Abdominal radiology (New York)最新文献

{"title":"Mucinous cystic neoplasm of the liver with biliary prolapse mimicking intraductal papillary neoplasm of the bile duct: a case report.","authors":"Naotoshi Hatsuda, Toshiyuki Sato, Suzune Tsukamoto, Shunsuke Ito, Hirokazu Sawamura, Saya Ando, Kaori Kuriyama, Naoko Matsubara, Kotaro Shimada, Kazuna Kawabata, Mitsunori Kanagaki, Ryuta Nishitai, Hiroyuki Kimura","doi":"10.1007/s00261-026-05507-z","DOIUrl":"10.1007/s00261-026-05507-z","url":null,"abstract":"<p><p>Mucinous cystic neoplasm of the liver (MCN-L) is a rare cyst-forming epithelial neoplasm that typically lacks bile duct communication. Intraductal protrusion is uncommon and can mimic cystic intraductal papillary neoplasm of the bile duct (IPNB). A 39-year-old woman undergoing fertility treatment presented with recurrent hyperbilirubinemia and predominantly cholestatic liver test abnormalities. MRI demonstrated a 10.5-cm multilocular cystic lesion in segment 4 of the liver with downstream biliary dilatation, and internal septa were visible within the dilated bile duct on T2-weighted single-shot fast spin-echo (SSFSE) images. Contrast-enhanced computed tomography (CT) revealed enhanced cyst wall and septa, while endoscopic retrograde cholangiography revealed a smooth, oval-shaped filling defect. Endoscopic and intraductal ultrasonography indicated septate cystic components of the bile duct, and biopsy revealed mucin-producing columnar epithelium overlying the ovarian-like stroma, confirming MCN. The patient was treated via extended left hepatectomy with extrahepatic bile duct resection and reconstruction. Pathological examination revealed low-grade intraepithelial neoplasia. The patient remained recurrence-free for 20 months. This case suggests that, although biliary communication usually favors cystic IPNB over MCN-L, identification of intraductal extension of the cyst wall or septa within the dilated bile duct may provide an important clue to the diagnosis of MCN-L.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":"5989-5992"},"PeriodicalIF":2.2,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147794777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy and precision of automated kidney stone detection on CT.","authors":"Charat Thongprayoon, Andrea Ferrero, Tubo Shi, John C Lieske, Kevin Koo, Theodora A Potretzke, Brandon R Grossardt, Aidan F Mullan, Cole J Cook, Cynthia H McCollough, Timothy L Kline, Andrew D Rule","doi":"10.1007/s00261-026-05499-w","DOIUrl":"10.1007/s00261-026-05499-w","url":null,"abstract":"<p><strong>Background: </strong>While computed tomography (CT) is the preferred imaging modality for kidney stone detection and measurement, quantifying the accuracy and precision of stone size metrics is needed, particularly with the growing use of automated image analysis tools to measure kidney stone size.</p><p><strong>Methods: </strong>A phantom study was conducted using 120 kidney stones of various known maximum diameters (ranging from 1.4 to 9.9 mm) and compositions (60 calcium, 30 uric acid, and 30 mixed calcium and uric acid). The stones were placed in an anthropomorphic phantom and CT images were reconstructed with slice thicknesses of 1, 3, or 5 mm and processed using an in-house quantitative Stone Analysis Software (qSAS) to detect each stone and determine its maximum diameter. Separately, we also assessed the agreement between qSAS and a radiologist in determining the maximum diameter of 45 kidney stones on CT images (1-mm slice) from patients.</p><p><strong>Results: </strong>Stone detection frequencies by qSAS for stones in phantoms were 100%, 93%, and 86% for 1-, 3-, and 5-mm CT slice thicknesses, respectively. The proportion of qSAS-detected stones with a diameter error > 1 mm was 5%, 28%, and 64% for 1-, 3-, and 5-mm CT slice thickness, respectively. The CT-measured diameters on 1-mm images were accurate regardless of stone composition. However, diameters with thicker slices trended toward underestimation in uric acid stones and overestimation in calcium and mixed stones. Stone diameter by a radiologist was relatively unbiased but had limited precision with a diameter error > 1 mm occurring in 51% compared to qSAS.</p><p><strong>Conclusions: </strong>This study quantifies the improved precision with an automated assessment of stone diameter on CT as well as the bias and imprecision that remains across different slice thicknesses and stone compositions.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":"5930-5938"},"PeriodicalIF":2.2,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147978446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRI T1 signal intensity ratios correlate with fibrosis in recurrent acute and chronic pancreatitis.","authors":"Aida A Metri, Mahya Faghih, Elizabeth Thompson, Michael Noë, Rifat Mannan, Rita Kalyani, Elham Afghani, Venkata S Akshintala, Daniel Warren, Niraj M Desai, Zhaoli Sun, Christi Walsh, Martin Makary, Ralph Hruban, Jin He, Vikesh K Singh, Atif Zaheer","doi":"10.1007/s00261-026-05555-5","DOIUrl":"10.1007/s00261-026-05555-5","url":null,"abstract":"<p><strong>Purpose: </strong>T1 signal intensity ratio (SIR) on MRI has not been rigorously evaluated as a noninvasive method to detect pancreatic fibrosis in patients undergoing surgery for recurrent acute (RAP) and chronic pancreatitis (CP). The aim of our study was to evaluate the association between histologic fibrosis score (FS) and T1 SIR and contrast enhancement of the pancreas on MRI among patients with RAP and CP undergoing total pancreatectomy with islet autotransplantation (TPIAT).</p><p><strong>Methods: </strong>Patients who underwent MRI < 6 months before TPIAT between 2011 and 2023 were classified into 3 groups: definite CP (n = 23) and indeterminate CP (n = 11) by M-ANNHEIM criteria; and RAP defined as ≥ 2 episodes of imaging-documented acute pancreatitis (n = 22). The perilobular and intralobular fibrosis of each surgical biopsy was scored from 0 to 6. The FS was the sum of perilobular and intralobular fibrosis (0-12). We measured the T1 signal intensity of the pancreas and reference organs using pre-contrast T1-weighted fat-saturated (T1WFS) sequences to obtain the T1 SIR. We also measured the T1 signal intensity of the pancreas in the pre-contrast, arterial, venous, and delayed phases.</p><p><strong>Results: </strong>A total of 56 patients were included. The median FS was 6.25 (range 0-12). Pancreas-to-spleen T1 SIR (p = 0.004) and pancreas-to-paraspinal T1 SIR (p = 0.03) were significantly associated with pancreatic fibrosis after adjusting for age, BMI, exocrine insufficiency, fat fraction, diabetes mellitus, and clinical diagnosis. Analysis of the enhancement curves showed that the venous phase of T1 signal intensity can differentiate between indeterminate CP, RAP and definite CP (p < 0.004 for all).</p><p><strong>Conclusion: </strong>Both the T1 SIR of the pancreas-to-spleen and pancreas-to-paraspinal muscle show an independent association with fibrosis. T1 SIR demonstrates a significant association with histologically quantified pancreatic fibrosis and may serve as a promising noninvasive imaging biomarker pending further validation.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":"5978-5988"},"PeriodicalIF":2.2,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148008485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intratumoral habitat imaging for progression-free survival prediction of patients with high-risk, non-metastatic clear cell renal cell carcinoma.","authors":"Feng Zhang, Yaoyao Wu, Zhengyu Hu, Piao Yang, Wenting Lan, Zhi Li, Zhan Feng","doi":"10.1007/s00261-026-05527-9","DOIUrl":"10.1007/s00261-026-05527-9","url":null,"abstract":"<p><strong>Purpose: </strong>Accurate risk stratification for patients with high-risk, non-metastatic clear cell renal cell carcinoma (ccRCC) remains a clinical challenge. Our aim is to develop and validate an imaging model based on intratumoral habitat imaging for non-invasive assessment of progression-free survival (PFS) in this high-interest population.</p><p><strong>Methods: </strong>A retrospective analysis was performed on a cohort of 220 patients with ccRCC from three hospitals. Preoperative CT images and clinical data were comprehensively analyzed. K-mean clustering method was used to generate habitat subregions using contrast-enhanced CT images. Radiomic features were extracted from habitat subregions and the entire tumor, Random Survival Forest for PFS prediction were constructed using conventional radiomics features, habitat subregions-derived radiomics. Model evaluation included calibration curve, receiver operating characteristic curve (ROC) and Kaplan-Meier survival analysis.</p><p><strong>Results: </strong>The Habitat 3 model demonstrated favorable prognostic performance. In the training cohort, 1-, 3-, and 5-year AUCs were 0.92, 0.92, and 0.78, respectively. In the external test set, the model maintained robustness with 1-, 3-, and 5-year AUCs of 0.87, 0.74, and 0.94, outperforming traditional radiomics and other Habitat models. Furthermore, patients stratified by Habitat 3 showed significant survival differences between high-risk and low-risk groups in both cohorts.</p><p><strong>Conclusion: </strong>We proposed a habitat-based imaging technique for the preliminary analysis of high-risk ccRCC. This retrospective study suggests that habitat signatures are associated with PFS, serving as a potential non-invasive complement to provide insights into tumor heterogeneity.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":"5918-5929"},"PeriodicalIF":2.2,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147960584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative evaluation of conventional radiomics and VGG-SAM fusion strategies for MRI-based preoperative prediction of perineural invasion in cervical cancer.","authors":"Lihua Tan, Yanwei Xia, Da Teng, Dan Zhao","doi":"10.1007/s00261-026-05559-1","DOIUrl":"10.1007/s00261-026-05559-1","url":null,"abstract":"<p><strong>Objective: </strong>Perineural invasion (PNI) is an adverse feature in cervical cancer and may influence nerve-sparing surgery. We compared conventional radiomics and VGG-SAM deep-learning strategies for MRI-based preoperative prediction of PNI.</p><p><strong>Methods: </strong>A retrospective cohort of 103 patients with cervical cancer, including 82 PNI-negative and 21 PNI-positive patients, was analyzed. PyRadiomics features were extracted from raw DICOM MRI and paired tumor masks. Four deep variants were evaluated: VGG only, SAM only, VGG + SAM naive fusion, and VGG + SAM learnable fusion. Patient-level stratified five-fold cross-validation was used. Primary metrics were sensitivity, specificity, balanced accuracy, F1-score, ROC-AUC, and PR-AUC. Uncertainty for the naive-versus-learnable comparison was assessed with 10,000 paired bootstrap resamples and exact McNemar tests.</p><p><strong>Results: </strong>The strongest radiomics baseline, PyRadiomics + XGBoost, achieved balanced accuracy 0.6057, F1-score 0.3684, ROC-AUC 0.6731, and PR-AUC 0.4460. Naive VGG + SAM fusion achieved the best sensitivity (0.5714), balanced accuracy (0.7491), F1-score (0.6154), ROC-AUC (0.7854), and PR-AUC (0.6231). Learnable fusion achieved the highest specificity (0.9634) and precision (0.7500) while matching the highest accuracy (0.8544). Paired bootstrap comparisons showed wide confidence intervals across clinically relevant metrics.</p><p><strong>Conclusion: </strong>Hybrid VGG-SAM modeling outperformed conventional radiomics alone, but greater fusion complexity did not yield uniform benefit. Naive fusion favored sensitivity-oriented discrimination, whereas learnable fusion mainly shifted the operating point toward higher specificity. Larger multi-institutional cohorts and clinical comparators are needed.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":"5971-5977"},"PeriodicalIF":2.2,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147990498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRI-proton density fat fraction accurately reflects hepatic steatosis despite concomitant inflammation and fibrosis in a MASLD rat model.","authors":"Yuxi Ding, Jianxin Pang, Ruoxi Li, Jili Wang, Feng Zhao","doi":"10.1007/s00261-026-05566-2","DOIUrl":"10.1007/s00261-026-05566-2","url":null,"abstract":"<p><strong>Background: </strong>Magnetic resonance imaging-proton density fat fraction (MRI-PDFF) is a noninvasive biomarker for hepatic steatosis, but its quantitative reliability in the presence of inflammation or fibrosis remains incompletely defined.