A Nomogram Modeling 11C-MET PET/CT and Clinical Features in Glioma Helps Predict IDH Mutation - Zhou, Weiyan; Zhou, Zhirui; Wen, Jianbo; Xie, Fang; Zhu, Yuhua; Zhang, Zhengwei; Xiao, Jianfei; Chen, Yijing; Li, Ming; Guan, Yihui; Hua, Tao (Frontiers in Oncology, 2020)
Purpose: We developed a 11C-Methionine positron emission tomography/computed tomography (11C-MET PET/CT)-based nomogram model that uses easy-accessible imaging and clinical features to achieve reliable non-invasive isocitrate dehydrogenase (IDH)-mutant prediction with strong clinical translational capability. Methods:110 patients with pathologically proven glioma who underwent pretreatment 11C-MET PET/CT were retrospectively reviewed. IDH genotype was determined by IDH1 R132H immunohistochemistry staining. Maximum, mean and peak tumor-to-normal brain tissue(TNRmax, TNRmean, TNRpeak), metabolic tumor volume (MTV), total lesion methionine uptake (TLMU), and standard deviation of SUV(SUVSD) of the lesions on MET PET images were obtained via a dedicated workstation (Siemens. syngo.via). Univariate and multivariate logistic regression models were used to identify the predictive factors for IDH mutation. Nomogram and calibration plots were further performed. Results: In the entire population, TNRmean, TNRmax, TNRpeak and SUVSD of IDH-mutant glioma patients were significantly lower than these values of IDH wildtype. Receiver operating characteristic (ROC) analysis suggested SUVSD had the best performance for IDH-mutant discrimination (AUC = 0.731, cut-off 0.29, p0.001). All pairs of the 11C-MET PET metrics showed linear associations by Pearson correlation coefficients between 0.228-0.986. Multivariate analyses demonstrated that SUVSD (＞0.29 vs. 0.29 OR: 0.053, p= 0.010), dichotomized brain midline structure involvement(no vs. yes OR: 26.52, p = 0.000) and age (45y vs.＞45y OR:3.23, p = 0.023), were associated with a higher incidence of IDH mutation. The nomogram modeling showed good discrimination, with a C-statistics of 0.866 (95%CI: 0.796 - 0.937) and was well-calibrated. Conclusions: 11C-Methionine PET/CT imaging features (SUVSD and the involvement of brain midline structure) can be conveniently used to facilitate the pre-operative prediction of IDH genotype. The nomogram model based on 11C-Methionine PET/CT and clinical age features might be clinically useful in non-invasive IDH mutation status prediction for untreated glioma patients.