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The goal of the Small Animal/Co-clinical Improved DICOM Compliance and Data Integration sub-project is to directly compare data from co-clinical animal models to real-time clinical data from TCGA. The team will accomplish this by applying common data elements used in TCGA with animal applicability, such as estrogen-receptor (ER) negative and positive, to a co-clinical data set. Specifically, this sub-project will:

• Develop a supplement to the DICOM standard to accommodate small animal imaging.
• Identify a pilot co-clinical data set to integrate with TCIA and TCGA.

For example, consider the following research question, made possible through increased DICOM compliance by small animal/co-clinical data.

• If you treat a mouse with an estrogen-receptor (ER) negative tumor with a certain drug, how does the outcome compare to that of a human with the same tumor and ER status?

Researchers could also search in-vivo imaging, radiology, and digital pathology data from the patient, run a gene panel, and identify abnormal genes in the patient. With small animal/co-clinical data meeting the DICOM standard, researchers could find a mouse with the same kind of tumor and compare its response to various therapies that could help generate sophisticated diagnoses and treatment plans.Improving the compliance of co-clinical data with DICOM will help improve doctors' ability to make firm diagnoses.

Pilot Challenges

1)      AIM 3 - “Pilot Challenges” to compare the decision support systems for three imaging research domains: Clinical Imaging, Pre-clinical Imaging, and Digital Pathology.

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