Abdominal Radiology最新文献

{"title":"Correction to: Impact of anatomical features of non-thrombotic left iliac venous compression on the development of venous leg ulcers based on CT venography.","authors":"Fandong Li, Xiaojie Lian, Mengtao Wu, Deqing Zhang, Dianjun Tang, Qiang Sun","doi":"10.1007/s00261-025-04850-x","DOIUrl":"10.1007/s00261-025-04850-x","url":null,"abstract":"","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3905"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143699341","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":"Corrigendum to \"Computed tomography-based prediction model for identifying patients with high probability of non-muscle-invasive bladder cancer\" [Abdominal Radiology (2024) 49:163-172.].","authors":"Sung Yoon Park","doi":"10.1007/s00261-024-04763-1","DOIUrl":"10.1007/s00261-024-04763-1","url":null,"abstract":"","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":"3374-3375"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142863011","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":"Correction to: Evaluation value of contrast enhanced ultrasound quantitative parameters in ischemic-type biliary lesions after liver transplantation—a prospectively study","authors":"Ying Feng, Li Li, Wanwan Wen, Xiangdong Hu, Linxue Qian, Yujiang Liu, Zhanxiong Yi, Enhui He, Ruifang Xu","doi":"10.1007/s00261-025-04946-4","DOIUrl":"10.1007/s00261-025-04946-4","url":null,"abstract":"","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":"50 8","pages":"3904 - 3904"},"PeriodicalIF":2.2,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144176416","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":"A computed tomography-based radiomics prediction model for BRAF mutation status in colorectal cancer.","authors":"Boqi Zhou, Huaqing Tan, Yuxuan Wang, Bin Huang, Zhijie Wang, Shihui Zhang, Xiaobo Zhu, Zhan Wang, Junlin Zhou, Yuntai Cao","doi":"10.1007/s00261-025-04983-z","DOIUrl":"https://doi.org/10.1007/s00261-025-04983-z","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of this study was to develop and validate CT venous phase image-based radiomics to predict BRAF gene mutation status in preoperative colorectal cancer patients.</p><p><strong>Methods: </strong>In this study, 301 patients with pathologically confirmed colorectal cancer were retrospectively enrolled, comprising 225 from Centre I (73 mutant and 152 wild-type) and 76 from Centre II (36 mutant and 40 wild-type). The Centre I cohort was randomly divided into a training set (n = 158) and an internal validation set (n = 67) in a 7:3 ratio, while Centre II served as an independent external validation set (n = 76). The whole tumor region of interest was segmented, and radiomics characteristics were extracted. To explore whether tumor expansion could improve the performance of the study objectives, the tumor contour was extended by 3 mm in this study. Finally, a t-test, Pearson correlation, and LASSO regression were used to screen out features strongly associated with BRAF mutations. Based on these features, six classifiers-Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), K-Nearest Neighbors (KNN), and Extreme Gradient Boosting (XGBoost)-were constructed. The model performance and clinical utility were evaluated using receiver operating characteristic (ROC) curves, decision curve analysis, accuracy, sensitivity, and specificity.</p><p><strong>Results: </strong>Gender was an independent predictor of BRAF mutations. The unexpanded RF model, constructed using 11 imaging histologic features, demonstrated the best predictive performance. For the training cohort, it achieved an AUC of 0.814 (95% CI 0.732-0.895), an accuracy of 0.810, and a sensitivity of 0.620. For the internal validation cohort, it achieved an AUC of 0.798 (95% CI 0.690-0.907), an accuracy of 0.761, and a sensitivity of 0.609. For the external validation cohort, it achieved an AUC of 0.737 (95% CI 0.616-0.847), an accuracy of 0.658, and a sensitivity of 0.667.</p><p><strong>Conclusions: </strong>A machine learning model based on CT radiomics can effectively predict BRAF mutations in patients with colorectal cancer. The unexpanded RF model demonstrated optimal predictive performance.