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 Cancer Care by Incorporating the Patient's Voice in Symptom Management (IMPROVE): A Multicenter-Prospective Pilot Study

PURPOSE/OBJECTIVE(S)

IMPROVE is a prospective multicenter pilot study. It evaluates whether routine physician review of patient-reported outcomes measures (PROMs) during radiotherapy alters physicians' perception of cancer patients' treatment-related toxicity and influences symptom management.

MATERIALS/METHODS

We are enrolling patients with thoracic or gastrointestinal cancers amenable to conventional-fractionated radiotherapy. Patients may receive concurrent chemotherapy. Patients report (1) symptoms, using PRO-CTCAE measures, (2) the most burdensome symptom, and (3) how symptoms interfere with daily activities. Patients complete the measures before seeing their physician during each on-treatment visit. During weekly visits and before reviewing the patient's PROMs, physicians rate the symptom burden for each patient from 0 to 10, using available clinical data. These data include vital signs, lab work, physical exams, nursing assessments, and physicians' clinical judgment. After reviewing the patients' PROMs, physicians re-rate each patient's symptom burden and report any changes in recommended interventions. Changes could include (1) additional counseling, (2) new medications or interventions, (3) referrals to other services, or (4) further testing or evaluation. After each patient's course of radiotherapy, providers complete a Clinician Feedback Form about the impact of PROM review on symptom perception and management during treatment. This study commenced November 11, 2020 at a multi-site tertiary academic cancer center (using electronic or paper questionnaires) and July 21, 2021 at a multi-site community cancer center (using paper forms).

RESULTS

To be determined.

CONCLUSION

To be determined.

Sexual Function and Dosimetric Relationships to Erectile Structures among Patients Treated Definitively with Pd-103 LDR Prostate Brachytherapy

PURPOSE/OBJECTIVE(S)

Sexual potency and erectile function are important quality of life metrics for many men and is a significant consideration when planning and treating prostate cancer. There are limited long-term data correlating post-implant dosimetry with patient-reported sexual toxicity outcomes following LDR prostate brachytherapy using Pd-103, specifically as it pertains to genital substructures. Our aim was to correlate dosimetric patterns with quality-of-life outcomes to determine if dose to the pudendal arteries and neurovascular bundles is a significant consideration when planning prostate LDR brachytherapy.

MATERIALS/METHODS

We analyzed a prospectively collected IRB-approved database of men receiving LDR prostate brachytherapy between 11/2014-04/2019 at our institution. Patients received either LDR brachytherapy only, or combined with intensity-modulated radiation therapy (IMRT) to the prostate with or without pelvic lymph node coverage. Patients were given quality of life questionnaires at consultation and at subsequent follow up visits. Outcomes data related to sexual toxicity were evaluated based on the Sexual Health Inventory (SHIM) Questionnaire. The right/left pudendal arteries, and right/left neurovascular bundles (NVB) were contoured retrospectively on CT-MRI fusion sequences. Dosimetric data for each of the erectile substructures was analyzed. Statistical analyses included generalized linear mixed effects models with random intercept for patient to explore the association between dose and SHIM confidence.

RESULTS

A total of 50 patients met criteria for inclusion in the analysis. 5 patients received combined IMRT to 45 Gy with Pd-103 (90-100 Gy) and 45 patients received Pd-103 monotherapy (125 Gy). Median follow-up was 18 months for 50 patients; 40 (80%) patients had follow-up greater than 2 years, and 15 (30%) greater than 5 years. There were 344 individual questionnaires completed. 28% of records reported low or very low confidence level (Question #1 of SHIM questionnaire). Likelihood of moderate-very high confidence increased up to 2 years after beginning of treatment (p = 0.052) and then subsequently decreased between 2- and 5 years post treatment (p = 0.042). NVB doses were not associated with SHIM confidence level. D100 greater than 150 cGy to either pudendal artery was associated with worse SHIM confidence score after treatment (p = 0.003).

CONCLUSION

Sexual function is variable in the post treatment setting following definitive prostate radiation with Pd-103 LDR-brachytherapy. Avoiding pudendal artery dose may improve sexual outcomes and should be considered when planning prostate brachytherapy. Further investigation with a larger prospective, cohort may be warranted.

Operational Ontology for Radiation Oncology (OORO): A Professional Society-Based, Multi-Stakeholder Consensus Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data

PURPOSE/OBJECTIVE(S)

There is a critical need for large-scale, multi-institutional "real-world" data to evaluate patient, diagnosis and treatment factors affecting oncology patient outcomes. However, lack of data standardization undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), Radiation Oncology Information Systems and other cancer care databases. As next step to promote data standardization beyond the American Association of Physicists in Medicine (AAPM)'s TG-263 guidance for radiotherapy (RT) nomenclature, the AAPM's Big Data Subcommittee (BDSC) has led an international RT professional society collaboration to develop the Operational Ontology for Radiation Oncology (OORO).

MATERIALS/METHODS

Initiated July 2019 to explore issues that typically compromise formation of large inter- and intra- institutional databases from EHRs, the AAPM's BDSC membership includes representatives from the AAPM, American Society of Radiation Oncology (ASTRO), Canadian Organization of Medical Physicists (COMP), Canadian Association of Radiation Oncology (CARO), European Society of Therapeutic Radiation Oncology (ESTRO) and clinical trials experts from NRG Oncology. Multiple external stakeholders were engaged, including government agencies, vendors and RT community members through the iterative and consensus-driven approach to OORO development.

RESULTS

The OORO includes 42 key elements, 359 attributes, 144 value sets, and 155 relationships, ranked for priority of implementation based on clinical significance, likelihood of availability in EHRs, or ability to modify routine clinical processes to permit aggregation. The initial version of OORO includes many disease-site independent concepts common for all cancer patients and a smaller set specific for prostate cancer. The OORO development methodology is currently being applied/adapted to include additional disease site-specific concepts beginning with head and neck cancers.

CONCLUSION

The first of its kind in radiation oncology, the OORO is a professional society-based, multi-stakeholder, consensus driven informatics standard. The iterative and collaborative approach to ontology development and refinement aims to ensure that OORO serves as a « living » guidance document, facilitating incremental expansion of data elements over time, as disease site-specific standards are set and RT concepts evolve. Supporting construction of comprehensive "real-world" datasets and application of advanced analytic techniques, including artificial intelligence (AI), OORO holds the potential to revolutionize patient management and improve outcomes.

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.

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.

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.

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.

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.

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 COST_base 25 v COST_6M 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.

Financial toxicity in lung cancer: an assessment of magnitude, perception, and impact on quality of life

BACKGROUND

Advances in lung cancer therapy have resulted in improved clinical outcomes. Unfortunately, advances can come at a financial cost to patients and their families that poses a significant risk to overall quality of life (QoL). Financial distress has been shown to be associated with increased symptom burden and decreased treatment compliance but the magnitude of financial distress is not well characterized in lung cancer populations.

PATIENTS AND METHODS

Patients with stage II-IV newly diagnosed lung cancer and starting first-line therapy were recruited at a tertiary academic institution between July 2018 and April 2019. The comprehensive score for financial toxicity (COST) was used to assess financial toxicity and the Functional Assessment of Cancer Therapy-Lung (FACT-L) was used to assess QoL. Associations between financial toxicity and baseline variables were assessed using multivariable linear regression and correlations were assessed using the Pearson correlation.

RESULTS

In this study, 143 consecutive patients were approached and 91.6% agreed to participate (N = 131). The median age was 65 years (35-90); 52.7% were male (n = 69), and 75.6% were white (n = 99). The inability to afford basic necessities and having <1 month of savings was associated with increased financial toxicity (P < 0.001) after adjusting for other factors such as age, race, insurance, and income. There was also a trend toward increased financial toxicity among those who were employed but on sick leave (P = 0.06). Increased financial toxicity was correlated with a decrease in QoL (correlation coefficient 0.41, P < 0.001). Patients' anticipated out-of-pocket (OOP) expenses for the upcoming 6 months ranged from $0 to $50 000 (median $2150). However, there was no correlation between anticipated OOP expenses and either financial toxicity or QoL.

CONCLUSIONS

These data identify key factors for identifying at-risk patients and builds a framework for exploring the benefit of financial counseling interventions, which may improve QoL and oncologic outcomes.

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.

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.

