Journal of Medical Radiation Sciences最新文献

{"title":"Building Research Capacity in Medical Radiation Sciences Through University-Clinical Partnerships: A Commentary on Working Smarter, Not Harder.","authors":"Therese Gunn, Michael Neep, Pamela Rowntree, Deborah Starkey","doi":"10.1002/jmrs.70120","DOIUrl":"10.1002/jmrs.70120","url":null,"abstract":"<p><p>A research partnership model frames university-clinical collaboration as central to strengthening medical radiation sciences research capacity. By aligning students, academics, clinicians, resources, ethics processes, skills development and outputs, the model supports sustainable, evidence-informed practice with potential benefits for patients and professionals.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13540145/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148887868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How We Embedded Consumer Engagement Into Workplace Education and Continuing Professional Development: A Quality Improvement Initiative in a Tertiary Imaging Department.","authors":"Ilona Lavender, Mohamed K Badawy","doi":"10.1002/jmrs.70121","DOIUrl":"10.1002/jmrs.70121","url":null,"abstract":"<p><p>Consumer engagement, meaning the active involvement of patients and carers with lived experience, is increasingly recognised as central to high-quality, patient-centred healthcare, and in Australia it is embedded in national accreditation standards. Within diagnostic imaging departments, however, consumer perspectives remain under-represented in workplace education and continuing professional development (CPD), where educational activities have traditionally prioritised technical competency and workflow. This is despite the fact that clinicians frequently meet patients at vulnerable moments. This paper describes how a tertiary imaging department embedded consumer engagement across workplace education and CPD, governance and service improvement, and outlines practical lessons for departments wishing to implement similar initiatives. It draws on a series of initiatives undertaken within a tertiary imaging department between 2024 and 2025, including consumer storytelling within multidisciplinary workshops and continuing professional development, consumer co-design of patient information resources, a dedicated patient-experience role, and consumer participation in departmental governance. We considered these activities alongside established frameworks for patient involvement in health-professions education and for consumer participation, and we reflected on the practical conditions that distinguish meaningful engagement from tokenism: clarity of purpose, attention to consumer wellbeing, and a shift from symbolic inclusion towards genuine partnership. The activities are illustrated with feedback volunteered by clinicians and consumers, although we are careful to note that these reflections are not a formal evaluation. We argue that consumer storytelling and structured engagement are feasible, low-resource strategies that may promote reflection on empathy, communication and patient-centred practice, while offering practical approaches for embedding consumer engagement within imaging departments. Formal evaluation of educational and patient outcomes remains the necessary next step.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13535535/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuing Professional Development—Radiation Therapy","authors":"","doi":"10.1002/jmrs.70108","DOIUrl":"10.1002/jmrs.70108","url":null,"abstract":"<p>Maximise your continuing professional development (CPD) by reading the selected article and answering the five questions. Please remember to self-claim your CPD and retain your supporting evidence. Answers will be available via the QR code and published in JMRS – Volume 73, Issue 4, December 2026.</p><p>Scan this QR code or https://www.surveymonkey.com/r/JMRS_Sept2026_RT to find the answers.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"73 3","pages":"377-378"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13398473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148391132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Procedure Completion and Engagement of Neurodivergent Patients in Medical Imaging: A Systematic Review","authors":"Rheann Wickramasinghe,&nbsp;Glenda McLean","doi":"10.1002/jmrs.70023","DOIUrl":"10.1002/jmrs.70023","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Neurodivergent conditions such as autism and attention deficit hyperactivity disorder (ADHD) are increasingly recognised in clinical and societal contexts. However, neurodivergent individuals continue to face barriers in accessing healthcare services, including medical imaging. Their complex sensory, communication and emotional needs often go unmet, contributing to reduced rates of completed medical imaging examinations. This systematic review aimed to identify strategies reported in the literature to improve imaging procedure completion among neurodivergent patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A systematic search of medical databases was conducted using relevant keywords related to neurodivergence and medical imaging. After screening titles and abstracts and reviewing full texts, studies that investigated interventions or strategies to support neurodivergent individuals during imaging procedures were included and analysed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The search yielded 1789 peer-reviewed articles. After applying inclusion and exclusion criteria, 40 articles underwent full-text review, with 11 meeting eligibility for inclusion. Thematic analysis identified that both pre-examination and examination strategies are necessary to improve procedure completion. These included preparatory interventions, such as mock imaging sessions, environmental adaptations, involvement of carers and flexibility in imaging techniques and scheduling.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Improving access to imaging for neurodivergent individuals requires adjustments across all phases of the examination. Despite the existence of supportive strategies, no formal guidelines currently exist to assist medical imaging professionals (radiographers, sonographers and nuclear medicine technologists) in delivering accessible, neurodivergent-inclusive imaging care. Further research and guideline development are needed to ensure equitable access for this patient population.