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

Sci Data. 2017 Sep 5;4:170117. doi: 10.1038/sdata.2017.117.

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.

Publication types

  • Dataset
  • Research Support, N.I.H., Extramural

MeSH terms

  • Brain Neoplasms / diagnostic imaging
  • Brain Neoplasms / genetics*
  • DNA, Neoplasm*
  • Glioma / diagnostic imaging
  • Glioma / genetics*
  • Humans
  • Image Interpretation, Computer-Assisted
  • Magnetic Resonance Imaging
  • Multimodal Imaging

Substances

  • DNA, Neoplasm