Radiology最新文献

{"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":"Photon-counting CT-derived Quantification of Hepatic Fat Fraction: A Clinical Validation Study.","authors":"Tatjana Dell, Narine Mesropyan, Yannik Layer, Verena Tischler, Leonie Weinhold, Johannes Chang, Christian Jansen, Bernhard Schmidt, Markus Jürgens, Alexander Isaak, Patrick Kupczyk, Claus Christian Pieper, Carsten Meyer, Julian Luetkens, Daniel Kuetting","doi":"10.1148/radiol.241677","DOIUrl":"https://doi.org/10.1148/radiol.241677","url":null,"abstract":"<p><p>Background Steatosis is a critical health problem, creating a growing need for opportunistic screening. Early detection may allow for effective treatment and prevention of further liver complications. Purpose To evaluate photon-counting CT (PCCT) fat quantification on contrast-enhanced scans and validate the results against fat quantification via histopathologic assessment, controlled attenuation parameter (CAP) from transient elastography, and MRI proton density fat fraction (PDFF). Materials and Methods In this prospective, observational clinical study, PCCT-derived fat fraction quantification was assessed in participants with known or suspected liver disease. Participants underwent PCCT between February 2022 and January 2024. Participants also underwent biopsy, US with CAP measurement, or MRI with a PDFF sequence for hepatic fat fraction quantification. Liver fat fraction was measured on virtual noncontrast PCCT images using spectral processing software with a three-material decomposition algorithm for fat, liver tissue, and iodine. Steatosis was graded for each modality. Correlation between PCCT-based steatosis grades and biopsy- and CAP-based grades was assessed with the Spearman correlation coefficient. Agreement between PCCT and MRI PDFF measurements was assessed with the intraclass correlation coefficient. Receiver operating characteristic curve analysis was conducted to determine the optimal PCCT fat fraction threshold for distinguishing between participants with and those without steatosis. Results The study included 178 participants, of whom 27 (mean age, 60.7 years ± 15.2 [SD]; 18 male participants) underwent liver biopsy, 26 (mean age, 60.0 years ± 18.3; 15 male participants) underwent CAP measurement, and 125 (mean age, 61.2 years ± 13.1; 70 male participants) underwent MRI PDFF measurement. There was excellent agreement between PCCT and MRI PDFF assessment of liver fat fraction (intraclass correlation coefficient, 0.91 [95% CI: 0.87, 0.94]). In stratified analysis, the intraclass correlation coefficient was 0.84 (95% CI: 0.63, 0.93) in participants with known fibrosis and 0.92 (95% CI: 0.88, 0.94) in participants without fibrosis. There was moderate correlation of PCCT-based steatosis grade with histologic (ρ = 0.65) and CAP-based (ρ = 0.45) steatosis grade. Based on the Youden index, the PCCT fat fraction threshold that best discriminated between participants with and those without steatosis was 4.8%, with a maximum achievable sensitivity of 81% (38 of 47) and a specificity of 71% (55 of 78). Conclusion PCCT in a standard clinical setting allowed for accurate estimation of liver fat fraction compared with MRI PDFF-based reference standard measurements. © RSNA, 2025 See also the editorial by Kartalis and Grigoriadis in this issue.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e241677"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143658176","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":"Photon-counting CT: The New Kid on the Block for Liver Fat Quantification.","authors":"Nikolaos Kartalis, Aristeidis Grigoriadis","doi":"10.1148/radiol.250480","DOIUrl":"https://doi.org/10.1148/radiol.250480","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e250480"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143658221","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":"Value of Using a Generative AI Model in Chest Radiography Reporting: A Reader Study.","authors":"Eun Kyoung Hong, Byungseok Roh, Beomhee Park, Jae-Bock Jo, Woong Bae, Jai Soung Park, Dong-Wook Sung","doi":"10.1148/radiol.241646","DOIUrl":"https://doi.org/10.1148/radiol.241646","url":null,"abstract":"<p><p>Background Multimodal generative artificial intelligence (AI) technologies can produce preliminary radiology reports, and validation with reader studies is crucial for understanding the clinical value of these technologies. Purpose To assess the clinical value of the use of a domain-specific multimodal generative AI tool for chest radiograph interpretation by means of a reader study. Materials and Methods A retrospective, sequential, multireader, multicase reader study was conducted using 758 chest radiographs from a publicly available dataset from 2009 to 2017. Five radiologists interpreted the chest radiographs in two sessions: without AI-generated reports and with AI-generated reports as preliminary reports. Reading times, reporting agreement (RADPEER), and quality scores (five-point scale) were evaluated by two experienced thoracic radiologists and compared between the first and second sessions from October to December 2023. Reading times, report agreement, and quality scores were analyzed