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Involvement of many variables, uncertainty in treatment response, and inter-patient heterogeneity challenge objective decision-making in dynamic treatment regime (DTR) in oncology. Advanced machine learning analytics in conjunction with information-rich dense multi-omics data have the ability to overcome such challenges. We have developed a comprehensive artificial intelligence (AI)-based optimal decision-making framework for assisting oncologists in DTR. In this work, we demonstrate the proposed framework to Knowledge Based Response-Adaptive Radiotherapy (KBR-ART) applications by developing an interactive software tool entitled Adaptive Radiotherapy Clinical Decision Support (ARCliDS). ARCliDS is composed of two main components: Artifcial RT Environment (ARTE) and Optimal Decision Maker (ODM). ARTE is designed as a Markov decision process and modeled via supervised learning. Given a patient's pre- and during-treatment information, ARTE can estimate treatment outcomes for a selected daily dosage value (radiation fraction size). ODM is formulated using reinforcement learning and is trained on ARTE. ODM can recommend optimal daily dosage adjustments to maximize the tumor local control probability and minimize the side effects. Graph Neural Networks (GNN) are applied to exploit the inter-feature relationships for improved modeling performance and a novel double GNN architecture is designed to avoid nonphysical treatment response. Datasets of size 117 and 292 were available from two clinical trials on adaptive RT in non-small cell lung cancer (NSCLC) patients and adaptive stereotactic body RT (SBRT) in hepatocellular carcinoma (HCC) patients, respectively. For training and validation, dense data with 297 features were available for 67 NSCLC patients and 110 features for 71 HCC patients. To increase the sample size for ODM training, we applied Generative Adversarial Networks to generate 10,000 synthetic patients. The ODM was trained on the synthetic patients and validated on the original dataset. We found that, Double GNN architecture was able to correct the nonphysical dose-response trend and improve ARCliDS recommendation. The average root mean squared difference (RMSD) between ARCliDS recommendation and reported clinical decisions using double GNNs were 0.61 [0.03] Gy/frac (mean [sem]) for adaptive RT in NSCLC patients and 2.96 [0.42] Gy/frac for adaptive SBRT HCC compared to the single GNN's RMSDs of 0.97 [0.12] Gy/frac and 4.75 [0.16] Gy/frac, respectively. Overall, For NSCLC and HCC, ARCliDS with double GNNs was able to reproduce 36% and 50% of the good clinical decisions (local control and no side effects) and improve 74% and 30% of the bad clinical decisions, respectively. In conclusion, ARCliDS is the first web-based software dedicated to assist KBR-ART with multi-omics data. ARCliDS can learn from the reported clinical decisions and facilitate AI-assisted clinical decision-making for improving the outcomes in DTR., (© 2023. The Author(s).)

Purpose: Current radiation therapy (RT) treatment planning relies mainly on pre-defined dose-based objectives and constraints to develop plans that aim to control disease while limiting damage to normal tissues during treatment. These objectives and constraints are generally population-based, in that they are developed from the aggregate response of a broad patient population to radiation. However, correlations of new biologic markers and patient-specific factors to treatment efficacy and toxicity provide the opportunity to further stratify patient populations and develop a more individualized approach to RT planning. We introduce a novel intensity-modulated radiation therapy (IMRT) optimization strategy that directly incorporates patient-specific dose response models into the planning process. In this strategy, we integrate the concept of utility-based planning where the optimization objective is to maximize the predicted value of overall treatment utility, defined by the probability of efficacy (e.g., local control) minus the weighted sum of toxicity probabilities. To demonstrate the feasibility of the approach, we apply the strategy to treatment planning for non-small cell lung cancer (NSCLC) patients., Methods and Materials: We developed a prioritized approach to patient-specific IMRT planning. Using a commercial treatment planning system (TPS), we calculate dose based on an influence matrix of beamlet-dose contributions to regions-of-interest. Then, outside of the TPS, we hierarchically solve two optimization problems to generate optimal beamlet weights that can then be imported back to the TPS. The first optimization problem maximizes a patient's overall plan utility subject to typical clinical dose constraints. In this process, we facilitate direct optimization of efficacy and toxicity trade-off based on individualized dose-response models. After optimal utility is determined, we solve a secondary optimization problem that minimizes a conventional dose-based objective subject to the same clinical dose constraints as the first stage but with the addition of a constraint to maintain the optimal utility from the first optimization solution. We tested this method by retrospectively generating plans for five previously treated NSCLC patients and comparing the prioritized utility plans to conventional plans optimized with only dose metric objectives. To define a plan utility function for each patient, we utilized previously published correlations of dose to local control and grade 3-5 toxicities that include patient age, stage, microRNA levels, and cytokine