yasui keisuke

Abstract Background Accurate dosimetry is important in radiotherapy, and all equipment used for radiotherapy shoud be audited by an independent external dose audit. Radiophotoluminescence glass dosimeter (RPLD) has excellent characteristics and is widely used for postal dose audit; however, postal dose audit for proton therapy using RPLD has not been established. Purpose This study aims to develop a postal dose audit procedure for scanning proton beams using RPLD, estimate uncertainties, and conduct a multicenter pilot study to validate the methodology. Methods A postal toolkit was developed and a postal dose audit procedure for RPLD measurements of scanning proton beams was established in cooperation with several facilities that employ various accelerators, irradiation equipment, and treatment planning systems (TPS) for clinical use. Based on basic and previous studies, an uncertainty budget was developed for estimating relative uncertainty and pilot studies were conducted at each site. A method for postal dose audits was developed in a multicenter collaboration to develop an approach suitable for implementation across multiple facilities. Results The relative response of 60 RPLDs for scanning proton beam examined in this study was 1.00 ± 1.28% mean ± standard deviation. The combined relative standard uncertainty of postal dosimetry for scanning proton beams using the RPLD was 2.97% (k = 1). Under the reference condition, the maximum differences between the ionization chamber measurement (IC) and TPS, RPLD and TPS, and RPLD and IC were 0.97, 1.88, and 2.12%, respectively. The maximum differences between the RPLD and ionization chamber for plateau measurements at 3 cm depth using single‐energy and non‐reference conditions were 11.31 and 4.02%, respectively. Conclusion We established a procedure for the postal dose audits of proton beams using RPLD and presented the results of a multicenter pilot study. By standardizing the reference conditions, the dosimetry uncertainty was estimated at 2.92%. The results demonstrated the feasibility of performing an independent third‐party dose audit of scanning proton beams using RPLD, and for such postal dose audits for proton beams, the irradiation conditions should be standardized to reduce uncertainties. These results are expected to contribute to the development of proton beams.

This study aimed to evaluate the performance for answering the Japanese medical physicist examination and providing the benchmark of knowledge about medical physics in language-generative AI with large language model. We used questions from Japan's 2018, 2019, 2020, 2021 and 2022 medical physicist board examinations, which covered various question types, including multiple-choice questions, and mainly focused on general medicine and medical physics. ChatGPT-3.5 and ChatGPT-4.0 (OpenAI) were used. We compared the AI-based answers with the correct ones. The average accuracy rates were 42.2 ± 2.5% (ChatGPT-3.5) and 72.7 ± 2.6% (ChatGPT-4), showing that ChatGPT-4 was more accurate than ChatGPT-3.5 [all categories (except for radiation-related laws and recommendations/medical ethics): p value < 0.05]. Even with the ChatGPT model with higher accuracy, the accuracy rates were less than 60% in two categories; radiation metrology (55.6%), and radiation-related laws and recommendations/medical ethics (40.0%). These data provide the benchmark for knowledge about medical physics in ChatGPT and can be utilized as basic data for the development of various medical physics tools using ChatGPT (e.g., radiation therapy support tools with Japanese input).

Background This study evaluates dose perturbations caused by nonradioactive seeds in clinical cases by employing treatment planning system-based Monte Carlo (TPS-MC) simulation. Methodology We investigated dose perturbation using a water-equivalent phantom and 20 clinical cases of prostate cancer (10 cases with seeds and 10 cases without seeds) treated at Fujita Health University Hospital, Japan. First, dose calculations for a simple geometry were performed using the RayStation MC algorithm for a water-equivalent phantom with and without a seed. TPS-independent Monte Carlo (full-MC) simulations and film measurements were conducted to verify the accuracy of TPS-MC simulation. Subsequently, dose calculations using TPS-MC were performed on CT images of clinical cases of prostate cancer with and without seeds, and the dose distributions were compared. Results In clinical cases, dose calculations using MC simulations revealed hotspots around the seeds. However, the size of the hotspot was not correlated with the number of seeds. The maximum difference in dose perturbation between TPS-MC simulations and film measurements was 3.9%, whereas that between TPS-MC simulations and full-MC simulations was 3.7%. The dose error of TPS-MC was negligible for multiple beams or rotational irradiation. Conclusions Hotspots were observed in dose calculations using TPS-MC performed on CT images of clinical cases with seeds. The dose calculation accuracy around the seeds using TPS-MC simulations was comparable to that of film measurements and full-MC simulations, with differences within 3.9%. Although the clinical impact of hotspots occurring around the seeds is minimal, utilizing MC simulations on TPSs can be beneficial to verify their presence.