Radiology最新文献

{"title":"SAR Consensus Recommendations for Defining Small Bowel Crohn Disease Strictures at CT and MR Enterography.","authors":"Bari Dane, Jonathan R Dillman, Jeff Fidler, Sudha A Anupindi, Clifton G Fulmer, Ilyssa O Gordon, David H Bruining, Parakkal Deepak, Abdul-Rahman Abualruz, Mahmoud Al-Hawary, Emre Altinmakas, Flavius F Guglielmo, Tracy Jaffe, Jordi Rimola, Dominik Bettenworth, Florian Rieder, Joel G Fletcher, Mark E Baker","doi":"10.1148/radiol.243123","DOIUrl":"https://doi.org/10.1148/radiol.243123","url":null,"abstract":"<p><p>More than half of patients with Crohn disease will develop strictures. Strictures are areas of bowel luminal narrowing composed of a combination of inflammatory cells, muscular hypertrophy, and fibrosis. Most patients with strictures eventually require endoscopic or surgical intervention. This article reviews small bowel Crohn disease stricture histopathology, current imaging definitions and challenges, and stricture management. Current imaging-based stricture definitions use different criteria and do not recognize strictures without upstream dilation nor failed endoscopic passage. This consensus was endorsed by the Society of Abdominal Radiology and developed by the Society of Abdominal Radiology Inflammatory Bowel Disease Disease Focused Panel as well as gastroenterology and pathology experts in Crohn disease strictures. Updated imaging stricture definitions and recommendations are presented. Most importantly, the panel now defines a Crohn disease small bowel stricture using a threshold small bowel dilation of 2.5 cm (rather than 3.0 cm) and incorporates failed endoscopic passage, even when there is no associated bowel dilation at CT or MR enterography. With these updated imaging stricture definitions, it is hoped that patients with Crohn disease may benefit from more timely stricture identification and management.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"316 1","pages":"e243123"},"PeriodicalIF":12.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Connecting Ambient Air Pollution and Myocardial Fibrosis.","authors":"Davis M Vigneault","doi":"10.1148/radiol.251801","DOIUrl":"https://doi.org/10.1148/radiol.251801","url":null,"abstract":"\"Just Accepted\" papers have undergone full peer review and have been accepted for publication in Radiology. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content.","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"11 1","pages":"e251801"},"PeriodicalIF":19.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144533346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ANCA-associated Vasculitis with Bilateral Renal Ruptures.","authors":"Xiaolong Liu,Zhanguo Sun","doi":"10.1148/radiol.243414","DOIUrl":"https://doi.org/10.1148/radiol.243414","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"35 1","pages":"e243414"},"PeriodicalIF":19.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144533475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable AI in MRI for Breast Cancer Detection: Another Step Forward.","authors":"Min Sun Bae, Sungwon Ham","doi":"10.1148/radiol.251790","DOIUrl":"https://doi.org/10.1148/radiol.251790","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"316 1","pages":"e251790"},"PeriodicalIF":12.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Cost of Strength: Weight Lifting-Induced Ureteral Dissection.","authors":"Hongliang Li, Qingyu Ji","doi":"10.1148/radiol.243482","DOIUrl":"https://doi.org/10.1148/radiol.243482","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"316 1","pages":"e243482"},"PeriodicalIF":12.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection.","authors":"Felipe Oviedo, Anum S Kazerouni, Philipp Liznerski, Yixi Xu, Michael Hirano, Robert A Vandermeulen, Marius Kloft, Elyse Blum, Adam M Alessio, Christopher I Li, William B Weeks, Rahul Dodhia, Juan M Lavista Ferres, Habib Rahbar, Savannah C Partridge","doi":"10.1148/radiol.241629","DOIUrl":"10.1148/radiol.241629","url":null,"abstract":"<p><p>Background Artificial intelligence (AI) models hold potential to increase the accuracy and efficiency of breast MRI screening; however, existing models have not been rigorously evaluated in populations with low cancer prevalence and lack interpretability, both of which are essential for clinical adoption. Purpose To develop an explainable AI model for cancer detection at breast MRI that is effective in both high- and low-cancer-prevalence settings. Materials and Methods This retrospective study included 9738 breast MRI examinations from a single institution (2005-2022), with external testing in a publicly available multicenter dataset (221 examinations). In total, 9567 consecutive examinations were used to develop an explainable fully convolutional data description (FCDD) anomaly detection model to detect malignancies on contrast-enhanced MRI scans. Performance was evaluated in three cohorts: grouped cross-validation (for both balanced [20.0% malignant] and imbalanced [1.85% malignant] detection tasks), an internal independent test set (171 examinations), and an external dataset. Explainability was assessed through pixelwise comparisons with reference-standard malignancy annotations. Statistical significance was assessed using the Wilcoxon signed rank test. Results FCDD outperformed the benchmark binary cross-entropy (BCE) model in cross-validation for both