Journal of Medical Imaging and Radiation Sciences最新文献

{"title":"Evaluating ‘Pair’: A Generative AI Chatbot for Standardizing Radiographic Protocols","authors":"Tan Eugene, Crystal Chin Jing, Celine Tan Ying Yi","doi":"10.1016/j.jmir.2025.102053","DOIUrl":"10.1016/j.jmir.2025.102053","url":null,"abstract":"<div><h3>Aim</h3><div>The “Pair” chatbot, introduced as a government AI assistant, marks a significant step forward in leveraging large language models (LLMs) in healthcare. This innovation has driven the exploration of generative AI (GenAI) to tackle challenges in radiography, such as fragmented information-sharing and an over-reliance on senior radiographers for clarifications. Discrepancies in protocol interpretation among senior radiographers further hinder the standardization of imaging procedures.</div><div>To address these challenges, the ““Pair”” chatbot is being piloted as a potential solution. However, deploying GenAI in high-stakes fields like radiography involves risks, as inaccurate guidance could jeopardize patient safety. Many GenAI models generate plausible yet potentially incorrect answers, underscoring the importance of rigorous validation and evaluation before clinical implementation.</div><div>This study seeks to rigorously evaluate the chatbot's performance in terms of accuracy, appropriateness, and consistency by analyzing its responses across various radiographic scenarios. The evaluation involves comparing its outputs to established expert consensus and assessing consistency across different query formulations. The ultimate goal is to ensure the chatbot delivers accurate, relevant, and contextually appropriate responses that align with clinical standards.</div></div><div><h3>Methods</h3><div>A dataset of 100 clinical questions, covering image acquisition, patient positioning, and protocol adherence, was developed to represent real-world radiographic scenarios. The chatbot’s performance was evaluated using three key metrics: accuracy, appropriateness, and semantic consistency. Accuracy was measured using the F1 score, which balances precision and recall. Appropriateness was assessed through the Intraclass Correlation Coefficient (ICC) and Fleiss' Kappa, evaluating consistency and inter-rater reliability. Semantic consistency examined the chatbot’s ability to provide consistent answers across rephrased questions, ensuring its adaptability to various question formulations in clinical practice.</div></div><div><h3>Results</h3><div>The chatbot's performance reflects a substantial level of accuracy, with an F1 score of 0.7013, although recall could be further optimized to address all aspects of the queries. The Intraclass Correlation Coefficient (ICC) of 0.5075 indicates moderate inter-rater reliability, while Fleiss' Kappa of 0.2424 suggests fair agreement among raters, highlighting the challenges in defining universal standards for radiographic practice. Notably, the chatbot demonstrated high semantic consistency, achieving 90.37%, which underscores its ability to provide consistent responses despite variations in question phrasing.</div></div><div><h3>Conclusion</h3><div>The evaluation of the chatbot’s performance reveals both strengths and areas for improvement. It demonstrated strong consistency, with a semantic consistency","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 2","pages":"Article 102053"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722662","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":"CALM (Catch And Light-up Marker)","authors":"Gu Qinglong","doi":"10.1016/j.jmir.2025.102048","DOIUrl":"10.1016/j.jmir.2025.102048","url":null,"abstract":"<div><h3>Aim</h3><div>This study aims to assist radiographers in accurately placing anatomical markers during radiographic procedures by leveraging computer vision and AI technologies. The system seeks to reduce human error and enhance workflow efficiency, which is essential for ensuring precise diagnosis and treatment.</div></div><div><h3>Methods</h3><div>CALM integrates AI-driven models with automated monitoring tools, including scanners and cameras, to capture data from laboratory instruments and visual observations. It uses real-time screen monitoring via an HDMI splitter to detect X-ray orders, extract “R” or “L”, and display the corresponding marker on an LED screen next to the X-ray machine.</div></div><div><h3>Results</h3><div>In the initial 10 tests, when X-ray orders were captured from the screen, CALM successfully identified the right and left sides and correctly displayed “R” or “L” on the LED screen with 100% accuracy. However, when the orders were captured from paper forms, the accuracy dropped to 90%, likely due to OCR limitations in extracting the correct side information from the printed text.</div></div><div><h3>Conclusion</h3><div>In conclusion, CALM has proven to be useful in accurately identifying and displaying the correct side (right or left) in X-ray orders captured from the screen, achieving 100% accuracy. However, this study is limited to orders that specifically contain the words “right” and “left.” For orders with other terminology, different approaches will need to be further investigated and developed to ensure consistent and accurate marker placement.