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The use of positron emission tomography (PET) in radiation therapy (RT) is rapidly increasing in the areas of staging, segmentation, treatment planning, and response assessment. The most common radiotracer is 18 F-fluorodeoxyglucose ([ 18 F]FDG), a glucose analog with demonstrated efficacy in cancer diagnosis and staging. However, diagnosis and RT planning are different endeavors with unique requirements, and very little literature is available for guiding physicists and clinicians in the utilization of [ 18 F]FDG-PET in RT. The two goals of this report are to educate and provide recommendations. The report provides background and education on current PET imaging systems, PET tracers, intensity quantification, and current utilization in RT (staging, segmentation, image registration, treatment planning, and therapy response assessment). Recommendations are provided on acceptance testing, annual and monthly quality assurance, scanning protocols to ensure consistency between interpatient scans and intrapatient longitudinal scans, reporting of patient and scan parameters in literature, requirements for incorporation of [ 18 F]FDG-PET in treatment planning systems, and image registration. The recommendations provided here are minimum requirements and are not meant to cover all aspects of the use of [ 18 F]FDG-PET for RT., (© 2019 American Association of Physicists in Medicine.)

Purpose: To develop an automated optimization program to generate optimal beam settings for whole-breast radiation therapy driven by clinically oriented goals., Materials and Methods: Forty patients were retrospectively included in this study. Each patient's planning images, contoured structures of planning target volumes, organs-at-risk, and breast wires were used to optimize for patient-specific-beam settings. Two beam geometries were available tangential beams only and tangential plus supraclavicular beams. Beam parameters included isocenter position, gantry, collimator, couch angles, and multileaf collimator shape. A geometry-based goal function was defined to determine such beam parameters to minimize out-of-field target volume and in-field ipsilateral lung volume. For each geometry, the weighting in the goal function was trained with 10 plans and tested on 10 additional plans. For each query patient, the optimal beam setting was searched for different gantry-isocenter pairs. Optimal fluence maps were generated by an in-house automatic fluence optimization program for target coverage and homogeneous dose distribution, and dose calculation was performed in Eclipse. Automatically generated plans were compared with manually generated plans for target coverage and lung and heart sparing., Results: The program successfully produced a set of beam parameters for every patient. Beam optimization time ranged from 10 to 120 s. The automatic plans had overall comparable plan quality to manually generated plans. For all testing cases, the mean target V 95% was 91.0% for the automatic plans and 88.5% for manually generated plans. The mean ipsilateral lung V 20Gy was lower for the automatic plans (15.2% vs 17.9%). The heart mean dose, maximum dose of the body, and conformity index were all comparable., Conclusion: We developed an automated goal-driven beam setting optimization program for whole-breast radiation therapy. It provides clinically relevant solutions based on previous clinical practice as well as patient specific anatomy on a substantially faster time frame.

Purpose: To construct a robotic SPECT system and to demonstrate its capability to image a thorax phantom on a radiation therapy flat-top couch, as a step toward onboard functional and molecular imaging in radiation therapy., Methods: A robotic SPECT imaging system was constructed utilizing a gamma camera detector (Digirad 2020tc) and a robot (KUKA KR150 L110 robot). An imaging study was performed with a phantom (PET CT Phantom(TM)), which includes five spheres of 10, 13, 17, 22, and 28 mm diameters. The phantom was placed on a flat-top couch. SPECT projections were acquired either with a parallel-hole collimator or a single-pinhole collimator, both without background in the phantom and with background at 1/10th the sphere activity concentration. The imaging trajectories of parallel-hole and pinhole collimated detectors spanned 180° and 228°, respectively. The pinhole detector viewed an off-centered spherical common volume which encompassed the 28 and 22 mm spheres. The common volume for parallel-hole system was centered at the phantom which encompassed all five spheres in the phantom. The maneuverability of the robotic system was tested by navigating the detector to trace the phantom and flat-top table while avoiding collision and maintaining the closest possible proximity to the common volume. The robot base and tool coordinates were used for image reconstruction., Results: The robotic SPECT system was able to maneuver parallel-hole and pinhole collimated SPECT detectors in close proximity to the phantom, minimizing impact of the flat-top couch on detector radius of rotation. Without background, all five spheres were visible in the reconstructed parallel-hole image, while four spheres, all except the smallest one, were visible in the reconstructed pinhole image. With background, three spheres of 17, 22, and 28 mm diameters were readily observed with the parallel-hole imaging, and the targeted spheres (22 and 28 mm diameters) were readily observed in the pinhole region-of-interest imaging., Conclusions: Onboard SPECT could be achieved by a robot maneuvering a SPECT detector about patients in position for radiation therapy on a flat-top couch. The robot inherent coordinate frames could be an effective means to estimate detector pose for use in SPECT image reconstruction.

In this article, the application of radiotherapy, alone and in combination with surgery and chemotherapy, in the treatment of metastases to the brain (the most common malignant brain lesion), primary malignant gliomas (the most common malignant primary brain tumor), and metastases to the osseous spine is reviewed. Brain metastases may be treated with surgical resection, whole-brain radiotherapy, stereotactic radiosurgery, or some combination of these treatments. The optimum treatment of brain metastases is a matter of controversy, and patient and disease factors favoring one approach over another are presented., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Introduction: The mechanisms of radiation-induced erectile dysfunction (ED) are unclear, as clinical studies are limited, and previous animal models were based on wide-field irradiation, which does not model current radiotherapy (RT) techniques., Aims: To perform functional and morphological analyses of erectile function (EF) utilizing image-guided stereotactic prostate-confined RT in a rat model., Methods: Sixty young adult male rats aged 10-12 weeks old were divided into age-matched sham and RT groups. A single 20-Gy fraction to the prostate was delivered to RT animals. Penile bulb, shaft, and testes were excluded from treatment fields., Main Outcome Measures: Bioassay and intracavernous pressure (ICP) measurements were conducted at 2, 4, and 9 weeks following RT. Perfusion analysis of the corpora cavernosa (CC) was conducted using Hoechst injected prior to sacrifice. Penile shaft and cavernous nerve (CN) were evaluated by immunohistochemistry. Plasma testosterone level was analyzed using a testosterone enzyme-linked immunosorbent assay (ELISA) assay kit., Results: Irradiated animals demonstrated statistically significant time-dependent functional impairment of EF by bioassay and ICP measurement from 4 weeks. Neuronal nitric oxide synthase (NOS) expression was decreased in CN by 4 weeks. In CC, expression levels of anti-alpha smooth muscle actin and endothelial NOS were significantly decreased at 9 weeks. In penile dorsal vessels, smooth muscle/collagen ratio was significantly decreased at 4 and 9 weeks. Additionally, Hoechst perfusion showed time-dependent decrease in CC of RT animals, whereas CD31 expression was not affected. No toxicities were noted; testosterone levels were similar in both groups., Conclusion: We demonstrated time-dependent ED following image-guided stereotactic RT. Our results imply that reduction of neuronal NOS expression in cavernous nerve could trigger consecutive reduction of smooth muscle content as well as blood perfusion in CC that resulted in corporal veno-occlusive dysfunction. Present study could be a cornerstone to future research that may bring comprehensive scientific understanding of radiation-induced ED., (© 2011 International Society for Sexual Medicine.)

This paper reports an inverse arc-modulated radiation therapy planning technique based on linear models. It is implemented with a two-step procedure. First, fluence maps for 36 fixed-gantry beams are generated using a linear model-based intensity-modulated radiation therapy (IMRT) optimization algorithm. The 2D fluence maps are decomposed into 1D fluence profiles according to each leaf pair position. Second, a mixed integer linear model is used to construct the leaf motions of an arc delivery that reproduce the 1D fluence profile previously derived from the static gantry IMRT optimization. The multi-leaf collimator (MLC) sequence takes into account the starting and ending leaf positions in between the neighbouring apertures, such that the MLC segments of the entire treatment plan are deliverable in a continuous arc. Since both steps in the algorithm use linear models, implementation is simple and straightforward. Details of the algorithm are presented, and its conceptual correctness is verified with clinical cases representing prostate and head-and-neck treatments.

Purpose: To assess the impact of new technologies on deviation rates in radiation therapy (RT)., Methods and Materials: Treatment delivery deviations in RT were prospectively monitored during a time of technology upgrade. In January 2003, our department had three accelerators, none with "modern" technologies (e.g., without multileaf collimators [MLC]). In 2003 to 2004, we upgraded to five new accelerators, four with MLC, and associated advanced capabilities. The deviation rates among patients treated on "high-technology" versus "low-technology" machines (defined as those with vs. without MLC) were compared over time using the two-tailed Fisher's exact test., Results: In 2003, there was no significant difference between the deviation rate in the "high-technology" versus "low-technology" groups (0.16% vs. 0.11%, p = 0.45). In 2005 to 2006, the deviation rate for the "high-technology" groups was lower than the "low-technology" (0.083% vs. 0.21%, p = 0.009). This difference was caused by a decline in deviations on the "high-technology" machines over time (p = 0.053), as well as an unexpected trend toward an increase in deviations over time on the "low-technology" machines (p = 0.15)., Conclusions: Advances in RT delivery systems appear to reduce the rate of treatment deviations. Deviation rates on "high-technology" machines with MLC decline over time, suggesting a learning curve after the introduction of new technologies. Associated with the adoption of "high-technology" was an unexpected increase in the deviation rate with "low-technology" approaches, which may reflect an over-reliance on tools inherent to "high-technology" machines. With the introduction of new technologies, continued diligence is needed to ensure that staff remain proficient with "low-technology" approaches.

