Radiology最新文献

{"title":"Multiparametric MRI for Bladder Cancer: A Practical Approach to the Clinical Application of VI-RADS.","authors":"Martina Pecoraro, Stefano Cipollari, Emanuele Messina, Ludovica Laschena, Ailin Dehghanpour, Antonella Borrelli, Francesco Del Giudice, Valdair Francisco Muglia, Hebert Alberto Vargas, Valeria Panebianco","doi":"10.1148/radiol.233459","DOIUrl":"https://doi.org/10.1148/radiol.233459","url":null,"abstract":"<p><p>Multiparametric MRI of the bladder is highly accurate in the detection and local staging of bladder cancer. The Vesical Imaging Reporting and Data System (VI-RADS) scoring system has improved the diagnostic accuracy, reproducibility, and interpretability of bladder MRI in the assessment of the invasion of the muscularis propria. There are several technical details concerning bladder MRI that need to be strictly applied to obtain the highest possible diagnostic potential from the MRI. In addition, image evaluation, accurate interpretation, and reporting need to be standardized to optimize diagnostic accuracy and interreader agreement. This review describes the patient population for bladder MRI and discusses, with a practical approach, the correct acquisition protocol for optimal image quality using VI-RADS with reporting tips, pitfalls, and challenges for its clinical application. This review also discusses the latest evidence, clinical implications, current controversies, and future challenges, including gaps in knowledge, of the VI-RADS scoring system.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e233459"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543188","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":"Unveiling the Future: A Deep Learning Model for Accurate Detection of Adrenal Nodules.","authors":"Ashkan A Malayeri, Baris Turkbey","doi":"10.1148/radiol.250387","DOIUrl":"https://doi.org/10.1148/radiol.250387","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e250387"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543194","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":"¹⁸F-Fluoroestradiol PET/CT for Staging Low-Grade Estrogen Receptor-Positive Breast Cancer.","authors":"Amy M Fowler","doi":"10.1148/radiol.250135","DOIUrl":"https://doi.org/10.1148/radiol.250135","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e250135"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543231","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":"Peripheral Nerve Imaging: MR Neurography versus High-Resolution US.","authors":"Swati Deshmukh","doi":"10.1148/radiol.242775","DOIUrl":"https://doi.org/10.1148/radiol.242775","url":null,"abstract":"<p><p>\u0000 <i>\"Just Accepted\" papers have undergone full peer review and have been accepted for publication in <i>Radiology</i>. 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.</i>\u0000 </p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e242775"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543190","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":"Left Coronary Artery-to-Right Ventricle Fistula with Giant Aneurysm.","authors":"Limin Lei, Yuhan Zhou","doi":"10.1148/radiol.242019","DOIUrl":"https://doi.org/10.1148/radiol.242019","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e242019"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543187","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 Diagnostic Accuracy of ¹⁸F-FDG PET and ¹⁸F-FES PET for Staging Grade 1-2 Estrogen Receptor-Positive Breast Cancer.","authors":"Jelijn J Knip, Ramsha Iqbal, Emma C Bonjer, Lemonitsa H Mammatas, Annette A van Zweeden, Paola Perin, Jaap J M Teunissen, Gwen M P Diepenhorst, Laura J Schijf, Sandra D Bakker, Noortje Schoenmakers, Susanne van der Velde, Ellis Barbé, Katya Duvivier, Inge R Konings, Gerben J C Zwezerijnen, Albert D Windhorst, Ronald Boellaard, Daniela E Oprea-Lager, C Willemien Menke-van der Houven van Oordt","doi":"10.1148/radiol.241850","DOIUrl":"https://doi.org/10.1148/radiol.241850","url":null,"abstract":"<p><p>Background According to current guidelines, staging of patients with locally advanced breast cancer and local-regional recurrent breast cancer is preferably performed with PET using 2-fluorine 18-fluoro-2-deoxy-d-glucose (¹⁸F-FDG). However, ¹⁸F-FDG PET might underperform in low-grade estrogen receptor (ER)-positive breast cancer. Alternatively, 