Journal of Medical Imaging and Radiation Sciences最新文献

{"title":"Retraction notice to “Insights into enhanced learning through virtual reality” [Journal of Medical Imaging and Radiation Sciences 55 (2024) 101767]","authors":"Olena Petrovna Ivanova, Pavlo Shevchenko, Kateryna Ivanovna Petrenko","doi":"10.1016/j.jmir.2025.102125","DOIUrl":"10.1016/j.jmir.2025.102125","url":null,"abstract":"","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"57 1","pages":"Article 102125"},"PeriodicalIF":2.0,"publicationDate":"2025-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145472568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A step towards global understanding of advanced practice radiation therapist clinical activities: International Delphi consensus","authors":"Kitty Chan ,&nbsp;Nicole Harnett ,&nbsp;Yat Tsang","doi":"10.1016/j.jmir.2025.102138","DOIUrl":"10.1016/j.jmir.2025.102138","url":null,"abstract":"<div><h3>Background</h3><div>Advanced practice radiation therapist (APRT) roles have expanded internationally to address cancer workforce shortages and improve service delivery. A Canadian consensus process previously established 20 standardized APRT clinical activities across five themes. This study evaluated the international applicability of these activities through expert consensus to establish a global framework for APRT practice.</div></div><div><h3>Methods and materials</h3><div>A systematic three-round international Delphi consensus study was conducted following established quality framework recommendations. Expert panel members were recruited from an international Community of Practice using objective selection criteria ensuring recognized APRT expertise and diverse geographical representation. Participant anonymity was maintained throughout all rounds. Controlled feedback provided quantitative results and anonymized qualitative comments between rounds. Consensus threshold was defined <em>a priori</em> at 80% agreement, and activities were evaluated for inclusion in international APRT scope of practice across five themes: patient interactions, multidisciplinary consultation, virtual consultation, resource optimization, and technical activities.</div></div><div><h3>Results</h3><div>Twenty-three international experts were invited to take part in the study with response rates of 81% (Round 1), 89% (Round 2), and 89% (Round 3). Twenty clinical activities were systematically evaluated. Five activities achieved immediate Round 1 consensus: Planning Consultation (83%), Multidisciplinary Pre-treatment Consultation (83%), Care Coordination (96%), Patient Navigation (87%), and Technical Consultation (87%). Following iterative three-round evaluation, 16 of 20 activities (80%) achieved final international consensus for APRT practice inclusion. Four activities failed to reach consensus: Patient Education/Informed Consent (75%), Follow-up Consultation (78%), Clinical Examination (78%), and MR Applicator Assessment (65%). The validated framework demonstrates substantial global alignment while identifying specific jurisdictional variations in advanced practice acceptance.</div></div><div><h3>Conclusions</h3><div>This study establishes international consensus on core APRT clinical activities, providing evidence-based foundations for standardized global APRT role development and implementation. These findings support healthcare systems in addressing workforce challenges through validated advanced practice frameworks while maintaining quality cancer care delivery.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"57 1","pages":"Article 102138"},"PeriodicalIF":2.0,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145461063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative evaluation of an artificial intelligence-assisted platform in CT acquisition workflow","authors":"Marco Caballo ,&nbsp;Laura McLennan ,&nbsp;Matthew Benbow ,&nbsp;Mark Condron ,&nbsp;Andrea Foden ,&nbsp;Sue Thomas ,&nbsp;Russell Bull","doi":"10.1016/j.jmir.2025.102133","DOIUrl":"10.1016/j.jmir.2025.102133","url":null,"abstract":"<div><h3>Background</h3><div>Artificial intelligence (AI) may help reduce the examination time and simplify the scanning process during CT image acquisition. This cross-sectional study aims to quantitatively and objectively assess the potential benefits of an AI-assisted CT acquisition platform in streamlining CT acquisition workflow, by reducing time and user interactions, compared to a non-AI-assisted platform.