Implementation of a programmatic assessment model in radiation oncology medical physics training.

PURPOSE: In 2019, a formal review and update of the current training program for medical physics residents/registrars in Australasia was conducted. The purpose of this was to ensure the program met current local clinical and technological requirements, to improve standardization of training across Australia and New Zealand and generate a dynamic curriculum and programmatic assessment model. METHODS: A four-phase project was initiated, including a consultant desktop review of the current program and stakeholder consultation. Overarching program outcomes on which to base the training model were developed, with content experts used to update the scientific content. Finally, assessment specialists reviewed a range of assessment models to determine appropriate assessment methods for each learning outcome, creating a model of programmatic assessment. RESULTS: The first phase identified a need for increased standardized assessment incorporating programmatic assessment. Seven clear program outcome statements were generated and used to guide and underpin the new curriculum framework. The curriculum was expanded from the previous version to include emerging technologies, while removing previous duplication. Finally, a range of proposed assessments for learning outcomes in the curriculum were generated into the programmatic assessment model. These new assessment methods were structured to incorporate rubric scoring to provide meaningful feedback. CONCLUSIONS: An updated training program for Radiation Oncology Medial Physics registrars/residents was released in Australasia. Scientific content from a previous program was used as a foundation and revised for currency with the ability to accommodate a dynamic curriculum model. A programmatic model of assessment was created after comprehensive review and consultation. This new model of assessment provides more structured, ongoing assessment throughout the training period. It contains allowances for local bespoke assessment, and guidance for supervisors by the provision of marking templates and rubrics.

Clinical physicists' perceptions of weekly chart checks and the potential role for automated image review assessed by structured interviews.

BACKGROUND: This study utilizes interviews of clinical medical physicists to investigate self-reported shortcomings of the current weekly chart check workflow and opportunities for improvement. METHODS: Nineteen medical physicists were recruited for a 30-minute semi-structured interview, with a particular focus placed on image review and the use of automated tools for image review in weekly checks. Survey-type questions were used to gather quantitative information about chart check practices and importance placed on reducing chart check workloads versus increasing chart check effectiveness. Open-ended questions were used to probe respondents about their current weekly chart check workflow, opinions of the value of weekly chart checks and perceived shortcomings, and barriers and facilitators to the implementation of automated chart check tools. Thematic analysis was used to develop common themes across the interviews. RESULTS: Physicists ranked highly the value of reducing the time spent on weekly chart checks (average 6.3 on a scale from 1 to 10), but placed more value on increasing the effectiveness of checks with an average of 9.2 on a 1-10 scale. Four major themes were identified: (1) weekly chart checks need to adapt to an electronic record-and-verify chart environment, (2) physicists could add value to patient care by analyzing images without duplicating the work done by physicians, (3) greater support for trending analysis is needed in weekly checks, and (4) automation has the potential to increase the value of physics checks. CONCLUSION: This study identified several key shortcomings of the current weekly chart check process from the perspective of the clinical medical physicist. Our results show strong support for automating components of the weekly check workflow in order to allow for more effective checks that emphasize follow-up, trending, failure modes and effects analysis, and allow time to be spent on other higher value tasks that improve patient safety.

AAPM WGPE report 394: Simulated error training for the physics plan and chart review.

