Abdominal Radiology最新文献

{"title":"AI-enabled body composition biomarkers at post-mortem CT for enriching autopsy: analysis of a large decedent cohort.","authors":"Max V Golden, Matthew H Lee, John W Garrett, Shamsi Daneshvari Berry, Nicollette Appel, Ronald M Summers, Heather J H Edgar, Perry J Pickhardt","doi":"10.1007/s00261-025-04878-z","DOIUrl":"https://doi.org/10.1007/s00261-025-04878-z","url":null,"abstract":"<p><strong>Objective: </strong>To correlate fully-automated PMCT-based body composition measures with causes of death and comorbidities.</p><p><strong>Materials and methods: </strong>Retrospective study of New Mexico Decedent Image Database (NMDID) with non-contrast PMCT scans between 2010 and 2017. Automated pipeline of AI-driven algorithms for quantifying skeletal muscle, subcutaneous/visceral fat, and aortic calcification from the abdominal component of PMCT scans was used. Scans with more than minimal decomposition were excluded. Cause of death was categorized as \"acute\" or \"chronic.\" A predetermined model derived CT-based \"biological age.\"</p><p><strong>Results: </strong>6638 decedents (mean age, 50±18 [SD]; 74% male) comprised the final cohort. 80% of deaths were classified as \"acute,\" 10% as \"chronic,\" and 10% \"uncertain.\" Muscle density (HU) and area at the L3 lumbar level were higher in the \"acute\" versus \"chronic\" group (26 HU vs. 18 HU, p < 0.001; 192 cm² vs. 183 cm², p < 0.001). Muscle density and area at the L3 level were higher among those without cancer (25 HU vs. 16 HU, p < 0.001; 190 cm² vs. 169 cm², p < 0.01). Aortic Agatston scores were higher in those who died of heart disease (5120 vs. 2098, p < 0.001). Diabetic patients had higher L3 visceral fat area (227 cm² vs. 175 cm², p < 0.001) and lower muscle density (17 HU vs. 25 HU, p < 0.001). The deviation between chronological and biological age was significantly higher in the chronic versus acute group (median age deviation, 19 years vs. 10 years; p < 0.001).</p><p><strong>Conclusion: </strong>Fully-automated quantitative PMCT-based tissue biomarkers correlate with the temporal nature of death and chronic co-morbidities, supporting their use for enhancing autopsies.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655955","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":"Preoperative MRI-based predictive model for biochemical recurrence following radical prostatectomy.","authors":"Qianyu Peng, Lili Xu, Daming Zhang, Jiahui Zhang, Xiaoxiao Zhang, Xin Bai, Li Chen, Erjia Guo, Linjing Yang, Yongfei Wu, Chen Chen, Sihong Yu, Zhengyu Jin, Gumuyang Zhang, Hao Sun","doi":"10.1007/s00261-025-04877-0","DOIUrl":"https://doi.org/10.1007/s00261-025-04877-0","url":null,"abstract":"<p><strong>Purpose: </strong>To determine the biochemical recurrence (BCR)-related pelvic anatomic characteristics before radical prostatectomy (RP) and to establish a new predictive model for BCR-free survival (BCRFS).</p><p><strong>Methods: </strong>The study involved 170 patients who underwent RP between January 2015 and December 2022. Kaplan-Meier plots were applied to estimate survival probabilities. Multivariate Cox regression models were employed to identify predictors for BCRFS, which were subsequently incorporated into an MRI-based nomogram to visualize the model. The Harrell's concordance index (C-index) was employed to evaluate the discrimination, and compared with a basic model without incorporating pelvic anatomy. Time-dependent receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were applied to identify the advantage of the new predictive model. Three risk categories were created.</p><p><strong>Results: </strong>Multifactorial analysis revealed that age, capsule contact length (CCL), tumor's distance to the proximal membranous urethra (UD), urethral width, and annual surgery volume were independent risk factors for BCR (all p < 0.05). The established predictive model yielded a C-index of 0.850 that was superior to aforementioned basic model with C-index of 0.771 (p < 0.001). Our new model with an area under the ROC curve (AUC) of 0.893 revealed better predictive ability in BCRFS than basic model with the AUC of 0.823 (p = 0.01), and DCA demonstrated that our model generated more net benefits.