Personalized radiomics signature to screen for KIT-11 mutation genotypes among patients with gastrointestinal stromal tumors: a retrospective multicenter study

基因型 主旨 医学 突变 伊马替尼 内科学 回顾性队列研究 PDGFRA公司 队列 胃肠病学 肿瘤科 间质细胞 生物 遗传学 基因 髓系白血病
作者
Qing‐Wei Zhang,Ranying Zhang,Zhibo Yan,Yuxuan Zhao,Xinyuan Wang,Jing-Zheng Jin,Qi-Xuan Qiu,J.‐H. Chen,Zhenhui Xie,Jiang Lin,Hui Cao,Yan Zhou,Huimin Chen,Xiaobo Li
出处
期刊:Journal of Translational Medicine [BioMed Central]
卷期号:21 (1) 被引量:3
标识
DOI:10.1186/s12967-023-04520-w
摘要

Abstract Objectives Gastrointestinal stromal tumors (GISTs) carrying different KIT exon 11 (KIT-11) mutations exhibit varying prognoses and responses to Imatinib. Herein, we aimed to determine whether computed tomography (CT) radiomics can accurately stratify KIT-11 mutation genotypes to benefit Imatinib therapy and GISTs monitoring. Methods Overall, 1143 GISTs from 3 independent centers were separated into a training cohort (TC) or validation cohort (VC). In addition, the KIT-11 mutation genotype was classified into 4 categories: no KIT-11 mutation (K11-NM), point mutations or duplications (K11-PM/D), KIT-11 557/558 deletions (K11-557/558D), and KIT-11 deletion without codons 557/558 involvement (K11-D). Subsequently, radiomic signatures (RS) were generated based on the arterial phase of contrast CT, which were then developed as KIT-11 mutation predictors using 1408 quantitative image features and LASSO regression analysis, with further evaluation of its predictive capability. Results The TC AUCs for K11-NM, K11-PM/D, K11-557/558D, and K11-D ranged from 0.848 (95% CI 0.812–0.884), 0.759 (95% CI 0.722–0.797), 0.956 (95% CI 0.938–0.974), and 0.876 (95% CI 0.844–0.908), whereas the VC AUCs ranged from 0.723 (95% CI 0.660–0.786), 0.688 (95% CI 0.643–0.732), 0.870 (95% CI 0.824–0.918), and 0.830 (95% CI 0.780–0.878). Macro-weighted AUCs for the KIT-11 mutant genotype ranged from 0.838 (95% CI 0.820–0.855) in the TC to 0.758 (95% CI 0.758–0.784) in VC. TC had an overall accuracy of 0.694 (95%CI 0.660–0.729) for RS-based predictions of the KIT-11 mutant genotype, whereas VC had an accuracy of 0.637 (95%CI 0.595–0.679). Conclusions CT radiomics signature exhibited good predictive performance in estimating the KIT-11 mutation genotype, especially in prediction of K11-557/558D genotype. RS-based classification of K11-NM, K11-557/558D, and K11-D patients may be an indication for choice of Imatinib therapy.
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