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 (see: VASARI Research Project). Research trials that incorporate imaging present unique challenges due to nonstandard use of terminologies, absence of uniform data collection and validation. These obstacles traditionally limit the impact of imaging as an effective biomarker in oncology. The original purpose of this project was to assess reliability of tools and terminology developed by the Cancer Bioinformatics Grid (caBIG) initiative when performing a multireader simultaneous assessments of glioblastoma MR imaging features. It has since grown into a number of diverse research initiatives conducted by a geographically disparate open science research team.

Join the Research Group

This is an open/ad-hoc research group which has seen participation from many different people over the life of the project. We hold weekly teleconference meetings on Tuesdays at 2pm ET. Please contact us at cancerimagingarchive@mail.nih.gov if you would like to join our calls or be kept in the loop as this effort moves forward.

Group Projects

This is a listing of ongoing projects. Feel free to join one of our teleconferences to tell us about how you intend to use this data and discuss how we might be able to collaborate.

VASARI Research Project - Multiple readers reviewing TCGA brain cases and evaluating them based on the VASARI feature set and evaluating the results for reader agreement along with possible connection to related clinical/genetic/pathology data collected for the TCGA. This project is being led by Adam Flanders at Thomas Jefferson University.
DSC T2* MR Perfusion Analysis - Survival prediction using molecular classification of glioblastomas using DSC T2* MR perfusion. This project has been accepted/presented at multiple conferences (see below) and is being led by Rajan Jain at Henry Ford Hospital.
Prediction of outcome using clinical, imaging and genetic information - This project seeks to use the VASARI Research Project output in combination with data from the TCGA Data Portal to evaluate survival and time to recurrence. This project is being led by Max Wintermark and Manal Nicolas Jilwan of the University of Virginia.
Mapping of Edema/Cellular Invasion to MR Phenotypes - This project set out to present the first comprehensive radiogenomic analysis using quantitative MRI volumetrics and large-scale gene- and microRNA expression profiling in GBM. This project was led by Pascal Zinn and Rivka Colen of MDACC and BWH respectively.
Man-machine correlation of VASARI features between human and machine observers - This project is being led by Dave Gutman (Emory) and Rivka Colen (BWH).
Analysis of Diffusion-Sensitized MRI for Predicting the Histopathologic, Genomic, and Clinical Features - This is a newer project being initiated and led by Scott Hwang at Emory University
CAD Texture Analysis - Led by Brad Erickson at Mayo
Growth Kinetics - Led by Andrew Trister at Sage Bionetworks

Publications

Citation	TCIA Shared Lists	Supporting Materials
Zinn PO, Majadan B, Sathyan P, Singh SK, Majumder S, et al. 2011 Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme. PLoS ONE 6(10): e25451. doi:10.1371/journal.pone.0025451 (link)	Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes

Note: For more information on how Shared Lists are used to cite and share data please view our TCIA Citation Guidelines.

Conference Abstracts

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

Title	Presentation Time (CST) and Location	Supporting Materials
A Coordinated Method for Clinical Trials Research: Multireader Assessment of MR Imaging Features of Human Gliomas A E Flanders, MD, Philadelphia, PA; E Huang, PhD; M Wintermark, MD; M Nicolas-Jilwan, MD; P Raghavan, MD; C A Holder, MD; et al.	Tue Nov 29 2011 9:25AM - 9:35AM ROOM E451B	Full abstract
Computer-aided Visual Image Analysis of Glioblastomas and Genomic Features S N Hwang, PhD,MD, Atlanta, GA; C A Holder, MD; E Huang, PhD; R A Clifford; D Hammoud, MD; P Raghavan, MD; et al.	Sun Nov 27 2011 12:30PM - 1:00PM ROOM Lakeside Learning Center (poster) Mon Nov 28 2011 11:10AM - 11:20AM ROOM N226 (oral)	Full abstract
A Novel Statistical Method for Lossless Compression of Diagnostic Imaging Features E Huang, PhD, Rockville, MD; J B Freymann, BS; J Kirby; R A Clifford; C Jaffe, MD; A E Flanders, MD	Wed Nov 30 2011 12:15PM - 12:45PM ROOM Lakeside Learning Center	Full abstract
Prediction of Glioblastoma Multiforme (GBM) Time to Recurrence Using MRI Image Features and Gene Expression M Nicolasjilwan, MD, Charlottesville, VA; R A Clifford; A E Flanders, MD; L Scarpace; P Raghavan, MD; D Hammoud, MD; et al.	Thu Dec 01 2011 11:50AM - 12:00PM ROOM N229	Full abstract
Radiogenomic Mapping in GBM: A Novel Quantitative Merge between Imaging and Genomics - The Creation of a Signature for Tumor Necrosis Using Image Genomic Analysis in 12, 764 genes and 555 microRNAs R R Colen, MD, Boston, MA; P O Zinn, MD; J R Bruyere, BS,MA; B Mahajan, MBBS; F A Jolesz, MD	Tue Nov 29 2011 11:00 AM - 11:10 AM ROOM E451B	Full abstract

SNO 2011 (Nov 17-20, 2011, Orange County, CA)

Title	Supporting Materials
Radiogenomic Mapping in GBM in Patients with High versus Low Edema/Tumor Infiltration using An Image- Genomic Analysis of 12, 764 genes and 555 microRNAs Rivka R. Colen, Bhanu Mahajan, Ferenc A. Jolesz, Pascal O. Zinn	Full Abstract
*Survival prediction using molecular classification of glioblastomas: Role of tumor blood volume estimation using DSC T2 MR perfusion** Rajan Jain, Laila Poisson, Jayant Narang, Lisa Scarpace, David Gutman, Carl Jaffe, Joel Saltz, Adam Flanders, Brat Daniel, Tom Mikkelsen	Full Abstract

The Cancer Genome Atlas Network Symposium (Nov 17-18, 2011, Washington, DC)

Title	Supporting Materials
Neuroimaging Predictors of Survival, Pathology, and Molecular Profiles in TCGA Glioblastomas David A Gutman, Lee A.D. Cooper, Joel Saltz, Adam Flanders, Dan Brat and the TCGA Glioma Phenotype Research Group	Slides Presentation Video

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

Title	Supporting Materials
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	Full Abstract Presentation
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	Full Abstract Presentation
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	Full Abstract Presentation VASARI Features visual training guide
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	Full Abstract Presentation

Data Providers

We would like to thank the following institutions for contributing images to the TCGA-GBM collection utilized in this research project:

Henry Ford
UCSF
MDACC
Emory

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.