</div></div><div><h3>Methods</h3><div>Twelve certified diagnostic radiographers scanned an anthropomorphic body phantom for four different protocols on two similar CT systems, one equipped with an AI-assisted scanning platform and one without. Scanning sessions were video-recorded, and two primary variables (total examination time and number of user interactions with the platforms) were extracted. Differences in variable outcomes between the two platforms were analyzed statistically with the Mann-Whitney <em>U test</em> (with Bonferroni correction). The influence of radiographers’ experience on each variable outcome was quantified with Spearman correlation, and inter-reader agreement among the radiographers with the intra-class correlation coefficient (ICC).</div></div><div><h3>Results</h3><div>Acquisition time and number of interactions were both significantly lower on the AI-assisted platform (<em>P</em> &lt; 0.001). The average (±standard deviation) reduction in acquisition time was between 40.2 % (±9.8 %) and 52.8 % (±10.9 %), depending on the protocol. The average (±standard deviation) reduction in interactions was between 35.6 % (±9.7 %) and 45.1 % (±14.0 %), depending on the protocol. No significant correlation was found between radiographer experience and acquisition time or number of interactions for either platform (<em>P</em> ≥ 0.3). Inter-reader agreement was substantial on both platforms (acquisition time: ICC = 0.82 and ICC = 0.85 respectively for the AI-assisted and non-AI-assisted platform; interactions: ICC = 0.76 and ICC = 0.81 respectively for the AI-assisted and non-AI-assisted platform).</div></div><div><h3>Discussion</h3><div>AI-assisted CT acquisition platforms may improve CT acquisition workflow, pending further confirmation in future multicenter studies and with large datasets of patient data.</div></div><div><h3>Conclusion</h3><div>A reduction in time and interactions required to perform CT image acquisition may have real-world pragmatic implications in reducing radiographer workload and improving departmental throughput.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"57 1","pages":"Article 102133"},"PeriodicalIF":2.0,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145428679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experience matters, but support is essential: Managing claustrophobic patients in MRI practice","authors":"Mohamed Zakaria El-Sayed ,&nbsp;Mohammad Rawashdeh ,&nbsp;Husna. N ,&nbsp;Nasiha. N ,&nbsp;Nidha. S ,&nbsp;Shima Ibrahim Ali ,&nbsp;Magdi. A Ali","doi":"10.1016/j.jmir.2025.102132","DOIUrl":"10.1016/j.jmir.2025.102132","url":null,"abstract":"<div><h3>Introduction</h3><div>Magnetic Resonance Imaging (MRI) is a valuable diagnostic tool, but its enclosed environment can provoke claustrophobia in patients, often leading to incomplete scans and delayed diagnoses. Radiographers play a pivotal role in managing these cases, yet limited research has explored how their experience and the support they receive influence management strategies. This study aimed to assess radiographers' practices, perceived barriers, and the impact of professional experience and support structures in managing claustrophobic patients during MRI procedures in the UAE.</div></div><div><h3>Methods</h3><div>A cross-sectional, internet-based survey was conducted among licensed radiographers across the UAE using a validated, pre-tested 23-item questionnaire. Convenience and snowball sampling were applied, with data collected via Google Forms and analyzed using SPSS v20. Chi-square and Monte Carlo tests assessed associations between years of experience and reported practices or barriers and access to professional or institutional support.</div></div><div><h3>Results</h3><div>Out of 106 respondents, 53.8 % frequently encountered claustrophobic patients, and 39.6 % reported rescheduling scans. Experienced radiographers more often used techniques like scanner previews (X² = 18.929*, <em>p</em> = 0.015), comfort measures (X² = 22.265*, <em>p</em> = 0.012), and relaxation techniques (X² = 23.719*, <em>p</em> = 0.007). Significant barriers included lack of training (X² = 25.370*, <em>p</em> = 0.002), time constraints (X² = 16.508*, <em>p</em> = 0.030), and inadequate equipment (X² = 21.496*, <em>p</em> = 0.003). While newer radiographers highlighted training needs, experienced staff emphasized institutional limitations, reinforcing that both expertise and structured support are critical for effective patient management.</div></div><div><h3>Conclusion</h3><div>Radiographers' experience significantly influences how claustrophobic patients are managed. However, experience alone is insufficient without appropriate support systems that enable radiographers to apply their skills effectively and consistently. Despite individual efforts, systemic barriers persist.