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 2","pages":"Article 102048"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722656","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":"Message from the Editor","authors":"Amanda Bolderston EdD, MSc, MRT(T), FCAMRT","doi":"10.1016/j.jmir.2025.102002","DOIUrl":"10.1016/j.jmir.2025.102002","url":null,"abstract":"","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 4","pages":"Article 102002"},"PeriodicalIF":1.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672030","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":"Clarity in Career Choices: Examining Radiographers' Experiences with Pre-specialisation Modality Observation","authors":"Celine Tan Ying Yi,&nbsp;Rafidah Bte Abu Bakar","doi":"10.1016/j.jmir.2025.102059","DOIUrl":"10.1016/j.jmir.2025.102059","url":null,"abstract":"<div><h3>Aim</h3><div>Pre-specialisation modality observation, conducted before radiographers choose their specialisation after attaining full registration with the Allied Health Professions Council (AHPC), can play a crucial role in career decision-making processes. However, different modalities conduct the observation differently, potentially compromising the efficacy of these learning opportunities. This study aimed to retrospectively investigate radiographers' perceptions of pre-specialisation modality observation, the effectiveness of these observations in informing their choices, and provide recommendations for improvement.</div></div><div><h3>Methods</h3><div>A mixed-method study surveyed radiographers from diverse specialities who undertook pre-specialisation modality observations between 2022-2024, after achieving full AHPC registration but before selecting their specialisation. The survey used a 5-point Likert scale (1=strongly disagree, 5=strongly agree) to evaluate consistency, usefulness, and adequacy of observations. Open-ended questions captured qualitative insights on experiences and suggestions for improvement.</div></div><div><h3>Results</h3><div>Nineteen radiographers participated in the survey. 63.2% had less than 2 years of experience in their chosen speciality, while 36.8% were awaiting specialisation. Among the participants (n=12) who observed more than one modality, 66.66% found the experience to be uniform across specialisations, with 33.33% perceiving a moderate level of variation in their observation experiences. All radiographers felt the observation was useful. However, only 36.8% felt the observations had provided adequate information for their decision-making. Key inconsistencies identified were duration of observation, activities involved, staff interaction, and information provided. The most valuable elements observed included observing procedures, discussions with staff, understanding workflow, and understanding career progression. 47.4% of participants favoured standardisation for future observations, while 31.6% disagree and 21% remains neutral. 52.6% reported feeling confident in their decision to specialise in their chosen modality after completing the observation.</div></div><div><h3>Conclusion</h3><div>Pre-specialisation modality observations are perceived as useful there is significant potential to enhance their effectiveness in supporting radiographers' career decisions. While there is a desire for more consistency, a one-size-fits-all approach may not be ideal. A balanced approach offering flexibility while ensuring core elements included across all specialities might be most beneficial. Addressing the identified inconsistencies and incorporating the most valued elements could lead to better-informed specialisation choices, potentially improve long-term career satisfaction among radiographers</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 2","pages":"Article 102059"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722559","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":"Designing an AI-Driven Chatbot to Address Radiographers’ Needs: A Mixed-Methods Approach","authors":"Crystal Chin Jing","doi":"10.1016/j.jmir.2025.102054","DOIUrl":"10.1016/j.jmir.2025.102054","url":null,"abstract":"<div><h3>Aim</h3><div>Generative AI is revolutionizing industries by streamlining workflows and facilitating informed decision-making. However, existing AI-driven chatbots often target general audiences, offering broad functionalities that do not address the specific needs of niche professions. In healthcare, AI has demonstrated promise in automating tasks and improving knowledge retrieval, yet its application in radiography remains underexplored. Radiographers face unique challenges, including accessing updated imaging protocols, navigating diverse workflows, and making rapid decisions under time constraints. This study aims to bridge these gaps by assessing radiographers’ challenges and exploring their expectations of AI-driven chatbots to inform the development of a tailored solution that enhances efficiency and decision-making.