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144075235","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":"Low-osmolar contrast tagging in minimally cathartic CT colonography for colorectal cancer screening: an observational study.","authors":"Anna Eligulashvili, Zina Ricci, Devaraju Kanmaniraja, David Rezko, Kenny Q Ye, Judy Yee","doi":"10.1007/s00261-025-04971-3","DOIUrl":"https://doi.org/10.1007/s00261-025-04971-3","url":null,"abstract":"<p><strong>Objectives: </strong>Adequate bowel preparation and tagging are critical in optimizing CTC performance. Iohexol has a higher safety profile than other available tagging agents. This study aims to determine if iohexol serves as an adequate fluid and stool tagging agent in conjunction with minimally cathartic bowel preparation.</p><p><strong>Methods: </strong>In this prospective observational study, 50 participants ingested 50 mL of oral iohexol for tagging and 10 oz magnesium citrate for bowel preparation prior to CTC. Written informed consent was obtained. CTC was performed in all participants in at least two of the standard four positions (supine, prone, right decubitus, and left decubitus). Two board-certified abdominal radiologists independently scored the 6 colonic segments of participants who underwent successful CTC. The amount of residual fluid and solid stool, attenuation of tagged fluid, and efficacy of fluid and stool tagging were recorded in each segment. Statistical analyses were performed with R-4.4.0.</p><p><strong>Results: </strong>47 participants (mean age 66.39 ± 8.65 years; 39 female) underwent successful CTC. Of 1252 total colonic segments, 14.8% had no residual fluid and 59.5% had < 25% residual fluid. 73.6% of segments with residual fluid demonstrated good tagging. The mean fluid tagging efficacy ratio for all segments was 0.737 (95% CI: 0.700-0.775) with mean attenuation of 467 HU. Fluid tagging efficacy decreased from the cecum (0.934) to rectum (0.493). 92.8% of segments had no residual solid stool. Of the 7.2% of segments containing solid stool, 4.7% of segments had submerged stool ≤ 5 mm, 0.8% had 1-3 pieces of retained stool between 6 and 9 mm, and 1.8% had > 3 pieces 6-9 mm or single pieces > 1 cm.</p><p><strong>Conclusion: </strong>Low-volume (50 mL) iohexol is an effective fluid and fecal tagging agent for CTC with a minimally cathartic bowel preparation. This provides an easy option to label residual material and cleanse the bowel for patients undergoing CTC.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144075238","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":"Pictorial review of bilateral adnexal lesions.","authors":"Natália Henz Concatto, Salma Ayadi, Ariane Giovanaz, Camila Braga Visconti, Catherine Uzan, Jean-Paul Akakpo, Geoffroy Canlorbe, Yasmina Badachi, Olivier Lucidarme","doi":"10.1007/s00261-025-04978-w","DOIUrl":"https://doi.org/10.1007/s00261-025-04978-w","url":null,"abstract":"<p><p>Bilateral adnexal lesions involve structures such as the ovaries, fallopian tubes, and surrounding tissues, arising from diverse etiologies, including inflammatory, infectious, neoplastic, and functional causes. Their variable presentation poses a diagnostic challenge in clinical practice, necessitating a multidisciplinary approach for accurate assessment and management. The American College of Radiology (ACR) introduced the Ovarian-Adnexal Reporting and Data System (O-RADS) as a standardized lexicon and risk stratification tool for evaluating adnexal lesions via ultrasound (US) and magnetic resonance imaging (MRI). While MRI is the most accurate modality for assessing indeterminate adnexal masses, bilateral lesions frequently present diagnostic dilemmas, particularly when they exhibit divergent O-RADS classifications or arise from different etiologies. The O-RADS system does not provide specific guidelines for bilateral lesions, requiring independent classification of each lesion, with management dictated by the highest assigned category. Certain pathologies demonstrate a propensity for bilateral involvement, underscoring the importance of recognizing their imaging characteristics and differential diagnoses. Integrating this knowledge into diagnostic reports enhances clinical decision-making and optimizes patient outcomes.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143959953","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":"Segmentation of renal vessels on non-enhanced CT images using deep learning models.","authors":"Hai Zhong, Yuan Zhao, Yumeng Zhang","doi":"10.1007/s00261-025-04984-y","DOIUrl":"https://doi.org/10.1007/s00261-025-04984-y","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the possibility of performing renal vessel reconstruction on non-enhanced CT images using deep learning models.