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PurposeThe 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 (ROIS), treatment planning systems (TPSs), and other cancer care and outcomes databases. The effort sought to create a standardized ontology for clinical data, social determinants of health (SDOH), and other radiation oncology concepts and interrelationships.Methods and materialsThe American Association of Physicists in Medicine's (AAPM's) Big Data Science Committee (BDSC) was initiated July of 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 BDSC adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community.ResultsWe 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, or the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to four constituencies: device manufacturers, centers of clinical care, researchers, and professional societies.ConclusionsO3 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 creating large, representative, findable, accessible, interoperable and reusable (FAIR) datasets supporting the scientific objectives of grant programs. The construction of comprehensive "real world" datasets and application of advanced analytic techniques, including artificial intelligence (AI), holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative datasets.

The term Big Data has come to encompass a number of concepts and uses within medicine. This paper lays out the relevance and application of large collections of data in the radiation oncology community. We describe the potential importance and uses in clinical practice. The important concepts are then described and how they have been or could be implemented are discussed. Impediments to progress in the collection and use of sufficient quantities of data are also described. Finally, recommendations for how the community can move forward to achieve the potential of big data in radiation oncology are provided.

Purpose/objectives: Tracking patient dose in radiation oncology is challenging due to disparate electronic systems from various vendors. Treatment planning systems (TPS), radiation oncology information systems (ROIS), and electronic health records (EHR) lack uniformity, complicating dose tracking and reporting. To address this, we examined practices in multiple radiation oncology settings and proposed guidelines for current systems., Material/methods: A survey was conducted among members of various professional groups to understand dose reporting practices in TPS, ROIS, and EHR systems. The aim was to identify consistent components and develop guidelines., Results: We identified six treatment scenarios where current ROIS defaults fail in accurately representing dose totals. A standardized approach involving three reference point types - Primary Treatment Plan Reference, Dose Check, and Prescription Tracking - was proposed to address these scenarios. Standardizing naming conventions for reference points was also recommended for easier integration with EHRs. The approach requires minimal modifications to existing systems and facilitates easier data transfer and display in EHRs., Conclusion: Standardizing reference points in commercial TPS and ROIS can bridge infrastructure gaps and improve dose tracking in complex clinical scenarios. This standardization, aligned with AAPM's TG-263, paves the way for continual development of automated, standardized, interoperable tools, enhancing the ease of sharing reference point information., Competing Interests: Declaration of competing interest ALS reports membership of the EPIC Steering Board and mCODE Executive Committee, stock in Pfizer and GE, and financial support from Mayo Clinic, EPIC, and ABR. TM reports interest in Oncospace Inc. EC reports being chair of AAPM Task Group TG-263. RP reports financial support and royalties from Varian Medical Systems. KKB reports financial support from NIH (P30CA016672, 1R01CA221971, P01CA261669), Helen Black Image Guided Fund, MD Anderson Strategic Initiative Development Program (STRIDE), AAPM, and RaySearch Laboratories as well as a licensing agreement with RaySearch Laboratories. TGP reports royalties from RaySearch Laboratories and financial interest in Curait Medical. YJ reports an unpaid board membership on BHPA (Belgian Hospital Physicists Association) and financial support from Elekta Limited. PAB reports financial support from Varian Medical Systems and RaySearch Laboratories., (Copyright © 2024. Published by Elsevier Inc.)

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., Competing Interests: Disclosures Susan L. Richardson is Deputy Editor for the Journal of Applied Clinical Medical Physics. Walter R. Bosch reports grant from National Cancer Institute (NCI) (U24 CA 189893); Charles S. Mayo if Chair of American Association of Physicists in Medicine (AAPM) SC-263 and the Big Data Subcommittee. Todd R. McNutt is Chairman of the board of Oncospace and holds founder shares of Common Stock. Jean M. Moran reports software licensed to Fuse Oncology and grants or contracts from the National Institutes of Health (NIH), NCI, and Blue Cross Blue Shield of Michigan. Richard A. Popple reports honoraria and research support from Varian Medical Systems and also receives royalties for the University of Alabama at Birmingham Research Foundation. Ying Xiao reports no conflicts. Elizabeth L. Covington is the Chair of AAPM Task Group TG-263U1., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: New technologies are continuously emerging in radiation oncology. Inherent technological limitations can result in health care disparities in vulnerable patient populations. These limitations must be considered for existing and new technologies in the clinic to provide equitable care., Materials and Methods: We created a health disparity risk assessment metric inspired by failure mode and effects analysis. We provide sample patient populations and their potential associated disparities, guidelines for clinics and vendors, and example applications of the methodology., Results: A disparity risk priority number can be calculated from the product of 3 quantifiable metrics: the percentage of patients impacted, the severity of the impact of dosimetric uncertainty or quality of the radiation plan, and the clinical dependence on the evaluated technology. The disparity risk priority number can be used to rank the risk of suboptimal care due to technical limitations when comparing technologies and to plan interventions when technology is shown to have inequitable performance in the patient population of a clinic., Conclusions: The proposed methodology may simplify the evaluation of how new technology impacts vulnerable populations, help clinics quantify the limitations of their technological resources, and plan appropriate interventions to improve equity in radiation treatments., Competing Interests: Disclosures Dr Stanley is an educational consultant for Varian Medical Systems. Dr Paradis has grants from Varian Medical Systems and the Michigan Medicine Office of Wellbeing that are unrelated to this work. Dr Covington has a grant from the Michigan Medicine Office of Health Equity and Inclusion unrelated to this work. Drs. Mierzwa and Covington co-lead the M-EQUAL committee of the Michigan Radiation Oncology Quality Consortium (MROQC) where Dr Moncion serves as the physic quality lead for breast. Their work with MROQC is unrelated to this project., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: Few reports describe the risks of late ocular toxicities after radiation therapy (RT) for childhood cancers despite their effect on quality of life. The Pediatric Normal Tissue Effects in the Clinic (PENTEC) ocular task force aims to quantify the radiation dose dependence of select late ocular adverse effects. Here, we report results concerning retinopathy, optic neuropathy, and cataract in childhood cancer survivors who received cranial RT., Methods and Materials: A systematic literature search was performed using the PubMed, MEDLINE, and Cochrane Library databases for peer-reviewed studies published from 1980 to 2021 related to childhood cancer, RT, and ocular endpoints including dry eye, keratitis/corneal injury, conjunctival injury, cataract, retinopathy, and optic neuropathy. This initial search yielded abstracts for 2947 references, 269 of which were selected as potentially having useful outcomes and RT data. Data permitting, treatment and outcome data were used to generate normal tissue complication probability models., Results: We identified sufficient RT data to generate normal tissue complication probability models for 3 endpoints: retinopathy, optic neuropathy, and cataract formation. Based on limited data, the model for development of retinopathy suggests 5% and 50% risk of toxicity at 42 and 62 Gy, respectively. The model for development of optic neuropathy suggests 5% and 50% risk of toxicity at 57 and 64 Gy, respectively. More extensive data were available to evaluate the risk of cataract, separated into self-reported versus ophthalmologist-diagnosed cataract. The models suggest 5% and 50% risk of self-reported cataract at 12 and >40 Gy, respectively, and 50% risk of ophthalmologist-diagnosed cataract at 9 Gy (>5% long-term risk at 0 Gy in patients treated with chemotherapy only)., Conclusions: Radiation dose effects in the eye are inadequately studied in the pediatric population. Based on limited published data, this PENTEC comprehensive review establishes relationships between RT dose and subsequent risks of retinopathy, optic neuropathy, and cataract formation., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Purpose: Radiation myelitis (RM) is a rare complication of radiation therapy (RT). The Pediatric Normal Tissue Effects in the Clinic spinal cord task force aimed to identify RT dose effects and assess risk factors for RM in children. Through systematic review, we analyzed RT dose, fraction size, latency between completion of RT and toxicity, chemotherapy use, age when irradiated, and sex., Methods and Materials: We conducted literature searches of peer-reviewed manuscripts published from 1964 to June 2017 evaluating RM among children. Normality of variables was assessed with Kolmogorov-Smirnov or Shapiro-Wilk tests. Spearman's rank correlation coefficients were used to test correlations between RT dose/fraction size and latency between RT and development of toxicity., Results: Of 1329 identified and screened reports, 144 reports were fully reviewed and determined to have adequate data for analysis; 16 of these reports had a total of 33 cases of RM with a median age of 13 years (range, 0.2-18) at the time of RT. The most common primary tumor histologies were rhabdomyosarcoma (n = 9), medulloblastoma (n = 5), and Hodgkin lymphoma (n = 2); the most common chemotherapy agents given were vincristine (n = 15), intrathecal methotrexate (n = 12), and intrathecal cytarabine (n = 10). The median RT dose and fraction size were 40 Gy (range, 24-57.4 Gy) and 1.8 Gy (range, 1.3-2.6 Gy), respectively. RT dose resulting in RM in patients who also received chemotherapy was lower than in those not receiving chemotherapy (mean 39.6 vs 49.7 Gy; P = .04). There was no association of age with RT dose. The median latency period was 7 months (range, 1-29). Higher RT dose was correlated with longer latency periods (P = .03) to RM whereas sex, age, fraction size, and chemotherapy use were not. Two of 17 patients with adequate follow-up recovered from RM; unfortunately, it was fatal in 6 of 15 evaluable patients. Complication probability modeling was not possible because of the rarity of events., Conclusions: This report demonstrates a relatively short latency from RT (with or without chemotherapy) to RM and a wide range of doses (including fraction sizes) associated with RM. No apparent association with age at the time of RT could be discerned. Chemotherapy appears to reduce spinal cord tolerance. Recovery from RM is rare, and it is often fatal., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: Liver-directed radiation therapy is an effective treatment for hepatocellular carcinoma (HCC), but metachronous lesions develop outside the irradiated field in >50% of patients. We hypothesized that irradiation of these new lesions would produce an outcome like that of patients receiving a first course (C1) of treatment., Methods and Materials: We included patients with HCC who received a second course (C2) of radiation therapy >1 month after C1. Toxicity was defined as Child-Pugh score increase ≥2 within 6 months posttreatment (binary model) and as the change in albumin-bilirubin during the year after treatment (longitudinal model). Overall survival (OS) and local failure (LF) were captured at the patient and lesion level, respectively; both were summarized with Kaplan-Meier estimates. Predictors of toxicity and OS were assessed using generalized linear mixed and Cox regression models, respectively., Results: Of 340 patients with HCC, 47 underwent irradiation for metachronous HCC, receiving similar prescription dose in C1/C2. Median follow-up was 17 months after C1 and 15 months after C2. Twenty-two percent of patients experienced toxicity after C1, and 25% experienced toxicity after C2. Worse baseline albumin-bilirubin predicted toxicity in both binary (odds ratio, 2.40; 95% CI, 1.46-3.94; P = .0005) and longitudinal models (P < .005). Two-year LF rate was 11.2% after C1 and 8.3% after C2; tumor dose (hazard ratio [HR], 0.982; 95% CI, 0.969-0.995; P = .007) and tumor size (HR, 1.135; 95% CI, 1.068-1.206; P < .005) predicted LF. Two-year OS was 46.0% after C1 and 42.6% after C2; tumor dose (HR, 0.986; 95% CI, 0.979-0.992; P < .005) and tumor size (HR, 1.049; 95% CI, 1.010-1.088; P = .0124) predicted OS. Reirradiation was not associated with toxicity (P > .7), LF (P = .79), or OS (P = .39)., Conclusions: In this largest series in the Western hemisphere, we demonstrate that irradiation for metachronous HCC offers low rates of LF with acceptable toxicity and OS like that of patients receiving a C1. These findings support judicious selection of patients for reirradiation in metachronous HCC., Competing Interests: Disclosures None., (Copyright © 2023 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.)

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., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: We hypothesized that optimizing the utility of stereotactic body radiotherapy (SBRT) based on the individual patient's probability for tumor control and risk of liver injury would decrease toxicity without sacrificing local control in patients with impaired liver function or tumors not amenable to thermal ablation., Patients and Methods: Patients with Child-Pugh (CP) A to B7 liver function with aggregate tumor size >3.5 cm, or CP ≥ B8 with any size tumor were prospectively enrolled on an Institutional Review Board-approved phase II clinical trial to undergo SBRT with baseline and midtreatment dose optimization using a quantitative, individualized utility-based analysis. Primary endpoints were change in CP score of ≥2 points within 6 months and local control. Protocol-treated patients were compared with patients receiving conventional SBRT at another cancer center using overlap weighting., Results: A total of 56 patients with 80 treated tumors were analyzed with a median follow-up of 11.2 months. Two-year cumulative incidence of local progression was 6.4% [95% confidence interval (CI, 2.4-13.4)]. Twenty-one percent of patients experienced treatment-related toxicity within 6 months, which is similar to the rate for SBRT in patients with CP A liver function. An analysis using overlap weighting revealed similar local control [HR, 0.69; 95% CI (0.25-1.91); P = 0.48] and decreased toxicity [OR, 0.26; 95% CI (0.07-0.99); P = 0.048] compared with conventional SBRT., Conclusions: Treatment of individuals with impaired liver function or tumors not amenable to thermal ablation with a treatment paradigm designed to optimize utility may decrease treatment-related toxicity while maintaining tumor control., (©2023 American Association for Cancer Research.)

Background: As cancer therapies have improved, spinal metastases are increasingly common. Resulting complications have a significant impact on patient's quality of life. Optimal methods of surveillance and avoidance of neurologic deficits are understudied. This study compares the clinical course of patients who initially presented to the emergency department (ED) versus a multidisciplinary spine oncology clinic and who underwent stereotactic body radiation therapy (SBRT) secondary to progression/presentation of metastatic spine disease., Methods: We performed a retrospective analysis of a prospectively maintained database of adult oncologic patients who underwent spinal SBRT at a single hospital from 2010 to 2021. Descriptive statistics and survival analyses were performed., Results: We identified 498 spinal radiographic treatment sites in 390 patients. Of these patients, 118 (30.3%) presented to the ED. Patients presenting to the ED compared to the clinic had significantly more severe spinal compression (52.5% vs. 11.7%; p < 0.0001), severe pain (28.8% vs. 10.3%; p < 0.0001), weakness (24.5% vs. 4.5%; p < 0.0001), and difficulty walking (24.5% vs. 4.5%; p < 0.0001). Patients who presented to the ED compared to the clinic were significantly more likely to have surgical intervention followed by SBRT (55.4% vs. 15.3%; p < 0.0001) compared to SBRT alone. Patients who presented to the ED compared to the clinic had a significantly quicker interval to distant spine progression (5.1 ± 6.5 vs. 9.1 ± 10.2 months; p = 0.004), systemic progression (5.1 ± 7.2 vs. 9.2 ± 10.7 months; p < 0.0001), and worse overall survival (9.3 ± 10.0 vs. 14.3 ± 13.7 months; p = 0.002)., Conclusion: The establishment of multidisciplinary spine oncology clinics is an opportunity to potentially allow for earlier, more data-driven treatment of their spinal metastatic disease., (© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Background Aims: Early-stage HCC can be treated with thermal ablation or stereotactic body radiation therapy (SBRT). We retrospectively compared local progression, mortality, and toxicity among patients with HCC treated with ablation or SBRT in a multicenter, US cohort., Approach Results: We included adult patients with treatment-naïve HCC lesions without vascular invasion treated with thermal ablation or SBRT per individual physician or institutional preference from January 2012 to December 2018. Outcomes included local progression after a 3-month landmark period assessed at the lesion level and overall survival at the patient level. Inverse probability of treatment weighting was used to account for imbalances in treatment groups. The Cox proportional hazard modeling was used to compare progression and overall survival, and logistic regression was used for toxicity. There were 642 patients with 786 lesions (median size: 2.1 cm) treated with ablation or SBRT. In adjusted analyses, SBRT was associated with a reduced risk of local progression compared to ablation (aHR 0.30, 95% CI: 0.15-0.60). However, SBRT-treated patients had an increased risk of liver dysfunction at 3 months (absolute difference 5.5%, aOR 2.31, 95% CI: 1.13-4.73) and death (aHR 2.04, 95% CI: 1.44-2.88, p < 0.0001)., Conclusions: In this multicenter study of patients with HCC, SBRT was associated with a lower risk of local progression compared to thermal ablation but higher all-cause mortality. Survival differences may be attributable to residual confounding, patient selection, or downstream treatments. These retrospective real-world data help guide treatment decisions while demonstrating the need for a prospective clinical trial., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Association for the Study of Liver Diseases.)

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., (© 2023. The Author(s).)

Purpose: To use a hybrid method, combining statistical profiling, machine learning (ML), and clinical evaluation to predict emergency department (ED) visits among patients with head and neck cancer undergoing radiotherapy., Materials and Methods: Patients with head and neck cancer treated with radiation therapy from 2015 to 2019 were identified using electronic health record data. Records from 60 days before 90 days after treatment were analyzed. Statistical profiling and ML were used to create a predictive model for ED visits during or after radiation therapy. A comprehensive set of variables were studied. Multiple ML models were developed including extreme gradient-boosted decision tree and generalized logistic regression with comparison of multiple predictive performance metrics., Results: Of the 1,355 patients studied, 13% had an ED visit during or after treatment. Our hybrid methodology enabled evidence-based winnowing of candidate features from 141 to 11 with clinically applicable, evidence-based thresholds. Extreme gradient boosting had the highest area under the curve (0.81 ± 0.06) with a sensitivity of 0.89 ± 0.10 and exceeded generalized logistic regression (area under the curve 0.64 ± 0.02). Significant predictors of ED visits during treatment included increasingly complex opioid use, number of prior ED visits, tumor volume, rate of change of blood urea nitrogen, total bilirubin, body mass index, and distance from hospital., Conclusion: Our approach combining bootstrapped statistical profiling and ML importance analysis supported integration of clinician input to identify a distilled set of phenotypical characteristics for developing ML models predicting which patients undergoing head and neck cancer radiation therapy were at risk for ED visits.

Purpose: Recent clinical trials suggest hypofractionated treatment regimens are appropriate for treatment of many cancers. It is important to understand and document hypofractionation adoption because of its implications for treatment center patient volumes. There is no recent U.S. study of trends in hypofractionation adoption that includes comparisons of multiple disease sites and data since the onset of COVID-19. In this context, this study describes trends in treatment fractionation at a single academic center from 2010 to 2020., Methods and Materials: From an institutional database, records were extracted for treatment of 4 disease site categories: all cancers, breast cancer, prostate cancer, and bone metastases. For each disease site, the mean number of fractions per treatment course was reported for each year of the study period. To explore whether the COVID-19 pandemic was associated with increased hypofractionation adoption, piecewise linear regression models were used to estimate a changepoint in the time trend of mean monthly number of fractions per treatment course and to evaluate whether this changepoint coincided with pandemic onset., Results: The data set included 22,865 courses of radiation treatment and 375,446 treatment fractions. The mean number of fractions per treatment course for all cancers declined from 17.5 in 2010 to 13.6 in 2020. There was increased adoption of hypofractionation at this institution for all cancers and specifically for both breast and prostate cancer. For bone metastases, hypofractionation had largely been adopted before the study period. For most disease sites, adoption of hypofractionated treatment courses occurred before pandemic onset. Bone metastases was the only disease site where a pandemic-driven increase in hypofractionation adoption could not be ruled out., Conclusions: This study reveals increasing use of hypofractionated regimens for a variety of cancers throughout the study period, which largely occurred before the onset of the COVID-19 pandemic at this institution., (© 2022 The Authors.)

Purpose: Head and neck (HN) radiation (RT) treatment planning is complex and resource intensive. Deviations and inconsistent plan quality significantly affect clinical outcomes. We sought to develop a novel automated virtual integrative (AVI) knowledge-based planning application to reduce planning time, increase consistency, and improve baseline quality., Methods and Materials: An in-house write-enabled script was developed from a library of 668 previously treated HN RT plans. Prospective hazard analysis was performed, and mitigation strategies were implemented before clinical release. The AVI-planner software was retrospectively validated in a cohort of 52 recent HN cases. A physician panel evaluated planning limitations during initial deployment, and feedback was enacted via software refinements. A final second set of plans was generated and evaluated. Kolmogorov-Smirnov test in addition to generalized evaluation metric and weighted experience score were used to compare normal tissue sparing between final AVI planner versus respective clinically treated and historically accepted plans. A t test was used to compare the interactive time, complexity, and monitor units for AVI planner versus manual optimization., Results: Initially, 86% of plans were acceptable to treat, with 10% minor and 4% major revisions or rejection recommended. Variability was noted in plan quality among HN subsites, with high initial quality for oropharynx and oral cavity plans. Plans needing revisions were comprised of sinonasal, nasopharynx, P-16 negative squamous cell carcinoma unknown primary, or cutaneous primary sites. Normal tissue sparing varied within subsites, but AVI planner significantly lowered mean larynx dose (median, 18.5 vs 19.7 Gy; P < .01) compared with clinical plans. AVI planner significantly reduced interactive optimization time (mean, 2 vs 85 minutes; P < .01)., Conclusions: AVI planner reliably generated clinically acceptable RT plans for oral cavity, salivary, oropharynx, larynx, and hypopharynx cancers. Physician-driven iterative learning processes resulted in favorable evolution in HN RT plan quality with significant time savings and improved consistency using AVI planner., (© 2022 The Authors.)

Purpose: Due to a gap in published guidance, we describe our robust cycle of in-house clinical software development and implementation, which has been used for years to facilitate the safe treatment of all patients in our clinics., Methods and Materials: Our software development and implementation cycle requires clarity in communication, clearly defined roles, thorough commissioning, and regular feedback. Cycle phases include design requirements and use cases, development, physics evaluation testing, clinical evaluation testing, and full clinical release. Software requirements, release notes, test suites, and a commissioning report are created and independently reviewed before clinical use. Software deemed to be high-risk, such as those that are writable to a database, incorporate the use of a formal, team-based hazard analysis. Incident learning is used to both guide initial development and improvements as well as to monitor the safe use of the software., Results: Our standard process builds in transparency and establishes high expectations in the development and use of custom software to support patient care. Since moving to a commercial planning system platform in 2013, we have applied our team-based software release process to 16 programs related to scripting in the treatment planning system for the clinic., Conclusions: The principles and methodology described here can be implemented in a range of practice settings regardless of whether or not dedicated resources are available for software development. In addition to teamwork with defined roles, documentation, and use of incident learning, we strongly recommend having a written policy on the process, using phased testing, and incorporating independent oversight and approval before use for patient care. This rigorous process ensures continuous monitoring for and mitigatation of any high risk hazards., (© 2021 The Authors.)

Purpose: Our individualized functional response adaptive approach to liver stereotactic body radiation therapy (SBRT) with assessment of indocyanine green (ICG) retention at baseline and midtreatment to detect subclinical changes in liver function, permitting dose adjustment, has decreased toxicity while preserving efficacy. We hypothesized that assessment of the albumin-bilirubin (ALBI) score at baseline and midtreatment would allow for more practical identification of patients at risk for treatment-related toxicity (TRT)., Methods and Materials: Patients with hepatocellular carcinoma were treated on 3 prospective institutional review board-approved trials using baseline and midtreatment ICG to deliver individualized functional response adaptive liver SBRT. Patients received 3 or 5 fractions, with fraction 3 followed by a 1-month treatment break. TRT was a ≥2-point rise in Child-Pugh score within 6 months of SBRT. Logistic regression was used to estimate odds ratios (ORs) and confidence intervals (CIs) for assessment of TRT. Area under the receiver operating curve was used to compare predictive ability across models., Results: In total, 151 patients underwent 166 treatments. Baseline Child-Pugh class and ALBI grade were A (66.9%), B (31.3%), or C (1.8%) and 1 (25.9%), 2 (65.7%), or 3 (8.4%), respectively. Thirty-five patients (20.3%) experienced TRT. On univariate analysis, baseline ALBI (OR, 1.8; 95% CI, 1.24-2.62; P = .02), baseline ICG (OR, 1.66; 95% CI, 1.17-2.35; P = .04), and change in ALBI (OR, 3.07; 95% CI, 1.29-7.32; P = .003) were associated with increased odds of TRT. ALBI-centric models performed similarly to ICG-centric models on multivariate analyses predicting toxicity (area under the receiver operating curve of 0.79 for both). In a model incorporating baseline and midtreatment change in ALBI and ICG, both ALBI values were statistically significantly associated with toxicity, whereas ICG values were not., Conclusions: Incorporation of midtreatment change in ALBI in addition to baseline ALBI improves the ability to predict TRT in patients with hepatocellular carcinoma receiving SBRT. Our findings suggest that functional response adaptive treatment could be implemented in a practical manner because the ALBI score is easily obtained from standard laboratory values., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Purpose: We hypothesized that dose-intensified chemoradiation therapy targeting adversely prognostic hypercellular (TV HCV ) and hyperperfused (TV CBV ) tumor volumes would improve outcomes in patients with glioblastoma., Methods and Materials: This single-arm, phase 2 trial enrolled adult patients with newly diagnosed glioblastoma. Patients with a TV HCV /TV CBV >1 cm 3 , identified using high b-value diffusion-weighted magnetic resonance imaging (MRI) and dynamic contrast-enhanced perfusion MRI, were treated over 30 fractions to 75 Gy to the TV HCV /TV CBV with temozolomide. The primary objective was to estimate improvement in 12-month overall survival (OS) versus historical control. Secondary objectives included evaluating the effect of 3-month TV HCV /TV CBV reduction on OS using Cox proportional-hazard regression and characterizing coverage (95% isodose line) of metabolic tumor volumes identified using correlative 11 C-methionine positron emission tomography. Clinically meaningful change was assessed for quality of life by the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire C30, for symptom burden by the MD Anderson Symptom Inventory for brain tumor, and for neurocognitive function (NCF) by the Controlled Oral Word Association Test, the Trail Making Test, parts A and B, and the Hopkins Verbal Learning Test-Revised., Results: Between 2016 and 2018, 26 patients were enrolled. Initial patients were boosted to TV HCV alone, and 13 patients were boosted to both TV HCV /TV CBV . Gross or subtotal resection was performed in 87% of patients; 22% were O 6 -methylguanine-DNA methyltransferase (MGMT) methylated. With 26-month follow-up (95% CI, 19-not reached), the 12-month OS rate among patients boosted to the combined TV HCV /TV CBV was 92% (95% CI, 78%-100%; P = .03) and the median OS was 20 months (95% CI, 18-not reached); the median OS for the whole study cohort was 20 months (95% CI, 14-29 months). Patients whose 3-month TV HCV /TV CBV decreased to less than the median volume (3 cm 3 ) had superior OS (29 vs 12 months; P = .02). Only 5 patients had central or in-field failures, and 93% (interquartile range, 59%-100%) of the 11 C-methionine metabolic tumor volumes received high-dose coverage. Late grade 3 neurologic toxicity occurred in 2 patients. Among non-progressing patients, 1-month and 7-month deterioration in quality of life, symptoms, and NCF were similar in incidence to standard therapy., Conclusions: Dose intensification against hypercellular/hyperperfused tumor regions in glioblastoma yields promising OS with favorable outcomes for NCF, symptom burden, and quality of life, particularly among patients with greater tumor reduction 3 months after radiation therapy., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Purpose: Previous reports of stereotactic body radiation therapy (SBRT) for hepatocellular carcinoma (HCC) suggest unacceptably high rates of toxicity in patients with Child-Turcotte-Pugh (CTP) B liver disease. We hypothesized that an individualized adaptive treatment approach based on midtreatment liver function would maintain good local control while limiting toxicity in this population., Methods and Materials: Patients with CTP-B liver disease and HCC were treated on prospective trials of individualized adaptive SBRT between 2006 and 2018. Patients underwent pre- and midtreatment liver function assessments using indocyanine green. Treatment-related toxicity was defined as a ≥2-point increase in CTP score from pretreatment within 6 months of treatment. In addition, we performed analyses with a longitudinal model to assess changes in CTP score over 12 months after SBRT., Results: Eighty patients with CTP-B (median tumor size, 2.5 cm) were treated: 37 patients were CTP-B-7, 28 were CTP-B-8, and 15 were CTP-B-9. The median treatment dose was 36 Gy in 3 fractions. One-year local control was 92%. In a multivariate model controlling for tumor size, treatment dose, and baseline CTP score, higher treatment dose was associated with improved freedom from local progression (hazard ratio: 0.97; 95% confidence interval, 0.94-1.00; P = .04). Eighteen patients (24%) had a ≥2-point increase in CTP score within 6 months of SBRT. In a longitudinal model assessing changes in CTP score over 12 months after SBRT, controlling for baseline CTP and tumor size, increasing mean liver dose was associated with larger increases in CTP score (P = .04)., Conclusions: An individualized adaptive treatment approach allows for acceptable toxicity and effective local control in patients with HCC and CTP-B liver disease. Because increasing dose may increase both local control and toxicity, further work is needed to optimize treatment in patients with compromised liver function., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objectives: Improved prognosis for p16+ oropharyngeal squamous cell carcinoma (OPSCC) has led to efforts to mitigate long-term complications of treatment, which remains poorly defined in late survivors. Here we characterize very late dysphagia in OPSCC., Materials and Methods: Long-term review of 93 p16+ OPSCC patients treated with chemoradiation was performed. We scored videofluoroscopic swallow studies (VFSS) according to the Dynamic Imaging Grade of Swallowing Toxicity (DIGEST) scale. Very late dysphagia was defined >2.5 years from end of treatment. Fine-Gray regression models were used to assess dysphagia with competing risk of death., Results: Median follow up was 10.5 years. 402 total VFSS were assessed (median 4 per patient, range 0-8). 15.1% of patients had a DIGEST score ≥2 very late after treatment. Very late DIGEST score ≥2 correlated with T-stage (HR 1.7, p = 0.049), second cancer (HR 6.5, p = 0.004), superior pharyngeal constrictor dose (HR 1.11, p = 0.050), total tongue dose (HR 1.07, p = 0.045), but not hypoglossal nerve dose (p > 0.2). Seven patients (7.5%) had late progressive dysphagia, defined as DIGEST score that increased by ≥2 beyond one year after treatment, and this correlated with higher ipsilateral hypoglossal nerve D1cc dose (75 vs 72 Gy, p = 0.037)., Conclusion: In p16+ OPSCC patients treated with definitive chemoradiation, at least 7.5% developed late progressive dysphagia, and 15.1% experienced moderate dysphagia >2.5 years from treatment. Our study suggests that dose to tongue musculature may be associated with very late dysphagia, and hypoglossal nerve dose may be associated with late progressive dysphagia. More intensive long-term dysphagia survivorship monitoring is suggested., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Purpose: The radiation treatment summary provides a clinical and technical overview of a patient's full course of radiation therapy. Despite its importance to multiple stakeholders, there is no widely followed radiation treatment summary template., Methods and Materials: The Commission on Cancer convened a multistakeholder workgroup to develop a synoptic radiation treatment summary template. The workgroup included individuals with expertise in radiation, medical and surgical oncology, medical physics, oncology informatics, cancer registry, electronic medical record systems, treatment planning systems, and registry information systems. The workgroup iterated a template until consensus was achieved., Results: The consensus radiation treatment summary template is divided into 3 sections that allows for a mix of structured and free text. The first section, "Radiation Course Summary," is meant to provide information that is of broad interest and in a manner that is potentially accessible to patients, their families, and nononcology-trained care team members. The second section, "Anatomic Target Summary," provides information that is potentially useful to oncology-trained care team members who will be primarily interested in which anatomies were irradiated, by what modality, and to what cumulative dose. The third section, "Delivered Prescriptions," summarizes technical information that is primarily of interest and accessible to radiation oncology-trained clinicians, registrars, and researchers., Conclusions: We have proposed a consensus template with 3 sections to meet the needs of a diverse set of consumers. We recommend that providers, professional societies, and accreditation bodies with interest in the radiation treatment summary continue collaborative efforts to test, iterate, and drive adoption of a synoptic template., (Copyright © 2020 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.)

Purpose: To assess associations between parotid gland PET biomarkers and late radiation-induced xerostomia, and to validate improvement of xerostomia predictive models by adding pre-treatment PET features to models based on dose and pre-treatment xerostomia., Materials and Methods: Intensity PET features from 47 patients treated on institutional prospective clinical trials for HPV-associated oropharyngeal squamous cell carcinoma with uniform chemoRT were analyzed. Associations between 90th percentile of the parotid gland standardized uptake values (P90) from pre-treatment and post-treatment PET scans, mean parotid gland doses, and late xerostomia defined by the Xerostomia Questionnaire (XQ) and salivary flow rates were quantified. Multivariable analysis was applied for dose and PET features using penalized logistic regression for feature selection and generation of predictive models using the LASSO technique, and optimism bias was estimated by bootstrap resampling., Results: Significant associations between late xerostomia and both mean parotid gland dose and P90 were demonstrated, and were generally stronger for post-treatment PET scans. The addition of P90 from pre-treatment PET scans improved the prediction model for late moderate or severe xerostomia compared to the base model, from AUC = 0.74 to 0.78 (p-value <0.001) for XQ summary score and from 0.77 to 0.84 (p-value <0.001) for the single eating-related XQ item with the largest inter-patient variability; however, only the latter remained significant on cross validation (AUC = 0.69 to 0.70 and 0.73 to 0.80, respectively)., Conclusions: The addition of pre-treatment parotid gland PET biomarkers improved a predictive model for late patient-reported xerostomia over dose and pre-treatment xerostomia., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Purpose: We combined clinical practice changes, standardizations, and technology to automate aggregation, integration, and harmonization of comprehensive patient data from the multiple source systems used in clinical practice into a big data analytics resource system (BDARS). We then developed novel artificial intelligence algorithms, coupled with the BDARS, to identify structure dose volume histograms (DVH) metrics associated with dysphagia., Methods and Materials: From the BDARS harmonized data of ≥22,000 patients, we identified 132 patients recently treated for head and neck cancer who also demonstrated dysphagia scores that worsened from base line to a maximum grade ≥2. We developed a method that used both physical and biologically corrected (α/β = 2.5) DVH curves to test both absolute and percentage volume based DVH metrics. Combining a statistical categorization algorithm with machine learning (SCA-ML) provided more extensive detailing of response threshold evidence than either approach alone. A sensitivity guided, minimum input, machine learning (ML) model was iteratively constructed to identify the key structure DVH metric thresholds., Results: Seven swallowing structures producing 738 candidate DVH metrics were ranked for association with dysphagia using SCA-ML scoring. Structures included superior pharyngeal constrictor (SPC), inferior pharyngeal constrictor (IPC), larynx, and esophagus. Bilateral parotid and submandibular gland (SG) structures were categorized by relative mean dose (eg, SG&#95;high, SG&#95;low) as a dose versus tumor centric analog to contra and ipsilateral designations. Structure DVH metrics with high SCA-ML scores included the following: SPC: D20% (equivalent dose [EQD2] Gy) ≥47.7; SPC: D25% (Gy) ≥50.4; IPC: D35% (Gy) ≥61.7; parotid&#95;low: D60% (Gy) ≥13.2; and SG&#95;high: D35% (Gy) ≥61.7. Larynx: D25% (Gy) ≥21.2 and SG&#95;low: D45% ≥28.2 had high SCA-ML scores but were segmented on less than 90% of plans. A model based on SPC: D20% (EQD2 Gy) alone had sensitivity and area under the curve of 0.88 ± 0.13 and 0.74 ± 0.17, respectively., Conclusions: This study provides practical demonstration of combining big data with artificial intelligence to increase volume of evidence in clinical learning paradigms., (© 2020 The Author(s).)

Purpose: In recent years, the American Society for Radiation Oncology (ASTRO) has received requests for a standard list of data elements from other societies, database architects, Electronic Health Record vendors and, most recently, the pharmaceutical industry. These requests point to a growing interest in capturing radiation oncology data within registries and for quality measurement, interoperability initiatives, and research. Identifying a short and consistent list will lead to improved care coordination, a reduction in data entry by practice staff, and a more complete view of the holistic approach required for cancer treatment., Methods and Materials: The task force formulated recommendations based on analysis from radiation specific data elements currently in use in registries, accreditation programs, incident learning systems, and electronic health records. The draft manuscript was peer reviewed by 8 reviewers and ASTRO legal counsel and was revised accordingly and posted on the ASTRO website for public comment in April 2019 for 2 weeks. The final document was approved by the ASTRO Board of Directors in June 2019., (Copyright © 2019. Published by Elsevier Inc.)

Context: Adrenocortical carcinoma (ACC) is a rare malignancy with high rates of recurrence and poor prognosis. The role of radiotherapy (RT) in localized ACC has been controversial, and RT is not routinely offered., Objective: To evaluate the benefit of adjuvant RT on outcomes in ACC., Design: This is a retrospective propensity-matched analysis., Setting: All patients were seen through the University of Michigan's Endocrine Oncology program, and all those who underwent RT were treated at the University of Michigan., Participants: Of 424 patients with ACC, 78 were selected; 39 patients underwent adjuvant radiation., Intervention: Adjuvant RT to the tumor bed and adjacent lymph nodes., Main Outcomes Measures: Time to local failure, distant failure, or death., Results: Median follow-up time was 4.21 years (95% CI, 2.79 to 4.94). The median radiation dose was 55 Gy (range, 45 to 60). The 3-year overall survival estimate for patients improved from 48.6% for patients without RT (95% CI, 29.7 to 65.2) to 77.7% (95% CI, 56.3 to 89.5) with RT, with a hazard ratio (HR) of 3.59 (95% CI, 1.60 to 8.09; P = 0.002). RT improved local recurrence-free survival (RFS) from 34.2% (95% CI, 18.8 to 50.3) to 59.5% (95% CI, 39.0 to 75.0), with an HR of 2.67 (95% CI, 1.38 to 5.19; P = 0.0035). RT improved all RFS from 18.3% (95% CI, 6.7 to 34.3) to 46.7% (95% CI, 26.9 to 64.3), with an HR 2.59 (95% CI, 1.40 to 4.79; P = 0.0024)., Conclusions: In the largest single institution study to date, adjuvant RT after gross resection of ACC improved local RFS, all RFS, and overall survival in this propensity-matched analysis. Adjuvant RT should be considered a part of multidisciplinary management for patients with ACC., (Copyright © 2019 Endocrine Society.)

Purpose: To assess associations between a variety of patient-reported outcomes (PROs), observer reported toxicities (ORTs), and patient-reported overall quality of life (QOL) for head and neck cancer patients treated with radiotherapy, in order to identify important items for inclusion in prospective patient reporting in the clinic., Methods: 612 patients completed 27 PRO items from three questionnaires at 1273 follow-up visits, and clinicians provided ORTs according to CTCAE criteria. Using a big data approach, we measured associations among all PROs, between all PROs and ORTs, and between PROs/ORTs and QOL with Pearson (ρ) and Kendall (τ) correlation coefficients, and a novel analysis method based on receiver operating characteristic (ROC) curves used to detect thresholds in response levels demonstrating strong interactions., Results: PROs most strongly associated with QOL were recreation/entertainment, activity, and fatigue, with ρ = 0.51-0.60. Several PROs assessing a common functional outcome (eg. xerostomia) were highly associated with each other (PRO-PRO), with maximum ρ = 0.84. Maximum ORT-PRO correlations were ρ = 0.61 (dysgeusia versus taste), and ρ = 0.5 for ORT-QOL (dry mouth - day). The ROC method identified response thresholds with high area under the curve (AUC) scores for many ORT-PRO associations with maximum AUC avg  = 0.78., Conclusions: PRO associations identified activity, lifestyle and fatigue as items for strong consideration for inclusion in questionnaires in the clinic, and suggest that outcome information can be captured in fewer items than the 27 in this study. The ability of clinicians to assess patient toxicities is highest with more severe toxicities, underscoring the need for PRO collection in patient visits to understand and address patient symptoms., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Quantitative mapping of hyperperfused and hypercellular regions of glioblastoma has been proposed to improve definition of tumor regions at risk for local recurrence following conventional radiation therapy. As the processing of the multiparametric dynamic contrast-enhanced (DCE-) and diffusion-weighted (DW-) magnetic resonance imaging (MRI) data for delineation of these subvolumes requires additional steps that go beyond the standard practices of target definition, we sought to devise a workflow to support the timely planning and treatment of patients. A phase II study implementing a multiparametric imaging biomarker for tumor hyperperfusion and hypercellularity consisting of DCE-MRI and high b-value DW-MRI to guide intensified (75 Gy/30 fractions) radiation therapy (RT) in patients with newly diagnosed glioblastoma was launched. In this report, the workflow and the initial imaging outcomes of the first 12 patients are described. Among all the first 12 patients, treatment was initiated within 6 weeks of surgery and within 2 weeks of simulation. On average, the combined hypercellular volume and high cerebral blood volume/tumor perfusion volume were 1.8 times smaller than the T1 gadolinium abnormality and 10 times smaller than the FLAIR abnormality. Hypercellular volume and high cerebral blood volume/tumor perfusion volume each identified largely distinct regions and showed 57% overlap with the enhancing abnormality, and minimal-to-no extension outside of the FLAIR. These results show the feasibility of implementing a workflow for multiparametric magnetic resonance-guided radiation therapy into clinical trials with a coordinated multidisciplinary team, and the unique and complementary tumor subregions identified by the combination of high b-value DW-MRI and DCE-MRI.

It is an exciting time for big data efforts in radiation oncology. The use of big data to help aid both outcomes and decision-making research is becoming a reality. However, there are true challenges that exist in the space of gathering and utilizing performance and outcomes data. Here, we summarize the current state of big data in radiation oncology with respect to outcomes and discuss some of the efforts and challenges in radiation oncology big data., (© 2018 American Association of Physicists in Medicine.)

Purpose: Although inverse-planned intensity modulated radiotherapy (IMRT) and deep inspiration breath hold (DIBH) may allow for more conformal dose distributions, it is unknown whether using these technologies reduces cardiac or pulmonary toxicity of breast radiotherapy., Methods and Materials: A randomized controlled trial compared IMRT-DIBH versus standard, free-breathing, forward-planned, three-dimensional conformal radiotherapy in patients with left-sided, node-positive breast cancer in whom the internal mammary nodal region was targeted. Endpoints included dosimetric parameters and changes in pulmonary and cardiac perfusion and function, measured by single photon emission computed tomography (SPECT) scans and pulmonary function testing performed at baseline and 1 year post treatment., Results: Of 62 patients randomized, 54 who completed all follow-up procedures were analyzed. Mean doses to the ipsilateral lung, left ventricle, whole heart, and left anterior descending coronary artery were lower with IMRT-DIBH; the percent of left ventricle receiving ≥5 Gy averaged 15.8% with standard radiotherapy and 5.6% with IMRT-DIBH (P < .001). SPECT revealed no differences in perfusion defects in the left anterior descending coronary artery territory, the study's primary endpoint, but did reveal statistically significant differences (P = .02) in left ventricular ejection fraction (LVEF), a secondary endpoint. No differences were found for lung perfusion or function., Conclusion: The small but statistically significant benefit in preservation of cardiac LVEF observed here should motivate future studies that include LVEF as a potentially meaningful endpoint. Future studies should disaggregate the impact of IMRT from that of DIBH. Clinical practice should recognize the importance of minimizing cardiac dose, even when already low in comparison to historical levels., (Copyright © 2018 Elsevier Inc. All rights reserved.)

