Journal of the American College of Radiology : JACR最新文献

{"title":"Leveraging Large Language Models to Enhance Radiology Report Readability: A Systematic Review.","authors":"Vasant Patwardhan, Divya Balchander, David Fussell, John Joseph, Aditya Joshi, Hayden Troutt, Justin Ling, Katherine Wei, Brent Weinberg, Daniel Chow","doi":"10.1016/j.jacr.2025.09.004","DOIUrl":"https://doi.org/10.1016/j.jacr.2025.09.004","url":null,"abstract":"<p><strong>Background: </strong>Patients increasingly have direct access to their medical record. Radiology reports are complex and difficult for patients to understand and contextualize. One solution is to use large language models (LLMs) to translate reports into patient-accessible language. Objective This review summarizes the existing literature on using LLMs for the simplification of patient radiology reports. We also propose guidelines for best practices in future studies.</p><p><strong>Evidence acquisition: </strong>A systematic review was performed following PRISMA guidelines. Studies published and indexed using PubMed, Scopus, and Google Scholar up to February 2025 were included. Inclusion criteria comprised of studies that used large language models for simplification of diagnostic or interventional radiology reports for patients and evaluated readability. Exclusion criteria included non-English manuscripts, abstracts, conference presentations, review articles, retracted articles, and studies that did not focus on report simplification. The Mixed Methods Appraisal tool (MMAT) 2018 was used for bias assessment. Given the diversity of results, studies were categorized based on reporting methods, and qualitative and quantitative findings were presented to summarize key insights.</p><p><strong>Evidence synthesis: </strong>A total of 2126 citations were identified and 17 were included in the qualitative analysis. 71% of studies utilized a single LLM, while 29% of studies utilized multiple LLMs. The most prevalent LLMs included ChatGPT, Google Bard/Gemini, Bing Chat, Claude, and Microsoft Copilot. All studies that assessed quantitative readability metrics (n=12) reported improvements. Assessment of simplified reports via qualitative methods demonstrated varied results with physician vs non-physician raters.</p><p><strong>Conclusion and clinical impact: </strong>LLMs demonstrate the potential to enhance the accessibility of radiology reports for patients, but the literature is limited by heterogeneity of inputs, models, and evaluation metrics across existing studies. We propose a set of best practice guidelines to standardize future LLM research.</p>","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145058723","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-Friendly Summary of the ACR Appropriateness Criteria®: Chronic Hip Pain.","authors":"Abby Newman, Name Karen Chi-Lynn Chen","doi":"10.1016/j.jacr.2025.09.009","DOIUrl":"https://doi.org/10.1016/j.jacr.2025.09.009","url":null,"abstract":"","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145056486","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-Friendly Summary of the ACR Appropriateness Criteria®: Staging and Follow-Up of Anal Cancer.","authors":"Yuri G Takagawa, Sherry S Wang","doi":"10.1016/j.jacr.2025.09.010","DOIUrl":"10.1016/j.jacr.2025.09.010","url":null,"abstract":"","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145056476","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-Friendly Summary of the ACR Appropriateness Criteria®: Staging and Disease Monitoring of Colon Cancer and Appendiceal Cancer.","authors":"Sania Choudhary, David H Kim","doi":"10.1016/j.jacr.2025.09.008","DOIUrl":"10.1016/j.jacr.2025.09.008","url":null,"abstract":"","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145056466","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":"CPT® Coding for MR Safety Evaluation - Implementation Tips.","authors":"Cindy Yuan, Heidi A Edmonson, Colin Segovis","doi":"10.1016/j.jacr.2025.09.005","DOIUrl":"https://doi.org/10.1016/j.jacr.2025.09.005","url":null,"abstract":"","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145056444","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":"Certainty Amid Artful Ambiguity: An Editorial Comment on \"Communicating Diagnostic Certainty in Radiology Reports: Potential Frameworks From the American College of Radiology Commission on Quality and Safety\".","authors":"Hansel J Otero, Abass