国际医学放射学杂志2025，Vol.48Issue(2)：125-131,7.DOI:10.19300/j.2025.L21920
食管鳞状细胞癌新辅助化疗联合免疫治疗后头侧癌旁组织与切缘组织的CT影像组学对比研究
Comparative analysis of CT radiomics features between cephalic para-carcinoma tissues and resection margin in esophageal squamous cell carcinoma after neoadjuvant chemotherapy and immunotherapy
摘要
Abstract
Objective To explore the feasibility of radiomics models based on contrast-enhanced computed tomography(CECT)in distinguishing cephalic para-carcinoma tissues and resection margin in esophageal squamous cell carcinoma(ESCC)following neoadjuvant chemotherapy and immunotherapy(NACI).Methods This retrospective study included 188 pathologically confirmed ESCC patients who underwent NACI,recruited from two medical centers.A total of 138 patients from Center A were randomly divided into a training set(97 cases)and an internal validation set(41 cases)at a 7∶3 ratio,while 50 patients from Center B served as an external validation set.Using an open-source software 3D-Slicer,four regions of interest(ROIs)representing cephalic para-carcinoma tissues(P1,P2,P3,and P4)at 1 cm,2 cm,3 cm,and 4 cm above the tumor margin,respectively,and one ROI for resection margin tissue(P5,5 cm above the tumor)were delineated on CECT images.Radiomics features were extracted using the Pyradiomics package.The radiomics features obtained from four cephalic para-carcinoma tissues were individually paired with those of resection margin tissue to differentiate between them,which were designated as groups P1,P2,P3,and P4,respectively.Univariate analysis and the least absolute shrinkage and selection operator(LASSO)method were employed to select optimal radiomics features in the training sets,and logistic regression models were constructed.The area under the receiver operating characteristic(ROC)curve(AUC)was used to assess the discriminatory performance of the radiomics models.Results The AUCs of the P1 model in the training,internal validation,and external validation sets were 0.831,0.820,and 0.787,respectively.The AUCs of the P2 model were 0.809,0.797,and 0.769,respectively.Both the P1 and P2 models demonstrated good discriminatory performance(AUC＞0.76),with the P1 model achieving higher AUC values than the P2 model in all datasets.Conclusion The CECT-based radiomics model demonstrates high efficacy in distinguishing cephalad peritumoral(P1 and P2)and resection margin tissues in ESCC following NACI.关键词
食管鳞状细胞癌/新辅助化疗/免疫治疗/体层摄影术,X线计算机/影像组学Key words
Esophageal squamous cell carcinoma/Neoadjuvant chemotherapy/Immunotherapy/Tomography,X-ray computed/Radiomics分类
特种医学引用本文复制引用
苟月芹,高丹,欧静,陈天武..食管鳞状细胞癌新辅助化疗联合免疫治疗后头侧癌旁组织与切缘组织的CT影像组学对比研究[J].国际医学放射学杂志,2025,48(2):125-131,7.基金项目
国家自然科学基金(82271959) （82271959）
