Summary
Acknowledgements
We would like to thank Nimit Patel of the Small Animal Imaging Program for analyzing ultrasound and assisting with the experiment; Simone Difilippantonio for coordinating her staff and Amy James of the Animal Research Technical Support Program for preparing the drug and administration, measuring body weights, and tumor excision, Laboratory Animal Sciences Program, Frederick National Laboratory for Cancer Research.
This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract Number HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.
Data Access
Data Type | Download all or Query/Filter | License |
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Images (DICOM, 3.2 GB) |
Click the Versions tab for more info about data releases.
Additional Resources for this Dataset
The National Cancer Institute (NCI) has developed a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), in vitro patient-derived tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs) as well as patient-derived organoids (PDOrg). These models serve as a resource for public-private partnerships and for academic drug discovery efforts. These PDMs are clinically-annotated with molecular information and made available in the Patient-Derived Model Repository. Data related to the specific subjects in this Collection can be found at:
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.
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.
- Imaging Data Commons (IDC) (Imaging Data)
Detailed Description
Image Statistics | |
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Modalities | MR |
Number of Patients | 19 |
Number of Studies | 66 |
Number of Series | 131 |
Number of Images | 2222 |
Images Size (GB) | 3.2 |
This Standard Operating Procedure (SOP) describes the procedures for animal handling and monitoring, anesthesia, daily MRI QC/QA, and MRI sequences for single and multi-mouse imaging for detection and monitoring of tumors and metastatic lesions. This SOP is used/performed by the Small Animal Imaging Program (SAIP) at NCI-Frederick, Frederick National Laboratory for Cancer Research.
In addition to images, this collection may include Raw Data Storage SOP Class instances with MR Modality, generated by a Philips MR scanner; this data is not useful to anyone without the proprietary software to interpret it.
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
Tatum, J. L., Kalen, J. D., Ileva, L. V., Riffle, L. A., Jacobs, P. M., Hollingshead, M. G., Doroshow, J. H, Clunie, D. A, Smith, K. E, Wagner, U., Freymann, J. B. (2019). Imaging characterization of a metastatic patient derived model of bladder cancer: BL0293F (PDMR-BL0293-F563) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/tcia.2019.b6u7wmqw
Publication Citation
Tatum, J. L., Kalen, J. D., Jacobs, P. M., Ileva, L. V., Riffle, L. A., Hollingshead, M. G., & Doroshow, J. H. (2019). A spontaneously metastatic model of bladder cancer: imaging characterization. In Journal of Translational Medicine (Vol. 17, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s12967-019-02177-y
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. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7
Other Publications Using This Data
TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact TCIA's Helpdesk.
Version 1 (Current): Updated 2019/08/28
Data Type | Download all or Query/Filter |
---|---|
Images (DICOM, 3.2 GB) |
Additional Resources for this Dataset
The National Cancer Institute (NCI) has developed a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), in vitro patient-derived tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs) as well as patient-derived organoids (PDOrg). These models serve as a resource for public-private partnerships and for academic drug discovery efforts. These PDMs are clinically-annotated with molecular information and made available in the Patient-Derived Model Repository. Data related to the specific subjects in this Collection can be found at: