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Objective . Deep learning (DL) models for fluence map prediction (FMP) have great potential to reduce treatment planning time in intensity-modulated radiation therapy (IMRT) by avoiding the lengthy inverse optimization process. This study aims to improve the rigor of input feature design in a DL-FMP model by examining how different designs of input features influence model prediction performance. Approach . This study included 231 head-and-neck intensity-modulated radiation therapy patients. Three input feature designs were investigated. The first design (D1) assumed that information of all critical structures from all beam angles should be combined to predict fluence maps. The second design (D2) assumed that local anatomical information was sufficient for predicting radiation intensity of a beamlet at a respective beam angle. The third design (D3) assumed the need for both local anatomical information and inter-beam modulation to predict radiation intensity values of the beamlets that intersect at a voxel. For each input design, we tailored the DL model accordingly. All models were trained using the same set of ground truth plans (GT plans). The plans generated by DL models (DL plans) were analyzed using key dose-volume metrics. One-way ANOVA with multiple comparisons correction (Bonferroni method) was performed (significance level = 0.05). Main results . For PTV-related metrics, all DL plans had significantly higher maximum dose ( p  < 0.001), conformity index ( p  < 0.001), and heterogeneity index ( p  < 0.001) compared to GT plans, with D2 being the worst performer. Meanwhile, except for cord+5 mm ( p  < 0.001), DL plans of all designs resulted in OAR dose metrics that are comparable to those of GT plans. Significance . Local anatomical information contains most of the information that DL models need to predict fluence maps for clinically acceptable OAR sparing. Input features from beam angles are needed to achieve the best PTV coverage. These results provide valuable insights for further improvement of DL-FMP models and DL models in general., (© 2022 Institute of Physics and Engineering in Medicine.)

Purpose: To explore implications of various plan normalizations when implementing a linear Boltzmann transport equation solver dose calculation algorithm (LBTE) for lung stereotactic body radiation therapy (SBRT)., Methods and Materials: Eighty-seven plans originally calculated with a convolution-superposition algorithm (CS) were recalculated with LBTE and normalized in 3 ways: prescription covering 95% of planning target volume (PTV), 99% of internal target volume (ITV), and keeping the original planned PTV coverage. Effect on delivered dose after implementing the new algorithm was quantified using change in total monitor units for each renormalization strategy. Treatment planning system-reported changes in PTV, ITV, and organ at risk (OAR) doses were also quantified, along with the feasibility of LBTE plans to meet institutional OAR planning objectives., Results: LBTE renormalization resulted in monitor unit increases of 7.0 ± 8.8%, 0.31 ± 5.8%, and 7.9 ± 8.6% when normalizing to the PTV D95%, ITV D99%, and planned coverage, respectively. When normalizing to PTV D95%, the LBTE reported increased PTV and ITV D1% (Gy) relative to CS (median, 3.4% and 3.2%, respectively), and normalizing to ITV D99% showed a median 1.9% decrease. For LBTE plans, reported OAR doses were increased when normalizing to PTV D95% or planned coverage (median chest wall V30 Gy [cc] increase of 0.85 and 1.7 cc, respectively) and normalizing to ITV D99% resulted in decreased dose (median chest wall V30 Gy [cc] decrease of 1.8 cc). LBTE plans normalized to PTV D95% showed inferior ability to meet the OAR objectives, but reoptimizing kept the objectives manageable while maintaining PTV coverage., Conclusions: When transitioning from CS to LBTE dose calculation for lung SBRT, maintaining a PTV coverage-based normalization generally results in increased dose delivered relative to CS and increased reported target and OAR dose. In cases where PTV normalization results in unacceptably high doses to targets or OARs, normalizing based on ITV coverage can be considered to maintain similar target dose as CS., (Copyright © 2022 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.)

Objective: To design a deep transfer learning framework for modeling fluence map predictions for stereotactic body radiation therapy (SBRT) of adrenal cancer and similar sites that usually have a small number of cases. Approach: We developed a transfer learning framework for adrenal SBRT planning that leverages knowledge in a pancreas SBRT planning model. Treatment plans from the two sites had different dose prescriptions and beam settings but both prioritized gastrointestinal sparing. A base framework was first trained with 100 pancreas cases. This framework consists of two convolutional neural networks (CNN), which predict individual beam doses (BD-CNN) and fluence maps (FM-CNN) sequentially for 9-beam intensity-modulated radiation therapy (IMRT) plans. Forty-five adrenal plans were split into training/validation/test sets with the ratio of 20/10/15. The base BD-CNN was re-trained with transfer learning using 5/10/15/20 adrenal training cases to produce multiple candidate adrenal BD-CNN models. The base FM-CNN was directly used for adrenal cases. The deep learning (DL) plans were evaluated by several clinically relevant dosimetric endpoints, producing a percentage score relative to the clinical plans. Main results: Transfer learning significantly reduced the number of training cases and training time needed to train such a DL framework. The adrenal transfer learning model trained with 5/10/15/20 cases achieved validation plan scores of 85.4/91.2/90.7/89.4, suggesting that model performance saturated with 10 training cases. Meanwhile, a model using all 20 adrenal training cases without transfer learning only scored 80.5. For the final test set, the 5/10/15/20-case models achieved scores of 73.5/75.3/78.9/83.3. Significance: It is feasible to use deep transfer learning to train an IMRT fluence prediction framework. This technique could adapt to different dose prescriptions and beam configurations. This framework potentially enables DL modeling for clinical sites that have a limited dataset, either due to few cases or due to rapid technology evolution., (© 2021 Institute of Physics and Engineering in Medicine.)

Purpose. We have previously reported an artificial intelligence (AI) agent that automatically generates intensity-modulated radiation therapy (IMRT) plans via fluence map prediction, by-passing inverse planning. This AI agent achieved clinically comparable quality for prostate cases, but its performance on head-and-neck patients leaves room for improvement. This study aims to collect insights of the deep-learning-based (DL-based) fluence map prediction model by systematically analyzing its prediction errors. Methods. From the modeling perspective, the DL model's output is the fluence maps of IMRT plans. However, from the clinical planning perspective, the plan quality evaluation should be based on the clinical dosimetric criteria such as dose-volume histograms. To account for the complex and non-intuitive relationships between fluence map prediction errors and the corresponding dose distribution changes, we propose a novel error analysis approach that systematically examines plan dosimetric changes that are induced by varying amounts of fluence prediction errors. We investigated four decomposition modes of model prediction errors. The two spatial domain decompositions are based on fluence intensity and fluence gradient. The two frequency domain decompositions are based on Fourier-space banded frequency rings and Fourier-space truncated low-frequency disks. The decomposed error was analyzed for its impact on the resulting plans' dosimetric metrics. The analysis was conducted on 15 test cases spared from the 200 training and 16 validation cases used to train the model. Results. Most planning target volume metrics were significantly correlated with most error decompositions. The Fourier space disk radii had the largest Spearman's coefficients. The low-frequency region within a disk of ∼20% Fourier space contained most of errors that impact overall plan quality. Conclusions. This study demonstrates the feasibility of using fluence map prediction error analysis to understand the AI agent's performance. Such insights will help fine-tune the DL models in architecture design and loss function selection., (© 2021 The Author(s). Published on behalf of Institute of Physics and Engineering in Medicine by IOP Publishing Ltd.)

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., (© 2021 American Association of Physicists in Medicine.)

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., (© 2021 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.)

Purpose: To develop an artificial intelligence (AI) agent for fully automated rapid head-and-neck intensity-modulated radiation therapy (IMRT) plan generation without time-consuming dose-volume-based inverse planning., Methods: This AI agent was trained via implementing a conditional generative adversarial network (cGAN) architecture. The generator, PyraNet, is a novel deep learning network that implements 28 classic ResNet blocks in pyramid-like concatenations. The discriminator is a customized four-layer DenseNet. The AI agent first generates multiple customized two-dimensional projections at nine template beam angles from a patient's three-dimensional computed tomography (CT) volume and structures. These projections are then stacked as four-dimensional inputs of PyraNet, from which nine radiation fluence maps of the corresponding template beam angles are generated simultaneously. Finally, the predicted fluence maps are automatically postprocessed by Gaussian deconvolution operations and imported into a commercial treatment planning system (TPS) for plan integrity check and visualization. The AI agent was built and tested upon 231 oropharyngeal IMRT plans from a TPS plan library. 200/16/15 plans were assigned for training/validation/testing, respectively. Only the primary plans in the sequential boost regime were studied. All plans were normalized to 44 Gy prescription (2 Gy/fx). A customized Harr wavelet loss was adopted for fluence map comparison during the training of the PyraNet. For test cases, isodose distributions in AI plans and TPS plans were qualitatively evaluated for overall dose distributions. Key dosimetric metrics were compared by Wilcoxon signed-rank tests with a significance level of 0.05., Results: All 15 AI plans were successfully generated. Isodose gradients outside of PTV in AI plans were comparable to those of the TPS plans. After PTV coverage normalization, D mean of left parotid (D AI  = 23.1 ± 2.4 Gy; D TPS  = 23.1 ± 2.0 Gy), right parotid (D AI  = 23.8 ± 3.0 Gy; D TPS  = 23.9 ± 2.3 Gy), and oral cavity (D AI  = 24.7 ± 6.0 Gy; D TPS  = 23.9 ± 4.3 Gy) in the AI plans and the TPS plans were comparable without statistical significance. AI plans achieved comparable results for maximum dose at 0.01cc of brainstem (D AI  = 15.0 ± 2.1 Gy; D TPS  = 15.5 ± 2.7 Gy) and cord + 5mm (D AI  = 27.5 ± 2.3 Gy; D TPS  = 25.8 ± 1.9 Gy) without clinically relevant differences, but body D max results (D AI  = 121.1 ± 3.9 Gy; D TPS  = 109.0 ± 0.9 Gy) were higher than the TPS plan results. The AI agent needed ~3 s for predicting fluence maps of an IMRT plan., Conclusions: With rapid and fully automated execution, the developed AI agent can generate complex head-and-neck IMRT plans with acceptable dosimetry quality. This approach holds great potential for clinical applications in preplanning decision-making and real-time planning., (© 2021 American Association of Physicists in Medicine.)