using a generalized linear mixed model. Additionally, a subset of 258 chest radiographs was used to assess the factual correctness of the reports, and sensitivities and specificities were compared between the reports from the first and second sessions with use of the McNemar test. Results The introduction of AI-generated reports significantly reduced average reading times from 34.2 seconds ± 20.4 to 19.8 seconds ± 12.5 (<i>P</i> < .001). Report agreement scores shifted from a median of 5.0 (IQR, 4.0-5.0) without AI reports to 5.0 (IQR, 4.5-5.0) with AI reports (<i>P</i> < .001). Report quality scores changed from 4.5 (IQR, 4.0-5.0) without AI reports to 4.5 (IQR, 4.5-5.0) with AI reports (<i>P</i> < .001). From the subset analysis of factual correctness, the sensitivity for detecting various abnormalities increased significantly, including widened mediastinal silhouettes (84.3% to 90.8%; <i>P</i> < .001) and pleural lesions (77.7% to 87.4%; <i>P</i> < .001). While the overall diagnostic performance improved, variability among individual radiologists was noted. Conclusion The use of a domain-specific multimodal generative AI model increased the efficiency and quality of radiology report generation. © RSNA, 2025 <i>Supplemental material is available for this article.</i> See also the editorial by Babyn and Adams in this issue.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e241646"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606272","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":"CT-guided Percutaneous Ethanol Sympatholysis for Hyperhidrosis: How I Do It.","authors":"Christos Georgiades","doi":"10.1148/radiol.241430","DOIUrl":"https://doi.org/10.1148/radiol.241430","url":null,"abstract":"<p><p>Hyperhidrosis, excessive sweating from the eccrine sweat glands, is caused by overactivity of the sympathetic nerves. Facial, axillary, and/or palmar hyperhidrosis (excessive sweating of the face, armpits, and hands) has a reported prevalence of 1%-1.6%. This condition is initially treated conservatively using a combination of topical and pharmacologic treatments. Surgical sympathectomy or percutaneous sympatholysis are treatment options for severe hyperhidrosis (grade 3 or 4) that does not respond to conservative management. The aim of intervention is to permanently disrupt the sympathetic signal by targeting the thoracic vertebral levels T2, T3, and T4 of the paravertebral ganglia, located on the anterolateral surface of the vertebral body. This review presents the step-by-step technique for CT-guided percutaneous ethanol sympatholysis and discusses patient selection for the procedure, potential complications, and treatment outcomes. Although more than 90% of patients report complete resolution of hyperhidrosis immediately after sympatholysis, as many as 40% report symptom recurrence within 6 months. The probability of remaining hyperhidrosis-free long term (ie, more than 6 months) after CT-guided sympatholysis is 60%. Procedural risks include a 15% risk of compensatory hyperhidrosis elsewhere in the body, 8% risk of Horner syndrome (mostly self-limiting), 5% risk of pneumothorax, and 3% risk of severe intercostal neuralgia due to nontarget ethanol deposition. Despite the risks, this intervention can be life-altering for those with severe disease.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e241430"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143658533","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":"Case 335: Accidental Intra-Arterial Injection of Contrast Material.","authors":"Thomas Saliba, Olivier Cappeliez, Sanjiva Pather, Henri Maisonnier","doi":"10.1148/radiol.241602","DOIUrl":"https://doi.org/10.1148/radiol.241602","url":null,"abstract":"<p><strong>History: </strong>An 84-year-old female patient presented for routine CT angiography (CTA) of the arteries of the neck following right carotid endarterectomy for 75% stenosis, which had been performed without incident 2 months prior. The patient had also been diagnosed with 72% stenosis of the left carotid artery, although it was asymptomatic and thus endarterectomy was not required. The medical history included arterial hypertension and an incomplete left bundle branch block. CTA was performed according to standard procedure, with the region of interest to initiate the examination being placed within the aortic arch and contrast material injected at 5 mL/sec via a catheter placed in the left antecubital fossa. The catheter was successfully tested, and the contrast material was subsequently injected without incident, with the patient reporting no pain and the automatic pressure sensor showing no anomalies. The scan was automatically launched because the attenuation within the aortic arch reached 800 HU.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 3","pages":"e241602"},"PeriodicalIF":12.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143701296","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":"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":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11950872/pdf/","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":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}