Abstract
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Objectives: Different isocitrate dehydrogenase (IDH) status of gliomas results in different natural history, treatment, and prognosis. Low-grade gliomas (LGGs) with IDH mutant are kind of gliomas with the most favorable outcome. Radiomics analysis from multimodality MRI or FDG PET images have proved to be sufficient for IDH prediction. But they might be currently hard to interpret in routine clinical settings. A less invasive and convenient method for pre-operative prediction IDH genotype is desired. Therefore we tried to develop a methionine-positron emission tomography/computed tomography(MET PET/CT)-based nomogram model that only uses easy-accessible imaging features to achieve reliable non-invasive IDH-mutant prediction with strong clinical translation capability. Materials and Methods: This study investigates the potential ability of MET PET/CT to determine IDH genotype of diffuse gliomas through a retrospective review of information of 110 glioma patients. Patients underwent pre-operative MET-PET, followed by operation or biopsy and IDH histopathological analysis. SUVmax, SUVmean, SUVpeak, metabolic tumor volume(MTV), total lesion methionine uptake(TLMU), and standard deviation of SUV(SUVSD) of all MET PET images were obtained via a dedicated workstation(Siemens. syngo.via). The t-test and receiver operating characteristic(ROC) curve analysis were conducted for statistical analysis. Univariate and multivariate logistic regression models were used to identify the predictive factors for IDH mutation. Nomogram development and calibration plots were further performed.
Results: In the entire population, TNRmean, TNRmax, TNRpeak (defined as the lesion SUV/normal contralateral cortical SUVmean), and SUVSD of IDH-mutant glioma patients were lower than these values of IDH wild-type. No statistical differences of MTV or TLMU were observed between the two groups. Receiver operating characteristic analysis suggested SUVSD had the best performance among single parameters (AUC = 0.731, cutoff≤0.29, p < 0.001). SUVSD further displayed good correlations with other MET TNRs. Multivariate regression demonstrated that SUVSD (>0.29 vs ≤0.29 OR: 0.746, p= 0.010) , the involvement of brain middle line structure (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 IDHmut status. The nomogram showed good discrimination, with a C-index of 0.866 (95%CI: 0.796 - 0.937) and was well-calibrated.
Conclusions: C-Methionine PET/CT features( SUVSD and the involvement of brain line structure) can be conveniently used to facilitate the pre-operative prediction of the IDH genotype. The nomogram model based on C-Methionine PET/CT and clinical age features were clinically useful and promising.
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