16α-¹⁸F-fluoro-17β-estradiol (¹⁸F-FES) has emerged as a powerful tracer for in vivo visualization of ER-positive lesions. Purpose To assess whether ¹⁸F-FES PET improves staging of grade 1 or 2 ER-positive breast cancer compared with ¹⁸F-FDG PET. Materials and Methods Patients with clinical stage II/III or local-regional recurrent, grade 1 or 2, ER-positive breast cancer were included between December 2018 and January 2021 in this prospective multicenter pilot study. All participants underwent an ¹⁸F-FES PET examination in addition to standard staging with conventional imaging and ¹⁸F-FDG PET. Both PET scans were independently assessed. The disease stage was determined independently based on conventional imaging and ¹⁸F-FDG PET or ¹⁸F-FES PET. Relevant lesions suspected of malignancy were verified histopathologically, after which a final stage was determined. Results A total of 41 female participants (median age, 56 years [IQR, 48-71 years]) with 44 breast tumors were included. Overall, 29 of 41 participants (71%) were correctly staged at ¹⁸F-FDG PET compared with 34 of 41 (83%) at ¹⁸F-FES PET (<i>P</i> = .18). Seven of 10 and nine of 10 cases of lobular breast cancer were correctly staged at ¹⁸F-FDG and ¹⁸F-FES PET, respectively (70% vs 90%; <i>P</i> = .38) and seven of 12 and 11 of 12 cases of grade 1 tumors, respectively (58% vs 92%; <i>P</i> = .06). Regional lymph nodes were incorrectly staged at ¹⁸F-FDG PET in six of 44 cases (14%), whereas all cases were correctly staged at ¹⁸F-FES PET (<i>P</i> = .02). Both imaging methods had a sensitivity of 100% (95% CI: 59, 100) and a specificity of 91% (95% CI: 76, 98) for the detection of metastatic disease. Conclusion In this prospective pilot study, there was no evidence of a difference in diagnostic accuracy of ¹⁸F-FES PET and ¹⁸F-FDG PET in staging patients with grade 1 or 2 ER-positive breast cancer. Clinical trial registration no. NCT03726931 Published under a CC BY 4.0 license <i>Supplemental material is available for this article.</i> See also the editorial by Fowler in this issue.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e241850"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543191","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":"Alternating Views on the ABR Alternate Pathway.","authors":"Adarsh Ghosh, Eric Crotty","doi":"10.1148/radiol.240966","DOIUrl":"https://doi.org/10.1148/radiol.240966","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e240966"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543239","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":"AI-generated Podcast Summaries of <i>Radiology</i> Articles: Analysis of Content and Quality.","authors":"Ali S Tejani, Bardia Khosravi, Cody H Savage, Linda Moy, Charles E Kahn, Paul H Yi","doi":"10.1148/radiol.243270","DOIUrl":"https://doi.org/10.1148/radiol.243270","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e243270"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543233","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":"Two-Stage Deep Learning Model for Adrenal Nodule Detection on CT Images: A Retrospective Study.","authors":"Chang Ho Ahn, Taewoo Kim, Kyungmin Jo, Seung Shin Park, Min Joo Kim, Ji Won Yoon, Taek Min Kim, Sang Youn Kim, Jung Hee Kim, Jaegul Choo","doi":"10.1148/radiol.231650","DOIUrl":"https://doi.org/10.1148/radiol.231650","url":null,"abstract":"<p><p>Background The detection and classification of adrenal nodules are crucial for their management. Purpose To develop and test a deep learning model to automatically depict adrenal nodules on abdominal CT images and to simulate triaging performance in combination with human interpretation. Materials and Methods This retrospective study (January 2000-December 2020) used an internal dataset enriched with adrenal nodules for model training and testing and an external dataset reflecting real-world practice for further simulated testing in combination with human interpretation. The deep learning model had a two-stage architecture, a sequential detection and segmentation model, trained separately for the right and left adrenal glands. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for nodule detection and intersection over union for nodule segmentation. Results Of a total of 995 patients in the internal dataset, the AUCs for detecting right and left adrenal nodules in internal test set 1 (<i>n</i> = 153) were 0.98 (95% CI: 0.96, 1.00; <i>P</i> < .001) and 0.93 (95% CI: 0.87, 0.98; <i>P</i> < .001), respectively. These values were 0.98 (95% CI: 0.97, 0.99; <i>P</i> < .001) and 0.97 (95% CI: 0.96, 0.97; <i>P</i> < .001) in the external test set (<i>n</i> = 12 080) and 0.90 (95% CI: 0.84, 0.95; <i>P</i> < .001) and 0.89 (95% CI: 0.85, 0.94; <i>P</i> < .001) in internal test set 2 (<i>n</i> = 1214). The median intersection over union was 0.64 (IQR, 0.43-0.71) and 0.53 (IQR, 0.40-0.64) for right and left adrenal nodules, respectively. Combining the model with human interpretation achieved high sensitivity (up to 100%) and specificity (up to 99%), with triaging performance from 0.77 to 0.98. Conclusion The deep learning model demonstrated high performance and has the potential to improve detection of incidental adrenal nodules. © RSNA, 2025 <i>Supplemental material is available for this article.</i> See also the editorial by Malayeri and Turkbey in this issue.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e231650"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543193","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":"Coronary Plaque Quantification with Ultrahigh-Spatial-Resolution Photon-counting Detector CT: Intraindividual Comparison with Energy-integrating Detector CT.","authors":"Milán Vecsey-Nagy, Giuseppe Tremamunno, U Joseph Schoepf, Chiara Gnasso, Emese Zsarnóczay, Nicola Fink, Dmitrij Kravchenko, Moritz C Halfmann, Jim O'Doherty, Bálint Szilveszter, Pál Maurovich-Horvat, Ismail Mikdat Kabakus, Pal Spruill Suranyi, Tilman Emrich, Akos Varga-Szemes","doi":"10.1148/radiol.241479","DOIUrl":"https://doi.org/10.1148/radiol.241479","url":null,"abstract":"<p><p>Background Other than enhancing the accuracy of stenosis measurements, the improved spatial resolution of photon-counting detector (PCD) CT may have an impact on quantitative plaque assessment at coronary CT angiography (CCTA). Purpose To evaluate the effect of PCD CT on coronary plaque quantification and characterization compared with that of energy-integrating detector (EID) CT. Materials and Methods Consecutive participants undergoing clinically indicated CCTA at EID CT (192 × 0.6-mm collimation) were enrolled to undergo ultrahigh-spatial-resolution (UHR) PCD CT (120 × 0.2-mm collimation) within 30 days. PCD CT was performed using equivalent or lower CT dose index and equivalent contrast media volume as the clinical scan. Total, calcified, fibrotic, and low-attenuation coronary plaque volumes were quantified and compared between scanners. Intra- and interreader reproducibility was assessed for both systems. Results A total of 164 plaques from 48 participants were segmented on both scans. Total plaque volume was lower at PCD CT compared with EID CT (723.5 mm³ [IQR, 500.6-1184.7 mm³] vs 1084.7 mm³ [IQR, 710.7-1609.8 mm³]; <i>P</i> < .001). UHR-based segmentations produced lower fibrotic (325.4 mm³ [IQR, 151.7-519.2 mm³] vs 627.7 mm³ [IQR, 385.8-795.1 mm³], respectively; <i>P</i> < .001) and higher low-attenuation plaque volumes (72.1 mm³ [IQR, 38.6-161.9 mm³] vs 58.1 mm³ [IQR, 23.4-102.3 mm³], respectively; <i>P</i> = .004) than EID CT-based measurements. Calcified plaque volumes did not differ significantly between PCD CT and EID CT (344.5 mm³ [IQR, 174.3-605.7 mm³] vs 342.1 mm³ [IQR, 180.4-607.5 mm³], respectively; <i>P</i> = .13). Total, calcified, and fibrotic plaque volumes demonstrated excellent agreement between repeated measurements and between readers for both PCD CT and EID CT (all intraclass correlation coefficients [ICCs] > 0.90). Whereas low-attenuation plaque volume had strong intrareader (ICC, 0.84; 95% CI: 0.57, 0.94) and interreader (ICC, 0.92; 95% CI: 0.81, 0.97) agreements for PCD CT, EID CT showed only moderate (ICC, 0.62; 95% CI: 0.11, 0.86) and poor (ICC, 0.47; 95% CI: 0.01, 0.79) intrareader and interreader reproducibility. Conclusion Compared with EID CT, PCD CT UHR imaging reduced segmented coronary plaque volume by nearly one-third and improved reproducibility of low-attenuation plaque measurements. © RSNA, 2025 <i>Supplemental material is available for this article.</i></p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e241479"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543185","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}