{"id":5810,"date":"2023-09-04T03:39:35","date_gmt":"2023-09-04T03:39:35","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-analysis-result\/rsna-asnr-miccai-brats-2021\/"},"modified":"2023-09-13T12:11:56","modified_gmt":"2023-09-13T12:11:56","slug":"rsna-asnr-miccai-brats-2021","status":"publish","type":"tcia_analysis_result","link":"https:\/\/cm.vastapps.dev\/tcia-analysis-result\/rsna-asnr-miccai-brats-2021\/","title":{"rendered":"RSNA-ASNR-MICCAI-BRATS-2021"},"featured_media":8814,"template":"","cancer_types":["Glioma"],"citations":[4835,4836,4837,4838,2925,4839],"full_export":"

Summary<\/h1>This dataset includes brain MRI scans of adult brain glioma patients, comprising of 4 structural modalities (i.e., T1, T1c, T2, T2-FLAIR) and associated manually generated ground truth labels for each tumor sub-region (enhancement, necrosis, edema), as well as their MGMT promoter methylation status. These scans are a collection of data from existing TCIA collections, but also cases provided by individual institutions and willing to share with a cc-by license.<\/p>

The BraTS dataset describes a retrospective collection of brain tumor structural mpMRI scans of 2,040 patients (1,480 here), acquired from multiple different institutions under standard clinical conditions, but with different equipment and imaging protocols, resulting in a vastly heterogeneous image quality reflecting diverse clinical practice across different institutions. The 4 structural mpMRI scans included in the BraTS challenge describe a) native (T1) and b) post-contrast T1-weighted (T1Gd (Gadolinium)), c) T2-weighted (T2), and d) T2 Fluid Attenuated Inversion Recovery (T2-FLAIR) volumes, acquired with different protocols and various scanners from multiple institutions. Furthermore, data on the O[6]-methylguanine-DNA methyltransferase (MGMT) promoter methylation status is provided as a binary label. Notably, MGMT is a DNA repair enzyme that the methylation of its promoter in newly diagnosed glioblastoma has been identified as a favorable prognostic factor and a predictor of chemotherapy response.<\/p>

It is curated for computational image analysis of segmentation and prediction of the MGMT promoter methylation status.<\/div>

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A note about available TCIA data which were converted <\/em>for use in this Challenge: (Training, Validation, Test)<\/h3>

Dr. Bakas's group here provides brain-extracted Segmentation task <\/em>BraTS 2021 challenge TRAINING <\/strong>and VALIDATION <\/strong>set data in NIfTI that do not pose DUA-level risk of potential facial reidentification, and segmentations to go with them. This group has provided some of the brain-extracted <\/em>BraTS challenge TEST <\/strong>data in NIfTI, and segmentations to go with them (here<\/a> and here<\/a>, from the 2018 challenge, request through help@cancerimagingarchive.net<\/a>).<\/p>

This group here provides brain-extracted Classification task <\/em>BraTS 2021 challenge TRAINING <\/strong>and VALIDATION <\/strong>set data includes DICOM\u2192 NIfTI\u2192 dcm files, registered to original orientation, data files that do not strictly adhere to the DICOM standard. BraTS 2021 Classification challenge TEST <\/strong>files are unavailable at this time.<\/p>

You may want the original corresponding DICOM-format files drawn from TCIA Collections; please note that these original data are not brain-extracted and may pose enough reidentification risk that TCIA must keep them behind an explicit usage agreement.<\/p>

Please also note<\/strong><\/span> that specificity of which exact series in DICOM became which exact volume in NIfTI has, unfortunately, been lost to time but the available lists below represent our best effort <\/strong>at reconstructing the link to the BraTS source files.<\/p>

Acknowledgements<\/span><\/h3>

We would like to acknowledge the individuals and institutions that have provided data for this collection:<\/p>