Literature DB >> 30976546

Predicting peritumoral Glisson's sheath invasion of intrahepatic cholangiocarcinoma with preoperative CT imaging.

Yingfan Mao1, Yong Zhu2, Yudong Qiu3, Weiwei Kong4, Liang Mao3, Qun Zhou1, Jun Chen5, Jian He1.   

Abstract

BACKGROUND: To investigate the differences of clinicopathological characteristics and computed tomography (CT) features between intrahepatic cholangiocarcinomas (ICC) with and without peritumoral Glisson's sheath invasion (PGSI), and to construct a nomogram to predict PGSI of ICCs preoperatively.
METHODS: The clinicopathological characteristics and CT features of 84 ICCs were retrospectively analyzed and compared between ICCs with (30/84, 35.7%) and without PGSI (54/84, 64.3%). Multivariate logistic regression analysis was used to identify preoperative independent predictors of PGSI in ICCs. A nomogram was constructed to predict PGSI preoperatively.
RESULTS: ICCs with and without PGSI differed significantly in the presence of abdominal pain, serum carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) levels, TNM and T stages, tumor location, intratumoral calcifications, intrahepatic bile duct dilatation, intrahepatic bile duct calculus, morphologic type and dynamic enhancement pattern on CT images (all P<0.05). Abdominal pain, serum CEA level, intrahepatic bile duct dilatation, and morphologic type were independent predictors of PGSI in ICCs. A nomogram based on those predictors was constructed to predict PGSI preoperatively with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.908 (P<0.001).
CONCLUSIONS: Clinicopathological characteristics and CT features differed significantly between ICCs with and without PGSI. A nomogram including abdominal pain, serum CEA level, intrahepatic bile duct dilatation, and morphologic type could predict PGSI accurately.

Entities:  

Keywords:  Intrahepatic bile ducts; cholangiocarcinoma; nomogram; peritumoral Glisson’s sheath; spiral computed tomography

Year:  2019        PMID: 30976546      PMCID: PMC6414767          DOI: 10.21037/qims.2018.12.11

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  31 in total

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Journal:  Cancer J       Date:  2009 May-Jun       Impact factor: 3.360

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  1 in total

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