基于临床-CT影像构建肺癌脑转移风险预测模型的研究  

The construction of the clinical-CT imaging model for predicting the incidence of brain metastasis in lung cancer

作　　者：朱越 周之怀 王健[3] 陈文静 杜炎晨 ZHU Yue;ZHOU Zhihuai;WANG Jian;CHEN Wenjing;DU Yanchen(Department of Radiology,the Second Affiliated Hospital of Bengbu Medical College,Bengbu,Anhui Province 233040,China;School of Imaging,Bengbu Medical College,Bengbu,Anhui Province 233030,China;Department of Radiology,Tongde Hospital of Zhejiang Province,Hangzhou 311122,China)

机构地区：[1]蚌埠医科大学第二附属医院放射科,安徽蚌埠233040 [2]蚌埠医科大学影像学院,安徽蚌埠233030 [3]浙江省立同德医院放射科,浙江杭州311122

出　　处：《实用放射学杂志》2025年第3期404-409,共6页Journal of Practical Radiology

摘　　要：目的 探讨基于临床-CT影像构建肺癌脑转移风险预测模型的价值.方法 回顾性分析208例经手术病理或穿刺活检确诊为肺癌患者的临床及CT影像学资料,转移组98例,未转移组110例.2组间行单因素及二元logistic回归分析,根据筛选出的独立危险因素分别构建临床、CT影像和临床-CT影像模型,并绘制受试者工作特征(ROC)曲线、校准曲线及决策曲线分析(DCA)评估模型效能.结果 多因素分析发现肺部原发肿瘤的T分期、病理类型、放化疗治疗方式、手术切除、长径(LD)、短径(SD)、最小CT值(CT_(min))是预测脑转移的独立影响因素(P<0.05).构建的临床、CT影像和临床-CT影像模型的曲线下面积(AUC)分别为0.925、0.764、0.941.DeLong检验分析发现临床-CT影像模型与临床、CT影像模型的 AUC差异有统计学意义(Z=2.093、5.777,P均<0.05);校准曲线显示临床-CT影像模型的拟合度较好,DCA显示临床-CT影像模型的临床净收益更高.结论 临床-CT影像模型能有效地预测肺癌脑转移发生的风险,有助于指导临床制订精准的诊疗方案.Objective To investigate the value of constructing a risk prediction model of brain metastasis in lung cancer based on clinical-CT imaging.Methods The clinical and CT imaging data of 208 patients with lung cancer confirmed by surgical pathology or puncture biopsy were analyzed retrospectively,including 98 patients in the metastasis group and 110 patients in the non-metastasis group.Univariable and binary logistic regression analyses were performed between the two groups,and the clinical,CT imaging,and clinical-CT imaging models were constructed according to the selected independent risk factors.Prediction model performance was evaluated with receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA).Results Multivariate analysis showed that T stage,pathological type,radiotherapy and chemotherapy,surgery,long diameter(LD),short diameter(SD),minimum CT value(CT_(min))were the independent risk factors for predicting brain metastasis in lung cancer(P<0.05).The area under the curve(AUC)of clinical,CT imaging and clinical-CT imaging models were 0.925,0.764,0.941,respectively.DeLong test analysis showed that the AUC of clinical-CT imaging model,clinical model and CT imaging model was statistical difference(Z=2.093,5.777,all P<0.05).The calibration curve suggested a good fit of the clinical-CT imaging model.The DCA suggested that the clinical-CT imaging model demonstrates good clinical benefits.Conclusion The clinical-CT imaging model can effectively predict the occurrence of brain metastasis in lung cancer,which is helpful to guide the development of accurate diagnosis and treatment plan.

关 键 词：肺癌 脑转移 预测模型 计算机体层成像 

分 类 号：R734.2[医药卫生—肿瘤] R739.41[医药卫生—临床医学] R814.42