Unlocking the adaptive advantage: correlation and machine learning classification to identify optimal online adaptive stereotactic partial breast candidates.

Objective.Online adaptive radiotherapy (OART) is a promising technique for delivering stereotactic accelerated partial breast irradiation (APBI), as lumpectomy cavities vary in location and size between simulation and treatment. However, OART is resource-intensive, increasing planning and treatment times and decreasing machine throughput compared to the standard of care (SOC). Thus, it is pertinent to identify high-yield OART candidates to best allocate resources.Approach.Reference plans (plans based on simulation anatomy), SOC plans (reference plans recalculated onto daily anatomy), and daily adaptive plans were analyzed for 31 sequential APBI targets, resulting in the analysis of 333 treatment plans. Spearman correlations between 22 reference plan metrics and 10 adaptive benefits, defined as the difference between mean SOC and delivered metrics, were analyzed to select a univariate predictor of OART benefit. A multivariate logistic regression model was then trained to stratify high- and low-benefit candidates.Main results.Adaptively delivered plans showed dosimetric benefit as compared to SOC plans for most plan metrics, although the degree of adaptive benefit varied per patient. The univariate model showed high likelihood for dosimetric adaptive benefit when the reference plan ipsilateral breast V15Gy exceeds 23.5%. Recursive feature elimination identified 5 metrics that predict high-dosimetric-benefit adaptive patients. Using leave-one-out cross validation, the univariate and multivariate models classified targets with 74.2% and 83.9% accuracy, resulting in improvement in per-fraction adaptive benefit between targets identified as high- and low-yield for 7/10 and 8/10 plan metrics, respectively.Significance.This retrospective, exploratory study demonstrated that dosimetric benefit can be predicted using only ipsilateral breast V15Gy on the reference treatment plan, allowing for a simple, interpretable model. Using multivariate logistic regression for adaptive benefit prediction led to increased accuracy at the cost of a more complicated model. This work presents a methodology for clinics wishing to triage OART resource allocation.

Order From Chaos: The Benefits of Standardized Nomenclature in Radiation Oncology.

Although standardization has been shown to improve patient safety and improve the efficiency of workflows, implementation of standards can take considerable effort and requires the engagement of all clinical stakeholders. Engaging team members includes increasing awareness of the proposed benefit of the standard, a clear implementation plan, monitoring for improvements, and open communication to support successful implementation. The benefits of standardization often focus on large institutions to improve research endeavors, yet all clinics can benefit from standardization to increase quality and implement more efficient or automated workflow. The benefits of nomenclature standardization for all team members and institution sizes, including success stories, are discussed with practical implementation guides to facilitate the adoption of standardized nomenclature in radiation oncology.

Prospective Evaluation of Automated Contouring for CT-Based Brachytherapy for Gynecologic Malignancies.

Purpose: The use of deep learning to auto-contour organs at risk (OARs) in gynecologic radiation treatment is well established. Yet, there is limited data investigating the prospective use of auto-contouring in clinical practice. In this study, we assess the accuracy and efficiency of auto-contouring OARs for computed tomography-based brachytherapy treatment planning of gynecologic malignancies. Methods and Materials: An inhouse contouring tool automatically delineated 5 OARs in gynecologic radiation treatment planning: the bladder, small bowel, sigmoid, rectum, and urethra. Accuracy of each auto-contour was evaluated using a 5-point Likert scale: a score of 5 indicated the contour could be used without edits, while a score of 1 indicated the contour was unusable. During scoring, automated contours were edited and subsequently used for treatment planning. Dice similarity coefficient, mean surface distance, 95% Hausdorff distance, Hausdorff distance, and dosimetric changes between original and edited contours were calculated. Contour approval time and total planning time of a prospective auto-contoured (AC) cohort were compared with times from a retrospective manually contoured (MC) cohort. Results: Thirty AC cases from January 2022 to July 2022 and 31 MC cases from July 2021 to January 2022 were included. The mean (±SD) Likert score for each OAR was the following: bladder 4.77 (±0.58), small bowel 3.96 (±0.91), sigmoid colon 3.92 (±0.81), rectum 4.6 (±0.71), and urethra 4.27 (±0.78). No ACs required major edits. All OARs had a mean Dice similarity coefficient > 0.86, mean surface distance < 0.48 mm, 95% Hausdorff distance < 3.2 mm, and Hausdorff distance < 10.32 mm between original and edited contours. There was no significant difference in dose-volume histogram metrics (D2.0 cc/D0.1 cc) between original and edited contours (P values > .05). The average time to plan approval in the AC cohort was 19% less than the MC cohort. (AC vs MC, 117.0 + 18.0 minutes vs 144.9 ± 64.5 minutes, P = .045). Conclusions: Automated contouring is useful and accurate in clinical practice. Auto-contouring OARs streamlines radiation treatment workflows and decreases time required to design and approve gynecologic brachytherapy plans.