Linac based radiosurgery to multiple metastases is commonly planned with volumetric modulated arc therapy (VMAT) as it effectively achieves high conformality to complex target arrangements. However, as the number of targets increases, VMAT can struggle to block between targets, which can lead to highly modulated and/or nonconformal multi-leaf collimator (MLC) trajectories that unnecessarily irradiation of healthy tissue. In this study we introduce, describe, and evaluate a treatment planning technique called Conformal Arc Informed VMAT (CAVMAT), which aims to reduce the dose to healthy tissue while generating highly conformal treatment plans. CAVMAT is a hybrid technique which combines the conformal MLC trajectories of dynamic conformal arcs with the MLC modulation and versatility of inverse optimization. CAVMAT has 3 main steps. First, targets are assigned to subgroups to maximize MLC blocking between targets. Second, arc weights are optimized to achieve the desired target dose, while minimizing MU variation between arcs. Third, the optimized conformal arc plan serves as the starting point for limited inverse optimization to improve dose conformity to each target. Twenty multifocal VMAT cases were replanned with CAVMAT with 20Gy applied to each target. The total volume receiving 2.5 Gy [cm 3 ], 6 Gy [cm 3 ], 12 Gy [cm 3 ], and 16 Gy [cm 3 ], conformity index, treatment delivery time, and the total MU were used to compare the VMAT and CAVMAT plans. In addition, CAVMAT was compared to a broad range of planning strategies from various institutions (108 linear accelerator based plans, 14 plans using other modalities) for a 5-target case utilized in a recent plan challenge. For the linear accelerator-based plans, a plan complexity metric based on aperture opening area and perimeter, total monitor units (MU), and MU for a given aperture opening was utilized in the plan challenge scoring algorithm to compare the submitted plans to CAVMAT. After re-planning the 20 VMAT cases, CAVMAT reduced the average V 2.5Gy [cm 3 ] by 25.25 ± 19.23%, V 6Gy [cm 3 ] by 13.68 ± 18.97%, V 12Gy [cm 3 ] by 11.40 ± 19.44%, and V 16Gy [cm 3 ] by 6.38 ± 19.11%. CAVMAT improved conformity by 3.81 ± 7.57%, while maintaining comparable target dose. MU for the CAVMAT plans increased by 24.35 ± 24.66%, leading to an increased treatment time of 2 minutes. For the plan challenge case, CAVMAT was 1 of 12 linac based plans that met all plan challenge scoring criteria. Compared to the average submitted VMAT plan, CAVMAT increased the V 10% Gy[%] of healthy tissue (Brain-PTV) by roughly 3.42%, but in doing so was able to reduce the V 25% Gy[%] by roughly 3.73%, while also reducing V 50% Gy[%] , V 75% Gy[%], and V 100% Gy[%] . The CAVMAT technique successfully eliminated insufficient MLC blocking between targets prior to the inverse optimization, leading to less complex treatment plans and improved tissue sparing. Tissue sparing, improved conformity, and decreased plan complexity at the cost of slight increase in treatment delivery time indicates CAVMAT to be a promising method to treat brain metastases., (Copyright © 2020 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.)

The purpose of this work was to develop a deep learning (DL) based algorithm, Automatic intensity-modulated radiotherapy (IMRT) Planning via Static Field Fluence Prediction (AIP-SFFP), for automated prostate IMRT planning with real-time planning efficiency. The following method was adopted: AIP-SFFP generates a prostate IMRT plan through predictions of fluence maps using patient anatomy. No inverse planning is required. AIP-SFFP is centered on a custom-built deep learning (DL) neural network for fluence map prediction. Predictions are imported to a commercial treatment-planning system for dose calculation and plan generation. AIP-SFFP was demonstrated for prostate IMRT simultaneously-integrated-boost planning (58.8 Gy/70 Gy to PTV 58.8 Gy /PTV 70 Gy in 28 fx, PTV = Planning Target Volume). Training data was generated from 106 patients using a knowledge-based planning (KBP) plan generator. Two types of 2D projection images were designed to represent structures' sizes and locations, and a total of eight projections were utilized to describe targets and organs-at-risk. Projections at nine template beam angles were stacked as inputs for artificial intelligence (AI) training. 14 patients were used as independent tests. The generated test plans were compared with the plans from the KBP training plan generator and clinic practice. The following results were obtained: After normalization (PTV 70 Gy V 70 Gy = 95%), all 14 AI plans met institutional criteria. The coverage of PTV 58.8 Gy in the AI plans was comparable to KBP and clinic plans without statistical significance. The whole body (BODY) D1cc and rectum D0.1cc of AI plans were slightly higher (<1 Gy) compared to KBP and clinic plans; in contrast, the bladder D1cc and other rectum and bladder low doses in the AI plans were slightly improved without clinical relevance. The overall isodose distribution in the AI plans was comparable with KBP plans and clinical plans. AIP-SFFP generated each test plan within 20s including the prediction and the dose calculation. In conclusion, AIP-SFFP was successfully developed for prostate IMRT planning. AIP-SFFP demonstrated good overall plan quality and real-time efficiency. Showing great promise, AIP-SFFP will be investigated for immediate clinical application.

Purpose: To characterize key plan quality metrics in multi-target stereotactic radiosurgery (SRS) plans treated using single-isocenter volumetric modulated arc therapy (VMAT) in comparison to dynamic conformal arc (DCA) plans treating single target. To investigate the feasibility of quality improvement in VMAT planning based on previous planning knowledge., Materials and Methods: 97 VMAT plans of multi-target and 156 DCA plans of single-target treated in 2017 at a single institution were reviewed. A total of 605 targets were treated with these SRS plans. The prescription dose was normalized to 20 Gy in all plans for this analysis. Two plan quality metrics, target conformity index (CI) and normal tissue volume receiving more than 12 Gy (V12Gy), were calculated for each target. The distribution of V12Gy per target was plotted as a function of the target volume. For multi-target VMAT plans, the number of targets being treated in the same plan and the distance between targets were calculated to evaluate their impact on V12Gy. VMAT plans that had a large deviation of V12Gy from the average level were re-optimized to determine the possibility of reducing the variation of V12Gy in VMAT planning., Results: Conformity index of multi-target VMAT plans were lower than that of DCA plans while the mean values of 12 Gy were comparable. The V12Gy for a target in VMAT plan did not show apparent dependence on the total number of targets or the distance between targets. The distribution of V12Gy exhibited a larger variation in VMAT plans compared to DCA plans. Re-optimization of outlier plans reduced V12 Gy by 33.9% and resulted in the V12Gy distribution in VMAT plans more closely resembling that of DCA plans., Conclusion: The benchmark data on key plan quality metrics were established for single-isocenter multi-target SRS planning. It is feasible to use this knowledge to guide VMAT planning and reduce high V12Gy outliers., (© 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American.)

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.

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., (© 2019 American Association of Physicists in Medicine.)

