Isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase promoter (TERTp) mutations affect the clinical behavior and survival rate of diffuse gliomas. The detection of these mutations preoperatively is very critical for treatment planning. In this study, three different one dimensional convolutional neural network (1D-CNN) models were designed to identify IDH mutant (IDH-mut), TERTp mutant (TERTp-mut), and TERTp-only (IDH-wild type and TERTp-mut) gliomas based on proton magnetic-resonance spectroscopy (1H-MRS). The 1D-CNN models could identify IDH-mut, TERTp-mut, and TERTp-only gliomas with 94.11%, 76.92%, and 82.05% accuracies, respectively. This study showed the potential of deep-learning in predicting especially IDH-mutations in gliomas using 1H-MRS data.
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