The Cancer Imaging Archive (TCIA) Public Access

Space shortcuts

Child pages
  • TCGA Glioma Phenotype Research Group
10 more child pages

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 14 Next »

Summary

The TCGA Glioma Phenotype Research Group is part of the CIP TCGA Radiology Initiative. The group began as an ad hoc multi-institutional research team dedicated to discovering the value of applying controlled terminology to the MR imaging features of patients with gliomas. A pilot project was performed utilizing clinical and genomic data from REMBRANDT and the correlative imaging data from VASARI. Since then the group has begun detailed analysis of similar data from the TCGA Data Portal and the correlative TCGA-GBM imaging data stored within TCIA. This has led to a wider research focus with a number of sub groups focused on different aspects of analysis.

Accepted Abstracts

RSNA 2011 (Nov 27-Dec 2, 2011, Chicago, IL)

ASNR 2011 (June 4-9, 2011, Seattle, WA)

Relationship between MR Imaging Features, Gene Expression Subtype, and Histopathologic Features of Glioblastomas
Hwang SN, Clifford R, Huang E, Hammoud D, Jilwan M, Raghavan P, Wintermark M, Gutman DA, Moreno C, Cooper L, Freymann J, Kirby J, Krishnan A, Dehkharghani S, Jaffe C, Saltz JH, Flanders A, Brat DJ, Holder CA

"Results suggest an association between Proneural subtype of glioblastoma and smaller proportion of tumor enhancement. Overall tumor size and proportion of necrosis (derived from MR images) were associated with the presence of microvascular hyperplasia. This supports the observation that hypoxia related to necrosis induces microvascular hyperplasia."

Associations Between MR Imaging and Genomic Features of Glioblastomas
Hwang SN, Holder CA Huang E, Clifford R, Hammoud D, Raghavan P, Jilwan M, Wintermark M, Gutman DA, Cooper L, Moreno C, Kirby J, Freymann J, Dehkharghani S, Krishnan A, Jaffe C, Flanders A, Saltz JH, Brat DJ

"EGFR mutant tumors were significantly larger than TP53 mutant tumors, and were more likely to demonstrate pial involvement. CDKN2A homozygous deletion was associated with an ill-defined nonenhancing tumor margin and enhancing pial involvement."

A Methodology for Multi-reader Assessment of MR Imaging Features of Gliomas in Clinical Trials
Flanders, A. Huang E, Wintermark M, Hammoud D, Jilwan, M. Raghaven, Holder C, Hwang S, Clifford R, Freymann J, Kirby J, Jaffe C C

"Inclusion of vetted, tested and validated controlled terminologies into imaging arms of clinical trials is essential in adding value of imaging as a biomarker in cross-cutting correlative studies."

Prediction of Glioblastoma Multiforme (GBM) Patient Survival Using MRI Image Features and Gene Expression
Nicolasjilwan M, Clifford R, Raghavan P, Wintermark M, Hammoud D, Huang E, Jaffe C, Freymann J, Kirby J, Buetow K, Huang S, Holder C

"A subset of VASARI imaging features correlate well with patient survival. Linear regression models incorporating multiple imaging features or a single VASARI feature (ependymal extension) and tumor gene expression can be used to predict patient survival."

caBIG Tools for TCGA-GBM Analysis

Informatics software for use with this data has also been developed as part of the caBIG TCGA Enterprise Use-Case project. This caBIG enterprise use-case enabled TCGA images stored in NBIA (the same software powering the Cancer Imaging Archive) to be displayed on three different free and/or open source DICOM viewer workstations that possess annotation and markup capabilities based on Annotation Imaging Markup (AIM).  These workstations were customized to allow retrieval of images from NBIA over the caGrid (from the NCI CBIIT deployed NBIA server only), markup by AIM standards, and storage back to an AIM-E Grid data service. Some of these tools have been leveraged as part of the CIP TCGA Radiology Initiative where possible.

  • No labels