Automated Treatment Plan Integrity Verification for Proton Therapy: Enhancing Error Detection and Workflow Efficiency.

Purpose: Most automatic error detection studies in radiation therapy focus on photon therapy, with limited attention to proton therapy. This study developed and validated an automated framework for initial proton therapy plan review to enhance error detection capabilities and workflow efficiency in pencil-beam scanning treatments. Materials and Methods: Auto-IniCheck, an automated plan review script, was designed following AAPM TG-275 guidelines to systematically verify initial physics plan integrity for proton therapy. Treatment site-specific and modality-specific checklists were integrated into a comprehensive process map indicating manual, automated, or hybrid review requirements with color-coded risk levels. Risk levels for each step were determined using failure modes and effects analysis, guiding a more effective plan review. The efficiency and effectiveness of Auto-IniCheck were assessed by comparing risk priority numbers and quantifying risk reduction between manual and automated plan reviews. Results: Auto-IniCheck enabled 60% to 65% of checklist items to be reviewed automatically, reducing plan review time to <10 s. It achieved an average 65% risk priority number reduction across all process categories by improving error detectability, with 15 high-risk items reclassified as low risk. The greatest improvements were observed in robustness optimization, couch confirmation, and target validation for optimization, each with a 75% risk reduction. Conclusion: Auto-Ini Check streamlines proton therapy plan reviews by delivering measurable gains in efficiency and safety. This automated system proactively addresses proton-specific failure modes and facilitates practical application during initial plan review. As proton therapy programs grow, this approach offers a scalable solution to maintain rigorous quality assurance.