Abdominal Radiology最新文献

{"title":"Combining clinical and radiological features improves prediction of bowel ischemia in patients with CT findings of pneumatosis intestinalis.","authors":"Francesca Rigiroli, Masoud Nakhaei, Ramy Karam, Nicolas Tabah, Alexander Brook, Bettina Siewert, Olga Rachel Brook","doi":"10.1007/s00261-025-04814-1","DOIUrl":"10.1007/s00261-025-04814-1","url":null,"abstract":"<p><strong>Background: </strong>Pneumatosis intestinalis on CT presents a diagnostic dilemma, because it could reflect bowel ischemia or benign finding.</p><p><strong>Purpose: </strong>To determine radiological and clinical features that can predict bowel ischemia in patients with pneumatosis intestinalis on CT.</p><p><strong>Materials and methods: </strong>Patients with \"pneumatosis\" in abdominal CT reports performed between 1/1/2002 and 12/31/2018 were retrospectively included. Pneumatosis intestinalis was confirmed by review of images. Radiological features of pneumatosis, laboratory data, clinical signs and symptoms were collected. Pathologic pneumatosis intestinalis (PPI) was defined as presence of ischemic (viable or dead) bowel on surgery or death during admission or within 30 days of discharge due to ischemia. Univariate statistical analysis was used to identify features associated with PPI, followed by multivariate logistic regression models.</p><p><strong>Results: </strong>A total of 313 consecutive patients with pneumatosis intestinalis (162 (52%) men, median age 67 years, IQR 55-78 years) were included. Pathologic pneumatosis intestinalis was present in 114/313 (36%) patients. Presence of arterial or venous thrombosis, porto-mesenteric gas, fat stranding, and location in the small bowel were significantly associated with PPI. A combined clinical and radiological model, which included age, WBC, creatinine, abdominal distention, rebound or guarding, shock, presence of porto-mesenteric gas and fat stranding showed an AUC of 0.85 for prediction of PPI, higher than models using clinical (AUC = 0.80, p = 0.005) or radiological factors (AUC = 0.80, p < 0.0001) alone.</p><p><strong>Conclusion: </strong>Improved prediction of pathological pneumatosis intestinalis can be achieved by a model incorporating both clinical and radiological features (AUC = 0.85)rather than by either clinical (AUC = 0.80) or radiological (AUC = 0.80) features alone.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3447-3456"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143051347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning.","authors":"Zhongxian Pan, Qiuyi Chen, Haiwei Lin, Wensheng Huang, Junfeng Li, Fanqi Meng, Zhangnan Zhong, Wenxi Liu, Zhujing Li, Haodong Qin, Bingsheng Huang, Yueyao Chen","doi":"10.1007/s00261-025-04804-3","DOIUrl":"10.1007/s00261-025-04804-3","url":null,"abstract":"<p><strong>Purpose: </strong>Intra-pancreatic fat deposition (IPFD) is closely associated with the onset and progression of type 2 diabetes mellitus (T2DM). We aimed to develop an accurate and automated method for assessing IPFD on multi-echo Dixon MRI.</p><p><strong>Materials and methods: </strong>In this retrospective study, 534 patients from two centers who underwent upper abdomen MRI and completed multi-echo and double-echo Dixon MRI were included. A pancreatic segmentation model was trained on double-echo Dixon water images using nnU-Net. Predicted masks were registered to the proton density fat fraction (PDFF) maps of the multi-echo Dixon sequence. Deep semantic segmentation feature-based radiomics (DSFR) and radiomics features were separately extracted on the PDFF maps and modeled using the support vector machine method with 5-fold cross-validation. The first deep learning radiomics (DLR) model was constructed to distinguish T2DM from non-diabetes and pre-diabetes by averaging the output scores of the DSFR and radiomics models. The second DLR model was then developed to distinguish pre-diabetes from non-diabetes. Two radiologist models were constructed based on the mean PDFF of three pancreatic regions of interest.</p><p><strong>Results: </strong>The mean Dice similarity coefficient for pancreas segmentation was 0.958 in the total test cohort. The AUCs of the DLR and two radiologist models in distinguishing T2DM from non-diabetes and pre-diabetes were 0.868, 0.760, and 0.782 in the training cohort, and 0.741, 0.724, and 0.653 in the external test cohort, respectively. For distinguishing pre-diabetes from non-diabetes, the AUCs were 0.881, 0.688, and 0.688 in the training cohort, which included data combined from both centers. Testing was not conducted due to limited pre-diabetic patients. Intraclass correlation coefficients between radiologists' pancreatic PDFF measurements were 0.800 and 0.699 at two centers, suggesting good and moderate reproducibility, respectively.