探究PET/CT影像组学模型对非小细胞肺癌Ki-67表达状态的预测作用  

The investigation of the predictive effect of PET/CT radiomics model for Ki-67 expression status in non-small cell lung cancer

作　　者：李博 苏婕 陈晨 胡春峰 LI Bo;SU Jie;CHEN Chen;HU Chunfeng(Department of Radiology,the Affiliated Hospital of Xuzhou Medical University,Xuzhou,Jiangsu Province 221000,China;Department of Ultrasound Medicine,Xuzhou Children's HospitalAffiliated to Xuzhou Medical University,Xuzhou,Jiangsu Province 221000,China)

机构地区：[1]徐州医科大学附属医院放射科,江苏徐州221000 [2]徐州医科大学附属徐州儿童医院超声医学科,江苏徐州221000

出　　处：《实用放射学杂志》2024年第9期1429-1433,共5页Journal of Practical Radiology

摘　　要：目的 基于PET/CT影像组学特征联合临床特征构建融合模型对非小细胞肺癌(NSCLC)患者Ki-67表达状态的预测效果.方法 纳入NSCLC患者110例,行PET/CT检查、Ki-67检测.采用Mann-Whitney U检验、最小绝对收缩和选择算子(LASSO)算法和Spearman相关分析选择最显著的特征,建立PET模型、CT模型、PET/CT模型及融合模型,通过曲线下面积(AUC)等指标比较4种模型的效能.结果 基于PET/CT影像组学特征联合临床指标构建的融合模型训练集的AUC[0.961,95%置信区间(CI)0.922~0.999]和测试集的AUC(0.893,95%CI 0.772~1.000)均高于其他3种模型,其模型效能最好.结论 PET/CT影像组学特征联合临床指标构建的融合模型预测NSCLC患者的Ki-67表达状态效果最优,有助于评估患者预后情况及制订个体化治疗方案.Objective To predict the Ki-67 expression status of non-small cell lung cancer(NSCLC)by constructing a fusion model based on PET/CT radiomics features combined with clinical indicators.Methods A total of 11o NSCLC patients were enrolled,and underwent PET/CT scans and Ki-67 detection.The Mann-Whitney U test,the least absolute shrinkage and selection operator(LASSO)method,and Spearman correlation analysis were used to identify the most significant features.The PET model,CT model,PET/CT model,and fusion model were established and their efficacies were compared by the area under the curve(AUC).Results The fusion model with PET/CT radiomics features and clinical indicators outperformed the other three models,with an AUC of 0.961[95%confidence interval(CI)0.922-0.999]J in the training set and an AUC of 0.893(95%CI 0.772-1.000)in the test set.Conclusion The fusion model with PET/CT radiomics features and clinical indicators provides the most effective prediction of Ki-67 expression status in NSCLC patients,which is helpful for the assessment of patient prognosis and the formulation of personalized treat-ment plans.

关 键 词：非小细胞肺癌 KI-67 影像组学 融合模型 

分 类 号：R734.2[医药卫生—肿瘤] R445[医药卫生—临床医学] R446.8