):43S-63S.
10. MacManus MP, Hicks RJ, Matthews JP, et al. High rate of detection of unsuspected distant metastases by PET in apparent stage III non-small-cell lung cancer: implications for radical radiation therapy. Int J Radiat Oncol Biol Phys 2001;50:287–293.
11. Pieterman RM, van Putten JW, Meuzelaar JJ, et al. Preoperative staging of non-small-cell lung cancer with positron-emission tomography. N Engl J Med 2000;343:254–261.
12. Haerle SK, Schmid DT, Ahmad N, et al. The value of (18)F-FDG PET/CT for the detection of distant metastases in high-risk patients with head and neck squamous cell carcinoma. Oral Oncol2011;47:653–659.
13. Baba S, Abe K, Isoda T, et al. Impact of FDG-PET/CT in the management of lymphoma. Ann Nucl Med 2011;25:701–716.
14. Muijs CT, Beukema JC, Pruim J, et al. A systematic review on the role of FDG-PET/CT in tumour delineation and radiotherapy planning in patients with esophageal cancer. Radiother Oncol2010;97:165–171.
15. Schoder H, Noy A, Gonen M, et al. Intensity of 18-fluorodeoxyglucose uptake in positron emission tomography distinguishes between indolent and aggressive non-Hodgkin’s lymphoma. J Clin Oncol2005;23:4643–4651.
16. Suzuki A, Xiao L, Hayashi Y, et al. Prognostic significance of baseline positron emission tomography and importance of clinical complete response in patients with esophageal or gastroesophageal junction cancer treated with definitive chemoradiotherapy. Cancer 2011;117:4823–4833.
17. Schwarz JK, Siegel BA, Dehdashti F, et al. Metabolic response on posttherapy FDG-PET predicts patterns of failure after radiotherapy for cervical cancer. Int J Radiat Oncol Biol Phys 2012;83(1):185–190.
18. Ashamalla H, Rafla S, Parikh K, et al. The contribution of integrated PET/CT to the evolving definition of treatment volumes in radiation treatment planning in lung cancer. Int J Radiat Oncol Biol Phys2005;63:1016–1023.
19. Bradley J, Thorstad WL, Mutic S, et al. Impact of FDG-PET on radiation therapy volume delineation in non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 2004;59:78–86.
20. Deniaud-Alexandre E, Touboul E, Lerouge D, et al. Impact of computed tomography and 18F-deoxyglucose coincidence detection emission tomography image fusion for optimization of conformal radiotherapy in non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 2005;63:1432–1441.
21. Vanuytsel LJ, Vansteenkiste JF, Stroobants SG, et al. The impact of (18)F-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) lymph node staging on the radiation treatment volumes in patients with non-small cell lung cancer. Radiother Oncol 2000;55:317–324.
22. Bradley J, Bae K, Choi N, et al. A phase II comparative study of gross tumor volume definition with or without PET/CT fusion in dosimetric planning for non-small-cell lung cancer (NSCLC): primary analysis of Radiation Therapy Oncology Group (RTOG) 0515. Int J Radiat Oncol Biol Phys 2012;82:435–441.e1.
23. Grosu AL, Piert M, Weber WA, et al. Positron emission tomography for radiation treatment planning. Strahlenther Onkol 2005;181:483–499.
24. Yu J, Li X, Xing L, et al. Comparison of tumor volumes as determined by pathologic examination and FDG-PET/CT images of non-small-cell lung cancer: a pilot study. Int J Radiat Oncol Biol Phys2009;75:1468–1474.
25. Pehlivan B, Topkan E, Onal C, et al. Comparison of CT and integrated PET-CT based radiation therapy planning in patients with malignant pleural mesothelioma. Radiat Oncol 2009;4:35.
26. Spratt DE, Diaz R, McElmurray J, et al. Impact of FDG PET/CT on delineation of the gross tumor volume for radiation planning in non-small-cell lung cancer. Clin Nucl Med 2010;35:237–243.
27. Wanet M, Lee JA, Weynand B, et al. Gradient-based delineation of the primary GTV on FDG-PET in non-small cell lung cancer: a comparison with threshold-based approaches, CT and surgical specimens. Radiother Oncol2011;98:117–125.
28. Arens AI, Troost EG, Schinagl D, et al. FDG-PET/CT in radiation treatment planning of head and neck squamous cell carcinoma. Q J Nucl Med Mol Imaging 2011;55:521–528.
29. MacManus M, Nestle U, Rosenzweig KE, et al. Use of PET and PET/CT for radiation therapy planning: IAEA expert report 2006–2007. Radiother Oncol 2009;91:85–94.
30. Paulino AC, Koshy M, Howell R, et al. Comparison of CT- and FDG-PET-defined gross tumor volume in intensity-modulated radiotherapy for head-and-neck cancer. Int J Radiat Oncol Biol Phys2005;61:1385–1392.
31. Schwartz DL, Ford E, Rajendran J, et al. FDG-PET/CT imaging for preradiotherapy staging of head-and-neck squamous cell carcinoma. Int J Radiat Oncol Biol Phys 2005;61:129–136.
32. Schwartz DL, Ford EC, Rajendran J, et al. FDG-PET/CT-guided intensity modulated head and neck radiotherapy: a pilot investigation. Head Neck 2005;27:478–487.
33. Thiagarajan A, Caria N, Schöder H, et al. Target volume delineation in oropharyngeal cancer: impact of PET, MRI, and physical examination. Int J Radiat Oncol Biol Phys 2012;83(1):220–227.
34. Delouya G, Igidbashian L, Houle A, et al. 18F-FDG-PET imaging in radiotherapy tumor volume delineation in treatment of head and neck cancer. Radiother Oncol 2011;101:362–368.
35. Guido A, Fuccio L, Rombi B, et al. Combined 18F-FDG-PET/CT imaging in radiotherapy target delineation for head-and-neck cancer. Int J Radiat Oncol Biol Phys 2009;73:759–763.
36. Gregoire V, Daisne JF, Geets X. Comparison of CT- and FDG-PET-defined GT: in regard to Paulino et al. Int J Radiat Oncol Biol Phys 2005;63:308–309.
37. Breen SL, Publicover J, De Silva S, et al. Intraobserver and interobserver variability in GTV delineation on FDG-PET-CT images of head and neck cancers. Int J Radiat Oncol Biol Phys 2007;68:763–770.
38. Yu H, Caldwell C, Mah K, et al. Automated radiation targeting in head-and-neck cancer using region-based texture analysis of PET and CT images. Int J Radiat Oncol Biol Phys 2009;75:618–625.
39. Simon E, Fox TH, Lee D, et al. PET lesion segmentation using automated iso-intensity contouring in head and neck cancer. Technol Cancer Res Treat 2009;8:249–255.
40. Schinagl DA, Vogel WV, Hoffmann AL, et al. Comparison of five segmentation tools for 18F-fluoro-deoxy-glucose-positron emission tomography-based target volume definition in head and neck cancer. Int J Radiat Oncol Biol Phys 2007;69:1282–1289.
41. Ollers M, Bosmans G, van Baardwijk A, et al. The integration of PET-CT scans from different hospitals into radiotherapy treatment planning. Radiother Oncol 2008;87:142–146.
42. Leong T, Everitt C, Yuen K, et al. A prospective study to evaluate the impact of FDG-PET on CT-based radiotherapy treatment planning for oesophageal cancer. Radiother Oncol 2006;78:254–261.
43. Vrieze O, Haustermans K, De Wever W, et al. Is there a role for FDG-PET in radiotherapy planning in esophageal carcinoma? Radiother Oncol 2004;73:269–275.
44. Hong TS, Killoran JH, Mamede M, et al. Impact of manual and automated interpretation of fused PET/CT data on esophageal target definitions in radiation planning. Int J Radiat Oncol Biol Phys2008;72:1612–1628.
45. Vesprini D, Ung Y, Dinniwell R, et al. Improving observer variability in target delineation for gastro-oesophageal cancer—the role of (18F)fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography. Clin Oncol (R Coll Radiol) 2008;20:631–638.
46. Han D, Yu J, Yu Y, et al. Comparison of (18)F-fluorothymidine and (18)F-fluorodeoxyglucose PET/CT in delineating gross tumor volume by optimal threshold in patients with squamous cell carcinoma of thoracic esophagus. Int J Radiat Oncol Biol Phys 2010;76:1235–1241.
47. Vali FS, Nagda S, Hall W, et al. Comparison of standardized uptake value-based positron emission tomography and computed tomography target volumes in esophageal cancer patients undergoing radiotherapy. Int J Radiat Oncol Biol Phys 2010;78:1057–1063.
48. Braendengen M, Hansson K, Radu C, et al. Delineation of gross tumor volume (GTV) for radiation treatment planning of locally advanced rectal cancer using information from MRI or FDG-PET/CT: a prospective study. Int J Radiat Oncol Biol Phys 2011;81:e439–e445.
49. Buijsen J, van den Bogaard J, Janssen MH, et al. FDG-PET provides the best correlation with the tumor specimen compared to MRI and CT in rectal cancer. Radiother Oncol 2011;98:270–276.
50. Janssen MH, Aerts HJ, Ollers MC, et al. Tumor delineation based on time-activity curve differences assessed with dynamic fluorodeoxyglucose positron emission tomography-computed tomography in rectal cancer patients. Int J Radiat Oncol Biol Phys 2009;73:456–465.
51. Krengli M, Cannillo B, Turri L, et al. Target volume delineation for preoperative radiotherapy of rectal cancer: inter-observer variability and potential impact of FDG-PET/CT imaging. Technol Cancer Res Treat 2010;9:393–398.
52. Patel DA, Chang ST, Goodman KA, et al. Impact of integrated PET/CT on variability of target volume delineation in rectal cancer. Technol Cancer Res Treat 2007;6:31–36.
53. Esthappan J, Chaudhari S, Santanam L, et al. Prospective clinical trial of positron emission tomography/computed tomography image-guided intensity-modulated radiation therapy for cervical carcinoma with positive para-aortic lymph nodes. Int J Radiat Oncol Biol Phys 2008;72:1134–1139.
54. Lin LL, Mutic S, Malyapa RS, et al. Sequential FDG-PET brachytherapy treatment planning in carcinoma of the cervix. Int J Radiat Oncol Biol Phys 2005;63:1494–1501.
55. Schwarz JK, Lin LL, Siegel BA, et al. 18-F-fluorodeoxyglucose-positron emission tomography evaluation of early metabolic response during radiation therapy for cervical cancer. Int J Radiat Oncol Biol Phys 2008;72:1502–1507.
56. Lin LL, Mutic S, Low DA, et al. Adaptive brachytherapy treatment planning for cervical cancer using FDG-PET. Int J Radiat Oncol Biol Phys 2007;67:91–96.
57. Liang Y, Bydder M, Hoh CK, et al. Functional MRI-guided bone marrow-sparing intensity modulated radiotherapy for pelvic malignancies. Int J Radiat Oncol Biol Phys 2009;75:S121 (abstr).
58. Rose BS, Liang Y, Lau SK, et al. Correlation between radiation dose to (18)F-FDG-PET defined active bone marrow subregions and acute hematologic toxicity in cervical cancer patients treated with chemoradiotherapy. Int J Radiat Oncol Biol Phys 2012;83(4):1185–1191.
59. Ford EC, Lavely WC, Frassica DA, et al. Comparison of FDG-PET/CT and CT for delineation of lumpectomy cavity for partial breast irradiation. Int J Radiat Oncol Biol Phys 2008;71:595–602.
60. Girinsky T, Ghalibafian M, Bonniaud G, et al. Is FDG-PET scan in patients with early stage Hodgkin lymphoma of any value in the implementation of the involved-node radiotherapy concept and dose painting? Radiother Oncol 2007;85:178–186.
61. Hutchings M, Loft A, Hansen M, et al. Clinical impact of FDG-PET/CT in the planning of radiotherapy for early-stage Hodgkin lymphoma. Eur J Haematol 2007;78:206–212.
62. Topkan E, Yavuz AA, Aydin M, et al. Comparison of CT and PET-CT based planning of radiation therapy in locally advanced pancreatic carcinoma. J Exp Clin Cancer Res 2008;27:41.
63. Karam I, Devic S, Hickeson M, et al. PET/CT for radiotherapy treatment planning in patients with soft tissue sarcomas. Int J Radiat Oncol Biol Phys 2009;75:817–821.
64. Douglas JG, Stelzer KJ, Mankoff DA, et al. [F-18]-fluorodeoxyglucose positron emission tomography for targeting radiation dose escalation for patients with glioblastoma multiforme: clinical outcomes and patterns of failure. Int J Radiat Oncol Biol Phys 2006;64:886–891.
65. Schöder H, Ong SC. Fundamentals of molecular imaging: rationale and applications with relevance for radiation oncology. Semin Nucl Med 2008;38:119–128.
66. Blankenberg FG. The state of the art of molecular imaging: in vivo detection of apoptosis. J Nucl Med 2008;49(Suppl):81–95.