</div></div><div><h3>Methods</h3><div>An explanatory sequential design was employed, beginning with a survey of radiographers (n=39) to identify key challenges and expectations. Quantitative data were analysed using descriptive and inferential statistics. Subsequently, focus group discussions (FGDs) were conducted with purposively sampled participants (n=9), and transcribed through verbatim, and thematic analysis was conducted to gain deeper insights into radiographers’ experiences, perceptions, and expectations.</div></div><div><h3>Results</h3><div>Survey findings revealed that 87.2% of radiographers struggled with accessing updated imaging protocols, while 59% faced difficulties navigating workflows across different environments. Participants strongly prioritized quick access to imaging protocols (87.2%) and tailored workflow guidance (84.6%). Concerns about chatbot accuracy (87.2%) and ease of use (43.6%) were also prominent.</div><div>Thematic analysis revealed that fragmented resources and rotational roles were key factors underlying these challenges. Participants expressed a need for AI-driven chatbots to provide quick and reliable decision support, prioritizing features like rapid access to imaging protocols and workflow guidance. Chatbots were seen as a promising solution to standardize practices, reduce reliance on colleagues, and enhance efficiency. Critical factors influencing adoption included trust in the chatbot’s accuracy, evidence-based recommendations, concise responses, and mobile accessibility, enabling seamless integration across diverse clinical settings.</div></div><div><h3>Conclusion</h3><div>This study identifies radiographers’ operational challenges and provides actionable insights into their expectations for an AI-driven chatbot. A tailored solution that centralizes updated protocols, enhances decision-making, and supports workflow navigation can improve efficiency and reduce stress among radiographers. Future work will focus on integrating these findings into chatbot design and evaluating its impact on clinical workflows and patient care outcomes.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 2","pages":"Article 102054"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722663","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":"Patient Perception of Care","authors":"Ameerah Syahirah Binte Abdul Khalil,&nbsp;Koh Kai Xuan Regina","doi":"10.1016/j.jmir.2025.102061","DOIUrl":"10.1016/j.jmir.2025.102061","url":null,"abstract":"<div><h3>Aim</h3><div>Singapore’s healthcare system faces challenges from aging demographics and cultural diversity, with 1 in 4 Singaporeans expected to be aged 65+ by 2030. Cultural beliefs influence trust, decision-making, and treatment adherence, shaping patient expectations. This study explores how cultural and generational factors impact outpatient experiences, comparing Asian and Western perspectives.</div></div><div><h3>Methods</h3><div>A mixed-methods approach was used, combining qualitative and quantitative data. An online survey, distributed from July 2024 to January 2025, gathered responses from 160 participants (80 Singaporeans and 80 from Australia, the UK, and New Zealand), aged 20–80, who had recent outpatient treatment. Purposive sampling ensured cultural diversity. The survey, adapted from established tools like the Picker Patient Experience Questionnaire (PPE-15), assessed patient expectations, healthcare professional qualities, and cultural influences. Data analysis included descriptive statistics and thematic coding.</div></div><div><h3>Results</h3><div>Of 96 responses, 66 were valid. Western participants exhibited higher trust in doctors but included a subset with total distrust, while Asian participants sought greater involvement in decision-making. Older patients showed the highest confidence in doctors. Privacy and comfort were key concerns, with younger patients emphasizing personal space. Many felt healthcare resources did not significantly improve treatment. Cultural beliefs influenced psychological well-being, with younger and middle-aged groups reporting stronger impacts, while seniors viewed cultural preferences as comforting. Asian participants emphasized psychosocial well-being, whereas Western participants prioritized individual autonomy.</div></div><div><h3>Conclusion</h3><div>The findings highlight the need for culturally responsive strategies, particularly in patient engagement and environmental design. Effective communication and quality healthcare environments are crucial for patient satisfaction. Future research should explore broader structural influences to provide culturally sensitive care and address barriers to health-seeking behaviors in Singapore’s multicultural society.