This collection consists of magnetic resonance images (MRI) of genetically engineered mouse models (GEMMs) of high grade astrocytoma, including glioblastoma multiforme (GBM).
In these GEMMs, the most commonly disregulated networks in GBM -- RB, KRAS and/or PI3K signaling -- are perturbed at the genetic level. These genetic aberrations induce development of high grade astrocytoma in the mouse with properties similar to that of human disease. MRI was used to perform a qualitative and quantitative phenotypic characterization of the different genotypes and molecular subtypes. Additionally, mouse MRI images were compared human GBM imaging parameters using the VASARI lexicon. The MRI data contained herein includes anatomic T2 weighted images and dynamic contrast enhanced MRI.
We would like to acknowledge the individuals and institutions that have provided data for this collection:
- National Cancer Institute (Frederick, Maryland) - Special thanks to Sunny Jansen, PhD from the Department of Mouse Cancer Genetics Program.
Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search By Collection option.
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Number of Patients
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|Images Size (GB)||2.0 GB|
A presentation about this data set can be found at: Sunny_jansen_NBIA_mouseGBM_update_ICR_508.ppt.
Citations & Data Usage Policy
This collection is freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to email@example.com.
Please be sure to include the following citations in your work if you use this data set:
Jansen, Sunny, & Van Dyke, Terry. (2015). TCIA Mouse-Astrocytoma Collection. The Cancer Imaging Archive. https://doi.org/10.7937/K9TCIA.2017.SGW7CAQW
Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. (paper)
Other Publications Using This Data
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