Selective de-implementation of routine in vivo dosimetry.

As cone-beam computed tomography (CBCT) has become the localization method for a majority of cases, the indications for diode-based confirmation of accurate patient set-up and treatment are now limited and must be balanced between proper resource allocation and optimizing efficiency without compromising safety. We undertook a de-implementation quality improvement project to discontinue routine diode use in non-intensity modulated radiotherapy (IMRT) cases in favor of tailored selection of scenarios where diodes may be useful. After analysis of safety reports from the last 5 years, literature review, and stakeholder discussions, our safety and quality (SAQ) committee introduced a recommendation to limit diode use to specific scenarios in which in vivo verification may add value to standard quality assurance (QA) processes. To assess changes in patterns of use, we reviewed diode use by clinical indication 4 months prior and after the implementation of the revised policy, which includes use of diodes for: 3D conformal photon fields set up without CBCT; total body irradiation (TBI); electron beams; cardiac devices within 10 cm of the treatment field; and unique scenarios on a case-by-case basis. We identified 4459 prescriptions and 1038 unique instances of diode use across five clinical sites from 5/2021 to 1/2022. After implementation of the revised policy, we observed an overall decrease in diode use from 32% to 13.2%, with a precipitous drop in 3D cases utilizing CBCT (from 23.2% to 4%), while maintaining diode utilization in the 5 selected scenarios including 100% of TBI and electron cases. By identifying specific indications for diode use and creating a user-friendly platform for case selection, we have successfully de-implemented routine diode use in favor of a selective process that identifies cases where the diode is important for patient safety. In doing so, we have streamlined patient care and decreased cost without compromising patient safety.

Isolated progression of metastatic lung cancer: Clinical outcomes associated with definitive radiotherapy.

BACKGROUND: Progressive, metastatic non-small cell lung cancer (NSCLC) often requires the initiation of new systemic therapy. However, in patients with NSCLC that is oligoprogressive (≤3 lesions), local radiotherapy (RT) may allow for the eradication of resistant microclones and, therefore, the continuation of otherwise effective systemic therapy. METHODS: Patients treated from 2008 to 2019 with definitive doses of RT to all sites of intracranial or extracranial oligoprogression without a change in systemic therapy were identified. Radiographic progression-free survival (rPFS) and time to new therapy (TNT) were measured. Associations between baseline clinical and treatment-related variables were correlated with progression-free survival via Cox proportional hazards modeling. RESULTS: Among 198 unique patients, 253 oligoprogressive events were identified. Intracranial progression occurred in 51% of the patients, and extracranial progression occurred in 49%. In the entire cohort, the median rPFS was 7.9 months (95% CI, 6.5-10.0 months), and the median TNT was 8.8 months (95% CI, 7.2-10.9 months). On adjusted modeling, patients with the following disease characteristics were associated with better rPFS: better performance status (P = .003), fewer metastases (P = .03), longer time to oligoprogression (P = .009), and fewer previous systemic therapies (P = .02). Having multiple sites of oligoprogression was associated with worse rPFS (P < .001). CONCLUSIONS: In select patients with oligoprogression, definitive RT is a feasible treatment option to delay the initiation of next-line systemic therapies, which have more limited response rates and efficacy. Further randomized prospective data may help to validate these findings and identify which patients are most likely to benefit.

Hospitalization and definitive radiotherapy in lung cancer: incidence, risk factors and survival impact.

BACKGROUND: Unplanned hospitalization during cancer treatment is costly, can disrupt treatment, and affect patient quality of life. However, incidence and risks factors for hospitalization during lung cancer radiotherapy are not well characterized. METHODS: Patients treated with definitive intent radiation (≥45 Gy) for lung cancer between 2008 and 2018 at a tertiary academic institution were identified. In addition to patient, tumor, and treatment related characteristics, specific baseline frailty markers (Charlson comorbidity index, ECOG, patient reported weight loss, BMI, hemoglobin, creatinine, albumin) were recorded. All cancer-related hospitalizations during or within 30 days of completing radiation were identified. Associations between baseline variables and any hospitalization, number of hospitalizations, and overall survival were identified using multivariable linear regression and multivariable Cox proportional-hazards models, respectively. RESULTS: Of 270 patients included: median age was 66.6 years (31-88), 50.4% of patients were male (n = 136), 62% were Caucasian (n = 168). Cancer-related hospitalization incidence was 17% (n = 47), of which 21% of patients hospitalized (n = 10/47) had > 1 hospitalization. On multivariable analysis, each 1 g/dL baseline drop in albumin was associated with a 2.4 times higher risk of any hospitalization (95% confidence interval (CI) 1.2-5.0, P = 0.01), and baseline hemoglobin ≤10 was associated with, on average, 2.7 more hospitalizations than having pre-treatment hemoglobin > 10 (95% CI 1.3-5.4, P = 0.01). After controlling for baseline variables, cancer-related hospitalization was associated with 1.8 times increased risk of all-cause death (95% CI: 1.02-3.1, P = 0.04). CONCLUSIONS: Our data show baseline factors can predict those who may be at increased risk for hospitalization, which was independently associated with increased mortality. Taken together, these data support the need for developing further studies aimed at early and aggressive interventions to decrease hospitalizations during treatment.