levels, among other clinical factors., Results: The proposed optimization approach successfully generated RT plans for five NSCLC patients that improve overall plan utility based on personalized efficacy and toxicity models while accounting for clinical dose constraints. Prioritized utility plans demonstrated the largest average improvement in local control (16.6%) when compared to plans generated with conventional planning objectives. However, for some patients, the utility-based plans resulted in similar local control estimates with decreased estimated toxicity., Conclusion: The proposed optimization approach, where the maximization of a patient's RT plan utility is prioritized over the minimization of standardized dose metrics, has the potential to improve treatment outcomes by directly accounting for variability within a patient population. The implementation of the utility-based objective function offers an intuitive, humanized approach to biological optimization in which planning trade-offs are explicitly optimized., (© 2022 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Purpose: Historical racial disparities in lung cancer surgery rates resulted in lower survival in Black patients. Our objective was to examine racial differences in thoracic radiation treatments and toxicities in patients with non-small-cell lung cancer., Methods and Materials: A large institutional review board-approved statewide patient-level database of patients with stage II-III non-small-cell lung cancer who received definitive thoracic radiation from March 2012 to November 2019 was analyzed to assess associations between race and other variables. Race (White or Black) was defined by patient self-report. Provider-reported toxicity was defined by Common Terminology Criteria for Adverse Events version 4.0. Patient-reported toxicity was determined by the Functional Assessment of Cancer Therapy-Lung quality-of-life instrument. Univariable and multivariable regression models were fitted to assess relationships between race and variables of interest. Spearman rank-correlation coefficients were calculated between provider-reported toxicity and similar patient-reported outcomes., Results: One thousand four hundred forty-one patients from 24 institutions with mean age 68 years (range, 38-94 years) were evaluated. Race was not significantly associated with radiation or chemotherapy approach. There was significantly increased patient-reported general pain in Black patients at the preradiation and end-of-radiation time points. Black patients were significantly less likely to have provider-reported grade 2+ pneumonitis (odds ratio 0.36, P = .03), even after controlling for known patient and treatment factors. Correlation coefficients between provider- and patient-reported toxicities were generally similar across race groups except for a stronger correlation between patient- and provider-reported esophagitis in White patients., Conclusion: In this large multi-institutional study, we found no evidence of racial differences in radiation treatment or chemotherapy approaches. We did, however, unexpectedly find that Black race was associated with lower odds of provider-reported grade 2+ radiation pneumonitis. The stronger correlation between patient- and provider-reported esophagitis and swallowing symptoms for White patients also suggests possible under-recognition of symptoms in Black patients. Further research is needed to study the implications for Black patients., Competing Interests: Anna Mary Brown LaucisPatents, Royalties, Other Intellectual Property: Patent pending Matthew J. SchipperConsulting or Advisory Role: Innovative Analytics Peter A. PaximadisTravel, Accommodations, Expenses: Zeiss Thomas P. BoikeEmployment: MHP Radiation Oncology InstituteConsulting or Advisory Role: Blue Earth DiagnosticsSpeakers' Bureau: Boston Scientific Benjamin MovsasResearch Funding: Varian Medical Systems (Inst), Philips Healthcare (Inst), ViewRay (Inst)Patents, Royalties, Other Intellectual Property: Lung phantom for image guidance, MR-CT imaging–related patent for radiation oncologyTravel, Accommodations, Expenses: Varian Medical Systems Daniel E. SprattHonoraria: Varian Medical SystemsConsulting or Advisory Role: Janssen Oncology, AstraZeneca, Boston Scientific, Bayer, Blue Earth Diagnostics, Varian Medical SystemsResearch Funding: Janssen (Inst)Open Payments Link: https://openpaymentsdata.cms.gov/physician/869226 Michael M. DominelloResearch Funding: Novocure Martha M. MatuszakConsulting or Advisory Role: Varian Medical SystemsResearch Funding: Varian Medical SystemsOther Relationship: Blue Cross Blue Shield of Michigan Reshma JagsiThis author is a member of the Journal of Oncology Practice Editorial Board. Journal policy recused the author from having any role in the peer review of this manuscript.Employment: University of MichiganStock and Other Ownership Interests: Equity QuotientResearch Funding: Genentech (Inst)Expert Testimony: Baptist Health/Dressman Benziger Lavalle Law, Kleinbard, LLC, Sherinian and HassoTravel, Accommodations, Expenses: AmgenOther Relationship: JAMA OncologyOpen Payments Link: https://openpaymentsdata.cms.gov/physician/373670/summary Lori J. PierceStock and Other Ownership Interests: PFS GenomicsPatents, Royalties, Other Intellectual Property: UpToDate, PFS GenomicsUncompensated Relationships: Bristol Myers Squibb, Exact SciencesOpen Payments Link: https://openpaymentsdata.cms.gov/physician/1250431/summary Shruti JollyHonoraria: Varian Medical SystemsConsulting or Advisory Role: AstraZeneca, Varian Medical SystemsNo other potential conflicts of interest were reported.

