Brain tumors are among the deadliest types of cancer. Specifically, glioblastoma, and diffuse astrocytic glioma with molecular features of glioblastoma (WHO Grade 4 astrocytoma), are the most common and aggressive malignant primary tumor of the central nervous system in adults, with extreme intrinsic heterogeneity in appearance, shape, and histology, with a median survival of approximately 15 months. Brain tumors in general are challenging to diagnose, hard to treat and inherently resistant to conventional therapy because of the challenges in delivering drugs to the brain, as well as the inherent high heterogeneity of these tumors in their radiographic, morphologic, and molecular landscapes. Years of extensive research to improve diagnosis, characterization, and treatment have decreased mortality rates in the U.S by 7% over the past 30 years. Although modest, these research innovations have not translated to improvements in survival for adults and children in low- and middle-income countries (LMICs), particularly in sub-Saharan African (SSA) populations.
The Brain Tumor Segmentation (BraTS) Continuous Challenge seeks to identify the current, state-of-the-art segmentation algorithms for brain diffuse glioma patients and their sub-regions. Training and blinded validation data are made available year-round for building and evaluating segmentation algorithms. Evaluation metrics for predictions on the blinded validation data are returned immediately to participants with a continuously updated leaderboard. This continuous challenge will culminate in an annual, state-of-the-field evaluation where we will ask participants to submit containerized versions of their best models which will be run against a held out testing data set, and the results presented at the annual MICCAI conference.
The BraTS training and validation data available for download and methodological development by the participating teams describe a total of 5,880 MRI scans from 1,470 brain diffuse glioma patients and are identical to the data curated for the RSNA-ASNR-MICCAI BraTS 2021 Challenge. The unseen hold-out testing data will include the BraTS 2021 Challenge test data, as well as new data from out-of-sample sources including i) an independent multi-institutional dataset covering underrepresented SSA adult patient populations of brain diffuse glioma (Africa-BraTS), and ii) from another independent pediatric population of diffuse intrinsic pontine glioma (DIPG) patients. These new out-of-sample datasets are meant to evaluate the generalizability of existing models to new, out-of-sample populations. All challenge data are routine clinically-acquired, multi-institutional multi-parametric magnetic resonance imaging (mpMRI) scans of brain tumor patients.