The evolution of financial toxicity in patients with lung cancer

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Background: Financial toxicity (FT), or the cost-related side effect of cancer therapy, has been linked to poor clinical outcomes, greater symptom burden, and worse quality of life. While the repercussions of FT have been thoroughly explored, the longitudinal patient relationship with FT in the initial course of therapy is unknown. Methods: Patients with stage II – IV lung cancer were recruited in a prospective longitudinal non-interventional study between July 2018 and January 2020. FT was measured via the COST score, a validated questionnaire for benchmarking FT, at a) the time of cancer diagnosis and then later at b) 6-month follow up (6MFU). In this model, a lower COST score indicates increased financial hardship. Completed 6MFU data was compared to corresponding baseline data for each patient. Linear regression analysis was used to compare patient characteristics with baseline COST (COSTbase) and 6-month COST (COST6M) scores. Results: At the time of analysis, 209 patients were screened and 194 (95.1%) patients agreed to participate and complete the baseline survey. Subsequently, 93 patients completed the 6MFU survey, 32 patients had died, and 7 patients were lost to follow up. The remaining 62 patients have not met the study end point to date. Of the 93 patients that completed the 6MFU and baseline survey, the median age was 65 (range 35-89), 50.5% were male, and 76.3% were Caucasian. Over the first six months of therapy 36.5% overestimated OOP expenses by > $1000 and 22.5% reported a decrease in total monetary savings, but only 4.3% of patients made decisions about health care based on cost of care. FT was present at both time points but was worse at diagnosis than at 6MFU (median COSTbase 25 [range 1-44] vs. median COST6M 27 [range 0-44]; p = 0.04). Linear regression correlated risk factors with FT at baseline ( < 1 month monetary savings, employed but on sick leave, and inability to afford basic necessities; all p < 0.001) that were different from risk factors at 6MFU (paying much more than expected OOP and sacrificing spending to meet medical costs; p < 0.001). There was no significant difference between estimated OOP costs at baseline (median $2550 [range $0 - $500,000]) and actual OOP costs (median $2496 [range $0 – 25,900]; p = 0.25). Conclusions: FT toxicity is pervasive at both diagnosis and at 6-month follow up, however, the magnitude of toxicity changes with time. Few patients are willing to sacrifice medical care regardless of the cost. Risk factors for FT evolve, suggesting that different groups may benefit from financial intervention at diagnosis versus 6MFU.

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.

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.

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.

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.

Predicting acute radiation induced xerostomia in head and neck Cancer using MR and CT Radiomics of parotid and submandibular glands

Purpose

To analyze baseline CT/MR-based image features of salivary glands to predict radiation-induced xerostomia 3-months after head-and-neck cancer (HNC) radiotherapy.

Methods

A retrospective analysis was performed on 266 HNC patients who were treated using radiotherapy at our institution between 2009 and 2018. CT and T1 post-contrast MR images along with NCI-CTCAE xerostomia grade (3-month follow-up) were prospectively collected at our institution. CT and MR images were registered on which parotid/submandibular glands were contoured. Image features were extracted for ipsilateral/contralateral parotid and submandibular glands relative to the location of the primary tumor. Dose-volume-histogram (DVH) parameters were also acquired. Features were pre-selected based on Spearman correlation before modelling by examining the correlation with xerostomia (p < 0.05). A shrinkage regression analysis of the pre-selected features was performed using LASSO. The internal validity of the variable selection was estimated by repeating the entire variable selection procedure using a leave-one-out-cross-validation. The most frequently selected variables were considered in the final model. A generalized linear regression with repeated ten-fold cross-validation was developed to predict radiation-induced xerostomia at 3-months after radiotherapy. This model was tested in an independent dataset (n = 50) of patients who were treated at the same institution in 2017–2018. We compared the prediction performances under eight conditions (DVH-only, CT-only, MR-only, CT + MR, DVH + CT, DVH + CT + MR, Clinical+CT + MR, and Clinical+DVH + CT + MR) using the area under the receiver operating characteristic curve (ROC-AUC).

Results

Among extracted features, 7 CT, 5 MR, and 2 DVH features were selected. The internal cohort (n = 216) ROC-AUC values for DVH, CT, MR, and Clinical+DVH + CT + MR features were 0.73 ± 0.01, 0.69 ± 0.01, 0.70 ± 0.01, and 0.79 ± 0.01, respectively. The validation cohort (n = 50) ROC-AUC values for DVH, CT, MR, and Clinical+DVH + CT + MR features were 0.63, 0.57, 0.66, and 0.68, respectively. The DVH-ROC was not significantly different than the CT-ROC (p = 0.8) or MR-ROC (p = 0.4). However, the CT + MR-ROC was significantly different than the CT-ROC (p = 0.03), but not the Clinical+DVH + CT + MR model (p = 0.5).

Conclusion

Our results suggest that baseline CT and MR image features may reflect baseline salivary gland function and potential risk for radiation injury. The integration of baseline image features into prediction models has the potential to improve xerostomia risk stratification with the ultimate goal of truly personalized HNC radiotherapy.

Electronic supplementary material

The online version of this article (10.1186/s13014-019-1339-4) contains supplementary material, which is available to authorized users.

Applying Non-Homogeneous Dose Optimization to Improve Conventionally Fractionated Radiation Plan Quality in Patients with Non-Small Cell Lung Cancer

PURPOSE

Nonhomogeneous dose optimization (NHDO) is exploited in stereotactic body radiation therapy (SBRT) to increase dose delivery to the tumor and allow rapid dose falloff to surrounding normal tissues. We investigate changes in plan quality when NHDO is applied to inverse-planned conventionally fractionated radiation therapy (CF-RT) plans in patients with non-small cell lung cancer.

