The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification

• Type of Material: Article
• Authors: Brent Weinberg, Emory University
• Language: English
• Date: 2021-09-12
• Publisher: arXiv
• Publication Version: Preprint (Prior to Peer Review)
• Copyright Statement: The copyright holder for this preprint is the author/funder, who has granted arXiv a license to display the preprint in perpetuity.
• License: Creative Commons Attribution 4.0 International
• Title of Journal or Parent Work: arXiv
• Volume: 02314
• Issue: 2
• Grant/Funding Information: Research reported in this publication was partly supported by the National Cancer Institute (NCI) Informatics Technology for Cancer Research (ITCR) program and the National Institute of Neurological Disorders and Stroke (NINDS) of the National Institutes of Health (NIH), under award numbers NCI:U01CA242871, NCI:U24CA189523, NINDS:R01NS042645, Contract No. HHSN261200800001E, Ruth L. Kirschstein Institutional National Research Service Award number T32 EB001631. Research reported in this publication was also partly supported by the RSNA Research & Education Foundation grant number RR2011, and by the ASNR Foundation Grant in Artificial Intelligence (JDR). Sage Bionetworks support of challenge organization and infrastructure was supported by the NCI ITCR program under award number U24CA248265. The content of this publication is solely the responsibility of the authors and does not represent the official views of the NIH or of the RSNA R&E Foundation, or the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.
• Keywords: BraTS; Glioma; tumor; radiomics; brain; MGMT; challenge; glioblastoma; segmentation; machine learning; classification

Abstract

The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR), and the Medical Image Computing and Computer Assisted Interventions (MICCAI) society. Since its inception, BraTS has been focusing on being a common benchmarking venue for brain glioma segmentation algorithms, with well-curated multi-institutional multi-parametric Magnetic Resonance Imaging (mpMRI) data. Gliomas are the most common primary malignancies of the central nervous system, with varying degrees of aggressiveness and prognosis. The RSNA-ASNR-MICCAI BraTS 2021 challenge targets the evaluation of computational algorithms assessing the same tumor compartmentalization, as well as the underlying tumor’s molecular characterization, in pre-operative baseline mpMRI data from 2,040 patients. Specifically, the two tasks that BraTS 2021 focuses on are: a) the segmentation of the histologically distinct brain tumor subregions, and b) the classification of the tumor’s O[6]-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. The performance evaluation of all participating algorithms in BraTS 2021 will be conducted through the Sage Bionetworks Synapse platform (Task 1) and Kaggle (Task 2), concluding in distributing to the top ranked participants monetary awards of $60,000 collectively.