67. Krohn KA, Link JM, Mason RP. Molecular imaging of hypoxia. J Nucl Med 2008; 49(Suppl):129–148.
68. Bading JR, Shields AF. Imaging of cell proliferation: status and prospects. J Nucl Med 2008;49(Suppl):64–80.
69. Wahl RL, Herman JM, Ford E. The promise and pitfalls of positron emission tomography and single-photon emission computed tomography molecular imaging-guided radiation therapy. Semin Radiat Oncol 2011;21:88–100.
70. Grosu AL, Weber WA, Riedel E, et al. L-(methyl-11C) methionine positron emission tomography for target delineation in resected high-grade gliomas before radiotherapy. Int J Radiat Oncol Biol Phys2005;63:64–74.
71. Astner ST, Dobrei-Ciuchendea M, Essler M, et al. Effect of 11C-methionine-positron emission tomography on gross tumor volume delineation in stereotactic radiotherapy of skull base meningiomas. Int J Radiat Oncol Biol Phys 2008;72:1161–1167.
72. Niyazi M, Geisler J, Siefert A, et al. FET-PET for malignant glioma treatment planning. Radiother Oncol 2011;99:44–48.
73. Grosu AL, Astner ST, Riedel E, et al. An interindividual comparison of O-(2-[18F]fluoroethyl)-L-tyrosine (FET)- and L-[methyl-11C]methionine (MET)-PET in patients with brain gliomas and metastases. Int J Radiat Oncol Biol Phys 2011;81:1049–1058.
74. Milker-Zabel S, Zabel-du Bois A, Henze M, et al. Improved target volume definition for fractionated stereotactic radiotherapy in patients with intracranial meningiomas by correlation of CT, MRI, and [68Ga]-DOTATOC-PET. Int J Radiat Oncol Biol Phys 2006;65:222–227.
75. Gehler B, Paulsen F, Oksüz MO, et al. [68Ga]-DOTATOC-PET/CT for meningioma IMRT treatment planning. Radiat Oncol 2009;4:56.
76. Rasey JS, Koh WJ, Evans ML, et al. Quantifying regional hypoxia in human tumors with positron emission tomography of [18F]fluoromisonidazole: a pretherapy study of 37 patients. Int J Radiat Oncol Biol Phys 1996;36:417–428.
77. Rischin D, Hicks RJ, Fisher R, et al. Prognostic significance of [18F]-misonidazole positron emission tomography-detected tumor hypoxia in patients with advanced head and neck cancer randomly assigned to chemoradiation with or without tirapazamine: a substudy of Trans-Tasman Radiation Oncology Group Study 98.02. J Clin Oncol 2006;24:2098–2104.
78. Grosu AL, Souvatzoglou M, Röper B, et al. Hypoxia imaging with FAZA-PET and theoretical considerations with regard to dose painting for individualization of radiotherapy in patients with head and neck cancer. Int J Radiat Oncol Biol Phys 2007;69:541–551.
79. Chao KS, Bosch WR, Mutic S, et al. A novel approach to overcome hypoxic tumor resistance: Cu-ATSM-guided intensity-modulated radiation therapy. Int J Radiat Oncol Biol Phys 2001;49:1171–1182.
80. Dehdashti F, Grigsby PW, Mintun MA, et al. Assessing tumor hypoxia in cervical cancer by positron emission tomography with 60Cu-ATSM: relationship to therapeutic response-a preliminary report. Int J Radiat Oncol Biol Phys 2003;55:1233–1238.
81. Chang JH, Joon DL, Lee ST, et al. Histopathological correlation of (11)C-choline PET scans for target volume definition in radical prostate radiotherapy. Radiother Oncol 2011;99:187–192.
82. Wang H, Vees H, Miralbell R, et al. 18F-fluorocholine PET-guided target volume delineation techniques for partial prostate re-irradiation in local recurrent prostate cancer. Radiother Oncol 2009;93:220–225.
83. Everitt S, Hicks RJ, Ball D, et al. Imaging cellular proliferation during chemo-radiotherapy: a pilot study of serial 18F-FLT positron emission tomography/computed tomography imaging for non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 2009;75:1098–1104.
84. Muijs CT, Beukema JC, Widder J, et al. 18F-FLT-PET for detection of rectal cancer. Radiother Oncol 2011;98:357–359.
85. Troost EG, Vogel WV, Merkx MA, et al. 18F-FLT PET does not discriminate between reactive and metastatic lymph nodes in primary head and neck cancer patients. J Nucl Med 2007;48:726–735.
86. Aoyama H, Shirato H, Nishioka T, et al. Magnetic resonance imaging system for three-dimensional conformal radiotherapy and its impact on gross tumor volume delineation of central nervous system tumors. Int J Radiat Oncol Biol Phys 2001;50:821–827.
87. Stall B, Zach L, Ning H, et al. Comparison of T2 and FLAIR imaging for target delineation in high grade gliomas. Radiat Oncol 2010;5:5.
88. Emami B, Sethi A, Petruzzelli GJ. Influence of MRI on target volume delineation and IMRT planning in nasopharyngeal carcinoma. Int J Radiat Oncol Biol Phys 2003;57:481–488.
89. Gardner M, Halimi P, Valinta D, et al. Use of single MRI and 18F-FDG PET-CT scans in both diagnosis and radiotherapy treatment planning in patients with head and neck cancer: advantage on target volume and critical organ delineation. Head Neck 2009;31:461–467.
90. Buyyounouski MK, Horwitz EM, Price RA, et al. Intensity-modulated radiotherapy with MRI simulation to reduce doses received by erectile tissue during prostate cancer treatment. Int J Radiat Oncol Biol Phys 2004;58:743–749.
91. Parker CC, Damyanovich A, Haycocks T, et al. Magnetic resonance imaging in the radiation treatment planning of localized prostate cancer using intra-prostatic fiducial markers for computed tomography co-registration. Radiother Oncol 2003;66:217–224.
92. Usmani N, Sloboda R, Kamal W, et al. Can images obtained with high field strength magnetic resonance imaging reduce contouring variability of the prostate? Int J Radiat Oncol Biol Phys 2011;80:728–734.
93. Yeung AR, Vargas CE, Falchook A, et al. Dose-volume differences for computed tomography and magnetic resonance imaging segmentation and planning for proton prostate cancer therapy. Int J Radiat Oncol Biol Phys2008;72:1426–1433.
94. Viswanathan AN, Dimopoulos J, Kirisits C, et al. Computed tomography versus magnetic resonance imaging-based contouring in cervical cancer brachytherapy: results of a prospective trial and preliminary guidelines for standardized contours. Int J Radiat Oncol Biol Phys 2007;68:491–498.
95. Karlsson M, Karlsson MG, Nyholm T, et al. Dedicated magnetic resonance imaging in the radiotherapy clinic. Int J Radiat Oncol Biol Phys 2009;74:644–651.
96. Hamilton RJ, Sweeney PJ, Pelizzari CA, et al. Functional imaging in treatment planning of brain lesions. Int J Radiat Oncol Biol Phys 1997;37:181–188.
97. Liu WC, Schulder M, Narra V, et al. Functional magnetic resonance imaging aided radiation treatment planning. Med Phys 2000;27:1563–1572.
98. Schad LR, Bock M, Baudendistel K, et al. Improved target volume definition in radiosurgery of arteriovenous malformations by stereotactic correlation of MRA, MRI, blood bolus tagging, and functional MRI. Eur Radiol1996;6:38–45.
99. Aoyama H, Kamada K, Shirato H, et al. Integration of functional brain information into stereotactic irradiation treatment planning using magnetoencephalography and magnetic resonance axonography. Int J Radiat Oncol Biol Phys 2004;58:1177–1183.
100. Chang J, Narayana A. Functional MRI for radiotherapy of gliomas. Technol Cancer Res Treat 2010;9:347–358.
101. Wang TJ, Brisman R, Lu ZF, et al. Image registration strategy of T(1)-weighted and FIESTA MRI sequences in trigeminal neuralgia gamma knife radiosurgery. Stereotact Funct Neurosurg 2010;88:239–245.
102. Chávez GD, De Salles AA, Solberg TD, et al. Three-dimensional fast imaging employing steady-state acquisition magnetic resonance imaging for stereotactic radiosurgery of trigeminal neuralgia. Neurosurgery 2005;56:E628.
103. Pirzkall A, Li X, Oh J, et al. 3D MRSI for resected high-grade gliomas before RT: tumor extent according to metabolic activity in relation to MRI. Int J Radiat Oncol Biol Phys 2004;59:126–137.
104. Chan AA, Lau A, Pirzkall A, et al. Proton magnetic resonance spectroscopy imaging in the evaluation of patients undergoing gamma knife surgery for Grade IV glioma. J Neurosurg 2004;101:467–475.
105. van Lin EN, Futterer JJ, Heijmink SW, et al. IMRT boost dose planning on dominant intraprostatic lesions: gold marker-based three-dimensional fusion of CT with dynamic contrast-enhanced and 1H-spectroscopic MRI. Int J Radiat Oncol Biol Phys 2006;65:291–303.
106. Meijer HJ, van Lin EN, Debats OA, et al. High occurrence of aberrant lymph node spread on magnetic resonance lymphography in prostate cancer patients with a biochemical recurrence after radical prostatectomy. Int J Radiat Oncol Biol Phys 2012;82(4):1405–1410.
107. Meijer HJ, Debats OA, Kunze-Busch M, et al. Magnetic resonance lymphography-guided selective high-dose lymph node irradiation in prostate cancer. Int J Radiat Oncol Biol Phys 2012;82:175–183.
108. Craciunescu OI, Yoo DS, Cleland E, et al. Dynamic contrast-enhanced MRI in head-and-neck cancer: the impact of region of interest selection on the intra- and interpatient variability of pharmacokinetic parameters. Int J Radiat Oncol Biol Phys 2012;82:e345–e350.
109. Lazanyi KS, Abramyuk A, Wolf G, et al. Usefulness of dynamic contrast enhanced computed tomography in patients with non-small-cell lung cancer scheduled for radiation therapy. Lung Cancer2010;70:280–285.
110. Kierkels RG, Backes WH, Janssen MH, et al. Comparison between perfusion computed tomography and dynamic contrast-enhanced magnetic resonance imaging in rectal cancer. Int J Radiat Oncol Biol Phys 2010;77:400–408.
111. Mayr NA, Huang Z, Wang JZ, et al. Characterizing tumor heterogeneity with functional imaging and quantifying high-risk tumor volume for early prediction of treatment outcome: cervical cancer as a model. Int J Radiat Oncol Biol Phys 2012;83(3):972–979.
112. Liang Y, Bydder M, Hoh CK, et al. Correlation between increased bone marrow glucose metabolism and acute changes in fat fraction during pelvic radiation therapy. Int J Radiat Oncol Biol Phys2010;78:S118–S119 (abstr).
113. Ganswindt U, Paulsen F, Corvin S, et al. Intensity modulated radiotherapy for high risk prostate cancer based on sentinel node SPECT imaging for target volume definition. BMC Cancer 2005;5:91.
114. Jani AB, Blend MJ, Hamilton R, et al. Influence of radioimmunoscintigraphy on postprostatectomy radiotherapy treatment decision making. J Nucl Med 2004; 45:571–578.
115. Jani AB, Blend MJ, Hamilton R, et al. Radioimmunoscintigraphy for post-prostatectomy radiotherapy: analysis of toxicity and biochemical control. J Nucl Med 2004; 45:1315–1322.
116. Ellis RJ, Vertocnik A, Kim E, et al. Four-year biochemical outcome after radioimmunoguided transperineal brachytherapy for patients with prostate adenocarcinoma. Int J Radiat Oncol Biol Phys2003;57:362–370.
117. Ellis RJ, Sodee DB, Spirnak JP, et al. Feasibility and acute toxicities of radioimmunoguided prostate brachytherapy. Int J Radiat Oncol Biol Phys 2000;48:683–687.
118. Liauw SL, Weichselbaum RR, Zagaja GP, et al. Salvage radiotherapy after postprostatectomy biochemical failure: does pretreatment radioimmunoscintigraphy help select patients with locally confined disease? Int J Radiat Oncol Biol Phys 2008;71:1316–1321.
119. Grosu AL, Weber W, Feldmann HJ, et al. First experience with I-123-alpha-methyl-tyrosine SPECT in the 3-D radiation treatment planning of brain gliomas. Int J Radiat Oncol Biol Phys 2000;47:517–526.
120. Grosu AL, Feldmann H, Dick S, et al. Implications of IMT-SPECT for postoperative radiotherapy planning in patients with gliomas. Int J Radiat Oncol Biol Phys 2002;54:842–854.
121. Krengli M, Loi G, Sacchetti G, et al. Delineation of target volume for radiotherapy of high-grade gliomas by 99m Tc-MIBI SPECT and MRI fusion. Strahlenther Onkol 2007;183:689–694.