PurposeTo develop a method of biologically guided deep learning for post-radiation 18FDG-PET image outcome prediction based on pre-radiation images and radiotherapy dose information.MethodsBased on the classic reaction-diffusion mechanism, a novel biological model was proposed using a partial differential equation that incorporates spatial radiation dose distribution as a patient-specific treatment information variable. A 7-layer encoder-decoder-based convolutional neural network (CNN) was designed and trained to learn the proposed biological model. As such, the model could generate post-radiation 18FDG-PET image outcome predictions with breakdown biological components for enhanced explainability. The proposed method was developed using 64 oropharyngeal patients with paired 18FDG-PET studies before and after 20-Gy delivery (2 Gy/day fraction) by intensity-modulated radiotherapy (IMRT). In a two-branch deep learning execution, the proposed CNN learns specific terms in the biological model from paired 18FDG-PET images and spatial dose distribution in one branch, and the biological model generates post-20-Gy 18FDG-PET image prediction in the other branch. As in 2D execution, 718/233/230 axial slices from 38/13/13 patients were used for training/validation/independent test. The prediction image results in test cases were compared with the ground-truth results quantitatively.ResultsThe proposed method successfully generated post-20-Gy 18FDG-PET image outcome prediction with breakdown illustrations of biological model components. Standardized uptake value (SUV) mean values in 18FDG high-uptake regions of predicted images (2.45 ± 0.25) were similar to ground-truth results (2.51 ± 0.33). In 2D-based Gamma analysis, the median/mean Gamma Index (

PurposeTo assess stereotactic radiotherapy (SRT)/stereotactic body radiotherapy (SBRT) practices by polling clinics participating in multi-institutional clinical trials.MethodsThe NRG Oncology Medical Physics Subcommittee distributed a survey consisting of 23 questions, which covered general technologies, policies, and procedures used in the Radiation Oncology field for the delivery of SRT/SBRT (9 questions), and site-specific questions for brain SRT, lung SBRT, and prostate SBRT (14 questions). Surveys were distributed to 1,996 radiotherapy institutions included on the membership rosters of the five National Clinical Trials Network (NCTN) groups. Patient setup, motion management, target localization, prescriptions, and treatment delivery technique data were reported back by 568 institutions (28%).Results97.5% of respondents treat lung SBRT patients, 77.0% perform brain SRT, and 29.1% deliver prostate SBRT. 48.8% of clinics require a physicist present for every fraction of SBRT, 18.5% require a physicist present for the initial SBRT fraction only, and 14.9% require a physicist present for the entire first fraction, including set-up approval for all subsequent fractions. 55.3% require physician approval for all fractions, and 86.7% do not reposition without x-ray imaging. For brain SRT, most institutions (83.9%) use a planning target volume (PTV) margin of 2 mm or less. Lung SBRT PTV margins of 3 mm or more are used in 80.6% of clinics. Volumetric modulated arc therapy (VMAT) is the dominant delivery method in 62.8% of SRT treatments, 70.9% of lung SBRT, and 68.3% of prostate SBRT.ConclusionThis report characterizes SRT/SBRT practices in radiotherapy clinics participating in clinical trials. Data made available here allows the radiotherapy community to compare their practice with that of other clinics, determine what is achievable, and assess areas for improvement.

Objective: Despite its prevalence, cone beam computed tomography (CBCT) has poor soft‐tissue contrast, making it challenging to localize liver tumors. We propose a patient‐specific deep learning model to generate synthetic magnetic resonance imaging (MRI) from CBCT to improve tumor localization. Methods: A key innovation is using patient‐specific CBCT‐MRI image pairs to train a deep learning model to generate synthetic MRI from CBCT. Specifically, patient planning CT was deformably registered to prior MRI, and then used to simulate CBCT with simulated projections and Feldkamp, Davis, and Kress reconstruction. These CBCT‐MRI images were augmented using translations and rotations to generate enough patient‐specific training data. A U‐Net‐based deep learning model was developed and trained to generate synthetic MRI from CBCT in the liver, and then tested on a different CBCT dataset. Synthetic MRIs were quantitatively evaluated against ground‐truth MRI. Results: The synthetic MRI demonstrated superb soft‐tissue contrast with clear tumor visualization. On average, the synthetic MRI achieved 28.01, 0.025, and 0.929 for peak signal‐to‐noise ratio, mean square error, and structural similarity index, respectively, outperforming CBCT images. The model performance was consistent across all three patients tested. Conclusion: Our study demonstrated the feasibility of a patient‐specific model to generate synthetic MRI from CBCT for liver tumor localization, opening up a potential to democratize MRI guidance in clinics with conventional LINACs. [ABSTRACT FROM AUTHOR]

The charges on this task group (TG) were as follows: (a) provide specific procedural guidelines for performing the tests recommended in TG 142; (b) provide estimate of the range of time, appropriate personnel, and qualifications necessary to complete the tests in TG 142; and (c) provide sample daily, weekly, monthly, or annual quality assurance (QA) forms. Many of the guidelines in this report are drawn from the literature and are included in the references. When literature was not available, specific test methods reflect the experiences of the TG members (e.g., a test method for door interlock is self‐evident with no literature necessary). In other cases, the technology is so new that no literature for test methods was available. Given broad clinical adaptation of volumetric modulated arc therapy (VMAT), which is not a specific topic of TG 142, several tests and criteria specific to VMAT were added. [ABSTRACT FROM AUTHOR]

Background and purpose: The efficacy of clinical trials and the outcome of patient treatment are dependent on the quality assurance (QA) of radiation therapy (RT) plans. There are two widely utilized approaches that include plan optimization guidance created based on patient‐specific anatomy. This study examined these two techniques for dose‐volume histogram predictions, RT plan optimizations, and prospective QA processes, namely the knowledge‐based planning (KBP) technique and another first principle (FP) technique. Methods: This analysis included 60, 44, and 10 RT plans from three Radiation Therapy Oncology Group (RTOG) multi‐institutional trials: RTOG 0631 (Spine SRS), RTOG 1308 (NSCLC), and RTOG 0522 (H&N), respectively. Both approaches were compared in terms of dose prediction and plan optimization. The dose predictions were also compared to the original plan submitted to the trials for the QA procedure. Results: For the RTOG 0631 (Spine SRS) and RTOG 0522 (H&N) plans, the dose predictions from both techniques have correlation coefficients of >0.9. The RT plans that were re‐optimized based on the predictions from both techniques showed similar quality, with no statistically significant differences in target coverage or organ‐at‐risk sparing. The predictions of mean lung and heart doses from both methods for RTOG1308 patients, on the other hand, have a discrepancy of up to 14 Gy. Conclusions: Both methods are valuable tools for optimization guidance of RT plans for Spine SRS and Head and Neck cases, as well as for QA purposes. On the other hand, the findings suggest that KBP may be more feasible in the case of inoperable lung cancer patients who are treated with IMRT plans that have spatially unevenly distributed beam angles. [ABSTRACT FROM AUTHOR]

The use of positron emission tomography (PET) in radiation therapy (RT) is rapidly increasing in the areas of staging, segmentation, treatment planning, and response assessment. The most common radiotracer is 18F‐fluorodeoxyglucose ([18F]FDG), a glucose analog with demonstrated efficacy in cancer diagnosis and staging. However, diagnosis and RT planning are different endeavors with unique requirements, and very little literature is available for guiding physicists and clinicians in the utilization of [18F]FDG‐PET in RT. The two goals of this report are to educate and provide recommendations. The report provides background and education on current PET imaging systems, PET tracers, intensity quantification, and current utilization in RT (staging, segmentation, image registration, treatment planning, and therapy response assessment). Recommendations are provided on acceptance testing, annual and monthly quality assurance, scanning protocols to ensure consistency between interpatient scans and intrapatient longitudinal scans, reporting of patient and scan parameters in literature, requirements for incorporation of [18F]FDG‐PET in treatment planning systems, and image registration. The recommendations provided here are minimum requirements and are not meant to cover all aspects of the use of [18F]FDG‐PET for RT. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to develop an accurate and reliable dose volume histogram (DVH) prediction method for external beam radiation therapy plans with multiple planning target volumes (PTVs). Materials and methods: We present a novel DVH prediction workflow, including new features and a modeling methodology, that makes better use of multiple PTVs: (a) We propose a generalized feature to characterize the geometric relationship of organ‐at‐risk (OARs) with respect to two or more PTVs with different prescribed dose levels; (b) We incorporate a novel data augmentation method to improve the data distribution in the feature space; (c) A similarity metric that leverages such information is subsequently used to select a subset of similar cases from the training dataset for model building; (d) Finally, a DVH prediction model is trained with these selected cases. To evaluate this new modeling workflow, we used 120 head and neck (HN) cases to tune the model, and used a separate dataset consisting of 148 cases for validation. The proposed model has been compared with the conventional knowledge‐based model in terms of model prediction accuracy, which was measured by the root mean squared error (RMSE) between the predicted DVHs and the actual clinical plan DVHs. Furthermore, 25 randomly selected plans were replanned guided by the proposed model and evaluated against clinical plans using clinical evaluation criteria. Results: The proposed modeling workflow significantly improved DVH prediction accuracy for brainstem (P < 0.001), cord (P < 0.001), larynx (P = 0.004), mandible (P < 0.001), oral cavity (P = 0.011), parotid (P < 0.001) and pharynx (P = 0.001). Cases replanned with the guidance of the proposed model spared OARs significantly better by clinical evaluation criteria. The replanned cases showed a 15% increase in the number of satisfied criteria, compared with clinical plans. Conclusions: The proposed modeling workflow generates DVH predictions with improved accuracy and robustness when multiple PTVs exist in a plan. It has demonstrated that the improvement in the DVH prediction model translates into better plan quality in knowledge‐based planning. [ABSTRACT FROM AUTHOR]