Objectives: The addition of adjuvant durvalumab improves overall survival in locally advanced nonsmall-cell lung cancer (NSCLC) patients treated with definitive chemoradiation, but the real-world uptake of adjuvant durvalumab is unknown., Materials and Methods: We identified patients with stage III NSCLC treated with definitive concurrent chemoradiation from January 2018 to October 2020 from a statewide radiation oncology quality consortium, representing a mix of community (n=22 centers) and academic (n=5) across the state of Michigan. Use of adjuvant durvalumab was ascertained at the time of routine 3-month or 6-month follow-up after completion of chemoradiation., Results: Of 421 patients with stage III NSCLC who completed chemoradiation, 322 (76.5%) initiated adjuvant durvalumab. The percentage of patients initiating adjuvant durvalumab increased over time from 66% early in the study period to 92% at the end of the study period. There was substantial heterogeneity by treatment center, ranging from 53% to 90%. In multivariable logistic regression, independent predictors of durvalumab initiation included more recent month (odds ratio [OR]: 1.05 per month, 95% confidence interval [CI]: 1.02-1.08, P=0.003), lower Eastern Cooperative Oncology Group score (OR: 4.02 for ECOG 0 vs. 2+, 95% CI: 1.67-9.64, P=0.002), and a trend toward significance for female sex (OR: 1.66, 95% CI: 0.98-2.82, P=0.06)., Conclusion: Adjuvant durvalumab for stage III NSCLC treated with definitive chemoradiation was rapidly and successfully incorporated into clinical care across a range of community and academic settings in the state of Michigan, with over 90% of potentially eligible patients starting durvalumab in more recent months., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: Multiple factors influence the risk of developing pneumonitis after radiation therapy (RT) for lung cancer, but few resources exist to guide clinicians in predicting risk in an individual patient treated with modern techniques. We analyzed toxicity data from a state-wide consortium to develop an integrated pneumonitis risk model., Methods and Materials: All patients (N = 1302) received conventionally fractionated RT for stage II-III non-small cell lung cancer between April 2012 and July 2019. Pneumonitis occurring within 6 months of treatment was graded by local practitioners and collected prospectively from 27 academic and community clinics participating in a state-wide quality consortium. Pneumonitis was modeled as either grade ≥2 (G2+) or grade ≥3 (G3+). Logistic regression models were fit to quantify univariable associations with dose and clinical factors, and stepwise Akaike information criterion-based modeling was used to build multivariable prediction models., Results: The overall rate of pneumonitis of any grade in the 6 months following RT was 16% (208 cases). Seven percent of cases (n = 94) were G2+ and <1% (n = 11) were G3+. Adjusting for incomplete follow-up, estimated rates for G2+ and G3+ were 14% and 2%, respectively. In univariate analyses, gEUD, V5, V10, V20, V30, and mean lung dose (MLD) were positively associated with G2+ pneumonitis risk, whereas current smoking status was associated with lower odds of pneumonitis. G2+ pneumonitis risk of ≥22% was independently predicted by MLD of ≥20 Gy, V20 of ≥35%, and V5 of ≥75%. In multivariate analyses, the lung V5 metric remained a significant predictor of G2+ pneumonitis, even when controlling for MLD, despite their close correlation. For G3+ pneumonitis, MLD and V20 were statistically significant predictors. Number of patient comorbidities was an independent predictor of G3+, but not G2+ pneumonitis., Conclusions: We present an analysis of pneumonitis risk after definitive RT for lung cancer using a large, prospective dataset. We incorporate comorbidity burden, smoking status, and dosimetric parameters in an integrated risk model. These data may guide clinicians in assessing pneumonitis risk in individual patients., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Purpose: To study the dosimetric risk factors for radiation-induced proximal bronchial tree (PBT) toxicity in patients treated with radiation therapy for non-small cell lung cancer (NSCLC)., Methods and Materials: Patients with medically inoperable or unresectable NSCLC treated with conventionally fractionated 3-dimensional conformal radiation therapy (3DCRT) in prospective clinical trials were eligible for this study. Proximal bronchial tree (PBT) and PBT wall were contoured consistently per RTOG 1106 OAR-Atlas. The dose-volume histograms (DVHs) of physical prescription dose (DVHp) and biological effective dose (α/β = 2.5; DVH2.5) were generated, respectively. The primary endpoint was PBT toxicities, defined by CTCAE 4.0 under the terminology of bronchial stricture/atelectasis., Results: Of 100 patients enrolled, with a median follow-up of 64 months (95% confidence interval [CI], 50-78), 73% received 70 Gy or greater and 17% developed PBT toxicity (grade 1, 8%; grade 2, 6%; grade 3, 0%; and grade 4, 3%). The median time interval between RT initiation and onset of PBT toxicity was 8.4 months (95% CI, 4.7-44.1). The combined DVHs showed that no patient with a PBT maximum physical dose <65 Gy developed any PBT toxicity. Cox proportional hazards analysis and receiver operating characteristic analysis demonstrated that V75 of PBT was the most significant dosimetric parameter for both grade 1+ (P = .035) and grade 2+ (P = .037) PBT toxicities. The dosimetric thresholds for V75 of PBT were 6.8% and 11.9% for grade 1+ and grade 2+ PBT toxicity, respectively., Conclusions: V75 of PBT appeared be the most significant dosimetric parameter for PBT toxicity after conventionally fractionated thoracic 3DCRT. Constraining V75 of PBT can limit clinically significant PBT toxicity., (Copyright © 2020. Published by Elsevier Inc.)

