Meeting Banner
Abstract #1156

Predicting isocitrate dehydrogenase mutation status using contrastive learning and graph neural networks

Yiran Wei1, Chao Li1, and Stephen John Price1
1Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom


The isocitrate dehydrogenase (IDH) gene mutation status is a prognostic biomarker for gliomas. As an alternative approach to the invasive gold standard of IDH mutation detection, radiogenomics approaches using features of MRI showed promising results in the same task. Here, we proposed an approach to predict the IDH status based on the image and morphology features extracted using contrastive learning. We then constructed a large patient graph based on the extracted features, which could predict the IDH mutation using graph neural networks. The results showed the proposed method outperforms the classifiers which leverage either image or morphology features only.

This abstract and the presentation materials are available to members only; a login is required.

Join Here