Introduction: Stereotactic radiosurgery (SRS) is a promising treatment option for patients with multiple brain metastases (BM). Recent technical advances have made LINAC based SRS a patient friendly technique, allowing for accurate patient positioning and a short treatment time. Since SRS is increasingly being used for patients with multiple BM, it remains essential that SRS be performed with the highest achievable quality in order to prevent unnecessary complications such as radionecrosis. The purpose of this article is to provide guidance for high-quality LINAC based SRS for patients with BM, with a focus on single isocenter non-coplanar volumetric modulated arc therapy (VMAT). Methods: The article is based on a consensus statement by the study coordinators and medical physicists of four trials which investigated whether patients with multiple BM are better palliated with SRS instead of whole brain radiotherapy (WBRT): A European trial (NCT02353000), two American trials and a Canadian CCTG lead intergroup trial (CE.7). This manuscript summarizes the quality assurance measures concerning imaging, planning and delivery. Results: To optimize the treatment, the interval between the planning-MRI (gadolinium contrast-enhanced, maximum slice thickness of 1.5 mm) and treatment should be kept as short as possible (< two weeks). The BM are contoured based on the planning-MRI, fused with the planning-CT. GTV-PTV margins are minimized or even avoided when possible. To maximize efficiency, the preferable technique is single isocenter (non-)coplanar VMAT, which delivers high doses to the target with maximal sparing of the organs at risk. The use of flattening filter free photon beams ensures a lower peripheral dose and shortens the treatment time. To bench mark SRS treatment plan quality, it is advisable to compare treatment plans between hospitals. Conclusion: This paper provides guidance for quality assurance and optimization of treatment delivery for LINAC-based radiosurgery for patients with multiple BM. [ABSTRACT FROM AUTHOR]

Purpose: To develop an automatic treatment planning system for whole breast radiation therapy (WBRT) based on two intensity-modulated tangential fields, enabling near-real-time planning. Methods and Materials: A total of 40 WBRT plans from a single institution were included in this study under IRB approval. Twenty WBRT plans, 10 with single energy (SE, 6MV) and 10 with mixed energy (ME, 6/15MV), were randomly selected as training dataset to develop the methodology for automatic planning. The rest 10 SE cases and 10 ME cases served as validation. The auto-planning process consists of three steps. First, an energy prediction model was developed to automate energy selection. This model establishes an anatomy-energy relationship based on principle component analysis (PCA) of the gray level histograms from training cases' digitally reconstructed radiographs (DRRs). Second, a random forest (RF) model generates an initial fluence map using the selected energies. Third, the balance of overall dose contribution throughout the breast tissue is realized by automatically selecting anchor points and applying centrality correction. The proposed method was tested on the validation dataset. Non-parametric equivalence test was performed for plan quality metrics using one-sided Wilcoxon Signed-Rank test. Results: For validation, the auto-planning system suggested same energy choices as clinical-plans in 19 out of 20 cases. The mean (standard deviation, SD) of percent target volume covered by 100% prescription dose was 82.5% (4.2%) for auto-plans, and 79.3% (4.8%) for clinical-plans (p > 0.999). Mean (SD) volume receiving 105% Rx were 95.2 cc (90.7 cc) for auto-plans and 83.9 cc (87.2 cc) for clinical-plans (p = 0.108). Optimization time for auto-plan was <20 s while clinical manual planning takes between 30 min and 4 h. Conclusions: We developed an automatic treatment planning system that generates WBRT plans with optimal energy selection, clinically comparable plan quality, and significant reduction in planning time, allowing for near-real-time planning. [ABSTRACT FROM AUTHOR]

Purpose: On‐board MRI can provide superb soft tissue contrast for improving liver SBRT localization. However, the availability of on‐board MRI in clinics is extremely limited. On the contrary, on‐board kV imaging systems are widely available on radiotherapy machines, but its capability to localize tumors in soft tissue is limited due to its poor soft tissue contrast. This study aims to explore the feasibility of using an on‐board kV imaging system and patient prior knowledge to generate on‐board four‐dimensional (4D)‐MRI for target localization in liver SBRT. Methods: Prior 4D MRI volumes were separated into end of expiration (EOE) phase (MRIprior) and all other phases. MRIprior was used to generate a synthetic CT at EOE phase (sCTprior). On‐board 4D MRI at each respiratory phase was considered a deformation of MRIprior. The deformation field map (DFM) was estimated by matching DRRs of the deformed sCTprior to on‐board kV projections using a motion modeling and free‐form deformation optimization algorithm. The on‐board 4D MRI method was evaluated using both XCAT simulation and real patient data. The accuracy of the estimated on‐board 4D MRI was quantitatively evaluated using Volume Percent Difference (VPD), Volume Dice Coefficient (VDC), and Center of Mass Shift (COMS). Effects of scan angle and number of projections were also evaluated. Results: In the XCAT study, VPD/VDC/COMS among all XCAT scenarios were 10.16 ± 1.31%/0.95 ± 0.01/0.88 ± 0.15 mm using orthogonal‐view 30° scan angles with 102 projections. The on‐board 4D MRI method was robust against the various scan angles and projection numbers evaluated. In the patient study, estimated on‐board 4D MRI was generated successfully when compared to the “reference on‐board 4D MRI” for the liver patient case. Conclusions: A method was developed to generate on‐board 4D MRI using prior 4D MRI and on‐board limited kV projections. Preliminary results demonstrated the potential for MRI‐based image guidance for liver SBRT using only a kV imaging system on a conventional LINAC. [ABSTRACT FROM AUTHOR]

Purpose: Often, the inverse deformation vector field (DVF) is needed together with the corresponding forward DVF in four‐dimesional (4D) reconstruction and dose calculation, adaptive radiation therapy, and simultaneous deformable registration. This study aims at improving both accuracy and efficiency of iterative algorithms for DVF inversion, and advancing our understanding of divergence and latency conditions. Method: We introduce a framework of fixed‐point iteration algorithms with active feedback control for DVF inversion. Based on rigorous convergence analysis, we design control mechanisms for modulating the inverse consistency (IC) residual of the current iterate, to be used as feedback into the next iterate. The control is designed adaptively to the input DVF with the objective to enlarge the convergence area and expedite convergence. Three particular settings of feedback control are introduced: constant value over the domain throughout the iteration; alternating values between iteration steps; and spatially variant values. We also introduce three spectral measures of the displacement Jacobian for characterizing a DVF. These measures reveal the critical role of what we term the nontranslational displacement component (NTDC) of the DVF. We carry out inversion experiments with an analytical DVF pair, and with DVFs associated with thoracic CT images of six patients at end of expiration and end of inspiration. Results: The NTDC‐adaptive iterations are shown to attain a larger convergence region at a faster pace compared to previous nonadaptive DVF inversion iteration algorithms. By our numerical experiments, alternating control yields smaller IC residuals and inversion errors than constant control. Spatially variant control renders smaller residuals and errors by at least an order of magnitude, compared to other schemes, in no more than 10 steps. Inversion results also show remarkable quantitative agreement with analysis‐based predictions. Conclusion: Our analysis captures properties of DVF data associated with clinical CT images, and provides new understanding of iterative DVF inversion algorithms with a simple residual feedback control. Adaptive control is necessary and highly effective in the presence of nonsmall NTDCs. The adaptive iterations or the spectral measures, or both, may potentially be incorporated into deformable image registration methods. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this study was to apply statistical metrics to identify outliers and to investigate the impact of outliers on knowledge-based planning in radiation therapy of pelvic cases. We also aimed to develop a systematic workflow for identifying and analyzing geometric and dosimetric outliers. Methods Four groups (G1-G4) of pelvic plans were sampled in this study. These include the following three groups of clinical IMRT cases: G1 (37 prostate cases), G2 (37 prostate plus lymph node cases) and G3 (37 prostate bed cases). Cases in G4 were planned in accordance with dynamic-arc radiation therapy procedure and include 10 prostate cases in addition to those from G1. The workflow was separated into two parts: 1. identifying geometric outliers, assessing outlier impact, and outlier cleaning; 2. identifying dosimetric outliers, assessing outlier impact, and outlier cleaning. G2 and G3 were used to analyze the effects of geometric outliers (first experiment outlined below) while G1 and G4 were used to analyze the effects of dosimetric outliers (second experiment outlined below). A baseline model was trained by regarding all G2 cases as inliers. G3 cases were then individually added to the baseline model as geometric outliers. The impact on the model was assessed by comparing leverages of inliers (G2) and outliers (G3). A receiver-operating-characteristic ( ROC) analysis was performed to determine the optimal threshold. The experiment was repeated by training the baseline model with all G3 cases as inliers and perturbing the model with G2 cases as outliers., A separate baseline model was trained with 32 G1 cases. Each G4 case (dosimetric outlier) was subsequently added to perturb the model. Predictions of dose-volume histograms ( DVHs) were made using these perturbed models for the remaining 5 G1 cases. A Weighted Sum of Absolute Residuals ( WSAR) was used to evaluate the impact of the dosimetric outliers., Results The leverage of inliers and outliers was significantly different. The Area-Under-Curve ( AUC) for differentiating G2 (outliers) from G3 (inliers) was 0.98 (threshold: 0.27) for the bladder and 0.81 (threshold: 0.11) for the rectum. For differentiating G3 (outlier) from G2 (inlier), the AUC (threshold) was 0.86 (0.11) for the bladder and 0.71 (0.11) for the rectum. Significant increase in WSAR was observed in the model with 3 dosimetric outliers for the bladder ( P < 0.005 with Bonferroni correction), and in the model with only 1 dosimetric outlier for the rectum ( P < 0.005). Conclusions We established a systematic workflow for identifying and analyzing geometric and dosimetric outliers, and investigated statistical metrics for outlier detection. Results validated the necessity for outlier detection and clean-up to enhance model quality in clinical practice. [ABSTRACT FROM AUTHOR]

