Clinical Physics Boot Camp for Radiation Oncology Residents: A Pilot Study.

The physics curriculum is a source of anxiety both for medical students considering radiation oncology (RO) as a possible career and for current residents facing the physics boards. To improve the orientation process for residents and medical students, we created a physics boot camp using clinically relevant patient vignettes to teach physics fundamentals. The initial boot camp was a week-long program of 1.5 to 2 hours daily, with each day consisting of a didactic session and hands-on laboratory. Boot camp topics covered included physics fundamentals, electron treatments, photon treatments, brachytherapy, and urgent clinical setups. Learners completed pre- and postsurveys, where each rated their knowledge and comfort level with RO workflow on a 5-point scale. Learners also completed daily knowledge-based assessments testing the information presented before and after these daily sessions. A total of 10 participants were included in the initial boot camp: 8 residents and 2 medical students. A repeat, single-day, multi-institutional boot camp a year later included 5 of the original resident participants. Participant scores were paired for analysis using student t tests. For the initial boot camp, all participants reported significantly increased confidence in the physics aspects of the RO workflow (mean 3.24 vs 4.18; P = .0023). However, when comparing those self-assessment scores from participants with more than a year of physics background to those earlier in their training, only the early training participants' scores remained significant (advanced learners: mean 4.0 vs 4.38, P = .129; early learners: mean 2.66 vs 4.02, P = .0025). All participants had improved scores on their knowledge-based assessments (mean 74% vs 89%; P = .0001), which remained statistically significant for both early learners (mean 68% vs 87%; P = .0005) and advanced learners (mean 84% vs 93%; P = .0447). For repeat participants, preboot camp knowledge showed continued improvement (mean 61% vs 79%; P = .049) at 1 year. A formal physics boot camp orientation improves both resident comfort level and knowledge base with clinical physics, with participants early in their training deriving the greatest benefit.

Knowledge Models as Teaching Aid for Training Intensity Modulated Radiation Therapy Planning: A Lung Cancer Case Study.

Purpose: Artificial intelligence (AI) employs knowledge models that often behave as a black-box to the majority of users and are not designed to improve the skill level of users. In this study, we aim to demonstrate the feasibility that AI can serve as an effective teaching aid to train individuals to develop optimal intensity modulated radiation therapy (IMRT) plans. Methods and Materials: The training program is composed of a host of training cases and a tutoring system that consists of a front-end visualization module powered by knowledge models and a scoring system. The current tutoring system includes a beam angle prediction model and a dose-volume histogram (DVH) prediction model. The scoring system consists of physician chosen criteria for clinical plan evaluation as well as specially designed criteria for learning guidance. The training program includes six lung/mediastinum IMRT patients: one benchmark case and five training cases. A plan for the benchmark case is completed by each trainee entirely independently pre- and post-training. Five training cases cover a wide spectrum of complexity from easy (2), intermediate (1) to hard (2). Five trainees completed the training program with the help of one trainer. Plans designed by the trainees were evaluated by both the scoring system and a radiation oncologist to quantify planning quality. Results: For the benchmark case, trainees scored an average of 21.6% of the total max points pre-training and improved to an average of 51.8% post-training. In comparison, the benchmark case's clinical plans score an average of 54.1% of the total max points. Two of the five trainees' post-training plans on the benchmark case were rated as comparable to the clinically delivered plans by the physician and all five were noticeably improved by the physician's standards. The total training time for each trainee ranged between 9 and 12 h. Conclusion: This first attempt at a knowledge model based training program brought unexperienced planners to a level close to experienced planners in fewer than 2 days. The proposed tutoring system can serve as an important component in an AI ecosystem that will enable clinical practitioners to effectively and confidently use KBP.