Improved Dosimetry and Plan Quality for Accelerated Partial Breast Irradiation Using Online Adaptive Radiation Therapy: A Single Institutional Study.

Purpose: Accelerated partial breast irradiation (APBI) is an attractive treatment modality for eligible patients as it has been shown to result in similar local control and improved cosmetic outcomes compared with whole breast radiation therapy. The use of online adaptive radiation therapy (OART) for APBI is promising as it allows for a reduction of planning target volume margins because breast motion and lumpectomy cavity volume changes are accounted for in daily imaging. Here we present a retrospective, single-institution evaluation on the adequacy of kV-cone beam computed tomography (CBCT) OART for APBI treatments. Methods and Materials: Nineteen patients (21 treatment sites) were treated to 30 Gy in 5 fractions between January of 2022 and May of 2023. Time between simulation and treatment, change in gross tumor (ie, lumpectomy cavity) volume, and differences in dose volume histogram metrics with adaption were analyzed. The Wilcoxon paired, nonparametric test was used to test for dose volume histogram metric differences between the scheduled plans (initial plans recalculated on daily CBCT anatomy) and delivered plans, either the scheduled or adapted plan, which was reoptimized using daily anatomy. Results: Median (interquartile range) time from simulation to first treatment was 26 days (21-32 days). During this same time, median gross tumor volume reduction was 16.0% (7.3%-23.9%) relative to simulation volume. Adaptive treatments took 31.3 minutes (27.4-36.6 minutes) from start of CBCT to treatment session end. At treatment, the adaptive plan was selected for 86% (89/103) of evaluable fractions. In evaluating plan quality, 78% of delivered plans met all target, organs at risk, and conformity metrics evaluated, compared with 34% of scheduled plans. Conclusions: Use of OART for stereotactic linac-based APBI allowed for safe, high-quality treatments in this cohort of 21 treatment courses. Although treatment delivery times were longer than traditional stereotactic body treatments, there were notable improvements in plan quality for APBI using OART.

Automated evaluation for rapid implementation of knowledge-based radiotherapy planning models.

PURPOSE: Knowledge-based planning (KBP) offers the ability to predict dose-volume metrics based on information extracted from previous plans, reducing plan variability and improving plan quality. As clinical integration of KBP is increasing there is a growing need for quantitative evaluation of KBP models. A .NET-based application, RapidCompare, was created for automated plan creation and analysis of Varian RapidPlan models. METHODS: RapidCompare was designed to read calculation parameters and a list of reference plans. The tool copies the reference plan field geometry and structure set, applies the RapidPlan model, optimizes the KBP plan, and generates data for quantitative evaluation of dose-volume metrics. A cohort of 85 patients, divided into training (50), testing (10), and validation (25) groups, was used to demonstrate the utility of RapidCompare. After training and tuning, the KBP model was paired with three different optimization templates to compare various planning strategies in the validation cohort. All templates used the same set of constraints for the planning target volume (PTV). For organs-at-risk, the optimization template provided constraints using the whole dose-volume histogram (DVH), fixed-dose/volume points, or generalized equivalent uniform dose (gEUD). The resulting plans from each optimization approach were compared using DVH metrics. RESULTS: RapidCompare allowed for the automated generation of 75 total plans for comparison with limited manual intervention. In comparing optimization techniques, the Dose/Volume and Lines optimization templates generated plans with similar DVH metrics, with a slight preference for the Lines technique with reductions in heart V30Gy and spinal cord max dose. The gEUD model produced high target heterogeneity. CONCLUSION: Automated evaluation allowed for the exploration of multiple optimization templates in a larger validation cohort than would have been feasible using a manual approach. A final KBP model using line optimization objectives produced the highest quality plans without human intervention.

Evaluation and correlation of patient movement during online adaptive radiotherapy with CBCT and a surface imaging system.

PURPOSE: With the clinical implementation of kV-CBCT-based daily online-adaptive radiotherapy, the ability to monitor, quantify, and correct patient movement during adaptive sessions is paramount. With sessions lasting between 20-45 min, the ability to detect and correct for small movements without restarting the entire session is critical to the adaptive workflow and dosimetric outcome. The purpose of this study was to quantify and evaluate the correlation of observed patient movement with machine logs and a surface imaging (SI) system during adaptive radiation therapy. METHODS: Treatment machine logs and SGRT registration data log files for 1972 individual sessions were exported and analyzed. For each session, the calculated shifts from a pre-delivery position verification CBCT were extracted from the machine logs and compared to the SGRT registration data log files captured during motion monitoring. The SGRT calculated shifts were compared to the reported shifts of the machine logs for comparison for all patients and eight disease site categories. RESULTS: The average (±STD) net displacement of the SGRT shifts were 2.6 ± 3.4 mm, 2.6 ± 3.5 mm, and 3.0 ± 3.2 in the lateral, longitudinal, and vertical directions, respectively. For the treatment machine logs, the average net displacements in the lateral, longitudinal, and vertical directions were 2.7 ± 3.7 mm, 2.6 ± 3.7 mm, and 3.2 ± 3.6 mm. The average difference (Machine-SGRT) was -0.1 ± 1.8 mm, 0.2 ± 2.1 mm, and -0.5 ± 2.5 mm for the lateral, longitudinal, and vertical directions. On average, a movement of 5.8 ± 5.6 mm and 5.3 ± 4.9 mm was calculated prior to delivery for the CBCT and SGRT systems, respectively. The Pearson correlation coefficient between CBCT and SGRT shifts was r = 0.88. The mean and median difference between the treatment machine logs and SGRT log files was less than 1 mm for all sites. CONCLUSION: Surface imaging should be used to monitor and quantify patient movement during adaptive radiotherapy.

Understanding the Effect of Prescription Isodose in Single-Fraction Stereotactic Radiosurgery on Plan Quality and Clinical Outcomes for Solid Brain Metastases.

BACKGROUND AND OBJECTIVES: There is wide variation in treatment planning strategy for central nervous system (CNS) stereotactic radiosurgery. We sought to understand what relationships exist between intratumor maximum dose and local control (LC) or CNS toxicity, and dosimetric effects of constraining hotspots on plan quality of multiple metastases volumetric modulated arc therapy radiosurgery plans. METHODS: We captured brain metastases from 2015 to 2017 treated with single-isocenter volumetric modulated arc therapy radiosurgery. Included tumors received single-fraction stereotactic radiosurgery, had no previous surgery or radiation, and available follow-up imaging. Our criterion for local failure was 25% increase in tumor diameter on follow-up MRI or pathologic confirmation of tumor recurrence. We defined significant CNS toxicity as Radiation Therapy Oncology Group irreversible Grade 3 or higher. We performed univariate and multivariate analyses evaluating factors affecting LC. We examined 10 stereotactic radiosurgery plans with prescriptions of 18 Gy to all targets originally planned without constraints on the maximum dose within the tumor. We replanned each with a constraint of Dmax 120%. We compared V50%, mean brain dose, and Dmax between plans. RESULTS: Five hundred and thirty tumors in 116 patients were available for analysis. Median prescription dose was 18 Gy, and median prescription isodose line (IDL) was 73%. Kaplan-Meier estimate of 12-month LC only tumor volume (HR 1.43 [1.22-1.68] P < .001) was predictive of local failure on univariate analysis; prescription IDL and histology were not. In multivariate analysis, tumor volume impacted local failure (HR 1.43 [1.22-1.69] P < .001) but prescription IDL did not (HR 0.95 [0.86-1.05] P = .288). Only a single grade 3 and 2 grade 4 toxicities were observed; tumor volume was predictive of CNS toxicity (HR 1.58 [1.25-2.00]; P < .001), whereas prescription IDL was not (HR 1.01 [0.87-1.17] P = .940). CONCLUSION: The prescription isodose line had no impact on local tumor control or CNS toxicity. Penalizing radiosurgery hotspots resulted in worse radiosurgery plans with poorer gradient. Limiting maximum dose in gross tumor causes increased collateral exposure to surrounding tissue and should be avoided.

Benchmarking Automated Machine Learning-Enhanced Planning With Ethos Against Manual and Knowledge-Based Planning for Locally Advanced Lung Cancer.