Acute toxicity outcomes and dosimetric implications from incidental irradiation of adjacent tissues in tangent field hypofractionated breast radiotherapy.

PURPOSE: Adjacent tissues-in-beam (TIB) may receive substantial incidental doses within standard tangent fields during hypofractioned whole breast irradiation (HF-WBI). To characterize the impact of dose to TIB, we analyzed dosimetric parameters of TIB and associated acute toxicity. MATERIALS AND METHODS: Plans prescribed to 40.5 Gy/15 fractions from 4/2016-1/2018 were evaluated. Structures of interest were contoured: (1) TIB: all tissues encompassed by plan 30% isodose lines, (2) breast, (3) non-breast TIB (nTIB): TIB minus contoured breast. Volumes of TIB, breast, and nTIB receiving 100%-107% of prescription dose (V100-V107) were calculated. Twelve patient- and physician-reported acute toxicities were prospectively collected weekly. Correlations between volumetric and dosimetric parameters were assessed. Uni- and multivariable logistic regressions evaluated toxicity grade changes as a function of TIB, breast, and nTIB V100-V107 (in cm3). RESULTS: We evaluated 137 plans. Breast volume was positively correlated with nTIB and nTIB V100 (rho = 0.52, rho = 0.30, respectively, both p < 0.001). V107 > 2 cm3 were noted in 14% of breast and 21% of nTIB volumes. On multivariable analyses, increasing breast and nTIB V100 significantly raised odds of grade 2+ dermatitis and burning/twinging pain, respectively; increasing nTIB V105 elevated odds of hyperpigmentation and burning pain; and increasing nTIB V107 raised odds of burning pain. Threshold volumes for >6-fold odds of developing burning pain were TIB V105 > 100 cm3 and V107 > 5 cm3. CONCLUSIONS: For HF-WBI, doses to nTIB over the prescription predicted acute toxicities independent of breast doses. These data support inclusion of TIB as a region of interest in treatment planning and protocol design.

Comparison of treatment planning approaches for spatially fractionated irradiation of deep tumors.

PURPOSE: The purpose of this work was to compare the dosimetry and delivery times of 3D-conformal (3DCRT)-, volumetric modulated arc therapy (VMAT)-, and tomotherapy-based approaches for spatially fractionated radiation therapy for deep tumor targets. METHODS: Two virtual GRID phantoms were created consisting of 7 "target" cylinders (1-cm diameter) aligned longitudinally along the tumor in a honey-comb pattern, mimicking a conventional GRID block, with 2-cm center-to-center spacing (GRID2 cm ) and 3-cm center-to-center spacing (GRID3 cm ), all contained within a larger cylinder (8 and 10 cm in diameter for the GRID2 cm and GRID3 cm , respectively). In a single patient, a GRID3 cm structure was created within the gross tumor volume (GTV). Tomotherapy, VMAT (6 MV + 6 MV-flattening-filter-free) and multi-leaf collimator segment 3DCRT (6 MV) plans were created using commercially available software. Two tomotherapy plans were created with field widths (TOMO2.5 cm ) 2.5 cm and (TOMO5 cm ) 5 cm. Prescriptions for all plans were set to deliver a mean dose of 15 Gy to the GRID targets in one fraction. The mean dose to the GRID target and the heterogeneity of the dose distribution (peak-to-valley and peak-to-edge dose ratios) inside the GRID target were obtained. The volume of normal tissue receiving 7.5 Gy was determined. RESULTS: The peak-to-valley ratios for GRID2 cm /GRID3 cm /Patient were 2.1/2.3/2.8, 1.7/1.5/2.8, 1.7/1.9/2.4, and 1.8/2.0/2.8 for the 3DCRT, VMAT, TOMO5 cm , and TOMO2.5 cm plans, respectively. The peak-to-edge ratios for GRID2 cm /GRID3 cm /Patient were 2.8/3.2/5.4, 2.1/1.8/5.4, 2.0/2.2/3.9, 2.1/2.7/5.2 and for the 3DCRT, VMAT, TOMO5 cm , and TOMO2.5 cm plans, respectively. The volume of normal tissue receiving 7.5 Gy was lowest in the TOMO2.5 cm plan (GRID2 cm /GRID3 cm /Patient = 54 cm3 /19 cm3 /10 cm3 ). The VMAT plans had the lowest delivery times (GRID2 cm /GRID3 cm /Patient = 17 min/8 min/9 min). CONCLUSION: Our results present, for the first time, preliminary evidence comparing IMRT-GRID approaches which result in high-dose "islands" within a target, mimicking what is achieved with a conventional GRID block but without high-dose "tail" regions outside of the target. These approaches differ modestly in their ability to achieve high peak-to-edge ratios and also differ in delivery times.

