New Dataset: The University of Missouri Post-operative Glioma Dataset (MU-Glioma-Post)
The University of Missouri Post-operative Glioma Dataset (MU-Glioma-Post) consists of an institutional review board-approved retrospective analysis of pathologically proven glioma patients at the University Hospital of the University of Missouri – Anatomic Pathology CoPathPlus database, collected glioma cases over the last 10 years. The heterogeneity of glioma imaging characteristics and management strategies contributes to a lack of reliable findings when evaluating treatment outcomes with conventional MRI. The overlapping imaging features of radiation necrosis and tumor progression post-treatment can be particularly challenging for radiologists. This robust dataset should contribute to the development of AI models to improve the evaluation of treatment outcomes.
It includes MR imaging from 203 glioma patients with 617 different post-treatment MR time points, and tumor segmentations. Clinical data includes patient demographics, genomics, and treatment details. Preprocessing of MR images followed a standardized pipeline with automatic tumor segmentation based on nnUNet deep learning approach. The automatic tumor segmentations were manually validated and refined by neuroradiologists.