</p><p><strong>Methods: </strong>Forty rats were fed a methionine-and choline-deficient (MCD) diet for 2, 4, 6, 8, or 10 weeks (n = 8 per time point), while eight additional rats served as controls. All animals underwent MRI-PDFF examination immediately prior to sacrifice, followed by histopathologic assessment within 4 h using the NASH Clinical Research Network scoring system. Associations between PDFF and histologic fat content, steatosis grade, inflammation, and fibrosis were analyzed using Pearson and Spearman correlations, with subgroup analyses performed in animals with fibrosis.</p><p><strong>Results: </strong>MRI-PDFF showed a near-perfect correlation with histologic fat percentage in the entire cohort (r = 0.994, p < 0.0001), which remained strong in animals with fibrosis (r = 0.983, p < 0.0001). PDFF was also strongly associated with steatosis grade overall (ρ = 0.893, p < 0.0001) and within the fibrosis subgroup (ρ = 0.727, p < 0.0001). In contrast, PDFF values did not differ significantly across inflammation grades and were comparable between animals with and without lobular inflammation (all p > 0.05). Intra-scan reproducibility of PDFF was excellent (intraclass correlation coefficient (ICC) = 0.935).</p><p><strong>Conclusions: </strong>MRI-PDFF provides a robust and reproducible quantitative assessment of hepatic steatosis in the MCD rat model of MASLD. Its quantitative relationship with hepatic fat burden and steatosis grade is preserved in animals with concomitant fibrosis and is not materially influenced by inflammatory activity.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":"5950-5958"},"PeriodicalIF":2.2,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147978264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A clinical and contrast-enhanced CT-based model for preoperative prediction of CK19- and GPC3-positive dual-phenotype hepatocellular carcinoma.","authors":"Yi Long, Wanli Zhang, Zongqiao Ren, Jiamin Li, Bo Li, Enhui Chang, Boxuan Zheng, Mingyong Gao, Xinqing Jiang, Ruimeng Yang","doi":"10.1007/s00261-026-05541-x","DOIUrl":"10.1007/s00261-026-05541-x","url":null,"abstract":"<p><strong>Objective: </strong>To explore the predictive value of preoperative clinical and multiphase dynamic contrast-enhanced CT (CECT)-based qualitative and quantitative features for identifying Cytokeratin 19 (CK19)- and Glypican 3 (GPC3)-positive dual-phenotype hepatocellular carcinoma (DPHCC_CG+).</p><p><strong>Materials and methods: </strong>A total of 363 HCC patients who received preoperative CECT and surgical resection from two medical centers were retrospectively included. Patients were divided into DPHCC_CG+ (CK19- and GPC3-positive) or Non-DPHCC_CG+ (CK19- and/or GPC3-negative) groups based on histopathology. Qualitative and quantitative CECT features, along with clinical variables, were compared between the two groups. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of DPHCC_CG+. Three predictive models (CT qualitative-clinical, CT quantitative-clinical and combined model) were developed in the training cohort and externally validated. Model performance was assessed and compared using receiver operating characteristic (ROC) analysis and the DeLong test.</p><p><strong>Results: </strong>Both the CT qualitative-clinical and CT quantitative-clinical models demonstrated good predictive performance for identifying DPHCC_CG + in both the training and external validation cohorts (AUCs > 0.79). Independent predictors of DPHCC_CG+ included serum AFP ≥ 400 ng/mL, presence of mosaic appearance, arterial phase tumor-to-aorta attenuation ratio (A-TAR ≤ 0.262), and delayed phase normalized washout ratio (D-NWR ≤ -0.141). The combined model integrating these predictors achieved optimal diagnostic performance, with AUCs of 0.878 (95% CI: 0.822-0.935) in the training cohort and 0.806 (95% CI: 0.723-0.889) in the external validation cohort.</p><p><strong>Conclusion: </strong>The combined model integrating preoperative serum AFP level with CECT qualitative and quantitative parameters enables effective, noninvasive identification of DPHCC_CG+ before treatment, providing potential clinical value for risk stratification and personalized management of HCC patients.