</p><p><strong>Conclusion: </strong>The DLR model demonstrated superior performance over radiologists, providing a more efficient, accurate and stable method for monitoring IPFD and predicting the risk of T2DM and pre-diabetes. This enables IPFD assessment to potentially serve as an early biomarker for T2DM, providing richer clinical information for disease progression and management.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3685-3697"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12267358/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of MR fusion biopsy, systematic biopsy and combined biopsy on prostate cancer detection rate in 1229 patients stratified by PI-RADSv2 score on 3T multi-parametric MRI.","authors":"Hannah H Riskin-Jones, Alex G Raman, Rushikesh Kulkarni, Corey W Arnold, Anthony Sisk, Ely Felker, David S Lu, Leonard S Marks, Steven S Raman","doi":"10.1007/s00261-024-04753-3","DOIUrl":"10.1007/s00261-024-04753-3","url":null,"abstract":"<p><strong>Purpose: </strong>We analyzed the additional value of systematic biopsy (SB) to MR-Ultrasound fusion biopsy (MRgFbx) for detection of clinically significant prostate cancer (csPCa), as increased sampling may cause increased morbidity.</p><p><strong>Materials and methods: </strong>This retrospective study cohort was comprised of 1229 biopsy sessions between July 2016 and May 2020 in men who had a Prostate Imaging-Reporting and Data System (PI-RADSv2) category ≥ 3 lesion on 3 Tesla multiparametric MRI (3TmpMRI) and subsequent combined biopsy (CB; MRgFbx and SB) for suspected prostate cancer (PCa). Cancer detection rates (CDR) were calculated for CB, MRgFbx and SB in the study cohort and sub-cohorts stratified by biopsy history and PI-RADSv2 category. For 927 men with unilateral MR-visible lesions, SB CDR was additionally calculated for contralateral (SBc) and ipsilateral (SBi) subcohorts.</p><p><strong>Results: </strong>On CB, the CDR for csPCa was 54.8% (673/1229). CDR for csPCa was significantly higher for MRgFbx (50.0%, CI 47.1-52.8%) compared to SB (35.3%, CI 32.6-38.1%) for all PI-RADSv2 ≥ 3 categories (p < .05). The MRgFbx CDR for PI-RADSv2 categories 3, 4, and 5 were 81.5%, 88.5%, and 95.6% respectively. For unilateral lesion cases, significantly more csPCa was detected in the SBi compared to the SBc subcohort (30.1% (279/927) vs. 10.4%, (96/927), p < 0.001). The combination of MRgFbx and SBi detected csPCa in 97.0% (480) of the 495 csPCa detected by CB.</p><p><strong>Conclusion: </strong>MRgFbx had a higher CDR for csPCa than SB. While CB detected more csPCa than either method alone, in patients with a PI-RADSv2 category of 5, MRgFbx approximated the performance of CB. In unilateral lesion cases, SBc provided minimal added benefit.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3784-3793"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12267314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intracellular enhancement technique for gadoxetic acid-enhanced hepatobiliary-phase magnetic resonance imaging: evaluation of hepatic function.","authors":"Dara Fonseca, Yuko Nakamura, Toru Higaki, Shogo Maeda, Takashi Nishihara, Yoshitaka Bito, Masahiro Takizawa, Shota Kondo, Ryo Higashino, Shintaro Morishita, Yuji Akiyama, Shingo Fukuma, Tomokazu Kawaoka, Masataka Tsuge, Shiro Oka, Kazuo Awai","doi":"10.1007/s00261-025-04817-y","DOIUrl":"10.1007/s00261-025-04817-y","url":null,"abstract":"<p><strong>Purpose: </strong>To investigate the utility of intracellular enhancement (ICE) technique which suppresses signals from the extracellular space for the evaluation of hepatic function on gadoxetic acid-enhanced hepatobiliary-phase (HBP) images.</p><p><strong>Methods: </strong>We subjected 67 patients with suspected neoplastic hepatic lesions to gadoxetic acid-enhanced HBP imaging with and without ICE [i-HBP, conventional-HBP (c-HBP)]. A radiologist calculated the liver/spleen contrast (LSC) [LSC = signal intensity (SI) of liver/SI of spleen]. Receiver-operating analysis was used to evaluate the diagnostic value of the LSC on i-HBP- (i-LSC) and c-HBP images (c-LSC) to differentiate between Child-Pugh classes A and B.</p><p><strong>Results: </strong>Of the 67 patients, 57 were in Child-Pugh class A and 10 were in class B. For their differentiation, the area under the curve value of i-LSC was higher than of c-LSC (0.81 vs. 0.68).</p><p><strong>Conclusions: </strong>ICE technique can improve the accuracy of estimating hepatic function on HBP images.