The tumor biology of diffuse-gliomas is best reflected by their molecular profile. Isocitrate dehydrogenase (IDH) mutation status has the strongest correlation to treatment response and patient survival among all molecular markers. The aim of this study is to predict IDH mutation status of gliomas based on short-echo time MR spectroscopic (MRS) biomarkers by using machine learning algorithms at 3T. Our results indicated that MRS based biomarkers were able to discriminate between IDH-mutant and IDH-wild type patients with up to 91% sensitivity, %78 specificity, and 86.9% accuracy by using an ensemble of bootstrap-aggregated decision trees classification with a three-fold cross validation.
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