Purpose To investigate the feasibility of using structural-based principal component analysis ( PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D- CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy. Methods A technique for lung 4D- CBCT reconstruction has been previously developed using a deformation field map ( DFM)-based strategy. In the previous method, each phase of the 4D- CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion model extracted by a global PCA and free-form deformation ( GMM- FD) technique, using a data fidelity constraint and deformation energy minimization. In this study, a new structural PCA method was developed to build a structural motion model ( SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4 DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation ( WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respiratory changes from planning 4D- CT to on-board volume to evaluate the method. The estimation accuracy was evaluated by the volume percent difference ( VPD)/center-of-mass-shift ( COMS) between lesions in the estimated and 'ground-truth' on-board 4D- CBCT. Different on-board projection acquisition scenarios and projection noise levels were simulated to investigate their effects on the estimation accuracy. The method was also evaluated against three lung patients. Results The SMM- WFD method achieved substantially better accuracy than the GMM- FD method for CBCT estimation using extremely small scan angles or projections. Using orthogonal 15° scanning angles, the VPD/ COMS were 3.47 ± 2.94% and 0.23 ± 0.22 mm for SMM- WFD and 25.23 ± 19.01% and 2.58 ± 2.54 mm for GMM- FD among all eight XCAT scenarios. Compared to GMM- FD, SMM- WFD was more robust against reduction of the scanning angles down to orthogonal 10° with VPD/ COMS of 6.21 ± 5.61% and 0.39 ± 0.49 mm, and more robust against reduction of projection numbers down to only 8 projections in total for both orthogonal-view 30° and orthogonal-view 15° scan angles. SMM- WFD method was also more robust than the GMM- FD method against increasing levels of noise in the projection images. Additionally, the SMM- WFD technique provided better tumor estimation for all three lung patients compared to the GMM- FD technique. Conclusion Compared to the GMM- FD technique, the SMM- WFD technique can substantially improve the 4D- CBCT estimation accuracy using extremely small scan angles and low number of projections to provide fast low dose 4D target verification. [ABSTRACT FROM AUTHOR]

Purpose: Sparing of single-side parotid gland is a common practice in head-and-neck (HN) intensity modulated radiation therapy (IMRT) planning. It is a special case of dose sparing tradeoff between different organs-at-risk. The authors describe an improved mathematical model for predicting achievable dose sparing in parotid glands in HN IMRT planning that incorporates single-side sparing considerations based on patient anatomy and learning from prior plan data. Methods: Among 68 HN cases analyzed retrospectively, 35 cases had physician prescribed single-side parotid sparing preferences. The single-side sparing model was trained with cases which had single-side sparing preferences, while the standard model was trained with the remainder of cases. A receiver operating characteristics (ROC) analysis was performed to determine the best criterion that separates the two case groups using the physicianˈs single-side sparing prescription as ground truth. The final predictive model (combined model) takes into account the single-side sparing by switching between the standard and single-side sparing models according to the single-side sparing criterion. The models were tested with 20 additional cases. The significance of the improvement of prediction accuracy by the combined model over the standard model was evaluated using the Wilcoxon rank-sum test. Results: Using the ROC analysis, the best single-side sparing criterion is (1) the predicted median dose of one parotid is higher than 24 Gy; and (2) that of the other is higher than 7 Gy. This criterion gives a true positive rate of 0.82 and a false positive rate of 0.19, respectively. For the bilateral sparing cases, the combined and the standard models performed equally well, with the median of the prediction errors for parotid median dose being 0.34 Gy by both models ( p = 0.81). For the single-side sparing cases, the standard model overestimates the median dose by 7.8 Gy on average, while the predictions by the combined model differ from actual values by only 2.2 Gy ( p = 0.005). Similarly, the sum of residues between the modeled and the actual plan DVHs is the same for the bilateral sparing cases by both models ( p = 0.67), while the standard model predicts significantly higher DVHs than the combined model for the single-side sparing cases ( p = 0.01). Conclusions: The combined model for predicting parotid sparing that takes into account single-side sparing improves the prediction accuracy over the previous model. [ABSTRACT FROM AUTHOR]

Purpose: Currently, no 3D or 4D volumetric x-ray imaging techniques are available for intrafraction verification of target position during actual treatment delivery or in-between treatment beams, which is critical for stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) treatments. This study aims to develop a limited-angle intrafraction verification (LIVE) system to use prior information, deformation models, and limited angle kV-MV projections to verify target position intrafractionally. Methods: The LIVE system acquires limited-angle kV projections simultaneously during arc treatment delivery or in-between static 3D/IMRT treatment beams as the gantry moves from one beam to the next. Orthogonal limited-angle MV projections are acquired from the beamˈs eye view (BEV) exit fluence of arc treatment beam or in-between static beams to provide additional anatomical information. MV projections are converted to kV projections using a linear conversion function. Patient prior planning CT at one phase is used as the prior information, and the on-board patient volume is considered as a deformation of the prior images. The deformation field is solved using the data fidelity constraint, a breathing motion model extracted from the planning 4D-CT based on principal component analysis (PCA) and a free-form deformation (FD) model. LIVE was evaluated using a 4D digital extended cardiac torso phantom (XCAT) and a CIRS 008A dynamic thoracic phantom. In the XCAT study, patient breathing pattern and tumor size changes were simulated from CT to treatment position. In the CIRS phantom study, the artificial target in the lung region experienced both size change and position shift from CT to treatment position. Varian Truebeam research mode was used to acquire kV and MV projections simultaneously during the delivery of a dynamic conformal arc plan. The reconstruction accuracy was evaluated by calculating the 3D volume percentage difference (VPD) and the center of mass (COM) difference of the tumor in the true on-board images and reconstructed images. Results: In both simulation and phantom studies, LIVE achieved substantially better reconstruction accuracy than reconstruction using PCA or FD deformation model alone. In the XCAT study, the average VPD and COM differences among different patient scenarios for LIVE system using orthogonal 30° scan angles were 4.3% and 0.3 mm when using kV+BEV MV. Reducing scan angle to 15° increased the average VPD and COM differences to 15.1% and 1.7 mm. In the CIRS phantom study, the VPD and COM differences for the LIVE system using orthogonal 30° scan angles were 6.4% and 1.4 mm. Reducing scan angle to 15° increased the VPD and COM differences to 51.9% and 3.8 mm. Conclusions: The LIVE system has the potential to substantially improve intrafraction target localization accuracy by providing volumetric verification of tumor position simultaneously during arc treatment delivery or in-between static treatment beams. With this improvement, LIVE opens up a new avenue for margin reduction and dose escalation in both fractionated treatments and SRS and SBRT treatments. [ABSTRACT FROM AUTHOR]

Compared to other radiation therapy modalities, clinical electron beam therapy has remained practically unchanged for the past few decades even though electron beams with multiple energies are widely available on most linacs. In this paper, we present the concept of dynamic electron arc radiotherapy (DEAR), a new conformal electron therapy technique with synchronized couch motion. DEAR utilizes combination of gantry rotation, couch motion, and dose rate modulation to achieve desirable dose distributions in patient. The electron applicator is kept to minimize scatter and maintain narrow penumbra. The couch motion is synchronized with the gantry rotation to avoid collision between patient and the electron cone. In this study, we investigate the feasibility of DEAR delivery and demonstrate the potential of DEAR to improve dose distributions on simple cylindrical phantoms. DEAR was delivered on Varian's TrueBeam linac in Research Mode. In conjunction with the recorded trajectory log files, mechanical motion accuracies and dose rate modulation precision were analyzed. Experimental and calculated dose distributions were investigated for different energies (6 and 9 MeV) and cut-out sizes (1×10 cm2 and 3×10 cm2 for a 15×15 cm2 applicator). Our findings show that DEAR delivery is feasible and has the potential to deliver radiation dose with high accuracy (root mean square error, or RMSE of <0.1 MU, <0.1° gantry, and <0.1 cm couch positions) and good dose rate precision (1.6 MU min−1). Dose homogeneity within ±2% in large and curved targets can be achieved while maintaining penumbra comparable to a standard electron beam on a flat surface. Further, DEAR does not require fabrication of patient-specific shields. These benefits make DEAR a promising technique for conformal radiotherapy of superficial tumors. [ABSTRACT FROM AUTHOR]