A substantial barrier to the single- and multi-institutional aggregation of data to supporting clinical trials, practice quality improvement efforts, and development of big data analytics resource systems is the lack of standardized nomenclatures for expressing dosimetric data. To address this issue, the American Association of Physicists in Medicine (AAPM) Task Group 263 was charged with providing nomenclature guidelines and values in radiation oncology for use in clinical trials, data-pooling initiatives, population-based studies, and routine clinical care by standardizing: (1) structure names across image processing and treatment planning system platforms; (2) nomenclature for dosimetric data (eg, dose-volume histogram [DVH]-based metrics); (3) templates for clinical trial groups and users of an initial subset of software platforms to facilitate adoption of the standards; (4) formalism for nomenclature schema, which can accommodate the addition of other structures defined in the future. A multisociety, multidisciplinary, multinational group of 57 members representing stake holders ranging from large academic centers to community clinics and vendors was assembled, including physicists, physicians, dosimetrists, and vendors. The stakeholder groups represented in the membership included the AAPM, American Society for Radiation Oncology (ASTRO), NRG Oncology, European Society for Radiation Oncology (ESTRO), Radiation Therapy Oncology Group (RTOG), Children's Oncology Group (COG), Integrating Healthcare Enterprise in Radiation Oncology (IHE-RO), and Digital Imaging and Communications in Medicine working group (DICOM WG); A nomenclature system for target and organ at risk volumes and DVH nomenclature was developed and piloted to demonstrate viability across a range of clinics and within the framework of clinical trials. The final report was approved by AAPM in October 2017. The approval process included review by 8 AAPM committees, with additional review by ASTRO, European Society for Radiation Oncology (ESTRO), and American Association of Medical Dosimetrists (AAMD). This Executive Summary of the report highlights the key recommendations for clinical practice, research, and trials., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

Patient- and provider-reported outcomes are recognized as important in evaluating quality of care, guiding health care policy, comparative effectiveness research, and decision-making in radiation oncology. Combining patient and provider outcome data with a detailed description of disease and therapy is the basis for these analyses. We report on the combination of technical solutions and clinical process changes at our institution that were used in the collection and dissemination of this data. This initiative has resulted in the collection of treatment data for 23 541 patients, 20 465 patients with provider-based adverse event records, and patient-reported outcome surveys submitted by 5622 patients. All of the data is made accessible using a self-service web-based tool.

Background: Early death after a treatment can be seen as a therapeutic failure. Accurate prediction of patients at risk for early mortality is crucial to avoid unnecessary harm and reducing costs. The goal of our work is two-fold: first, to evaluate the performance of a previously published model for early death in our cohorts. Second, to develop a prognostic model for early death prediction following radiotherapy., Material and Methods: Patients with NSCLC treated with chemoradiotherapy or radiotherapy alone were included in this study. Four different cohorts from different countries were available for this work (N = 1540). The previous model used age, gender, performance status, tumor stage, income deprivation, no previous treatment given (yes/no) and body mass index to make predictions. A random forest model was developed by learning on the Maastro cohort (N = 698). The new model used performance status, age, gender, T and N stage, total tumor volume (cc), total tumor dose (Gy) and chemotherapy timing (none, sequential, concurrent) to make predictions. Death within 4 months of receiving the first radiotherapy fraction was used as the outcome., Results: Early death rates ranged from 6 to 11% within the four cohorts. The previous model performed with AUC values ranging from 0.54 to 0.64 on the validation cohorts. Our newly developed model had improved AUC values ranging from 0.62 to 0.71 on the validation cohorts., Conclusions: Using advanced machine learning methods and informative variables, prognostic models for early mortality can be developed. Development of accurate prognostic tools for early mortality is important to inform patients about treatment options and optimize care.

Emergence of big data analytics resource systems (BDARSs) as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs) have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events. BDARS present opportunities to augment and extend RCTs. Preliminary modeling using single- and muti-institutional BDARS may lead to better design and less cost. Standardizations in data elements, clinical processes, and nomenclatures used to decrease variability and increase veracity needed for automation and multi-institutional data pooling in BDARS also support ability to add clinical validation phases to clinical trial design and increase participation. However, volume and variety in BDARS present other technical, policy, and conceptual challenges including applicable statistical concepts, cloud-based technologies. In this summary, we will examine both the opportunities and the challenges for use of big data in design of clinical trials.

Purpose: To develop statistical dose-volume histogram (DVH)-based metrics and a visualization method to quantify the comparison of treatment plans with historical experience and among different institutions., Methods and Materials: The descriptive statistical summary (ie, median, first and third quartiles, and 95% confidence intervals) of volume-normalized DVH curve sets of past experiences was visualized through the creation of statistical DVH plots. Detailed distribution parameters were calculated and stored in JavaScript Object Notation files to facilitate management, including transfer and potential multi-institutional comparisons. In the treatment plan evaluation, structure DVH curves were scored against computed statistical DVHs and weighted experience scores (WESs). Individual, clinically used, DVH-based metrics were integrated into a generalized evaluation metric (GEM) as a priority-weighted sum of normalized incomplete gamma functions. Historical treatment plans for 351 patients with head and neck cancer, 104 with prostate cancer who were treated with conventional fractionation, and 94 with liver cancer who were treated with stereotactic body radiation therapy were analyzed to demonstrate the usage of statistical DVH, WES, and GEM in a plan evaluation. A shareable dashboard plugin was created to display statistical DVHs and integrate GEM and WES scores into a clinical plan evaluation within the treatment planning system. Benchmarking with normal tissue complication probability scores was carried out to compare the behavior of GEM and WES scores., Results: DVH curves from historical treatment plans were characterized and presented, with difficult-to-spare structures (ie, frequently compromised organs at risk) identified. Quantitative evaluations by GEM and/or WES compared favorably with the normal tissue complication probability Lyman-Kutcher-Burman model, transforming a set of discrete threshold-priority limits into a continuous model reflecting physician objectives and historical experience., Conclusions: Statistical DVH offers an easy-to-read, detailed, and comprehensive way to visualize the quantitative comparison with historical experiences and among institutions. WES and GEM metrics offer a flexible means of incorporating discrete threshold-prioritizations and historic context into a set of standardized scoring metrics. Together, they provide a practical approach for incorporating big data into clinical practice for treatment plan evaluations.

Although large volumes of information are entered into our electronic health care records, radiation oncology information systems and treatment planning systems on a daily basis, the goal of extracting and using this big data has been slow to emerge. Development of strategies to meet this goal is aided by examining issues with a data farming instead of a data mining conceptualization. Using this model, a vision of key data elements, clinical process changes, technology issues and solutions, and role for professional societies is presented. With a better view of technology, process and standardization factors, definition and prioritization of efforts can be more effectively directed.