Stereotactic Body Radiation Therapy for Isolated Local Recurrence After Surgical Resection of Pancreatic Ductal Adenocarcinoma Appears to be Safe and Effective.

BACKGROUND: A standardized treatment regimen for unresectable isolated local recurrence (ILR) of pancreatic ductal adenocarcinoma has not been established. This study evaluated the outcomes for patients with ILR who underwent stereotactic body radiation therapy (SBRT). METHODS: The records of patients with ILR who underwent SBRT between 2010 and 2016 were retrospectively reviewed. Symptom palliation and treatment-related toxicity were recorded. Associations between patient or treatment characteristics and overall survival (OS), progression-free survival (PFS), and local progression-free survival (LPFS) were assessed. RESULTS: The study identified 51 patients who received SBRT for ILR. Of the 51 patients, 26 (51%) had not received radiation therapy before SBRT. The median OS was 36 months after diagnosis. From the first day of SBRT, the median OS, PFS, and LPFS were respectively 16, 7, and 10 months. Patients with a recurrence-free interval of 9 months or longer after surgery had superior OS (P = 0.019). Maintenance chemotherapy after SBRT was associated with superior OS (P < 0.001) and LPFS (P = 0.027). In the multivariable analysis, poorly differentiated tumor grade [hazard ratio (HR) 11.274], positive surgical margins (HR 0.126), and reception of maintenance chemotherapy (HR 0.141) were independently associated with OS. Positive surgical margins (HR 0.255) and maintenance chemotherapy (HR 0.299) were associated with improved LPFS. Of 16 patients, 10 (63%) experienced abdominal pain relief after SBRT. Four patients (8%) experienced grade 3 gastrointestinal toxicity, and one patient experienced grade 4 gastrointestinal toxicity. CONCLUSIONS: Use of SBRT for ILR improved pain for a majority of the patients with acceptable acute and late toxicity. The findings show that SBRT is a feasible treatment for select patients with ILR. For those who receive SBRT, maintenance chemotherapy should be considered.

Data integrity systems for organ contours in radiation therapy planning.

The purpose of this research is to develop effective data integrity models for contoured anatomy in a radiotherapy workflow for both real-time and retrospective analysis. Within this study, two classes of contour integrity models were developed: data driven models and contiguousness models. The data driven models aim to highlight contours which deviate from a gross set of contours from similar disease sites and encompass the following regions of interest (ROI): bladder, femoral heads, spinal cord, and rectum. The contiguousness models, which individually analyze the geometry of contours to detect possible errors, are applied across many different ROI's and are divided into two metrics: Extent and Region Growing over volume. After analysis, we found that 70% of detected bladder contours were verified as suspicious. The spinal cord and rectum models verified that 73% and 80% of contours were suspicious respectively. The contiguousness models were the most accurate models and the Region Growing model was the most accurate submodel. 100% of the detected noncontiguous contours were verified as suspicious, but in the cases of spinal cord, femoral heads, bladder, and rectum, the Region Growing model detected additional two to five suspicious contours that the Extent model failed to detect. When conducting a blind review to detect false negatives, it was found that all the data driven models failed to detect all suspicious contours. The Region Growing contiguousness model produced zero false negatives in all regions of interest other than prostate. With regards to runtime, the contiguousness via extent model took an average of 0.2 s per contour. On the other hand, the region growing method had a longer runtime which was dependent on the number of voxels in the contour. Both contiguousness models have potential for real-time use in clinical radiotherapy while the data driven models are better suited for retrospective use.

Predictive Factors for Prophylactic Percutaneous Endoscopic Gastrostomy (PEG) Tube Placement and Use in Head and Neck Patients Following Intensity-Modulated Radiation Therapy (IMRT) Treatment: Concordance, Discrepancies, and the Role of Gabapentin.

