This prospective study will test artificial intelligence (AI) and machine learning (ML) decision support tools. This tool is designed to help doctors, physicists and other staff during pre-treatment peer review, a step where treatment plans are checked before a patient begins care.
The system highlights summaries showing how different providers may vary in their treatment planning (provider-variability summaries) and points out the best signals or warning signs to look for (optimal cues). By drawing attention to these patterns and cues, the tool aims to help reviewers spot possible treatment-planning mistakes earlier, reduce the chance of errors, and improve overall patient safety.
≥18 years
Peer-review attendees at participating clinics
≥18 years
All patients with prostate cancer radiation therapy cases treated at participating sites (no intervention delivered to patients)
None
Parallel
The Artificial Intelligence (AI)/ Machine Learning (ML) contribution to treatment planning
DeviceAll treatment planning and clinical monitoring are conducted in accordance with institutional standards and established departmental policies. Peer review activities proceed as they would in routine clinical practice, with the addition of optional Artificial Intelligence (AI) generated analytics available for clinician review. AI / Machine Learning (ML) system is embedded in scheduled departmental peer review meetings and presents analytic summaries and visualizations through a dashboard that is integrated into the existing clinical workflow. The system functions solely as a decision support aid and does not perform or initiate any autonomous treatment planning actions, dose delivery changes, or clinical interventions. During simulation (SIM) review, physician generated target and organ at risk contours are reviewed first, consistent with standard practice. Only after this initial review may the treating physician optionally access the AI generated contours for comparative purposes.
Percentage of patients with changes nodal volume contours
Percentage of patients with documented changes regarding nodal volume contours after Artificial Intelligence (AI) enhanced peer review.
Click on the lead sponsor to view all of their trials.
UNC Lineberger Comprehensive Cancer Center
Lead sponsor
Agency for Healthcare Research and Quality (AHRQ)
Collaborator
