Gliomas that only have the telomerase reverse transcriptase promoter mutation (TERTp-only) are known to have the worst overall survival. The aim of this study was to analyze magnetic resonance spectroscopic (MRS) differences of different grades of TERTp-only gliomas, and classify these groups using machine learning. The results indicated that the ratios of glycerophosphocholine (GPC), glutathione (GSH), total choline (tCho), and glutamine and glutamate complex (Glx) to total creatine increased along with the tumor grade, and machine learning models classified low- and high-grade TERTp-only gliomas with a high accuracy.
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