无线电技术
医学
新辅助治疗
模式
磁共振成像
放射科
肿瘤科
内科学
癌症
乳腺癌
社会科学
社会学
作者
Maxiaowei Song,Shuai Li,Hongzhi Wang,Ke Hu,Fengwei Wang,Huajing Teng,Zhi Wang,Jin Liu,Angela Y. Jia,Yong Cai,Yongheng Li,Xianggao Zhu,Jie Geng,Yangzi Zhang,Xiang-Bo Wan,Weihu Wang
标识
DOI:10.1038/s41416-022-01786-7
摘要
To analyse the performance of multicentre pre-treatment MRI-based radiomics (MBR) signatures combined with clinical baseline characteristics and neoadjuvant treatment modalities to predict complete response to neoadjuvant (chemo)radiotherapy in locally advanced rectal cancer (LARC).Baseline MRI and clinical characteristics with neoadjuvant treatment modalities at four centres were collected. Decision tree, support vector machine and five-fold cross-validation were applied for two non-imaging and three radiomics-based models' development and validation.We finally included 674 patients. Pre-treatment CEA, T stage, and histologic grade were selected to generate two non-imaging models: C model (clinical baseline characteristics alone) and CT model (clinical baseline characteristics combining neoadjuvant treatment modalities). The prediction performance of both non-imaging models were poor. The MBR signatures comprising 30 selected radiomics features, the MBR signatures combining clinical baseline characteristics (CMBR), and the CMBR incorporating neoadjuvant treatment modalities (CTMBR) all showed good discrimination with mean AUCs of 0.7835, 0.7871 and 0.7916 in validation sets, respectively. The three radiomics-based models had insignificant discrimination in performance.The performance of the radiomics-based models were superior to the non-imaging models. MBR signatures seemed to reflect LARC's true nature more accurately than clinical parameters and helped identify patients who can undergo organ preservation strategies.
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