Purpose: Onboard imaging-currently performed primarily by x-ray transmission modalities-is essential in modern radiation therapy. As radiation therapy moves toward personalized medicine, molecular imaging, which views individual gene expression, may also be important onboard. Nuclear medicine methods, such as single photon emission computed tomography (SPECT), are premier modalities for molecular imaging. The purpose of this study is to investigate a robotic multipinhole approach to onboard SPECT. Methods: Computer-aided design (CAD) studies were performed to assess the feasibility of maneuvering a robotic SPECT system about a patient in position for radiation therapy. In order to obtain fast, high-quality SPECT images, a 49-pinhole SPECT camera was designed which provides high sensitivity to photons emitted from an imaging region of interest. This multipinhole system was investigated by computer-simulation studies. Seventeen hot spots 10 and 7 mm in diameter were placed in the breast region of a supine female phantom. Hot spot activity concentration was six times that of background. For the 49-pinhole camera and a reference, more conventional, broad field-of-view (FOV) SPECT system, projection data were computer simulated for 4-min scans and SPECT images were reconstructed. Hot-spot localization was evaluated using a nonprewhitening forced-choice numerical observer. Results: The CAD simulation studies found that robots could maneuver SPECT cameras about patients in position for radiation therapy. In the imaging studies, most hot spots were apparent in the 49-pinhole images. Average localization errors for 10-mm- and 7-mm-diameter hot spots were 0.4 and 1.7 mm, respectively, for the 49-pinhole system, and 3.1 and 5.7 mm, respectively, for the reference broad-FOV system. Conclusions: A robot could maneuver a multipinhole SPECT system about a patient in position for radiation therapy. The system could provide onboard functional and molecular imaging with 4-min scan times. [ABSTRACT FROM AUTHOR]

Purpose: Adaptive radiation therapy for prostate cancer using online reoptimization provides an improved control of interfractional anatomy variations. However, the clinical implementation of online reoptimization is currently limited by the low efficiency of current strategies and the difficulties associated with integration into the current treatment planning system. This study investigates the strategies for performing fast (∼2 min) automatic online reoptimization with a clinical fluence-map-based treatment planning system; and explores the performance with different input parameters settings: dose-volume histogram (DVH) objective settings, starting stage, and iteration number (in the context of real time planning). Methods: Simulated treatments of 10 patients were reoptimized daily for the first week of treatment (5 fractions) using 12 different combinations of optimization strategies. Options for objective settings included guideline-based RTOG objectives, patient-specific objectives based on anatomy on the planning CT, and daily-CBCT anatomy-based objectives adapted from planning CT objectives. Options for starting stages involved starting reoptimization with and without the original plan's fluence map. Options for iteration numbers were 50 and 100. The adapted plans were then analyzed by statistical modeling, and compared both in terms of dosimetry and delivery efficiency. Results: All online reoptimized plans were finished within ∼2 min with excellent coverage and conformity to the daily target. The three input parameters, i.e., DVH objectives, starting stage, and iteration number, contributed to the outcome of optimization nearly independently. Patient-specific objectives generally provided better OAR sparing compared to guideline-based objectives. The benefit in high-dose sparing from incorporating daily anatomy into objective settings was positively correlated with the relative change in OAR volumes from planning CT to daily CBCT. The use of the original plan fluence map as the starting stage reduced OAR dose at the mid-dose region, but increased the monitor units by 17%. Differences of only 2cc or less in OAR V50%/V70Gy/V76Gy were observed between 100 and 50 iterations. Conclusions: It is feasible to perform automatic online reoptimization in ∼2 min using a clinical treatment planning system. Selecting optimal sets of input parameters is the key to achieving high quality reoptimized plans, and should be based on the individual patient's daily anatomy, delivery efficiency, and time allowed for plan adaptation. [ABSTRACT FROM AUTHOR]

Purpose: Cone-beam x-ray imaging with flat panel detectors is used for target localization in image guided radiation therapy. This imaging includes cone-beam computed tomography (CBCT) and planar imaging. Use of two orthogonal x-ray systems could reduce imaging time for CBCT, provide simultaneous orthogonal views in planar imaging, facilitate dual-energy methods, and be useful in alleviating cone-beam artifacts by providing two axially offset focal-spot trajectories. However, the potential advantages of a second cone-beam system come at the cost of cross scatter, i.e., scatter of photons originating from one tube into the noncorresponding detector. Herein, cross scatter is characterized for dual cone-beam imaging, and a method for avoiding cross scatter is proposed and evaluated. Methods: A prototype dual-source CBCT system has been developed that models the geometry of a gantry-mounted kV imaging device used in radiation therapy. Cross scatter was characterized from 70 to 145 kVp in projections and reconstructed images using this system and three cylindrical phantoms (15, 20, and 30 cm) with a common Catphan core. A novel strategy for avoiding cross scatter in dual CBCT was developed that utilized interleaved data acquisition on each imaging chain. Interleaving, while maintaining similar angular sampling, can be achieved by either doubling the data acquisition rate or, as presented herein, halving the rotation speed. Results: The ratio of cross scatter to the total detected signal was found to be as high as 0.59 in a 30 cm diameter phantom. The measured scatter-to-primary ratio in some cases exceeded 4. In the 30 cm phantom, reconstructed contrast was reduced across all ROIs by an average of 48.7% when cross scatter was present. These cross-scatter degradations were almost entirely avoided by the method of interleaved exposures. Conclusions: Cross scatter is substantial in dual cone-beam imaging, but its effects can be largely removed by interleaved acquisition, which can be achieved at the same angular sampling rate either by doubling the data acquisition rate or halving the rotation speed. [ABSTRACT FROM AUTHOR]

Purpose: The authors present an evidence-based approach to quantify the effects of an array of patient anatomical features of the planning target volumes (PTVs) and organs-at-risk (OARs) and their spatial relationships on the interpatient OAR dose sparing variation in intensity modulated radiation therapy (IMRT) plans by learning from a database of high-quality prior plans. Methods: The authors formulized the dependence of OAR dose volume histograms (DVHs) on patient anatomical factors into feature models which were learned from prior plans by a stepwise multiple regression method. IMRT plans for 64 prostate, 82 head-and-neck (HN) treatments were used to train the models. Two major groups of anatomical features were considered in this study: the volumetric information and the spatial information. The geometry of OARs relative to PTV is represented by the distance-to-target histogram, DTH. Important anatomical and dosimetric features were extracted from DTH and DVH by principal component analysis. The final models were tested by additional 24 prostate and 24 HN plans. Results: Significant patient anatomical factors contributing to OAR dose sparing in prostate and HN IMRT plans have been analyzed and identified. They are: the median distance between OAR and PTV, the portion of OAR volume within an OAR specific distance range, and the volumetric factors: the fraction of OAR volume which overlaps with PTV and the portion of OAR volume outside the primary treatment field. Overall, the determination coefficients R2 for predicting the first principal component score (PCS1) of the OAR DVH by the above factors are above 0.68 for all the OARs and they are more than 0.53 for predicting the second principal component score (PCS2) of the OAR DVHs except brainstem and spinal cord. Thus, the above set of anatomical features combined has captured significant portions of the DVH variations for the OARs in prostate and HN plans. To test how well these features capture the interpatient organ dose sparing variations in general, the DVHs and specific dose-volume indices calculated from the regression models were compared with the actual DVHs and dose-volume indices from each patient's plan in the validation dataset. The dose-volume indices compared were V99%, V85%, and V50% for bladder and rectum in prostate plans and parotids median dose in HN plans. The authors found that for the bladder and rectum models, 17 out of 24 plans (71%) were within 6% OAR volume error and 21 plans (85%) were within 10% error; For the parotids model, the median dose values for 30 parotids out of 48 (63%) were within 6% prescription dose error and the values in 40 parotids (83%) were within 10% error. Conclusions: Quantitative analysis of patient anatomical features and their correlation with OAR dose sparing has identified a number of important factors that explain significant amount of interpatient DVH variations in OARs. These factors can be incorporated into evidence-based learning models as effective features to provide patient-specific OAR dose sparing goals. [ABSTRACT FROM AUTHOR]