</p><p><strong>Conclusion: </strong>UD and urethral width are independent predictors of BCRFS. Our new model exhibits superior predictive accuracy with respect to BCRFS relative to the basic model. Apart from tumor features, pelvic anatomical features should also be considered before the treatment decision making of PCa patients.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143655958","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":"Preliminary study on determining the optimal position of region of interest for evaluating hepatic steatosis using ultrasound Attenuation imaging.","authors":"Mingsen Bi, Fangyi Liu, Jie Yu, Yun He, Ping Liang, Hong Yang","doi":"10.1007/s00261-025-04876-1","DOIUrl":"https://doi.org/10.1007/s00261-025-04876-1","url":null,"abstract":"<p><strong>Purpose: </strong>To find the optimal position of region of interest (ROI) for evaluating hepatic steatosis using attenuation imaging (ATI) in patients with metabolic dysfunction-associated fatty liver disease (MAFLD).</p><p><strong>Methods: </strong>We retrospectively enrolled 143 consecutive patients who underwent percutaneous liver biopsy for the evaluation of MAFLD between October 2020 and October 2022. All ATI measurements were performed by the same radiologist. The ATI-ROI was placed at four different positions using a specialized workstation: the top edge of the sampling box (P1), the lower edge of the dark orange region (P2), 0.5 cm and 1 cm below the lower edge of the dark orange region (P3 and P4). Multivariate linear regression analysis and the area under the curve (AUC) analysis were performed.</p><p><strong>Results: </strong>The AUCs of ATI at the four different ATI-ROI positions were 0.472 (95% confidence interval [CI]: 0.362-0.581), 0.693(0.611-0.768), 0.757(0.611-0.768), and 0.809 (0.735-0.870) for ≥ S1; 0.544 (0.459-0.628), 0.779 (0.702-0.844), 0.842 (0.772-0.898), and 0.865 (0.798-0.916) for ≥ S2; and 0.655 (0.571-0.733), 0.904 (0.843-0.947), 0.95 (0.9-0.979), and 0.949 (0.9-0.979) for S3, respectively. The factor that most significantly affected ATI was steatosis grade(P<0.001), when ATI-ROI was placed at the position of P2, P3, and P4.</p><p><strong>Conclusion: </strong>Hepatic steatosis grade was the most significant determinant factor for ATI value at multivariate analysis. When clinicians conduct ATI measurement, the dark orange region indicating the area of reverberation artifact should be avoided, and placing the ATI-ROI 1 cm below the lower edge of the dark orange region may be a better choice.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646767","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":"Progress in the application of machine learning in CT diagnosis of acute appendicitis.","authors":"Jiaxin Li, Jiayin Ye, Yiyun Luo, Tianyang Xu, Zhenyi Jia","doi":"10.1007/s00261-025-04864-5","DOIUrl":"https://doi.org/10.1007/s00261-025-04864-5","url":null,"abstract":"<p><p>Acute appendicitis represents a prevalent condition within the spectrum of acute abdominal pathologies, exhibiting a diverse clinical presentation. Computed tomography (CT) imaging has emerged as a prospective diagnostic modality for the identification and differentiation of appendicitis. This review aims to synthesize current applications, progress, and challenges in integrating machine learning (ML) with CT for diagnosing acute appendicitis while exploring prospects. ML-driven advancements include automated detection, differential diagnosis, and severity stratification. For instance, deep learning models such as AppendiXNet achieved an AUC of 0.81 for appendicitis detection, while 3D convolutional neural networks (CNNs) demonstrated superior performance, with AUCs up to 0.95 and an accuracy of 91.5%. ML algorithms effectively differentiate appendicitis from similar conditions like diverticulitis, achieving AUCs between 0.951 and 0.972. They demonstrate remarkable proficiency in distinguishing between complex and straightforward cases through the innovative use of radiomics and hybrid models, achieving AUCs ranging from 0.80 to 0.96. Even with these advancements, challenges remain, such as the \"black-box\" nature of artificial intelligence, its integration into clinical workflows, and the significant resources required. Future directions emphasize interpretable models, multimodal data fusion, and cost-effective decision-support systems. By addressing these barriers, ML holds promise for refining diagnostic precision, optimizing treatment pathways, and reducing healthcare costs.