Routine review of patient-reported outcome data influences radiotherapy care: IMPROVE study results.

Background: Radiation oncologists closely monitor patients during weekly on-treatment visits (OTVs). This study examines whether routine patient-reported outcome measures (PROMs) during OTVs change physicians' perceptions of treatment-toxicity and inform symptom-management.

Patient And Methods: IMPROVE is a single-arm prospective multicenter trial, conducted from 2020 to 2023.

Best practice guidelines for use of reference points in radiation oncology information systems to aggregate longitudinal dosimetric data.

Purpose/objectives: Tracking patient dose in radiation oncology is challenging due to disparate electronic systems from various vendors. Treatment planning systems (TPS), radiation oncology information systems (ROIS), and electronic health records (EHR) lack uniformity, complicating dose tracking and reporting. To address this, we examined practices in multiple radiation oncology settings and proposed guidelines for current systems.

Clinical VMAT machine parameter optimization for localized prostate cancer using deep reinforcement learning.

Background: Volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) remains computationally expensive and sensitive to input dose objectives creating challenges for manual and automatic planning. Reinforcement learning (RL) involves machine learning through extensive trial-and-error, demonstrating performance exceeding humans, and existing algorithms in several domains.

Purpose: To develop and evaluate an RL approach for VMAT MPO for localized prostate cancer to rapidly and automatically generate deliverable VMAT plans for a clinical linear accelerator (linac) and compare resultant dosimetry to clinical plans.

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.

Oncologic and Functional Outcomes After Stereotactic Body Radiation Therapy for High-Grade Malignant Spinal Cord Compression.

Purpose: Although surgical decompression is the gold standard for metastatic epidural spinal cord compression (MESCC) from solid tumors, not all patients are candidates or undergo successful surgical Bilsky downgrading. We report oncologic and functional outcomes for patients treated with stereotactic body radiation therapy (SBRT) to high-grade MESCC.

Methods And Materials: Patients with Bilsky grade 2 to 3 MESCC from solid tumor metastases treated with SBRT at a single institution from 2009 to 2020 were retrospectively reviewed.

Developing the POTOMAC Model: A Novel Prediction Model to Study the Impact of Lymphopenia Kinetics on Survival Outcomes in Head and Neck Cancer Via an Ensemble Tree-Based Machine Learning Approach.

Purpose: Lymphopenia is associated with poor survival outcomes in head and neck squamous cell carcinoma (HNSCC), yet there is no consensus on whether we should limit lymphopenia risks during treatment. To fully elucidate the prognostic role of baseline versus treatment-related lymphopenia, a robust analysis is necessary to investigate the relative importance of various lymphopenia metrics (LMs) in predicting survival outcomes.

Methods: In this prospective cohort study, 363 patients were eligible for analysis (patients with newly diagnosed, nonmetastatic HNSCC treated with neck radiation with or without chemotherapy in 2015-2019).

Effects of LRRK2 Inhibitors in Nonhuman Primates.

Toxicology studies in nonhuman primates were conducted to evaluate selective, brain penetrant inhibitors of LRRK2. GNE 7915 was limited to 7-day administration in cynomolgus monkeys at 65 mg/kg/day or limited to 14 days in rhesus at 22.5 mg/kg b.

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

Purpose: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships.

Methods And Materials: The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs.

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.

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.

A digital physician peer to automatically detect erroneous prescriptions in radiotherapy.

Appropriate dosing of radiation is crucial to patient safety in radiotherapy. Current quality assurance depends heavily on a physician peer-review process, which includes a review of the treatment plan's dose and fractionation. Potentially, physicians may not identify errors during this manual peer review due to time constraints and caseload.

Finite Element-Based Personalized Simulation of Duodenal Hydrogel Spacer: Spacer Location Dependent Duodenal Sparing and a Decision Support System for Spacer-Enabled Pancreatic Cancer Radiation Therapy.

Purpose: Pancreatic cancer is the fourth leading cause of cancer-related death, with a very low 5-year overall survival rate (OS). Radiation therapy (RT) together with dose escalation significantly increases the OS at 2 and 3 years. However, dose escalation is very limited due to the proximity of the duodenum.

Interplay Between Duration of Androgen Deprivation Therapy and External Beam Radiotherapy With or Without a Brachytherapy Boost for Optimal Treatment of High-risk Prostate Cancer: A Patient-Level Data Analysis of 3 Cohorts.

Importance: Radiotherapy combined with androgen deprivation therapy (ADT) is a standard of care for high-risk prostate cancer. However, the interplay between radiotherapy dose and the required minimum duration of ADT is uncertain.

Objective: To determine the specific ADT duration threshold that provides a distant metastasis-free survival (DMFS) benefit in patients with high-risk prostate cancer receiving external beam radiotherapy (EBRT) or EBRT with a brachytherapy boost (EBRT+BT).

Performance of a Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography-Derived Risk-Stratification Tool for High-risk and Very High-risk Prostate Cancer.

Importance: Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) can detect low-volume, nonlocalized (ie, regional or metastatic) prostate cancer that was occult on conventional imaging. However, the long-term clinical implications of PSMA PET/CT upstaging remain unclear.

Objectives: To evaluate the prognostic significance of a nomogram that models an individual's risk of nonlocalized upstaging on PSMA PET/CT and to compare its performance with existing risk-stratification tools.

Trimodality therapy for esophageal cancer: The role of surgical and radiation treatment parameters in the development of anastomotic complications.

Background: Here, we investigated the relationship between clinical parameters, including the site of surgical anastomosis and radiation dose to the anastomotic region, and anastomotic complications in esophageal cancer patients treated with trimodality therapy.

Methods: Between 2007 and 2016, esophageal cancer patients treated with trimodality therapy at a tertiary academic cancer center were identified. Patient, treatment, and outcome parameters were collected.

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.

Spatial descriptions of radiotherapy dose: normal tissue complication models and statistical associations.

For decades, dose-volume information for segmented anatomy has provided the essential data for correlating radiotherapy dosimetry with treatment-induced complications. Dose-volume information has formed the basis for modelling those associations via normal tissue complication probability (NTCP) models and for driving treatment planning. Limitations to this approach have been identified.

Patterns of Clinical Progression in Radiorecurrent High-risk Prostate Cancer.

The natural history of radiorecurrent high-risk prostate cancer (HRPCa) is not well-described. To better understand its clinical course, we evaluated rates of distant metastases (DM) and prostate cancer-specific mortality (PCSM) in a cohort of 978 men with radiorecurrent HRPCa who previously received either external beam radiation therapy (EBRT, n = 654, 67%) or EBRT + brachytherapy (EBRT + BT, n = 324, 33%) across 15 institutions from 1997 to 2015. In men who did not die, median follow-up after treatment was 8.