Summary

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.

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Acknowledgements

  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.


Data Access

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Images (DICOM, 2.0 GB)

        

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Additional Resources for this Dataset

The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.

Detailed Description

Collection Statistics


Modalities

MR

Number of Participants

48

Number of Studies

48

Number of Series

286

Number of Images

37110

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 

Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:

Data Citation

Jansen, Sunny, & Van Dyke, Terry. (2015). TCIA Mouse-Astrocytoma Collection. The Cancer Imaging Archive. https://doi.org/10.7937/K9TCIA.2017.SGW7CAQW

TCIA Citation

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. DOI: 10.1007/s10278-013-9622-7

Other Publications Using This Data

See the Publications page for papers about this data set. If you have a publication you'd like to add, please contact the TCIA Helpdesk.

Version 1 (Current): Updated 2017/03/21

Data TypeDownload all or Query/Filter
Images ( 2.0 GB)

       

(Download requires the NBIA Data Retriever)



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