122. Fenig E, Mishaeli M, Yerushalmi R, et al. Treatment of neuroblastoma using the fused imaging guided radiotherapy (FIGURA) system. Clin Nucl Med 2006;31:256–258.
123. Christian JA, Partridge M, Nioutsikou E, et al. The incorporation of SPECT functional lung imaging into inverse radiotherapy planning for non-small cell lung cancer. Radiother Oncol 2005;77:271–277.
124. Roeske JC, Lujan A, Reba RC, et al. Incorporation of SPECT bone marrow imaging into intensity modulated whole-pelvic radiation therapy treatment planning for gynecologic malignancies. Radiother Oncol 2005;77:11–17.
125. Langen KM, Jones DT. Organ motion and its management. Int J Radiat Oncol Biol Phys 2001;50:265–278.
126. Manning MA, Wu Q, Cardinale RM, et al. The effect of setup uncertainty on normal tissue sparing with IMRT for head-and-neck cancer. Int J Radiat Oncol Biol Phys 2001;51:1400–1409.
127. Engelsman M, Damen EM, De Jaeger K, et al. The effect of breathing and set-up errors on the cumulative dose to a lung tumor. Radiother Oncol 2001;60:95–105.
128. Gierga DP, Chen GT, Kung JH, et al. Quantification of respiration-induced abdominal tumor motion and its impact on IMRT dose distributions. Int J Radiat Oncol Biol Phys 2004;58:1584–1595.
129. Hector CL, Evans PM, Webb S. The dosimetric consequences of inter-fractional patient movement on three classes of intensity-modulated delivery techniques in breast radiotherapy. Radiother Oncol2001;59:281–291.
130. de Crevoisier R, Tucker SL, Dong L, et al. Increased risk of biochemical and local failure in patients with distended rectum on the planning CT for prostate cancer radiotherapy. Int J Radiat Oncol Biol Phys 2005;62:965–973.
131. Simpson DR, Lawson JD, Nath SK, et al. A survey of image-guided radiation therapy use in the United States. Cancer 2010;116:3953–3960.
132. Hangiandreou NJ. B-mode US: basic concepts and new technology. Radiographics 2003;23:1019–1033.
133. Bouchet LG, Meeks SL, Goodchild G, et al. Calibration of three-dimensional ultrasound images for image-guided radiation therapy. Phys Med Biol 2001;46:559–577.
134. Tome WA, Meeks SL, Orton NP, et al. Commissioning and quality assurance of an optically guided three-dimensional ultrasound target localization system for radiotherapy. Med Phys 2002;29:1781–1788.
135. Chandra A, Dong L, Huang E, et al. Experience of ultrasound-based daily prostate localization. Int J Radiat Oncol Biol Phys 2003;56:436–447.
136. Lattanzi J, McNeeley S, Hanlon A, et al. Ultrasound-based stereotactic guidance of precision conformal external beam radiation therapy in clinical localized prostate cancer. Urology 2000;55:73–78.
137. Serago CF, Chungbin SJ, Buskirk SJ, et al. Initial experience with ultrasound localization for positioning prostate cancer patients for external beam radiotherapy. Int J Radiat Oncol Biol Phys2002;53:1130–1138.
138. Trichter F, Ennis RD. Prostate localization using transabdominal ultrasound imaging. Int J Radiat Oncol Biol Phys 2003;56:1225–1233.
139. Fuss M, Cavanugh SX, Fuss C, et al. Daily stereotactic ultrasound prostate targeting: inter-user variability. Technol Cancer Res Treat 2003;2:161–170.
140. Little DJ, Dong L, Levy LB, et al. Use of portal images and BAT ultrasonography to measure setup error and organ motion for prostate IMRT: implications for treatment margins. Int J Radiat Oncol Biol Phys 2003;56:1218–1224.
141. Dobler B, Mai S, Ross C, et al. Evaluation of possible prostate displacement induced by pressure applied during transabdominal ultrasound image acquisition. Strahlenther Onkol 2006;182:240–246.
142. Artignan X, Smitsmans MH, Lebesque JV, et al. Online ultrasound image guidance for radiotherapy of prostate cancer: impact of image acquisition on prostate displacement. Int J Radiat Oncol Biol Phys2004;59:595–601.
143. Fung AYC, Enke CA, Ayyangar KM, et al. Prostate motion and isocenter adjustment from ultrasound-based localization during delivery of radiation therapy. Int J Radiat Oncol Biol Phys 2005;61:984–992.
144. Langen KM, Pouliot J, Anezinos C, et al. Evaluation of ultrasound-based prostate localization for image-guided radiotherapy. Int J Radiat Oncol Biol Phys 2003;57:635–644.
145. Kuban DA, Dong L, Cheung R, et al. Ultrasound-based localization. Semin Radiat Oncol 2005;15:180–191.
146. Huang E, Dong L, Chandra A, et al. Intrafraction prostate motion during IMRT for prostate cancer. Int J Radiat Oncol Biol Phys 2002;53:261–268.
147. Lattanzi J, McNeeley S, Donnelly S, et al. Ultrasound-based stereotactic guidance in prostate cancer—quantification of organ motion and set-up errors in external beam radiation therapy. Comput Aided Surg 2000;5:289–295.
148. O’Daniel JC, Dong L, Zhang L, et al. Dosimetric comparison of four target alignment methods for prostate cancer radiotherapy. Int J Radiat Oncol Biol Phys 2006;66:883–891.
149. Van den Heuvel F, Powell T, Seppi E, et al. Independent verification of ultrasound based image-guided radiation treatment, using electronic portal imaging and implanted gold markers. Med Phys2003;30:2878–2887.
150. Scarbrough TJ, Golden NM, Ting JY, et al. Comparison of ultrasound and implanted seed marker prostate localization methods: implications for image-guided radiotherapy. Int J Radiat Oncol Biol Phys2006;65:378–387.
151. Gayou O, Miften M. Comparison of mega-voltage cone-beam computed tomography prostate localization with online ultrasound and fiducial markers methods. Med Phys 2008;35:531–538.
152. Kupelian PA, Thakkar VV, Khuntia D, et al. Hypofractionated intensity-modulated radiotherapy (70 Gy at 2.5 Gy per fraction) for localized prostate cancer: long-term outcomes. Int J Radiat Oncol Biol Phys 2005;63:1463–1468.
153. Zerini D, Jereczek-Fossa BA, Vavassori A, et al. 3D-conformal hypofractionated radiotherapy for prostate cancer with daily transabdominal ultrasonography prostate localization: toxicity and outcome of a pilot study. Tumori2010;96:941–946.
154. Lock M, Best L, Wong E, et al. A phase II trial of arc-based hypofractionated intensity-modulated radiotherapy in localized prostate cancer. Int J Radiat Oncol Biol Phys 2011;80:1306–1315.
155. Jani AB, Gratzle J, Muresan E, et al. Analysis of acute toxicity with the use of transabdominal ultrasonography for prostate positioning during intensity modulated radiotherapy. Urology 2005;65:504–508.
156. Jani AB, Gratzle J, Muresan E, et al. Impact on late toxicity of using transabdominal ultrasound for prostate cancer patients treated with intensity modulated radiotherapy. Technol Cancer Res Treat2005;4:115–120.
157. Bohrer M, Schroder P, Welzel G, et al. Reduced rectal toxicity with ultrasound-based image guided radiotherapy using BAT (B-mode acquisition and targeting system) for prostate cancer. Strahlenther Onkol 2008;184:674–678.
158. Paskalev K, Feigenberg S, Jacob R, et al. Target localization for post-prostatectomy patients using CT and ultrasound image guidance. J Appl Clin Med Phys 2005;6:40–49.
159. Chinnaiyen P, Tomee W, Patel R, et al. 3D-ultrasound guided radiation therapy in the post-prostatectomy setting. Technol Cancer Res Treat 2003;2:455–458.
160. Kim H, Brandner E, Hug MS, Beriwal S. Clinical application of ultrasound imaging in radiation therapy. In: Minin IV, Minin OV, eds. Ultrasound imaging—medical applications. Rijeka, Croatia: InTech Publishing, 2011:313–330.
161. Small W Jr, Strauss JB, Hwang CS, et al. Should uterine tandem applicators ever be placed without ultrasound guidance? No: a brief report and review of the literature. Int J Gynecol Cancer2011;21:941–944.
162. Davidson MTM, Yuen J, D’Souza DP, et al. Optimization of high-dose-rate cervix brachytherapy applicator placement: the benefits of intraoperative ultrasound guidance. Brachytherapy 2008;7:248–253.
163. Chadha M, Young A, Geraghty C, et al. Image guidance using 3D-ultrasound (3D-US) for daily positioning of lympectomy cavity for boost irradiation. Radiat Oncol 2011;6:45–49.
164. Wong P, Heimann R, Hard D, et al. A multi-institutional comparison study evaluating the use of 3D-ultrasound for defining the beast tumor bed for IGRT in chemotherapy versus non-chemotherapy patients. Int J Radiat Oncol Biol Phys 2008;72:179–180.
165. Boda-Heggemann J, Walter C, Mai S, et al. Frameless stereotactic radiosurgery of a solitary liver metastasis using active breathing control and stereotactic ultrasound. Strahlenther Onkol 2006;182:216–221.
166. Fuss M, Salter BJ, Cavanagh SX, et al. Daily ultrasound-based image-guided targeting for radiotherapy of upper abdominal malignancies. Int J Radiat Oncol Biol Phys 2004;59:1245–1256.
167. Meeks SL, Buatti JM, Bouchet LG, et al. Ultrasound-guided extracranial radiosurgery: technique and application. Int J Radiat Oncol Biol Phys 2003;55:1092–1101.
168. Fuller CD, Thomas CR, Wong A, et al. Image-guided intensity-modulated radiation therapy for gallbladder carcinoma. Radiother Oncol 2006;81:65–72.
169. Fuller CD, Dang ND, Wang SJ, et al. Image-guided intensity-modulated radiotherapy (IG-IMRT) for biliary adenocarcinomas: initial clinical results. Radiother Oncol 2009;92:249–254.
170. Fuss M, Wong A, Fuller CD, et al. Image-guided intensity-modulated radiotherapy for pancreatic carcinoma. Gastrointest Cancer Res 2007;1:2–11.
171. Connor W, Boone M, Veomett R, et al. Patient repositioning and motion detection using a video cancellation system. Int J Radiat Oncol Biol Phys 1975;1:147–153.
172. Milliken BD, Rubin SJ, Hamilton RJ, et al. Performance of a video-image-subtraction-based patients positioning system. Int J Radiat Oncol Biol Phys 1997;38:855–866.
173. Johnson S, Milliken BD, Hadley SW, et al. Initial clinical experience with a video-based patient positioning system. Int J Radiat Oncol Biol Phys 1999;45:205–213.
174. Baroni G, Ferrigno G, Orrechia R, et al. Real-time opto-electronic verification of patient position in breast cancer radiotherapy. Comput Aided Surg 2000;5:296–306.
175. Bert C, Metheany KG, Doppke K, et al. A phantom evaluation of a stereo-vision surface imaging system for radiotherapy patient setup. Med Phys 2005;32:2753–2762.
176. Miller DA, Klein EE. Video-guided patient positioning and localization using the Align RT system in a patient with breast cancer. In: Mundt AJ, Roeske J, eds. Image-guided radiation therapy: a clinical perspective. Shelton, CT: People’s Medical Publishing House-USA, 2011:308–311.
177. Cerviño LI, Pawlicki T, Lawson JD, et al. Frame-less and mask-less cranial stereotactic radiosurgery: a feasibility study. Phys Med Biol 2010;55:1863–1873.
178. Cerviño LI, Detorie N, Taylor M, et al. Initial clinical experience with a frameless and maskless stereotactic radiosurgery treatment. Pract Radiat Oncol 2012;2:54–62.
179. Li G, Ballangrud A, Kuo LC, et al. Motion monitoring for cranial frameless stereotactic radiosurgery using video-based three-dimensional optical surface imaging. Med Phys 2011;38:3981–3994.
180. Li S, Geng J. Real-time-3D-video-guided IMRT: Emerging technology. In: Mundt AJ, Roeske JC, eds. Intensity modulated radiation therapy: a clinical perspective. Toronto: BC Decker, 2005:407–413.
181. Djajaputra D, Li S. Real-time surface-image-guided beam setup in radiotherapy of breast cancer. Med Phys 2005;32:65–75.
182. Li S, Liu D, Yin G, et al. Real-time 3D surface-guided head refixation useful for fractionated stereotactic radiotherapy. Med Phys 2006;33:492–503.
183. De Neve W, van den Heuvel F, de Beukeleer M, et al. Routine clinical on-line portal imaging followed by immediate field adjustment using a tele-controlled patient couch. Radiother Oncol 1992;24:45–54.
184. Gildersleve J, Dearnaley DP, Evans PM, et al. A randomized trial of patient repositioning during radiotherapy using a megavoltage imaging system. Radiother Oncol 1994;31:161–168.