Purpose: To investigate the impact of intra- and inter-fractional esophageal motion on dosimetry and observed toxicity in a phase I dose escalation study of accelerated radiotherapy with concurrent chemotherapy for locally advanced lung cancer., Methods and Materials: Patients underwent computed tomography imaging for radiotherapy treatment planning (CT1 and 4DCT1) and at 2 weeks (CT2 and 4DCT2) and 5 weeks (CT3 and 4DCT3) after initiating treatment. Each computed tomography scan consisted of 10-phase 4DCTs in addition to a static free-breathing or breath-hold computed tomography. The esophagus was independently contoured on all computed tomographies and 4DCTs. Both CT2 and CT3 were rigidly registered with CT1 and doses were recalculated using the original intensity-modulated radiation therapy plan based on CT1 to assess the impact of interfractional motion on esophageal dosimetry. Similarly, 4DCT1 data sets were rigidly registered with CT1 to assess the impact of intrafractional motion. The motion was characterized based on the statistical analysis of slice-by-slice center shifts (after registration) for the upper, middle, and lower esophageal regions, respectively. For the dosimetric analysis, the following quantities were calculated and assessed for correlation with toxicity grade: the percent volumes of esophagus that received at least 20 Gy (V20) and 60 Gy (V60), maximum esophageal dose, equivalent uniform dose, and normal tissue complication probability., Results: The interfractional center shifts were 4.4 ± 1.7 mm, 5.5 ± 2.0 mm and 4.9 ± 2.1 mm for the upper, middle, and lower esophageal regions, respectively, while the intrafractional center shifts were 0.6 ± 0.4 mm, 0.7 ± 0.7 mm, and 0.9 ± 0.7 mm, respectively. The mean V60 (and corresponding normal tissue complication probability) values estimated from the interfractional motion analysis were 7.8% (10%), 4.6% (7.5%), 7.5% (8.6%), and 31% (26%) for grade 0, grade 1, grade 2, and grade 3 toxicities, respectively., Conclusions: Interfractional esophageal motion is significantly larger than intrafractional motion. The mean values of V60 and corresponding normal tissue complication probability, incorporating interfractional esophageal motion, correlated positively with esophageal toxicity grade.

Aim: The aim of the study is to develop a geometrically adaptive and statistically robust plan quality inference method., Methods and Materials: We propose a knowledge-based plan quality inference method that references to similar plans in the historical database for patient-specific plan quality evaluation. First, a novel plan similarity metric with high-dimension geometrical difference quantification is utilized to retrieve similar plans. Subsequently, dosimetric statistical inferences are obtained from the selected similar plans. Two plan quality metrics-dosimetric result probability and dose deviation index-are proposed to quantify plan quality among prior similar plans. To evaluate the performance of the proposed method, we exported 927 clinically approved head and neck treatment plans. Eight organs at risk, including brain stem, cord, larynx, mandible, pharynx, oral cavity, left parotid and right parotid, were analyzed. Twelve suboptimal plans identified by dosimetric result probability were replanned to validate the capability of the proposed methods in identifying inferior plans., Results: After replanning, left and right parotid median doses are reduced by 31.7% and 18.2%, respectively; 83% of these cases would not be identified as suboptimal without the proposed similarity plan selection. Analysis of population plan quality reveals that average parotid sparing has been improving significantly over time (21.7% dosimetric result probability reduction from year 2006-2007 to year 2016-2017). Notably, the increasing dose sparing over time in retrospective plan quality analysis is strongly correlated with the increasing dose prescription ratios to the 2 planning targets, revealing the collective trend in planning conventions., Conclusions: The proposed similar plan retrieval and analysis methodology has been proven to be predictive of the current plan quality. Therefore, the proposed workflow can potentially be applied in the clinics as a real-time plan quality assurance tool. The proposed metrics can also serve the purpose of plan quality analytics in finding connections and historical trends in the clinical treatment planning workflow.

Knowledge models in radiotherapy capture the relation between patient anatomy and dosimetry to provide treatment planning guidance. When treatment schemes evolve, existing models struggle to predict accurately. We propose a case-based reasoning framework designed to handle novel anatomies that are of same type but vary beyond original training samples. A total of 105 pelvic intensity-modulated radiotherapy cases were analyzed. Eighty cases were prostate cases while the other 25 were prostate-plus-lymph-node cases. We simulated 4 scenarios: Scarce scenario, Semiscarce scenario, Semiample scenario, and Ample scenario. For the Scarce scenario, a multiple stepwise regression model was trained using 85 cases (80 prostate, 5 prostate-plus-lymph-node). The proposed workflow started with evaluating the feature novelty of new cases against 5 training prostate-plus-lymph-node cases using leverage statistic. The case database was composed of a 5-case dose atlas. Case-based dose prediction was compared against the regression model prediction using sum of squared residual. Mean sum of squared residual of case-based and regression predictions for the bladder of 13 identified outliers were 0.174 ± 0.166 and 0.459 ± 0.508, respectively ( P = .0326). For the rectum, the respective mean sum of squared residuals were 0.103 ± 0.120 and 0.150 ± 0.171 for case-based and regression prediction ( P = .1972). By retaining novel cases, under the Ample scenario, significant statistical improvement was observed over the Scarce scenario ( P = .0398) for the bladder model. We expect that the incorporation of case-based reasoning that judiciously applies appropriate predictive models could improve overall prediction accuracy and robustness in clinical practice.

Beam angle configuration is a major planning decision in intensity modulated radiation treatment (IMRT) that has a significant impact on dose distributions and thus quality of treatment, especially in complex planning cases such as those for lung cancer treatment. We propose a novel method to automatically determine beam configurations that incorporates noncoplanar beams. We then present a completely automated IMRT planning algorithm that combines the proposed method with a previously reported OAR DVH prediction model. Finally, we validate this completely automatic planning algorithm using a set of challenging lung IMRT cases. A beam efficiency index map is constructed to guide the selection of beam angles. This index takes into account both the dose contributions from individual beams and the combined effect of multiple beams by introducing a beam-spread term. The effect of the beam-spread term on plan quality was studied systematically and the weight of the term to balance PTV dose conformity against OAR avoidance was determined. For validation, complex lung cases with clinical IMRT plans that required the use of one or more noncoplanar beams were re-planned with the proposed automatic planning algorithm. Important dose metrics for the PTV and OARs in the automatic plans were compared with those of the clinical plans. The results are very encouraging. The PTV dose conformity and homogeneity in the automatic plans improved significantly. And all the dose metrics of the automatic plans, except the lung V 5 Gy , were statistically better than or comparable with those of the clinical plans. In conclusion, the automatic planning algorithm can incorporate non-coplanar beam configurations in challenging lung cases and can generate plans efficiently with quality closely approximating that of clinical plans.

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 cm 3 for manual plans to 1.8 ± 0.6 cm 3 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., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Purpose: Limited-angle intrafraction verification (LIVE) has been previously developed for four-dimensional (4D) intrafraction target verification either during arc delivery or between three-dimensional (3D)/IMRT beams. Preliminary studies showed that LIVE can accurately estimate the target volume using kV/MV projections acquired over orthogonal view 30° scan angles. Currently, the LIVE imaging acquisition requires slow gantry rotation and is not clinically optimized. The goal of this study is to optimize the image acquisition parameters of LIVE for different patient respiratory periods and gantry rotation speeds for the effective clinical implementation of the system., Method: Limited-angle intrafraction verification imaging acquisition was optimized using a digital anthropomorphic phantom (XCAT) with simulated respiratory periods varying from 3 s to 6 s and gantry rotation speeds varying from 1°/s to 6°/s. LIVE scanning time was optimized by minimizing the number of respiratory cycles needed for the four-dimensional scan, and imaging dose was optimized by minimizing the number of kV and MV projections needed for four-dimensional estimation. The estimation accuracy was evaluated by calculating both the center-of-mass-shift (COMS) and three-dimensional volume-percentage-difference (VPD) between the tumor in estimated images and the ground truth images. The robustness of LIVE was evaluated with varied respiratory patterns, tumor sizes, and tumor locations in XCAT simulation. A dynamic thoracic phantom (CIRS) was used to further validate the optimized imaging schemes from XCAT study with changes of respiratory patterns, tumor sizes, and imaging scanning directions., Results: Respiratory periods, gantry rotation speeds, number of respiratory cycles scanned and number of kV/MV projections acquired were all positively correlated with the estimation accuracy of LIVE. Faster gantry rotation speed or longer respiratory period allowed less respiratory cycles to be scanned and less kV/MV projections to be acquired to estimate the target volume accurately. Regarding the scanning time minimization, for patient respiratory periods of 3-4 s, gantry rotation speeds of 1°/s, 2°/s, 3-6°/s required scanning of five, four, and three respiratory cycles, respectively. For patient respiratory periods of 5-6 s, the corresponding respiratory cycles required in the scan changed to four, three, and two cycles, respectively. Regarding the imaging dose minimization, for patient respiratory periods of 3-4 s, gantry rotation speeds of 1°/s, 2-4°/s, 5-6°/s required acquiring of 7, 5, 4 kV and MV projections, respectively. For patient respiratory periods of 5-6 s, 5 kV and 5 MV projections are sufficient for all gantry rotation speeds. The optimized LIVE system was robust against breathing pattern, tumor size and tumor location changes. In the CIRS study, the optimized LIVE system achieved the average center-of-mass-shift (COMS)/volume-percentage-difference (VPD) of 0.3 ± 0.1 mm/7.7 ± 2.0% for the scanning time priority case, 0.2 ± 0.1 mm/6.1 ± 1.2% for the imaging dose priority case, respectively, among all gantry rotation speeds tested. LIVE was robust against different scanning directions investigated., Conclusion: The LIVE system has been preliminarily optimized for different patient respiratory periods and treatment gantry rotation speeds using digital and physical phantoms. The optimized imaging parameters, including number of respiratory cycles scanned and kV/MV projection numbers acquired, provide guidelines for optimizing the scanning time and imaging dose of the LIVE system for its future evaluations and clinical implementations through patient studies., (© 2017 American Association of Physicists in Medicine.)

