ArticleJournal of applied clinical medical physics2022
Development and validation of a checklist for use with automatically generated radiotherapy plans.
Article in Journal of applied clinical medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Can physics review catch prescription and PTV margin errors in fully automated radiotherapy plans? A hazard study.Journal of applied clinical medical physics · 2026Article
- AAPM WGTEACH Report 366: Best practices in the teaching and mentoring of medical physics.Journal of applied clinical medical physics · 2025Article
- "If You're Talking, I Think You're Muted": Follow-up Analysis of Weekly Peer Review Discussion and Plan Changes After Transitioning From Virtual to In-Person Format.Clinical oncology (Royal College of Radiologists (Great Britain)) · 2024Article
- Enhancing patient safety in radiotherapy: Implementation of a customized electronic checklist for radiation therapists.Technical innovations & patient support in radiation oncology · 2024Article
- Evaluating automatically generated normal tissue contours for safe use in head and neck and cervical cancer treatment planning.Journal of applied clinical medical physics · 2024Article
- A geometry and dose-volume based performance monitoring of artificial intelligence models in radiotherapy treatment planning for prostate cancer.Physics and imaging in radiation oncology · 2023Article
- Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant.JCO global oncology · 2023Review
- Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?Diagnostics (Basel, Switzerland) · 2023Review
- Development and validation of a checklist for use with automatically generated radiotherapy plans.Journal of applied clinical medical physics · 2022Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo develop a checklist that improves the rate of error detection during the plan review of automatically generated radiotherapy plans.
methodsA custom checklist was developed using guidance from American Association of Physicists in Medicine task groups 275 and 315 and the results of a failure modes and effects analysis of the Radiation Planning Assistant (RPA), an automated contouring and treatment planning tool. The preliminary checklist contained 90 review items for each automatically generated plan. In the first study, eight physicists were recruited from our institution who were familiar with the RPA. Each physicist reviewed 10 artificial intelligence-generated resident treatment plans from the RPA for safety and plan quality, five of which contained errors. Physicists performed plan checks, recorded errors, and rated each plan's clinical acceptability. Following a 2-week break, physicists reviewed 10 additional plans with a similar distribution of errors using our customized checklist. Participants then provided feedback on the usability of the checklist and it was modified accordingly. In a second study, this process was repeated with 14 senior medical physics residents who were randomly assigned to checklist or no checklist for their reviews. Each reviewed 10 plans, five of which contained errors, and completed the corresponding survey.
resultsIn the first study, the checklist significantly improved the rate of error detection from 3.4 ± 1.1 to 4.4 ± 0.74 errors per participant without and with the checklist, respectively (p = 0.02). Error detection increased by 20% when the custom checklist was utilized. In the second study, 2.9 ± 0.84 and 3.5 ± 0.84 errors per participant were detected without and with the revised checklist, respectively (p = 0.08). Despite the lack of statistical significance for this cohort, error detection increased by 18% when the checklist was utilized.
conclusionOur results indicate that the use of a customized checklist when reviewing automated treatment plans will result in improved patient safety.
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