The TCGA-GBM data collection is part of a larger effort to enhance the The Cancer Genome Atlas (TCGA) data set with characterized radiological images. The Cancer Imaging Program (CIP) with the cooperation of several of the TCGA tissue-contributing institutions has archived a large portion of the radiological images of the genetically-analyzed GBM cases.
Clinical, genetic, and pathology data resides in the TCGA data portal while the radiological data is stored on The Cancer Imaging Archive. The data utilizes the same TCGA patient identifiers in both repositories, allowing researchers to explore the correlations between tissue genotype and radiological phenotype. This Collection within the Cancer Imaging Archive is related to the GBM disease type within TCGA.
Institutions that have provided data for this collection include:
- Henry Ford
- MD Anderson
- Emory (in progress)
- Duke (in progress)
Number of Patients
131 (additional cases to be added shortly)
Number of Studies
Number of Series
Number of Images
You can view and download these images on the Cancer Imaging Archive by selecting the TCGA-GBM collection. If you are unsure how to download this Collection view our quick guide on Searching by Collection or you can refer to our The Cancer Imaging Archive User's Guide for more detailed instructions on using the site.
The Cancer Imaging Program has begun multiple projects to collaborate with the academic community to encourage cross disciplinary research which utilizes the data provided in these resources. Much more can be learned about this effort on the CIP TCGA Radiology Initiative page.
caBIG Tools for TCGA-GBM Analysis
Informatics software for use with this data has also been developed as part of the caBIG TCGA Enterprise Use-Case project. This caBIG enterprise use-case enabled TCGA images stored in NBIA (the same software powering the Cancer Imaging Archive) to be displayed on three different free and/or open source DICOM viewer workstations that possess annotation and markup capabilities based on Annotation Imaging Markup (AIM). These workstations were customized to allow retrieval of images from NBIA over the caGrid (from the NCI CBIIT deployed NBIA server only), markup by AIM standards, and storage back to an AIM-E Grid data service. Some of these tools have been leveraged as part of the CIP TCGA Radiology Initiative where possible.