The prophylactic placement of a percutaneous endoscopic gastrostomy (PEG) tube in the head and neck cancer (HNC) patient is controversial. We sought to identify factors associated with prophylactic PEG placement and actual PEG use. Since 2010, data regarding PEG placement and use were prospectively recorded in a departmental database from January 2010 to December 2012. HNC patients treated with intensity-modulated radiation therapy (IMRT) were retrospectively evaluated from 2010 to 2012. Variables potentially associated with patient post-radiation dysphagia from previous literature, and our experience was evaluated. We performed multivariate logistic regression on these variables with PEG placement and PEG use, respectively, to compare the difference of association between the two arms. We identified 192 HNC patients treated with IMRT. Prophylactic PEG placement occurred in 121 (63.0 %) patients, with PEG use in 97 (80.2 %) patients. PEG placement was associated with male gender (p < .01), N stage ≥ N2 (p < .05), pretreatment swallowing difficulties (p < .01), concurrent chemotherapy (p < .01), pretreatment KPS ≥80 (p = .01), and previous surgery (p = .02). Concurrent chemotherapy (p = .03) was positively associated with the use of PEG feeding by the patient, whereas pretreatment KPS ≥80 (p = .03) and prophylactic gabapentin use (p < .01) were negatively associated with PEG use. The analysis suggests there were discrepancies between prophylactic PEG tube placement and actual use. Favorable pretreatment KPS, no pretreatment dysphagia, no concurrent chemotherapy, and the use of gabapentin were significantly associated with reduced PEG use. This analysis may help refine the indications for prophylactic PEG placement.

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

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

Improving Quality Metrics in Radiation Oncology: Implementation of Pretreatment Peer Review for Stereotactic Body Radiation Therapy in Patients with Thoracic Cancer.

Purpose: Traditional peer reviews occur weekly, and can take place up to 1 week after the start of treatment. The American Society for Radiation Oncology peer-review white paper identified stereotactic body radiation therapy (SBRT) as a high priority for contour/plan review before the start of treatment, considering both the rapid-dose falloff and short treatment course. Yet, peer-review goals for SBRT must also balance physician time demands and the desire to avoid routine treatment delays that would occur in the setting of a 100% pretreatment (pre-Tx) review compliance requirement or prolonging the standard treatment planning timeline. Herein, we report on our pilot experience of a pre-Tx peer review of thoracic SBRT cases. Methods and Materials: From March 2020 to August 2021, patients undergoing thoracic SBRT were identified for pre-Tx review, and placed on a quality checklist. We implemented twice-weekly meetings for detailed pre-Tx review of organ-at-risk/target contours and dose constraints in the treatment planning system for SBRT cases. Our quality metric goal was to peer review ≥90% of SBRT cases before exceeding 25% of the dose delivered. We used a statistical process control chart with sigma limits (ie, standard deviations [SDs]) to access compliance rates with pre-Tx review implementation. Results: We identified 252 patients treated with SBRT to 294 lung nodules. When comparing pre-Tx review completion from initial rollout to full implementation, our rates improved from 19% to 79% (ie, from 1 sigma limit [SDs]) below to >2 sigma limits (SDs) above. Additionally, early completion of any form of contour/plan review (defined as any pre-Tx or standard review completed before exceeding 25% of the dose delivered) increased from 67% to 85% (March 2020-November 2020) to 76% to 94% (December 2020-August 2021). Conclusions: We successfully implemented a sustainable workflow for detailed pre-Tx contour/plan review for thoracic SBRT cases in the context of twice-weekly disease site-specific peer-review meetings. We reached our quality improvement objective to peer review ≥90% of SBRT cases before exceeding 25% of the dose delivered. This process was feasible to conduct in an integrated network of sites across our system.

Evaluation of the Clinical Utility of the Bone Metastases Ensemble Trees for Survival Decision Support Platform (BMETS-DSP): A Case-Based Pilot Assessment.