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646771","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":"Usefulness of multiphasic MRI in assessing suitability for SIRT in treatment of liver malignancies.","authors":"Cagri Erdim, Elife Akgun, Tevfik Guzelbey, Gulsah Yilmaz, Mehmet Hamza Turkcanoglu, Ali Dablan, Burcu Esen Akkas, Ozgur Kilickesmez","doi":"10.1007/s00261-025-04875-2","DOIUrl":"https://doi.org/10.1007/s00261-025-04875-2","url":null,"abstract":"<p><strong>Aim: </strong>To evaluate the predictive value of multiphasic magnetic resonance imaging (MRI) in identifying liver tumor perfusion characteristics and to compare it with hepatic artery perfusion scintigraphy findings in patients considered for selective internal radiation therapy (SIRT) with yttrium-90 (Y-90).</p><p><strong>Methods: </strong>This study included 93 patients diagnosed with primary or secondary liver cancer between May 2021 and February 2024, comprising 47 patients (27 M/20F) deemed unsuitable for SIRT and 46 patients (26 M/20F) eligible for SIRT. The relationship between multiphasic MRI and scintigraphy findings in determining perfusion of tumors was analyzed. Predictive performance was evaluated with receiver operating characteristic (ROC) analysis, and the optimal cut-off values were determined using the Youden index.</p><p><strong>Results: </strong>The SIRT unsuitable group had a lower frequency of intratumoral arterial phase hyperenhancement(APHE) (40.43% vs. 69.57%, p = 0.042), presence of hyperintensity on T2 sequence (72.34% vs. 95.65%, p = 0.026), lower lesion intensity in the portal phase (p = 0.033), and a lower lesion-to-liver intensity ratio in the portal phase (≤ 0.97, p = 0.011). The absence of intratumoral APHE [p = 0.049, AUC (95% CI) = 0.646 (0.508-0.783)] and a lesion-to-liver intensity ratio in the portal phase with a cut-off value of ≤ 0.97 [p = 0.011, AUC (95% CI) = 0.689 (0.564-0.815)] were significant predictors of SIRT unsuitability.</p><p><strong>Conclusion: </strong>Both the absence of intratumoral APHE and a lower lesion-to-liver intensity ratio in the portal phase were significant predictors of SIRT unsuitability.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646524","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":"Comparing two deep learning spectral reconstruction levels for abdominal evaluation using a rapid-kVp-switching dual-energy CT scanner.","authors":"Hakki Serdar Sagdic, Mohammadreza Hosseini-Siyanaki, Abheek Raviprasad, Sefat Munjerin, Daniella Fabri, Joseph Grajo, Victor Martins Tonso, Laura Magnelli, Daniela Hochhegger, Evelyn Anthony, Bruno Hochhegger, Reza Forghani","doi":"10.1007/s00261-025-04868-1","DOIUrl":"https://doi.org/10.1007/s00261-025-04868-1","url":null,"abstract":"<p><strong>Purpose: </strong>Deep Learning Spectral Reconstruction (DLSR) potentially improves dual-energy CT (DECT) image quality, but there is a paucity of research involving human abdominal DECT scans. The purpose of this study was to comprehensively evaluate image quality by quantitatively and qualitatively comparing strong and standard levels of a DLSR algorithm. Optimal virtual monochromatic image (VMI) energy levels were also evaluated.</p><p><strong>Methods: </strong>DECT scans of the abdomen/pelvis from 51 patients were retrospectively evaluated. VMIs were reconstructed at energy levels ranging from 35 to 200 keV using both standard and strong DLSR levels. For quantitative analysis, various abdominal structures were assessed using regions of interest, and mean signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values were calculated. This was supplemented with a qualitative evaluation of VMIs reconstructed at 35, 45, 55, and 65 keV.</p><p><strong>Results: </strong>The strong-level DLSR demonstrated significantly better SNR and CNR values (p < 0.0001) compared to standard-level DLSR across all structures. The optimal SNR was observed at 70 keV (p < 0.0001), while the optimal CNR was found at 65 keV (p < 0.0001). The average qualitative scores between standard and strong DLSR were significantly different at 45, 55, and 65 keV (p < 0.0001). There was a moderate level of agreement between observers (ICC = 0.427, p < 0.0001).</p><p><strong>Conclusion: </strong>A DLSR set to a strong level significantly improves image quality compared to standard-level DLSR, potentially enhancing the diagnostic evaluation of abdominal DECT scans. In addition to achieving a very high SNR, 65 keV VMIs had the highest CNR, which differs from what is typically observed with traditional DECT using non-deep learning reconstruction approaches.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646761","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":"Fallopian fimbriae entrapped in an ovarian endometriotic cyst mimicking malignancy: a case report.","authors":"Atsushi Yoshida, Shigeshi Kohno, Shojiro Oka, Yuko Someya, Shigeki Arizono, Tsuyoshi Suga, Reiichi Ishikura, Hiroe Itami, Shinichiro Maeda, Kumiko Ando","doi":"10.1007/s00261-025-04882-3","DOIUrl":"https://doi.org/10.1007/s00261-025-04882-3","url":null,"abstract":"<p><p>Ovarian endometriotic cysts are associated with an increased risk of clear cell and endometrioid carcinomas, as well as borderline neoplasms. Although contrast-enhancing nodules on magnetic resonance imaging (MRI) suggest malignancy, benign endometriotic cysts can also present with such features, complicating differentiation from malignancy. When malignancy is suspected, minimally invasive procedures, such as laparoscopic cystectomy, are typically avoided. However, preserving fertility and ovarian function warrants careful consideration when selecting invasive surgical procedures. From the perspective of selecting appropriate surgical approaches, accurate preoperative differentiation between benign and malignant ovarian tumors is essential. We present the first case of MRI showing fallopian fimbriae entrapped in an endometriotic cyst mimicking malignancy. A 49-year-old female presented with atypical genital bleeding. MRI revealed a right ovarian endometriotic cyst with a contrast-enhancing mural nodule (10 mm), suggestive of malignancy. The nodule demonstrated T2-weighted hypointensity equivalent to the cyst fluid without diffusion restriction. Laparotomy revealed the nodule as entrapped fallopian fimbriae within the endometriotic cyst, with no malignancy detected. In this case, the fallopian fimbriae entrapped in the endometriotic cyst appeared as an enhancing nodule because of their vascularity, mimicking malignancy. Fallopian fimbriae are inconspicuous structures that can produce false findings suggestive of malignancy, similar to other benign enhancing nodules, such as polypoid endometriosis and decidualization. However, their lack of diffusion restriction and low T2-weighted signal intensity may help distinguish them from malignancy. This knowledge is crucial for accurate diagnosis and avoiding unnecessary interventions.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646741","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 cholangiocarcinoma: role of imaging as a critical component for multi-disciplinary treatment approach.","authors":"Betzaira G Childers, Jason W Denbo, Richard D Kim, Sarah E Hoffe, Tetiana Glushko, Aliya Qayyum, Daniel A Anaya","doi":"10.1007/s00261-025-04856-5","DOIUrl":"https://doi.org/10.1007/s00261-025-04856-5","url":null,"abstract":"<p><p>Cholangiocarcinoma (CCA) is a unifying title granted to epithelial adenocarcinomas specific to the bile ducts making up 10-25% of all hepatobiliary malignancies. CCA is more appropriately classified based on anatomic site of origin within the biliary tract into intrahepatic cholangiocarcinoma (iCCA), peri-hilar (pCCA) cholangiocarcinoma, and distal cholangiocarcinoma (dCCA). Intrahepatic cholangiocarcinoma makes up 10-20% of CCA and originates within and/or proximal to the second order bile ducts. The incidence of iCCA has been rising overtime with up to 1.26 per 100,000 persons, per year in the United States and up to 3.3 per 100, 000 persons, per year affected globally. Risk factors include chronic hepatic inflammation secondary to viral hepatitis, alcohol/NASH cirrhosis, biliary cystic lesions, and endemic causes, among other less common genetic drivers. Given its rarity, the recognition and diagnosis of cholangiocarcinoma, iCCA specifically, remains challenging resulting in delays in treatment initiation or any treatment at all. Median overall survival (mOS) for iCCA remains low. Early diagnosis, and stage-based treatment approaches have evolved and are associated with improved survival. To this goal, a multi-disciplinary treatment approach has been demonstrated to improve patient outcomes by providing expert evaluation as it pertains to an accurate imaging and histologic diagnosis, staging, radiologic and surgical review for resectability, operative expertise, post operative care, as well as comprehensive knowledge and implementation of systemic/targeted or liver directed therapies. Here, we discuss the central role of imaging in the diagnosis of intrahepatic cholangiocarcinoma to implement a comprehensive treatment plan that frequently involves multiple disciplines to achieve the best outcome for each patient.