The MRI-based 3D-ResNet-101 deep learning model for predicting preoperative grading of gliomas: a multicenter study

The preoperative accurate and non-invasive prediction of glioma grading remains challenging. To accurately predict high-or low-grade gliomas, we constructed a 3D-ResNet101 deep learning model with data from a multicenter. These data were obtained from the Second Hospital of Lanzhou University, with 708 glioma patients, and the TCIA database, with 211 patients. The areas under the curve of the 3D-ResNet-101 deep learning model are 0.97 and 0.89 in the test cohort and external test cohort, respectively. This new method can be used for non-invasive prediction of glioma grading before surgery.