Purpose: Currently, there is insufficient guidance for standard fractionation lung planning using the Varian Ethos adaptive treatment planning system and its unique intelligent optimization engine. Here, we address this gap in knowledge by developing a methodology to automatically generate high-quality Ethos treatment plans for locally advanced lung cancer. Methods and Materials: Fifty patients previously treated with manually generated Eclipse plans for inoperable stage IIIA-IIIC non-small cell lung cancer were included in this institutional review board-approved retrospective study. Fifteen patient plans were used to iteratively optimize a planning template for the Daily Adaptive vs Non-Adaptive External Beam Radiation Therapy With Concurrent Chemotherapy for Locally Advanced Non-Small Cell Lung Cancer: A Prospective Randomized Trial of an Individualized Approach for Toxicity Reduction (ARTIA-Lung); the remaining 35 patients were automatically replanned without intervention. Ethos plan quality was benchmarked against clinical plans and reoptimized knowledge-based RapidPlan (RP) plans, then judged using standard dose-volume histogram metrics, adherence to clinical trial objectives, and qualitative review. Results: Given equal prescription target coverage, Ethos-generated plans showed improved primary and nodal planning target volume V95% coverage (P < .001) and reduced lung gross tumor volume V5 Gy and esophagus D0.03 cc metrics (P ≤ .003) but increased mean esophagus and brachial plexus D0.03 cc metrics (P < .001) compared with RP plans. Eighty percent, 49%, and 51% of Ethos, clinical, and RP plans, respectively, were "per protocol" or met "variation acceptable" ARTIA-Lung planning metrics. Three radiation oncologists qualitatively scored Ethos plans, and 78% of plans were clinically acceptable to all reviewing physicians, with no plans receiving scores requiring major changes. Conclusions: A standard Ethos template produced lung radiation therapy plans with similar quality to RP plans, elucidating a viable approach for automated plan generation in the Ethos adaptive workspace.

Prostate Stereotactic Body Radiation Therapy With a Focal Simultaneous Integrated Boost: 5-Year Toxicity and Biochemical Recurrence Results From a Prospective Trial.

PURPOSE: Stereotactic body radiation therapy (SBRT) is increasingly used as a definitive treatment option for patients with prostate adenocarcinoma. The aim of this study was to assess the late toxicity, patient-reported quality of life outcomes, and biochemical recurrence rates after prostate SBRT with simultaneous integrated boost (SIB) targeting lesions defined by magnetic resonance imaging (MRI). METHODS AND MATERIALS: Patients were eligible if they had biopsy-proven low- or intermediate-risk prostate adenocarcinoma, one or more focal lesions on MRI, and an MRI-defined total prostate volume of <120 mL. All patients received SBRT delivered to the entire prostate to a dose of 36.25 Gy in 5 fractions with an SIB to the lesions seen on MRI to 40 Gy in 5 fractions. Late toxicity was defined as any possible treatment-related adverse event occurring after 3 months from the completion of SBRT. Patient-reported quality of life was ascertained using standardized patient surveys. RESULTS: A total of 26 patients were enrolled. Six patients (23.1%) had low-risk disease and 20 patients had intermediate-risk disease (76.9%). Seven patients (26.9%) received androgen deprivation therapy. Median follow-up was 59.5 months. No biochemical failures were observed. Three patients (11.5%) experienced late grade 2 genitourinary (GU) toxicity requiring cystoscopy, and 7 patients (26.9%) had late grade 2 GU toxicity requiring oral medications. Three patients (11.5%) had late grade 2 gastrointestinal toxicity characterized by hematochezia requiring colonoscopy and steroids per rectum. There were no grade 3 or higher toxicity events observed. The patient-reported quality-of-life metrics at the time of last follow-up were not significantly different than the pre-treatment baseline. CONCLUSIONS: The results of this study support that SBRT to the entire prostate to a dose of 36.25 Gy in 5 fractions with focal SIB to 40 Gy in 5 fractions has excellent biochemical control and is not associated with undue late gastrointestinal or GU toxicity or long-term quality of life decrement. Focal dose escalation with an SIB planning approach may be an opportunity to improve biochemical control while limiting dose to nearby organs at risk.

Commissioning and clinical evaluation of the IDENTIFYTM surface imaging system for frameless stereotactic radiosurgery.

PURPOSE: To commission and assess the clinical performance of a new commercial surface imaging (SI) system by analyzing intra-fraction motion from the initial cohort of patients treated with frameless stereotactic radiosurgery (fSRS). METHODS: The IDENTIFYTM SI system was commissioned for clinical use on an Edge (Varian Medical Systems, Palo Alto, CA) linear accelerator. All patients who received intracranial radiotherapy with HyperArcTM (Varian Medical Systems, Palo Alto, CA) were immobilized with the EncompassTM (Qfix, Avondale, PA) thermoplastic mask and monitored for intra-fraction motion with SI. IDENTIFYTM log files were correlated with trajectory log files to correlate treatment parameters with SI-reported offsets. IDENTIFYTM reported offsets were correlated with gantry and couch angles to assess system performance for obstructed and clear camera field of view. Data were stratified by race to evaluate performance differences due to skin tone. RESULTS: All commissioning data were found to meet recommended tolerances. IDENTIFYTM was used to monitor intra-fraction motion on 1164 fractions from 386 patients. The median magnitude of translational SI reported offsets at the end of treatment was 0.27 mm. SI reported offsets were shown to increase when camera pods are blocked by the gantry with larger increases seen at non-zero couch angles. With camera obstruction, the median magnitude of the SI reported offset was 0.50 and 0.80 mm for White and Black patients, respectively. CONCLUSIONS: IDENTIFYTM performance during fSRS is comparable to other commercially available SI systems where offsets are shown to increase at non-zero couch angles and during camera pod blockage.

Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer.

PURPOSE: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships. METHODS AND MATERIALS: The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs. The Big Data Science Committee adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community. RESULTS: We developed the Operational Ontology for Oncology (O3), which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, and the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to 4 constituencies: device manufacturers, centers of clinical care, researchers, and professional societies. CONCLUSIONS: O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used to create large, representative, findable, accessible, interoperable, and reusable data sets to support the scientific objectives of grant programs. The construction of comprehensive "real-world" data sets and application of advanced analytical techniques, including artificial intelligence, holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative data sets.

A roadmap for implementation of kV-CBCT online adaptive radiation therapy and initial first year experiences.

PURPOSE: Online Adaptive Radiation Therapy (oART) follows a different treatment paradigm than conventional radiotherapy, and because of this, the resources, implementation, and workflows needed are unique. The purpose of this report is to outline our institution's experience establishing, organizing, and implementing an oART program using the Ethos therapy system. METHODS: We include resources used, operational models utilized, program creation timelines, and our institutional experiences with the implementation and operation of an oART program. Additionally, we provide a detailed summary of our first year's clinical experience where we delivered over 1000 daily adaptive fractions. For all treatments, the different stages of online adaption, primary patient set-up, initial kV-CBCT acquisition, contouring review and edit of influencer structures, target review and edits, plan evaluation and selection, Mobius3D 2nd check and adaptive QA, 2nd kV-CBCT for positional verification, treatment delivery, and patient leaving the room, were analyzed. RESULTS: We retrospectively analyzed data from 97 patients treated from August 2021-August 2022. One thousand six hundred seventy seven individual fractions were treated and analyzed, 632(38%) were non-adaptive and 1045(62%) were adaptive. Seventy four of the 97 patients (76%) were treated with standard fractionation and 23 (24%) received stereotactic treatments. For the adaptive treatments, the generated adaptive plan was selected in 92% of treatments. On average(±std), adaptive sessions took 34.52 ± 11.42 min from start to finish. The entire adaptive process (from start of contour generation to verification CBCT), performed by the physicist (and physician on select days), was 19.84 ± 8.21 min. CONCLUSION: We present our institution's experience commissioning an oART program using the Ethos therapy system. It took us 12 months from project inception to the treatment of our first patient and 12 months to treat 1000 adaptive fractions. Retrospective analysis of delivered fractions showed that the average overall treatment time was approximately 35 min and the average time for the adaptive component of treatment was approximately 20 min.

A focused review of statistical practices for relating radiation dose-volume exposure and toxicity.