METHODS AND MATERIALS

Patients with near-central non-small cell lung cancer treated with CF-RT in 2018 at a single institution were identified. CF-RT plans were replanned using NHDO techniques, including normalizing to a lower isodose line, while maintaining clinically acceptable normal tissue constraints and target coverage. Tumor control probabilities were calculated. We compared delivered CF-RT plans using homogenous dose optimization (HDO) versus NHDO using Wilcoxon signed-rank tests. Median values are reported.

RESULTS

Thirteen patients were replanned with NHDO techniques. Planning target volume coverage by the prescription dose was similar (NHDO = 96% vs HDO = 97%, P = .3). All normal-tissue dose constraints were met. NHDO plans were prescribed to a lower-prescription isodose line compared with HDO plans (85% vs 97%, P = .001). NHDO increased mean dose to the planning target volume (73 Gy vs 67 Gy), dose heterogeneity, and dose falloff gradient (P < .03). NHDO decreased mean dose to surrounding lungs, esophagus, and heart (relative reduction of 6%, 14%, and 15%, respectively; P < .05). Other normal tissue objectives improved with NHDO, including total lung V40 and V60, heart V30, and maximum esophageal dose (P < .05). Tumor control probabilities doubled from 31.6% to 65.4% with NHDO (P = .001).

CONCLUSIONS

In select patients, NHDO principles used in SBRT optimization can be applied to CF-RT. NHDO results in increased tumor dose, reduction in select organ-at-risk dose objectives, and better maintenance of target coverage and normal-tissue constraints compared with HDO. Our data demonstrate that principles of NHDO used in SBRT can also improve plan quality in CF-RT.

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 (GRID_2 cm) and 3‐cm center‐to‐center spacing (GRID_3 cm), all contained within a larger cylinder (8 and 10 cm in diameter for the GRID_2 cm and GRID_3 cm, respectively). In a single patient, a GRID_3 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 (TOMO_2.5 cm) 2.5 cm and (TOMO_5 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 GRID_2 cm/GRID_3 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, TOMO_5 cm, and TOMO_2.5 cm plans, respectively. The peak‐to‐edge ratios for GRID_2 cm/GRID_3 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, TOMO_5 cm, and TOMO_2.5 cm plans, respectively. The volume of normal tissue receiving 7.5 Gy was lowest in the TOMO_2.5 cm plan (GRID_2 cm/GRID_3 cm/Patient = 54 cm³/19 cm³/10 cm³). The VMAT plans had the lowest delivery times (GRID_2 cm/GRID_3 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.

Dose/Volume histogram patterns in Salivary Gland subvolumes influence xerostomia injury and recovery

Xerostomia is a common consequence of radiotherapy in head and neck cancer. The objective was to compare the regional radiation dose distribution in patients that developed xerostomia within 6 months of radiotherapy and those recovered from xerostomia within 18 months post-radiotherapy. We developed a feature generation pipeline to extract dose volume histogram features from geometrically defined ipsilateral/contralateral parotid glands, submandibular glands, and oral cavity surrogates for each patient. Permutation tests with multiple comparisons were performed to assess the dose difference between injury vs. non-injury and recovery vs. non-recovery. Ridge logistic regression models were applied to predict injury and recovery using clinical features along with dose features (D10-D90) of the subvolumes extracted from oral cavity and salivary gland contours + 3 mm peripheral shell. Model performances were assessed by the area under the receiver operating characteristic curve (AUC) using nested cross-validation. We found that different regional dose/volume metrics patterns exist for injury vs. recovery. Compared to injury, recovery has increased importance to the subvolumes receiving lower dose. Within the subvolumes, injury tends to have increased importance towards D10 from D90. This suggests that different threshold for xerostomia injury and recovery. Injury is induced by the subvolumes receiving higher dose, and the ability to recover can be preserved by further reducing the dose to subvolumes receiving lower dose.

Treatment data and technical process challenges for practical big data efforts in radiation oncology

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.

Improving prediction of surgical resectability over current staging guidelines in patients with pancreatic cancer who receive stereotactic body radiation therapy

Purpose

For patients with localized pancreatic cancer (PC) with vascular involvement, prediction of resectability is critical to define optimal treatment. However, the current definitions of borderline resectable (BR) and locally advanced (LA) disease leave considerable heterogeneity in outcomes within these classifications. Moreover, factors beyond vascular involvement likely affect the ability to undergo resection. Herein, we share our experience developing a model that incorporates detailed radiologic, patient, and treatment factors to predict surgical resectability in patients with BR and LA PC who undergo stereotactic body radiation therapy (SBRT).

