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 等 12 位
Guangzhou First People's Hospital Jinan University First Affiliated Hospital of Jinan University Sun Yat-sen University
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OBJECTIVES: To 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 METHODS: We 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. RESULTS: The 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). CONCLUSION: The 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.
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生物医学Hepatocellular Carcinoma Treatment and Prognosis
Radiomics and Machine Learning in Medical Imaging · MRI in cancer diagnosis
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