Purpose: A TrueBeam linear accelerator (TB-LINAC) is designed to deliver traditionally flattened and flattening-filter-free (FFF) beams. Although it has been widely adopted in many clinics for patient treatment, limited information is available related to commissioning of this type of machine. In this work, commissioning data of three units were measured, and multiunit comparison was presented to provide valuable insights and reliable evaluations on the characteristics of the new treatment system. Methods: The TB-LINAC is equipped with newly designed waveguide, carousel assembly, monitoring control, and integrated imaging systems. Each machine in this study has 4, 6, 8, 10, 15 MV flattened photon beams, and 6 MV and 10 MV FFF photon beams as well as 6, 9, 12, 16, 20, and 22 MeV electron beams. Dosimetric characteristics of the three new TB-LINAC treatment units are systematically measured for commissioning. High-resolution diode detectors and ion chambers were used to measure dosimetric data for a range of field sizes from 10 × 10 to 400 × 400 mm2. The composite dosimetric data of the three units are presented in this work. The commissioning of intensity modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT), image-guided radiation therapy, and gating systems are also illustrated. Critical considerations of Pion of FFF photon beams and small field dosimetric measurements were investigated. Results: The authors found all PDDs and profiles matched well among the three machines. Beam data were quantitatively compared and combined through average to yield composite beam data. The discrepancies among the machines were quantified using standard deviation (SD). The mean SD of the PDDs among the three units is 0.12%, and the mean SD of the profiles is 0.40% for 10 MV FFF open fields. The variations of Pion of the chamber CC13 is 1.2 ± 0.1% under 6 MV FFF and 2.0 ± 0.5% under 10 MV FFF from dmax to the 18 cm-off-axis point at 35 cm depth under 40 × 40 cm2. The mean penumbra of crossplane flattened photon beams at collimator angle of 0° is measured from 5.88 ± 0.09 to 5.99 ± 0.13 mm from 4 to 15 MV at 10 cm depth of 100 × 100 mm2. The mean penumbra of crossplane beams at collimator angle of 0° is measured as 3.70 ± 0.21 and 4.83 ± 0.04 mm for 6 MV FFF and 10 MV FFF, respectively, at 10 cm depth with a field size of 5 × 5 cm2. The end-to-end test procedures of both IMRT and VMAT were performed for various energy modes. The mean ion chamber measurements of three units showed less than 2% between measurement and calculation; the mean MultiCube ICA measurements demonstrated over 90% pixels passing gamma analysis (3%, 3 mm, 5% threshold). The imaging dosimetric data of KV planar imaging and CBCT demonstrated improved consistency with vendor specifications and dose reduction for certain imaging protocols. The gated output verification showed a discrepancy of 0.05% or less between gating radiation delivery and nongating radiation delivery. Conclusions: The commissioning data indicated good consistency among the three TB-LINAC units. The commissioning data provided us valuable insights and reliable evaluations on the characteristics of the new treatment system. The systematically measured data might be useful for future reference. [ABSTRACT FROM AUTHOR]

Purpose: In image-guided radiation therapy, cone-beam CT has been adopted for three-dimensional target localization in the treatment room. In many of these cone-beam CT images, dark and light crescent artifacts can be seen. This study investigates potential causes of this artifact and a technique for mitigating the crescents. Methods: Three deviations from an ideal geometry were simulated to assess their ability to cause crescent artifacts: Bowtie filter sag, x-ray tube sag, and x-ray tube rotation. The magnitudes of these deviations were estimated by matching shifts in simulated projections to those observed with clinical systems. To correct the artifacts, angle-dependent blank projections were acquired and incorporated into image reconstruction. The degree of artifact reduction was evaluated with varying numbers (1-380) of blank projections. Scanner-acquired phantom and patient studies were conducted to demonstrate the effectiveness of the proposed correction method. Results: All three investigated causes of the crescent artifact introduced similar mismodeling of the acquired projections and similar crescent artifacts. The deviations required for these artifacts were in the range of 0.5-5 mm or 0.1°. RMS error is reduced from 8.91×10-4 to 5.25×10-7 for 1-380 blank projections over a 200° scan angle. In the patient and phantom studies, reconstructions that utilized 380 blank projections largely mitigated the crescent artifacts. Conclusions: Small deviations from an ideal geometry can result in crescent artifacts due to steep gradients in the bowtie filter. Angle-dependent blank projections can largely alleviate the artifacts. [ABSTRACT FROM AUTHOR]

Purpose: To ensure plan quality for adaptive IMRT of the prostate, we developed a quantitative evaluation tool using a machine learning approach. This tool generates dose volume histograms (DVHs) of organs-at-risk (OARs) based on prior plans as a reference, to be compared with the adaptive plan derived from fluence map deformation. Methods: Under the same configuration using seven-field 15 MV photon beams, DVHs of OARs (bladder and rectum) were estimated based on anatomical information of the patient and a model learned from a database of high quality prior plans. In this study, the anatomical information was characterized by the organ volumes and distance-to-target histogram (DTH). The database consists of 198 high quality prostate plans and was validated with 14 cases outside the training pool. Principal component analysis (PCA) was applied to DVHs and DTHs to quantify their salient features. Then, support vector regression (SVR) was implemented to establish the correlation between the features of the DVH and the anatomical information. Results: DVH/DTH curves could be characterized sufficiently just using only two or three truncated principal components, thus, patient anatomical information was quantified with reduced numbers of variables. The evaluation of the model using the test data set demonstrated its accuracy ∼80% in prediction and effectiveness in improving ART planning quality. Conclusions: An adaptive IMRT plan quality evaluation tool based on machine learning has been developed, which estimates OAR sparing and provides reference in evaluating ART. [ABSTRACT FROM AUTHOR]

The task group (TG) for quality assurance of medical accelerators was constituted by the American Association of Physicists in Medicine’s Science Council under the direction of the Radiation Therapy Committee and the Quality Assurance and Outcome Improvement Subcommittee. The task group (TG-142) had two main charges. First to update, as needed, recommendations of Table II of the AAPM TG-40 report on quality assurance and second, to add recommendations for asymmetric jaws, multileaf collimation (MLC), and dynamic/virtual wedges. The TG accomplished the update to TG-40, specifying new test and tolerances, and has added recommendations for not only the new ancillary delivery technologies but also for imaging devices that are part of the linear accelerator. The imaging devices include x-ray imaging, photon portal imaging, and cone-beam CT. The TG report was designed to account for the types of treatments delivered with the particular machine. For example, machines that are used for radiosurgery treatments or intensity-modulated radiotherapy (IMRT) require different tests and/or tolerances. There are specific recommendations for MLC quality assurance for machines performing IMRT. The report also gives recommendations as to action levels for the physicists to implement particular actions, whether they are inspection, scheduled action, or immediate and corrective action. The report is geared to be flexible for the physicist to customize the QA program depending on clinical utility. There are specific tables according to daily, monthly, and annual reviews, along with unique tables for wedge systems, MLC, and imaging checks. The report also gives specific recommendations regarding setup of a QA program by the physicist in regards to building a QA team, establishing procedures, training of personnel, documentation, and end-to-end system checks. The tabulated items of this report have been considerably expanded as compared with the original TG-40 report and the recommended tolerances accommodate differences in the intended use of the machine functionality (non-IMRT, IMRT, and stereotactic delivery). [ABSTRACT FROM AUTHOR]

We developed a novel digital tomosynthesis (DTS) reconstruction method using a deformation field map to optimally estimate volumetric information in DTS images. The deformation field map is solved by using prior information, a deformation model, and new projection data. Patients’ previous cone-beam CT (CBCT) or planning CT data are used as the prior information, and the new patient volume to be reconstructed is considered as a deformation of the prior patient volume. The deformation field is solved by minimizing bending energy and maintaining new projection data fidelity using a nonlinear conjugate gradient method. The new patient DTS volume is then obtained by deforming the prior patient CBCT or CT volume according to the solution to the deformation field. This method is novel because it is the first method to combine deformable registration with limited angle image reconstruction. The method was tested in 2D cases using simulated projections of a Shepp–Logan phantom, liver, and head-and-neck patient data. The accuracy of the reconstruction was evaluated by comparing both organ volume and pixel value differences between DTS and CBCT images. In the Shepp–Logan phantom study, the reconstructed pixel signal-to-noise ratio (PSNR) for the 60° DTS image reached 34.3 dB. In the liver patient study, the relative error of the liver volume reconstructed using 60° projections was 3.4%. The reconstructed PSNR for the 60° DTS image reached 23.5 dB. In the head-and-neck patient study, the new method using 60° projections was able to reconstruct the 8.1° rotation of the bony structure with 0.0° error. The reconstructed PSNR for the 60° DTS image reached 24.2 dB. In summary, the new reconstruction method can optimally estimate the volumetric information in DTS images using 60° projections. Preliminary validation of the algorithm showed that it is both technically and clinically feasible for image guidance in radiation therapy. [ABSTRACT FROM AUTHOR]

Radiographic image guidance has emerged as the new paradigm for patient positioning, target localization, and external beam alignment in radiotherapy. Although widely varied in modality and method, all radiographic guidance techniques have one thing in common—they can give a significant radiation dose to the patient. As with all medical uses of ionizing radiation, the general view is that this exposure should be carefully managed. The philosophy for dose management adopted by the diagnostic imaging community is summarized by the acronym ALARA, i.e., as low as reasonably achievable. But unlike the general situation with diagnostic imaging and image-guided surgery, image-guided radiotherapy (IGRT) adds the imaging dose to an already high level of therapeutic radiation. There is furthermore an interplay between increased imaging and improved therapeutic dose conformity that suggests the possibility of optimizing rather than simply minimizing the imaging dose. For this reason, the management of imaging dose during radiotherapy is a different problem than its management during routine diagnostic or image-guided surgical procedures. The imaging dose received as part of a radiotherapy treatment has long been regarded as negligible and thus has been quantified in a fairly loose manner. On the other hand, radiation oncologists examine the therapy dose distribution in minute detail. The introduction of more intensive imaging procedures for IGRT now obligates the clinician to evaluate therapeutic and imaging doses in a more balanced manner. This task group is charged with addressing the issue of radiation dose delivered via image guidance techniques during radiotherapy. The group has developed this charge into three objectives: (1) Compile an overview of image-guidance techniques and their associated radiation dose levels, to provide the clinician using a particular set of image guidance techniques with enough data to estimate the total diagnostic dose for a specific treatment scenario, (2) identify ways to reduce the total imaging dose without sacrificing essential imaging information, and (3) recommend optimization strategies to trade off imaging dose with improvements in therapeutic dose delivery. The end goal is to enable the design of image guidance regimens that are as effective and efficient as possible. [ABSTRACT FROM AUTHOR]