Purpose: The heart has been identified as a potential significant organ at risk in patients with locally advanced non-small cell lung cancer treated with radiation. Practice patterns and radiation dose delivered to the heart in routine practice in academic and community settings are unknown., Methods and Materials: Between 2012 and 2017, 746 patients with stage III non-small cell lung cancer were treated with radiation within the statewide Michigan Radiation Oncology Quality Consortium (MROQC). Cardiac radiation dose was characterized, including mean and those exceeding historical or recently proposed Radiation Therapy Oncology Group and NRG Oncology constraints. Sites were surveyed to determine dose constraints used in practice. Patient-, anatomic-, and treatment-related associations with cardiac dose were analyzed using multivariable regression analysis and inverse probability weighting., Results: Thirty-eight percent of patients had a left-sided primary, and 80% had N2 or N3 disease. Median prescription was 60 Gy (interquartile range, 60-66 Gy). Twenty-two percent of patients were prescribed 60 Gy in 2012, which increased to 62% by 2017 (P < .001). Median mean heart dose was 12 Gy (interquartile range, 5-19 Gy). The volume receiving 30 Gy (V30 Gy) exceeded 50% in 5% of patients, and V40 Gy was >35% in 3% of cases. No heart dose constraint was uniformly applied. Intensity modulated radiation therapy (IMRT) usage increased from 33% in 2012 to 86% in 2017 (P < .001) and was significantly associated with more complex cases (larger planning target volume, higher stage, and preexisting cardiac disease). In multivariable regression analysis, IMRT was associated with a lower percent of the heart receiving V30 Gy (absolute reduction = 3.0%; 95% confidence interval, 0.5%-5.4%) and V50 Gy (absolute reduction = 3.6%; 95% confidence interval, 2.4%-4.8%) but not mean dose. In inverse probability weighting analysis, IMRT was associated with 29% to 48% relative reduction in percent of the heart receiving V40-V60 Gy without increasing lung or esophageal dose or compromising planning target volume coverage., Conclusions: Within MROQC, historical cardiac constraints were met in most cases, yet 1 in 4 patients received a mean heart dose exceeding 20 Gy. Future work is required to standardize heart dose constraints and to develop treatment approaches that allow for constraints to be met without compromising other planning goals., (Copyright © 2019 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.)

Purpose: Radiation-induced cardiac toxicity (RICT) is an increasingly well-appreciated source of morbidity and mortality in patients receiving thoracic radiotherapy (RT). Currently available methods to predict RICT are suboptimal. We investigated circulating microRNAs (c-miRNAs) as potential biomarkers of RICT in patients undergoing definitive RT for non-small-cell lung cancer (NSCLC)., Methods: Data from 63 patients treated on institutional trials were analyzed. Prognostic models of grade 3 or greater (G3 +) RICT based on pre-treatment c-miRNA levels ('c-miRNA'), mean heart dose (MHD) and pre-existing cardiac disease (PCD) ('clinical'), and a combination of these ('c-miRNA + clinical') were developed. Elastic net Cox regression and full cross validation were used for variable selection, model building, and model evaluation. Concordance statistic (c-index) and integrated Brier score (IBS) were used to evaluate model performance., Results: MHD, PCD, and serum levels of 14 c-miRNA species were identified as jointly prognostic for G3 + RICT. The 'c-miRNA and 'clinical' models yielded similar cross-validated c-indices (0.70 and 0.72, respectively) and IBSs (0.26 and 0.28, respectively). However, prognostication was not improved by combining c-miRNA and clinical factors (c-index 0.70, IBS 0.28). The 'c-miRNA' and 'clinical' models were able to significantly stratify patients into high- and low-risk groups of developing G3 + RICT. Chi-square testing demonstrated a marginally significantly higher prevalence of PCD in patients with high- compared to low-risk c-miRNA profile (p = 0.09), suggesting an association between some c-miRNAs and PCD., Conclusions: We identified a pre-treatment c-miRNA signature prognostic for G3 + RICT. With further development, pre- and mid-treatment c-miRNA profiling could contribute to patient-specific dose selection and treatment adaptation.