Background: In volumetric modulated arc therapy (VMAT), gantry angles, dose rate and the MLC positions vary with the radiation delivery. The quality assurance (QA) system should be able to catch the planning and machine errors. The aim of this study was to investigate the sensitivity of three VMAT QA systems to machine errors., Methods: Several types of potential linac machine errors unique to VMAT delivery were simulated in sinusoidal function of gantry angle, including gantry angle itself, MLC position and linac output. Two commercial QA systems, ArcCheck and Delta 4 , and an in-house developed EPID technique were compared in this study. Fifteen full arcs from head and neck plans were selected and modified to include five magnitudes of each type of error, resulting in measurements and γ analyses of 240 arcs on each system. Both qualitative and quantitative comparisons were performed using receiver operating characteristic (ROC), γ pass rate gradient, and overlap histogram methods., Results: In ROC analysis, the area under curve (AUC) represents the sensitivity and increases with the error magnitude. Using the criteria of 2 %/2 mm/2° (angle to agreement, ATA, only for EPID) and keeping AUC > 0.95, the minimum error detectable of ArcCheck, Delta 4 and EPID are (2, 3, 3)° in gantry angle and (4, 2, 3) mm in MLC positions for the head and neck plans. No system is sensitive to the simulated output error, the AUC values were all below 0.70 even with 5 % output error. The γ gradient for gantry angle, MLC position and output errors are (-5.1, -2.6, -3.6)%/°, (-2.6, -7.1, -3.3)%/mm and (-0.2, -0.2, -0.3)%/% for ArcCheck, Delta 4 and EPID, respectively. Therefore, these two analyses are consistent and support the same conclusion. The ATA parameter in EPID technique can be adjusted to tune its sensitivity., Conclusions: We found that ArcCheck is more sensitive to gantry angle error and Delta 4 is more sensitive to MLC position error. All three systems are not sensitive to the simulated output error. With additional analysis parameter, the EPID technique can be tuned to have optimal sensitivity and is able to perform QA for full field size with highest resolution. In addition, ROC analysis avoids the choice of γ pass rate threshold and is more robust compared with other analysis methods.

The purpose of this work was to evaluate the potential of a new transmission detector for real-time quality assurance of dynamic-MLC-based radiotherapy. The accuracy of detecting dose variation and static/dynamic MLC position deviations was measured, as well as the impact of the device on the radiation field (surface dose, transmission). Measured dose variations agreed with the known variations within 0.3%. The measurement of static and dynamic MLC position deviations matched the known deviations with high accuracy (0.7-1.2 mm). The absorption of the device was minimal (~ 1%). The increased surface dose was small (1%-9%) but, when added to existing collimator scatter effects could become significant at large field sizes (≥ 30 × 30 cm2). Overall the accuracy and speed of the device show good potential for real-time quality assurance., (© 2016 The Authors.)

Previous work demonstrated improved dosimetry of single isocenter volumetric modulated arc therapy (VMAT) of multiple intracranial targets when they are located ≤ 4cm from isocenter because of narrower multileaf collimators (MLCs). In follow-up, we sought to determine if decreasing isocenter-target distance (d iso ) by using 2 to 3 isocenters would improve dosimetry for spatially dispersed targets. We also investigated the effect of a maximum dose constraint during VMAT optimization, and the dosimetric effect of the number of VMAT arcs used for a larger number of targets (i.e., 7 to 9). We identified radiosurgery cases that had multiple intracranial targets with d iso of at least 1 target > 5cm. A single isocenter VMAT plan was created using a standardized 4-arc technique with 18Gy per target. Each case was then replanned (1) using 2 to 3 isocenters, (2) including a maximum dose constraint per target, and in the case of 7 to 9 targets, (3) using 3 to 6 arcs. Dose evaluation included brain V 6Gy and V 12Gy , and conformity index (CI), gradient index (GI), and heterogeneity index (HI) per target. Two isocenters were sufficient to limit d iso to ≤ 4cm and ≤ 5cm for 11/15 and 13/15 cases, respectively; after replanning with 2 to 3 isocenters, d iso decreased from 5.8 ± 2.8cm (2.3 14.9) to 2.5 ± 1.4cm (0 5.2). All dose statistics improved on average, albeit modestly: V 6Gy = 6.9 ± 7.1%, V 12Gy = 0.9% ± 4.4%, CI = 2.6% ± 4.6%, GI = 0.9% ± 12.7%, and HI = 2.6% ± 5.2%; however, the number of arcs doubled and monitor units increase by nearly 2-fold. A maximum dose constraint had a negative effect on all dose indices, increasing V 12Gy by 9.7 ± 6.9%. For ≥ 7 targets, increasing number of arcs to > 3 improved CI, V 12Gy , and V 6Gy . A single isocenter is likely sufficient for VMAT radiosurgery of multiple intracranial metastases. Optimal treatment plan quality is achieved when no constraint is placed on the maximum target dose; for cases with many targets at least 4 arcs are needed for optimal plan quality., (Copyright © 2016 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.)

An atlas-based IMRT planning technique for prostate cancer was developed and evaluated. A multi-dose atlas was built based on the anatomy patterns of the patients, more specifically, the percent distance to the prostate and the concaveness angle formed by the seminal vesicles relative to the anterior-posterior axis. A 70-case dataset was classified using a k-medoids clustering analysis to recognize anatomy pattern variations in the dataset. The best classification, defined by the number of classes or medoids, was determined by the largest value of the average silhouette width. Reference plans from each class formed a multi-dose atlas. The atlas-guided planning (AGP) technique started with matching the new case anatomy pattern to one of the reference cases in the atlas; then a deformable registration between the atlas and new case anatomies transferred the dose from the atlas to the new case to guide inverse planning with full automation. 20 additional clinical cases were re-planned to evaluate the AGP technique. Dosimetric properties between AGP and clinical plans were evaluated. The classification analysis determined that the 5-case atlas would best represent anatomy patterns for the patient cohort. AGP took approximately 1 min on average (corresponding to 70 iterations of optimization) for all cases. When dosimetric parameters were compared, the differences between AGP and clinical plans were less than 3.5%, albeit some statistical significances observed: homogeneity index (p  >  0.05), conformity index (p  <  0.01), bladder gEUD (p  <  0.01), and rectum gEUD (p  =  0.02). Atlas-guided treatment planning is feasible and efficient. Atlas predicted dose can effectively guide the optimizer to achieve plan quality comparable to that of clinical plans.

Increased interest regarding sensitivity of pre-treatment intensity modulated radiotherapy and volumetric modulated arc radiotherapy (VMAT) quality assurance (QA) to delivery errors has led to the development of dose-volume histogram (DVH) based analysis. This paradigm shift necessitates a change in the acceptance criteria and action tolerance for QA. Here we present a knowledge based technique to objectively quantify degradations in DVH for prostate radiotherapy. Using machine learning, organ-at-risk (OAR) DVHs from a population of 198 prior patients' plans were adapted to a test patient's anatomy to establish patient-specific DVH ranges. This technique was applied to single arc prostate VMAT plans to evaluate various simulated delivery errors: systematic single leaf offsets, systematic leaf bank offsets, random normally distributed leaf fluctuations, systematic lag in gantry angle of the mutli-leaf collimators (MLCs), fluctuations in dose rate, and delivery of each VMAT arc with a constant rather than variable dose rate.Quantitative Analyses of Normal Tissue Effects in the Clinic suggests V75Gy dose limits of 15% for the rectum and 25% for the bladder, however the knowledge based constraints were more stringent: 8.48 ± 2.65% for the rectum and 4.90 ± 1.98% for the bladder. 19 ± 10 mm single leaf and 1.9 ± 0.7 mm single bank offsets resulted in rectum DVHs worse than 97.7% (2σ) of clinically accepted plans. PTV degradations fell outside of the acceptable range for 0.6 ± 0.3 mm leaf offsets, 0.11 ± 0.06 mm bank offsets, 0.6 ± 1.3 mm of random noise, and 1.0 ± 0.7° of gantry-MLC lag.Utilizing a training set comprised of prior treatment plans, machine learning is used to predict a range of achievable DVHs for the test patient's anatomy. Consequently, degradations leading to statistical outliers may be identified. A knowledge based QA evaluation enables customized QA criteria per treatment site, institution and/or physician and can often be more sensitive to errors than criteria based on organ complication rates.