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3506-3515"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12267321/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiomics for prediction of perineural invasion in colorectal cancer: a systematic review and meta-analysis.","authors":"Ning Tang, Shicen Pan, Qirong Zhang, Jian Zhou, Zhiwei Zuo, Rui Jiang, Jinping Sheng","doi":"10.1007/s00261-024-04713-x","DOIUrl":"10.1007/s00261-024-04713-x","url":null,"abstract":"<p><strong>Background: </strong>Perineural invasion (PNI) in colorectal cancer (CRC) is a significant prognostic factor associated with poor outcomes. Radiomics, which involves extracting quantitative features from medical imaging, has emerged as a potential tool for predicting PNI. This systematic review and meta-analysis aimed to evaluate the diagnostic accuracy of radiomics models in predicting PNI in CRC.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted across PubMed, Embase, and Web of Science for studies published up to July 28, 2024. Inclusion criteria focused on studies using radiomics models to predict PNI in CRC with sufficient data to construct diagnostic accuracy metrics. The quality of the included studies was assessed using QUADAS-2 and METRICS tools. Pooled estimates of sensitivity, specificity, and area under the curve (AUC) were calculated. Subgroup analyses were performed based on imaging modalities, segmentation methods, and other variables.</p><p><strong>Results: </strong>Twelve studies comprising 2853 patients were included in the systematic review, with ten studies contributing to the meta-analysis. The pooled sensitivity and specificity for radiomics models in predicting PNI were 0.74 (95% CI: 0.63-0.82) and 0.85 (95% CI: 0.79-0.90), respectively, in the training cohorts. In the validation cohorts, the sensitivity was 0.65 (95% CI: 0.57-0.72), and specificity was 0.85 (95% CI: 0.81-0.89). The AUC was 0.87 (95% CI: 0.63-0.82) for the training cohorts and 0.84 (95% CI: 0.81-0.87) for the validation cohorts, indicating good diagnostic accuracy. The METRICS scores for the included studies ranged from 65.8 to 85.1%, with an overall average score of 67.25%, reflecting good methodological quality. However, significant heterogeneity was observed across studies, particularly in sensitivity and specificity estimates.</p><p><strong>Conclusion: </strong>Radiomics models show promise as a non-invasive tool for predicting PNI in CRC, with moderate to good diagnostic accuracy. However, the current study's limitations, including reliance on retrospective data, geographic concentration in China, and methodological variability, suggest that further research is needed. Future studies should focus on prospective designs, standardization of methodologies, and the integration of advanced machine-learning techniques to improve the clinical applicability and reliability of radiomics models in CRC management.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3415-3434"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Three-dimensional MRI follicle segmentation and counting using SegmentWithSAM in the diagnosis of polycystic ovary syndrome.","authors":"Anrong Zeng, Jing Lu, Ying Li","doi":"10.1007/s00261-025-04818-x","DOIUrl":"10.1007/s00261-025-04818-x","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to investigate the diagnostic performance of Follicle numbers measured on ultrasound (US), conventional magnetic resonance imaging (2D MRI), and three-dimensional (3D) MRI in patients with polycystic ovary syndrome (PCOS) and to compare the diagnostic efficacy of these imaging modalities.</p><p><strong>Method: </strong>In this prospective study, 58 PCOS patients and 60 healthy women underwent US, conventional 2D MRI, and 3D MRI. Clinical laboratory tests and ovarian volume were compared between PCOS and control groups. Follicle numbers measured on US (FN-US), 2D MRI (FN-2D), and 3D MRI (FN-3D) using SegmentWithSAM were compared between PCOS and control groups using receiver operating characteristic (ROC) curve analysis and the DeLong test.</p><p><strong>Results: </strong>Ovarian volume and follicle numbers were significantly higher in the PCOS group than in the control group. The diagnostic performance was found with FN-3D achieving the highest AUC of 0.94 (95% CI: 0.90-0.98), superior to that of US (0.80 [95% CI: 0.72-0.88]) and 2D MRI (0.90 [95% CI: 0.84-0.96]), respectively. Significant differences in the diagnostic efficacy of follicle counts were observed between US, conventional MRI, and 3D MRI, with 3D MRI showing superior results.</p><p><strong>Conclusion: </strong>3D MRI was superior to US and 2D MRI in diagnosing PCOS, with the ability to display small follicles.