Methods and materials

Patients with BR or LA PC who were treated with SBRT between 2010 and 2016 were included. The primary endpoint was margin negative resection, and predictors included age, sex, race, treatment year, performance status, initial staging, tumor volume and location, baseline and pre-SBRT carbohydrate antigen 19-9 levels, chemotherapy regimen and duration, and radiation dose. In addition, we characterized the relationship between tumors and key arteries (superior mesenteric, celiac, and common hepatic arteries), using overlap volume histograms derived from computed tomography data. A classification and regression tree was built, and leave-one-out cross-validation was performed. Prediction of surgical resection was compared between our model and staging in accordance with the National Comprehensive Care Network guidelines using McNemar's test.

Results

A total of 191 patients were identified (128 patients with LA and 63 with BR), of which 87 patients (46%) underwent margin negative resection. The median total dose was 33 Gy. Predictors included the chemotherapy regimen, amount of arterial involvement, and age. Importantly, radiation dose that covers 95% of gross tumor volume (GTV D95), was a key predictor of resectability in certain subpopulations, and the model showed improved accuracy in the prediction of margin negative resection compared with National Comprehensive Care Network guideline staging (75% vs 63%; P < .05).

Conclusions

We demonstrate the ability to improve prediction of surgical resectabiliy beyond the current staging guidelines, which highlights the value of assessing vascular involvement in a continuous manner. In addition, we show an association between radiation dose and resectability, which suggests the potential importance of radiation to allow for resection in certain populations. External data are needed for validation and to increase the robustness of the model.

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.

Evaluation of classification and regression tree (CART) model in weight loss prediction following head and neck cancer radiation therapy

OBJECTIVE

We explore whether a knowledge-discovery approach building a Classification and Regression Tree (CART) prediction model for weight loss (WL) in head and neck cancer (HNC) patients treated with radiation therapy (RT) is feasible.

METHODS AND MATERIALS

HNC patients from 2007 to 2015 were identified from a prospectively collected database Oncospace. Two prediction models at different time points were developed to predict weight loss ≥5 kg at 3 months post-RT by CART algorithm: (1) during RT planning using patient demographic, delineated dose data, planning target volume-organs at risk shape relationships data and (2) at the end of treatment (EOT) using additional on-treatment toxicities and quality of life data.

RESULTS

Among 391 patients identified, WL predictors during RT planning were International Classification of Diseases diagnosis; dose to masticatory and superior constrictor muscles, larynx, and parotid; and age. At EOT, patient-reported oral intake, diagnosis, N stage, nausea, pain, dose to larynx, parotid, and low-dose planning target volume-larynx distance were significant predictive factors. The area under the curve during RT and EOT was 0.773 and 0.821, respectively.

CONCLUSIONS

We demonstrate the feasibility and potential value of an informatics infrastructure that has facilitated insight into the prediction of WL using the CART algorithm. The prediction accuracy significantly improved with the inclusion of additional treatment-related data and has the potential to be leveraged as a strategy to develop a learning health system.

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.

Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132

Image registration and fusion algorithms exist in almost every software system that creates or uses images in radiotherapy. Most treatment planning systems support some form of image registration and fusion to allow the use of multimodality and time-series image data and even anatomical atlases to assist in target volume and normal tissue delineation. Treatment delivery systems perform registration and fusion between the planning images and the in-room images acquired during the treatment to assist patient positioning. Advanced applications are beginning to support daily dose assessment and enable adaptive radiotherapy using image registration and fusion to propagate contours and accumulate dose between image data taken over the course of therapy to provide up-to-date estimates of anatomical changes and delivered dose. This information aids in the detection of anatomical and functional changes that might elicit changes in the treatment plan or prescription. As the output of the image registration process is always used as the input of another process for planning or delivery, it is important to understand and communicate the uncertainty associated with the software in general and the result of a specific registration. Unfortunately, there is no standard mathematical formalism to perform this for real-world situations where noise, distortion, and complex anatomical variations can occur. Validation of the software systems performance is also complicated by the lack of documentation available from commercial systems leading to use of these systems in undesirable 'black-box' fashion. In view of this situation and the central role that image registration and fusion play in treatment planning and delivery, the Therapy Physics Committee of the American Association of Physicists in Medicine commissioned Task Group 132 to review current approaches and solutions for image registration (both rigid and deformable) in radiotherapy and to provide recommendations for quality assurance and quality control of these clinical processes.

Very High-Risk Localized Prostate Cancer: Outcomes Following Definitive Radiation

PURPOSE

Existing definitions of high-risk prostate cancer consist of men who experience significant heterogeneity in outcomes. As such, criteria that identify a subpopulation of National Comprehensive Cancer Network (NCCN) high-risk prostate cancer patients who are at very high risk (VHR) for poor survival outcomes following prostatectomy were recently developed at our institution and include the presence of any of the following disease characteristics: multiple NCCN high-risk factors, primary Gleason pattern 5 disease and/or ≥5 biopsy cores with Gleason sums of 8 to 10. Whether these criteria also apply to men undergoing definitive radiation is unclear, as is the optimal treatment regimen in these patients.