185. Michalski JM, Graham MV, Bosch WR, et al. Prospective clinical evaluation of a electronic portal imaging device. Int J Radiat Oncol Biol Phys 1996;34:943–951.
186. Bel A, Keus R, Vijlbrief RE, et al. Setup deviations in wedged pair irradiation of parotid gland and tonsillar tumors, measured with an electronic portal imaging device. Radiother Oncol 1995;37:153–159.
187. de Boer HCJ, Sornsen de Koste JR, Senan S, et al. Analysis and reduction of 3D systematic and random setup errors during the simulation and treatment of lung cancer patients with CT-based external beam radiotherapy dose planning. Int J Radiat Oncol Biol Phys 2001;49:857–868.
188. Fein DA, McGee KP, Schultheiss TE, et al. Intra- and inter-fractional reproducibility of tangential breast fields: a prospective on-line portal imaging study. Int J Radiat Oncol Biol Phys 1996;34:733–740.
189. Olofsen-van Acht M, van den Berg H, Quint S, et al. Reduction of irradiation small bowel volume and accurate patient positioning by use of a bellyboard device in pelvic radiotherapy of gynecological cancer patients. Radiother Oncol 2001;59:87–93.
190. Herman MG. Clinical use of electronic portal imaging. Sem Radiat Oncol 2005;15:157–167.
191. Van de Steene J, Van den Heuvel F, Bel A, et al. Electronic portal imaging with on-line correction of setup error in thoracic irradiation: clinical evaluation. Int J Radiat Oncol Biol Phys 1998;40:967–976.
192. Stroom JC, Olofsen-van Acht MJJ, Quint S, et al. On-line setup corrections during radiotherapy of patients with gynecologic tumors. Int J Radiat Oncol Biol Phys 2000;46:499–506.
193. Antonuk L. Electronic portal imaging devices: a review and historical perspective of contemporary technologies and research. Phys Med Biol 2002;47:R31–R65.
194. Boyer AL, Antonuk L, Fenster A, et al. A review of electronic portal imaging devices (EPIDs). Med Phys 1992;19:1–16.
195. Bel A, van Herk M, Bartelink H, et al. A verification procedure to improve patient setup accuracy using portal images. Radiother Oncol 1993;29:253–260.
196. Bel A, Vos PH, Rodrigus PTR, et al. High precision prostate cancer irradiation by clinical application of an offline patient setup verification procedure, using portal imaging. Int J Radiat Oncol Biol Phys1996;35:321–332.
197. Erridge SC, Seppenwoolde Y, Muller SH, et al. Portal imaging to assess setup-errors, tumor motion and tumor shrinkage during conformal radiotherapy of non-small cell lung cancer. Radiother Oncol2003;66:75–85.
198. de Boer HCJ, van Sornsen de Koste JR, Creutzbeerg CL, et al. Electronic portal image assisted reduction of systematic set-up errors in head and neck irradiation. Radiother Oncol 2001;61:299–308.
199. de Boer HCJ, Meijman BJM. A protocol for the reduction of systematic patient setup errors with minimal portal imaging workload. Int J Radiat Oncol Biol Phys 2001;50:1350–1365.
200. Vigneault E, Pouliot J, Laverdiere J, et al. Electronic portal imaging device detection of radiopaque markers for the evaluation of prostate position during megavoltage radiation: a clinical study. Int J Radiat Oncol Biol Phys1997;37:205–212.
201. Welsh JS, Berta C, Borzillary S, et al. Fiducial markers implanted during prostate brachytherapy for guiding conformal external beam radiation therapy. Technol Cancer Res Treat 2004;3:359–364.
202. Pouliot J, Aubin M, Langen KM, et al. (Non)-migration of radiopaque markers used for on-line localization of the prostate with an electronic portal imaging device. Int J Radiat Oncol Biol Phys2003;56:862–866.
203. Chung PWM, Haycocks T, Brown T, et al. On-line aSi portal imaging of implanted fiducial markers for the reduction of interfraction error during conformal radiotherapy of prostate carcinoma. Int J Radiat Oncol Biol Phys2004;60:329–334.
204. Schallenkamp JM, Herman MG, Kruse JJ, et al. Prostate position relative to pelvic bony anatomy based on intraprostatic gold markers and electronic portal imaging. Int J Radiat Oncol Biol Phys2005;63:800–811.
205. Ullman KL, Ning H, Susil RC, et al. Intra- and inter-radiation therapist reproducibility of daily isocenter verification using prostatic fiducial markers. Radiat Oncol 2006;1:2–6.
206. Kupelian PA, Willoughby TR, Meeks SL, et al. Intraprostatic fiducials for localization of the prostate gland: monitoring inter-marker distances during radiation therapy to test for marker stability. Int J Radiat Oncol Biol Phys2005;62:1291–1296.
207. Nichol AM, Rosewall T, Catton CN, et al. Intra-prostatic fiducial markers and concurrent androgen deprivation. Clin Oncol (R Coll Radiol) 2005;17:465–468.
208. Kaatee RS, Olofesen MJ, Verstraate MB, et al. Detection of organ movement in cervix cancer patients using a fluoroscopic electronic portal imaging device and radiopaque markers. Int J Radiat Oncol Biol Phys 2002;54:576–583.
209. Wu WC, Leung WS, Kay SS, et al. A comparison between electronic portal imaging device and cone beam CT in radiotherapy verification of nasopharyngeal carcinoma. Med Dosim 2011;36:109–112.
210. Topolnjak R, Sonke JJ, Nijkamp J, et al. Breast patient setup error assessment: comparison of electronic portal image devices and cone-beam computed tomography matching results. Int J Radiat Oncol Biol Phys 2010;78:1235–1243.
211. Zaghlouol MS, Mousa AG, Eldebawy E, et al. Comparison of electronic portal imaging and cone beam computed tomography for position verification in children. Clin Oncol (R Coll Radiol)2010;22:850–861.
212. Nichol A, Chung P, Lockwood G, et al. A phase II study of localized prostate cancer treated to 75.6 Gy with 3D conformal radiotherapy. Radiother Oncol 2005;76:11–17.
213. Peeters STH, Heemsbergen WD, van Putten WLJ, et al. Acute and late complications after radiotherapy for prostate cancer: results of a multicenter randomized trial comparing 68 Gy to 78 Gy. Int J Radiat Oncol Biol Phys2005;61:1019–1034.
214. Ost P, De Gersem W, De Potter B, et al. A comparison of the acute toxicity profile between two-dimensional and three-dimensional image-guided radiotherapy for postoperative prostate cancer. Clin Oncol (R Coll Radiol)2011;23:344–349.
215. Adler JR, Murphy MJ, Chang SD, et al. Image guided robotic radiosurgery. Neurosurgery 1999;44:1299–1306.
216. Furweger C, Drexler C, Kufeld M, et al. Patient motion and targeting accuracy in robotic spinal radiosurgery: 260 single-fraction fiducial-free cases. Int J Radiat Oncol Biol Phys 2010;78:937–945.
217. Murphy MJ, Cox RS. The accuracy of dose localization for an image-guided frameless radiosurgery system. Med Phys 1996;23:2043–2049.
218. Yu C, Main W, Taylor D, et al. An anthropomorphic phantom study of the accuracy of Cyberknife spine radiosurgery. Neurosurgery 2004;55:1138–1149.
219. Kajiwara K, Saito K, Yoshikawa K, et al. Image-guided radiosurgery with the Cyberknife for pituitary adenomas. Minim Invasive Neurosurg 2005;48:91–96.
220. Iwata H, Sato K, Tatewaki K, et al. Hypofractionated stereotactic radiotherapy with CyberKnife for nonfunctioning pituitary adenoma: a high local control with low toxicity. Neuro Oncol 2011;13:916–922.
221. Ishihara H, Saito K, Nishizaki T, et al. Cyberknife radiosurgery for vestibular schwannoma. Minim Invasive Neurosurg 2004;47:290–293.
222. Yoshikawa K, Saito K, Kajiwara K, et al. Cyberknife stereotactic radiotherapy for patients with malignant glioma. Minim Invasive Neurosurg 2006;49:110–115.
223. Villavicencio AT, Nurneikiene S, Romanelli P, et al. Survival following stereotactic radiosurgery for newly diagnosed and recurrent glioblastoma multiforme: a multicenter experience. Neurosurg Rev2009;32:417–424.
224. Shimamoto S, Inoue T, Shiomi H, et al. Cyberknife stereotactic irradiation for metastatic brain tumors. Radiat Med 2002;20:299–304.
225. Colombo F, Casentini L, Cavedon C, et al. CyberKnife radiosurgery for benign meningiomas: short-term results in 199 patients. Neurosurgery 2009;64:A7–A13.
226. Tang CT, Chang SD, Tseng KY, et al. CyberKnife stereotactic radiosurgical rhizotomy for refractory trigeminal neuralgia. J Clin Neurosci 2011;18:1449–1453.
227. Villavicencio AT, Lim M, Burneikiene S, et al. CyberKnife radiosurgery for trigeminal neuralgia treatment: a preliminary multicenter experience. Neurosurgery 2008;62:647–655.
228. Colombo F, Cavedon C, Casentini L, et al. Early results of CyberKnife radiosurgery for arteriovenous malformations. J Neurosurg 2009;111:807–819.
229. Mehta VK, Lee QT, Chang SD, et al. Image-guided stereotactic radiosurgery for lesions in proximity to the anterior visual pathways: a preliminary report. Technol Cancer Res Treat 2002;1:173–180.
230. Pham CJ, Chang SD, Gibbs IC, et al. Preliminary visual field preservation after staged Cyberknife radiosurgery for perioptic lesions. Neurosurgery 2004;54:799–810.
231. Giller CA, Berger BD, Gillo JP, et al. Feasibility of radiosurgery for malignant brain tumors in infants by use of image-guided robotic radiosurgery: preliminary report. Neurosurgery 2004;55:916–924.
232. Giller CA, Berger BD, Pistenmaa DA, et al. Robotically guided radiosurgery for children. Pediatr Blood Cancer 2005;45:304–331.
233. Dodd RL, Ryu MR, Kamnerdsupaphon P, et al. Cyberknife radiosurgery for benign intradural extramedullary spinal tumors. Neurosurgery 2006;58:674–685.
234. Ryu SI, Chang SD, Kim DH, et al. Image-guided hypo-fractionated stereotactic radiosurgery to spinal lesions. Neurosurgery 2001;49:838–846.
235. Sinclair J, Chang SD, Gibbs IC, et al. Multisession Cyberknife radiosurgery for intramedullary spinal cord arteriovenous malformations. Neurosurgery 2006;58:1081–1089.
236. Gerszten PC, Ozhasoglu C, Burton SA, et al. Cyberknife frameless single-fraction stereotactic radiosurgery for tumors of the sacrum. Neurosurg Focus 2003;15:E7.
237. Gerszten PC, Germanwala A, Burton SA, et al. Combination kyphoplasty and spinal radiosurgery: a new treatment paradigm for pathological fractures. J Neurosurg Spine 2005;3:296–301.
238. Gerszten PC, Ozhasoglu C, Burton SA, et al. Cyberknife frameless stereotactic radiosurgery for spinal lesions: clinical experience in 125 cases. Neurosurgery 2004;55:89–99.
239. Bhatnagar AK, Gerszten PC, Ozhasaglu C, et al. Cyberknife frameless radiosurgery for the treatment of extracranial benign tumors. Technol Cancer Res Treat 2005;4:571–576.
240. Patel VB, Wegner RE, Heron DE, et al. Comparison of whole versus partial vertebral body stereotactic body radiation therapy for spinal metastases. Technol Cancer Res Treat 2012;11:105–115.
241. Kufeld M, Wowra B, Muacevic A, et al. Radiosurgery of spinal meningiomas and schwannomas. Technol Cancer Res Treat 2012;11:27–34.
242. Martin AG, Cowley IR, Taylor BA, et al. Stereotactic radiosurgery XIX: spinal radiosurgery—two year experience in a UK centre. Br J Neurosurg 2012;26:53–58.
243. Chang UK, Rhee CH, Youn SM, et al. Radiosurgery using the Cyberknife for benign spinal tumors: Korea Cancer Center Hospital experience. J Neurooncol 2011;101:91–99.
244. Tsai JT, Lin JW, Chiu WT, et al. Assessment of image-guided CyberKnife radiosurgery for metastatic spine tumors. J Neurooncol 2009;94:119–127.
245. Gagnon GJ, Nasr NM, Liao JJ, et al. Treatment of spinal tumors using CyberKnife fractionated stereotactic radiosurgery: pain and quality-of-life assessment after treatment in 200 patients. Neurosurgery2009;64:297–306.
246. Sahgal A, Chou D, Ames C, et al. Image-guided robotic stereotactic body radiotherapy for benign spinal tumors: the University of California San Francisco preliminary experience. Technol Cancer Res Treat 2007;6:595–604.
