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Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features.

Authors :
Bakas S
Akbari H
Sotiras A
Bilello M
Rozycki M
Kirby JS
Freymann JB
Farahani K
Davatzikos C
Source :
Scientific data [Sci Data] 2017 Sep 05; Vol. 4, pp. 170117. Date of Electronic Publication: 2017 Sep 05.
Publication Year :
2017

Abstract

Gliomas belong to a group of central nervous system tumors, and consist of various sub-regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for both clinical and computational studies, including radiomic and radiogenomic analyses. Towards this end, we release segmentation labels and radiomic features for all pre-operative multimodal magnetic resonance imaging (MRI) (n=243) of the multi-institutional glioma collections of The Cancer Genome Atlas (TCGA), publicly available in The Cancer Imaging Archive (TCIA). Pre-operative scans were identified in both glioblastoma (TCGA-GBM, n=135) and low-grade-glioma (TCGA-LGG, n=108) collections via radiological assessment. The glioma sub-region labels were produced by an automated state-of-the-art method and manually revised by an expert board-certified neuroradiologist. An extensive panel of radiomic features was extracted based on the manually-revised labels. This set of labels and features should enable i) direct utilization of the TCGA/TCIA glioma collections towards repeatable, reproducible and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments, as well as ii) performance evaluation of computer-aided segmentation methods, and comparison to our state-of-the-art method.

Details

Language :
English
ISSN :
2052-4463
Volume :
4
Database :
MEDLINE
Journal :
Scientific data
Publication Type :
Academic Journal
Accession number :
28872634
Full Text :
https://doi.org/10.1038/sdata.2017.117