METHODS AND MATERIALS

All men consecutively treated with definitive radiation by a single provider from 1993 to 2006 and who fulfilled criteria for NCCN high-risk disease were identified (n=288), including 99 patients (34%) with VHR disease. Multivariate-adjusted competing risk regression models were constructed to assess associations between the VHR definition and biochemical failure (BF), distant metastasis (DM), and prostate cancer-specific mortality (PCSM). Multivariate-adjusted Cox regression analysis assessed the association of the VHR definition with overall mortality (OM). Cumulative incidences of failure endpoints were compared between VHR men and other NCCN high-risk men.

RESULTS

Men with VHR disease compared to other NCCN high-risk men experienced a higher 10-year incidence of BF (54.0% vs 35.4%, respectively, P<.001), DM (34.9% vs 13.4%, respectively, P<.001), PCSM (18.5% vs 5.9%, respectively, P<.001), and OM (36.4% vs 27.0%, respectively, P=.04). VHR men with a detectable prostate-specific antigen (PSA) concentration at the end of radiation (EOR) remained at high risk of 10-year PCSM compared to VHR men with an undetectable EOR PSA (31.0% vs 13.7%, respectively, P=.05).

CONCLUSIONS

NCCN high-risk prostate cancer patients who meet VHR criteria experience distinctly worse outcomes following definitive radiation and long-term androgen deprivation therapy, particularly if an EOR PSA is detectable. Optimal use of local therapies for VHR patients should be explored further, as should novel agents.

A prospective study evaluating stereotactic body radiation therapy in unresectable, recurrent, or residual pancreatic adenocarcinoma

454

Background: The purpose of this prospective, non-randomized phase II single-institution study was to evaluate if local control can be achieved with reasonable acute and late GI toxicity using fractionated SBRT in patients with unresectable, recurrent, or residual locally advanced pancreatic cancer (LAPC). Methods: A total of 24 patients with LAPC were enrolled from June 2013 to August 2014. Eligibility required stability after induction chemotherapy or residual disease or local failure after surgery. Induction chemotherapy regimens consisted of: (1) gemcitabine alone (8%); (2) gemcitabine-based regimens (17%); (3) FOLFIRINOX-based regimens (63%); or (4) combination regimens (13%). Chemotherapy was discontinued one week prior to SBRT. Patients received a median cumulative dose of 33 Gy in 5 fractions (5-6.6 Gy/fraction). Patients were permitted to resume chemotherapy one week post-SBRT. Toxicity was assessed using the NCI CTCAE version 4.0. Results: Of the 24 patients, 58% were male and 50% had tumors in the head of the pancreas. Median age at diagnosis was 66.8 years, and median follow-up from the date of diagnosis was 11.9 months (range, 7.4-29.7 months). There have not been any acute or late grade ≥ 2 gastritis, enteritis, fistula, or ulcer toxicities (primary endpoint). Median OS has not yet been reached, median LPFS was 19.3 months (95% CI, 12.3-14.8), median DMFS was 13.6 months (95% CI, 9.2-17.9) and median PFS was 13.6 months (95% CI, 13.5-25.2). Plasma CA 19-9 level was non-significantly reduced after SBRT, displaying a -9.15 average percent change from baseline (median time after SBRT, 1.2 months). FFLP at 1 year was 83.9%. Eight (33%) patients underwent successful surgery following SBRT, with rates of both margin- and node-negative resection being 75%. Conclusions: Chemotherapy followed by fractionated SBRT results in favorable local control and survival with minimal acute and late GI toxicity. A notable proportion of patients initially deemed unresectable underwent successful resection. This study suggests that SBRT can be safely given following more aggressive multiagent chemotherapy in patients with LAPC. Clinical trial information: NCT01781728.

Dosimetric predictors of sexual function decline following LDR brachytherapy for prostate cancer (PCa)