247. Gibbs IC, Kamnerdsupaphon P, Ryu MR, et al. Image-guided robotic radiosurgery for spinal metastases. Radiother Oncol 2007;82:185–190.
248. Gwak HS, Yoo HJ, Youn SM, et al. Hypofractionated stereotactic radiation therapy for skull base and upper cervical chordoma and chondrosarcoma: preliminary results. Stereotact Funct Neurosurg2005;83:233–243.
249. Chang UK, Youn SM, Park SQ, et al. Clinical results of CyberKnife radiosurgery for spinal metastases. J Korean Neurosurg Soc 2009;46:538–544.
250. King CR, Lehmann J, Adler JR, et al. Cyberknife radiotherapy for localized prostate cancer: rationale and technical feasibility. Technol Cancer Res Treat 2003;2:25–30.
251. Nuyttens JJ, Prevost JB, Praag J, et al. Lung tumor tracking during stereotactic radiotherapy treatment with the CyberKnife: marker placement and early results. Acta Oncol 2006;45:961–965.
252. King CR, Brooks JD, Gill H, et al. Stereotactic body radiosurgery for localized prostate cancer: interim results of a prospective phase II clinical trial. Int J Radiat Oncol Biol Phys 2009;73:1043–1048.
253. McBride SM, Wong DS, Dombrowski JJ, et al. Hypofractionated stereotactic body radiotherapy in low-risk prostate adenocarcinoma: preliminary results of a multi-institutional phase I feasibility trial. Cancer2012;118(15):3681–3690.
254. Brown WT, Wu X, Fayad F, et al. CyberKnife radiosurgery for stage I lung cancer: results at 36 months. Clin Lung Cancer 2007;8:488–492.
255. Kim MS, Choi C, Yoo S, et al. Stereotactic body radiation therapy in patients with pelvic recurrence from rectal carcinoma. Jpn J Clin Oncol 2008;38:695–700.
256. Choi CW, Cho CK, Yoo SY, et al. Image-guided stereotactic body radiation therapy in patients with isolated para-aortic lymph node metastases from uterine cervical and corpus cancer. Int J Radiat Oncol Biol Phys2009;74:147–153.
257. Roh KW, Jang JS, Kim MS, et al. Fractionated stereotactic radiotherapy as reirradiation for locally recurrent head and neck cancer. Int J Radiat Oncol Biol Phys 2009;74:1348–1355.
258. Son SH, Choi BO, Ryu MR, et al. Stereotactic body radiotherapy for patients with unresectable primary hepatocellular carcinoma: dose-volumetric parameters predicting the hepatic complication. Int J Radiat Oncol Biol Phys2010;78:1073–1080.
259. Yan H, Yin FF, Kim JH. A phantom study on the positioning accuracy of the Novalis Body system. Med Phys 2003;30:2052–2060.
260. Rahimian J, Chen JC, Rao AA, et al. Geometrical accuracy of the Novalis stereotactic radiosurgery system for trigeminal neuralgia. J Neurosurg 2004;101:351–355.
261. Chen JC, Girvigian M, Greathouse H, et al. Treatment of trigeminal neuralgia with linear accelerator radiosurgery: initial results. J Neurosurg 2004;101:346–350.
262. Ernst-Stecken A, Lambrecht U, Mueller R, et al. Dose escalation in large anterior skull-base tumors by means of IMRT. First experience with the Novalis system. Strahlenther Onkol 2006;182:183–189.
263. Pedroso AG, De Salles AA, Tajik K, et al. Novalis shaped beam radiosurgery of arteriovenous malformations. J Neurosurg 2004;101:425–434.
264. Whang CJ, Yee GT, Choi CY et al. First experience in using Novalis shaped beam radiosurgery in Korea. J Neurosurg 2004;101:341–345.
265. Chen JC, Rahimian J, Rahimian R, et al. Frameless image-guided radiosurgery for initial treatment of typical trigeminal neuralgia. World Neurosurg 2010; 74:538–543.
266. Hashizume C, Mori Y, Kobayashi T, et al. Stereotactic radiotherapy using Novalis for craniopharyngioma adjacent to optic pathways. J Neurooncol 2010;98:239–247.
267. Mori Y, Hashizume C, Kobayashi T, et al. Stereotactic radiotherapy using Novalis for skull base metastases developing with cranial nerve symptoms. J Neurooncol 2010;98:213–219.
268. Biswas T, Okunieff P, Schell MC, et al. Stereotactic radiosurgery for glioblastoma: retrospective analysis. Radiat Oncol 2009;4:11–15.
269. Benzil DL, Saboori M, Mogilner AY, et al. Safety and efficacy of stereotactic radiosurgery for tumors of the spine. J Neurosurg 2004;101:413–418.
270. De Salles AA, Pedroso AG, Medin P, et al. Spinal lesions treated with Novalis shaped beam intensity-modulated radiosurgery and stereotactic radiotherapy. J Neurosurg 2004;101:435–440.
271. Ryu S, Yin FF, Rock J, et al. Image-guided and intensity-modulated radiosurgery for patients with spinal metastasis. Cancer 2003;97:2013–2018.
272. Ryu S, Rock J, Rosenblum M, et al. Patterns of failure after single-dose radiosurgery for spinal metastasis. J Neurosurg 2004;101:402–405.
273. Ernst-Stecken A, Lambrecht U, Mueller R, et al. Hypofractionated stereotactic radiotherapy for primary and secondary intrapulmonary tumors: first results of a phase I/II study. Strahlenther Onkol2006;182:696–702.
274. Videtic GM, Stephans K, Reddy C, et al. Intensity-modulated radiotherapy-based stereotactic body radiotherapy for medically inoperable early-stage lung cancer: excellent local control. Int J Radiat Oncol Biol Phys2010;77:344–349.
275. Iawata H, Shibamoto Y, Hashizume C, et al. Hypofractionated stereotactic body radiotherapy for primary and metastático liver tumors using the Novalis image-guided system: preliminary results regarding efficacy and toxicity. Technol Cancer Res Treat 2010;9:619–627.
276. Dhakal S, Corbin KS, Milano MT, et al. Stereotactic body radiotherapy for pulmonary metastases from soft-tissue sarcomas: excellent local lesion control and improved patient survival. Int J Radiat Oncol Biol Phys2012;82:940–945.
277. Ryu S, Khan M, Yin FF, et al. Image-guided radiosurgery of head and neck cancers. Otolaryngol Head Neck Surg 2004;130:690–697.
278. Soete G, Arcangeli S, De Meerleer G, et al. Phase II study of a four-week hypofractionated external beam radiotherapy regimen for prostate cancer: report on acute toxicity. Radiother Oncol 2006;80:78–81.
279. Soete G, Verellen D, Michielsen D, et al. Clinical use of stereoscopic x-ray positioning of patients treated with conformal radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2002;54:948–952.
280. Shirato H, Shimizu S, Kuneida T, et al. Physical aspects of a real-time tumor-tracking system for gated radiotherapy. Int J Radiat Oncol Biol Phys 2000;48:1187–1195.
281. Harada T, Shirato H, Ogura S, et al. Real-time tumor-tracking radiation therapy for lung carcinoma by the aid of insertion of a gold marker using broncho-fiberoscopy. Cancer 2002;95:1720–1727.
282. Shirato H, Shimizu S, Kitamura K et al. Four-dimensional treatment planning and fluoroscopic real-time tumor tracking radiotherapy for moving tumor. Int J Radiat Oncol Biol Phys 2000;48:435–442.
283. Kitamura K, Shirato H, Seppenwoolde Y, et al. Three-dimensional intrafractional movement of the prostate measured during real-time tumor-tracking radiotherapy in supine and prone treatment positions. Int J Radiat Oncol Biol Phys 2002;53:1117–1123.
284. Kitamura K, Shirato H, Seppenwoolde Y, et al. Tumor location, cirrhosis and surgical history contribute to tumor movement in the liver, as measured during stereotactic irradiation using a real-time tumor-tracking radiotherapy system. Int J Radiat Oncol Biol Phys 2003;56:221–228.
285. Kitamura K, Shirato H, Shinohara N, et al. Reduction in acute morbidity using hypofractionated intensity-modulated radiation therapy assisted with a fluoroscopic real-time tumor-tracking system for prostate cancer: preliminary results of a phase I/II study. Cancer J 2003;9:268–276.
286. Imura M, Yamazaki K, Shirato H, et al. Insertion and fixation of fiducial markers for setup and tracking of lung tumors in radiotherapy. Int J Radiat Oncol Biol Phys 2005;63:1442–1447.
287. Hashimoto T, Shirato H, Kato M, et al. Real-time monitoring of a digestive tract marker to reduce adverse effects of moving organs at risk in radiotherapy for thoracic and abdominal tumors. Int J Radiat Oncol Biol Phys2005;61:1559–1564.
288. Yamamoto R, Yonesaka A, Watari H, et al. High dose three-dimensional conformal boost (3DCB) using an orthogonal diagnostic x-ray set-up for patients with gynecological malignancy: a new application of real-time tumor-tracking system. Radiother Oncol 2004;73:219–222.
289. Shirato H, Suzuki K, Sharp GC, et al. Speed and amplitude of lung tumor motion precisely detected in four-dimensional setup and in real-time tumor-tracking radiotherapy. Int J Radiat Oncol Biol Phys2006;64:1229–1236.
290. Shimizu S, Shirato H, Ogura S, et al. Detection of lung tumor movement in real-time tumor-tracking radiotherapy. Int J Radiat Oncol Biol Phys 2001;51:304–310.
291. Sakakibara-Konishi J, Oizumi S, Kinoshita I, et al. Phase I study of concurrent real-time tumor-tracking thoracic radiation therapy with paclitaxel and carboplatin in locally advanced non-small cell lung cancer. Lung Cancer2011;74:248–252.
292. Park HC, Shimizu S, Yonesaka A, et al. High dose three-dimensional conformal boost using the real-time tumor tracking radiotherapy system in cervical cancer patients unable to receive intracavitary brachytherapy. Yonsei Med J 2010;51:93–99.
293. Taguchi H, Sakuhara Y, Hige S, et al. Intercepting radiotherapy using a real-time tumor-tracking radiotherapy system for highly selected patients with hepatocellular carcinoma unresectable with other modalities. Int J Radiat Oncol Biol Phys 2007;69:376–380.
294. Ahn YC, Shimizu S, Shirato H, et al. Application of real-time tumor-tracking and gated radiotherapy system for unresectable pancreatic cancer. Yonsei Med J 2004;45:584–590.
295. Balter J, Brock K, Litzenberg DW, et al. Daily targeting of intrahepatic tumors for radiotherapy. Int J Radiat Oncol Biol Phys 2002;52:266–271.
296. Wong J, Sharpe MB, Jaffray DA, et al. The use of active breathing control (ABC) to reduce margin for breathing motion. Int J Radiat Oncol Biol Phys 1999;44:911–919.
297. Ben-Josef E, Normolle D, Ensminger WD, et al. Phase II trial of high-dose conformal radiation therapy with concurrent hepatic artery floxurdine for unresectable intra-hepatic malignancies. J Clin Oncol2005;23:8739–8747.
298. Britton KR, Takai Y, Mitsuya M, et al. Evaluation of inter- and intrafraction organ motion during intensity modulated radiation therapy (IMRT) for localized prostate cancer measured by a newly developed on-board image-guided system. Radiat Med 2005;23:14–24.
299. Takai Y, Mitsuya M, Nemoto K, et al. Development of a real-time tumor tracking system with dMLC with dual x-ray fluoroscopy and amorphous silicon flat panel on the gantry of a linear accelerator. Int J Radiat Oncol Biol Phys 2002;54:193–194.
300. Berbeco RI, Jiang SB, Sharp GC, et al. Integrated radiotherapy imaging system (IRIS): design considerations of tumour tracking with Linac gantry-mounted diagnostic x-ray systems with flat-panel detectors. Phys Med Biol2004;49:243–255.
301. Fox T, Huntzinger C, Johnstone P, et al. Performance evaluation of an automated image registration algorithm using an integrated kilovoltage imaging and guidance system. J Appl Clin Med Phys2006;7:97–104.
302. Zinniker J, Filiberti R, Huntzinger C. Isocenter stability of Linac with an on-board imager. Med Phys 2004;31:1783.
303. Jaffray SA, Drake DG, Moreau M, et al. A radiographic and tomographic imaging system integrated into a medical linear accelerator for localization of bone and soft-tissue targets. Int J Radiat Oncol Biol Phys 1999;45:773–789.
304. Lawson JD, Fox T, Elder E, et al. Early clinical experience with kilovoltage image-guided radiation therapy for interfraction motion management. Med Dosim 2008;33:268–274.
305. Pisani L, Lockman D, Jaffray D, et al. Setup error in radiotherapy: on-line correction using electronic kilovoltage and megavoltage radiographs. Int J Radiat Oncol Biol Phys 2000;47:825–839.