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"57 1","pages":"Article 102132"},"PeriodicalIF":2.0,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145428680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in medical imaging: Utilization, challenges, and practitioner perceptions in Rwanda","authors":"Marie Mukandayisenga,&nbsp;Joseph Tabaro,&nbsp;Bornface Chinene,&nbsp;Afodun Adam,&nbsp;Mukangendo Mecthilde,&nbsp;Fils Turatsinze,&nbsp;Emmanuel A. Odumeru","doi":"10.1016/j.jmir.2025.102127","DOIUrl":"10.1016/j.jmir.2025.102127","url":null,"abstract":"<div><h3>Introduction</h3><div>Artificial intelligence (AI) holds transformative potential for medical imaging in low-resource settings like Rwanda, where shortages of imaging professionals contribute to diagnostic delays. While global research has examined AI adoption in high-income countries, limited evidence exists for sub-Saharan Africa. This study aimed to assess AI utilization patterns, implementation challenges, and practitioner perceptions across Rwanda's healthcare system, providing critical insights for optimizing AI integration in resource-constrained environments.</div></div><div><h3>Methods</h3><div>A cross-sectional study was conducted from December 2024 to April 2025, surveying 107 medical imaging practitioners (74 % response rate) across teaching, provincial, and district hospitals. Using a validated questionnaire, data were collected on AI utilization, implementation barriers, and practitioner attitudes. Descriptive statistics and chi-square tests analyzed patterns and associations.</div></div><div><h3>Results</h3><div>Automated measurements were the most widely used AI application (69.2 % of practitioners), while segmentation AI was the least adopted (7.7 %). Utilization disparities were stark: 71.0 % of teaching hospitals used AI versus 13.1 % of district hospitals. Key barriers included high costs (27.1 % of respondents), system integration challenges (26.2 %), and training deficiencies (44.2 % across all professional ranks, <em>p</em> &gt; 0.05). Despite these challenges, 86 % of practitioners viewed AI positively, with 37.4 % strongly agreeing it improves diagnostic accuracy.</div></div><div><h3>Conclusion</h3><div>Rwanda's AI adoption in medical imaging shows promise but remains uneven, with teaching hospitals leading implementation. Systemic barriers, particularly costs, infrastructure limitations, and training gaps, must be addressed to ensure equitable expansion. The overwhelmingly positive practitioner attitudes indicate readiness for AI integration, suggesting Rwanda is poised for growth with targeted policy interventions. These findings provide a foundation for optimizing AI implementation in low-resource settings across sub-Saharan Africa. Future research should explore cost-effective scaling strategies and long-term impacts on diagnostic outcomes.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"57 1","pages":"Article 102127"},"PeriodicalIF":2.0,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145428678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the utility of different radiographic imaging modalities for assessing intussusception, Crohn's Disease and adenocarcinoma to the small bowel: A systematic review","authors":"Caitlin Cassimatis,&nbsp;Peter O'Reilly,&nbsp;Amir Tavakoli Taba","doi":"10.1016/j.jmir.2025.102126","DOIUrl":"10.1016/j.jmir.2025.102126","url":null,"abstract":"<div><h3>Introduction</h3><div>Radiography is a crucial alternative in diagnosing small bowel pathologies due to the challenges of endoscopy. This review evaluates intussusception, Crohn’s Disease, and small bowel adenocarcinoma to compare modalities across age groups and provide optimal imaging recommendations.</div></div><div><h3>Methods</h3><div>A systematic search was performed in Embase, Medline, Scopus and Web of Science following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The review included studies from the past five years comparing modalities for the diagnosis of intussusception, Crohn’s Disease, or small bowel adenocarcinoma. The Critical Appraisal Skills Programme tool was used for quality assessment. Data extraction was completed using a standardised template, and a thematic approach for narrative synthesis was performed.</div></div><div><h3>Results</h3><div>Thirty-five studies were included, highlighting a higher diagnostic accuracy of ultrasound over radiography in pediatric intussusception. In adults, computed tomography (CT) was the only viable imaging modality, and adenocarcinoma was the most common malignant underlying cause of obstruction. Literature on adenocarcinoma was limited, with no analysis beyond standard cross-sectional modalities. In Crohn’s Disease, magnetic resonance imaging (MRI) was considered advantageous for young people. CT techniques were emerging in terms of prominence for the monitoring of Crohn’s Disease activity.