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646764","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":"Treatment-related changes in adenomyosis: a primer for radiologists.","authors":"Brunna Clemente Oliveira, Myra K Feldman, Priyanka Jha, Scott Young, Arnaldo Schizzi Cambiaghi, Luciana P Chamié","doi":"10.1007/s00261-025-04866-3","DOIUrl":"https://doi.org/10.1007/s00261-025-04866-3","url":null,"abstract":"<p><p>Adenomyosis is a common, estrogen-dependent condition where endometrial tissue grows within the myometrium, often accompanied by smooth muscle hypertrophy. Initially thought to represent a condition primarily seen in multiparas with menorrhagia, and dysmenorrhea, adenomyosis is now increasingly recognized in younger patients and those with infertility and subfertility. As a result, conservative treatments aimed at preserving the uterus and improving reproductive outcomes have gained attention to treat adenomyosis. While research has largely focused on managing abnormal uterine bleeding and dysmenorrhea, there is limited evidence on the treatment of infertility associated with adenomyosis, particularly in terms of imaging follow-up. This paper reviews the emerging literature, highlighting key imaging findings before and after uterus-preserving treatments for adenomyosis, to better inform management and decision-making.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646518","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":"Differentiation between mucinous cystic neoplasms and simple cysts of the liver: a systematic review and meta-analysis.","authors":"Gita Manzari Tavakoli, Mahshad Afsharzadeh, Mahya Mobinikhaledi, Shima Behzad, Hamed Ghorani, Faeze Salahshour","doi":"10.1007/s00261-025-04874-3","DOIUrl":"https://doi.org/10.1007/s00261-025-04874-3","url":null,"abstract":"<p><strong>Purpose: </strong>Radiologic examinations frequently identify cystic liver lesions, which encompass various entities from simple benign cysts to malignant neoplasms. This work analyses the available data to compare diagnostic features of biliary cystic neoplasms and hepatic simple cysts.</p><p><strong>Methods: </strong>A systematic search of PubMed, Scopus, Embase, and Web of Science up to October 2024 was conducted. The characteristics were categorized into hepatic simple cysts (HSC) and mucinous cystic neoplasms (MCN), including biliary cystadenoma (BCA) and cystadenocarcinoma (BCAC) detected by imaging modalities including ultrasound, CT scans with IV contrast, or MRI. We analyzed biliary cystic neoplasms and hepatic simple cysts across multiple studies using Review Manager Ver. 5, calculating summary measures for each feature.</p><p><strong>Results: </strong>The study analyzed 577 lesions in 577 patients and 49 studies. Hepatic simple cysts were the most common finding, with 349 identified, mainly in the right hepatic lobe, presented with abdominal pain or incidentally. Intracystic septation was found in 50.1% of HSC lesions, with thick septation in 10.52% of lesions. 228 (49.9%) patients were diagnosed with MCN, with abdominal swelling and pain as the most common presentation. Septation was the most common radiological feature of MCNs, with thick septa in 50.61%. MCNs had internal septa, solid mural nodule, upstream bile duct dilation, presence in the left hepatic lobe, septal thickening, cystic wall enhancement, calcifications, and internal debris. The presence of a cyst in the left lobe was more related to MCNs.</p><p><strong>Conclusion: </strong>Characterizing cystic liver lesions necessitates a comprehensive evaluation of the lesions' location, size, and complexity. Imaging and clinical findings are essential for a final diagnosis.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143646738","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}