PURPOSE: Relating dose-volume histogram (DVH) information to patient outcomes is critical for outcomes research in radiation oncology, but this is statistically challenging. We performed this focused review of DVH toxicity studies to characterize current statistical approaches and determine the need for updated reporting recommendations. METHODS AND MATERIALS: We performed a focused MEDLINE search to identify studies published in 5 radiation oncology specialty journals that associated dosimetry with toxicity outcomes in humans receiving radiotherapy between 2015 and 2021. Elements abstracted from each manuscript included the study outcome, organs-at-risk (OARs) considered, DVH parameters analyzed, summary of the analytic approach, use of multivariable statistics, goodness-of-fit reporting, completeness of model reporting, assessment of multicollinearity, adjustment for multiple comparisons, and methods for dichotomizing variables. Each study was also assessed for sufficient reporting to allow for replication of results. RESULTS: The MEDLINE search returned 2,300 studies for review and 325 met the inclusion criteria for the analysis. DVH variables were dichotomized using cut points in 154 (47.4%) studies. Logistic regression (55.4% of studies) was the most common statistical method used to relate DVH to toxicity outcomes, followed by Cox regression (20.6%) and linear regression (12.0%). Multivariable statistical tests were performed in 226 (69.5%) studies; of these, the possibility of multicollinearity was addressed in 47.8% and model goodness-of-fit were reported in 32.6%. The threshold for statistical significance was adjusted to account for multiple comparisons in 41 of 196 (17.1%) studies that included multiple statistical comparisons. Twenty-eight (8.6%) studies were classified as missing details necessary to reproduce the study results. CONCLUSIONS: Current practices of statistical reporting in DVH outcomes suggest that studies may be vulnerable to threats against internal and external validity. Recommendations for reporting are provided herein to guard against such threats and to promote cohesiveness among radiation oncology outcomes researchers.

Leveraging intelligent optimization for automated, cardiac-sparing accelerated partial breast treatment planning.

Background: Accelerated partial breast irradiation (APBI) yields similar rates of recurrence and cosmetic outcomes as compared to whole breast radiation therapy (RT) when patients and treatment techniques are appropriately selected. APBI combined with stereotactic body radiation therapy (SBRT) is a promising technique for precisely delivering high levels of radiation while avoiding uninvolved breast tissue. Here we investigate the feasibility of automatically generating high quality APBI plans in the Ethos adaptive workspace with a specific emphasis on sparing the heart. Methods: Nine patients (10 target volumes) were utilized to iteratively tune an Ethos APBI planning template for automatic plan generation. Twenty patients previously treated on a TrueBeam Edge accelerator were then automatically replanned using this template without manual intervention or reoptimization. The unbiased validation cohort Ethos plans were benchmarked via adherence to planning objectives, a comparison of DVH and quality indices against the clinical Edge plans, and qualitative reviews by two board-certified radiation oncologists. Results: 85% (17/20) of automated validation cohort plans met all planning objectives; three plans did not achieve the contralateral lung V1.5Gy objective, but all other objectives were achieved. Compared to the Eclipse generated plans, the proposed Ethos template generated plans with greater evaluation planning target volume (PTV_Eval) V100% coverage (p = 0.01), significantly decreased heart V1.5Gy (p< 0.001), and increased contralateral breast V5Gy, skin D0.01cc, and RTOG conformity index (p = 0.03, p = 0.03, and p = 0.01, respectively). However, only the reduction in heart dose was significant after correcting for multiple testing. Physicist-selected plans were deemed clinically acceptable without modification for 75% and 90% of plans by physicians A and B, respectively. Physicians A and B scored at least one automatically generated plan as clinically acceptable for 100% and 95% of planning intents, respectively. Conclusions: Standard left- and right-sided planning templates automatically generated APBI plans of comparable quality to manually generated plans treated on a stereotactic linear accelerator, with a significant reduction in heart dose compared to Eclipse generated plans. The methods presented in this work elucidate an approach for generating automated, cardiac-sparing APBI treatment plans for daily adaptive RT with high efficiency.

Dose prescription and reporting in stereotactic body radiotherapy: A multi-institutional study.

BACKGROUND AND PURPOSE: Radiation dose prescriptions are foundational for optimizing treatment efficacy and limiting treatment-related toxicity. We sought to assess the lack of standardization of SBRT dose prescriptions across institutions. MATERIALS & METHODS: Dosimetric data from 1298 patients from 9 academic institutions treated with IMRT and VMAT were collected. Dose parameters D100, D98, D95, D50, and D2 were used to assess dosimetric variability. RESULTS: Disease sites included lung (48.3 %) followed by liver (29.7 %), prostate (7.5 %), spine (6.8 %), brain (4.1 %), and pancreas (2.5 %). The PTV volume in lung varied widely with bimodality into two main groups (22.0-28.7 cm3) and (48.0-67.1 cm3). A hot spot ranging from 120-150 % was noted in nearly half of the patients, with significant variation across institutions. A D50 ≥ 110 % was found in nearly half of the institutions. There was significant dosimetric variation across institutions. CONCLUSIONS: The SBRT prescriptions in the literature or in treatment guidelines currently lack nuance and hence there is significant variation in dose prescriptions across academic institutions. These findings add greater importance to the identification of dose parameters associated with improved clinical outcome comparisons as we move towards more hypofractionated treatments. There is a need for standardized reporting to help institutions in adapting treatment protocols based on the outcome of clinical trials. Dosimetric parameters are subsequently needed for uniformity and thereby standardizing planning guidelines to maximize efficacy, mitigate toxicity, and reduce treatment disparities are urgently needed.

