Evidence map›Paper›PMID 40536607›Full record

ArticleInsights into imaging2025

Association between ultrasound-based biliary and parenchymal intrahepatic mass-forming cholangiocarcinoma subtypes and clinicopathological features and survival.

Cong-Jian Wen, Hui Liu, Li-Ping Sun, Chong-Ke Zhao, Hao-Hao Yin, Li-Fan Wang, Ming-Rui Zhu, Yi-Kang Sun, Ya-Qin Zhang, Zi-Tong Chen and 5 more

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Article in Insights into imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

15 authors.

Cong-Jian Wen *Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Hui Liu *Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, Ultrasound Education and Research Institute, School of Medicine, Tongji University, Shanghai, China.
Li-Ping SunDepartment of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, Ultrasound Education and Research Institute, School of Medicine, Tongji University, Shanghai, China.
Chong-Ke ZhaoDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Hao-Hao YinDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Li-Fan WangDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Ming-Rui ZhuDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Yi-Kang SunDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Ya-Qin ZhangDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Zi-Tong ChenDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Xi WangDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Han-Sheng XiaDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Hong HanDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Hui-Xiong XuDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China. xuhuixiong@126.com.ORCID http://orcid.org/0000-0002-8699-854X
Bo-Yang ZhouDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China. zhouboyang@live.cn.

Funding

Pilot Medical Construction Project of Fudan University Grant IDF 152076Scientific Research and Development Fund of Zhongshan Hospital of Fudan University Grant 2022ZSQD07 and ZSLCYJ202317Shanghai Municipal Health Commission Grant SHSLCZDZK03502the Ministry of Science and Technology of China Grant 2023YFC2414204the Science and Technology Commission of Shanghai Municipality Grants 18441905500 and 19DZ2251100
6 · The paper itself

Abstract

objectiveMass-forming intrahepatic cholangiocarcinomas (MF-ICCs) can be classified into ductal and parenchymal types using magnetic resonance imaging (MRI). We aimed to subclassify MF-ICC into biliary and parenchymal types based on ultrasound (US) findings and to investigate the differences in their contrast-enhanced ultrasound (CEUS) patterns, clinicopathologic features, and prognosis.

methodsIn this study, 141 patients who underwent US with pathologically proven MF-ICC from two hospitals were retrospectively enrolled. MF-ICCs were divided into biliary (bMF-ICCs) and parenchymal MF-ICC (pMF-ICCs) based on the signs of bile duct dilation in US images. Clinicopathological, imaging, and short-term survival data were collected from medical records and compared.

resultsAmong 141 patients (61.96 ± 10.15 years, 83 men), bMF-ICCs (33/141, 23.4%) showed significantly more CEA ≥ 5 µg/L (42.4% vs 20.2%, p = 0.01), microvascular invasion (54.5% vs 10.2%, p < 0.001), lymph node metastasis (48.5% vs 5.6%, p < 0.001), bile duct invasion (48.5% vs 5.6%, p < 0.001), and high Ki-67 expression (63.6% vs 38.9%, p = 0.01) than pMF-ICCs. Pathologically, bMF-ICCs were more inclined toward the large duct type (78.1% vs 11.7%, p < 0.001). In addition, the bMF-ICCs were usually located in the left lobe of the liver (63.6% vs 41.7%, p = 0.03). pMF-ICCs showed better overall survival than bMF-ICCs (p = 0.04).

conclusionsSubclassification of MF-ICCs into biliary and parenchymal types based on US is useful for discriminating clinicopathological characteristics. CRITICAL RELEVANCE STATEMENT: The subclassification of mass-forming intrahepatic cholangiocarcinoma (MF-ICC) into biliary (bMF-ICC) and parenchymal (pMF-ICC) subtypes using ultrasound can provide clinicopathological and prognostic information before surgery. KEY POINTS: We subclassified mass-forming intrahepatic cholangiocarcinomas into biliary and parenchymal types using ultrasound. Biliary and parenchymal types have different clinicopathological features and postsurgical outcomes. Biliary type above and below 50 mm exhibits different unfavorable clinicopathological characteristics. Our classification has certain similarities with MRI classification in clinicopathological characteristics.

Indexed as

Bile ductsCholangiocarcinomaPrognosisSubtypesUltrasonography

Identifiers

PMID40536607
PMCPMC12179021

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.