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3847-3855"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of a combined radiomic and clinical model based on contrast-enhanced ultrasound for preoperative prediction of CK19-positive hepatocellular carcinoma.","authors":"Li Liang, Jin-Shu Pang, Rui-Zhi Gao, Qiao Que, Yu-Quan Wu, Jin-Bo Peng, Xiu-Mei Bai, Qiong Qin, Quan-Quan Tang, Li-Peng Li, Yun He, Hong Yang","doi":"10.1007/s00261-025-04799-x","DOIUrl":"10.1007/s00261-025-04799-x","url":null,"abstract":"<p><strong>Purpose: </strong>We aimed to develop and validate a combined model integrating radiomic features derived from Contrast-Enhanced Ultrasound (CEUS) images and clinical parameters for preoperative prediction of CK19-positive status in hepatocellular carcinoma (HCC).</p><p><strong>Methods: </strong>A total of 434 patients who underwent CEUS and surgical resection from January 2020 to December 2023 were included. Patients were randomly divided into a training cohort (n = 304) and a validation cohort (n = 130). Radiomic features were extracted from multiphase CEUS images, including two-dimensional ultrasound (US), arterial, portal venous, and delayed phases, and combined to derive a Radscore model. Subsequently, a Combined Model was constructed using the Radscore and clinical parameters. Model performance was assessed using calibration, discrimination, and clinical utility.</p><p><strong>Results: </strong>Multivariate logistic regression analysis identified Radscore (OR = 10.054, 95% CI: 5.931-19.120, p < 0.001) and AFP levels > 200 ng/mL (OR = 5.027, 95% CI: 2.089-12.784, p < 0.001) as significant predictors in the combined model. The AUC (Area Under the Curve) for the Combined Model was 0.954 in the training cohort and 0.927 in the validation cohort, compared to 0.939 and 0.917 for the Radscore Model alone. Calibration curves demonstrated strong concordance between predicted and actual outcomes. Decision curve analysis (DCA) showed that both the Radscore Model and the Combined Model exhibited good net benefits across a wide range of threshold values in both the training and validation cohorts.</p><p><strong>Conclusion: </strong>The Radscore based on CEUS, combined with the serum markers AFP > 200 ng/L to construct a Combined Model, shows good predictive performance for CK19 + hepatocellular carcinoma (HCC).</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3516-3529"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143187927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can multiparametric MRI clear cell likelihood scores differentiate fat-Poor AML from CcRCC in subcentimeter lesions?","authors":"Ying Xiong, Yinglong Guo, Xiaoxia Li, Pingyi Zhu, Jianyi Qu, Shunfa Huang, Run Wang, Jianjun Zhou, Jianfeng Huang, Chenchen Dai","doi":"10.1007/s00261-025-04822-1","DOIUrl":"10.1007/s00261-025-04822-1","url":null,"abstract":"<p><strong>Objective: </strong>To investigate the potential of multiparametric MRI clear cell likelihood scores (ccLS) for differentiating between fat-poor angiomyolipoma (AML) and clear cell renal cell carcinoma (ccRCC) in subcentimeter Lesions (1 cm or smaller).</p><p><strong>Materials and methods: </strong>This retrospective study included consecutive patients with subcentimeter renal masses who underwent multiparametric MRI between September 2009 and September 2022 across three hospitals. Clinical and MRI findings were analyzed to differentiate between fat-poor AML and ccRCC. Lesions were categorized using the ccLS and receiver operating characteristic curve analysis was performed to assess ccLS performance.</p><p><strong>Results: </strong>Thirty-eight patients (mean age: 52 years ± 12; 19 women) with 39 lesions were included. Of the 39 lesions [mean size: 9.1 mm ± 1.0 (range, 6.0-10.0 mm)], 20 (51%) were ccRCC and 19 (49%) were fat-poor AML. Compared to the ccRCC, subcentimeter fat-poor AMLs were more likely to show hypointensity on T2WI (P < 0.001), homogeneous enhancement (P = 0.010), the presence of microscopic fat (P = 0.036), and the absence of a pseudocapsule (P = 0.020). The diagnostic percentage of fat-poor AML was 47% for a ccLS of 1 or 2, and ccRCC accounted for 75% in the ccLS 4 or 5 category. The AUC for discrimination was 0.846 (95% CI: 0.695-0.941, P < 0.001), with a sensitivity of 75.00% (95% CI: 50.9-91.3) and a specificity of 89.47% (95% CI: 66.9-98.7).</p><p><strong>Conclusion: </strong>Multiparametric MRI clear cell likelihood scores can potentially be used to differentiate between fat-poor AML and ccRCC in lesions 1 cm or smaller.