A recent publication indicated that the patient anatomical feature (PAF) model was capable of predicting optimal objectives based on past experience. In this study, the benefits of IMRT optimization using PAF-predicted objectives as guidance for prostate were evaluated. Three different optimization methods were compared.1) Expert Plan: Ten prostate cases (16 plans) were planned by an expert planner using conventional trial-and-error approach started with institutional modified OAR and PTV constraints. Optimization was stopped at 150 iterations and that plan was saved as Expert Plan. 2) Clinical Plan: The planner would keep working on the Expert Plan till he was satisfied with the dosimetric quality and the final plan was referred to as Clinical Plan. 3) PAF Plan: A third sets of plans for the same ten patients were generated fully automatically using predicted DVHs as guidance. The optimization was based on PAF-based predicted objectives, and was continued to 150 iterations without human interaction. DMAX and D98% for PTV, DMAX for femoral heads, DMAX, D10cc, D25%/D17%, and D40% for bladder/rectum were compared. Clinical Plans are further optimized with more iterations and adjustments, but in general provided limited dosimetric benefits over Expert Plans. PTV D98% agreed within 2.31% among Expert, Clinical, and PAF plans. Between Clinical and PAF Plans, differences for DMAX of PTV, bladder, and rectum were within 2.65%, 2.46%, and 2.20%, respectively. Bladder D10cc was higher for PAF but &lt; 1.54% in general. Bladder D25% and D40% were lower for PAF, by up to 7.71% and 6.81%, respectively. Rectum D10cc, D17%, and D40% were 2.11%, 2.72%, and 0.27% lower for PAF, respectively. DMAX for femoral heads were comparable (&lt; 35 Gy on average). Compared to Clinical Plan (Primary + Boost), the average optimization time for PAF plan was reduced by 5.2 min on average, with a maximum reduction of 7.1min. Total numbers of MUs per plan for PAF Plans were lower than Clinical Plans, indicating better delivery efficiency. The PAF-guided planning process is capable of generating clinical-quality prostate IMRT plans with no human intervention. Compared to manual optimization, this automatic optimization increases planning and delivery efficiency, while maintainingplan quality.

The purpose of this study was to compare dosimetric parameters of treatment plans among four techniques for preoperative single-fraction partial breast radiotherapy in order to select an optimal treatment technique. The techniques evaluated were noncoplanar 3D conformal radiation therapy (3D CRT), noncoplanar intensity-modulated radiation therapy (IMRTNC), coplanar IMRT (IMRTCO), and volumetric-modulated arc therapy (VMAT). The planning CT scans of 16 patients in the prone position were used in this study, with the single-fraction prescription doses of 15 Gy for the first eight patients and 18 Gy for the remaining eight patients. Six (6) MV photon beams were designed to avoid the heart and contralateral breast. Optimization for IMRT and VMAT was performed to reduce the dose to the skin and normal breast. All plans were normalized such that 100% of the prescribed dose covered greater than 95% of the clinical target volume (CTV) consisting of gross tumor volume (GTV) plus 1.5 cm margin. Mean homogeneity index (HI) was the lowest (1.05 ± 0.02) for 3D CRT and the highest (1.11 ± 0.04) for VMAT. Mean conformity index (CI) was the lowest (1.42 ± 0.32) for IMRTNC and the highest (1.60 ± 0.32) for VMAT. Mean of the maximum point dose to skin was the lowest (73.7 ± 11.5%) for IMRTNC and the highest (86.5 ± 6.68%) for 3D CRT. IMRTCO showed very similar HI, CI, and maximum skin dose to IMRTNC (differences &lt;1%). The estimated mean treatment delivery time, excluding the time spent for patient positioning and imaging, was 7.0 ± 1.0, 8.3 ± 1.1, 9.7 ± 1.0, and 11.0 ± 1.5min for VMAT, IMRTCO, IMRTNC and 3D CRT, respectively. In comparison of all four techniques for preoperative single-fraction partial breast radiotherapy, we can conclude that noncoplanar or coplanar IMRT were optimal in this study as IMRT plans provided homogeneous and conformal target coverage, skin sparing, and relatively short treatment delivery time.

The purpose of this study was to evaluate the effect of dose calculation accuracy and the use of an intermediate dose calculation step during the optimization of intensity-modulated radiation therapy (IMRT) planning on the final plan quality for lung cancer patients. This study included replanning for 11 randomly selected free-breathing lung IMRT plans. The original plans were optimized using a fast pencil beam convolution algorithm. After optimization, the final dose calculation was performed using the analytical anisotropic algorithm (AAA). The Varian Treatment Planning System (TPS) Eclipse v11, includes an option to perform intermediate dose calculation during optimization using the AAA. The new plans were created using this intermediate dose calculation during optimization with the same planning objectives and dose constraints as in the original plan. Differences in dosimetric parameters for the planning target volume (PTV) dose coverage, organs-at-risk (OARs) dose sparing, and the number of monitor units (MU) between the original and new plans were analyzed. Statistical significance was determined with a p-value of less than 0.05. All plans were normalized to cover 95% of the PTV with the prescription dose. Compared with the original plans, the PTV in the new plans had on average a lower maximum dose (69.45 vs. 71.96Gy, p = 0.005), a better homogeneity index (HI) (0.08 vs. 0.12, p = 0.002), and a better conformity index (CI) (0.69 vs. 0.59, p = 0.003). In the new plans, lung sparing was increased as the volumes receiving 5, 10, and 30 Gy were reduced when compared to the original plans (40.39% vs. 42.73%, p = 0.005; 28.93% vs. 30.40%, p = 0.001; 14.11%vs. 14.84%, p = 0.031). The volume receiving 20 Gy was not significantly lower (19.60% vs. 20.38%, p = 0.052). Further, the mean dose to the lung was reduced in the new plans (11.55 vs. 12.12 Gy, p = 0.024). For the esophagus, the mean dose, the maximum dose, and the volumes receiving 20 and 60 Gy were lower in the new plans than in the original plans (17.91 vs. 19.24 Gy, p = 0.004; 57.32vs. 59.81 Gy, p = 0.020; 39.34% vs. 41.59%, p = 0.097; 12.56%vs. 15.35%, p = 0.101). For the heart, the mean dose, the maximum dose, and the volume receiving 40 Gy were also lower in new plans (11.07 vs. 12.04 Gy, p = 0.007; 56.41 vs. 57.7 Gy, p = 0.027; 7.16% vs. 9.37%, p= 0.012). The maximum dose to the spinal cord in the new plans was significantly lower than in the original IMRT plans (29.1 vs. 31.39Gy, p = 0.014). Difference in MU between the IMRT plans was not significant (1216.90 vs. 1198.91, p = 0.328). In comparison to the original plans, the number of iterations needed to meet the optimization objectives in the new plans was reduced by a factor of 2 (2-3 vs. 5-6 iterations). Further, optimization was 30% faster corresponding to an average time savings of 10-15 min for the reoptimized plans. Accuracy of the dose calculation algorithm during optimization has an impact on planning efficiency, as well as on the final plan dosimetric quality. For lung IMRT treatment planning, utilizing the intermediate dose calculation during optimization is feasible for dose homogeneity improvement of the PTV and for improvement of optimization efficiency.

The purpose is to dosimetrically compare the following 3 delivery techniques: 3-dimensional conformal radiation therapy (3D-CRT), intensity-modulated arc therapy (IMRT), and volumetric-modulated arc therapy (V-MAT) in the treatment of accelerated partial-breast irradiation (APBI). Overall, 16 patients with T1/2N0 breast cancer were treated with 3D-CRT (multiple, noncoplanar photon fields) on the RTOG 0413 partial-breast trial. These cases were subsequently replanned using static gantry IMRT and V-MAT technology to understand dosimetric differences among these 3 techniques. Several dosimetric parameters were used in plan quality evaluation, including dose conformity index (CI) and dose-volume histogram analysis of normal tissue coverage. Quality assurance studies including gamma analysis were performed to compare the measured and calculated dose distributions. The IMRT and V-MAT plans gave more conformal target dose distributions than the 3D-CRT plans (p < 0.05 in CI). The volume of ipsilateral breast receiving 5 and 10Gy was significantly less using the V-MAT technique than with either 3D-CRT or IMRT (p < 0.05). The maximum lung dose and the ipsilateral lung volume receiving 10 (V10) or 20Gy (V20) were significantly less with both V-MAT and IMRT (p < 0.05). The IMRT technique was superior to 3D-CRT and V-MAT of low dose distributions in ipsilateral lung (p < 0.05 in V5 and D5). The total mean monitor units (MUs) for V-MAT (621.0 ± 111.9) were 12.2% less than those for 3D-CRT (707.3 ± 130.9) and 46.5% less than those for IMRT (1161.4 ± 315.6) (p < 0.05). The average machine delivery time was 1.5 ± 0.2 minutes for the V-MAT plans, 7.0 ± 1.6 minutes for the 3D-CRT plans, and 11.5 ± 1.9 minutes for the IMRT plans, demonstrating much less delivery time for V-MAT. Based on this preliminary study, V-MAT and IMRT techniques offer improved dose conformity as compared with 3D-CRT techniques without increasing dose to the ipsilateral lung. In terms of MU and delivery time, V-MAT is significantly more efficient for APBI than for conventional 3D-CRT and static-beam IMRT., (Copyright © 2014 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.)

