Radiology最新文献

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.

Background Contrast-enhanced mammography (CEM) is an emerging modality that generates low-energy (LE) images that are visually equivalent to full-field digital mammography (FFDM) and recombined images that show lesion vascularity such as MRI. Supplemental whole-breast US increases cancer detection rates when performed with FFDM but not with MRI. Purpose To compare the performance of CEM, LE images, and LE images supplemented with whole-breast US in breast cancer detection during screening. Materials and Methods This prospective study recruited female participants from December 2014 to February 2019 who were scheduled for screening mammography and whole-breast US. CEM (including LE images and recombined images) and whole-breast US images were interpreted by separate breast radiologists blinded to the findings on images from the other modality. Statistical differences in sensitivity and specificity, positive predictive value (PPV), negative predictive value, and abnormal interpretation rate were assessed. Biopsy recommendation rate and PPVs of biopsies performed (PPV₃) were calculated at the lesion level. Results Across 468 participants (median age, 54 years [IQR, 48-59 years]; all female participants), nine screen-detected cancers were diagnosed in eight participants: one cancer was depicted at LE imaging alone (cancer detection rate, 2.1 of 1000), four were depicted at LE imaging with whole-breast US (cancer detection rate, 8.5 of 1000), and eight were depicted at CEM (cancer detection rate, 17.1 of 1000; P < .05). The abnormal interpretation rate was 10.3% (48 of 468) for LE images, 13.7% (64 of 468) for LE images with whole-breast US, and 18.6% (87 of 468) for CEM (P < .001). The biopsy recommendation rate was 15.0 of 1000 for LE images, 38.4 of 1000 for LE images with whole-breast US, and 42.7 of 1000 for CEM. Seven biopsies were recommended based on LE images (PPV₃ of one of seven [14.3%]), 18 biopsies based on LE images with whole-breast US (with a PPV₃ of five of 18 [27.8%]), and 20 biopsies based on CEM (PPV₃ of 9 of 20 [45.0%]). Conclusion Breast cancer detection improved with CEM compared with LE images alone or LE images with whole-breast US. ClinicalTrials.gov Identifier: NCT02310698 © RSNA, 2025 Supplemental material is available for this article.

Background The US Liver Imaging Reporting and Data System (LI-RADS) includes an assessment category (US-1, negative; US-2, subthreshold; and US-3, positive) and a visualization score reflecting image quality (VIS-A, no or minimal limitations; VIS-B, moderate limitations; and VIS-C, severe limitations). The US-3 and VIS-C impact patient treatment. Purpose To establish the distributions of categories and visualization scores, estimate the proportions of hepatocellular carcinoma (HCC) and overall malignancy in the US-3 category, and identify variables associated with the VIS-C score by conducting a meta-analysis. Materials and Methods A systematic search of articles published between January 1, 2017, and September 17, 2023, identified studies reporting distributions of US LI-RADS version 2017 categories or visualization scores. Characteristics of the study design, patient cohorts, and outcomes of interest (distributions of US categories and visualization scores, percentages of probable or definite HCC and malignancy in US-3 category, and variables associated with VIS-C) were extracted. For the meta-analysis, estimates were established with random-effects models. Results Fifteen studies comprising 39 166 US examinations were included. Of all examinations, 89.7% (95% CI: 86.8, 91.8) were categorized US-1; 4.4% (95% CI: 2.8, 6.2), US-2; and 5.9% (95% CI: 4.1, 8.0), US-3. Of the US-3 examinations, 25.9% (95% CI: 17.1, 34.7) had probable or definite HCC and 26.4% (95% CI: 18.4, 34.5) had overall malignancy. Among all examinations, 59.7% (95% CI: 46.9, 67.8) were assigned VIS-A; 32.5% (95% CI: 21.9, 41.6), VIS-B; and 7.8% (95% CI: 2.8, 14.3), VIS-C. Obesity (odds ratio [OR], 2.37; 95% CI: 1.57, 3.59), nonalcoholic fatty liver disease (NAFLD) (OR, 2.24; 95% CI: 1.64, 3.06), and Child-Pugh B or C (OR, 2.41; 95% CI: 1.43, 4.06) were associated with VIS-C score. Conclusion Overall, 90% of surveillance US results were negative (US-1), and 92% were of adequate quality (VIS-A or VIS-B); 26% of patients with US-3 results had HCC. VIS-C was associated with obesity, NAFLD, and cirrhosis. Systemic review registry no. CRD42022384925 © RSNA, 2025 Supplemental material is available for this article.

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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.