Purpose: Functional-guided radiation therapy (RT) plans have the potential to limit damage to normal tissue and reduce toxicity. Although functional imaging modalities have continued to improve, a limited understanding of the functional response to radiation and its application to personalized therapy has hindered clinical implementation. The purpose of this study was to retrospectively model the longitudinal, patient-specific dose-function response in non-small cell lung cancer patients treated with RT to better characterize the expected functional damage in future, unknown patients., Methods and Materials: Perfusion single-photon emission computed tomography/computed tomography scans were obtained at baseline (n = 81), midtreatment (n = 74), 3 months post-treatment (n = 51), and 1 year post-treatment (n = 26) and retrospectively analyzed. Patients were treated with conventionally fractionated RT or stereotactic body RT. Normalized perfusion single-photon emission computed tomography voxel intensity was used as a surrogate for local lung function. A patient-specific logistic model was applied to each individual patient's dose-function response to characterize functional reduction at each imaging time point. Patient-specific model parameters were averaged to create a population-level logistic dose-response model., Results: A significant longitudinal decrease in lung function was observed after RT by analyzing the voxelwise change in normalized perfusion intensity. Generated dose-function response models represent the expected voxelwise reduction in function, and the associated uncertainty, for an unknown patient receiving conventionally fractionated RT or stereotactic body RT. Differential treatment responses based on the functional status of the voxel at baseline suggest that initially higher functioning voxels are damaged at a higher rate than lower functioning voxels., Conclusions: This study modeled the patient-specific dose-function response in patients with non-small cell lung cancer during and after radiation treatment. The generated population-level dose-function response models were derived from individual patient assessment and have the potential to inform functional-guided treatment plans regarding the expected functional lung damage. This type of patient-specific modeling approach can be applied broadly to other functional response analyses to better capture intrapatient dependencies and characterize personalized functional damage., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background and Purpose: To study whether cytokine markers may improve predictive accuracy of radiation esophagitis (RE) in non-small cell lung cancer (NSCLC) patients., Materials and Methods: A total of 129 patients with stage I-III NSCLC treated with radiotherapy (RT) from prospective studies were included. Thirty inflammatory cytokines were measured in platelet-poor plasma samples. Logistic regression was performed to evaluate the risk factors of RE. Stepwise Akaike information criterion (AIC) and likelihood ratio test were used to assess model predictions., Results: Forty-nine of 129 patients (38.0%) developed grade ≥2 RE. Univariate analysis showed that age, stage, concurrent chemotherapy, and eight dosimetric parameters were significantly associated with grade ≥2 RE (p < 0.05). IL-4, IL-5, IL-8, IL-13, IL-15, IL-1α, TGFα and eotaxin were also associated with grade ≥2 RE (p < 0.1). Age, esophagus generalized equivalent uniform dose (EUD), and baseline IL-8 were independently associated grade ≥2 RE. The combination of these three factors had significantly higher predictive power than any single factor alone. Addition of IL-8 to toxicity model significantly improves RE predictive accuracy (p = 0.019)., Conclusions: Combining baseline level of IL-8, age and esophagus EUD may predict RE more accurately. Refinement of this model with larger sample sizes and validation from multicenter database are warranted., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: To assess the utility of circulating serum microRNAs (c-miRNAs) to predict response to high-dose radiation therapy for locally advanced non-small cell lung cancer (NSCLC)., Methods and Materials: Data from 80 patients treated from 2004 to 2013 with definitive standard- or high-dose radiation therapy for stages II-III NSCLC as part of 4 prospective institutional clinical trials were evaluated. Pretreatment serum levels of 62 miRNAs were measured by quantitative reverse transcription-polymerase chain reaction array. We combined miRNA data and clinical factors to generate a dose-response score (DRS) for predicting overall survival (OS) after high-dose versus standard-dose radiation therapy. Elastic net Cox regression was used for variable selection and parameter estimation. Model assessment and tuning parameter selection were performed through full cross-validation. The DRS was also correlated with local progression, distant metastasis, and grade 3 or higher cardiac toxicity using Cox regression, and grade 2 or higher esophageal and pulmonary toxicity using logistic regression., Results: Eleven predictive miRNAs were combined with clinical factors to generate a DRS for each patient. In patients with low DRS, high-dose radiation therapy was associated with significantly improved OS compared to treatment with standard-dose radiation therapy (hazard ratio 0.22). In these patients, high-dose radiation also