306. Perkins CL, Fox T, Elder E, et al. Image-guided radiation therapy in gastrointestinal tumors. J Pancreas 2006;7:372–381.
307. Sorcini B, Tilikidis A. Clinical application of image-guided radiotherapy, IGRT (on the Varian OBI platform). Cancer Radiother 2006;10:252–257.
308. Nath SK, Sandhu AP, Sethi RA, et al. Target localization and toxicity in dose-escalated prostate radiotherapy with image-guided approach using daily planar kilovoltage imaging. Technol Cancer Res Treat 2011;19:31–37.
309. Jayachandran P, Minn AY, Van Dam J, et al. Interfractional uncertainty in the treatment of pancreatic cancer with radiation. Int J Radiat Oncol Biol Phys 2010;76:603–607.
310. Varadarajulu S, Trevino JM, Shen S, et al. The use of endoscopic ultrasound-guided gold markers in image-guided radiation therapy of pancreatic cancers: a case series. Endoscopy 2010;42:423–425.
311. Lawson JD, Elder E, Fox T, et al. Quantification of dosimetric impact of implementation of on-board imaging (OBI) for IMRT treatment of head and neck malignancies. Med Dosim 2007;32:287–294.
312. Mechalakos JG, Hunt MA, Lee NY, et al. Using an onboard kilovoltage imager to measure setup deviation in intensity-modulated radiation therapy for head-and-neck patients. J Appl Clin Med Phys2007;8:2439–2443.
313. Bray T, Albuquerque K. KV planar image guided 3DCRT using a Varian linear accelerator in a patient with endometrial adenosarcoma. In: Mundt AJ, Roeske JC, eds. Image-guided radiation therapy: a clinical perspective.Shelton, CT: People’s Medical Publishing House-USA, 2011:462–465.
314. Hong LX, Chen CC, Garg M, et al. Clinical experiences with onboard imager KV images for linear accelerator-based stereotactic radiosurgery. Int J Radiat Oncol Biol Phys 2009;73:556–561.
315. Wang JZ, Rice R, Mundt A, et al. Image-guided stereotactic spine radiosurgery on a conventional linear accelerator. Med Dosim 2010;35:53–62.
316. Wojcicka J, Yankelevich R, Iorio S, et al. On-board imager-based mammosite treatment verification. Med Biol Eng Comment 2007;45:1065–1069.
317. Willis DJ, Kron T, Hubbard P, et al. Online kidney position verification using non-contrast radiographs on a linear accelerator with on board KV x-ray imaging capability. Med Dosim 2009;34:293–300.
318. Uematsu M, Shioda A, Tahara K, et al. Focal, high dose and fractionated modified stereotactic radiation therapy for lung carcinoma patients: a preliminary experience. Cancer 1998;82:1062–1070.
319. Uematsu M, Shioda A, Suda A, et al. Computed tomography-guided frameless stereotactic radiotherapy for stage I non-small cell lung cancer: a 5-year experience. Int J Radiat Oncol Biol Phys2001;51:666–670.
320. Uematsu M, Shioda A, Suda A, et al. Intrafractional tumor position stability during computed tomography (CT)-guided frameless stereotactic radiation therapy for lung or liver cancers with a fusion of CT and linear accelerator (FOCAL) unit. Int J Radiat Oncol Biol Phys 2000;48:443–448.
321. Uematsu M, Fukui T, Shioda A, et al. A dual computed tomography linear accelerator unit for stereotactic radiation therapy: a new approach without cranially fixated stereotactic frames. Int J Radiat Oncol Biol Phys1996;35:587–592.
322. Yenice KM, Lovelock DM, Hunt MA, et al. CT image-guided intensity-modulated therapy for paraspinal tumors using stereotactic immobilization. Int J Radiat Oncol Biol Phys 2003;55:583–593.
323. Yamada Y, Lovelock DM, Yenice KM, et al. Multifractionated image-guided and stereotactic intensity-modulated radiotherapy of paraspinal tumors: a preliminary report. Int J Radiat Oncol Biol Phys2005;62:53–61.
324. Wright JL, Lovelock DM, Bilsky MH, et al. Clinical outcomes after reirradiation of paraspinal tumors. Am J Clin Oncol 2006;29:495–502.
325. Zelefsky MJ, Greco C, Motzer R, et al. Tumor control outcomes after hypofractionated and single-dose stereotactic image-guided intensity-modulated radiotherapy for extracranial metastases from renal cell carcinoma. Int J Radiat Oncol Biol Phys 2012;82(5):1744–1748.
326. Kuriyama K, Onishi H, Sano N, et al. A new irradiation unit constructed of self-moving gantry-CT and Linac. Int J Radiat Oncol Biol Phys 2003;55:428–435.
327. Onishi H, Kuriyama K, Komiyama T, et al. A new irradiation system for lung cancer combining linear accelerator, computed-tomography, patient self-breath-holding, and patient-directed beam-control without respiratory monitoring devices. Int J Radiat Oncol Biol Phys 2003;56:14–20.
328. Onishi H, Kuriyama K, Komiyama T, et al. Clinical outcomes of stereotactic radiotherapy for stage I non-small cell lung cancer using a novel irradiation technique: patient self-controlled breath-hold and beam switching using a combination linear accelerator and CT scanner. Lung Cancer 2004;45:45–55.
329. Shiu AS, Chang EL, Ye JS, et al. Near simultaneous computed tomography image-guided stereotactic spinal radiotherapy: an emerging paradigm for achieving true stereotaxy. Int J Radiat Oncol Biol Phys 2003;57:605–613.
330. Chang EL, Shiu AS, Li MF, et al. Phase I clinical evaluation of near-simultaneous computed tomographic image-guided stereotactic body radiotherapy for spinal metastasis. Int J Radiat Oncol Biol Phys2004;59:1288–1294.
331. Court L, Rosen I, Mohan R, et al. Evaluation of mechanical precision and alignment uncertainties for an integrated CT/Linac system. Med Phys 2003;30:1–13.
332. Chang EL, Shiu AS, Mendel E, et al. Phase I/II study of stereotactic body radiotherapy for spinal metastasis and its pattern of failure. J Neurosurg Spine 2007;7:151–160.
333. Nguyen QN, Shiu AS, Rhines LD, et al. Management of spinal metastases from renal cell carcinoma using stereotactic body radiotherapy. Int J Radiat Oncol Biol Phys 2010;76:1185–1192.
334. Garg AK, Wang XS, Shiu AS, et al. Prospective evaluation of spinal reirradiation by using stereotactic body radiation therapy. Cancer 2011;117:3509–3516.
335. Wong JR, Grimm L, Uematsu M, et al. Image-guided radiotherapy for prostate cancer by CT-linear accelerator combination: prostate movements and dosimetric considerations. Int J Radiat Oncol Biol Phys 2005;61:561–569.
336. Cheng CW, Wong J, Grimm L, et al. Commissioning and clinical implementation of a sliding gantry CT scanner installed in an existing treatment room and early clinical experience for precise tumor localization. Am J Clin Oncol 2003;26:28–36.
337. Chen L, Paskalev K, Xu X, et al. Rectal dose variation during the course of image-guided radiation therapy of prostate cancer. Radiother Oncol 2010;95:198–202.
338. Chen RJ, Paskalev K, Litwin S, et al. Esophageal motion during radiotherapy: quantification and margin implications. Dis Esophagus 2010;23:473–479.
339. Ma CM, Paskalev K. In-room techniques for image-guided radiation therapy. Med Dosim 2006;1:30–39.
340. Owen R, Foroudi F, Kron T, et al. A comparison of in-room computerized tomography options for detection of fiducial markers in prostate cancer radiotherapy. Int J Radiat Oncol Biol Phys2010;77:1248–1256.
341. Simpson RG, Chen CT, Grubbs EA, et al. A 4-MV CT scanner for radiation therapy: the prototype system. Med Phys 1982;9:574–579.
342. Nakagawa K, Aoki Y, Akanuma A, et al. Technological features and clinical feasibility of megavoltage CT scanning. Eur Radiol 1992;2;184–189.
343. Nakagawa K, Aoki Y, Tago M, et al. Megavoltage CT-assisted stereotactic radiosurgery for thoracic tumors: original research in the treatment of thoracic neoplasms. Int J Radiat Oncol Biol Phys2000;48:449–457.
344. Mackie TR, Kapatoes J, Ruchala K, et al. Image guidance for precise conformal radiotherapy. Int J Radiat Oncol Biol Phys 2003;56:89–105.
345. Tomsej M. The Tomotherapy Hi-Art System for sophisticated IMRT and IGRT with helical delivery: recent developments and clinical applications. Cancer Radiother 2006;10:288–295.
346. Jeraj R, Mackie TR, Balog J, et al. Radiation characteristics of helical tomotherapy. Med Phys 2004;31:396–404.
347. Forrest LJ, Mackie TR, Ruchala K, et al. The utility of megavoltage computed tomography images from a helical tomotherapy system for setup verification purposes. Int J Radiat Oncol Biol Phys2004;60:1639–1644.
348. Mahan SL, Ramsey CR, Scaperoth DD, et al. Evaluation of image-guided helical tomotherapy for the re-treatment of spinal metastasis. Int J Radiat Oncol Biol Phys 2005;63:1576–1583.
349. Welsh JS, Bradley K, Ruchala KJ, et al. Megavoltage computed tomography imaging: a potential tool to guide and improve the delivery of thoracic radiation therapy. Clin Lung Cancer 2004;5:303–306.
350. Hodge W, Tome WA, Jaradat HA, et al. Feasibility report of image guided stereotactic body radiotherapy (IG-SBRT) with tomotherapy for early stage medically inoperable lung cancer using extreme hypofractation. Acta Oncol2006;45:890–896.
351. Song WY, Chiu B, Bauman GS, et al. Prostate contouring uncertainty in megavoltage computed tomography images acquired with a helical tomotherapy unity during image-guided radiation therapy. Int J Radiat Oncol Biol Phys2006;65:595–607.
352. Langen KM, Zhang Y, Andrews RD, et al. Initial experience with megavoltage (MV) CT guidance for daily prostate alignments. Int J Radiat Oncol Biol Phys 2005;62:1517–1524.
353. Hui SK, Kapatoes J, Fowler J, et al. Feasibility study of helical tomotherapy for total body or total marrow irradiation. Med Phys 2005;32:3214–3224.
354. Pezner RD, Liu A, Han C, et al. Dosimetric comparison of helical tomotherapy treatment and step-and-shoot intensity-modulated radiotherapy of retroperitoneal sarcoma. Radiother Oncol 2006;81:81–87.
355. Sheng K, Molloy JA, Read PW. Intensity-modulated radiation therapy (IMRT) dosimetry of the head and neck: a comparison of treatment plans using linear accelerator-based IMRT and helical tomotherapy. Int J Radiat Oncol Biol Phys 2006;65:917–923.
356. Choe J, Kulasekere R, Oddo D, et al. Helical tomotherapy versus conventional radiation to deliver abdominopelvic radiation. Technol Cancer Res Treat 2012;11:49–56.
357. Eldebawy E, Parker W, Abdel Rahman W, et al. Dosimetric study of current treatment options for radiotherapy in retinoblastoma. Int J Radiat Oncol Biol Phys 2012;82:e501–e505.
358. Maggio A, Fiorino C, Mangili P, et al. Feasibility of safe ultra-high (EQD(2)>100 Gy) dose escalation on dominant intra-prostate lesions (DILs) by helical tomotherapy. Acta Oncol 2011;50:25–34.
359. Jones R, Yang W, Read P, et al. Radiation therapy of post-mastectomy patients with positive nodes using fixed beam tomotherapy. Radiother Oncol 2011;100:247–252.
360. Nguyen NP, Krafft SP, Vinh-Hung V, et al. Feasibility of tomotherapy to reduce normal lung and cardiac toxicity for distal esophageal cancer compared to three-dimensional radiotherapy. Radiother Oncol 2011;101:438–442.
361. Ren G, Du L, Ma L, et al. Clinical observation of 73 nasopharyngeal carcinoma patient treated by helical tomotherapy: the China experience. Technol Cancer Res Treat 2011;10:259–266.
362. Kim B, Soisson E, Duma C, et al. Treatment of recurrent high grade gliomas with hypofractionated stereotactic image-guided helical tomotherapy. Clin Neurol Neurosurg 2011;113:509–512.
363. Mesbah L, Matute R, Usychkin S, et al. Helical tomotherapy in the treatment of pediatric malignancies: a preliminary report of feasibility and acute toxicity. Radiat Oncol 2011;6:102–107.
364. Engels B, Tournel K, Everaert H, et al. Phase II study of preoperative helical tomotherapy with a simultaneous integrated boost for rectal cancer. Int J Radiat Oncol Biol Phys 2012;83(1):142–148.
365. Marnitz S, Kohler C, Burova E, et al. Helical tomotherapy with simultaneous integrated boost after laparoscopic staging in patients with cervical cancer: analysis of feasibility and early toxicity. Int J Radiat Oncol Biol Phys2012;82:e137–e143.