Head and Neck Radiation Therapy Patterns of Practice Variability Identified as a Challenge to Real-World Big Data: Results From the Learning from Analysis of Multicentre Big Data Aggregation (LAMBDA) Consortium.

Purpose: Outside of randomized clinical trials, it is difficult to develop clinically relevant evidence-based recommendations for radiation therapy (RT) practice guidelines owing to lack of comprehensive real-world data. To address this knowledge gap, we formed the Learning from Analysis of Multicenter Big Data Aggregation consortium to cooperatively implement RT data standardization, develop software solutions for data analysis, and recommend clinical practice change based on real-world data analyzed. The first phase of this "Big Data" study aimed at characterizing variability in clinical practice patterns of dosimetric data for organs at risk (OARs) that would undermine subsequent use of large-scale, electronically aggregated data to characterize associations with outcomes. Evidence from this study was used as the basis for practical recommendations to improve data quality. Methods and Materials: Dosimetric details of patients with head and neck cancer treated with radiation therapy between 2014 and 2019 were analyzed. Institutional patterns of practice were characterized, including structure nomenclature, volumes, and frequency of contouring. Dose volume histogram (DVH) distributions were characterized and compared with institutional constraints and literature values. Results: Plans for 4664 patients treated to a mean plan dose of 64.4 ± 13.2 Gy in 32 ± 4 fractions were aggregated. Before implementation of TG-263 guidelines in each institution, there was variability in OAR nomenclature across institutions and structures. With evidence from this study, we identified a targeted and practical set of recommendations aimed at improving the quality of real-world data. Conclusions: Quantifying similarities and differences among institutions for OAR structures and DVH metrics is the launching point for next steps to investigate potential relationships between DVH parameters and patient outcomes.

Do we need patient-specific QA for adaptively generated plans? Retrospective evaluation of delivered online adaptive treatment plans on Varian Ethos.

BACKGROUND: The clinical introduction of dedicated treatment units for online adaptive radiation therapy (OART) has led to widespread adoption of daily adaptive radiotherapy. OART allows for rapid generation of treatment plans using daily patient anatomy, potentially leading to reduction of treatment margins and increased normal tissue sparing. However, the OART workflow does not allow for measurement of patient-specific quality assurance (PSQA) during treatment delivery sessions and instead relies on secondary dose calculations for verification of adapted plans. It remains unknown if independent dose verification is a sufficient surrogate for PSQA measurements. PURPOSE: To evaluate the plan quality of previously treated adaptive plans through multiple standard PSQA measurements. METHODS: This IRB-approved retrospective study included sixteen patients previously treated with OART at our institution. PSQA measurements were performed for each patient's scheduled and adaptive plans: five adaptive plans were randomly selected to perform ion chamber measurements and two adaptive plans were randomly selected for ArcCHECK measurements. The same ArcCHECK 3D dose distribution was also sent to Mobius3D to evaluate the second-check dosimetry system. RESULTS: All (n = 96) ion chamber measurements agreed with the planned dose within 3% with a mean of 1.4% (± 0.7%). All (n = 48) plans passed ArcCHECK measurements using a 95% gamma passing threshold and 3%/2 mm criteria with a mean of 99.1% (± 0.7%). All (n = 48) plans passed Mobius3D second-check performed with 95% gamma passing threshold and 5%/3 mm criteria with a mean of 99.0% (± 0.2%). CONCLUSION: Plan measurement for PSQA may not be necessary for every online-adaptive treatment verification. We recommend the establishment of a periodic PSQA check to better understand trends in passing rates for delivered adaptive treatments.

Dose Optimization for Single-Channel Vaginal Cylinder High-Dose-Rate Brachytherapy: A Double Prescription Method for Patients With Endometrial Adenocarcinoma.