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 2","pages":"Article 102061"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722561","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":"Review on early-stage laryngeal cancer soft tissue imaging protocol","authors":"Heather Tan Jiahui,&nbsp;Sin Sze Yarn","doi":"10.1016/j.jmir.2025.102051","DOIUrl":"10.1016/j.jmir.2025.102051","url":null,"abstract":"<div><h3>Aim</h3><div>Historically, early-stage laryngeal cancer has been treated with lateral opposing fields, centred at thyroid cartilage, with a field size of approximately 6 × 6cm. Since 2017, our centre has adopted the volumetric modulated arc therapy (VMAT) technique, followed by daily cone beam computed tomography (CBCT) for soft tissue matching while adhering to departmental protocol of 0.3cm spinal cord tolerance. Precision of target volume irradiation is crucial to avoid compromising tumour control and overdosing adjacent healthy organs. Due to the concerns about geographical misses from laryngeal motion from swallowing and breathing, we aim to review the critical steps in soft tissue matching for early-stage laryngeal cancer radiotherapy and update our current imaging protocol.</div></div><div><h3>Methods</h3><div>Fifty-three patients treated with VMAT and daily CBCT imaging were audited. CBCT images of patient re-setups were reviewed and matched manually on MOSIAQ. Bone-based registration covered C3-6 vertebrae while soft tissue-based registration focused on planning target volume (PTV) and thyroid cartilage. Magnitude of shifts (x-, y-, z-directions) were recorded and the variances were calculated. Further observations on the onset and number of re-setups were made.</div></div><div><h3>Results</h3><div>Thirty-seven out of the 53 patients required re-setups, with the highest being 18 re-setups for a particular patient. A total of 205 repeated CBCTs were analyzed and it was observed that 82% of the re-setups was due to the z-direction [0.64mm ± 0.32 (0.00 - 2.00)], followed by y-direction [0.16mm ± 0.14 (0.00 - 1.00)] and x-direction [0.09mm ± 0.09 (0.00 - 0.40)]. The larger variance in the longitudinal direction is due to the swallowing motion. Majority of re-setups occurred during week 1 and from week 3 onwards. This could be due to patients’ uneasiness or difficulty following instructions at the start of radiotherapy course. Gradual laryngeal shifts contributing to setup errors over the course of radiotherapy are common, often from laryngeal oedema or weight loss.</div></div><div><h3>Conclusion</h3><div>CBCT has enabled precise soft tissue anatomical-based matching, especially for early-stage laryngeal cancer, because inferior dosimetry has been shown to compromise survival in head and neck cancer patients. Initially, a conservative approach limiting spinal cord variance from target to 0.3cm was to ensure minimal dosimetric impact on spinal cord dose. However, considering the frequency of re-setups and a significant portion of discrepancies exceeding 0.3cm, increasing the allowable tolerance up to 0.5cm is justifiable. This would accommodate anatomical changes, reduce re-setups and maintain clinically acceptable dosimetric outcomes</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 2","pages":"Article 102051"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722660","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":"Investigation of IVIM diffusion weighted MRI in muscles of the lower limb at rest","authors":"Zen Kai Song Yeo ,&nbsp;Jia Yan Chye ,&nbsp;Ahmad Hamizan Izzul Haq ,&nbsp;Roy Tze Jian Seah ,&nbsp;Yong Jun Liew ,&nbsp;Xiaomeng Wang ,&nbsp;Derek Hausenloy ,&nbsp;Pek-Lan Khong ,&nbsp;Ying Hwey Nai ,&nbsp;Cheryl Pei Ling Lian","doi":"10.1016/j.jmir.2025.102055","DOIUrl":"10.1016/j.jmir.2025.102055","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Aim&lt;/h3&gt;&lt;div&gt;Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging (IVIM DW-MRI) provides a means for non-invasive, simultaneous assessment of tissue water diffusion and perfusion characteristics without the need for contrast agent administration. In this study, we aim to analyse the differences in water perfusion and diffusion in the lower limb calf muscles of healthy human volunteers and clinically diagnosed patients with Peripheral Arterial Disease (PAD) with acquired IVIM MR images.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;15 healthy subjects with no mobility issues and 9 clinically diagnosed PAD patients were included in this study. The axial MR images were acquired on the 3T Siemens Biograph mMR (Siemens Healthineers, Germany), with a 12-channel external phased-array coil covering both legs and positioned around the midpoint of the lower leg. Structural T1-weighted images were acquired before a set of baseline (BL) and high-quality (HQ) DWI images which were subsequently registered against each other. BL scan used 16 b-values, with a scan time of 2.5 minutes while HQ scan used 10 b-values with multiple averages to increase the signal-to-noise-ratio (SNR) for the images to be clinically acceptable with a scan time of 7.5 minutes. We utilised an open-source software, Medical Imaging Interaction Toolkit, MITK (version 2018.04.2), to segment the structural T1 images of the lower limb into five muscle groups; tibialis anterior (TA), peroneal muscles (PER), deep posterior calf muscles (DP), soleus muscle (SOL) and the gastrocnemius muscle (GM) regions. An in-house coded MATLAB script was then used to extract the Apparent Diffusion Coefficient (ADC) imaging parameter using the mono-exponential model, perfusion fraction (f), diffusion coefficient (D) and pseudo-diffusion (D*) imaging parameters from the 2-step, fixed D, Intravoxel Incoherent Motion (IVIM) model of the DWI images. Intraclass Correlation Coefficients (ICC) and Mann-Whitney U test were used to evaluate quantitative reproducibility of the paired BL and HQ images, and to determine significant differences between healthy subjects and PAD patients respectively.