conferred lower risk of distant metastasis and local progression, although the latter association was not statistically significant. Patients with high DRS exhibited similar rates of OS regardless of dose (hazard ratio 0.78). The DRS did not correlate with treatment-related toxicity., Conclusions: Using c-miRNA signature and clinical factors, we developed a DRS that identified a subset of patients with locally advanced NSCLC who derive an OS benefit from high-dose radiation therapy. This DRS may guide dose escalation in a patient-specific manner., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background and Purpose: Current methods to estimate risk of radiation-induced lung toxicity (RILT) rely on dosimetric parameters. We aimed to improve prognostication by incorporating clinical and cytokine data, and to investigate how these factors may interact with the effect of mean lung dose (MLD) on RILT., Materials and Methods: Data from 125 patients treated from 2004 to 2013 with definitive radiotherapy for stages I-III NSCLC on four prospective clinical trials were analyzed. Plasma levels of 30 cytokines were measured pretreatment, and at 2 and 4weeks midtreatment. Penalized logistic regression models based on combinations of MLD, clinical factors, and cytokine levels were developed. Cross-validated estimates of log-likelihood and area under the receiver operating characteristic curve (AUC) were used to assess accuracy., Results: In prognosticating grade 3 or greater RILT by MLD alone, cross-validated log-likelihood and AUC were -28.2 and 0.637, respectively. Incorporating clinical features and baseline cytokine levels increased log-likelihood to -27.6 and AUC to 0.669. Midtreatment cytokine data did not further increase log-likelihood or AUC. Of the 30 cytokines measured, higher levels of 13 decreased the effect of MLD on RILT, corresponding to a lower odds ratio for RILT per Gy MLD, while higher levels of 4 increased the association., Conclusions: Although the added prognostic benefit from cytokine data in our model was modest, understanding how clinical and biologic factors interact with the MLD-RILT relationship represents a novel framework for understanding and investigating the multiple factors contributing to radiation-induced toxicity., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Purpose and Objectives: We previously reported that the combination of mean lung dose (MLD) and inflammatory cytokines interleukin-8 (IL-8) and transforming growth factor-β1 (TGF-β1) may provide a more accurate model for radiation-induced lung toxicity (RILT) prediction in 58 patients with non-small cell lung cancer (NSCLC). This study is to validate the previous findings with new patients and to explore new models with more cytokines., Methods and Materials: One hundred forty-two patients with stage I-III NSCLC treated with definitive radiation therapy (RT) from prospective studies were included. Sixty-five new patients were used to validate previous findings, and all 142 patients were used to explore new models. Thirty inflammatory cytokines were measured in plasma samples before RT and 2 weeks and 4 weeks during RT (pre, 2w, 4w). Grade ≥2 RILT was defined as grade 2, and higher radiation pneumonitis or symptomatic pulmonary fibrosis was the primary endpoint. Logistic regression was performed to evaluate the risk factors of RILT. The area under the curve (AUC) for the receiver operating characteristic curves was used for model assessment., Results: Sixteen of 65 patients (24.6%) experienced RILT2. Lower pre IL-8 and higher TGF-β1 2w/pre ratio were associated with higher risk of RILT2. The AUC increased to 0.73 by combining MLD, pre IL-8, and TGF-β1 2w/pre ratio compared with 0.61 by MLD alone to predict RILT. In all 142 patients, 29 patients (20.4%) experienced grade ≥2 RILT. Among the 30 cytokines measured, only IL-8 and TGF-β1 were significantly associated with the risk of RILT2. MLD, pre IL-8 level, and TGF-β1 2w/pre ratio were included in the final predictive model. The AUC increased to 0.76 by combining MLD, pre IL-8, and TGF-β1 2w/pre ratio compared with 0.62 by MLD alone., Conclusions: We validated that a combination of mean lung dose, pre IL-8 level, and TGF-β1 2w/pre ratio provided a more accurate model to predict the risk of RILT2 compared with MLD alone., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Purpose Radiation therapy is a critical component in the care of patients with non-small-cell lung cancer (NSCLC), yet cardiac injury after treatment is a significant concern. Therefore, we wished to elucidate the incidence of cardiac events and their relationship to radiation dose to the heart. Patients and Materials Study eligibility criteria included patients with stage II to III NSCLC treated on one of four prospective radiation therapy trials at two centers from 2004 to 2013. All cardiac events were reviewed and graded per Common Terminology Criteria for Adverse Events (v4.03). The primary end point was the development of a grade ≥ 3 cardiac event. Results In all, 125 patients met eligibility criteria; median follow-up was 51 months for surviving patients. Median prescription dose was 70 Gy, 84% received concurrent chemotherapy, and 27% had pre-existing cardiac disease. Nineteen patients had a grade ≥ 3 cardiac event at a median of 11 months (interquartile range, 6 to 24 months), and 24-month cumulative incidence was 11% (95% CI, 5% to 16%). On