</p><p><strong>Materials and methods: </strong>177 patients' CT scans in the non-enhanced phase, arterial phase and venous phase were chosen. These data were randomly divided into the training set (n = 120), validation set (n = 20) and test set (n = 37). In training set and validation set, a radiologist marked out the right renal arteries and veins on non-enhanced CT phase images using contrast phases as references. Trained deep learning models were tested and evaluated on the test set. A radiologist performed renal vessel reconstruction on the test set without the contrast phase reference, and the results were used for comparison. Reconstruction using the arterial phase and venous phase was used as the gold standard.</p><p><strong>Results: </strong>Without the contrast phase reference, both radiologist and model could accurately identify artery and vein main trunk. The accuracy was 91.9% vs. 97.3% (model vs. radiologist) in artery and 91.9% vs. 100% in vein, the difference was insignificant. The model had difficulty identify accessory arteries, the accuracy was significantly lower than radiologist (44.4% vs. 77.8%, p = 0.044). The model also had lower accuracy in accessory veins, but the difference was insignificant (64.3% vs. 85.7%, p = 0.094).</p><p><strong>Conclusion: </strong>Deep learning models could accurately recognize the right renal artery and vein main trunk, and accuracy was comparable to that of radiologists. Although the current model still had difficulty recognizing small accessory vessels, further training and model optimization would solve these problems.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143958541","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":"The utility of low-dose pre-operative CT of ovarian tumor with artificial intelligence iterative reconstruction for diagnosing peritoneal invasion, lymph node and hepatic metastasis.","authors":"Xiaojia Cai, Jintao Han, Wanhui Zhou, Fan Yang, Jing Liu, Qi Wang, Ruxun Li","doi":"10.1007/s00261-025-04977-x","DOIUrl":"https://doi.org/10.1007/s00261-025-04977-x","url":null,"abstract":"<p><strong>Purpose: </strong>Diagnosis of peritoneal invasion, lymph node metastasis, and hepatic metastasis is crucial in the decision-making process of ovarian tumor treatment. This study aimed to test the feasibility of low-dose abdominopelvic CT with an artificial intelligence iterative reconstruction (AIIR) for diagnosing peritoneal invasion, lymph node metastasis, and hepatic metastasis in pre-operative imaging of ovarian tumor.</p><p><strong>Methods: </strong>This study prospectively enrolled 88 patients with pathology-confirmed ovarian tumors, where routine-dose CT at portal venous phase (120 kVp/ref. 200 mAs) with hybrid iterative reconstruction (HIR) was followed by a low-dose scan (120 kVp/ref. 40 mAs) with AIIR. The performance of diagnosing peritoneal invasion and lymph node metastasis was assessed using receiver operating characteristic (ROC) analysis with pathological results serving as the reference. The hepatic parenchymal metastases were diagnosed and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured. The perihepatic structures were also scored on the clarity of porta hepatis, gallbladder fossa and intersegmental fissure.</p><p><strong>Results: </strong>The effective dose of low-dose CT was 79.8% lower than that of routine-dose scan (2.64 ± 0.46 vs. 13.04 ± 2.25 mSv, p < 0.001). The low-dose AIIR showed similar area under the ROC curve (AUC) with routine-dose HIR for diagnosing both peritoneal invasion (0.961 vs. 0.960, p = 0.734) and lymph node metastasis (0.711 vs. 0.715, p = 0.355). The 10 hepatic parenchymal metastases were all accurately diagnosed on the two image sets. The low-dose AIIR exhibited higher SNR and CNR for hepatic parenchymal metastases and superior clarity for perihepatic structures.</p><p><strong>Conclusion: </strong>In low-dose pre-operative CT of ovarian tumor, AIIR delivers similar diagnostic accuracy for peritoneal invasion, lymph node metastasis, and hepatic metastasis, as compared to routine-dose abdominopelvic CT. It is feasible and diagnostically safe to apply up to 80% dose reduction in CT imaging of ovarian tumor by using AIIR.