Summary
The imaging characteristics of this model (PDMR-425362-245-T) which is available from the National Cancer Institute Patient-Derived Models Repository (https://pdmr.cancer.gov/), is highly favorable for preclinical research studies of metastatic disease when used in conjunction with non-contrast T2 weighted MRI.
Results: Melanoma (PDMR-425362-245-T)
Table 1: Penetrance and location of pathological confirmed metastatic lesion(s).
# animals in group | # animals that displayed metastasis in MRI and confirmed by Pathology | Pathology confirmation of MRI (primary imaging site) | Other confirmed Location (s) |
10 (non-resected) | 4 (6 mice were EU due to xenograft size prior to observation of metastasis) | Lung | Kidney |
10 (resected) | 10 | Lung | Kidney, Liver, Pancreas |
Percent penetrance with respect to the average time-to-metastasis for non-resected (plot A: time from implant) and resected (plot B: time from tumor resection) cohorts.
Plot A | Plot B |
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PET/CT Characterization of the primary tumor: Baseline PET (SOP attached) were performed when tumor reached an approximate 200 mm3. Average SUVmax values (n=5) were calculated; [18F]FDG: 2.7 ± 0.5 and [18F]FLT: 2.0 ± 0.3.
Conclusion:
Melanoma PDMR-425362-245-T model can be challenging due to the rapid growth of the xenograft and regrowth. Metastases was well observed on T2 MRI imaging allowing non-invasive evaluation in treatment trials.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
- Frederick National Laboratory for Cancer Research – Special Thanks to Joseph D. Kalen, PhD, Lilia V. Ileva, MS, Lisa A Riffle, Nimit Patel, Keita Saito, PhD, Yvonne Evrard, PhD, Elijah Edmondson, DVM, PhD, Jessica Phillips, Simone Difilippantonio, PhD, Chelsea Sanders, Amy Janes, Lia Thang, Ulrike Wagner, Yanling Liu, PhD, John B. Freymann, and Justin Kirby.
- Division of Cancer Therapeutics and Diagnosis/National Cancer Institute - James L. Tatum, MD, Paula M Jacobs, PhD, Melinda G. Hollingshead, DVM, and James H. Doroshow, MD
- PixelMed Publishing – Special Thanks to David A. Clunie, MD
- University of Arkansas for Medical Sciences – Special Thanks to Kirk E. Smith
- This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261201500003I. 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
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Detailed Description
Image Statistics | |
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Modalities | MR |
Number of Subjects | 20 |
Number of Studies | 115 |
Number of Series | 210 |
Number of Images | 3509 |
Images Size (GB) | 2.3 GB |
Citations & Data Usage Policy
These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work:
Data Citation
Tatum, J. L., (https://orcid.org/0000-0002-3217-2478) Kalen, J. D., (https://orcid.org/0000-0002-7163-4604) Jacobs, P. M., (https://orcid.org/0000-0002-9423-6473) Ileva, L. V., (https://orcid.org/0000-0001-8286-8396) Riffle, L. A., (https://orcid.org/0000-0003-3975-3088) Keita, S., Patel, N., (https://orcid.org/0000-0002-8251-7155) Sanders, C., (https://orcid.org/0000-0001-8042-4783) James, A., Difilippantonio, S., (https://orcid.org/0000-0002-8234-1559) Thang, L. Hollingshead, M. G., (https://orcid.org/0000-0002-1207-1397) Phillips, J., Edmondson, Ehttps://orcid.org/0000-0002-6106-3705Evrard, Y., Clunie, D. A, (https://orcid.org/0000-0002-2406-1145) Liu, Y., Smith, K. E, (https://orcid.org/0000-0002-8735-7576) Wagner, U., (https://orcid.org/0000-0002-3230-5058) Freymann, J. B. Kirby, J.,https://orcid.org/0000-0003-3487-8922) Doroshow, J. H, (https://orcid.org/0000-0002-4463-1790)
Acknowledgement
This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261201500003I. 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.
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: https://doi.org/10.1007/s10278-013-9622-7
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Version 1 (Current): Updated yyyy/mm/dd
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