The identification of the isocitrate dehydrogenase mutant (IDHMUT) glioma and IDH wild-type (IDHWT) glioma has significant diagnostic, prognostic, and therapeutic implications. In this work, we evaluated the non-invasive prediction of IDH mutation status in glioma mice by employing a combination of high spectral resolution CEST MRI at 11.7T together with data analysis using machine learning approaches. We demonstrated that in vivo CEST signals correspond very well with glioma genotypes. Among several CEST signals, the signals at Δω =3.5 ppm may serve as the major indicator to differentiate the IDH genotype glioma from other types.
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