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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
Starting or Joining a Research Project
We are currently hosting calls in support of TCGA glioma based research projects (TCGA-GBM or TCGA-LGG) on 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 ETEastern. Please contact us at cancerimagingarchive@mail.nih.gov if you would like to join our calls inquire about setting up a new research project, discuss potential collaborations with existing groups or be otherwise kept in the loop as this effort moves forward.
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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 collaborateIf you are working with the TCGA glioma data hosted on TCIA please let us know and we would be happy to add a section describing your project here.
- 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.
- Growth Kinetics - A collaboration between Andrew Trister at Sage Bionetworks and Kristin Swanson at the University of Washington to make measurements of tumor growth kinetics in two modes (diffusion and proliferation) from pretreatment MRIs.
- 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 Ashlee Byrd and Brad Erickson at Mayo, they are using multispectral features, including intensity, texture, and morphology, to identify imaging features that predict genetic patterns.
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