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The goal of this sub-project is to create a digital pathology image server that can accept images from multiple domains and run integrative queries on that data. This will create a type of data mashup whereby Using this server, data can be selected from distinct imaging sources and made accessible for image algorithms.

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Integrating Imaging and Molecular Data

All three research domains will clearly need an imaging archive that can be leveraged for integration across multiple data types and sourcesTo make data comparable, it must first be collected in a structured fashion. For example, TCGA relies on Common Data Elements, which are the standard elements that were used to validate TCGA clinical data.

We are exploring the standardization of informatics. Use all the tools we have to create standard informatics to compare patient to animal data. We are using the available standards: DICOM, AIM, micro AIM. Fundamental to integrative queries.

All three research domains need an imaging archive that can be leveraged for integration across multiple data types and sources. For example, TCGA program has the goal of producing a program has the goal of producing a comprehensive genomic characterization and analysis of 200 types of cancer and providing this information to the research community. TCIA and the underlying National Biomedical Image Archive (NBIA) software stack were created to manage well-curated, publicly-available collections of medical image data, including diagnostic images associated with the tissue samples sequenced by TCGA. TCIA currently supports over 40 active research groups including researchers who are exploiting the existing linkages between TCGA and TCIA. TCIA has recently released an Application Program Interface (API) that provides a REST API to TCIA metadata and image collections. This API is built using a middleware platform called Bindaas,and this API is being designed to support federation of multiple information repositories using the concepts of a data mashups. This infrastructure can be expanded to include more data types and additional integration, and provide analytic and decision support, which will act as a foundation for a broader set of novel community research projects.

What the data is used for

Relate data from TCIA, caMicroscope, animal modelgenomics, animal

how do we make a decision on a firm diagnosis?

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We are setting up the data structure so when that is done, we'll be able to see what use cases are possible.

To make data comparable, we must collect it in a structured fashion. Common Data Elements for TCGA.

We are pulling data out of caDSR (ER negative and positive, other common data elements) and we are asking Bob Cardiff's team to ask the same questions so that we can compare human and mouse data.

We are exploring the standardization of informatics. Use all the tools we have to create standard informatics to compare patient to animal data. We are using the available standards: DICOM, AIM, micro AIM. Fundamental to integrative queries. 

If you did an integrative query, how would you do it? Data calls to do different integrative queries. How would you use sufficient standard data. Come out with information that will allow you to make a decision. Pilot challenges to compare the decision support systems for three domains.

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