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"73 3","pages":"319-326"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13398792/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145085539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Equity of Care for Culturally and Linguistically Diverse Patients: Utilising Multilingual Software to Support Breath-Hold Breast Radiation Therapy","authors":"Toby Lowe,&nbsp;Rory Hartley,&nbsp;John Atyeo,&nbsp;Brooke Griffiths,&nbsp;Brian Porter,&nbsp;Gillian Lamoury,&nbsp;Marita Morgia,&nbsp;Gabrielle Metz,&nbsp;Susan Carroll","doi":"10.1002/jmrs.70095","DOIUrl":"10.1002/jmrs.70095","url":null,"abstract":"<p>Breath-hold techniques, including Deep Inspiration Breath Hold (DIBH) and Exhalation Breath Hold (EBH), are commonly used in radiation therapy to reduce radiation exposure to organs at risk while maintaining accurate tumour targeting. However, high failure rates during breath-hold simulations have been associated with patient anxiety and insufficient preparation—particularly when instruction is given only 20 min prior to the procedure. These challenges are amplified for patients from culturally and linguistically diverse (CALD) backgrounds. To address this, a multilingual mobile application (app) has been developed to improve patient education, communication, and compliance, with a particular focus on supporting CALD patients. Replacing traditional pamphlets with interactive instructional videos, visual aids, and real-time translation in seven languages, the app allows patients to familiarise themselves with breath-hold techniques before their Computed Tomography (CT) simulation. A General Radiation Therapy (RT) section in the app further supports communication between radiation therapists (RTs) and their patients by providing translated commands for standard patient positioning and movement instructions, improving accuracy and workflow efficiency. The app integrates with in-room sound systems, allowing RTs to provide remote coaching while maintaining clear and consistent communication. Additionally, the Frequently Asked Questions (FAQ) section of the app addresses common concerns that patients have about radiation therapy, helping them gain a better understanding with the possibility of reducing anxiety. The app has been implemented at the Northern Sydney Cancer Centre (NSCC) and is expected to improve patient compliance in breath-hold techniques and streamline clinical workflows.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"73 3","pages":"352-358"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13398367/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148218128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Australian Society of Medical Imaging and Radiation Therapy Image Registration in Radiation Therapy Position Paper","authors":"Tamara Barry,&nbsp;Huong Nguyen,&nbsp;Laurel Schmidt,&nbsp;Kate Stewart,&nbsp;Nigel Anderson","doi":"10.1002/jmrs.70071","DOIUrl":"10.1002/jmrs.70071","url":null,"abstract":"<p>The report from the American Association of Physicists in Medicine (AAPM) Task Group 132, published in 2017, established a framework and recommendations for the safe implementation of rigid image registration (RIR) and deformable image registration (DIR) into radiation oncology clinical practice. The Medical Image Registration Special Interest Group (MRSIG) of the Australasian College of Physical Scientists and Engineers in Medicine further built on these recommendations through the publishing of best practice guidelines for DIR warping based on increased accessibility to such tools in the clinical environment. There remains an increasing responsibility on radiation therapists, a critical member of the radiation oncology multidisciplinary team, to safely embed RIR and DIR process into their routine clinical practice, along all steps of the patient's radiation therapy treatment journey. This position paper, authored by the Australian Society of Medical Imaging and Radiation Therapy (ASMIRT) Image Registration Working Party and endorsed by the ASMIRT Executive, (i) details the role of radiation therapists in the application of RIR and DIR in day-to-day clinical practice and (ii) delivers a series of recommendations to support the safe implementation of RIR and DIR into radiation therapist workflows.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"73 3","pages":"345-351"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13398652/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146220180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuing Professional Development – Medical Imaging","authors":"","doi":"10.1002/jmrs.70112","DOIUrl":"10.1002/jmrs.70112","url":null,"abstract":"<p>Maximise your continuing professional development (CPD) by reading the selected article and answering the five questions. Please remember to self-claim your CPD and retain your supporting evidence. Answers will be available via the QR code and published in JMRS – Volume 73, Issue 4, December 2026.</p><p>Scan this QR code or https://www.surveymonkey.com/r/JMRS_Sept2026_MI to find the answers</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"73 3","pages":"375-376"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13398893/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148447528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shaping the Future of Radiography Education: Lessons From ChatGPT and Generative AI","authors":"Minh T. Chau,&nbsp;Haydn Kerr,&nbsp;Clare L. Singh,&nbsp;Bismark Ofori-Manteaw,&nbsp;Elio Arruzza,&nbsp;Kelly Bentley-Spuur","doi":"10.1002/jmrs.70075","DOIUrl":"10.1002/jmrs.70075","url":null,"abstract":"<p>Generative artificial intelligence (AI), particularly large language models such as ChatGPT, is increasingly influencing learning and continuing professional development (CPD) across health professions. The radiography discipline is well positioned to explore the benefits and limitations of these technologies. This article presents a narrative review and conceptual synthesis of emerging evidence on the use of generative artificial intelligence in radiography education. Drawing on emerging radiography-specific studies, the paper synthesises evidence relating to image critique, professional communication training, simulation-based learning, CPD planning and reflective practice. Evidence suggests that ChatGPT can provide structured guidance, support self-assessment and scaffold learning processes that bridge classroom knowledge and clinical expectations. In image evaluation tasks, generative AI may identify broad positioning and exposure issues and prompt metacognitive reasoning when learners are encouraged to critically appraise its outputs. In communication tasks, AI systems can offer structural support but consistently lack the