366. Longobardi B, Berardi G, Fiorino C, et al. Anatomical and clinical predictors of acute bowel toxicity in whole pelvic irradiation for prostate cancer with tomotherapy. Radiother Oncol 2011;101:460–464.
367. Wong JYC, Rosenthal K, Liu A, et al. Image guided total marrow irradiation (TMI) using helical tomotherapy in patients with multiple myeloma and acute leukemia undergoing hematopoietic cell transplantation. Int J Radiat Oncol Biol Phys 2009;73:273–279.
368. Jaffray DA. Emergent technologies for 3-dimensional image-guided radiation delivery. Sem Radiat Oncol 2005;15:208–216.
369. Feldkamp LA, Davis LC, Kress JW. Practical cone-beam algorithm. J Opt Soc Am A 1984;1:612–619.
370. Morin O, Gillis A, Chen J, et al. Megavoltage cone-beam CT: system description and clinical applications. Med Dosim 2006;31:51–61.
371. Mosleh-Shirazi MA, Evans PM, Swindell W, et al. A cone-beam megavoltage CT scanner for treatment verification in conformal radiotherapy. Radiother Oncol 1998;48:319–328.
372. Ford EC, Chang J, Mueller K, et al. Cone-beam CT with megavoltage beams and an amorphous silicon electronic portal imaging device: potential for verification of radiotherapy of lung cancer. Med Phys 2002;29:2913–2934.
373. Sidhu K, Ford EC, Spirou S, et al. Optimization of conformal thoracic radiotherapy using cone-beam CT imaging for treatment verification. Int J Radiat Oncol Biol Phys 2003;55:757–767.
374. Pouliot J, Bani-Hashemi A, Chen J, et al. Low-dose megavoltage cone-beam CT for radiation therapy. Int J Radiat Oncol Biol Phys 2005;61(2):552–650.
375. Bylund KC, Bayouth JE, Smith MC, et al. Analysis of interfraction prostate motion using megavoltage cone beam computed tomography. Int J Radiat Oncol Biol Phys 2008;72:949–956.
376. Nakamura N, Shikama N, Takahashi O, et al. Variability in bladder volumes of full bladders in definitive radiotherapy for cases of localized prostate cancer. Strahlenther Onkol 2010;186:637–642.
377. Aubin M, Morin O, Chen J, et al. The use of megavoltage cone-beam CT to complement CT for target definition in pelvic radiotherapy in the presence of hip replacement. Br J Radiol 2006;79:918–921.
378. Sorensen SP, Chow PE, Kriminiski S, et al. Image-guided radiotherapy using a mobile kilovoltage x-ray device. Med Dosim 2006;31:40–50.
379. Swamy K, Sathiya Narayanan VK, Basu S, et al. Dose escalation in image-guided, intensity-modulated radiotherapy of carcinoma prostate: initial experience in India. J Cancer Res Ther 2009;5(4):277–283.
380. Sorensen S, Mitschke M, Solberg T. Cone-beam CT using a mobile C-arm: a registration solution for IGRT with an optical tracking system. Phys Med Biol 2007;52:3389–3404.
381. Kriminiski S, Mitschke M, Sorensen S, et al. Respiratory correlated cone-beam computed tomography on an isocentric c-arm. Phys Med Biol 2005;50:5263–5280.
382. Siewerdsen JH, Moseley DJ, Burch S, et al. Volume CT with a flat-panel detector on a mobile, isocentric C-arm: pre-clinical investigation in guidance of minimally invasive surgery. Med Phys2005;32:241–254.
383. Rafferty MA, Siewerdsen JH, Chan Y, et al. Investigation of C-arm cone-beam CT-guided surgery of the frontal recess. Laryngosope 2005;115:2138–2143.
384. Letourneau D, Wong JW, Oldham M, et al. Cone-beam-CT guided radiation therapy: technical implementation. Radiother Oncol 2005;75:279–286.
385. Sykes JR, Amer A, Czjka J, et al. A feasibility study for image guided radiotherapy using low dose, high speed, cone beam x-ray volumetric imaging. Radiother Oncol 2005;77:45–52.
386. Thilmann C, Nill S, Tucking T, et al. Correction of patient positioning errors based on in-line cone beam CTs: clinical implementation and first experiences. Radiat Oncol 2006;1:16–21.
387. Oelfke U, Tucking T, Nill S, et al. Linac-integrated kv-cone beam CT: technical features and first applications. Med Dosim 2006;31:62–70.
388. Oldham M, Letourneau D, Watt L, et al. Cone-beam-CT guided radiation therapy: a model for on-line application. Radiother Oncol 2005;75:271–278.
389. Letourneau D, Martinez AA, Lockman D, et al. Assessment of residual error for online cone-beam XT-guided treatment of prostate cancer patients. Int J Radiat Oncol Biol Phys 2005;62:1239–1246.
390. McBain CA, Henry AM, Sykes J, et al. X-ray volumetric imaging in image-guided radiotherapy: the new standard in on-treatment imaging. Int J Radiat Oncol Biol Phys 2006;64:625–634.
391. Guckenberg M, Meyer J, Vordermark D, et al. Magnitude and clinical relevance of translational and rotational patient setup errors: a cone-beam CT study. Int J Radiat Oncol Biol Phys 2006;65:934–942.
392. Henry AM, Stratford J, McCarthy C, et al. X-ray volume imaging in bladder radiotherapy verification. Int J Radiat Oncol Biol Phys 2006;64:1174–1178.
393. Ho KF, Marchant T, Moore C, et al. Monitoring dosimetric impact of weight loss with kilovoltage (kV) cone beam CT (CBCT) during parotid-sparing IMRT and concurrent chemotherapy. Int J Radiat Oncol Biol Phys2012;82:e375–e382.
394. Masi L, Casamassima F, Menichelli C, et al. On-line image guidance for frameless stereotactic radiotherapy of lung malignancies by cone beam CT: comparison between target localization and alignment on bony anatomy. Acta Oncol 2008;47:1422–1431.
395. Nazmy MS, Khafaga Y, Mousa A, et al. Cone beam CT for organ motion evaluation in pediatric abdominal neuroblastoma. Radiother Oncol 2012;102:388–392.
396. Sondergaard J, Olsen KO, Muren LP, et al. A study of image-guided radiotherapy of bladder cancer based on lipiodol injection in the bladder wall. Acta Oncol 2010;49:1109–1115.
397. Groh BA, Siewerdsen JH, Drake DG, et al. A performance comparison of flat-panel imager-based MV and KV cone-beam CT. Med Phys 2002;29:967–975.
398. Godfrey DJ, Yin FF, Oldham M, et al. Digital tomosynthesis with an on-board kilovoltage imaging device. Int J Radiat Oncol Biol Phys 2006;65:8–15.
399. Litzenberg DW. Electromagnetic tracking. In: Mundt AJ, Roeske JC, eds. Image-guided radiation therapy: a clinical perspective. Shelton, CT: People’s Medical Publishing House-USA, 2011:143–155.
400. Kupelian P, Willoughby T, Mahadevan A, et al. Multi-institutional clinical experience with the Calypso system in localization and continuous, real-time monitoring of the prostate gland during external radiotherapy. Int J Radiat Oncol Biol Phys 2007;67:1088–1098.
401. Rajendran RR, Palastaras JP, Mick R, et al. Daily isocenter correction with electromagnetic-based localization improves target coverage and rectal sparing during prostate radiotherapy. Int J Radiat Oncol Biol Phys2010;76:1092–1099.
402. Su Z, Zhang L, Murphy M, et al. Analysis of prostate patient setup and tracking data: potential intervention strategies. Int J Radiat Oncol Biol Phys 2011;81:880–887.
403. King BL, Butler WM, Merrick GS, et al. Electromagnetic transponders indicate prostate size increase followed by decrease during the course of external beam radiation therapy. Int J Radiat Oncol Biol Phys 2011;79:1350–1357.
404. Tanyi JA, He T, Summers PA, et al. Assessment of planning target volume margins for intensity-modulated radiotherapy of the prostate gland: role of daily inter- and intrafraction motion. Int J Radiat Oncol Biol Phys2010;78:1579–1585.
405. Shinohara ET, Kassaee A, Mitra N, et al. Feasibility of electromagnetic transponder use to monitor inter- and intrafractional motion in locally advanced pancreatic cancer patients. Int J Radiat Oncol Biol Phys 2012;83(2):566–573.
406. Lagendijk JJ, Raaymakers BW, Raaijmakers AJ, et al. MRI/Linac integration. Radiother Oncol 2008;86:25–29.
407. Raaymakers BW, de Boer JC, Knox C, et al. Integrated MV portal imaging with a 1.5 T MRI Linac. Phys Med Biol 2011;56:N207–N214.
408. Fallone BG, Murray B, Rathee S, et al. First MR images obtained during megavoltage photon irradiation from a prototype integrated Linac-MR system. Med Phys 2009;36:2084–2088.
409. St Aubin J, Steciw S, Fallone BG. Magnetic decoupling of the Linac in a low field biplanar Linac-MR system. Med Phys 2010;37:4755–4761.
410. St Aubin J, Santos DM, Steciw S, et al. Effect of longitudinal magnetic fields on a simulated in-line 6 MV Linac. Med Phys 2010;37:4916–4923.
411. Lamey M, Yun J, Burke B, et al. Radio frequency noise from an MLC: a feasibility study of the use of an MLC for Linac-MR systems. Phys Med Biol 2010;55:981–994.
412. Kron T, Eyles D, John SL, et al. Magnetic resonance imaging for adaptive cobalt tomotherapy: a proposal. J Med Phys 2006;31:242–254.
413. Raaijmakers AJ, Raaymakers BW, Lagendijk JJ. Magnetic-field-induced dose effects in MR-guided radiotherapy systems: dependence on the magnetic field strength. Phys Med Biol 2008;53:909–923.
414. Roper J, Bowsher J, Yin FF. On-board SPECT for localizing functional targets: a simulation study. Med Phys 2009;36:1727–1735.
415. Parodi K, Paganetti H, Shih HA, et al. Patient study of in vivo verification of beam delivery and range, using positron emission tomography and computed tomography imaging after proton therapy. Int J Radiat Oncol Biol Phys2007;68:920–934.
416. Attanasi F, Knopf A, Parodi K, et al. Extension and validation of an analytical model for in vivo PET verification of proton therapy—a phantom and clinical study. Phys Med Biol 2011;56:5079–5098.
417. Zhu X, España S, Daartz J, et al. Monitoring proton radiation therapy with in-room PET imaging. Phys Med Biol 2011;56:4041–4057.
418. Seppenwoolde Y, Shirato H, Kitamura K, et al. Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. Int J Radiat Oncol Biol Phys2002;53:822–834.
419. Vedam SS, Keall PJ, Kini VR, et al. Acquiring a four-dimensional computed tomography dataset using an external respiratory signal. Phys Med Biol 2003;48:45–62.
420. Pan T, Lee TY, Rietzel E, et al. 4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT. Med Phys 2004;31:333–340.
421. Nath SK, Sandhu AP, Kim D, et al. Locoregional and distant failure following image-guided stereotactic body radiation for early-stage primary lung cancer. Radiother Oncol 2011;99:12–17.
422. Shimizu S, Shirato H, Aoyama H, et al. High-speed magnetic resonance imaging for four-dimensional treatment planning of conformal radiotherapy of moving body tumors. Int J Radiat Oncol Biol Phys2000;48:471–474.
423. Nehmeh SA, Erdi YE. Respiratory motion in positron emission tomography/computed tomography: a review. Semin Nuc Med 2008;38:167–176.
424. Bettinardi V, Picchio M, Muzio ND, et al. Detection and compensation of organ/lesion motion using 4D-PET/CT respiratory gated acquisition techniques. Radiother Oncol 2010;96:311–316.
425. Chen GT, Kung JH, Beaudette KP. Artifacts in computed tomography scanning of moving objects. Semin Radiat Oncol 2004;14:19–26.
426. Watkins WT, Li R, Lewis J, et al. Patient-specific motion artifacts in 4DCT. Med Phys 2010;37:2855–2861.
427. Kauweloa KI, Ruan D, Park JC, et al. GateCT surface tracking system for respiratory signal reconstruction in 4DCT imaging. 2012;39:492.
428. Zhao T, Lu W, Yang D, et al. Characterization of free breathing patterns with 5D lung motion model. Med Phys 2009;36:5183–5189.
429. Otani Y, Fukuda I, Tsukamoto N, et al. A comparison of the respiratory signals acquired by different respiratory monitoring systems used in respiratory gated radiotherapy. Med Phys 2010;37:6178–6186.
430. Keall P. 4-Dimensional computed tomography imaging and treatment planning. Semin Radiat Oncol 2004;14:81–90.
431. ICRU Report 62. Prescribing, recording, and reporting photon beam therapy (supplement to ICRU Report 50). Washington, DC: ICRU, 1999.
