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The National Cancer Institute Clinical and Translational Imaging Informatics Project (NCI CTIIP) unites sub-projects from three imaging research domains--digital pathology, co-clinical, and molecular biology—with the goal of creating an informatics platform and open source software tools to better diagnose and treat patients with cancer.

The components of CTIIP that will make this possible include the following sub-projects, which are discussed in this guide.

• Digital Pathology Data Integration and Integrated Query System
• Small Animal/Co-clinical Improved DICOM Compliance and Data Integration
• Pilot Challenges

Digital Pathology Data Integration and Integrated Query System

Digital pathology, unlike its more mature radiographic counterpart, has yet to standardize on a single storage and transport media. While DICOM has published a digital pathology standard, none of the major vendors in this space have adopted the standard.

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.

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.

Solution 1: Integrating Image and Molecular Data

The first step towards the goal of image data integration is the creation of an image server that can host and serve digital pathology images for any of the major vendors without recoding, which often introduces additional compression artifacts. This image server will be caMicroscope, with its functionality expanded by the OpenSlide library.

• caMicroscope is a digital pathology viewer provides researchers with an HTML5-based web client that can be used to view a digitized pathology image at full resolution. While it is standards-based, implementing both the Annotation and Image Markup (AIM) and Digital Imaging and Communications in Medicine (DICOM) standards, it supports limited formats adopted by whole-slide vendors.
• OpenSlide is a C library that can read whole-slide images in many common formats adopted by whole-slide vendors.

This project is also proposing a standard for markup and annotations called microAIM.

This infrastructure can be expanded to include more data types and additional integration, which will provide analytic and decision support to researchers, who can then pursue a broader set of novel community research projects.

Introduction to CTIIP

The National Cancer Institute Clinical and Translational Imaging Informatics Project (NCI CTIIP) unites efforts from the imaging research domains of genomics, diagnostic imaging, and digital pathology to better diagnose and treat patients with cancer. These efforts aim to create a common informatics infrastructure that each domain can share to support research and decision support systems.   

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