PURPOSE: The Bone Metastases Ensemble Trees for Survival Decision Support Platform (BMETS-DSP) provides patient-specific survival predictions and evidence-based recommendations to guide multidisciplinary management for symptomatic bone metastases. We assessed the clinical utility of the BMETS-DSP through a pilot prepost design in a simulated clinical environment. METHODS: Ten Radiation Oncology physicians reviewed 55 patient cases at two time points: without and then with the use of BMETS-DSP. Assessment included 12-month survival estimate, confidence in and likelihood of sharing estimates with patients, and recommendations for open surgery, systemic therapy, hospice referral, and radiotherapy (RT) regimen. Paired statistics compared pre- versus post-DSP outcomes. Reported statistical significance is P < .05. RESULTS: Pre- versus post-DSP, overestimation of true minus estimated survival time was significantly reduced (mean difference -2.1 [standard deviation 4.1] v -1 month [standard deviation 3.5]). Prediction accuracy was significantly improved at cut points of < 3 (72 v 79%), ≤ 6 (64 v 71%), and ≥ 12 months (70 v 81%). Median ratings of confidence in and likelihood of sharing prognosis significantly increased. Significantly greater concordance was seen in matching use of 1-fraction RT with the true survival < 3 months (70 v 76%) and < 10-fraction RT with the true survival < 12 months (55 v 62%) and appropriate use of open surgery (47% v 53%), without significant changes in selection of hospice referral or systemic therapy. CONCLUSION: This pilot study demonstrates that BMETS-DSP significantly improved physician survival estimation accuracy, prognostic confidence, likelihood of sharing prognosis, and use of prognosis-appropriate RT regimens in the care of symptomatic bone metastases, supporting future multi-institutional validation of the platform.

Longitudinal Trends of Financial Toxicity in Patients With Lung Cancer: A Prospective Cohort Study.

BACKGROUND: Cancer therapy is associated with severe financial burden. However, the magnitude and longitudinal patient relationship with financial toxicity (FT) in the initial course of therapy is unclear. METHODS: Patients with stage II-IV lung cancer were recruited in a prospective longitudinal study between July 2018 and March 2020. FT was measured via the validated COmprehensive Score for financial Toxicity (COST) at the time of cancer diagnosis and at 6-month follow-up (6MFU). 6MFU data were compared with corresponding baseline data. A lower COST score indicates increased financial hardship. RESULTS: At the time of analysis, 215 agreed to participate. Subsequently, 112 patients completed 6MFU. On average, slightly more FT was observed at diagnosis compared with 6MFU (median COSTbase 25 v COST6M 27; P < .001); however, individual patients experienced large changes in FT. At 6MFU, 27.7% of patients had made financial sacrifices to pay for treatment but only 4.5% refused medical care based on cost. Median reported out-of-pocket (OOP) costs for the initial 6 months of cancer treatment was $2,496 (range, $0-25,900). Risk factors for FT at diagnosis were unique from risk factors at 6MFU. Actual OOP expenses were not correlated with FT; however, inability to predict upcoming treatment expenses resulted in higher FT at 6MFU. DISCUSSION: FT is a pervasive challenge during the initiation of lung cancer treatment. Few patients are willing to sacrifice medical care regardless of the cost. Risk factors for FT evolve, resulting in unique interventional targets throughout therapy.

Improving Early Identification of Significant Weight Loss Using Clinical Decision Support System in Lung Cancer Radiation Therapy.

PURPOSE: Early identification of patients who may be at high risk of significant weight loss (SWL) is important for timely clinical intervention in lung cancer radiotherapy (RT). A clinical decision support system (CDSS) for SWL prediction was implemented within the routine clinical workflow and assessed on a prospective cohort of patients. MATERIALS AND METHODS: CDSS incorporated a machine learning prediction model on the basis of radiomics and dosiomics image features and was connected to a web-based dashboard for streamlined patient enrollment, feature extraction, SWL prediction, and physicians' evaluation processes. Patients with lung cancer (N = 37) treated with definitive RT without prior RT were prospectively enrolled in the study. Radiomics and dosiomics features were extracted from CT and 3D dose volume, and SWL probability (≥ 0.5 considered as SWL) was predicted. Two physicians predicted whether the patient would have SWL before and after reviewing the CDSS prediction. The physician's prediction performance without and with CDSS and prediction changes before and after using CDSS were compared. RESULTS: CDSS showed significantly better prediction accuracy than physicians (0.73 v 0.54) with higher specificity (0.81 v 0.50) but with lower sensitivity (0.55 v 0.64). Physicians changed their original prediction after reviewing CDSS prediction for four cases (three correctly and one incorrectly), for all of which CDSS prediction was correct. Physicians' prediction was improved with CDSS in accuracy (0.54-0.59), sensitivity (0.64-0.73), specificity (0.50-0.54), positive predictive value (0.35-0.40), and negative predictive value (0.76-0.82). CONCLUSION: Machine learning-based CDSS showed the potential to improve SWL prediction in lung cancer RT. More investigation on a larger patient cohort is needed to properly interpret CDSS prediction performance and its benefit in clinical decision making.

A method for optimizing LINAC treatment geometry for volumetric modulated arc therapy of multiple brain metastases.

