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To serve the need for research across domains, the National Cancer Institute Clinical and Translational Imaging Informatics Project (NCI CTIIP) team is developing and deploying software that supports a comprehensive and reusable exploration and fusion of imaging, clinical, and molecular data. The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA) projects have created a rich multi-domain data set. This data set, however, is in an infrastructure that provides limited query capability for identifying cases based on all of the available data types. (For example...?) The CTIIP team will therefore develop a unified query interface to facilitate cross-disciplinary analysis. This infrastructure would then be applied to clinical/co-clinical settings and provide a common platform and data engine for the hosting of “pilot challenges”challenges.” The algorithms used in the pilot challenges will be shared with the community via an open-source software clearinghouse.
The Most importantly, the common informatics infrastructure will provide researchers with analysis tools they can use to directly mine data from multiple high-volume information repositories, creating a foundation for research and decision support systems to better diagnose and treat patients with cancer.
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| Sub-Project | Goal |
|---|---|
| Digital Pathology and Integrated Query System | Address the interoperability of digital pathology data, improve integration and analytic capabilities between TCIA and TCGA, and raise the level of interoperability to create the foundation required for pilot demonstration projects in each of the targeted research domains: clinical imaging, pre-clinical imaging, and digital pathology imaging. |
| DICOM Standards for Small Animal Imaging; Use of Informatics for Co-clinical Trials | Address the need for standards in pre-clinical imaging and test the informatics created in the Digital Pathology and Integrated Query System sub-project for decision support in co-clinical trials. |
| Pilot ChallengesLeverage the work done in the Digital Pathology and Integrated Query System sub-project to further enhance the informatics and infrastructure in several Pilot | Challenges . These challenges will be designed to develop knowledge extraction tools and compare decision support systems for the three research domains, which will now be represented as a set of integrated data from TCIA and TCGA. The intent is not to specifically implement a rigorous “Grand Challenge”Challenge,” but rather to develop Pilot Challenge pilot challenge projects. These would use limited data sets for proof-of-concept, and test the informatics infrastructure needed for such “Grand Challenges” that would be scaled up and supported by extramural initiatives later in 2014 and beyond. |
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Data Standards Applicable to CTIIP
Within these three research domains, only one, clinical imaging, has made some progress in terms of establishing a framework and standards for informatics solutions. For pre-clinical imaging and digital pathology, there are no such standards that allow for the seamless viewing, integration, and analysis of disparate data sets to produce integrated views of the data, quantitative analysis, data integration, and research or clinical decision support systems.
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CBIIT has worked extensively for several years in the area of data standards for both clinical research and healthcare, working with the community and Standards Development Organizations (SDOs), such as the Clinical Data Interchange Standards Consortium (CDISC), Health Level 7 (HL7) and the International Organization for Standardization (ISO). From that work, EVS and caDSR is harmonized with the BRIDG, SDTM, and HL7 RIM models. Standardized Case Report Forms (CRFs), including those for imaging, have also been created. This work provides the bioinformatics foundation for semantic interoperability in digital pathology and co-clinical trials integrated with clinical and patient demographic data and data contained in TCIA / TCGA.Three complementary projects were proposed and approved.
Digital Pathology and Integrated Query System
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