摘要
目的探讨动脉增强分数(AEF)联合腹部脂肪面积参数对肝细胞癌(HCC)微血管侵犯(MVI)的预测价值。方法回顾性分析210例行根治性切除术的HCC患者相关临床数据。通过单因素及多因素Logistic回归分析筛选HCC MVI的独立危险因素,运用R软件构建术前预测HCC MVI的列线图预测模型。采用Bootstrap法进行模型的内部验证,用验证组进行模型的外部验证,通过一致性指数、校准曲线和决策曲线分析(DCA)评估列线图的区分度、校准度和临床适用性。结果多因素Logistic回归分析显示肿瘤动脉增强分数(T-AEF)、肿瘤直径、内脏脂肪面积(VFA)和皮下脂肪面积(SFA)是HCC MVI的独立预测因子。由这四个变量构建的列线图模型在模型组和验证组的一致性指数分别为0.819(95%CI:0.756,0.883)和0.752(95%CI:0.624,0.881)。通过Youden指数计算出列线图的最佳截断值为116分,该截断值下的敏感度、特异度在模型组中分别为83.3%、84.1%,在验证组中分别为78.0%、80.0%。结论T-AEF联合肿瘤直径、VFA、SFA构建的列线图预测模型可提高对HCC MVI的预测效能,提示临床工作中,T-AEF联合腹部脂肪面积构建的列线图预测模型有助于术前HCC MVI的预测。
Objective To explore the predictive value of the arterial enhancement fraction(AEF)combined with abdominal fat area parameters for microvascular invasion(MVI)in hepatocellular carcinoma(HCC).Methods Clinical data of 210 HCC patients who underwent radical resection at the Second Affiliated Hospital of Kunming Medical University were retrospectively analyzed.Univariate and multivariate Logistic regression analyses were used to screen independent risk factors for HCC MVI,and R software was applied to construct a nomogram prediction model for preoperative prediction of HCC MVI.The Bootstrap method was used for internal validation of the model,and an external validation cohort was used for external validation.The discrimination,calibration,and clinical applicability of the nomogram were evaluated by the concordance index(C-index),calibration curve,and decision curve analysis(DCA).Results Multivariate Logistic regression analysis showed that T-AEF,tumor diameter,visceral fat area(VFA),and subcutaneous fat area(SFA)were independent predictors of HCC MVI.The C-indices of the nomogram model constructed with these four variables were 0.819(95%CI:0.756,0.883)in the modeling group and 0.752(95%CI:0.624,0.881)in the validation group,respectively.The optimal cutoff value of the nomogram calculated by the Youden index was 116 points,the sensitivity and specificity at the critical value were 83.3%and 84.1%in the modeling group,and 78%and 80%in the validation group,respectively.Conclusion The nomogram prediction model constructed by combining T-AEF with tumor diameter,VFA,and SFA can improve the predictive efficacy for HCC MVI,suggesting that in clinical practice,the nomogram prediction model based on T-AEF combined with abdominal fat area is helpful for the preoperative prediction of HCC MVI.
作者
崔梦玲
孙文梅
赵睿敏
鲁春志
王家平
CUI Mengling;SUN Wenmei;ZHAO Ruimin(Department of Radiology,The Second Affiliated Hospital of Kunming Medical University,Kunming,Yunnan Province 650500,P.R.China)
出处
《临床放射学杂志》
北大核心
2026年第1期98-103,共6页
Journal of Clinical Radiology
基金
昆医联合专项项目(编号:202401AY070001-005)
昆明医科大学第二附属医院院内临床项目(编号:ynIIT2022019)。
关键词
动脉增强分数
腹部脂肪面积
肝细胞癌
微血管侵犯
列线图
Arterial enhancement fraction
Abdominal fat area
Hepatocellular carcinoma
Microvascular invasion
Nomograms
