Abstract #3483

MRI based IDH and grade prediction using convolutional neural networks

Sumeet Shinde¹, Abhilasha Indoria², Jitender Saini², Manish Beniwal², Vani Santosh², and Madhura Ingalhalikar¹

¹Symbiosis centre for medical image analysis, Symbiosis International University, Pune, India, ²Dept of Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India

Recent developments in glioma subtyping suggest that IDH genotype as well as the histological grading are both crucial factors. However, earlier classification studies based on MRI features have focused either only on grade or IDH. In this work we employ an automated deep learning based technique to delineate the grade as well as the IDH status on a dataset of 178 subjects. Our classifier performs with a superior accuracy of 93.5% and the model explanability is achieved through class activation maps that illustrate the areas important in the classification.

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