Digital tomosynthesis (DTS) is a fast, low-dose three-dimensional (3D) imaging approach which yields slice images with excellent in-plane resolution, though low plane-to-plane resolution. A stack of DTS slices can be reconstructed from a single limited-angle scan, with typical scan angles ranging from 10° to 40° and acquisition times of less than 10 s. The resulting DTS slices show soft tissue contrast approaching that of full cone-beam CT. External beam radiotherapy target localization using DTS requires the registration of on-board DTS images with corresponding reference image data. This study evaluates three types of reference volume: original reference CT, exact reference DTS (RDTS), and a more computationally efficient approximate reference DTS (RDTSapprox), as well as three different DTS scan angles (22°, 44°, and 65°) for the DTS target localization task. Three-dimensional mutual information (MI) shared between reference and on-board DTS volumes was computed in a region surrounding the spine of a chest phantom, as translations spanning ±5 mm and rotations spanning ±5° were simulated along each dimension in the reference volumes. The locations of the MI maxima were used as surrogates for registration accuracy, and the width of the MI peaks were used to characterize the registration robustness. The results show that conventional treatment planning CT volumes are inadequate reference volumes for direct registration with on-board DTS data. The efficient RDTSapprox method also appears insufficient for MI-based registration without further refinement of the technique, though it may be suitable for manual registration performed by a human observer. The exact RDTS volumes, on the other hand, delivered a 3D DTS localization accuracy of 0.5 mm and 0.5° along each axis, using only a single 44° coronal on-board DTS scan of the chest phantom. [ABSTRACT FROM AUTHOR]

Purpose: In order to achieve functional and molecular imaging as patients are in position for radiation therapy, a robotic multipinhole SPECT system is being developed. Alignment of the SPECT system-to the linear accelerator (LINAC) coordinate frame and to the coordinate frames of other on-board imaging systems such as cone-beam CT (CBCT)-is essential for target localization and image reconstruction. An alignment method that utilizes line sources and one pinhole projection is proposed and investigated to achieve this goal. Potentially, this method could also be applied to the calibration of the other pinhole SPECT systems. Methods: An alignment model consisting of multiple alignment parameters was developed which maps line sources in three-dimensional (3D) space to their two-dimensional (2D) projections on the SPECT detector. In a computer-simulation study, 3D coordinates of line-sources were defined in a reference room coordinate frame, such as the LINAC coordinate frame. Corresponding 2D line-source projections were generated by computer simulation that included SPECT blurring and noise effects. The Radon transform was utilized to detect angles (α) and offsets (ρ) of the line-source projections. Alignment parameters were then estimated by a nonlinear least squares method, based on the α and ρ values and the alignment model. Alignment performance was evaluated as a function of number of line sources, Radon transform accuracy, finite line-source width, intrinsic camera resolution, Poisson noise, and acquisition geometry. Experimental evaluations were performed using a physical line-source phantom and a pinhole-collimated gamma camera attached to a robot. Results: In computer-simulation studies, when there was no error in determining angles (α) and offsets (ρ) of the measured projections, six alignment parameters (three translational and three rotational) were estimated perfectly using three line sources. When angles (α) and offsets (ρ) were provided by the Radon transform, estimation accuracy was reduced. The estimation error was associated with rounding errors of Radon transform, finite line-source width, Poisson noise, number of line sources, intrinsic camera resolution, and detector acquisition geometry. Statistically, the estimation accuracy was significantly improved by using four line sources rather than three and by thinner line-source projections (obtained by better intrinsic detector resolution). With five line sources, median errors were 0.2 mm for the detector translations, 0.7 mm for the detector radius of rotation, and less than 0.5° for detector rotation, tilt, and twist. In experimental evaluations, average errors relative to a different, independent registration technique were about 1.8 mm for detector translations, 1.1 mm for the detector radius of rotation (ROR), 0.5° and 0.4° for detector rotation and tilt, respectively, and 1.2° for detector twist. Conclusions: Alignment parameters can be estimated using one pinhole projection of line sources. Alignment errors are largely associated with limited accuracy of the Radon transform in determining angles (α) and offsets (ρ) of the line-source projections. This alignment method may be important for multipinhole SPECT, where relative pinhole alignment may vary during rotation. For pinhole and multipinhole SPECT imaging on-board radiation therapy machines, the method could provide alignment of SPECT coordinates with those of CBCT and the LINAC. [ABSTRACT FROM AUTHOR]

Purpose: To investigate whether the effect of organ motion can be further reduced with the application of a cardiac gating technique, together with respiratory gating. Methods and Materials: Axial and coronal images through the heart and liver were continuously scanned with fast cine magnetic resonance imaging scans at three different gating settings: (1) without respiratory and cardiac gating; (2) with respiratory gating, but without cardiac gating; and (3) with both respiratory and cardiac gating. The effect of motion for either the heart or liver was analyzed with probability maps. Results: With the application of respiratory gating only, the marginal region on the probability map was reduced by 10.0% in the axial slice and 19.8% in the coronal slice for the heart. It was reduced by 5.2% in the axial slice and 20.8% in the coronal slice for the liver. With the application of cardiac gating together with respiratory gating, the marginal region on the probability map was reduced further. The reduction was 8.0% in the axial slice and 13.6% in the coronal slice for the heart and 5.9% in the axial slice and 7.0% in the coronal slice for the liver. Conclusion: The effect of organ motion can be further reduced with the application of cardiac gating together with respiratory gating. The potential application to treatment planning merits further investigation. [Copyright &y& Elsevier]

Purpose: Pancreas stereotactic body radiation therapy (SBRT) treatment planning requires planners to make sequential, time-consuming interactions with the treatment planning system to reach the optimal dose distribution. We sought to develop a reinforcement learning (RL)-based planning bot to systematically address complex tradeoffs and achieve high plan quality consistently and efficiently.Methods and Materials: The focus of pancreas SBRT planning is finding a balance between organ-at-risk sparing and planning target volume (PTV) coverage. Planners evaluate dose distributions and make planning adjustments to optimize PTV coverage while adhering to organ-at-risk dose constraints. We formulated such interactions between the planner and treatment planning system into a finite-horizon RL model. First, planning status features were evaluated based on human planners' experience and defined as planning states. Second, planning actions were defined to represent steps that planners would commonly implement to address different planning needs. Finally, we derived a reward system based on an objective function guided by physician-assigned constraints. The planning bot trained itself with 48 plans augmented from 16 previously treated patients, and generated plans for 24 cases in a separate validation set.Results: All 24 bot-generated plans achieved similar PTV coverages compared with clinical plans while satisfying all clinical planning constraints. Moreover, the knowledge learned by the bot could be visualized and interpreted as consistent with human planning knowledge, and the knowledge maps learned in separate training sessions were consistent, indicating reproducibility of the learning process.Conclusions: We developed a planning bot that generates high-quality treatment plans for pancreas SBRT. We demonstrated that the training phase of the bot is tractable and reproducible, and the knowledge acquired is interpretable. As a result, the RL planning bot can potentially be incorporated into the clinical workflow and reduce planning inefficiencies. [ABSTRACT FROM AUTHOR]

Purpose: To develop a tradeoff hyperplane model to facilitate tradeoff decision-making before inverse planning.Methods and Materials: We propose a model-based approach to determine the tradeoff hyperplanes that allow physicians to navigate the clinically viable space of plans with best achievable dose-volume parameters before planning. For a given case, a case reference set (CRS) is selected using a novel anatomic similarity metric from a large reference plan pool. Then, a regression model is built on the CRS to estimate the expected dose-volume histograms (DVHs) for the current case. This model also predicts the DVHs for all CRS cases and captures the variation from the corresponding DVHs in the clinical plans. Finally, these DVH variations are analyzed using the principal component analysis to determine the tradeoff hyperplane for the current case. To evaluate the effectiveness of the proposed approach, 244 head and neck cases were randomly partitioned into reference (214) and validation (30) sets. A tradeoff hyperplane was built for each validation case and evenly sampled for 12 tradeoff predictions. Each prediction yielded a tradeoff plan. The root-mean-square errors of the predicted and the realized plan DVHs were computed for prediction achievability evaluation.Results: The tradeoff hyperplane with 3 principal directions accounts for 57.8% ± 3.6% of variations in the validation cases, suggesting the hyperplanes capture a significant portion of the clinical tradeoff space. The average root-mean-square errors in 3 tradeoff directions are 5.23 ± 2.46, 5.20 ± 2.52, and 5.19 ± 2.49, compared with 4.96 ± 2.48 of the knowledge-based planning predictions, indicating that the tradeoff predictions are comparably achievable.Conclusions: Clinically relevant tradeoffs can be effectively extracted from existing plans and characterized by a tradeoff hyperplane model. The hyperplane allows physicians and planners to explore the best clinically achievable plans with different organ-at-risk sparing goals before inverse planning and is a natural extension of the current knowledge-based planning framework. [ABSTRACT FROM AUTHOR]