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3599-3606"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143187914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Liver and pancreatic fat fractions as predictors of disease severity in acute pancreatitis: an MRI IDEAL-IQ study.","authors":"Kemal Panc, Hasan Gundogdu, Sumeyye Sekmen, Mustafa Basaran, Enes Gurun","doi":"10.1007/s00261-025-04809-y","DOIUrl":"10.1007/s00261-025-04809-y","url":null,"abstract":"<p><strong>Purpose: </strong>Metabolic dysfunction-associated steatotic liver disease (MASLD) and non-alcoholic fatty pancreatic disease (NAFPD) are metabolic diseases with rising incidence. Fatty infiltration may lead to dysfunction of the liver and pancreatic tissues. This study aims to quantify liver and pancreatic fat fractions and examine their correlation with disease severity in acute pancreatitis patients.</p><p><strong>Methods: </strong>The severity of acute pancreatitis was assessed using the revised Atlanta classification (RAC), computed tomography severity index (CTSI), and modified CTSI (mCTSI). Proton density fat fraction (PDFF) levels of the liver and pancreas were measured via IDEAL MRI. Patients were categorized into biliary and non-biliary pancreatitis groups. Correlations between PDFF levels and the RAC, CTSI, and mCTSI scores were analyzed.</p><p><strong>Results: </strong>A total of 127 patients were included, with MASLD present in 40.9% and NAFPD in 30%. Liver PDFF values were significantly higher in non-biliary pancreatitis (p = 0.040). Patients with MASLD exhibited higher CTSI and mCTSI scores (p = 0.009, p = 0.033, respectively). No significant differences were observed in severity scales between patients with and without NAFPD. Liver PDFF was positively correlated with CTSI and mCTSI scores in biliary pancreatitis. ROC analysis identified a liver PDFF > 3.9% (p = 0.002) and pancreatic corpus PDFF > 12.1% (0.028) as diagnostic markers for severe pancreatitis. In addition, a liver PDFF < 4.5% (p = 0.042) was an indicator for biliary pancreatitis.</p><p><strong>Conclusion: </strong>MASLD is associated with increased severity in acute pancreatitis. IDEAL MRI-derived PDFF levels of the liver and pancreas show potential in predicting severe acute pancreatitis and distinguishing between biliary and non-biliary etiologies.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3734-3743"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12267334/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Layering hyperintensity in T1-weighted magnetic resonance imaging predicts gallbladder sludge: a retrospective cohort and diagnostic accuracy study in patients with significant liver disease.","authors":"Rosa Alba Pugliesi, Timo Siepmann, Daniel P O Kaiser","doi":"10.1007/s00261-024-04756-0","DOIUrl":"10.1007/s00261-024-04756-0","url":null,"abstract":"<p><strong>Background: </strong>Layering hyperintensity in the gallbladder is frequently observed on T1-weighted (T1w) magnetic resonance imaging (MRI), but its association with hepatobiliary disorders is not well understood.</p><p><strong>Objective: </strong>This study aimed to evaluate the prevalence of T1w layering in the gallbladder and its correlation with ultrasound (US) findings and patient characteristics in a cohort with significant liver disease.</p><p><strong>Methods: </strong>A single-center study from 2015 to 2022 included patients who underwent MRI and abdominal US within one week. Exclusion criteria were poor imaging quality and prior cholecystectomy. MRI findings were correlated with US and analyzed against patient characteristics.</p><p><strong>Results: </strong>Among 415 patients (mean age 58.3 ± 14.8 years; mean BMI 28.0 ± 4.5 kg/m²), 67% had abnormal liver function tests, with high prevalences of cirrhosis (n = 260), transjugular intrahepatic portosystemic shunt (TIPS) (n = 233), and choledocholithiasis (n = 106). T1w layering was observed in 56% (n = 232) and associated with higher BMI (p = 0.001) and with cholecystolithiasis (p < 0.001), but not with age, sex, or liver disease indicators. T1w layering was predictive of gallbladder sludge on US (odds ratio 17.2, 95% confidence interval 9.87-31.44, p < 0.001), with a sensitivity of 92.7% but moderate specificity (57.9%).</p><p><strong>Conclusion: </strong>T1w layering on MRI strongly predicts gallbladder sludge detected on US and is associated with increased BMI in this cohort of patients with liver disease. However, the moderate specificity requires cautious interpretation, and our findings suggest that T1w layering may serve as a complementary diagnostic tool.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3553-3559"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12267354/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143187931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}