Enhancing 1p/19q Classification in Brain Gliomas Using IDH Status: A Deep Learning Study

BACKGROUND AND PURPOSE: IDH mutation & 1p/19q codeletion are critical biomarkers for glioma diagnosis & therapy. 1p/19q codeletion occurs exclusively in IDH-mutated gliomas. In this study, we developed a 2-stage, non-invasive, MRI-based deep learning method that leverages IDH status to enhance 1p/19q predictions. MATERIALS AND METHODS: Predicted IDH-wildtype cases default to 1p/19q non-codeleted. Then the IDH-mutated cases were further classified for 1p/19q status using the 1p/19q-networks. RESULTS: achieved accuracies of 91.5% & 91.2% respectively, improving the classification accuracy by ∼5%. CONCLUSIONS: to gate 1p/19q predictions. The developed method offers a reliable, non-invasive approach to determine important biomarkers for glioma diagnosis.