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 physician's 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.

Volumetric modulated arc therapy (VMAT) is a relatively new treatment modality for dynamic photon radiation therapy. Pre-treatment quality assurance (QA) is necessary and many efforts have been made to apply electronic portal imaging device (EPID)-based IMRT QA methods to VMAT. It is important to verify the gantry rotation speed during delivery as this is a new variable that is also modulated in VMAT. In this paper, we present a new technique to perform VMAT QA using an EPID. The method utilizes EPID cine mode and was tested on Varian TrueBeam in research mode. The cine images were acquired during delivery and converted to dose matrices after profile correction and dose calibration. A sub-arc corresponding to each cine image was extracted from the original plan and its portal image prediction was calculated. Several analyses were performed including 3D γ analysis (2D images + gantry angle axis), 2D γ analysis, and other statistical analyses. The method was applied to 21 VMAT photon plans of 3 photon energies. The accuracy of the cine image information was investigated. Furthermore, this method's sensitivity to machine delivery errors was studied. The pass rate (92.8 ± 1.4%) for 3D γ analysis was comparable to those from Delta(4) system (99.9 ± 0.1%) under similar criteria (3%, 3 mm, 5% threshold and 2° angle to agreement) at 6 MV. The recorded gantry angle and start/stop MUs were found to have sufficient accuracy for clinical QA. Machine delivery errors can be detected through combined analyses of 3D γ, gantry angle, and percentage dose difference. In summary, we have developed and validated a QA technique that can simultaneously verify the gantry angle and delivered MLC fluence for VMAT treatment.This technique is efficient and its accuracy is comparable to other QA methods.

Background and Purpose: To report single institution's IGRT and dosimetry analysis on the 37 Gy/5 fraction prostate SBRT clinical trial., Materials/methods: The IRB (Duke University Medical Center) approved clinical trial has treated 28 patients with stage T1-T2c prostate cancer with a regimen of 37 Gy in 5 fractions using IMRT and IGRT protocols since 2009. The clinical trial protocol requires CT/MRI imaging for the prostate delineation; a margin of 3 mm in posterior direction and 5 mm elsewhere for planning target volume (PTV); and strict dose constraints for primary organs-at-risks (OARs) including the bladder, the rectum, and the femoral heads. Rigid IGRT process is also an essential part of the protocol. Precise patient and prostate positioning and dynamic tracking of prostate motion are performed with electromagnetic localization device (Calypso) and on-board imaging (OBI) system. Initial patient and target alignment is performed based on fiducials with OBI imaging system and Calypso system. Prior to treatment, cone-beam CT (CBCT) is performed for soft tissue alignment verification. During treatment, per-beam corrections for target motion using translational couch movements is performed before irradiating each field, based on electromagnetic localization or on-board imaging localization. Dosimetric analysis on target coverage and OAR sparing is performed based on key DVH parameters corresponding to protocol guidance. IGRT analysis is focused on the average frequency and magnitude of corrections during treatment, and overall intra-fractional target drift. A margin value is derived using actual target motion data and the margin recipe from Van Herk et al., and is compared to the current one in practice. In addition, cumulative doses with and without per-beam IGRT corrections are compared to assess the benefit of online IGRT., Results: 1. No deviation has been found in 10 of 14 dosimetric constraints, with minor deviations in the rest 4 constraints.2. Online IGRT techniques including Calypso, OBI and CBCT supplement each other to create an effective and reliable system on tracking target and correcting intra-fractional motion.3. On average ½ corrections have been performed per fraction, with magnitude of (0.22 ± 0.11) cm. Average target drift magnitude is (0.7 ± 1.3) mm in one direction during each fraction.4. Benefit from per-beam correction in overall review is small: most differences from no correction are < 0.1 Gy for PTV D1cc/Dmean and < 1%/1.5 cc for OAR parameters. Up to 1.5 Gy reduction was seen in PTV D99% without online correction. Largest differences for OARs are -4.1 cc and +1.6 cc in the V50% for the bladder and the rectum, respectively. However, online IGRT helps to catch unexpected significant target motion.5. Margin derived from actual target motion is 2.5 mm isotropic, consist with current practice., Conclusions: Clinical experience of the 37 Gy/5-fraction prostate SBRT from a single institution is reported. Dosimetric analysis demonstrated excellent target coverage and OAR sparing for our first 28 patients in this trial. Online IGRT techniques implemented are both effective and reliable. Per-beam correction in general provides a small benefit in dosimetry. Target motion measured by online localization devices confirms that current margin selection is adequate.

Purpose: Intensity modulated radiation therapy (IMRT) treatment planning can have wide variation among different treatment centers. We propose a system to leverage the IMRT planning experience of larger institutions to automatically create high-quality plans for outside clinics. We explore feasibility by generating plans for patient datasets from an outside institution by adapting plans from our institution., Methods and Materials: A knowledge database was created from 132 IMRT treatment plans for prostate cancer at our institution. The outside institution, a community hospital, provided the datasets for 55 prostate cancer cases, including their original treatment plans. For each "query" case from the outside institution, a similar "match" case was identified in the knowledge database, and the match case's plan parameters were then adapted and optimized to the query case by use of a semiautomated approach that required no expert planning knowledge. The plans generated with this knowledge-based approach were compared with the original treatment plans at several dose cutpoints., Results: Compared with the original plan, the knowledge-based plan had a significantly more homogeneous dose to the planning target volume and a significantly lower maximum dose. The volumes of the rectum, bladder, and femoral heads above all cutpoints were nominally lower for the knowledge-based plan; the reductions were significantly lower for the rectum. In 40% of cases, the knowledge-based plan had overall superior (lower) dose-volume histograms for rectum and bladder; in 54% of cases, the comparison was equivocal; in 6% of cases, the knowledge-based plan was inferior for both bladder and rectum., Conclusions: Knowledge-based planning was superior or equivalent to the original plan in 95% of cases. The knowledge-based approach shows promise for homogenizing plan quality by transferring planning expertise from more experienced to less experienced institutions., (Copyright © 2013 Elsevier Inc. All rights reserved.)

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 R(2) 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.

Purpose: To explore an effective and efficient end-to-end patient-specific quality-assurance (QA) protocol for volumetric modulated arc radiotherapy (VMAT) and to evaluate the suitability of a stationary radiotherapy QA device (two-dimensional [2D] ion chamber array) for VMAT QA., Methods and Materials: Three methods were used to analyze 39 VMAT treatment plans for brain, spine, and prostate: ion chamber (one-dimensional absolute, n = 39), film (2D relative, coronal/sagittal, n = 8), and 2D ion chamber array (ICA, 2D absolute, coronal/sagittal, n = 39) measurements. All measurements were compared with the treatment planning system dose calculation either via gamma analysis (3%, 3- to 4-mm distance-to-agreement criteria) or absolute point dose comparison. The film and ion chamber results were similarly compared with the ICA measurements., Results: Absolute point dose measurements agreed well with treatment planning system computed doses (ion chamber: median deviation, 1.2%, range, -0.6% to 3.3%; ICA: median deviation, 0.6%, range, -1.8% to 2.9%). The relative 2D dose measurements also showed good agreement with computed doses (>93% of pixels in all films passing gamma, >90% of pixels in all ICA measurements passing gamma). The ICA relative dose results were highly similar to those of film (>90% of pixels passing gamma). The coronal and sagittal ICA measurements were statistically indistinguishable by the paired t test with a hypothesized mean difference of 0.1%. The ion chamber and ICA absolute dose measurements showed a similar trend but had disparities of 2-3% in 18% of plans., Conclusions: After validating the new VMAT implementation with ion chamber, film, and ICA, we were able to maintain an effective yet efficient patient-specific VMAT QA protocol by reducing from five (ion chamber, film, and ICA) to two measurements (ion chamber and single ICA) per plan. The ICA (Matrixx®, IBA Dosimetry) was validated for VMAT QA, but ion chamber measurements are recommended for absolute dose comparison until future developments correct the ICA angular dependence., (Copyright © 2012 Elsevier Inc. All rights reserved.)

