Training a residual CNN on preoperative magnetic resonance imaging of gliomas allows the prediction of IDH status.66 Several studies testing these tools achieved 79% to 94% prediction accuracy of IDH status in patients with high-grade gliomas.66-68 Machine learning models using structural brain networks and graph neural networks can be powerful tools for predicting IDH mutation status based on pretreatment MRI. The gene discussed is IDH1; the disease is glioma.