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Sub-Project NameDescription
CTIIP Primer (DRAFT)Digital PathologyAddresses the interoperability accessibility of digital pathology data, improves integration and analytic capabilities between TCIA and TCGA, and raises the level of interoperability to create the foundation required for pilot demonstration tools for annotation and markup of pathology images through the development of microAIM, and analysis tools with caMicroscope projects in each of the targeted research domains: clinical imaging, pre-clinical imaging, and digital pathology imaging. raises the level of interoperability (take out pilot project)
Integrated Query System 
DICOM Standards for Small Animal Imaging; Use of Informatics for Co-clinical TrialsAddresses the need for standards in pre-clinical imaging and tests the informatics tools created in the Digital Pathology and Integrated Query System sub-project for decision support in co-clinical trials.
CTIIP Primer (DRAFT)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 TCGAare a tool for ... The pilot challenges would use limited data sets for proof-of-concept, and test the informatics infrastructure needed for more rigorous “Grand Challenges” that could later be scaled up and supported by extramural initiatives.

The Importance of Data Standards

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 image data standards exist to support communicating image data in a common way, the data standards that do exist for image data are inconsistently adopted. One reason for the lack of uniform adoption is that vendors of image management tools required for the analysis of imaging data have created these tools so that they only accept proprietary data formats. Researchers then make sure their data can be interpreted by these tools. The result is that images produced on different systems cannot be analyzed via the same mechanisms.

Another challenge for CTIIP with its goal of integrating data from complimentary domains is the lack of a defined standard for co-clinical and digital pathology data. Without a data standard for these domains, it is very difficult to share and leverage such data across studies and institutions. As part of the CTIIP project, the team will extend the DICOM model to co-clinical and small animal imaging.

NCI 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, Enterprise Vocabulary Services (EVS) and Cancer Data Standards Registry and Repository (caDSR) are harmonized with the Biomedical Research Integrated Domain Group (BRIDG), Study Data Tabulation Model (SDTM), and Health Level Seven® Reference Information Model 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 and TCGA.

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 image data standards exist to support communicating image data in a common way, the data standards that do exist for image data are inconsistently adopted. One reason for the lack of uniform adoption is that vendors of image management tools required for the analysis of imaging data have created these tools so that they only accept proprietary data formats. Researchers then make sure their data can be interpreted by these tools. The result is that data produced on different systems cannot be analyzed by the same mechanisms.

Another challenge for CTIIP with its goal of integrating data from complimentary domains is the lack of a defined standard for co-clinical and digital pathology data. Without a data standard for these domains, it is very difficult to share and leverage such data across studies and institutions. As part of the CTIIP project, the team has extended the DICOM model to co-clinical and small animal imagingNCI 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, Enterprise Vocabulary Services (EVS) and Cancer Data Standards Registry and Repository (caDSR) are harmonized with the Biomedical Research Integrated Domain Group (BRIDG), Study Data Tabulation Model (SDTM), and Health Level Seven® Reference Information Model 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 and TCGA.

Within the three research domains that CTIIP intends to make available for integrative queries, only one, clinical imaging, has made some progress in terms of establishing a framework and standards for informatics solutions. Those standards include Annotation and Image Markup (AIM), which allow researchers to standardize annotations and markup for radiology and pathology images, and Digital Imaging and Communications in Medicine (DICOM), which is a standard for handling, storing, printing, and transmitting information in medical imaging. 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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DomainData SetApplicable Standard
Clinical ImagingThe Cancer Genome Atlas (TCGA) clinical and molecular dataDICOM 
Clinical ImagingThe Cancer Imaging Archive (TCIA) in vivo imaging dataDICOM
Pre-ClinicalSmall animal models

N/AMicroAIM in development

A standard exists but has not been adopted

Digital PathologycaMicroscope

DICOM

A standard exists but has not been adopted

AllAnnotations and markup on imagesAIM

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