We conducted a planning study to compare Varian's RapidArc (RA) and helical TomoTherapy (HT) for the treatment of pancreatic cancer. Three intensity-modulated radiotherapy (IMRT) plans were generated for 8 patients with pancreatic cancer: one using HT with 6-MV beam (Plan&#95;(HT6)), one using single-arc RA with 6-MV beam (Plan&#95;(RA6)), and one using single-arc RA with 15-MV beam (Plan&#95;(RA15)). Dosimetric indices including high/low conformality index (CI(100%)/CI(50%)), heterogeneity index (HI), monitor units (MUs), and doses to organs at risk (OARs) were compared. The mean CI(100%) was statistically equivalent with respect to the 2 treatment techniques, as well as beam energy (0.99, 1.01, and 1.02 for Plan&#95;(HT6), Plan&#95;(RA6), and Plan&#95;(RA156,) respectively). The CI(50%) and HI were improved in both RA plans over the HT plan. The RA plans significantly reduced MU (MU(RA6) = 697, MU(RA15) = 548) compared with HT (MU(HT6) = 6177, p = 0.008 in both cases). The mean maximum cord dose was decreased from 29.6 Gy in Plan&#95;(HT6) to 21.6 Gy (p = 0.05) in Plan&#95;(RA6) and 21.7 Gy (p = 0.04) in Plan&#95;(RA15). The mean bowel dose decreased from 17.2 Gy in Plan&#95;(HT6) to 15.2 Gy (p = 0.03) in Plan&#95;(RA6) and 15.0 Gy (p = 0.03) Plan&#95;(RA15). The mean liver dose decreased from 8.4 Gy in Plan&#95;(HT6) to 6.3 Gy (p = 0.04) in Plan&#95;(RA6) and 6.2 Gy in Plan&#95;(RA15). Variations of the mean dose to the duodenum, kidneys, and stomach were statistically insignificant. RA and HT can both deliver conformal dose distributions to target volumes while limiting the dose to surrounding OARs in the treatment of pancreatic cancer. Dosimetric advantages might be gained by using RA over HT by reducing the dose to OARs and total MUs used for treatment., (Copyright © 2011 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.)

The purpose of this study was to investigate the accuracy of motion tracking and radiation delivery control of integrated gating systems on a Novalis Tx system. The study was performed on a Novalis Tx system, which is equipped with Varian Real-time Position Management (RPM) system, and BrainLAB ExacTrac gating systems. In this study, the two systems were assessed on accuracy of both motion tracking and radiation delivery control. To evaluate motion tracking, two artificial motion profiles and five patients' respiratory profiles were used. The motion trajectories acquired by the two gating systems were compared against the references. To assess radiation delivery control, time delays were measured using a single-exposure method. More specifically, radiation is delivered with a 4 mm diameter cone within the phase range of 10%-45% for the BrainLAB ExacTrac system, and within the phase range of 0%-25% for the Varian RPM system during expiration, each for three times. Radiochromic films were used to record the radiation exposures and to calculate the time delays. In the work, the discrepancies were quantified using the parameters of mean and standard deviation (SD). Pearson's product-moment correlational analysis was used to test correlation of the data, which is quantified using a parameter of r. The trajectory profiles acquired by the gating systems show good agreement with those reference profiles. A quantitative analysis shows that the average mean discrepancies between BrainLAB ExacTrac system and known references are 1.5 mm and 1.9 mm for artificial and patient profiles, with the maximum motion amplitude of 28.0 mm. As for the Varian RPM system, the corresponding average mean discrepancies are 1.1 mm and 1.7 mm for artificial and patient profiles. With the proposed single-exposure method, the time delays are found to be 0.20 ± 0.03 seconds and 0.09 ± 0.01 seconds for BrainLAB ExacTrac and Varian RPM systems, respectively. The results indicate the systems can track motion and control radiation delivery with reasonable accuracy. The proposed single-exposure method has been demonstrated to be feasible in measuring time delay efficiently.

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 approximately 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.

The purpose of this investigation was to study apparatus-dependent dose distribution differences specific to spine stereotactic body radiotherapy (SBRT) treatment planning. This multi-institutional study was performed evaluating an image-guided robotic radiosurgery system (CK), intensity modulated protons (IMP), multileaf collimator (MLC) fixed-field IMRT with 5 mm (11 field), 4 mm (9 field), and 2.5 mm (8- and 9-field) leaf widths and intensity modulated volumetric arc therapy (IMVAT) with a 2.5 mm MLC. Treatment plans were systematically developed for targets consisting of one, two and three consecutive thoracic vertebral bodies (VBs) with the esophagus and spinal cord contoured as the organs at risk. It was found that all modalities achieved acceptable treatment planning constraints. However, following normalization fixed field IMRT with a 2.5 mm MLC, IMVAT and IMP systems yielded the smallest ratio of maximum dose divided by the prescription dose (MD/PD) for one-, two- and three-VB PTVs (ranging from 1.1-1.16). The 2.5 mm MLC 9-field IMRT, IMVAT and CK plans resulted in the least dose to 0.1 cc volumes of spinal cord and esophagus. CK plans had the greatest degree of target dose inhomogeneity. As the level of complexity increased with an increasing number of vertebral bodies, distinct apparatus features such as the use of a high number of beams and a finer leaf size MLC were favored. Our study quantified apparatus-dependent dose-distribution differences specific to spine SBRT given strict, but realistic, constraints and highlights the need to benchmark physical dose distributions for multi-institutional clinical trials.

Purpose: To investigate the technical feasibility of volumetric modulated arc therapy (V-MAT) in the delivery of partial breast irradiation (PBI)., Methods and Materials: V-MAT and the standard, three-dimensional conformal radiotherapy (3D-CRT), were compared retrospectively in 8 patients previously treated with PBI. These patients' plans were replanned with a single partial arc using V-MAT that included partial blocking to minimize normal tissue dose. Dosimetric parameters were calculated to evaluate plan quality. Quality assurance studies included verifying both the point and the multiple planar doses. Total monitor units and delivery time were also evaluated, and collision clearance was analyzed., Results: Volumes of ipsilateral lung irradiated to 10 Gy (V10) and 20 Gy (V20) by V-MAT were significantly less than those of 3D-CRT (p = 0.03 for V10 and p = 0.025 for V20). The volume of ipsilateral breast irradiated to 5 Gy was significantly less by using V-MAT than with 3D-CRT (p = 0.02), with a ratio of integrated dose of <1.00. The total mean monitor units (489 +/- 38) for V-MAT were significantly less than those for 3D-CRT (634 +/- 123) (p = 0.017), with a 23% reduction. The average machine delivery time was 1.21 +/- 0.10 min for the V-MAT plans and 6.28 +/- 1.40 min for the 3D-CRT plans, resulting in a reduction factor of 80.1%. The conformity indexes were 1.3 in the V-MAT plans and 1.5 in the 3D-CRT plans (p = 0.102)., Conclusions: V-MAT technology is feasible for PBI patients. Compared to a conventional 3D-CRT technique, it is more efficient, offers equivalent or better dose conformity, delivers lower doses to the ipsilateral lung and breast, and may potentially reduce intrafractional motion., (Published by Elsevier Inc.)

Purpose: Dosimetric results and treatment delivery efficiency of RapidArc plans to those of conventional intensity-modulated radiotherapy (IMRT) plans were compared using the Eclipse treatment planning system for high-risk prostate cancer., Materials and Methods: This study included 10 patients. The primary planning target volume (PTV(P)) contained prostate, seminal vesicles, and pelvic lymph nodes with a margin. The boost PTV (PTV(B)) contained prostate and seminal vesicles with a margin. The total prescription dose was 75.6 Gy (46.8 Gy to PTV(P) and an additional 28.8 Gy to PTV(B); 1.8 Gy/fraction). Three plans were generated for each PTV: Multiple-field IMRT, one-arc RapidArc (1ARC), and two-arc RapidArc (2ARC)., Results: In the primary IMRT with PTV(P), average mean doses to bladder, rectum and small bowel were lower by 5.9%, 7.7% and 4.3%, respectively, than in the primary 1ARC and by 3.6%, 4.8% and 3.1%, respectively, than in the primary 2ARC. In the boost IMRT with PTV(B), average mean doses to bladder and rectum were lower by 2.6% and 4.8% than with the boost 1ARC and were higher by 0.6% and 0.2% than with the boost 2ARC. Integral doses were 7% to 9% higher with RapidArc than with IMRT for both primary and boost plans. Treatment delivery time was reduced by 2-7 minutes using RapidArc., Conclusion: For PTVs including prostate, seminal vesicles, and lymph nodes, IMRT performed better in dose sparing for bladder, rectum, and small bowel than did RapidArc. For PTVs including prostate and seminal vesicles, RapidArc with two arcs provided plans comparable to those for IMRT. The treatment delivery is more efficient with RapidArc., (Copyright (c) 2010 Elsevier Inc. All rights reserved.)

