摘要
Abstract
Objective To investigate the risk factors for microvascular invasion(MVI)in small hepatocellular carcinoma(SHCC)and establish a preoperative nomogram prediction model,and assess the accuracy of it.Methods A retrospective analysis was conducted on the clinical data of 288 patients who underwent hepatectomy due to SHCC at the Affiliated Union Hospital of Tongji Medical College,Huazhong University of Science and Technology from Aug.2018 to Aug.2023.Based on the postoperative pathological results,they were divided into MVI positive group(n=96)and MVI negative group(n=192).The general data,serological indicators,inflammatory factors,preoperative imaging data and pathological indicators were collected.Lasso regression analysis combined with univariate and multivariate logistic regression analysis were used to explore the main risk factors for MVI in SHCC patients,and establish a preoperative nomogram prediction model.Results Out of 288 SHCC patients,MVI was confirmed in 96(33.3%).The results of multivariate logistic regression analysis showed that the maximum diameter of the tumor,capsule enhancement,AFP≥200 ng/mL,neutrophil/lymphocyte ratio(NLR)≥1.63,and systemic immune inflammation(SII)≥170.86,platelet count(PLT)≥183.0×109/L were independent risk factors for MVI in SHCC patients(P<0.05).The area under the curve(AUC)of the preoperative nomogram prediction model was 0.823.The optimal cutoff value of the column chart calculated by the Youden index was 181.3 points.The sensitivity,specificity,positive predictive value,and negative predictive value under the cutoff value were 65.6%,84.9%,68.5%,and 83.2%,which showed good discrimination and consistency.Conclusion The preoperative nomogram prediction model based on tumor maximum diameter,capsule enhancement,AFP≥200 ng/mL,NLR≥1.63,SII≥170.86 and PLT≥183.0×109/L has high predictive value for the risk of MVI in SHCC,and is of great significance for guiding clinical decision-making and improving poor prognosis.关键词
小肝癌/微血管侵犯/列线图预测模型/炎症因子/影像组学Key words
small hepatocellular carcinoma/microvascular invasion/nomogram prediction model/inflammatory factors/radiomics分类
医药卫生
