探讨增强CT图像的影像征象在术前预测肝细胞肝癌微血管浸润的价值

To Explore the Value of Imaging Features of Enhanced CT Images in Predicting Microvascular Infiltration in Hepatocellular Carcinoma

摘要: 目的：探讨增强CT图像的影像征象在术前预测肝细胞肝癌(hepatocellular carcinoma, HCC)微血管浸润(microvascular invasion, MVI)方面的价值。方法：对121例经术后病理证实并术前行CT平扫 + 增强扫描的HCC患者进行回顾性研究，分析患者临床指标(年龄、性别、甲胎蛋白)及影像征象(肿瘤最大径、假包膜、肿瘤形态、瘤周低密度环、瘤内动脉、病灶数目、瘤周异常灌注、大血管侵犯、强化方式)，根据有无微血管浸润分为MVI阳性组及MVI阴性组，以单因素分析及多因素logistic回归分析筛选HCC MVI的增强CT图像的影像征象相关独立危险因素，构建回归模型，绘制受试者工作特征(receiver operating characteristic, ROC)曲线，计算曲线下面积(area under the curve, AUC)，评估独立预测因素及回归模型对MVI的预测效能。结果：MVI阳性组AFP水平及肿瘤最大径高于MVI阴性组(P < 0.05)，MVI阳性组肿瘤形态不规则、瘤内动脉、病灶数目及大血管侵犯的发生率均高于MVI阴性组(P < 0.05)，肿瘤形态及数目是MVI的独立预测因素，其预测MVI的AUC分别为0.637和0.625，回归模型的AUC值为0.714。结论：增强CT图像的影像特征可以有效的预测肝细胞肝癌MVI。

Abstract: Objective: To explore the value of imaging features of enhanced CT images in preoperative predict-ing microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Methods: 121 patients with primary hepatocellular carcinoma confirmed by postoperative pathology and underwent CT plain scan and enhanced scan before operation were studied retrospectively. The clinical indexes (Age, Sex, Alpha Fetoprotein-AFP) and imaging features (tumor maximum diameter, pseudocapsule, tu-mor morphology, peritumoral low density ring, intratumoral artery, lesion number, abnormal peritumoralperfusion, macrovessel invasion, enhancement type) were analyzed. They were divided into MVI positive group and MVI negative group according to the presence of microvascular inva-sion. Univariate analysis and multivariate logistic regression analysis were used to screen the in-dependent predictors of HCC MVI among the image features of enhanced CT images, and then a re-gression model was constructed. Receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC) was calculated to evaluate the predictive efficacy of independent pre-dictors and regression model for MVI. Results: The AFP and tumor maximum diameter in MVI posi-tive groups were higher than the MVI negative group (P < 0.05), and the MVI positive group had ir-regular morphology; internal artery, lesion number and large vessel invasion were higher than the MVI negative group (P < 0.05); tumor morphology and number were independent predictors of MVI, with AUC for HCC MVI of 0.637 and 0.625, respectively, while the AUC of the regression model was 0.714. Conclusion: Enhanced imaging features of CT images can effectively predict HCC MVI.