The aim of this study was to explore similarities between intensity-modulated radiotherapy (IMRT) and intensity-modulated arc therapy (IMAT) techniques in the context of the number of multi-leaf collimator (MLC) segments required to achieve plan objectives, the major factor influencing plan quality. Three clinical cases with increasing complexity were studied: (a) prostate only, (b) prostate and seminal vesicles and (c) prostate and pelvic lymph nodes. Initial 'gold-standard' plans with the maximum possible organ-at-risk sparing were generated for all three cases. For each case, multiple IMRT and IMAT plans were generated with varying intensity levels (IMRT) and arc control points (IMAT), which translate into varying MLC segments in both modalities. The IMAT/IMRT plans were forced to mimic the organ-at-risk sparing and target coverage in the gold-standard plans, thereby only allowing the target dose inhomogeneity to be variable. A higher target dose inhomogeneity (quantified as D5--dose to the highest 5% of target volume) implies that the plan is less capable of modulation. For each case, given a similar number of MLC segments, both IMRT and IMAT plans exhibit similar target dose inhomogeneity, indicating that there is no difference in their ability to provide dose painting. Target dose inhomogeneity remained approximately constant with decreasing segments, but sharply increased below a specific critical number of segments (70, 100, 110 for cases a, b, c, respectively). For the cases studied, IMAT and IMRT plans are similar in their dependence on the number of MLC segments. A minimum critical number of segments are required to ensure adequate plan quality. Future studies are needed to establish the range of minimum critical number of segments for different treatment sites and target-organ geometries.

Purpose: This clinical study evaluates the feasibility of using volumetric arc-modulated treatment (VMAT) for spine stereotactic body radiotherapy (SBRT) to achieve highly conformal dose distributions that spare adjacent organs at risk (OAR) with reduced treatment time., Methods and Materials: Ten spine SBRT patients were studied retrospectively. The intensity-modulated radiotherapy (IMRT) and VMAT plans were generated using either one or two arcs. Planning target volume (PTV) dose coverage, OAR dose sparing, and normal tissue integral dose were measured and compared. Differences in treatment delivery were also analyzed., Results: The PTV DVHs were comparable between VMAT and IMRT plans in the shoulder (D(99%)-D(90%)), slope (D(90%)-D(10%)), and tail (D(10%)-D(1%)) regions. Only VMAT(2arc) had a better conformity index than IMRT (1.09 vs. 1.15, p = 0.007). For cord sparing, IMRT was the best, and VMAT(1arc) was the worst. Use of IMRT achieved greater than 10% more D(1%) sparing for six of 10 cases and 7% to 15% more D(10%) sparing over the VAMT(1arc). The differences between IMRT and VAMT(2arc) were smaller and statistically nonsignificant at all dose levels. The differences were also small and statistically nonsignificant for other OAR sparing. The mean monitor units (MUs) were 8711, 7730, and 6317 for IMRT, VMAT(1arc), and VMAT(2arc) plans, respectively, with a 26% reduction from IMRT to VMAT(2arc). The mean treatment time was 15.86, 8.56, and 7.88 min for IMRT, VMAT(1arc,) and VMAT(2arc). The difference in integral dose was statistically nonsignificant., Conclusions: Although VMAT provided comparable PTV coverage for spine SBRT, 1arc showed significantly worse spinal cord sparing compared with IMRT, whereas 2arc was comparable to IMRT. Treatment efficiency is substantially improved with the VMAT.

Despite the widespread use of intensity-modulated radiation therapy (IMRT) for approximately a decade, a lack of adequate guidelines for documenting these treatments persists. Proper IMRT treatment documentation is necessary for accurate reconstruction of prior treatments when a patient presents with a marginal recurrence. This is especially crucial when the follow-up care is managed at a second treatment facility not involved in the initial IMRT treatment. To address this issue, an American Society for Radiation Oncology (ASTRO) workgroup within the American ASTRO Radiation Physics Committee was formed at the request of the ASTRO Research Council to develop a set of recommendations for documenting IMRT treatments. This document provides a set of comprehensive recommendations for documenting IMRT treatments, as well as image-guidance procedures, with example forms provided.

In inverse planning for intensity-modulated radiation therapy (IMRT), the dose specification and related weighting factor of an objective function for involved organs is usually predefined by a single value and then iteratively optimized, subject to a set of dose-volume constraints. Because the actual dose distribution is essentially non-uniform and considerably affected by the geometric shape and distribution of the anatomic structures involved, the spatial information regarding those structures should be incorporated such that the predefined parameter distribution is made to approach the clinically expected distribution. Ideally, these parameter distributions should be predefined on a voxel basis in a manual method. However, such an approach is too time-consuming to be feasible in routine use. In the present study, we developed a computer-aided method to achieve the goal described above, producing a non-uniform parameter distribution based on spatial information about the anatomic structures involved. The method consists of two steps: Use distance transformation technique to calculate the distance distribution of the structures. Based on the distance distribution, produce the parameter distribution via a function guided by prior knowledge. We use two simulated cases to examine the effectiveness of the method. The results indicate that application of a non-uniform parameter distribution produced by distance transformation clearly improves dose-sparing of critical organs without compromising dose coverage of the planning target.

Purpose: High-precision intensity-modulated radiotherapy demands high patient positioning accuracy. On-board digital tomosynthesis (DTS) provides three-dimensional (3D) image guidance for daily positioning with a lower imaging dose, faster acquisition, and more geometric flexibility than 3D cone-beam computed tomography (CBCT). This clinical study evaluated DTS as a daily imaging technique for patient positioning and compared the results with 3D CBCT and two-dimensional (2D) radiography., Methods and Materials: Head and neck cancer patients undergoing intensity-modulated radiotherapy were studied. For each session, the patient was positioned using laser marks. On-board imaging data sets, including 2D kilovoltage radiographs, DTS, and CBCT, were obtained to measure the daily patient positioning variations. The mean and standard deviations of the positioning variations in the translational and rotational directions were calculated. The positioning differences among 2D radiography, DTS, and CBCT were analyzed., Results: Image data sets were collected from 65 treatment fractions for 10 patients. The systematic patient positioning variation was <0.10 cm and 1.0 degrees one dimensionally. The random variations were 0.27-0.34 cm in the translational and 0.93 degrees -1.99 degrees in the rotational direction. The mean vector isocenter variation was 0.48 cm. DTS with 40 degrees and 20 degrees scan angles in the coronal or sagittal directions yielded the same results for patient positioning. DTS performance was comparable to that of CBCT, with positioning differences of <0.1 cm and 0.5 degrees . The positioning difference between 2D radiography and DTS was approximately 0.1 cm and 0.2 cm in the vertical/longitudinal and lateral directions., Conclusion: Our results have demonstrated that DTS is a comparable 3D imaging technique to CBCT for daily patient positioning of head-and-neck patients as determined by manual registration of bony anatomy.

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.

Intensity-modulated photon radiation therapy (RT; IMRT) and proton therapy are advanced radiation technologies that permit improved conformation of radiation dose to target structures while limiting irradiation of surrounding normal tissues. Application of these technologies in the treatment of rectal and anal cancer is attractive, based on the potential reduction in radiation treatment toxicities that are frequently incurred in the pelvis and perineum. Furthermore, conformal RT might also allow for dose escalation to target areas, leading to improved tumor control. This review discusses the underlying principles of IMRT. In addition, the rationale and clinical data regarding the efficacy of radiation dose escalation for rectal and anal cancer will be highlighted, as well as tolerance of pelvic organs to RT and chemotherapy. Finally, preliminary results of IMRT in the treatment of lower gastrointestinal tract cancers will be reviewed. The potential and rationale for proton therapy in treatment of these malignancies are also discussed.

Purpose: Single photon emission computed tomography (SPECT) provides a map of the spatial distribution of lung perfusion. Thus, SPECT guidance can be used to divert dose away from higher-functioning lung, potentially reducing lung toxicity. We present a methodology for achieving this aim and test it in intensity-modulated radiotherapy (IMRT) treatment-planning., Methods and Materials: IMRT treatment plans were generated with and without SPECT guidance and compared for 5 patients. Healthy lung was segmented into four regions on the basis of SPECT intensity in the SPECT plan. Dose was sequentially allowed to the target via regions of increasing SPECT intensity. This process results in reduction of dose to functional lung, reflected in the dose-function histogram (DFH). The plans were compared using DFHs and F(20)/F(30) values (F(x) is the functional lung receiving dose above x Gy)., Results: In all cases, the SPECT-guided plan produced a more favorable DFH compared with the non-SPECT-guided plan. Additionally, the F(20) and F(30) values were reduced for all patients by an average of 13.6% +/- 5.2% and 10.5% +/- 5.8%, respectively. In all patients, DFHs of the two highest-functioning SPECT regions were reduced, whereas DFHs of the two lower-functioning regions were increased, illustrating the dose "give-take" between SPECT regions during redistribution., Conclusions: SPECT-guided IMRT shows potential for reducing the dose delivered to highly functional lung regions. This dose reduction could reduce the number of high-grade pneumonitis cases that develop after radiation treatment and improve patient quality of life.