基于增强CT的胆囊癌神经浸润危险因素分析及预测模型构建  

Risk factors and construction of prediction model of perineural invasion of gallbladder carcinoma based on enhanced CT-image features

作　　者：霍文礼 寇雪纯 李起 刘哲[1] 梁挺[1] HUO Wenli;KOU Xuechun;LI Qi;LIU Zhe;LIANG Ting(Department of Radiology,The First Affiliated Hospital of Xi'an Jiaotong University,Xi’an 710061;Department of Medical Business Unit,Shaanxi Healthcare Group Co.,Ltd.,Xi’an 710100;Department of Hepatobiliary Surgery,The First Affiliated Hospital of Xi'an Jiaotong University,Xi’an 710061,China)

机构地区：[1]西安交通大学第一附属医院医学影像科,陕西西安710061 [2]陕西健康医疗集团有限公司医疗事业部,陕西西安710100 [3]西安交通大学第一附属医院肝胆外科,陕西西安710061

出　　处：《西安交通大学学报（医学版）》2024年第3期455-460,共6页Journal of Xi’an Jiaotong University（Medical Sciences）

基　　金：国家自然科学基金面上项目(No.82272073)。

摘　　要：目的基于术前增强CT影像特征构建胆囊癌(gallbladder carcinoma,GBC)神经浸润(perineural invasion,PNI)的预测模型并评价其预测效能。方法回顾性分析180例行根治术的GBC患者的临床、影像及病理资料。根据是否存在PNI分为阳性组与阴性组。由2位影像科医师评估术前增强CT影像特征(包括有无胆囊结石、影像肝侵犯、血管侵犯、T分期及肝门部或腹膜后淋巴结转移)。采用独立样本t检验、Mann-Whitney U检验及χ^(2)检验比较CT征象与PNI的相关性,采用Logistics回归分析筛选独立危险因素并建立预测模型公式,采用受试者工作特征(ROC)曲线评估预测模型的预测效能并计算相应的曲线下面积(AUC),采用Hosmer-Lemeshow拟合优度检验对预测模型进行验证。结果单因素分析结果显示CA199、CA125和影像肝侵犯、血管侵犯(肝动脉或门静脉)、T分期及肝门部或腹膜后淋巴结转移与PNI相关(P<0.05)。Logistics多因素分析结果显示CA199、影像血管侵犯(肝动脉或门静脉)、影像T分期是PNI的独立危险因素。依据上述独立危险因素建立预测模型公式并绘制ROC曲线,AUC为0.807(95%CI:0.734~0.879),灵敏度为0.792,特异度为0.697。Hosmer-Lemeshow拟合优度检验卡方值为0.594,P=0.997,提示模型的预测值与实际值接近。结论联合CA199、影像血管侵犯、T分期等术前临床-增强CT特征建立预测模型,能够有效预测GBC术后PNI。Objective To construct the prediction model of perineural invasion(PNI)in gallbladder carcinoma(GBC)based on preoperative enhanced CT image features and evaluate its prediction efficiency.Methods The clinical,imaging and pathological data of 180 GBC patients undergoing radical operation were retrospectively analyzed.They were divided into positive and negative groups according to the presence or absence of PNI.Preoperative enhanced CT imaging features(including presence of gallstones,imaging hepatic invasion,vascular invasion,T-stage,and hilar or retroperitoneal lymph node metastases)were evaluated by two radiologists.Independent sample t-test,Mann Whitney U test,andχ^(2)test were used to compare the correlation between CT signs and PNI.Logistics regression analysis was used to screen independent risk factors and establish the prediction model formula.ROC curve was used to evaluate the prediction efficiency of the prediction model and the corresponding area under the curve(AUC)was calculated.Hosmer-Lemeshow goodness of fit test was used to verify the prediction model.Results Unifactorial analysis showed that CA199,CA125,imaging hepatic invasion,vascular invasion(hepatic artery or portal vein),T-stage,and hilar or retroperitoneal lymph node metastasis were correlated with nerve invasion(P<0.05).Logistics multi-factor analysis results showed that CA199,imaging vascular invasion(hepatic artery or portal vein),and imaging T stage were independent risk factors for PNI.Based on the above independent risk factors,a prediction model formula was established and ROC curve was drawn,with an AUC of 0.807(95%CI:0.734~0.879),sensitivity of 0.792,specificity of 0.697,and the chi-square value of Hosmer-Lemeshow goodness of fit test of 0.594(P=0.997),indicating that the predicted value of the model was close to the actual value.Conclusion Combining CA199,imaging vascular invasion,T-stage,and other preoperative clinically-enhanced CT features to establish a prediction model can effectively predict postoperative PNI of GBC.

关 键 词：胆囊癌(GBC) 神经浸润(PNI) 增强CT 预测模型 

分 类 号：R445.3[医药卫生—影像医学与核医学]