TY - JOUR
T1 - Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features
AU - Bakas, Spyridon
AU - Akbari, Hamed
AU - Sotiras, Aristeidis
AU - Bilello, Michel
AU - Rozycki, Martin
AU - Kirby, Justin S.
AU - Freymann, John B.
AU - Farahani, Keyvan
AU - Davatzikos, Christos
N1 - Publisher Copyright:
© The Author(s) 2017.
PY - 2017/9/5
Y1 - 2017/9/5
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85028870080&partnerID=8YFLogxK
U2 - 10.1038/sdata.2017.117
DO - 10.1038/sdata.2017.117
M3 - Article
C2 - 28872634
AN - SCOPUS:85028870080
SN - 2052-4463
VL - 4
JO - Scientific data
JF - Scientific data
M1 - 170117
ER -