multivariable analysis (MVA), pre-existing cardiac disease (hazard ratio [HR], 2.96; 95% CI, 1.07 to 8.21; P = .04) and mean heart dose (HR, 1.07/Gy; 95% CI, 1.02 to 1.13/Gy; P = .01) were significantly associated with grade ≥ 3 cardiac events. Analyzed as time-dependent variables on MVA analysis, both disease progression (HR, 2.15; 95% CI, 1.54 to 3.00) and grade ≥ 3 cardiac events (HR, 1.76; 95% CI, 1.04 to 2.99) were associated with decreased overall survival. However, disease progression (n = 71) was more common than grade ≥ 3 cardiac events (n = 19). Conclusion The 24-month cumulative incidence of grade ≥ 3 cardiac events exceeded 10% among patients with locally advanced NSCLC treated with definitive radiation. Pre-existing cardiac disease and higher mean heart dose were significantly associated with higher cardiac event rates. Caution should be used with cardiac dose to minimize risk of radiation-associated injury. However, cardiac risks should be balanced against tumor control, given the unfavorable prognosis associated with disease progression.

Background: In non-small-cell lung cancer radiotherapy, radiation pneumonitis≥grade 2 (RP2) depends on patients' dosimetric, clinical, biological and genomic characteristics., Methods: We developed a Bayesian network (BN) approach to explore its potential for interpreting biophysical signaling pathways influencing RP2 from a heterogeneous dataset including single nucleotide polymorphisms, micro RNAs, cytokines, clinical data, and radiation treatment plans before and during the course of radiotherapy. Model building utilized 79 patients (21 with RP2) with complete data, and model testing used 50 additional patients with incomplete data. A developed large-scale Markov blanket approach selected relevant predictors. Resampling by k-fold cross-validation determined the optimal BN structure. Area under the receiver-operating characteristics curve (AUC) measured performance., Results: Pre- and during-treatment BNs identified biophysical signaling pathways from the patients' relevant variables to RP2 risk. Internal cross-validation for the pre-BN yielded an AUC=0.82 which improved to 0.87 by incorporating during treatment changes. In the testing dataset, the pre- and during AUCs were 0.78 and 0.82, respectively., Conclusions: Our developed BN approach successfully handled a high number of heterogeneous variables in a small dataset, demonstrating potential for unraveling relevant biophysical features that could enhance prediction of RP2, although the current observations would require further independent validation., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Introduction: In 2014, the NRG Oncology Group initiated the first National Cancer Institute-sponsored, phase 1 clinical trial of stereotactic body radiation therapy (SBRT) for the treatment of multiple metastases in multiple organ sites (BR001; NCT02206334). The primary endpoint is to test the safety of SBRT for the treatment of 2 to 4 multiple lesions in several anatomic sites in a multi-institutional setting. Because of the technical challenges inherent to treating multiple lesions as their spatial separation decreases, we present the technical requirements for NRG-BR001 and the rationale for their selection., Methods and Materials: Patients with controlled primary tumors of breast, non-small cell lung, or prostate are eligible if they have 2 to 4 metastases distributed among 7 extracranial anatomic locations throughout the body. Prescription and organ-at-risk doses were determined by expert consensus. Credentialing requirements include (1) irradiation of the Imaging and Radiation Oncology Core phantom with SBRT, (2) submitting image guided radiation therapy case studies, and (3) planning the benchmark. Guidelines for navigating challenging planning cases including assessing composite dose are discussed., Results: Dosimetric planning to multiple lesions receiving differing doses (45-50 Gy) and fractionation (3-5) while irradiating the same organs at risk is discussed, particularly for metastases in close proximity (≤5 cm). The benchmark case was selected to demonstrate the planning tradeoffs required to satisfy protocol requirements for 2 nearby lesions. Examples of passing benchmark plans exhibited a large variability in plan conformity., Discussion: NRG-BR001 was developed using expert consensus on multiple issues from the dose fractionation regimen to the minimum image guided radiation therapy guidelines. Credentialing was tied to the task rather than the anatomic site to reduce its burden. Every effort was made to include a variety of delivery methods to reflect current SBRT technology. Although some simplifications were adopted, the successful completion of this trial will inform future designs of both national and institutional trials and would allow immediate clinical adoption of SBRT trials for oligometastases., Competing Interests: Notification: Ms. Winter reports grants from NCI Grant - subcontract to ACR, during the conduct of the study. Dr. Robinson reports grants and personal fees from Varian, personal fees from Radialogica, personal fees from ViewRay, grants from Elekta, personal fees from DFINE, outside the submitted work. Dr. Timmerman reports grants from Varian Medical systems, grants from Accuray, Inc., grants from Elekta Oncology, outside the submitted work., (Copyright © 2016 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.)