</div></div><div><h3>Conclusion</h3><div>Ultrasound is recommended for pediatric intussusception diagnosis, with radiographs favoured for predicting surgical outcomes. For Crohn’s Disease, the optimal use of CT and MRI depends upon the phase of disease at the time of imaging. Given the late diagnosis of small bowel adenocarcinoma, further research into an optimised diagnostic pathway is necessary. Novel small bowel imaging techniques emerging in ultrasound, CT and MRI demonstrate potential diagnostic benefits for clinical use due to increased ability to differentiate between pathologies and reduced radiation doses.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 6","pages":"Article 102126"},"PeriodicalIF":2.0,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145403435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Occupational radiation exposure in nuclear medicine technologists: A scoping review","authors":"Alyssa Payne ,&nbsp;Christopher Skilton ,&nbsp;Daphne James","doi":"10.1016/j.jmir.2025.102123","DOIUrl":"10.1016/j.jmir.2025.102123","url":null,"abstract":"<div><h3>Introduction/Background</h3><div>The ionising radiation exposure received by Nuclear Medicine Technologists (NMTs) is estimated to be greater than that of most other medical imaging professions. Despite the relatively low exposures considered to be received by medical imaging professionals as a whole, delayed health issues associated with potential stochastic effects from ionising radiation raise concerns. Aspects such as evolving theranostic practices, increased Positron Emission Tomography (PET) procedures, and workforce shortages contribute to heightened workloads of NMTs, thus exacerbating potential exposure risks. This scoping review intends to explore the occupational radiation exposure of NMTs, since the year 2000.</div></div><div><h3>Methods</h3><div>A scoping review of the relevant literature was conducted. Four databases were searched, consisting of Medline, Embase CINAHL, and Scopus. The retrieved relevant articles were screened for inclusion in Covidence. Study selection, data charting and the data extraction was performed by two independent reviewers. Ethics approval was not required for this study.</div></div><div><h3>Results</h3><div>Dose report data from 21 studies worldwide were analysed. Reported annual effective doses ranged from 0.06 mSv to 13.9 mSv. Procedures performed between sites consisted of general nuclear medicine, radionuclide therapy, and PET. Types of dosimeters used included Thermoluminescent Dosimeters (TLDs), Film Badges, Electronic Dosimeters (EDs), Radio-photoluminescence Dosimeters, and Optically Stimulated Luminescence Dosimeters (OSLs). Potential correlations have emerged between procedure types, dosimeters used, and the occupational radiation exposures reported.</div></div><div><h3>Discussion</h3><div>A potential link between a broader variety of procedures performed and increased dose was found, particularly implicating PET procedures. Certain dosimeters show more promise than others for enhanced sensitivity, especially in environments conducting high-energy procedures.</div></div><div><h3>Conclusion</h3><div>Despite heterogeneity between studies in dose reporting methods, all reported doses were within annual recommended limits. This scoping review provides a foundation for future research, aiming to refine methodologies and address challenges in the understanding of occupational radiation exposure in NMTs.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 6","pages":"Article 102123"},"PeriodicalIF":2.0,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145395866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Painting courage: The art of mask making","authors":"Gerry Ash","doi":"10.1016/j.jmir.2025.102121","DOIUrl":"10.1016/j.jmir.2025.102121","url":null,"abstract":"","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 6","pages":"Article 102121"},"PeriodicalIF":2.0,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145395991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geographic prompting and content fidelity in generative Artificial Intelligence: A multi-model study of demographics and imaging equipment in AI-generated videos and images of Canadian medical radiation technologists","authors":"Yousif Al-Naser ,&nbsp;Sonali Sharma ,&nbsp;Ken Niure ,&nbsp;Kevin Ibach ,&nbsp;Faisal Khosa ,&nbsp;Charlotte J. Yong-Hing","doi":"10.1016/j.jmir.2025.102122","DOIUrl":"10.1016/j.jmir.2025.102122","url":null,"abstract":"<div><h3>Background</h3><div>As generative AI tools increasingly produce medical imagery and videos for education, marketing, and communication, concerns have arisen about the accuracy and equity of these representations. Existing research has identified demographic biases in AI-generated depictions of healthcare professionals, but little is known about their portrayal of Medical Radiation Technologists (MRTs), particularly in the Canadian context.