Noor","doi":"10.1016/j.jacr.2025.09.001","DOIUrl":"10.1016/j.jacr.2025.09.001","url":null,"abstract":"","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145056380","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":"The Era Of AI: Can Radiologists Move From Invisible to Indispensable?","authors":"Nadja Kadom","doi":"10.1016/j.jacr.2025.09.002","DOIUrl":"https://doi.org/10.1016/j.jacr.2025.09.002","url":null,"abstract":"","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145056515","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":"Alternative Approaches to Resident Education.","authors":"Billy Chien, Jackson Pearce, Muhammad Qureshi, Puneet Bhargava, Mahan Mathur","doi":"10.1016/j.jacr.2025.08.054","DOIUrl":"10.1016/j.jacr.2025.08.054","url":null,"abstract":"<p><p>Radiology education pedagogy has traditionally focused on a combination of in-house workstation teaching and either didactic or case-based conferences. These approaches, however, may no longer be sustainable in the current radiology climate. The rising growth in imaging volumes combined with the demand for shorter report turnaround times, ongoing noninterpretative tasks, and the nationwide radiology workforce shortage have contributed to faculty burnout, which can have a significant impact on resident education. Fortunately, educators can leverage ongoing technological advances to provide a learning experience for residents that may overcome some of the current challenges. The authors discuss some of these pedagogic advances and offer strategies for their implementation during the clinical workday. A nuanced discussion of the advantages and challenges is provided, with a focus on the economic considerations associated with adopting each of these approaches.</p>","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006910","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":"The Silent Retreat: Quiet Quitting in the Academic Radiology Workforce.","authors":"Subha Ghosh","doi":"10.1016/j.jacr.2025.08.051","DOIUrl":"10.1016/j.jacr.2025.08.051","url":null,"abstract":"","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006926","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":"Closing the loop: nine-year outcomes of an electronic medical record-based protocol for reporting incidental imaging findings.","authors":"Rohan M Shah, Aniket Dehadrai, Ariz Keshwani, Brenda Schmitz, James C Carr","doi":"10.1016/j.jacr.2025.08.047","DOIUrl":"https://doi.org/10.1016/j.jacr.2025.08.047","url":null,"abstract":"<p><strong>Introduction: </strong>Incidental findings in radiology are common, especially with rising imaging volumes. Early disease recognition can greatly improve clinical outcomes, but in low-risk cases, incidental findings often lead to overdiagnosis and overtreatment, causing harm. Robust systems are critical to promote early identification without overburdening patients or healthcare systems.</p><p><strong>Methods: </strong>We conducted a retrospective analysis of incidental findings reported through a novel electronic notification system from January 1, 2015, to December 31, 2023. Adults undergoing CT, MRI, radiographs, or ultrasound were included. The protocol involved radiologists submitting findings via an EMR button, triggering a nursing-led follow-up algorithm that varied based on clinical setting (ED, inpatient, outpatient) and finding type (e.g., lung, kidney). Primary outcomes were utilization (total cases, compounded growth) and case resolution. Secondary outcomes included stratification by imaging modality and type of incidental finding. Descriptive statistics were used for analysis.</p><p><strong>Results: </strong>A total 25,175 incidental findings were reported, averaging 2,797 cases per year and 233 per month, with an overall compounded annual growth rate of 21.44%. Resolution rates remained consistently >99% after initial tracking began, with only two months below this threshold. From 2019-2023, among 17,205 available cases, lung findings were the most common (19.31%), followed by brain (7.29%) and kidney (7.17%). CT imaging was the most frequent modality (53.99%), followed by MRI (20.34%), radiographs (18.17%), and ultrasound (7.49%).</p><p><strong>Conclusions: </strong>We successfully implemented an incidental findings reporting protocol with strong provider uptake and case resolution. As imaging volumes continue to rise, structured follow-up systems are increasingly critical for hospitals.</p>","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006933","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}