Purpose This study aimed to explore the relationship between applicator surface dose and 5 mm-depth dose and to optimize both locations simultaneously for three most used cylinder sizes (2.5, 3.0, and 3.5 cm in diameter) in treating patients with endometrial adenocarcinoma. Materials and methods A total of 216 plans were created for each dose level and applicator size. For each dose level, four plans were created with single or double prescription doses. For plans with double prescription doses, the dose constraints were applied to all those points on the surface and 5 mm depth and optimize the two sites simultaneously.  Results A dose table between surface and 5 mm depth and its fifth order polynomial mapping functions were established for each applicator size, so any prescribed dose at one site can find the prescription dose on the other site in optimization on both locations. For plans with a 5 mm-depth prescription, the maximum dose on the surface can be reduced from 145% to 133% if the surface prescription dose is also used; for plans with surface dose prescription, the minimum dose and mean dose can be improved by 2% if 5 mm-depth dose prescription is also used in optimization. Conclusion Dose table and their mapping functions between surface prescription dose and their corresponding 5 mm-depth doses were created. A new optimization method that uses two prescription doses on both surface and 5 mm-depth sites was proposed to reduce the hot dose on the surface and improve the cold dose at 5 mm depth.

Analysis of a surface imaging system using a six degree-of-freedom couch.

PURPOSE: To validate surface imaging (SI)-reported offsets using a six degree-of-freedom couch and an anthropomorphic phantom for commissioning and routine quality assurance of an SI system used for stereotactic radiosurgery (SRS). METHODS: An anthropomorphic phantom with a radiopaque ball bearing (BB) placed either anterior, midline, or posterior, was tracked with SI with a typical SRS region of interest. Couch motion in all six degrees of freedom was programmed and delivered on a linac. SI system logs were synchronized with linac trajectory logs. Ten random couch positions were selected at couch 0°, 45°, 90°, 270°, 315° with megavolt (MV) images taken to account for couch walkout. The SI residual error (ε), the difference between SI reported offset and MV or trajectory log position, was calculated. Residual errors were measured with and without one SI pod blocked. RESULTS: The median [range] of magnitude of translational ε was 0.13 [0.07, 0.21], 0.16 [0.11, 0.26], 0.61 [0.50, 0.68], 0.49 [0.42, 0.55], 0.55 [0.38, 0.72] mm for couch rotations of 0°, 45°, 90°, 270°, 315°, respectively, for the midline BB and no pod blocked. The range of all translational ε from all couch angles (with and without pod block) at different BB positions is [0.05, 0.96] mm. The absolute range of difference when changing BB position when no pod is blocked in median translational ε is [0.01, 0.40] mm with the maximum at BB posterior. The absolute range of difference when not changing BB positions with and without pod block in median translational ε is [0.01, 0.37] mm with the maximum at BB posterior and couch 315°. CONCLUSION: SI system and linac trajectory log analysis can be used to assess SI system performance with automated couch motion to validate SI accuracy.

Incorporating Treatment Time into Butterfly Optimization to Reduce Total Treatment Time for Vaginal Cylinder Brachytherapy.

Purpose For patient comfort and safety, irradiation times should be kept at a minimum while maintaining high treatment quality. In this study of high dose rate (HDR) therapy with a vaginal cylinder, we used the butterfly optimization algorithm (BOA) to simultaneously optimize individual dwell times for precise dose conformity and for the reduction of total dwell time. Material and methods BOA is a population-based, meta-heuristic algorithm that averts local minima by conducting intensive local and global searching based on switching probability. We constructed an objective function (a stimulus intensity function) that consisted of two components. The first one was the root-mean-squared dose error (RMSE) defined as the square root of the sum of squared differences between the prescribed and delivered dose at the constraint points. The second component was weighted total treatment time. Eight previously treated cases were retrospectively reviewed by re-optimizing the clinical treatment plans with BOA.  Results Compared to the eight original plans generated with the commercial adaptive volume optimization algorithm (AVOA), the BOA-optimized plans reduced treatment times by 5.4% to 8.9%, corresponding to a time-saving of 13.1 to 47.7 seconds with the activities on the treatment day and saving from 29.3 to 64.6 seconds if treated with an activity of 5 CI. Dose deviations from the prescription were smaller than in the original plans. Conclusion  Dose optimizations based on the BOA algorithm yield closer dose conformity in vaginal HDR treatment than AVOA. Incorporating total treatment time into the optimization algorithm reduces the delivery time while having only a small effect on dose conformity.