432. Lagerwaard FJ, Van Sornsen de Koste JR, Nijssen-Visser MR, et al. Multiple “slow” CT scans for incorporating lung tumor mobility in radiotherapy planning. Int J Radiat Oncol Biol Phys 2001;51:932–937.
433. Wong JW, Sharpe MB, Jaffray DA, et al. The use of active breathing control (ABC) to reduce margin for breathing motion. Int J Radiat Oncol Biol Phys 1999;44:911–919.
434. Rietzel E, Liu AK, Doppke KP, et al. Design of 4D treatment planning target volumes. Int J Radiat Oncol Biol Phys 2006;66:287–295.
435. Underberg RW, Lagerwaard FJ, Slotman BJ, et al. Use of maximum intensity projections (MIP) for target volume generation in 4DCT scans for lung cancer. Int J Radiat Oncol Biol Phys 2005;63:253–260.
436. Muirhead R, McNee SG, Featherstone C, et al. Use of maximum intensity projections (MIPs) for target outlining in 4DCT radiotherapy planning. J Thoracic Oncol 2008;3:1433–1438.
437. Wolthaus JW, Sonke JJ, van Herk M, et al. Comparison of different strategies to use four-dimensional computed tomography in treatment planning for lung cancer patients. Int J Radiat Oncol Biol Phys2008;70:1229–1238.
438. Starkschall G, Britton K, McAleer, et al. Potential dosimetric benefits of four-dimensional radiation treatment planning. Int J Radiat Oncol Biol Phys 2009;73:1560–1565.
439. Mexner V, Wolthaus JWH, van Herk M, et al. Effects of respiration-induced density variations on dose distributions in radiotherapy of lung cancer. Int J Radiat Oncol Biol Phys 2009;74:1266–1275.
440. Li X, Wang X, Li Y, et al. A 4D IMRT planning method using deformable image registration to improve normal tissue sparing with contemporary delivery techniques. Radiat Oncol 2011;6:83.
441. Keall PJ, Mageras GS, Balter JM, et al. The management of respiratory motion in radiation oncology report of AAPM Task Group 76. 2006;33:3874–3900.
442. Rit S, Nijkamp J, van Herk M, et al. Comparative study of respiratory motion correction techniques in cone-beam computed tomography. Radiother Oncol 2011;100:356–359.
443. Park JC, Park SH, Kim JH, et al. Four-dimensional cone-beam computed tomography and digital tomosynthesis reconstructions using respiratory signals extracted from transcutaneously inserted metal markers for liver SBRT. Med Phys 2011;38:1028–1036.
444. Vergalasova I, Maurer J, Yin FF. Potential underestimation of the internal target volume (ITV) from free-breathing CBCT. Med Phys 2011;38:4689–4699.
445. Li R, Lewis JH, Cervino LI, et al. A feasibility study of markerless fluoroscopic gating for lung cancer radiotherapy using 4DCT templates. Phys Med Biol 2009;54:N489–N500.
446. Lin T, Li R, Tang X, et al. Markerless gating for lung cancer radiotherapy based on machine learning techniques. Phys Med Biol 2009;54:1555–1563.
447. Zhang T, Keller H, O’Brien MJ, et al. Application of the spirometer in respiratory gated radiotherapy. Med Phys 2003;30:3165–3171.
448. Wu H, Zhao Q, Berbeco RI, et al. Gating based on internal/external signals with dynamic correlation updates. Phys Med Biol 2008;53:7137–7150.
449. Chang Z, Liu T, Cai J, et al. Evaluation of integrated respiratory gating systems on a Novalis Tx system. J Appl Clin Med Phys 2011;12:3495.
450. Mageras GS, Yorke E. Deep inspiration breath hold and respiratory gating strategies for reducing organ motion in radiation treatment. Semin Radiat Oncol 2004;14:65–75.
451. Wong VY, Tung SY, Nq AW, et al. Real-time monitoring and control on deep inspiration breath-hold for lung cancer radiotherapy: combination of ABC and external marker tracking. Med Phys2010;37:4673–4683.
452. Eccles C, Brock KK, Bissonnette JP, et al. Reproducibility of liver position using active breathing coordinator for liver cancer radiotherapy. Int J Radiat Oncol Biol Phys 2006;64:751–759.
453. McIntosh A, Shoushtari AN, Benedict SH, et al. Quantifying the reproducibility of heart position during treatment and corresponding delivered heart dose in voluntary deep inhalation breath hold for left breast cancer patients treated with external beam radiotherapy. Int J Radiat Oncol Biol Phys 2011;81:e569–e576.
454. Peng JL, Kahler D, Li JG, et al. Characterization of a real-time surface image-guided stereotactic positioning system. Med Phys 2010;37:5421–5433.
455. Lax I, Blomgren H, Naslund I, et al. Stereotactic radiotherapy of malignancies in the abdomen: methodological aspects. Acta Oncol 1994;33:677–683.
456. Eccles CL, Patel R, Simeonov AK, et al. Comparison of liver tumor motion with and without abdominal compression using cine-magnetic resonance imaging. Int J Radiat Oncol Biol Phys 2011;79:602–608.
457. Han K, Cheugn P, Basran PS, et al. A comparison of two immobilization systems for stereotactic body radiation therapy of lung tumors. Radiother Oncol 2010;95:103–108.
458. Jiang SB. Radiotherapy of mobile tumors. Semin Radiat Oncol 2006;16:239–248.
459. Neicu T, Berbeco R, Wolfgang J, et al. Synchronized moving aperture radiation therapy (SMART): improvement of breathing pattern reproducibility using respiratory coaching. Phys Med Biol2006;51:617–636.
460. Neicu T, Shirato H, Seppenwoolde Y, et al. Synchronized moving aperture radiation therapy (SMART): average tumour trajectory for lung patients. Phys Med Biol 2003;48:587–598.
461. Hoogeman M, Prevost JB, Nuyttens J, et al. Clinical accuracy of the respiratory tumor tracking system of the Cyber Knife: assessment by analysis of log files. Int J Radiat Oncol Biol Phys 2009;74:297–303.
462. Wiersma RD, Mao W, Xing L. Combined kV and MV imaging for real-time tracking of implanted fiducial markers. Med Phys 2008;35:1191–1198.
463. Davies GA, Poludniowski G, Webb S. MLC tracking for Elekta VMAT: a modeling study. Phys Med Biol 2011;56:7541–7554.
464. Fledellius W, Keall PJ, Cho B, et al. Tracking latency in image-based dynamic MLC tracking with direct image access. Acta Oncol 2011;50:952–959.
465. Ravkilde T, Keall PJ, Hojbjerre K, et al. Geometric accuracy of dynamic MLC tracking with an implantable wired electromagnetic transponder. Acta Oncol 2011;50:944–951.
466. Depuvdt T, Verellen D, Haas O, et al. Geometric accuracy of a novel gimbals based radiation therapy tumor tracking system. Radiother Oncol 2011;98:365–372.
467. Sawant A, Dieterich S, Svatos M, et al. Failure mode and effect analysis-based quality assurance for dynamic MLC tracking systems. Med Phys 2010;37:6466–6479.
468. Poulsen PR, Cho B, Sawant A, et al. Detailed analysis of latencies in image-based dynamic MLC tracking. Med Phys 2010;37:4998–5005.
469. Poulsen PR, Cho B, Sawant A, et al. Dynamic MLC tracking of moving targets with a single kV imager for 3D conformal and IMRT treatments. Acta Oncol 2010;49:1092–1100.
470. Krauss A, Nill S, Tacke M, et al. Electromagnetic real-time tumor position monitoring and dynamic multileaf collimator tracking using a Siemens 160 MLC: geometric and dosimetric accuracy of an integrated system. Int J Radiat Oncol Biol Phys 2011;79:579–587.
471. Han-Oh S, Yi BY, Lerma F, et al. Verification of MLC based real-time tumor tracking using an electronic portal imaging device. Med Phys 2010;37:2435–2440.
472. Cerviño LI, Du J, Jiang SB. MRI-guided tumor tracking in lung cancer radiotherapy. Phys Med Biol 2011;56:3773–3785.
473. Keall PJ, Sawant A, Cho B, et al. Electromagnetic-guided dynamic multileaf collimator tracking enables motion management for intensity-modulated arc therapy. Int J Radiat Oncol Biol Phys2011;79:312–320.
474. Yan D, Vicini F, Wong J, et al. Adaptive radiation therapy. Phys Med Biol 1997;42:123–132.
475. Jaffray DA, Siewerdsen JH. Cone-beam computed tomography with a flat-panel imager: initial performance characterization. Med Phys 2000;27:1311–1323.
476. Song WY, Schaly B, Bauman G, et al. Image-guided adaptive radiation therapy (IGART): radiobiological and dose escalation considerations for localized carcinoma of the prostate. Med Phys2005;32:2193–2203.
477. Vargas C, Yan D, Kestin LL, et al. Phase II dose escalation study of image-guided adaptive radiotherapy for prostate cancer: use of dose-volume constraints to achieve rectal isotoxocity. Int J Radiat Oncol Biol Phys2005;62:141–149.
478. Brabbins D, Martinez A, Yan D, et al. A dose-escalation trial with the adaptive radiotherapy process as a delivery system in localized prostate cancer: analysis of chronic toxicity. Int J Radiat Oncol Biol Phys 2005;61:400–408.
479. Deutschmann H, Kametriser G, Steininger P, et al. First clinical release of an online, adaptive, aperture-based image-guided radiotherapy strategy in intensity-modulated radiotherapy to correct for inter- and intrafractional rotations of the prostate. Int J Radiat Oncol Biol Phys 2012;83(5):1624–1632.
480. Barker JL, Garden AS, Ang KK, et al. Quantification of volumetric and geometric changes during fractionated radiotherapy for head-and-neck cancer using an integrated CT/linear accelerator system. Int J Radiat Oncol Biol Phys 2004;59:960–970.
481. Hansen EK, Bucci MK, Quivey JM, et al. Repeat CT imaging and re-planning during the course of IMRT for head-and-neck cancer. Int J Radiat Oncol Biol Phys 2006;64:355–362.
482. Kupelian PA, Ramsey C, Meeks SL, et al. Serial megavoltage CT imaging during external beam radiotherapy for non-small-cell lung cancer: observations on tumor regression during treatment. Int J Radiat Oncol Biol Phys2005;63:1024–1028.
483. Riegel AC, Berson AM, Destian S, et al. Variability of gross tumor volume delineation in head-and-neck cancer using CT and PET/CT fusion. Int J Radiat Oncol Biol Phys 2006;65:726-732.
484. Van de Bunt L, van der Heided UA, Ketelaars M, et al. Conventional, conformal and intensity modulated radiation therapy treatment planning of external beam radiotherapy for cervical cancer: the impact of tumor regression. Int J Radiat Oncol Biol Phys 2006;64:189–196.
485. Ramsey CR, Langen KM, Kupelian PA, et al. A technique for adaptive image-guided helical tomotherapy for lung cancer. Int J Radiat Oncol Biol Phys 2006;64:1237–1244.
486. Wieder HA, Brucher BL, Zimmermann F, et al. Time course of tumor metabolic activity during chemoradiotherapy of esophageal squamous cell carcinoma and response to treatment. J Clin Oncol2004;22:900–908.
487. Gu X, Choi DJ, Men C, et al. GPU-based ultra-fast dose calculation using a finite pencil beam model. Phys Med Biol 2009;54:6287–6297.
488. Men C, Gu X, Choi DJ, et al. GPU-based ultrafast IMRT plan optimization. Phys Med Biol 2009;54:6565–6573.
489. Gu X, Pan H, Liang Y, et al. Implementation and evaluation of various demons deformable image registration algorithms on a GPU. Phys Med Biol 2009;55:207–219.
490. Jia X, Lou Y, Li R, et al. GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation. Med Phys 2010;37:1757–1760.
491. Jia X, Gu X, Sempau J, et al. Development of a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport. Phys Med Biol 2010;55:3077–3086.
492. Men C, Jia X, Jiang SB. GPU-based ultra-fast direct aperture optimization for online adaptive radiation therapy. Phys Med Biol 2010;55:4309–4319.
493. Gu X, Jelen U, Li J, et al. A GPU-based finite-size pencil beam algorithm with 3D-density correction for radiotherapy dose calculation. Phys Med Biol 2011;56:3337–3350.
494. Park JC, Park SH, Kim JS, et al. Ultra-fast digital tomosynthesis reconstruction using general purpose GPU programming for image-guided radiation therapy. Tech Cancer Res Treat 2011;10:295–306.
495. Jia X, Gu X, Jiang Y, et al. GPU-based fast Monte Carlo simulation for radiotherapy dose calculation. Phys Med Biol 2011;56:7017–7031.
496. Meng B, Pratx G, Xing L. Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment. Med Phys 2011;38:6603–6609.
497. Wang H, Ma Y, Pratx G, et al. Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure. Phys Med Biol 2011;56:N175–N181.