肝脏 ›› 2026, Vol. 31 ›› Issue (6): 838-841.

• 肝肿瘤 • 上一篇    下一篇

肝细胞癌微血管侵犯病理分级对患者预后不良风险的评估价值

王晓慧, 臧丹, 陈亦扬, 薛云, 李健   

  1. 453000 新乡 河南医科大学第一附属医院病理科
  • 收稿日期:2025-12-22 出版日期:2026-06-30 发布日期:2026-07-29
  • 通讯作者: 李健,Email:lijiandoc@163.com

The value of pathological grading of microvascular invasion in hepatocellular carcinoma in evaluating the risk of poor prognosis in patients

Wang Xiaohui, Zang Dan, Chen Yiyang, Xue Yun, Li Jian   

  1. The First Affiliated Hospital of Henan Medical University, Xinxiang 453000, China
  • Received:2025-12-22 Online:2026-06-30 Published:2026-07-29
  • Contact: Li Jian,Email:lijiandoc@163.com

摘要: 目的 基于病理特征构建肝细胞癌(HCC)微血管侵犯(MVI)风险分级体系,分析不同风险等级的病理侵袭特征、免疫微环境差异及其与术后预后的关系,评价MVI风险分级的独立预测价值,为术后风险评估及个体化治疗提供参考依据。方法 回顾性分析河南医科大学第一附属医院接受根治性切除的81例HCC患者的临床与病理资料。根据MVI数量、分布及形态学特征,将患者分为M0(53例)、M1(18例)和M2(10例)三组。比较不同MVI风险等级的病理侵袭行为、术后复发模式及免疫浸润特征,采用Kaplan-Meier法分析无复发生存率。结果 随着MVI风险分级升高,HCC侵袭性病理表现逐渐增强。M2组包膜完整率显著降低,中低分化比例、不清晰/浸润性边界及卫星结节出现率明显增加(P<0.05)。术后复发分析显示,M2组6个月、1年和2年内复发率分别为50.0%、70.0%和90.0%,均显著高于M0和M1组,中位复发时间显著缩短,再次切除率下降,复发后1年死亡率升高(P<0.05)。免疫微环境方面,高风险MVI患者CD4+、CD8+及NK细胞浸润显著减少,Treg、TAM及MDSC逐级升高(P<0.05),呈现免疫抑制表型。Kaplan-Meier分析提示不同风险等级患者无复发生存存在显著统计学差异(log-rank检验,P<0.001)。结论 基于病理特征构建的MVI风险分级体系可有效反映HCC侵袭性及免疫微环境差异,是术后复发及生存的独立预测因素。该分级体系较传统MVI有无评估更精细,可为HCC患者术后风险管理、随访策略及辅助治疗决策提供重要依据。

关键词: 肝细胞癌, 微血管侵犯, 病理特征, 免疫微环境, 预后分析

Abstract: Objective To establish a pathology-based microvascular invasion (MVI) risk stratification system for hepatocellular carcinoma (HCC), analyze the pathological invasion characteristics and immune microenvironment differences among different risk levels, and assess their association with postoperative prognosis. Furthermore, this study aimed to evaluate the independent prognostic value of MVI risk stratification and provide a reference for postoperative risk assessment and individualized treatment. Methods Clinical and pathological data of 81 patients with HCC who underwent curative resection in the First Affiliated Hospital of Henan Medical University were retrospectively analyzed. According to the number, distribution, and morphological characteristics of MVI, patients were categorized into three groups: M0 (n=53), M1 (n=18), and M2 (n=10). Pathological invasive behaviors, postoperative recurrence patterns, and immune infiltration characteristics were compared among different MVI risk levels. Recurrence-free survival was analyzed using the Kaplan-Meier method. Results With increasing MVI risk stratification, invasive pathological features of HCC progressively intensified. The M2 group showed significantly lower capsule integrity and markedly higher proportions of moderate-to-poor differentiation, unclear/infiltrative margins, and satellite nodules (P<0.05). Postoperative recurrence analysis revealed recurrence rates of 50.0%, 70.0%, and 90.0% at 6 months, 1 year, and 2 years, respectively, in the M2 group, which were significantly higher than those in the M0 and M1 groups. In the M2 group, the median recurrence time was markedly shorter, re-resection rates decreased, and 1-year mortality after recurrence increased (P<0.05). Regarding the immune microenvironment, high-risk MVI patients exhibited significantly reduced CD4+, CD8+, and NK cell infiltration, whereas Treg, TAM, and MDSC levels increased progressively (P<0.05), indicating an immunosuppressive phenotype. Kaplan-Meier analysis showed significant differences in recurrence-free survival among the risk groups (log-rank test, P<0.001). Conclusion The pathology-based MVI risk stratification system effectively reflects the invasive characteristics of HCC and differences in the immune microenvironment and serves as an independent predictor of postoperative recurrence and survival. Compared with traditional binary MVI assessment (presence/absence), this stratification system provides a more refined approach and may offer important guidance for postoperative risk management, follow-up strategies, and adjuvant treatment decision-making in HCC patients.

Key words: Hepatocellular carcinoma, Microvascular invasion, Pathological features, Immune microenvironment, Prognostic analysis