CHICAGO—A collection to imaging informatics tools developed under the umbrella of the National Cancer Institutes caBIG (cancer Biomedical Informatics Grid) are demonstrating the potential for collecting, analyzing, integrating, and disseminating information associated with cancer research and care, according to a scientific presentation at the 94th annual meeting of the Radiological Society of North America (RSNA).
“The caBIG is an information network enabling all constituencies in the cancer community to share data and knowledge to accelerate the discovery of new diagnostics and therapeutics, and to improve patient outcomes,” said Eliot L. Siegel, MD, professor and vice-chair of the department of diagnostic radiology at the University of Maryland School of Medicine in Baltimore.
The caBIG imaging workspace was created as a national multidisciplinary expert advisory board for the identification and prioritization of imaging informatics projects, Siegel told the audience.
Major projects of the initiative, include:
- eXtensible Imaging Platform (XIP)—A free and open-source platform that facilitates the sharing not of images and other patient data but of image display, processing, and analysis algorithms.
- GridCAD and Virtual PACS—Middleware components used to create interoperability between DICOM devices and the caGRID, which uses a service oriented architecture. Siegel noted that grid computing has received surprisingly little attention in diagnostic imaging despite its tremendous potential to promote interoperability, improve security, and support more efficient sharing of image data and software algorithms.
- Annotations and Imaging Markup (AIM)—Siegel said that this is first project of its kind, of which the group is aware, that proposes to create a standard means of adding information to an image in a clinical environment in order to create image content that can be easily and automatically searched.
- Algorithm Validation Tools (AVT) —A set of tools capable of generating measurements using validated and consistent methods for detecting change and to associate information, including clinical outcomes data, that would be helpful in assessing the performance of image-based change-assessment tools.
- DICOM Ontology Project—Creation of a single common reference information model for all caBIG projects that need to refer to imaging and other DICOM-related information in their individual information.
- Query Formulation—The Imaging Query Formulation tool will provide an interface that automates the creation of ontology-based queries to image resources, with delivery of a platform and Image Query Tool (IQ Tool), Siegel said.
Siegel reported that the developers and researchers dedicating their efforts to the caBIG imaging workspace initiative have made excellent progress over the past 12 months.
“This year's emphasis has been on practical implementations of the software for use in ongoing research projects,” he said.
According to developers working on the caBIG initiative, and demonstrating their tools in McCormick Place’s Lakeside Learning Center during the RSNA conference, the Network for Translational Research (NTR) and Clinical Trial Tools Integration (CTTI) projects are adoption efforts that aim to show the efficacy of the tools and standards developed by the caBIG imaging workspace across the clinical continuum.
The NTR project will involve the Network for Translational Research: Optical Imaging (NTROI – a multi-institutional imaging research group) making its collaborative data management system SciPort interoperable with the caGrid and the National Cancer Imaging Archive (NCIA), a tool developed by the NCI and associated with the caBIG Imaging Workspace.
The CTTI will involve bringing the Quality Assurance Review Center’s (QARC’s) legacy database system into compliance with the caBIG objective by grid enabling it over the caGrid, for potential future development in conjunction with the caBig Imaging’s AIM and XIP efforts.
According to John Niederhuber, MD, director of the NCI, although the caBIG initiative was initially focused on cancer research and care, the technology is widely applicable to other therapeutic areas.
“The caBIG is an example of a new approach to organizing medical research in the future that is really both an experiment and yet a transformation at the same time,” Niederhuber wrote in June this year (NIH publication 08-6457) “No single individual or organization can manage the amount of