113

Background: Conventional dosimetric standards for implant quality do not adequately predict patient reported QoL measures following prostate brachytherapy. We used a dynamic learning knowledgebase (Oncospace) to explore relationships between dose and patient-reported outcomes. Methods: Patient reported quality of life outcomes were prospectively collected for 366 patients with stage cT1-T2 PCa over a 10 year interval. Patients received Pd-103 seed implantation under real-time ultrasound guidance, and completed a QoL instrument (IIEF-5) prior to treatment and at follow-up. Multivariate risk models were used to evaluate dose/toxicity relationships and the Oncospace learning environment generated prediction models using granular dose volume relationships. Results: Median follow-up was 36 months (SD 28.5). In the cohort, 23.7% (n = 87) received combined brachytherapy and EBRT; 14.7% (n = 54) had received prior androgen suppression therapy. Sexual QoL data at minimum of 2 years was available in 141 men. The mean decrement in sexual function per the IIEF-5 instrument was 3.76 points (SD 10.3), with 17.0% of men reporting a decrement of 10 points or greater. There was no significant association with prior androgen suppression (p = 0.20) or combined EBRT use (p = 0.69). DVH curves were queried and dichotomized according to stable sexual function vs significant decline ( > 10) at 2 years post-implant. A logistic regression model was used to generate probability surface maps of volumetric dose effects on outcomes. Logistic regression revealed a correlation between dose to the cavernosal nerves and total SHIM score throughout the high dose region of the DVH curve (p < 0.05). No similar dose/volume correlation with sexual function emerged for structures. Conclusions: Granular dose/volume and toxicity correlation using the Oncospace learning environment exposed a statistically significant relationship between volumetric dose to the cavernosal nerves and sexual function decline in patients undergoing LDR brachytheramarpy. Minimization of dose to the cavernosal nerves may preserve sexual function after permanent prostate seed brachytherapy.

End-of-radiation PSA as a novel prognostic factor in patients undergoing definitive radiation for prostate cancer

68

Background: In patients with localized prostate cancer undergoing radiation therapy (RT) +/- androgen deprivation therapy (ADT), an end of radiation (EOR) PSA obtained during the last week of RT may serve as an early post-treatment predictor of poor outcomes and identify patients in whom to pursue treatment intensification or novel therapies. Methods: We reviewed an IRB-monitored, prospectively acquired database of patients with prostate cancer treated with definitive RT at our institution from 1993-2007 (n=890). Patients with an available EOR PSA were divided into two cohorts and analyzed separately based on inclusion of ADT into the treatment regimen. EOR PSA thresholds of 0.5 ng/mL and 1.0 ng/mL were explored. Multivariate analysis was performed to determine prognostic factors for biochemical failure-free survival (BFFS, Phoenix criteria) and overall survival (OS). Kaplan-Meier survival curves were constructed, with stratification by EOR PSA thresholds. Results: Median age was 69 years, with an even distribution of NCCN low risk (33.5%), intermediate risk (34.0%), and high risk (32.5%) patients. Median RT dose was 7020 cGy, and 54.5% were treated with ADT. Median follow-up of the entire cohort was 11.7 yrs. EOR PSA level was available for the majority of patients (77.5%). On multivariate analysis, EOR PSA >0.5 ng/mL was significantly associated with worse BFFS (p<0.0001) and OS (p<0.0001). In the subset of patients undergoing RT with ADT for NCCN intermediate/high risk disease, 5 yr BFFS was more disparate based an EOR PSA threshold of 0.5 ng/mL (5 yr BFFS: 87.3% vs. 41.1%, p<0.001), than initial NCCN risk level (5 yr BFFS: 88.7% vs. 76.9%, p=0.038). In NCCN low risk patients undergoing definitive RT alone, an EOR PSA threshold of 1.0 ng/mL was significantly prognostic of outcome (5 yr BFFS: 100.0% vs. 88.6%, p=0.024). Conclusions: For NCCN intermediate/high risk patients undergoing RT with ADT, EOR PSA >0.5 ng/mL may represent a better surrogate for poor outcomes than initial risk group. In addition, NCCN low risk patients undergoing RT alone who obtained an EOR PSA ≤1.0 ng/mL experienced excellent BFFS. Prospective evaluation of the utility of EOR PSA should be explored.

Clinical deployment of automatic treatment planning for pancreas SBRT patients

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Background: To clinically utilize an SQL relational database of prior treated patients to generate objectives for future treatment plans. A database approach allows for more rapid planning by starting with a better initial solution and improves safety by providing good known achievable dose values for the initial optimization. The use of a database allows for trending of dose, structure and toxicity data. Methods: A database of fifty-three patients from three institutions is populated with dose and structure data via an automatic script within the treatment planning system. For each new patient, overlap volume histograms (OVHs) are generated to describe the relationship between targets and critical structures. To aid in database consistency, a renaming interface is used which maps known alternative structure names to common names in the database. To ensure all required structures are present, the user is prompted with the names of missing structures. This interface allows selection of machine, energy and commonly used beam sets. The database is queried for all prior patients with the same or closer relationship between the target and each critical structure. The dose objectives reported are the lowest achievable dose from all patients as difficult or harder to plan as determined by OVH. Queried dose objectives are automatically loaded into the treatment planning system and optimized. A protocol quality tool is developed to quickly assess how well plans adhere to specified protocols. Results: Twenty-seven SBRT patients have been planned and clinically approved using the automatic planning tool and future patients continue to be added to the database. OVH computation required approximately 2 minutes, while typical plan optimization required 2.5 minutes. If auto-planned patients require even one fewer optimization to achieve an acceptable plan, total planning time is reduced. Safety is improved by reducing the number of protocol violations from 35% to 6% for one objective. Conclusions: Automatic treatment planning allows for rapid planning while reducing normal tissue dose to known achievable values. The continued addition of patients to the database allows for improvement of the automatically selected planning objectives.

An overlap-volume-histogram based method for rectal dose prediction and automated treatment planning in the external beam prostate radiotherapy following hydrogel injection

PURPOSE

Hydrogel injected between the rectum and prostate prior to radiotherapy provides a possible means of increased dose sparing to the rectum. Here the authors evaluate the overlap volume histogram (OVH) metric as a means to predict the rectal dose following hydrogel injection. Whether OVH predicted dose can serve as the dose objective or constraint for automated treatment planning was also investigated.

METHODS

Treatment planning was performed on 21 prostate cancer patients both pre- and posthydrogel injection, with five-field IMRT delivering 78 Gy to the planning target volume (PTV). The authors quantify the geometrical relationship between the rectum and the prostate PTV using an OVH metric which determines the fractional volume of the rectum that is within a specified distance of the PTV. For an OVH distance the authors selected, L(20), the PTV expansion distance at which 20% of the rectum overlaps. The authors calculated the rectal dose, D(20), received by 20% of the rectum volume on the dose volume histogram. Linear regression was used to examine the correlation between the L(20) and D(20), and between ΔL(20) and ΔD(20) (i.e., the change of L(20) and D(20) posthydrogel injection). Additionally, rectal dose D(15), D(25), D(35), D(50), and bladder dose D(15) were predicted from the OVH (L(15), L(25), L(35), L(50), for rectum and L(15) for bladder) by the L(x)-D(x) linear regression. The predicted doses were applied to the objectives for automated treatment planning of ten plans from five patients. Automatically generated plans were compared with plans manually generated on trial-and-error basis.

RESULTS

The rectal L(20) was increased and dose D(20) decreased due to the enlarged separation of rectum caused by the hydrogel injection. Linear regression showed an inverse linear correlation between L(20) and D(20), and between ΔL(20) and ΔD(20) (r(2) = 0.77, 0.60, respectively; p < 0.0001). The increase in rectal sparing (ΔD(20)) is only weakly correlated with the volume of injected hydrogel (r(2) = 0.17; p = 0.07), indicating OVH is a more predictive indicator of rectal sparing than the volume of hydrogel itself. Application of the predicted rectum and bladder doses to automated planning produced acceptable treatment plans, with rectal dose reduced for eight of ten plans.

CONCLUSIONS

The OVH metric can predict the rectal dose in the external beam prostate radiotherapy for patients with hydrogel injection. The predicted doses can be applied to the objectives of optimization in automated treatment planning to produce acceptable treatment plans.

Patterns of palliative radiation near the end of life: A single-institution retrospective analysis

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Background: The care of patients who receive radiation therapy (RT) at the end of life (EOL) is under scrutiny to ensure effectiveness and value, with many patients not completing RT (Gripp, 2010; Toole, 2012). This retrospective analysis seeks to describe patterns of utilization of palliative RT, including rates of completion of RT offered at the EOL and the use of single fraction RT for bone metastases. Methods: Electronic medical records were used to create a database of 3,383 RT plans for brain, bone, lung, and other metastatic sites in patients treated at Johns Hopkins Hospital from 9/1/2007-7/15/2012. RT plans without palliative intent were excluded. T-tests and logistic regression compared patient and treatment characteristics between patients who died > 1 month versus ≤ 1 month after their last RT fraction. Results: A total of 983 patients were treated to 1,524 sites, with an average of 1.7 RT sites (SD 1.3) per patient. Of these, 872 (89%) patients had complete records and were included in analysis. At the time of analysis, 85% had died. The mean age of 62.1 years (SD 3.4) did not differ statistically based on time from RT to death. Death ≤ 1 month after RT was documented in 215 (24.7%) patients. Compared to patients living > 1 month after RT, patients receiving RT within the last month of life were more likely to be lung (17% versus 9%), less likely to be brain (34% versus 44%), and equally likely to be bone (45% versus 43%) sites. Patients who died ≤ 1 month after completing RT spent on average 5 days (16.6%) of the last month of life receiving RT, with no significant difference by disease site. Conclusions: Most patients receiving palliative RT finish therapy, with 25% dying ≤ 1 month after RT. Single fraction bone RT was relatively uncommon, with no significant difference in the rates of single fraction RT based on time from RT to death. These data provide a framework to match treatment patterns with national guidelines. Additionally, they provide context to model risk of death shortly after RT, which can aid in clinical decision-making. [Table: see text]