Evidence map›Paper›PMID 41697554›Full record

ArticleInsights into imaging2026

Preoperative contrast-enhanced CT prediction of distinct vascular patterns in solitary early-stage hepatocellular carcinoma and its prognostic value.

Wanli Zhang, Wen Lv, Yi Long, Jiaxin Lin, Jiamin Li, Chuanxian Zhang, Yandong Zhao, Jie Zhan, Shengsheng Lai, Mingyong Gao and 2 more

Abstract read
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Article in Insights into imaging, 2026. 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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5 · Who and what money

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12 authors.

Wanli ZhangDepartment of Radiology, Guangzhou First People's Hospital, Guangzhou, China.
Wen LvDepartment of Radiology, Jinan University First Affiliated Hospital, Guangzhou, China.
Yi LongDepartment of Radiology, Guangzhou First People's Hospital, Guangzhou, China.
Jiaxin LinDepartment of Radiology, Guangzhou First People's Hospital, Guangzhou, China.
Jiamin LiDepartment of Radiology, Guangzhou First People's Hospital, Guangzhou, China.
Chuanxian ZhangDepartment of Radiology, The Zhaoqing Hospital of the Third Affiliated Hospital, Sun Yat-sen University, Zhaoqing, China.
Yandong ZhaoDepartment of Radiology, Guangzhou First People's Hospital, Guangzhou, China.
Jie ZhanDepartment of Radiology, Guangzhou First People's Hospital, Guangzhou, China.
Shengsheng LaiSchool of Medical Equipment, Guangdong Food and Drug Vocational College, Guangzhou, China.
Mingyong GaoDepartment of Radiology, The First People's Hospital of Foshan, Foshan, China.
Xinqing JiangDepartment of Radiology, Guangzhou First People's Hospital, Guangzhou, China.
Ruimeng YangDepartment of Radiology, Guangzhou First People's Hospital, Guangzhou, China. eyruimengyang@scut.edu.cn.ORCID http://orcid.org/0000-0003-2768-9429

Funding

2025 Research Project of the Guangdong Health Information Network Association MS-202509-0047GuangDong Basic and Applied Basic Research Foundation 2021A1515220060Guangzhou Key Laboratory of Molecular Imaging and Clinical Translational Medicine 202201020376Jiangxi Provincial Natural Science Foundation Project 20242BAB25546National Natural Science Foundation of China 81971574National Natural Science Foundation of China 82271938National Natural Science Foundation of China 82371908Natural Science Foundation of Guangdong Province 2021A1515011350Natural Science Foundation of Guangdong Province 2024A1515012177Science and Technology Project of Guangzhou 202102010025
6 · The paper itself

Abstract

objectivesTo investigate the value of qualitative and quantitative contrast-enhanced CT (CECT) features for noninvasive identification of two distinct vascular patterns, vessels that encapsulate tumor clusters (VETC) and/or microvascular invasion (MVI), in solitary early-stage (BCLC 0-A) hepatocellular carcinoma (HCC) and assess their prognostic implications. MATERIALS AND

methodsWe retrospectively included 347 patients with solitary early-stage HCC who underwent preoperative CECT and subsequent resection at two centers. Patients were divided into V/M+ (MVI and/or VETC positive, n = 174) and VM- (both MVI and VETC negative, n = 173) groups based on histopathology. Four predictive models (clinical, CT quantitative, CT qualitative, and combined) integrating clinical and CECT features were developed and validated for identifying V/M+ status. The optimal model was further applied to predict 2-year recurrence-free survival (RFS). Sensitivity analysis was performed using propensity score matching (PSM). Models' performance was evaluated and compared using AUC analyses and DeLong tests.

resultsThe combined model [serum AFP ≥ 200 ng/mL, non-smooth tumor margin, internal arteries, and lower tumor-to-liver density ratio in the portal venous phase (P-TLR)] achieved optimal predictive performance for V/M + HCC, with training AUC of 0.784 and 0.782 pre- and post-PSM, and external validating AUC of 0.794. A derived V/M+ score stratified patients, with higher scores associated with significantly shorter 2-year RFS. V/M+ score ≥ 34 and tumor size ≥ 60 mm were significant predictors of HCC recurrence (p < 0.05).

conclusionThe combined model integrating clinical and CECT-based features, enables non-invasive assessment of V/M status in early-stage solitary HCC and effectively stratifies patients according to recurrence risk. CRITICAL RELEVANCE STATEMENT: Specific CT-based qualitative and quantitative features are associated with a distinct vascular pattern of BCLC stage 0-A HCC. The developed combined model and derived V/M+ score offer a reliable tool for clinicians to predict V/M + HCC and patients' 2-year RFS. KEY POINTS: Specific CECT-based qualitative and quantitative features are associated with V/M + HCC at the BCLC stage 0-A. The developed combined model offers a reliable tool for clinicians to identify V/M + HCC. The derived V/M+ score helps stratify HCC patients into high- and low-risk groups for 2-year RFS, facilitating personalized management of HCC.

Indexed as

Computed tomographyHepatocellular carcinomaMicrovascular invasionRecurrence-free survivalVessels that encapsulate tumor clusters

Identifiers

PMID41697554
PMCPMC12909690

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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.