Abstract
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: One hundred and ten 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, p < 0.001). All pairs of the 11C-MET PET metrics showed linear associations by Pearson correlation coefficients between 0.228 and 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 (≤ 45 vs. >45 years 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.
Highlights
IntroductionIsocitrate dehydrogenase enzyme (IDH) mutations have been proven to be an inciting event in gliomagenesis, which made a great difference in the molecular and genetic route of oncogenic progression and clinical outcome [1]
Gliomas are the most prevalent malignant primary tumors of the brain
Our data demonstrated that TNRs and SUVSD were significantly lower in the isocitrate dehydrogenase enzyme (IDH)-mutant group compared with those IDH-wildtypes, which are consistent with those of Kim et al [15] 11C-MET PET derived SUVSD showed the most excellent ability to identify whether glioma had an IDH mutation or not besides other MET PET metrics
Summary
Isocitrate dehydrogenase enzyme (IDH) mutations have been proven to be an inciting event in gliomagenesis, which made a great difference in the molecular and genetic route of oncogenic progression and clinical outcome [1]. IDH mutations were identified in low grade glioma (LGG) and secondary glioblastoma multiforme (GBM) with a high percentage but in primary GBM with a much lower percentage [2]. Glioma patients with IDH mutation had been prone to significantly better progression-free survival than those IDH wildtype counterparts, irrespective of grade or received treatments [3]. The gold standard of IDH mutations detection relies on immunohistochemistry or genetic sequencing of the surgical specimens. Given the inherent risk of surgery or biopsy, substantial research efforts have focused on the pre-operative non-invasive prediction of IDH mutational status in gliomas
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