Purpose: This study aimed to compare lung dose-volume histogram (DVH) parameters such as mean lung dose (MLD) and the lung volume receiving ≥20 Gy (V20) of commonly used definitions of normal lung in terms of tumor/target subtraction and to determine to what extent they differ in predicting radiation pneumonitis (RP)., Methods and Materials: One hundred lung cancer patients treated with definitive radiation therapy were assessed. The gross tumor volume (GTV) and clinical planning target volume (PTVc) were defined by the treating physician and dosimetrist. For this study, the clinical target volume (CTV) was defined as GTV with 8-mm uniform expansion, and the PTV was defined as CTV with an 8-mm uniform expansion. Lung DVHs were generated with exclusion of targets: (1) GTV (DVHG); (2) CTV (DVHC); (3) PTV (DVHP); and (4) PTVc (DVHPc). The lung DVHs, V20s, and MLDs from each of the 4 methods were compared, as was their significance in predicting radiation pneumonitis of grade 2 or greater (RP2)., Results: There are significant differences in dosimetric parameters among the various definition methods (all Ps<.05). The mean and maximum differences in V20 are 4.4% and 12.6% (95% confidence interval 3.6%-5.1%), respectively. The mean and maximum differences in MLD are 3.3 Gy and 7.5 Gy (95% confidence interval, 1.7-4.8 Gy), respectively. MLDs of all methods are highly correlated with each other and significantly correlated with clinical RP2, although V20s are not. For RP2 prediction, on the receiver operating characteristic curve, MLD from DVHG (MLDG) has a greater area under curve of than MLD from DVHC (MLDC) or DVHP (MLDP). Limiting RP2 to 30%, the threshold is 22.4, 20.6, and 18.8 Gy, for MLDG, MLDC, and MLDP, respectively., Conclusions: The differences in MLD and V20 from various lung definitions are significant. MLD from the GTV exclusion method may be more accurate in predicting clinical significant radiation pneumonitis., (Published by Elsevier Inc.)

Purpose/objective(s): Volumetric modulated arc therapy (VMAT) allows for intensity-modulated radiation delivery during gantry rotation with dynamic MLC motion, variable dose rates and gantry speed modulation. We compared VMAT plans with 3D-CRT for hypofractionated lung radiotherapy., Materials/methods: Twenty-one 3D-CRT plans for Stage IA lung cancer previously treated stereotactically were selected. VMAT plans were generated by optimizing machine aperture shape and radiation intensity at 10 degrees intervals. A partial arc range of 180 degrees was manually selected to coincide with tumor location. The arc was resampled down to 5 degrees intervals to ensure dose calculation accuracy. Identical planning objectives were used for VMAT/3D-CRT. Parameters assessed included dose to PTV and organs-at-risk (OAR), monitor units, and multiple conformity and homogeneity indices. Plans were delivered to a phantom for time comparison., Results: Lung V(20/12.5/10/5) were less with VMAT (relative reduction 4.5%, p = .02; 3.2%, p = .01; 2.6%, p = .01; 4.2%, p = .03, respectively). Mean/maximum-doses to PTV, dose to additional OARs, 95% isodose line conformity, and target volume homogeneity were equivalent. VMAT improved conformity at both the 80% (1.87 vs. 1.93, p = .08) and 50% isodose lines (5.19 vs. 5.65, p = .01). Treatment times were reduced significantly with VMAT (mean 6.1 vs. 11.9 min, p < .01)., Conclusions: Single arc VMAT planning achieves highly conformal dose distributions while controlling dose to critical structures, including significant reduction in lung dose volume parameters. Employing a VMAT technique decreases treatment times by 37-63%, reducing the chance of error introduced by intrafraction variation. The quality and efficiency of VMAT is ideally suited for stereotactic lung radiotherapy delivery., (Copyright 2010 Elsevier Ireland Ltd. All rights reserved.)