Introduction: Establishment of standards within a practice and across disease site groups for nomenclatures, prescription formatting, and measured dose-volume histogram (DVH) metrics is a key enabling step for creating software and database solutions to make routine aggregation of dosimetric data for all patients treated in a practice, practical. A process of physician-driven, iterative dialogs coupled with development of technical tools is required to implement the cultural and procedural changes. The cumulative reward for this effort is a database that can be used for defining practice norms, benchmarking against national standards, and tracking dosimetric effects of longitudinal practice pattern changes., Methods and Materials: A 4-year project was carried out to develop and introduce standardizations, modify processes, and develop computer-based tools for reporting, aggregation, and analysis of prescription and DVH metrics. Physician disease site groups developed 42 target and 81 normal tissue templates. From the database of 32,002 DVH metrics, benchmarking was illustrated for a subgroup of breast (281) and prostate (324) patients treated with conventional fractionation over a 16-month period. Breast patients were segregated according to prescription template used: simple (S, tangents only) vs complex (C, tangents + supraclavicular ± intramammary nodes) and left (S-L or C-L) versus right (S-R or C-R)., Results: Prostate patients' median and 50% confidence intervals (CIs) for bladder, stated according to the nomenclature: the percentage of bladder volume receiving doses of ≥40 Gy (V40[%]), V65Gy[%], V70Gy[%], V75Gy[%], and V80Gy[%] were 45.5 (24.9-57.0), 15.6 (9.0-23.8), 7.6 (3.3-13.6), 2.0 (0.0-7.9), and 0.0 (0.0-1.4), respectively. Values for rectum: V50Gy[%], V60 Gy[%], V65Gy[%], V70Gy[%], and V75Gy[%] were 37.1 (27.8-43.5), 21.8 (15.6-25.5), 14.6 (9.6-18.0), 7.7 (1.9-12.3), and 1.0 (0-7.0), respectively. For breast patients, heart:mean Gray values were 1.5 (1.0-2.0), 3.1 (2.2-4.8), 0.4 (0.3-0.7), and 1.1 (0.8-2.2) for S-L, C-L, S-R, and C-R, respectively. Longitudinal, moving window plots of median, 50% CI, and 90% CI for 6-month periods demonstrated the effect of practice changes to reduce heart doses., Conclusions: Standardization was challenging as a practice change, but has resulted in significant improvements for both our clinical and research efforts., (Copyright © 2016 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.)

Introduction: To better understand the efficacy of liver SBRT we reviewed our prospectively collected institutional SBRT database., Methods: Between May 2008 and March 2013, 80 patients with 104 liver lesions received SBRT. The Kaplan-Meier method estimated local control (LC), overall survival (OS). Cox proportional hazards regression models identified factors associated with LC and OS., Results: The median follow-up for living patients was 38.6 months. Patients had primary (n=17) or metastatic (n=63) tumors. The median tumor size was 2.7 cm (range, 0.6-14.0). The 1 and 4 year rates of LC were 89.4% and 88%, respectively. Colorectal (CRC) metastasis was associated with lower rates of LC (p=0.013). OS at 1 and 4 years was 78% and 25%, respectively. Patients with CRC metastases had higher rates of OS (p=0.03). The occurrence of severe acute and late toxicity was 3.8% and 6.3%, respectively., Conclusions: SBRT should be studied in prospective clinical trials compared with other liver-directed treatment modalities., Competing Interests: Authors’ disclosure of potential conflicts of interest The authors reported no conflict of interest.

Background: Spine stereotactic body radiation therapy (SBRT) is becoming widely accepted as first-line treatment of oligometastatic spine disease as well as in the postoperative setting. The reported incidence of myelopathy is very low and guidelines vary widely on the maximum tolerable dose of the spinal cord and thecal sac., Methods and Materials: Between April 2008 and December 2010, radiation parameters were exported for 46 patients treated with spine SBRT at the Mayo Clinic. Using an in-house data mining program, dose-volume histogram constraints were extracted, including dose prescription, dose fractionation, planning target volume, planning target volume coverage, maximum dose to the cord, D2cc thecal sac, and D2cc spinal cord. Diagnostic magnetic resonance imaging scans and/or computed tomography myelograms were fused with the planning set to delineate the cord and thecal sac for receiver operating characteristic analysis of cord and thecal sac subvolume doses. A high-resolution planning at-risk volume was created in 1-mm increments for cord (1-7 mm) and the thecal sac (1-2 mm) to examine dose gradients that might be correlated with toxicity., Results: No patients experienced myelopathy with a median follow-up of 14 months. The most common toxicities were pain and nausea. Median values of D2cc maximum dose (maximum dose received by 2 cc of the organ at risk; biologically equivalent 2-Gy dose maximum [EQD2]) for cord and thecal sac were 38.5 Gy (range, 7.5-67.9 Gy) and 67.7 Gy (range, 15.5-155.8 Gy), respectively. Median values for high-dose subvolumes for cord and thecal sac were 2 times higher than the doses for 5% predicted grade 3 cord toxicity as recommended in the current literature. Cord D0.1cc[EQD2] ≥23.8 Gy was correlated with pain flare (n = 5). Thecal sac D2cc [EQD2] ≥29.3 Gy was a significant indicator of nausea., Conclusion: Current guidelines may overestimate the risk of myelopathy from spine SBRT. The current study's population included both radiation-naïve and retreatment cases, but no myelopathy was observed despite exceeding recommended spine limits.

Background: Stereotactic body radiotherapy (SBRT) is evolving into a standard of care for unresectable lung nodules. Local control has been shown to be in excess of 90% at 3 years. However, some patients present with synchronous lung nodules in the ipsilateral or contralateral lobe or metasynchronous disease. In these cases, patients may receive multiple courses of lung SBRT or a single course for synchronous nodules. The toxicity of such treatment is currently unknown., Methods: Between 2006 and 2012, 63 subjects with 128 metasynchronous and synchronous lung nodules were treated at the Mayo Clinic with SBRT. Demographic patient data and dosimetric data regarding SBRT treatments were collected. Acute toxicity (defined as toxicity < 90 days) and late toxicity (defined as toxicity > = 90 days) were reported and graded as per standardized CTCAE 4.0 criteria. Local control, progression free survival and overall survival were also described., Results: The median age of patients treated was 73 years. Sixty five percent were primary or recurrent lung cancers with the remainder metastatic lung nodules of varying histologies. Of 63 patients, 18 had prior high dose external beam radiation to the mediastinum or chest. Dose and fractionation varied but the most common prescriptions were 48 Gy/4 fractions, 54 Gy/3 fractions, and 50 Gy/5 fractions. Only 6 patients demonstrated local recurrence. With a median follow up of 12.6 months, median SBRT specific overall survival and progression free survival were 35.7 months and 10.7 months respectively. Fifty one percent (32/63 patients) experienced acute toxicity, predominantly grade 1 and 2 fatigue. One patient developed acute grade 3 radiation pneumonitis at 75 days. Forty six percent (29/63 patients) developed late effects. Most were grade 1 dyspnea. There was one patient with grade 5 pneumonitis., Conclusion: Multiple courses of SBRT and SBRT delivery after external beam radiotherapy appear to be feasible and safe. Most toxicity was grade 1 and 2 but the risk was approximately 50% for both acute and late effects.