PURPOSE: Volumetric modulated arc therapy (VMAT) is a rotational delivery technique in which MLC shapes, dose rate, and gantry rotation speed are optimized to produce conformal dose distributions. The aim of this work is to develop a beam projection method for deriving the optimal table and collimator angles for multilesion treatment planning. METHODS: The method consists of four steps. The first step is to define the vector of beam-eye-view (BEV)-Y-axis in the treatment planning CT coordinates. The second step is to project each target onto the BEV-Y-axis vector. In the third step, the best table and collimator angle are found with a brute-force optimization technique that minimizes MLC leaf sharing between lesions. The fourth step is to generate an optimized VMAT plan with appropriate table/collimator angles and evaluate the plan quality. RESULTS: The authors tested the method on three example cases with targets of various locations in the brain and sizes ranging from 1.18 to 17.86 cm(3). Applying the optimized geometric parameter to generate VMAT plan, a reduction of the 12 Gy volume was more than 6.1% for all cases; the plan homogeneity (D2%-D95%) was improved from 5.88 +/- 1.21 to 5.21 +/- 0.93 Gy vs a VMAT plan with the manufacturer recommended table and collimator angles. CONCLUSIONS: The authors conclude that the use of the projection method minimizes the sharing of MLC leaves between lesions and improves the plan quality for multilesion VMAT delivery.

Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy.

We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation therapy (IMRT) was measured between one month prior to and one week after the start of IMRT. Weight change between one week and two months after the commencement of IMRT was analyzed, and dichotomized at 5% WL. Each patient had a planning CT and contours of gross tumor volume (GTV) and esophagus (ESO). A total of 355 features including clinical parameter (CP), GTV and ESO (GTV&ESO) dose-volume histogram (DVH), GTV radiomics, and GTV&ESO dosiomics features were extracted. R&D features were categorized as first- (L1), second- (L2), higher-order (L3) statistics, and three combined groups, L1 + L2, L2 + L3 and L1 + L2 + L3. Multi-view texture analysis was performed to identify optimal R&D input features. In the training set (194 earlier patients), feature selection was performed using Boruta algorithm followed by collinearity removal based on variance inflation factor. Machine-learning models were developed using Laplacian kernel support vector machine (lpSVM), deep neural network (DNN) and their averaged ensemble classifiers. Prediction performance was tested on an independent test set (194 more recent patients), and compared among seven different input conditions: CP-only, DVH-only, R&D-only, DVH + CP, R&D + CP, R&D + DVH and R&D + DVH + CP. Combined GTV L1 + L2 + L3 radiomics and GTV&ESO L3 dosiomics were identified as optimal input features, which achieved the best performance with an ensemble classifier (AUC = 0.710), having statistically significantly higher predictability compared with DVH and/or CP features (p < 0.05). When this performance was compared to that with full R&D-only features which reflect traditional single-view data, there was a statistically significant difference (p < 0.05). Using optimized multi-view R&D input features is beneficial for predicting early WL in lung cancer radiotherapy, leading to improved performance compared to using conventional DVH and/or CP features.

Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

PURPOSE: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic covariates. To establish its relative clinical utility, we compared BMETS with 2 simpler Cox regression models used in this setting. METHODS AND MATERIALS: For 492 bone sites in 397 patients evaluated for palliative radiation therapy (RT) for SBM from January 2007 to January 2013, data for 27 clinical variables were collected. These covariates and the primary outcome of time from consultation to death were used to build BMETS using random survival forests. We then performed Cox regressions as per 2 validated models: Chow's 3-item (C-3) and Westhoff's 2-item (W-2) tools. Model performance was assessed using cross-validation procedures and measured by time-dependent area under the curve (tAUC) for all 3 models. For temporal validation, a separate data set comprised of 104 bone sites treated in 85 patients in 2018 was used to estimate tAUC from BMETS. RESULTS: Median survival was 6.4 months. Variable importance was greatest for performance status, blood cell counts, recent systemic therapy type, and receipt of concurrent nonbone palliative RT. tAUC at 3, 6, and 12 months was 0.83, 0.81, and 0.81, respectively, suggesting excellent discrimination of BMETS across postconsultation time points. BMETS outperformed simpler models at each time, with respective tAUC at each time of 0.78, 0.76, and 0.74 for the C-3 model and 0.80, 0.78, and 0.77 for the W-2 model. For the temporal validation set, respective tAUC was similarly high at 0.86, 0.82, and 0.78. CONCLUSIONS: For patients with SBM, BMETS improved survival predictions versus simpler traditional models. Model performance was maintained when applied to a temporal validation set. To facilitate clinical use, we developed a web platform for data entry and display of BMETS-predicted survival probabilities.

