Page History

...

Introduction to CTIIP

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

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

a)       Histopathology

i)       Incorporate Openslide with caMicrosocope enabling  caMicrosocope to directly serve whole slide pathology images from the majority of digital pathology vendors.

ii)      Incorporate support for basic image analysis algorithms into caMicroscope.

iii)     Standards-based image annotation utilizing the Annotation Image Markup (AIM) standard.

b)       Integrative Queries

i)       Programmatic Access to Data to TCGA-related image data.

ii)      Extend software to support data mashups between image-derived information from TCIA and clinical and molecular metadata from TCGA.

Problem Statement

Approach

Project 2

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

a)       Pilot improve small-animal DICOM compliance

b)       Identify co-clinical pilot data set and populate integrated ‘omics/imaging infrastructure.

Problem Statement

Approach

...