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

Effects of MRI Protocol Parameters, Preload Injection Dose, Fractionation Strategies, and Leakage Correction Algorithms on the Fidelity of Dynamic-Susceptibility Contrast MRI Estimates of Relative Cerebral Blood Volume in Gliomas

Fellows’ Journal Club The authors used DSC-MR imaging simulations to examine the influence of various acquisition parameters and leakage-correction strategies on the faithful estimation of CBV. Optimal strategies were determined by protocol with the lowest mean error. They conclude that