目的:携带不同KIT外显子11(KIT-11)突变的胃肠道间质瘤(GIST)表现出对伊马替尼的不同预后和反应。在这里,我们的目的是确定计算机断层扫描(CT)影像组学是否可以准确地对KIT-11突变基因型进行分层,从而有利于伊马替尼治疗和GIST监测.
方法:总的来说,来自3个独立中心的1143个GIST被分为训练队列(TC)或验证队列(VC)。此外,KIT-11突变基因型分为4类:无KIT-11突变(K11-NM),点突变或重复(K11-PM/D),KIT-11557/558缺失(K11-557/558D),和KIT-11缺失,不涉及密码子557/558(K11-D)。随后,根据对比CT的动脉期生成影像组学特征(RS),然后使用1408定量图像特征和LASSO回归分析将其开发为KIT-11突变预测因子,进一步评估其预测能力。
结果:K11-NM的TCAUC,K11-PM/D,K11-557/558D,K11-D范围为0.848(95%CI0.812-0.884),0.759(95%CI0.722-0.797),0.956(95%CI0.938-0.974),和0.876(95%CI0.844-0.908),而VCAUC范围为0.723(95%CI0.660-0.786),0.688(95%CI0.643-0.732),0.870(95%CI0.824-0.918),和0.830(95%CI0.780-0.878)。KIT-11突变基因型的宏观加权AUC范围为TC中的0.838(95%CI0.820-0.855)至VC中的0.758(95%CI0.758-0.784)。TC对基于RS的KIT-11突变基因型预测的总体准确度为0.694(95CI0.660-0.729),而VC的准确度为0.637(95CI0.595-0.679)。
结论:CT影像组学特征在估计KIT-11突变基因型方面表现出良好的预测性能,特别是在K11-557/558D基因型的预测中。基于RS的K11-NM分类,K11-557/558D,和K11-D患者可能是选择伊马替尼治疗的适应症。
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.
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.
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).
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.