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Our study found that the parameters &lt;em&gt;f, D&lt;/em&gt;, and ADC demonstrated moderate to excellent reproducibility (Healthy ICC:0.694, 0.913, 0.623, PAD ICC:0.715, 0.991, 0.819 respectively), while &lt;em&gt;D&lt;/em&gt;* showed weak reproducibility (Healthy ICC:0.344, PAD ICC:0.552) with the potential for future investigation. Imaging parameters ADC and &lt;em&gt;f&lt;/em&gt; were found to be statistically significant (p-value &lt; 0.05) when comparing across healthy subjects and PAD patients in BL and HQ scans, indicating these parameters' potential utility as imaging biomarkers to distinguish healthy subjects from clinically diagnosed PAD patients.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;From the results of this pilot study, the quantitative parameters obtained by the BL and HQ scans were reprod","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 2","pages":"Article 102055"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722556","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":"3D-Printing Service in Radiology: Emerging Technology and Point-of-Care Innovations for Efficient, Personalized Medical Care and Precise Treatment Planning","authors":"Phang Yi Xuan","doi":"10.1016/j.jmir.2025.102052","DOIUrl":"10.1016/j.jmir.2025.102052","url":null,"abstract":"<div><h3>Aim</h3><div> .</div></div><div><h3>Background</h3><div>3D printing is revolutionizing medicine by enabling the creation of patient-specific anatomical models, enhancing visualization, and advancing precision in medical care. This emerging technology, combined with the establishment of an in-house 3D printing centre, expands radiology’s role as a point-of-care service, facilitating faster and more personalized treatment planning.</div></div><div><h3>Objective</h3><div>To explore the transformative impact of 3D printing as an emerging technology in radiology, highlighting its role in customizing patient care and demonstrating how in-house capabilities improve the precision, efficiency and effectiveness of healthcare services.</div></div><div><h3>Methods</h3><div>This presentation examines the integration of 3D printing into treatment planning across various medical conditions. Key applications include the creation of advanced training models that allow surgeons to refine their skills for complex procedures and the development of patient-specific surgical guides that enhance intraoperative precision. Rapid prototyping was employed for urgent cases such as orbital wall fractures and pelvic pathologies, ensuring timely and accurate surgical planning. Virtual surgical planning, combined with specialized software and real-time collaboration with on-site engineers further streamlined processes, significantly improving precision and saving valuable time. Additionally, advancements in DIEP flap model printing, adapted from insights gained during HMDP training at Stanford Medicine Hospital, demonstrated the value of iterative improvements based on direct surgeon feedback.</div></div><div><h3>Results</h3><div>The use of 3D-printed training models significantly boosted surgeons’ confidence before surgery. The availability of an in-house 3D printing centre reduced model production time by 40%, facilitating rapid prototyping for urgent cases. Direct collaboration between surgeons and engineers allowed real-time adjustments to surgical guides, enhancing accuracy and efficiency. Virtual surgical planning and customized 3D models enhanced surgeons’ understanding of complex patient’s anatomical structures in 85% of cases. This innovation results in a more precise and effective treatment planning, setting a new level for individualized and efficient patient care.</div></div><div><h3>Conclusion</h3><div>3D printing stands at the forefront of medical revolution, reshaping healthcare by combining innovative and cutting-edge tools with point-of-care solutions. This enables in delivering a faster, more personalized medical care and precise treatment planning. The establishment of an in-house 3D printing centre exemplifies this transformation, enhancing radiology’s role in improving efficiency, accuracy, and the overall quality of patient care.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 2","pages":"Article 102052"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722661","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":"Subscription","authors":"","doi":"10.1016/S1939-8654(25)00222-X","DOIUrl":"10.1016/S1939-8654(25)00222-X","url":null,"abstract":"","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 2","pages":"Article 102073"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722753","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}