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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.   

seeks to create an informatics infrastructure and open-source software tools that allow researchers to create queries combining attributes from molecular, imaging, and clinical data, and to use such integrated queries to explore, filter, and select data for their driving biological problems .

• Creating 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 an informatics and IT infrastructure to implement pilot challenges for clinical and pre-clinical studies that integrate the genomics, diagnostic imaging, and digital pathology domains.
• DICOM Working Group 30?
• Developing DICOM standards for small animal imaging and identify co-clinical datasets to test the integration of TCIA and TCGA for this data.

Informatics infrastructure to support research and decision support systems in three imaging research domains: Clinical Imaging, Pre-clinical Imaging, and Digital Pathology

Imaging-based cancer research is in the beginning phase of an Integrative-biology revolution. It is now feasible to extract large sets of quantitative image features relevant to prognosis or treatment across three complementary research domains:  in vivo clinical imaging, pre-clinical imaging, and digital pathology. These high-dimensional image feature sets can be used to infer clinical phenotypes or correlate with gene–protein signatures. This type of analysis, however, requires large volumes of data. In this project, we propose to develop and deploy software that supports a comprehensive and reusable exploration and fusion of imaging, clinical, and molecular data. TCGA/TCIA provides a rich multi-domain dataset in an infrastructure that provides limited query capability for identifying cases based on all the data types available.  Cross-disciplinary analysis would be facilitated by providing a unified query interface.  This infrastructure would then be applied to clinical -co-clinical settings and provide a common platform and data engine for hosting of “pilot challenges”.   An opensource software clearinghouse will enable community sharing of algorithms used in the analyses.

Project 1: Integrated Query System for Existing TCGA Data

1)      AIM 1 - Integrated query system for existing TCGA data (including improved pathology systems)

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Problem Statement

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TCGA Infrastructure Applied to Co-Clinical

1)      AIM 2 - TCGA infrastructure ported to/applied to co-clinical setting 

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Problem Statement

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Pilot Challenges

1)      AIM 3 - “Pilot Challenges” to compare the decision support systems for three imaging research domains: Clinical Imaging, Pre-clinical Imaging, and Digital Pathology.

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