BACKGROUND: Simulated error training is a method to practice error detection in situations where the occurrence of error is low. Such is the case for the physics plan and chart review where a physicist may check several plans before encountering a significant problem. By simulating potentially hazardous errors, physicists can become familiar with how they manifest and learn from mistakes made during a simulated plan review. PURPOSE: The purpose of this project was to develop a series of training datasets that allows medical physicists and trainees to practice plan and chart reviews in a way that is familiar and accessible, and to provide exposure to the various failure modes (FMs) encountered in clinical scenarios. METHODS: A series of training datasets have been developed that include a variety of embedded errors based on the risk-assessment performed by American Association of Physicists in Medicine (AAPM) Task Group 275 for the physics plan and chart review. The training datasets comprise documentation, screen shots, and digital content derived from common treatment planning and radiation oncology information systems and are available via the Cloud-based platform ProKnow. RESULTS: Overall, 20 datasets have been created incorporating various software systems (Mosaiq, ARIA, Eclipse, RayStation, Pinnacle) and delivery techniques. A total of 110 errors representing 50 different FMs were embedded with the 20 datasets. The project was piloted at the 2021 AAPM Annual Meeting in a workshop where participants had the opportunity to review cases and answer survey questions related to errors they detected and their perception of the project's efficacy. In general, attendees detected higher-priority FMs at a higher rate, though no correlation was found between detection rate and the detectability of the FMs. Familiarity with a given system appeared to play a role in detecting errors, specifically when related to missing information at different locations within a given software system. Overall, 96% of respondents either agreed or strongly agreed that the ProKnow portal and training datasets were effective as a training tool, and 75% of respondents agreed or strongly agreed that they planned to use the tool at their local institution. CONCLUSIONS: The datasets and digital platform provide a standardized and accessible tool for training, performance assessment, and continuing education regarding the physics plan and chart review. Work is ongoing to expand the project to include more modalities, radiation oncology treatment planning and information systems, and FMs based on emerging techniques such as auto-contouring and auto-planning.

A Perspective from Ontario Tech University Industrial Research Chairs on 20 Years of Capacity Building in Health Physics and Radiation Science.

ABSTRACT: Ontario Tech University (University of Ontario Institute of Technology) is one of Canada's newest universities, having been incorporated in 2002. In 20 y, the University has increased enrollment from a few hundred students to over 10,000. The University was designed to be "market driven" and as such offered courses that had high market demand. The Faculty of Energy Systems and Nuclear Science was one of the first faculties to be established at the University, with the intent to fill a gap between personnel that were retiring out of the nuclear industry and the dearth of nuclear engineers and health physicists being educated in Canada. As such, the University established unique programs in both nuclear engineering and health physics/radiation science with strong input from industry stakeholders. This paper will discuss the evolution of the Health Physics and Radiation Science program at Ontario Tech from the teaching and capacity building perspective, and it provides insight regarding health physics and radiation science research at Ontario Tech under the industrial research chair program.

Technical note: A universal worksheet for failure mode and effects analysis-A project of the Japanese College of Medical Physics.

BACKGROUND: Failure mode and effects analysis (FMEA), which is an effective tool for error prevention, has garnered considerable attention in radiotherapy. FMEA can be performed individually, by a group or committee, and online. PURPOSE: To meet the needs of FMEA for various purposes and improve its accessibility, we developed a simple, self-contained, and versatile web-based FMEA risk analysis worksheet. METHODS: We developed an FMEA worksheet using Google products, such as Google Sheets, Google Forms, and Google Apps Script. The main sheet was created in Google Sheets and contained elements necessary for performing FMEA by a single person. Automated tasks were implemented using Apps Script to facilitate multiperson FMEA; these functions were built into buttons located on the main sheet. RESULTS: The usability of the FMEA worksheet was tested in several situations. The worksheet was feasible for individual, multiperson, seminar, meeting, and online purposes. Simultaneous online editing, automated survey form creation, automatic analysis, and the ability to respond to the form from multiple devices, including mobile phones, were particularly useful for online and multiperson FMEA. Automation enabled through Google Apps Script reduced the FMEA workload. CONCLUSIONS: The FMEA worksheet is versatile and has a seamless workflow that promotes collaborative work for safety.

Artificial intelligence model GPT4 narrowly fails simulated radiological protection exam.

