Journal of the American College of Radiology最新文献

{"title":"Opinions and Preferences Regarding Artificial Intelligence Use in Health Care Delivery: Results From a National Multisite Survey of Breast Imaging Patients","authors":"Brian N. Dontchos MD ,&nbsp;Katerina Dodelzon MD ,&nbsp;Sonya Bhole MD ,&nbsp;Christine E. Edmonds MD ,&nbsp;Lisa A. Mullen MD ,&nbsp;Jay R. Parikh MD ,&nbsp;Caroline P. Daly MD ,&nbsp;James A. Epling MD, MS ,&nbsp;Soren Christensen BS ,&nbsp;Lars J. Grimm MD, MHS","doi":"10.1016/j.jacr.2025.05.001","DOIUrl":"10.1016/j.jacr.2025.05.001","url":null,"abstract":"<div><h3>Objective</h3><div>Artificial intelligence (AI) utilization is growing, but patient perceptions of AI are unclear. Our objective was to understand patient perceptions of AI through a multisite survey of breast imaging patients.</div></div><div><h3>Methods</h3><div>A 36-question survey was distributed to eight US practices (six academic, two nonacademic) from October 2023 through October 2024. This article analyzes a subset of questions from the survey addressing digital health literacy and attitudes toward AI in medicine and breast imaging specifically. Multivariable analysis compared responses by respondent demographics.</div></div><div><h3>Results</h3><div><span>A total of 3,532 surveys were collected (response rate: 69.9%, 3,532 of 5,053). Median respondent age was 55 years (interquartile range 20). Most respondents were White (73.0%, 2,579 of 3,532) and had completed college (77.3%, 2,732 of 3,532). Overall, respondents were undecided (range: 43.2%-50.8%) regarding questions about general perceptions of AI in health care. Respondents with higher electronic health literacy, more education, and younger age were significantly more likely to consider it useful to use AI for aiding medical tasks (all </span><em>P &lt;</em> .001). In contrast, respondents with lower electronic health literacy and less education were significantly more likely to indicate it was a bad idea for AI to perform medical tasks (<em>P &lt;</em> .001). Non-White patients were more likely to express concerns that AI will not work as well for some groups compared with others (<em>P &lt;</em> .05). Overall, favorable opinions of AI use for medical tasks were associated with younger age, more education, and higher electronic health literacy.</div></div><div><h3>Discussion</h3><div>As AI is increasingly implemented into clinical workflows, it is important to educate patients and provide transparency to build patient understanding and trust.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Pages 1032-1040"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144030154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiology Innovation Amid Potential Research Funding Cuts","authors":"Joshua M. Liao MD, MSc ,&nbsp;Jonathan B. Jaffery MD, MS, MMM ,&nbsp;Stella K. Kang MD, MS ,&nbsp;Pina C. Sanelli MD, MPH ,&nbsp;Christoph I. Lee MD, MS, MBA","doi":"10.1016/j.jacr.2025.05.020","DOIUrl":"10.1016/j.jacr.2025.05.020","url":null,"abstract":"","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Pages 1095-1097"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144251181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Table of Content","authors":"","doi":"10.1016/S1546-1440(25)00394-1","DOIUrl":"10.1016/S1546-1440(25)00394-1","url":null,"abstract":"","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Pages A1-A4"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of the COVID-19 Pandemic on Breast Biopsy Delays: Factors Contributing to Disparities Across Prepandemic, Shutdown, and Postshutdown Periods","authors":"Babita Panigrahi MD ,&nbsp;Naveen Ghuman MD ,&nbsp;Joanna Rossi MD, MPH ,&nbsp;Kelly S. Myers MD ,&nbsp;Lisa A. Mullen MD ,&nbsp;Emily B. Ambinder MD, MS ,&nbsp;Eniola T. Oluyemi MD, MPH","doi":"10.1016/j.jacr.2025.05.008","DOIUrl":"10.1016/j.jacr.2025.05.008","url":null,"abstract":"<div><h3>Background</h3><div><span>The coronavirus disease of 2019 pandemic significantly disrupted </span>health care delivery, leading to delays in diagnostic procedures.</div></div><div><h3>Objective</h3><div>This study aimed to examine the factors associated with delays in time from diagnostic examination to image-guided breast biopsies during the prepandemic, shutdown, and postshutdown periods.</div></div><div><h3>Methods</h3><div><span>This retrospective cohort study included 4,415 examinations with a BI-RADS 4 or 5 assessment recommending image-guided biopsy for 4,197 patients at a multisite academic institution from January 1, 2019, to December 31, 2021. Delays in biopsy were assessed across three periods: prepandemic (January 1, 2019, to February 29, 2020, n = 1,551), shutdown (March 1, 2020, to May 31, 2020, n = 170), and postshutdown (June 1, 2020, to December 31, 2021, n = 2,694). Patient factors included age, race, ethnicity, personal or family history of breast cancer, area deprivation index, employment, insurance, and marital status. Clinical factors included BI-RADS assessment and biopsy modality. </span><em>t</em><span> Tests, Wilcoxon’s rank-sum tests, and univariate and multivariate logistic regression analyses were performed to quantify and identify factors associated with biopsy delay.</span></div></div><div><h3>Results</h3><div>The median time to biopsy from diagnostic examination significantly increased between the prepandemic (11 days) and postshutdown (16 days) periods (<em>P</em> &lt; .001). Significant biopsy delays, defined as ≥30 days to biopsy, increased between the prepandemic (9%) and postshutdown (12%) periods (<em>P</em> = .001). Compared with the prepandemic period, same-day biopsies increased in the shutdown period (from 8% to 24%, <em>P</em> &lt; .001) due to institutional implementation of same-day procedures during the shutdown, then sharply declined in the postshutdown period (2%, <em>P</em><span> &lt; .001). Biopsies were independently more likely to be delayed in the postshutdown period compared with the prepandemic period on multivariate analysis (odds ratio [OR] 1.4, </span><em>P</em> = .004). In addition to time period, patient factors including age between 60 and 70 years (OR 1.5, <em>P</em> = .020) or ≥70 years (OR 1.9, <em>P</em> = .002), Black (OR 1.6, <em>P</em> &lt; .001) or Asian (OR 1.9, <em>P</em> = .003) race, not having a personal history of breast cancer (OR 1.4, <em>P</em> = .018), being unemployed (OR 1.5, <em>P</em> = .005) or uninsured (OR 2.7, <em>P</em> = .001), being unmarried (OR 1.4, <em>P</em> = .004), and undergoing stereotactic (OR 1.3, <em>P</em> = .013) or MRI (OR 4.7, <em>P</em> &lt; .001) biopsies were significant predictors of delay in the prepandemic and postshutdown periods on multivariate analysis.</div></div><div><h3>Conclusions</h3><div>Delays in breast biopsies increased between the prepandemic and postshutdown periods. Significant delays were more prevalent among old","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Pages 1019-1026"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","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®: Imaging for Pulmonary Embolism, Known Clot","authors":"Veer S. Sawhney BA ,&nbsp;Sharon D’Souza MD, MPH","doi":"10.1016/j.jacr.2025.05.006","DOIUrl":"10.1016/j.jacr.2025.05.006","url":null,"abstract":"","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Page 1106"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144032186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RadGPT: A System Based on a Large Language Model That Generates Sets of Patient-Centered Materials to Explain Radiology Report Information","authors":"Sanna E. Herwald MD, PhD ,&nbsp;Preya Shah MD, PhD ,&nbsp;Andrew Johnston MD, MBA ,&nbsp;Cameron Olsen MD ,&nbsp;Jean-Benoit Delbrouck PhD ,&nbsp;Curtis P. Langlotz MD, PhD","doi":"10.1016/j.jacr.2025.06.013","DOIUrl":"10.1016/j.jacr.2025.06.013","url":null,"abstract":"<div><h3>Purpose</h3><div>The 21st Century Cures Act final rule requires that patients have real-time access to their radiology reports, which contain technical language. The objective of this study to was to use a novel system called RadGPT, which integrates concept extraction and a large language model (LLM), to help patients understand their radiology reports.</div></div><div><h3>Methods</h3><div>RadGPT generated 150 concept explanations and 390 question-and-answer pairs from 30 radiology report impressions from between 2012 and 2020. The extracted concepts were used to create concept-based explanations, as well as concept-based question-and-answer pairs for which questions were generated using either a fixed template or an LLM. Additionally, report-based question-and-answer pairs were generated directly from the impression using an LLM without concept extraction. One board-certified radiologist and four radiology residents rated the material quality using a standardized rubric.</div></div><div><h3>Results</h3><div>Concept-based LLM-generated questions were of significantly higher quality than concept-based template-generated questions (<em>P</em> &lt; .001). Excluding those template-based question-and-answer pairs from further analysis, nearly all (&gt;95%) of RadGPT-generated materials were rated highly, with at least 50% receiving the highest possible ranking from all five raters. No answers or explanations were rated as likely to affect the safety or effectiveness of patient care. Report-level LLM-based questions and answers were rated particularly highly, with 92% of report-level LLM-based questions and 61% of the corresponding report-level answers receiving the highest rating from all raters.</div></div><div><h3>Conclusions</h3><div>The educational tool RadGPT generated high-quality explanations and question-and-answer pairs that were personalized for each radiology report, unlikely to produce harmful explanations, and likely to enhance patient understanding of radiology information.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Pages 1050-1059"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144287496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diversity in Interventional Radiology Residency Programs","authors":"Samir S. Jambhekar MD ,&nbsp;David S. Shin MD ,&nbsp;Jeffrey Forris Beecham Chick MD, MPH ,&nbsp;Eric J. Monroe MD ,&nbsp;Matthew Abad-Santos MD ,&nbsp;Grace L. Laidlaw MD, MS ,&nbsp;Eunjee Lee PhD ,&nbsp;JinSeop Hyun PhD ,&nbsp;Mina S. Makary MD","doi":"10.1016/j.jacr.2025.05.009","DOIUrl":"10.1016/j.jacr.2025.05.009","url":null,"abstract":"<div><h3>Purpose</h3><div>The aim of this study was to assess diversity within integrated interventional radiology<span> (IR) residency programs.