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Page History
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| Sub-Project Name | Solution it Provides |
|---|---|
| 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 Challenges | 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,” but rather to develop 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 later be scaled up and supported by extramural initiatives. |
The Importance of Data Standards
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The common infrastructure that will result from CTIIP and its sub-projects depends on data interoperability, which is greatly aided by adherence to data standards. While standards such as Annotation and Image Markup (AIM) and Digital Imaging and Communications in Medicine (DICOM) exist to support images, vendors of data viewers and other tools required for the analysis of imaging data have not widely adopted them. The lack of standards in pre-clinical and pathology prevents the ability to share and leverage data across studies and institutions.
Furthermore, because each pathology-imaging vendor produces its own image management systems, these systems are also, by extension, proprietary and not standardized. The result is that images produced on different systems cannot be analyzed via the same mechanisms. In addition, no standard currently exists for markup and annotations on images(CKK: purpose of microAIM).
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.
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 are harmonized with the BRIDG, SDTM, and HL7 RIM models. Standardized Case Report Forms (CRFs), including those for imaging, have also been created. The CBIIT project 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.
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This sub-project addresses the lack of uniformly accepted standards within digital pathology and the simultaneous need for integration of pathology data with radiographic, genomic, and proteomic data. Creating Its mission is to create an open-source digital pathology image server that can host and serve digital pathology images for any of the major vendors without recoding, facilitating the integration of pathology data with radiographic, genomic, and proteomic data.Establishing data integration. This image server would establish an informatics and IT infrastructure to implement pilot challenges for clinical and pre-clinical studies that integrate the (CKK: talk to Ulli about different names for the same? domains mentioned on this page) genomics, diagnostic imaging, and digital pathology domains.
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