</div></div><div><h3>Methods</h3><div>This study evaluated 690 AI-generated outputs (600 images and 90 videos) created by eight leading text-to-image and text-to-video models using the prompt ``Image [or video] of a Canadian Medical Radiation Technologist.'' Each image and video was assessed for demographic characteristics (gender, race/ethnicity, age, religious representation, visible disabilities), and the presence and accuracy of imaging equipment. These were compared to real-world demographic data on Canadian MRTs (n = 20,755).</div></div><div><h3>Results</h3><div>Significant demographic discrepancies were observed between AI-generated content and real-world data. AI depictions included a higher proportion of visible minorities (as defined by Statistics Canada) (39% vs. 20.8%, <em>p</em> &lt; 0.001) and males (41.4% vs. 21.2%, <em>p</em> &lt; 0.001), while underrepresenting women (58.5% vs. 78.8%, <em>p</em> &lt; 0.001). Age representation skewed younger than actual workforce demographics (<em>p</em> &lt; 0.001). Equipment representation was inconsistent, with 66% of outputs showing CT/MRI and only 4.3% showing X-rays; 26% included inaccurate or fictional equipment.</div></div><div><h3>Conclusion</h3><div>Generative AI models frequently produce demographically and contextually inaccurate depictions of MRTs, misrepresenting workforce diversity and clinical tools. These inconsistencies pose risks for educational accuracy, public perception, and equity in professional representation. Improved model training and prompt sensitivity are needed to ensure reliable and inclusive AI-generated medical content.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 6","pages":"Article 102122"},"PeriodicalIF":2.0,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145331473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating a virtual simulation chatbot to improve communication for radiation therapy students: A pilot study","authors":"Nur Anis Izzati Che Mut ,&nbsp;Nor Aniza Azmi ,&nbsp;Nur Afiqah Mohd Sukri ,&nbsp;Muhamad Ikhwan Mustafa Kamal ,&nbsp;Rozilawati Ahmad ,&nbsp;Noorazrul Azmie Yahya ,&nbsp;Muhammad Safwan Ahmad Fadzil ,&nbsp;Noraini Ahmad Wahid ,&nbsp;Saiful Izzuan Hussin ,&nbsp;Liyana Shuib","doi":"10.1016/j.jmir.2025.102124","DOIUrl":"10.1016/j.jmir.2025.102124","url":null,"abstract":"<div><div>Effective communication is vital in radiotherapy to ensure patient understanding and cooperation. However, a conventional approach is often inadequate due to misunderstanding and limited retention of information. Additionally, students often have limited opportunities to develop these skills in clinical environments. SCIMORT, an immersive virtual simulation chatbot was designed to address this gap by providing realistic communication training. A pilot study was conducted to develop the SCIMORT and evaluate the user’s acceptance and engagement. In Phase 1, a 3D virtual patient chatbot integrated with voice and visual cues was developed using Blender and Bot Libre. In Phase 2, evaluation of the prototype using a survey among 28 students was conducted. Both novice and experienced groups reported high acceptance (Novice group: 3.919 ± 1.245, Experience group: 3.953 ± 1.114) and engagement scores (Novice: 3.526 ± 1.270, Experienced: 3.568 ± 1.142). Both groups agreed that SCIMORT provides an overview of the clinical environment, with the slightly higher mean score recorded in the experience group (4.13 ± 1.356) compared to the novice group (4.00 ± 1.080). Besides, both groups agreed that the tool is acceptable for communication skill training. No significant differences were observed between groups in acceptance (<em>U</em> = 97.000, <em>p</em> = 0.981) or engagement (<em>U</em> = 71.500, <em>p</em> = 0.204). Students highlighted SCIMORT’s realistic clinical environment and usability, though some reported cognitive load and challenges with immersion. SCIMORT demonstrated promising potential as an accessible communication skills training tool for radiotherapy students. While generally accepted and engaging, future development should enhance interactivity, personalize feedback, and integrate immersive VR features to improve realism and learning outcomes.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 6","pages":"Article 102124"},"PeriodicalIF":2.0,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145331509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}