Frequency of Complicated Symptomatic Bone Metastasis Over a Breadth of Operational Definitions.

PURPOSE: Numerous randomized trials have demonstrated noninferiority of single- versus multiple-fraction palliative radiation therapy (RT) in the management of uncomplicated bone metastases; yet there is neither a clear definition of what constitutes a complicated lesion, nor substantial data regarding the prevalence of such complicating features in clinical practice. Thus, we identify a range of evidence-based operational definitions of complicated symptomatic bone metastases and characterize the frequency of such complicating features at a high-volume, tertiary care center. METHODS AND MATERIALS: A retrospective review of patients seen in consultation for symptomatic bone metastases between March 1, 2007, and July 31, 2013, at Johns Hopkins Hospital identified patient and disease characteristics. Descriptive statistics characterized the frequency of the following complicating features: prior RT, prior surgery, neuraxis compromise, pathologic fracture, and soft tissue component at the symptomatic site. A range of definitions for complicated bone metastases was evaluated based on combinations of these features. Uni- and multivariable logistic regressions evaluated the odds of complicated bone metastases as a function of site of primary cancer and of the symptomatic target lesion. RESULTS: A total of 686 symptomatic bone metastases in 401 patients were evaluated. Percent of target sites complicated by prior RT was 4.4%, prior surgery was 8.9%, pathologic fracture was 20.6%, neuraxis compromise was 52.0% among spine and medial pelvis sites, and soft tissue component was 38.6%. More than 96 possible definitions of complicated bone metastases were identified. The presence of such complicated lesions ranged from 2.3% to 67.3%, depending on the operational definition used. Odds of a complicated lesion were significantly higher for spine sites and select nonbreast histologies. CONCLUSIONS: In this retrospective study, we found complicated symptomatic bone metastases may be present in up to two-thirds of patients. Literature review also demonstrates no clear standard definition of complicated bone metastases, potentially explaining underutilization of single-fraction palliative RT in this setting.

Low-Dose Image-Guided Pediatric CNS Radiation Therapy: Final Analysis From a Prospective Low-Dose Cone-Beam CT Protocol From a Multinational Pediatrics Consortium.

BACKGROUND: Lower-dose cone-beam computed tomography protocols for image-guided radiotherapy may permit target localization while minimizing radiation exposure. We prospectively evaluated a lower-dose cone-beam protocol for central nervous system image-guided radiotherapy across a multinational pediatrics consortium. METHODS: Seven institutions prospectively employed a lower-dose cone-beam computed tomography central nervous system protocol (weighted average dose 0.7 mGy) for patients ≤21 years. Treatment table shifts between setup with surface lasers versus cone-beam computed tomography were used to approximate setup accuracy, and vector magnitudes for these shifts were calculated. Setup group mean, interpatient, interinstitution, and random error were estimated, and clinical factors were compared by mixed linear modeling. RESULTS: Among 96 patients, with 2179 pretreatment cone-beam computed tomography acquisitions, median age was 9 years (1-20). Setup parameters were 3.13, 3.02, 1.64, and 1.48 mm for vector magnitude group mean, interpatient, interinstitution, and random error, respectively. On multivariable analysis, there were no significant differences in mean vector magnitude by age, gender, performance status, target location, extent of resection, chemotherapy, or steroid or anesthesia use. Providers rated >99% of images as adequate or better for target localization. CONCLUSIONS: A lower-dose cone-beam computed tomography protocol demonstrated table shift vector magnitude that approximate clinical target volume/planning target volume expansions used in central nervous system radiotherapy. There were no significant clinical predictors of setup accuracy identified, supporting use of this lower-dose cone-beam computed tomography protocol across a diverse pediatric population with brain tumors.

Development and Validation of a Clinical Prognostic Stage Group System for Nonmetastatic Prostate Cancer Using Disease-Specific Mortality Results From the International Staging Collaboration for Cancer of the Prostate.