Purpose: To use knowledge-based planning (KBP) as a method of producing high-quality, consistent, protocol-compliant treatment plans in a complex setting of spine stereotactic body radiation therapy on NRG Oncology Radiation Therapy Oncology Group (RTOG) 0631.Methods and Materials: An internally developed KBP model was applied to an external validation cohort of 22 anonymized cases submitted under NRG Oncology RTOG 0631. The original and KBP plans were compared via their protocol compliance, target conformity and gradient index, dose to critical structures, and dose to surrounding normal tissues.Results: The KBP model generated plans meeting all protocol objectives in a single optimization when tested on both internal and protocol-submitted NRG Oncology RTOG 0631 cases. Two submitted plans that were considered to have a protocol-unacceptable deviation were made protocol compliant through the use of the model. There were no statistically significant differences in protocol spinal cord metrics (D10% and D0.03cc) between the manually optimized plans and the KBP plans. The volume of planning target volume receiving prescription dose increased from 93.3% ± 3.2% to 98.3% ± 1.4% (P = .01) when using KBP. High-dose spillage to surrounding normal tissues (V105%) showed no significant differences (2.1 ± 7.3 cm3 for manual plans to 1.8 ± 0.6 cm3 with KBP), and dosimetric outliers with large amounts of spillage were eliminated through the use of KBP. Knowledge-based planning plans were also found to be significantly more consistent in several metrics, including target coverage and high dose outside of the target.Conclusion: Incorporation of KBP models into the clinical trial setting may have a profound impact on the quality of trial results, owing to the increase in consistency and standardization of planning, especially for treatment sites or techniques that are nonstandard. [ABSTRACT FROM AUTHOR]

Purpose: To provide a benchmark for seminal vesicle (SV) margin selection to account for intrafractional motion and to investigate the effectiveness of 2 motion surrogates in predicting intrafractional SV coverage.Methods and Materials: Fifteen prostate patients were studied. Each patient had 5 pairs (1 patient had 4 pairs) of pretreatment and posttreatment cone beam CTs (CBCTs). Each pair of CBCTs was registered on the basis of prostate fiducial markers. All pretreatment SVs were expanded with 1-, 2-, 3-, 4-, 5-, and 8-mm isotropic margins to form a series of planning target volumes, and their intrafractional coverage to the posttreatment SV determined the "ground truth" for exact coverage. Two motion surrogates, the center of mass (COM) and the border of contour, were evaluated by the use of Pearson product-moment correlation coefficient and exponential fitting for predicting SV underdosage. Action threshold of each surrogate was calculated. The margin for each surrogate was calculated according to a traditional margin recipe.Results: Ninety-five percent posttreatment SV coverage was achieved in 9%, 53%, 73%, 86%, 95%, and 97% of fractions with 1-, 2-, 3-, 4-, 5-, and 8-mm margins, respectively. The 5-mm margins provided 95% intrafractional SV coverage in over 90% of fractions. The correlation between the COM and border was weak, moderate, and strong in the left-right (L-R), anterior-posterior (A-P), and superior-inferior (S-I) directions, respectively. Exponential fitting gave the underdosage threshold of 4.5 and 7.0 mm for the COM and border. The Van Herk margin recipe recommended 0-, 0.5-, and 0.8-mm margins in the L-R, A-P, and S-I directions based on the COM, and 1.2-, 3.9-, and 2.5-mm margins based on the border.Conclusions: Five-millimeter isotropic margins for the SV constitute the minimum required to mitigate the intrafractional motion. Both the COM and the border are acceptable predictors for SV underdosage with 4.5- and 7.0-mm action threshold. Traditional margin based on the COM or border underestimates the margin. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to develop a techique to generate on-board volumetric cine-magnetic resonance imaging (VC-MRI) using patient prior images, motion modeling, and on-board 2-dimensional cine MRI.Methods and Materials: One phase of a 4-dimensional MRI acquired during patient simulation is used as patient prior images. Three major respiratory deformation patterns of the patient are extracted from 4-dimensional MRI based on principal-component analysis. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI. The deformation field is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by the data fidelity constraint using the acquired on-board single 2-dimensional cine MRI. The method was evaluated using both digital extended-cardiac torso (XCAT) simulation of lung cancer patients and MRI data from 4 real liver cancer patients. The accuracy of the estimated VC-MRI was quantitatively evaluated using volume-percent-difference (VPD), center-of-mass-shift (COMS), and target tracking errors. Effects of acquisition orientation, region-of-interest (ROI) selection, patient breathing pattern change, and noise on the estimation accuracy were also evaluated.Results: Image subtraction of ground-truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground-truth with prior image. Agreement between normalized profiles in the estimated and ground-truth VC-MRI was achieved with less than 6% error for both XCAT and patient data. Among all XCAT scenarios, the VPD between ground-truth and estimated lesion volumes was, on average, 8.43 ± 1.52% and the COMS was, on average, 0.93 ± 0.58 mm across all time steps for estimation based on the ROI region in the sagittal cine images. Matching to ROI in the sagittal view achieved better accuracy when there was substantial breathing pattern change. The technique was robust against noise levels up to SNR = 20. For patient data, average tracking errors were less than 2 mm in all directions for all patients.Conclusions: Preliminary studies demonstrated the feasibility of generating real-time VC-MRI for on-board localization of moving targets in radiation therapy. [ABSTRACT FROM AUTHOR]

Purpose To evaluate the relationship between liver tumor motion and diaphragm motion. Methods and Materials Fourteen patients with hepatocellular carcinoma (10 of 14) or liver metastases (4 of 14) undergoing radiation therapy were included in this study. All patients underwent single-slice cine–magnetic resonance imaging simulations across the center of the tumor in 3 orthogonal planes. Tumor and diaphragm motion trajectories in the superior–inferior (SI), anterior–posterior (AP), and medial–lateral (ML) directions were obtained using an in-house-developed normalized cross-correlation–based tracking technique. Agreement between the tumor and diaphragm motion was assessed by calculating phase difference percentage, intraclass correlation coefficient, and Bland-Altman analysis ( D i f f ). The distance between the tumor and tracked diaphragm area was analyzed to understand its impact on the correlation between the 2 motions. Results Of all patients, the mean (±standard deviation) phase difference percentage values were 7.1% ± 1.1%, 4.5% ± 0.5%, and 17.5% ± 4.5% in the SI, AP, and ML directions, respectively. The mean intraclass correlation coefficient values were 0.98 ± 0.02, 0.97 ± 0.02, and 0.08 ± 0.06 in the SI, AP, and ML directions, respectively. The mean Diff values were 2.8 ± 1.4 mm, 2.4 ± 1.1 mm, and 2.2 ± 0.5 mm in the SI, AP, and ML directions, respectively. Tumor and diaphragm motions had high concordance when the distance between the tumor and tracked diaphragm area was small. Conclusions This study showed that liver tumor motion had good correlation with diaphragm motion in the SI and AP directions, indicating diaphragm motion in the SI and AP directions could potentially be used as a reliable surrogate for liver tumor motion. [ABSTRACT FROM AUTHOR]

Purpose: To quantify uncertainties in delineating an internal target volume (ITV) and to understand how these uncertainties may be individually minimized for stereotactic body radiation therapy (SBRT) of early stage non-small cell lung cancer (NSCLC). Methods and Materials: Twenty patients with NSCLC who were undergoing SBRT were imaged with free-breathing 3-dimensional computed tomography (3DCT) and 10-phase 4-dimensional CT (4DCT) for delineating gross tumor volume (GTV)(3D) and ITV(10Phase) (ITV3). The maximum intensity projection (MIP) CT was also calculated from 10-phase 4DCT for contouring ITV(MIP) (ITV1). Then, ITV(COMB) (ITV2), ITV(10Phase+GTV3D) (ITV4), and ITV(10Phase+ITVCOMB) (ITV5) were generated by combining ITV(MIP) and GTV(3D), ITV(10phase) and GTV(3D), and ITV(10phase) and ITV(COMB), respectively. All 6 volumes (GTV(3D) and ITV1 to ITV5) were delineated in the same lung window by the same radiation oncologist. The percentage of volume difference (PVD) between any 2 different volumes was determined and was correlated to effective tumor diameter (ETD), tumor motion ranges, R(3D), and the amplitude variability of the recorded breathing signal (v) to assess their volume variations. Results: The mean (range) tumor motion (R(SI), R(AP), R(ML), and R(3D)) and breathing variability (v) were 7.6 mm (2-18 mm), 4.0 mm (2-8 mm), 3.3 mm (0-7.5 mm), 9.9 mm (4.1-18.7 mm), and 0.17 (0.07-0.37), respectively. The trend of volume variation was GTV(3D) Conclusion: Uncertainties in individualized ITVs for SBRT of early stage NSCLC could effectively be minimized by combining information from 3DCT, 4DCT, and MIP. If these images cannot be efficiently contoured, a combination of ITV(MIP) and GTV(3D) could be an effective alternative. [ABSTRACT FROM AUTHOR]