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":"5959-5970"},"PeriodicalIF":2.2,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147990416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical indicators combined with spectral CT in differentiating non-muscle-invasive bladder urothelial carcinoma from cystitis glandularis.","authors":"Yinping Han, Yingxia She, Jinyan Wei, Xueling Zhang, Junlin Zhou","doi":"10.1007/s00261-026-05546-6","DOIUrl":"10.1007/s00261-026-05546-6","url":null,"abstract":"<p><strong>Purpose: </strong>To investigate the diagnostic value of various indicators and models for the differential diagnosis of non-muscle-invasive bladder urothelial carcinoma (NIBUC) and cystitis glandularis (CG).</p><p><strong>Methods: </strong>A retrospective analysis was performed using clinical and spectral computed tomography (CT) data from consecutive patients at  Lanzhou University Second Hospital between January 2022 and January 2024. All patients underwent unenhanced arterial- and venous-phase spectral CT. Regions of interest were manually placed on the largest cross-section of the lesion. Iodine concentration (IC) and 40-70 keV monoenergetic CT values were measured in arterial and venous phases. The slope of the spectral CT-mono-energetic curve (40 and 70 keV; λHU) was calculated. Logistic regression analysis was used to construct two predictive models: one combining significant clinical indicators + conventional CT, and the other combining clinical indicators + conventional CT. +spectral CT parameters. The diagnostic performance was evaluated using receiver operating characteristic curve analysis.</p><p><strong>Results: </strong>Thirty-nine patients with NIBUC and 21 patients with CG, all pathologically confirmed by surgery, were included. Differences in age, lower urinary tract symptoms, and maximum lesion diameter were significant between the two groups (all P < 0.05). The IC and the slope of the spectral CT monoenergetic curve in the arterial and venous phases were significantly higher in the NIBUC group than in the CG group (all P < 0.05). The arterial-phase spectral curve slope showed good diagnostic performance among the arterial- and venous-phase IC and spectral curve slopes (area under the curve [AUC] = 0.879). The combined model CI-CCT-λHU, incorporating statistically significant clinical indicators, conventional CT parameters, and arterial phase spectral curve slope, achieved the best diagnostic accuracy (AUC = 0.919).</p><p><strong>Conclusion: </strong>The arterial phase spectral curve slope provided good diagnostic efficacy for differentiating NIBUC from CG. A CI-CCT-λHU model combining clinical indicators, conventional CT, and arterial phase spectral curve slope can further improve the accuracy of differential diagnosis for these two lesions.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":"5939-5949"},"PeriodicalIF":2.2,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147978227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-based CT radiomics for identifying high risk esophageal varices of bleeding in hepatocellular carcinoma.","authors":"Ping-Chien Li, Cheng-Yu Ma, Shih-An Chang, Chien-Cheng Chen","doi":"10.1007/s00261-026-05808-3","DOIUrl":"https://doi.org/10.1007/s00261-026-05808-3","url":null,"abstract":"<p><strong>Purpose: </strong>Esophageal variceal (EV) bleeding is a lethal complication in patients with hepatocellular carcinoma (HCC). Current risk stratification relies on invasive endoscopy or systemic surrogates of liver cirrhosis. This study aimed to develop a machine learning model utilizing EV-specific CT radiomics to identify high-risk esophageal varices, as defined by endoscopic criteria, in patients with HCC.</p><p><strong>Methods: </strong>151 HCC patients were enrolled and divided into a training cohort (n = 101; 75 high-risk; January 2017 - December 2022) and an independent temporal validation cohort (n = 50; 29 high-risk; January 2023 - December 2024). Endoscopic stigmata were used as an endpoint, including active bleeding or varices with high-risk features. Radiomic features were extracted from contrast-enhanced CT images acquired within six months prior to endoscopy. Model performance was evaluated using the area under the curve (AUC) of receiver operating characteristic (ROC), Brier score, calibration curves, and decision curve analysis (DCA).