balanced (mean area under the receiver operating characteristic curve [AUC] = 0.84 ± 0.01 [SD] vs 0.81 ± 0.01; <i>P</i> < .001) and imbalanced (mean AUC = 0.72 ± 0.03 vs 0.69 ± 0.03; <i>P</i> < .001) detection tasks. At a fixed 97% sensitivity in the imbalanced setting, mean specificity across folds was 13% for FCDD and 9% for BCE (<i>P</i> = .02). In the internal test set, FCDD outperformed BCE for balanced (mean AUC = 0.81 ± 0.02 vs 0.72 ± 0.02; <i>P</i> < .001) and imbalanced (mean AUC = 0.78 ± 0.05 vs 0.76 ± 0.01; <i>P</i> < .02) detection tasks. For model explainability, FCDD demonstrated better spatial agreement with reference-standard annotations than BCE (internal test set: mean pixelwise AUC = 0.92 ± 0.10 vs 0.81 ± 0.13; <i>P</i> < .001). External testing confirmed that FCDD performed well, and better than BCE, in the balanced detection task (AUC = 0.86 ± 0.01 vs 0.79 ± 0.01; <i>P</i> < .001). Conclusion The developed explainable AI model for cancer detection at breast MRI accurately depicted tumor location and outperformed commonly used models in both high- and low-cancer-prevalence scenarios. © RSNA, 2025 <i>Supplemental material is available for this article.</i> See also the editorial by Bae and Ham in this issue.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"316 1","pages":"e241629"},"PeriodicalIF":12.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Post-COVID-19 Chest CT Expert Consensus, and a Nod to the Law of the Instrument.","authors":"Loren Ketai","doi":"10.1148/radiol.251890","DOIUrl":"https://doi.org/10.1148/radiol.251890","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"316 1","pages":"e251890"},"PeriodicalIF":12.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144691370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between Long-term Exposure to Ambient Air Pollution and Myocardial Fibrosis Assessed with Cardiac MRI.","authors":"Jacques Du Plessis,Chloe DesRoche,Scott Delaney,Rachel C Nethery,Rachel Hong,Paaladinesh Thavendiranathan,Heather Ross,Felipe Castillo,Kate Hanneman","doi":"10.1148/radiol.250331","DOIUrl":"https://doi.org/10.1148/radiol.250331","url":null,"abstract":"Background Poor air quality is associated with cardiovascular morbidity. However, the underlying pathophysiologic mechanisms are unclear. Purpose To determine the relationship between long-term exposure to ambient fine particulate matter with 2.5-µm or smaller aerodynamic diameter (PM2.5) and the extent of diffuse myocardial fibrosis quantified with cardiac MRI. Materials and Methods In this single-center retrospective study, patients with dilated cardiomyopathy (DCM) or controls with normal cardiac MRI findings were included (January 2018 to December 2022). Diffuse myocardial fibrosis was quantified using cardiac MRI native T1 mapping z scores. Residence-specific ambient PM2.5 concentration was assessed as the mean of daily exposure concentration in the year before cardiac MRI using direct measurements from the nearest monitoring station. Multivariable models were adjusted for clinically relevant covariates. Results A total of 694 patients (mean age, 47 years ± 16 [SD]; 443 men; 493 with DCM, 201 controls) were included. In multivariable models, each 1-µg/m3 increase in 1-year mean PM2.5 exposure was associated with a 0.30 higher native T1 z score in patients with DCM (adjusted β coefficient: 0.30; 95% CI: 0.13, 0.47; P < .001) and 0.27 higher native T1 z score in controls (adjusted β coefficient: 0.27; 95% CI: 0.04, 0.51; P = .02). For absolute values, each 1-µg/m3 increase in 1-year mean PM2.5 exposure was associated with 9.1 msec higher native T1 at 1.5 T (β coefficient: 9.1; 95% CI: 2.04, 15.97; P = .01) and 12.1 msec higher native T1 at 3 T (β coefficient: 12.1; 95% CI: 5.74, 18.52; P < .001). Stratified models indicated the largest effect sizes for the association of PM2.5 exposure with native T1 z scores in women (β coefficient: 0.49; 95% CI: 0.23, 0.76; P < .001), smokers (β coefficient: 0.43; 95% CI: 0.02, 0.84; P = .04), and patients with hypertension (β coefficient: 0.48; 95% CI: 0.16, 0.80; P = .004). Conclusion Higher long-term exposure to ambient fine particulate air pollution is associated with greater diffuse myocardial fibrosis at cardiac MRI native T1 mapping in patients with DCM and healthy controls. © RSNA, 2025 See also the editorial by Vigneault in this issue.","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"7 1","pages":"e250331"},"PeriodicalIF":19.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144533470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lack of Transparency Regarding Role of AI in Ultra-High-field Coronary MR Angiography.","authors":"Shi-Hai Zhao","doi":"10.1148/radiol.243424","DOIUrl":"https://doi.org/10.1148/radiol.243424","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"648 1","pages":"e243424"},"PeriodicalIF":19.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144533347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breast MRI for Assessing Triple-Negative Breast Cancer after Neoadjuvant Chemoimmunotherapy.","authors":"Natsuko Onishi","doi":"10.1148/radiol.251503","DOIUrl":"https://doi.org/10.1148/radiol.251503","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"70 1","pages":"e251503"},"PeriodicalIF":19.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144533464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}