Importance: In 2016, the American Joint Committee on Cancer (AJCC) established criteria to evaluate prediction models for staging. No localized prostate cancer models were endorsed by the Precision Medicine Core committee, and 8th edition staging was based on expert consensus. Objective: To develop and validate a pretreatment clinical prognostic stage group system for nonmetastatic prostate cancer. Design, Setting, and Participants: This multinational cohort study included 7 centers from the United States, Canada, and Europe, the Shared Equal Access Regional Cancer Hospital (SEARCH) Veterans Affairs Medical Centers collaborative (5 centers), and the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) registry (43 centers) (the STAR-CAP cohort). Patients with cT1-4N0-1M0 prostate adenocarcinoma treated from January 1, 1992, to December 31, 2013 (follow-up completed December 31, 2017). The STAR-CAP cohort was randomly divided into training and validation data sets; statisticians were blinded to the validation data until the model was locked. A Surveillance, Epidemiology, and End Results (SEER) cohort was used as a second validation set. Analysis was performed from January 1, 2018, to November 30, 2019. Exposures: Curative intent radical prostatectomy (RP) or radiotherapy with or without androgen deprivation therapy. Main Outcomes and Measures: Prostate cancer-specific mortality (PCSM). Based on a competing-risk regression model, a points-based Score staging system was developed. Model discrimination (C index), calibration, and overall performance were assessed in the validation cohorts. Results: Of 19 684 patients included in the analysis (median age, 64.0 [interquartile range (IQR), 59.0-70.0] years), 12 421 were treated with RP and 7263 with radiotherapy. Median follow-up was 71.8 (IQR, 34.3-124.3) months; 4078 (20.7%) were followed up for at least 10 years. Age, T category, N category, Gleason grade, pretreatment serum prostate-specific antigen level, and the percentage of positive core biopsy results among biopsies performed were included as variables. In the validation set, predicted 10-year PCSM for the 9 Score groups ranged from 0.3% to 40.0%. The 10-year C index (0.796; 95% CI, 0.760-0.828) exceeded that of the AJCC 8th edition (0.757; 95% CI, 0.719-0.792), which was improved across age, race, and treatment modality and within the SEER validation cohort. The Score system performed similarly to individualized random survival forest and interaction models and outperformed National Comprehensive Cancer Network (NCCN) and Cancer of the Prostate Risk Assessment (CAPRA) risk grouping 3- and 4-tier classification systems (10-year C index for NCCN 3-tier, 0.729; for NCCN 4-tier, 0.746; for Score, 0.794) as well as CAPRA (10-year C index for CAPRA, 0.760; for Score, 0.782). Conclusions and Relevance: Using a large, diverse international cohort treated with standard curative treatment options, a proposed AJCC-compliant clinical prognostic stage group system for prostate cancer has been developed. This system may allow consistency of reporting and interpretation of results and clinical trial design.

Radiation treatment planning with embedded dose escalation.

BACKGROUND: Heterogeneous target doses are a common by-product from attempts to improve normal tissue sparing in radiosurgery treatment planning. These regions of escalated dose within the target may increase tumor control probability (TCP). Purposely embedding hot spots within tumors during optimization may also increase the TCP. This study discusses and compares five optimization approaches that not only eliminate homogeneity constraints, but also maximize heterogeneity and internal dose escalation. METHODS: Co-planar volumetric modulated arc therapy (VMAT) plans were produced for virtual spherical targets with 2-8 cm diameters, minimum target dose objectives of 25 Gy, and objectives to minimize normal tissue dose. Five other sets of plans were produced with additional target dose objectives: 1) minimum dose-volume histogram (DVH) objective on 10% of the target 2) minimum dose objective on a sub-structure within the target, and 3-5) minimum generalized equivalent uniform dose (gEUD) objectives assuming three different volume-effect parameters. Plans were normalized to provide equivalent maximum OAR dose and were compared in terms of target D0.1 cc, ratio of V12.5 Gy to PTV volume (R50%), monitor units per 5 Gy fraction (MU), and mean multi-leaf collimator (MLC) segment size. All planning approaches were also applied to a clinical patient dataset and compared. RESULTS: Mean ± standard deviation metrics achievable using the baseline and experimental approaches 1-5) included D0.1 cc: 27.7 ± 0.8, 64.6 ± 10.5, 56.5 ± 10.3, 48.9 ± 5.7, 44.8 ± 5.0, and 37.4 ± 4.5 Gy. R50%: 4.64 ± 3.27, 5.15 ± 2.32, 4.83 ± 2.64, 4.42 ± 1.83, 4.45 ± 1.88, and 4.21 ± 1.75. MU: 795 ± 27, 1988 ± 222, 1766 ± 259, 1612 ± 112, 1524 ± 90, and 1362 ± 146. MLC segment size: 4.7 ± 1.6, 2.3 ± 0.7, 2.6 ± 0.8, 2.7 ± 0.7, 2.7 ± 0.8, and 2.8 ± 0.8 cm. CONCLUSIONS: The DVH-based approach provided the highest embedded doses for all target diameters and patient example with modest increases in R50%, achieved by decreasing MLC segment size while increasing MU. These results suggest that embedding doses > 220% of tumor margin dose is feasible, potentially improving TCP for solid tumors.