This study assesses the efficacy of Generative Pre-Trained Transformers (GPT) published by OpenAI in the specialised domains of radiological protection and health physics. Utilising a set of 1064 surrogate questions designed to mimic a health physics certification exam, we evaluated the models' ability to accurately respond to questions across five knowledge domains. Our results indicated that neither model met the 67% passing threshold, with GPT-3.5 achieving a 45.3% weighted average and GPT-4 attaining 61.7%. Despite GPT-4's significant parameter increase and multimodal capabilities, it demonstrated superior performance in all categories yet still fell short of a passing score. The study's methodology involved a simple, standardised prompting strategy without employing prompt engineering or in-context learning, which are known to potentially enhance performance. The analysis revealed that GPT-3.5 formatted answers more correctly, despite GPT-4's higher overall accuracy. The findings suggest that while GPT-3.5 and GPT-4 show promise in handling domain-specific content, their application in the field of radiological protection should be approached with caution, emphasising the need for human oversight and verification.

The AAPM/ASTRO 2023 Core Physics Curriculum for Radiation Oncology Residents.

PURPOSE: The American Association of Physicists in Medicine Radiation Oncology Medical Physics Education Subcommittee (ROMPES) has updated the radiation oncology physics core curriculum for medical residents in the radiation oncology specialty. METHODS AND MATERIALS: Thirteen physicists from the United States and Canada involved in radiation oncology resident education were recruited to ROMPES. The group included doctorates and master's of physicists with a range of clinical or academic roles. Radiation oncology physician and resident representatives were also consulted in the development of this curriculum. In addition to modernizing the material to include new technology, the updated curriculum is consistent with the format of the American Board of Radiology Physics Study Guide Working Group to promote concordance between current resident educational guidelines and examination preparation guidelines. RESULTS: The revised core curriculum recommends 56 hours of didactic education like the 2015 curriculum but was restructured to provide resident education that facilitates best clinical practice and scientific advancement in radiation oncology. The reference list, glossary, and practical modules were reviewed and updated to include recent literature and clinical practice examples. CONCLUSIONS: ROMPES has updated the core physics curriculum for radiation oncology residents. In addition to providing a comprehensive curriculum to promote best practice for radiation oncology practitioners, the updated curriculum aligns with recommendations from the American Board of Radiology Physics Study Guide Working Group. New technology has been integrated into the curriculum. The updated curriculum provides a framework to appropriately cover the educational topics for radiation oncology residents in preparation for their subsequent career development.

Development of DynamicMC for PHITS Monte Carlo package.

Previously, we have developed DynamicMC for modeling relative movement of Oak Ridge National Laboratory phantom in a radiation field for the Monte Carlo N-Particle package (Health Physics. 2023,124(4):301-309). Using this software, three-dimensional dose distributions in a phantom irradiated by a certain mono-energetic (Mono E) source can be deduced through its graphical user interface. In this study, we extended DynamicMC to be used in combination with the Particle and Heavy Ion Transport code System (PHITS) by providing it with a higher flexibility for dynamic movement for an anthropomorphic phantom. For this purpose, we implemented four new functions into the software, which are (1) to generate not only Mono E sources but also those having an energy spectrum of an arbitrary radioisotope (2) to calculate the absorbed doses for several radiologically important organs (3) to automatically average the calculated absorbed doses along the path of the phantom and (4) to generate user-defined slab shielding materials. The first and third items utilize the PHITS-specific modalities named radioisotope-source and sumtally functions, respectively. The computational cost and complexity can be dramatically reduced with these features. We anticipate that the present work and the developed open-source tools will be in the interest of nuclear radiation physics community for research and teaching purposes.

Soil surface roughness impacts the risk arising from a hypothetical urban radiological dispersive device activation.

This study considers a deliberate hypothetical release of radioactive material over an inhabited urban zone. The event is initiated by the activation of a radiological dispersion device. The main threat is the deposition of radioactive material onto the soil's surface. The radiation represents the threat-defining risks, which depend on the main variables, i.e. soil surface roughness, sex, age of the exposed individuals and the moment of the release (day or nighttime). This study aims to evaluate the effect of soil surface roughness on the radiological risk. The simulation was performed by an analytical method using the HotSpot Health Physics code within the first 100 h. The results found relevant elements that allow for differentiating consequences as a function of the time of release (whether daytime or nighttime), thus allowing decision-makers to be supported with a little more detail about the situation, although in a critical initial phase.