relational nuance essential for safe clinical interactions. In reflective tasks, AI-generated reflections typically lack emotional depth, professional and ethical insight and accountability. Furthermore, custom AI-driven simulations show promise as tools for safe experimentation; however, their outputs commonly default to technically correct responses that provide limited contextual or professional insight. These findings suggest that the value of generative AI lies in how it is pedagogically framed. Rather than advancing algorithmic or performance-based claims, this paper interprets generative AI as a pedagogical artefact whose educational value is contingent on framing, educator oversight and learner critical engagement. The review integrates fragmented evidence with educational theory and professional regulation and proposes a conceptual framework for the responsible integration of generative AI in radiography education. By foregrounding AI literacy, ethical governance and professional accountability, this paper offers an integrative, design-level contribution to support educators and professional bodies navigating the adoption of generative AI across the radiography education continuum.</p>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"73 3","pages":"327-334"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13398642/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147317352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiation Dose Optimisation Through Artificial Intelligence (AI)-based Auto-Thorax Collimation","authors":"Derek (Yoon-Sang) Lee,&nbsp;Nicole Chan,&nbsp;Richard Knight,&nbsp;Christopher Hayre","doi":"10.1002/jmrs.70088","DOIUrl":"10.1002/jmrs.70088","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Artificial intelligence (AI) is increasingly adopted in digital radiography to enhance workflow efficiency, standardisation and support for radiation dose optimisation. Auto-thorax collimation (ATC) has been introduced to automate field size selection in chest X-ray (CXR) imaging; however, its clinical performance and impact on collimation consistency in routine chest X-ray practice require further evaluation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A single-centre retrospective study analysed 400 posteroanterior (PA) erect CXRs sourced from the Picture Archiving and Communication System (PACS) and local image archives. Collimation size was measured in both the superior–inferior and lateral dimensions. An additional, 200 erect CXRs were collected to assess the repeat rate due to collimation errors. Statistical analysis was performed using two-sample <i>t</i>-tests for collimation measurements and a two-proportion <i>Z</i>-test for repeat rates. The coefficient of variation (CV) was calculated to quantify the variability in collimation field size for each operator across both ATC and manual collimation methods.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>ATC demonstrated tighter inferior and left lateral collimation than manual collimation (<i>p</i> &lt; 0.05), while manual collimation showed tighter superior collimation. Collimation consistency was greater with ATC, as evidenced by lower CV values across operators. Repeat rates were comparable between ATC (7%) and manual collimation (8%).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>AI-based collimation provides collimation results similar to manual performance, with improved standardisation and reproducibility. Its consistent output suggests potential benefits in high-turnover environments, enhancing workflow efficiency whilst optimising radiation safety.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"73 3","pages":"300-308"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13399012/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147529982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of 1024-Matrix Size on Perforating Artery Visualisation in Cerebral Computed Tomography Angiography Using a 64-Slice CT Scanner","authors":"Hokuto Nagumo,&nbsp;Yuki Nagata,&nbsp;Mayumi Maruko,&nbsp;Jun Sakai,&nbsp;Yusuke Fujiwara,&nbsp;Joma Oikawa","doi":"10.1002/jmrs.70055","DOIUrl":"10.1002/jmrs.70055","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Computed tomography angiography (CTA) is essential for preoperative evaluation of intracranial vessels; however, the visualisation of small perforating arteries remains challenging with conventional systems. This study investigated whether increasing the reconstruction matrix size from 512 to 1024 pixels improves the visualisation of perforating arteries in cerebral CTA using a standard 64-slice computed tomography (CT) scanner.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The study comprised phantom and clinical components. Physical image properties were assessed through Task Transfer Function (TTF) and Noise Power Spectrum (NPS) analyses. In the clinical phase, 41 patients underwent cerebral CTA with both 512- and 1024-matrix reconstructions. Quantitative analysis was performed to determine the peak CT values of the anterior choroidal artery and standard deviation in the basal cistern. Two independent observers (CT radiographers) evaluated the visualisation of anterior choroidal and posterior thalamoperforating arteries using a 5-point scale.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Physical metrics showed minimal differences between matrix sizes, with 5% TTF values of 0.862 and 0.867 cycles/mm for 512 and 1024 pixels, respectively. The anterior choroidal artery exhibited higher peak CT values with 1024 pixels (139.31 ± 27.02 HU vs. 136.85 ± 26.69 HU, <i>p</i> &lt; 0.001). The qualitative assessment revealed significant improvements in vessel visualisation with 1024 pixels, particularly for the posterior thalamoperforating artery, where high-quality visualisation increased from 17.07% to 39.03%.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Although increasing the matrix size from 512 to 1024 pixels did not significantly affect the physical image quality metrics, it enhanced the visual detection of small perforating arteries through enhanced sampling density. This optimization technique offers a practical approach for enhancing preoperative vessel evaluation using existing CT technology without requiring specialised equipment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16382,"journal":{"name":"Journal of Medical Radiation Sciences","volume":"73 3","pages":"263-269"},"PeriodicalIF":2.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13398869/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147473898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}