分子影像学杂志2025，Vol.48Issue(4)：484-491,8.DOI:10.12122/j.issn.1674-4500.2025.04.15
CT增强影像组学模型对结直肠癌旁肿瘤沉积的诊断价值
Diagnostic value of imaging omics models based on CT enhanced intratumoral and peritumoral imaging in adjacent tumor deposition of colorectal cancer
摘要
Abstract
Objective To explore the diagnostic value of a radiomics model based on the intratumoral and peritumoral regions in contrast-enhanced CT for peritumoral tumor deposits(TDs)in colorectal cancer(CRC).Methods A retrospective analysis was conducted on contrast-enhanced CT images of 330 CRC patients,confirmed by surgical pathology,from our hospital and the TCIA database between January 2017 and September 2024.Based on postoperative pathology,patients were classified into TDs-positive and TDs-negative groups.Using random sampling,patients were split into a training set(n=231)and a testing set(n=99)in a 7:3 ratio.Regions of interest(ROI)were manually delineated layer by layer on contrast-enhanced venous-phase images to generate volume of interest.The peritumoral ROIs were expanded outward by 2,4 and 6 mm.Radiomic features were extracted from each ROI using pyradiomics,and LASSO was employed for feature selection.XGBoost machine learning algorithm was used to construct separate prediction models for intratumoral,peritumoral,and combined intratumoral-peritumoral features.The diagnostic performance of each model was evaluated using ROC curves,and the DeLong test was used to compare the predictive performance of different models.Results The area under the ROC curve(AUC)for the intratumoral model was 0.937 in the training set and 0.828 in the testing set.Among the peritumoral models,the 4 mm peritumoral region exhibited the best diagnostic performance,achieving an AUC of 0.933 in the training set and 0.830 in the testing set.The combined intratumoral-peritumoral model demonstrated the highest predictive performance,with an AUC of 0.951 in the training set and 0.883 in the testing set.Decision curve analysis indicated that the combined model provided the highest net benefit for predicting TDs.Conclusion The radiomics model integrating intratumoral and peritumoral regions based on contrast-enhanced CT effectively predicts peritumoral TDs in CRC,offering the highest net benefit for TDs prediction.This model can assist clinicians in decision-making and outperforms traditional radiomics models based on either intratumoral or peritumoral features alone.关键词
计算机断层扫描/瘤内瘤周/影像组学/结直肠癌/肿瘤沉积Key words
computed tomography/intratumoral tumor/radiomics/colorectal cancer/tumor deposition引用本文复制引用
刘燕,罗锦文,刘艳丽,唐亚霞..CT增强影像组学模型对结直肠癌旁肿瘤沉积的诊断价值[J].分子影像学杂志,2025,48(4):484-491,8.基金项目
广东省医学科研基金面上项目(A2023485) （A2023485）
广州市教育局高校研究生科研项目(2024312248) （2024312248）
广州市卫生健康科技一般引导项目(20241A011099) （20241A011099）