</span></div></div><div><h3>Methods</h3><div>The annual Association of American Medical Colleges Report on Residents, an observational cross-sectional study, was accessed from 2018 through 2023 to extract demographic information (gender, race, and type of medical school) on the various residency programs, including integrated IR. Demographic data were compared among different specialties using the χ² test, with a significance level of <em>P</em> &lt; .05.</div></div><div><h3>Results</h3><div>In 2023, integrated IR ranked 20th, 21st, and 19th out of the 21 specialties assessed for the representation of women, black, and Hispanic residents, respectively. The proportion of women increased from 20% in academic year (AY) 2018-2019 to 22.3% in AY 2022-2023. The percentage of black residents increased from 2.2% in AY 2019-2020 to 3.8% in AY 2022-2023, whereas that of Hispanics decreased from 7.1% to 6.6%. Additionally, the percentage of American Indians and Alaska Natives decreased from 0.8% to 0.7%, whereas that of Native Hawaiians and Pacific Islanders increased from 0% to 0.1%.</div></div><div><h3>Conclusions</h3><div>Diversity in integrated IR residency is one of the lowest among the medical specialties and has progressed minimally. A concerted effort to increase awareness and inclusion in the specialty would broaden its appeal and may eventually improve its availability.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Pages 1060-1068"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144096377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disparities of Distant Metastasis Evaluation Imaging for Rectal Cancer","authors":"Brittany Le MD ,&nbsp;Angelina Lo MD ,&nbsp;Wen-Pin Chen MS ,&nbsp;Gelareh Sadigh MD ,&nbsp;Jason Zell MD ,&nbsp;Sonia Lee MD","doi":"10.1016/j.jacr.2025.05.010","DOIUrl":"10.1016/j.jacr.2025.05.010","url":null,"abstract":"<div><h3>Purpose</h3><div><span>The aim of this study was to determine demographic factors associated with receipt of initial distant metastasis imaging and the time delay between diagnosis and imaging among patients with </span>rectal cancer.</div></div><div><h3>Methods</h3><div>Consecutive patients with rectal adenocarcinoma<span><span> from a cancer registry<span> were retrospectively reviewed for the presence of distant metastasis imaging and whether the received imaging was the first-line modality as determined by National Comprehensive Cancer Network and European Society for Medical Oncology guidelines. We obtained data for the clinical-demographic categories of ethnicity, sex, age, </span></span>body mass index<span>, census block, and insurance payer. Analyses included descriptive analysis and logistic regression analysis.</span></span></div></div><div><h3>Results</h3><div>Of 329 patients, 61.4% were male, and the average age was 58 years. The average time interval from tissue diagnosis to imaging systemic staging completion was 20.6 days. In multivariable analysis, non-Hispanic patients (odds ratio [OR], 4.57; 95% confidence interval [CI], 2.27-9.19) and those who were overweight (OR, 4.55; 95% CI, 2.04-10.12) and obese (OR, 4.21; 95% CI, 1.70-10.45) were more likely to complete initial staging, with those with public insurance (<em>P</em> = .03) less likely to receive staging in univariable analysis. Patients with more recent year of diagnosis (OR, 1.26; 95% CI, 1.07-1.50) in multivariable analysis and those with younger age (<em>P</em> = .04) and urban residence (<em>P</em> &lt; .01) in univariable analysis were associated with first-line imaging modality. Low body mass index was correlated with improved imaging timeliness (<em>P</em> = .03).</div></div><div><h3>Conclusions</h3><div>Multiple demographic factors affect the completion of imaging, receipt of recommended imaging, and the time interval to receive imaging. It is therefore necessary to ensure adequate compliance with initial workup recommendations and to improve radiologic access.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Pages 990-997"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144096376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Can Medical Physics Foster More Environmentally Sustainable Practices in Medical Imaging?","authors":"Andrew M. Hernandez PhD ,&nbsp;Megan E. Lipford PhD ,&nbsp;Youngkyoo Jung PhD","doi":"10.1016/j.jacr.2025.06.004","DOIUrl":"10.1016/j.jacr.2025.06.004","url":null,"abstract":"","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Pages 1101-1104"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144276939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identity Matters: The Potential for a Frictionless and Secure Patient Experience","authors":"Caryn Seidman Becker ,&nbsp;Elliot K. Fishman MD ,&nbsp;Steven P. Rowe MD, PhD ,&nbsp;Linda C. Chu MD ,&nbsp;Charles K. Crawford","doi":"10.1016/j.jacr.2025.02.005","DOIUrl":"10.1016/j.jacr.2025.02.005","url":null,"abstract":"","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 9","pages":"Pages 1098-1100"},"PeriodicalIF":5.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143384335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}