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中华消化病与影像杂志(电子版) ›› 2026, Vol. 16 ›› Issue (03) : 248 -255. doi: 10.3877/cma.j.issn.2095-2015.2026.03.011

论著

基于微血流成像联合超声造影的回归模型评估肝细胞癌微血管侵犯的临床价值
张洪涛1, 于大中2, 王静怡3,()   
  1. 1063000 河北省,唐山市第三医院超声科
    2063000 河北省,唐山市第三医院肿瘤科
    3063000 河北省,唐山市人民医院功能检查科
  • 收稿日期:2026-03-31 出版日期:2026-06-01
  • 通信作者: 王静怡
  • 基金资助:
    河北省卫生健康委医学科学研究课题(20201539)

Evaluation of the clinical value of microvascular invasion in hepatocellular carcinoma based on the regression model combining microvascular imaging and contrast-enhanced ultrasound

Hongtao Zhang1, Dazhong Yu2, Jingyi Wang3,()   

  1. 1Department of Ultrasound, Tangshan Third Hospital, Tangshan 063000, China
    2Department of Oncology, Tangshan Third Hospital, Tangshan 063000, China
    3Department of Functional Examination, Tangshan People's Hospital, Tangshan 063000, China
  • Received:2026-03-31 Published:2026-06-01
  • Corresponding author: Jingyi Wang
引用本文:

张洪涛, 于大中, 王静怡. 基于微血流成像联合超声造影的回归模型评估肝细胞癌微血管侵犯的临床价值[J/OL]. 中华消化病与影像杂志(电子版), 2026, 16(03): 248-255.

Hongtao Zhang, Dazhong Yu, Jingyi Wang. Evaluation of the clinical value of microvascular invasion in hepatocellular carcinoma based on the regression model combining microvascular imaging and contrast-enhanced ultrasound[J/OL]. Chinese Journal of Digestion and Medical Imageology(Electronic Edition), 2026, 16(03): 248-255.

目的

探讨基于术前微血流成像(MFI)联合超声造影(CEUS)的多参数回归模型在预测肝细胞癌(HCC)微血管侵犯(MVI)中的临床价值。

方法

回顾性分析唐山市第三医院2022年1月至2025年8月期间经术后病理证实的186例HCC患者的临床资料。所有患者术前均行MFI及CEUS检查。以术后病理诊断MVI为金标准,将患者分为MVI阳性组(72例)与MVI阴性组(114例)。采用单因素分析和LASSO回归筛选预测因子,并通过多因素Logistic回归构建联合预测模型。受试者工作特征(ROC)曲线评估模型及各独立预测因子的诊断效能。

结果

MVI阳性组的肿瘤最大直径显著大于阴性组,且甲胎蛋白>400 μg/L的患者比例更高(均P<0.001)。MVI阳性组的高MFI血流分级、瘤周滋养血管、增强不均匀性、早期廓清≤60 s及瘤周强化方面的比例均显著高于MVI阴性组(均P<0.001)。Spearman相关性分析显示,MVI状态与MFI血流分级、瘤周滋养血管、增强不均匀性、早期廓清以及瘤周强化均呈弱至中度正相关(r为0.173~0.419,均P<0.05)。多因素Logistic回归结果显示:肿瘤最大直径(OR=2.182)、甲胎蛋白>400 μg/L(OR=6.664)、高MFI血流分级(OR=7.126)、增强不均匀性(OR=4.418)及瘤周强化(OR=5.849)是预测MVI的独立危险因素(均P<0.05)。ROC分析显示,联合预测模型的曲线下面积为0.930,优于任一单一指标(均P<0.001),灵敏度为0.764,特异度为0.939。

结论

基于术前MFI联合CEUS构建的联合预测能有效预判HCC的MVI状态,其诊断价值显著优于单一影像或血清学指标,有望为HCC患者的术前个体化治疗决策提供有价值参考。

Objective

To explore the clinical value of a multi-parameter regression model based on preoperative microvascular flow imaging (MFI) combined with contrast-enhanced ultrasound (CEUS) in predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods

A retrospective analysis was conducted on the clinical data of 186 HCC patients who had undergone postoperative pathological confirmation in Tangshan Third Hospital from January 2022 to August 2025. All patients underwent MFI and CEUS examinations before surgery. The postoperative pathological diagnosis of MVI was used as the gold standard to divide the patients into the MVI positive group (72 cases) and the MVI negative group (114 cases). Univariate analysis and LASSO regression were used to screen the predictive factors, and a combined predictive model was constructed through multivariate Logistic regression. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the model and each independent predictive factor.

Results

The maximum diameter of tumors in the MVI positive group was significantly larger than that in the MVI negative group, and the proportion of patients with alpha-fetoprotein (AFP) >400 μg/L was also higher (both P<0.001). The proportions of high MFI blood flow grading, peritumoral nutrient vessels, heterogeneous enhancement, early clearance ≤60 seconds, and peritumoral enhancement in the MVI positive group were significantly higher than those in the MVI negative group (all P<0.001). Spearman correlation analysis showed that the MVI status was weakly to moderately positively correlated with MFI blood flow grading, peritumoral nutrient vessels, heterogeneous enhancement, early clearance, and peritumoral enhancement (r ranged from 0.173 to 0.419, all P<0.05). Multivariate Logistic regression analysis showed that the maximum tumor diameter (OR=2.182), AFP> 400 μg/L (OR=6.664), high MFI blood flow grading (OR=7.126), heterogeneous enhancement (OR=4.418), and peritumoral enhancement (OR=5.849) were independent risk factors for MVI (all P<0.05). ROC analysis showed that the area under the curve of the combined prediction model was 0.930, which was superior to any single indicator (all P<0.001), with a sensitivity of 0.764 and a specificity of 0.939.

Conclusion

The combined prediction model constructed based on preoperative MFI and CEUS can effectively predict the MVI status of HCC. Its diagnostic value is significantly superior to that of either imaging or serological indicators, and it is expected to provide an important reference for the preoperative individualized treatment decisions of HCC patients.

表1 两组肝细胞癌患者基线资料比较
表2 两组肝细胞癌患者超声指标比较
表3 肝细胞癌患者微血管侵犯与超声特征的相关性分析
图1 Lasso回归模型构建注:纵坐标为标准化后的回归系数,横坐标为对数(λ);MFI微血流成像;AFP甲胎蛋白
图2 Lasso回归模型筛选注:纵坐标为模型均方误差(MSE),横坐标为对数(λ)
表4 自变量赋值
表5 肝细胞癌患者的微血管侵犯状态影响因素分析
图3 各预测因子诊断效能的ROC曲线注:MFI微血流成像;AFP甲胎蛋白
表6 ROC曲线评估模型及各独立预测因子的诊断效能
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