</p><p><strong>Results: </strong>In the training cohort, the varix-specific radiomics signature developed via the least absolute shrinkage and selection operator (LASSO) demonstrated excellent discriminative power (cross-validated AUC: 0.956; 95% CI 0.872-1.000). In the temporal validation cohort, this model maintained high generalizability, yielding an AUC of 0.926 (95% CI 0.846-0.984, sensitivity: 93.1%, specificity: 71.4%) as well as a Brier score of 0.1186 and good calibration (intercept = -0.157, slope = 1.354). Surface-to-Volume Ratio (SVR) and NGTDM Coarseness are feasible radiomics.</p><p><strong>Conclusion: </strong>The varix-specific radiomics model provides highly sensitive and mathematically stable non-invasive risk stratification for EV bleeding in patients with HCC.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149229795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structured MRI reporting for deep pelvic endometriosis: objective report quality and surgeon-perceived clinical utility in a randomized comparative study.","authors":"Louis Burgart, Aline Host, Victor Gabriele, Valentin Ance, Valentin Bernard, Pierre Blonde, Mariem Eleuch, Rodolphe Jochem, Baptiste Labetowiez, Gaspard Ludes, Julien Messie, Thibaut Moerckel, Melanie Ribeiro, Eloise Sossavi, Amandine Streiff, Adrien Walch, Clement Xu, Ludivine Tochon, Catherine Roy, Sebastien Molière","doi":"10.1007/s00261-026-05838-x","DOIUrl":"https://doi.org/10.1007/s00261-026-05838-x","url":null,"abstract":"<p><strong>Objectives: </strong>To compare structured and free-text MRI reporting in terms of objective report quality and surgeon ratings of perceived clinical utility in suspected deep pelvic endometriosis.</p><p><strong>Materials and methods: </strong>In this single-center randomized reader study, 20 radiology residents were assigned to free-text or structured reporting. Five residents became unavailable before report generation and provided no outcome data. The remaining 15 readers completed the same 22 pelvic MRI examinations, generating 330 reports: 154 free-text and 176 structured reports. Reports were compared with an imaging reference standard established by two pelvic radiologists through independent review and consensus adjudication. The primary endpoint was clinically weighted completeness. Secondary endpoints included unweighted completeness, explicit negative discrepancies relative to the expert imaging reference, positive findings unsupported by the expert imaging reference, and reporting time. Objective outcomes were analyzed using mixed-effects models or Poisson generalized estimating equations. In an exploratory paired assessment, two expert gynecologic surgeons evaluated 44 reports, comprising one free-text and one structured report for each MRI examination.</p><p><strong>Results: </strong>Structured reporting was associated with an 8.1%-point increase in completeness compared with free-text reporting (95% CI, 4.1-12.1; p < 0.001) and a 5.6%-point increase in clinically weighted completeness (95% CI, 1.3-10.0; p = 0.011). Reporting time was 4.52 min longer with structured reporting (95% CI, 3.05-5.99; p < 0.001). Structured reporting was also associated with more explicit negative discrepancies relative to the expert imaging reference (rate ratio, 2.94; 95% CI, 1.73-4.98; p < 0.001). These discrepancies were mainly explicit compartment-based negative statements. In the exploratory surgeon assessment, structured reports received higher ratings for perceived completeness, usefulness for clinical decision-making, and adequacy to clinical needs, whereas clarity ratings were similar between formats.</p><p><strong>Conclusion: </strong>Structured MRI reporting was associated with higher objective completeness and, in an exploratory assessment, higher surgeon ratings for several dimensions of perceived clinical utility. These findings should be balanced against longer reporting time and more explicit negative discrepancies relative to the expert imaging reference.</p>","PeriodicalId":520541,"journal":{"name":"Abdominal radiology (New York)","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149217952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}