Deep learning-based prediction of H3K27M alteration in diffuse midline gliomas based on whole-brain MRI.

ABSTRACT:

Background

H3K27M mutation status significantly affects the prognosis of patients with diffuse midline gliomas (DMGs), but this tumor presents a high risk of pathological acquisition. We aimed to construct a fully automated model for predicting the H3K27M alteration status of DMGs based on deep learning using whole-brain MRI.

Methods

DMG patients from West China Hospital of Sichuan University (WCHSU; n = 200) and Chengdu Shangjin Nanfu Hospital (CSNH; n = 35) who met the inclusion and exclusion criteria from February 2016 to April 2022 were enrolled as the training and external test sets, respectively. To adapt the model to the human head MRI scene, we use normal human head MR images to pretrain the model. The classification and tumor segmentation tasks are naturally related

SUBMITTER: Huang B 

PROVIDER: S-EPMC10501256 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature