Cancer Informatics

The goal of cancer informatics is to obtain and organize large amounts of data (ie, histology, radiology, etc) in order to be able to formulate hypotheses and make discoveries about basic cancer development and guide physicians in making correct diagnostic and prognostic decisions. The ultimate goal of this line of research is to better characterize patient samples by incorporating a more complete picture of the cancer. While genomics is revolutionizing cancer care, both micro and macro-environmental aspects of the underlying tumor can have dramatic effects. A piece of tissue taken from the frontal lobe vs the brain stem may have identical genetics, but the clinical course of the patient will vary dramatically based on the location of the tumor.

Cancer Digital Slide Archive (CDSA)

One tool developed by our lab to facilitate this process is the Cancer Digital Slide Archive (CDSA), which is an integrated web-based whole-slide image visualizer and annotation program. The integration and visualization of multimodal datasets is a common challenge in biomedical informatics. Several recent studies of The Cancer Genome Atlas (TCGA) data have illustrated important relationships between morphology observed in whole-slide images, outcome, and genetic events. The pairing of genomics and rich clinical descriptions with whole-slide imaging provided by TCGA presents a unique opportunity to perform these correlative studies. However, better tools are needed to integrate the vast and disparate data types. We have developed an integrated web-based platform supporting whole-slide pathology image visualization and annotation and data integration which is accessible to the public and which currently hosts more than 20,000 whole-slide images from 22 cancer types.

Cancer Digital Slide Archive open version can be accessed by clicking here.

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Our lab is also focused on the development and use of ad-hoc image viewer software…

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VASARI Feature Set

One of the challenges in radio-oncology research is maintaining consistent measurement guidelines across institutions and research groups. Our lab is involved with the VASARI Research project, a part of the Cancer Genome Atlas (TCGA) initiative. The controlled “VASARI” terminology for describing the MR features of human gliomas was devised based upon previous radiological research involving the REMBRANDT project of the NCI. A comprehensive VASARI featureset was developed which consists of 24 observations familiar to neuroradiologists to describe the morphology of brain tumors on routine contrast-enhanced MRI. The featureset was empirically determined using MRI studies from 88 glioblastomas to provide consistent measurements and strong inter-observer agreement accross multiple readers. We hope that these results show that the VASARI featureset can be easily implemented in radio-oncologic research settings to lead to consistent and robust research findings involving the behavior and progression of various neoplasms. For more information, please visit the Cancer Imaging Archive (TCIA).

 

TCGA Glioma Phenotype Research Group

Emory University, along with six other universities is a member of The TCGA Glioma Phenotype Research Group which is part of an initiative focused on analyzing images from the TCGA-GBM collection. For more information including related discoveries and research abstracts, please visit the Cancer Imaging Archive (TCIA).