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143952061","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":"Intrahepatic diffuse periportal hyperintensity patterns on hepatobiliary phase of gadoxetate-enhanced MRI: a non-invasive imaging biomarker for clinical stratification of liver injury.","authors":"Feifei Wu, Wenjing Zhu, Sheng Du, Jifeng Jiang, Fei Xing, Tao Zhang, Qinrong Ma, Wei Xing","doi":"10.1007/s00261-025-04985-x","DOIUrl":"https://doi.org/10.1007/s00261-025-04985-x","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the clinicoradiological significance of intrahepatic periportal hyperintensity (PHI) detected by gadoxetate-enhanced hepatobiliary phase (HBP) MRI and T2-weighted imaging (T2WI), and to assess its potential as a noninvasive imaging biomarker for clinical stratification of liver injury in patients with cirrhosis.</p><p><strong>Methods: </strong>This retrospective study included 37 cirrhotic patients with intrahepatic diffuse PHI on HBP imaging, who underwent gadoxetate-enhanced MRI between October 2019 and November 2023. PHI patterns were classified into two groups based on the spatial concordance between periportal enhancement areas on HBP and periportal hyperintense areas on T2WI. The matching group (Type A, n = 21) demonstrated complete spatial overlap between the two sequences. The mismatching group, comprised Type B (n = 11), in which PHI on HBP was immediately outside of that on T2WI, and Type C (n = 5), in which PHI was present on HBP but absent on T2WI. Clinical etiologies and liver biochemical markers (ALT, AST, GGT, TBil, DBil, ALP, Alb, TP) were compared across PHI subtypes.</p><p><strong>Results: </strong>Type A PHI was predominantly associated with acute liver injury (e.g., acute viral hepatitis flares, drug-induced liver injury, autoimmune hepatitis), characterized by a strong ALT-AST correlation (r = 0.95, P < 0.001) and significantly elevated levels of ALT, AST, GGT, TBil, and DBil (all P < 0.001). In contrast, Types B and C PHI were primarily linked to chronic fibrotic conditions (e.g., HBV/HCV-related cirrhosis, primary biliary cholangitis, and primary sclerosing cholangitis), showing a strong TBil-DBil correlation (r = 0.95, P < 0.001) and moderately elevated ALP and Alb levels (P = 0.027 and P = 0.017, respectively). Receiver operating characteristic (ROC) analysis identified DBil > 37.5 μmol/L as the optimal threshold for differentiating Type A from Types B/C PHI (AUC = 0.922; sensitivity = 86.7%, specificity = 100%). Notably, HBP-doughnut nodules without arterial-phase hyperenhancement (APHE) were exclusively observed in the mismatching group (Type B: 4/11; Type C: 3/5), further supporting their association with chronic fibrotic changes.</p><p><strong>Conclusion: </strong>PHI phenotyping based on HBP-T2WI spatial concordance enables accurate, noninvasive differentiation between acute inflammatory and chronic fibrotic liver injury in cirrhotic patients. When integrated with the DBil threshold, this imaging-based approach provides as a robust biomarker for clinical stratification of liver injury and may facilitate individualized diagnosis and therapeutic decision-making in chronic liver disease.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143961311","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":"Ultrasound innovations in abdominal radiology: evaluation of focal liver lesions.","authors":"David P Burrowes, Christine D Merrill, Stephanie R Wilson","doi":"10.1007/s00261-025-04970-4","DOIUrl":"https://doi.org/10.1007/s00261-025-04970-4","url":null,"abstract":"<p><p>Focal liver lesions (FLLs) are common and are often first identified on abdominal ultrasound examinations. Although CT and MRI were historically required to noninvasively characterize many FLLs, introduction of microbubble contrast agents produced a groundbreaking change as contrast enhanced ultrasound (CEUS) showed vascularity to the capillary level for the first time. CEUS shows specific arterial phase enhancement patterns in benign lesions and accurately differentiates malignant lesions based on the timing and intensity of washout. Parametric time of arrival and microvascular imaging techniques can demonstrate vascularity in FLLs with significantly improved sensitivity compared with conventional Doppler techniques. Shear-wave elastography and quantitative ultrasound are generally used to evaluate diffuse liver disease but show promise in evaluation of FLLs.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143963603","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}