high-grade gliomas

Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas

Editor’s Choice MR imaging data and molecular information were retrospectively obtained from The Cancer Imaging Archives for 259 patients with either low- or high-grade gliomas. A convolutional neural network was trained to classify IDH1 mutation status, 1p/19q codeletion, and MGMT promotor methylation status. Classification

Early Biomarkers from Conventional and Delayed-Contrast MRI to Predict the Response to Bevacizumab in Recurrent High-Grade Gliomas

Editor’s Choice Twenty-four patients with recurrent high-grade gliomas were scanned before and during bevacizumab treatment with standard and delayed-contrast MRI. The mean change in lesion volumes of responders (overall survival, >1 year) and nonresponders (overall survival, <1 year) was evaluated.