Section site map: News

• News Home
• Media Press Room
• User/System News

News

Feel the Birn

TeraGrid-powered mapping tools distinguishes Alzheimer's from normal brains.

See a pdf of the print version.

Brain disorders are challenging to diagnose, which can confuse or delay beneficial treatments. To mitigate this delay, researchers collaborating in the Biomedical Informatics Research Network (BIRN), led by Mark Ellisman, University of California, San Diego (UCSD), are using specific structural or shape differences in patients brains to help identify brain disorders. "Using TeraGrid resources, this research has been able to successfully distinguish diagnostic categories such as Alzheimers and Semantic Dementia from control subjects," says Anthony Kolasny of the Center for Imaging Science (CIS) at Johns Hopkins University. "This can potentially lead to a powerful new cyberinfrastructure tool clinicians could use to make earlier, more accurate diagnoses."

The researchers at CIS and other participants in the National Institutes of Health/National Center for Research Resources (NIH/NCRR)-supported Morphometry BIRN testbed have collaborated on a multi-institution processing pipeline that can handle the demanding analysis of this brain structure data. CIS's Large Deformation Diffeomorphic Metric Mapping (LDDMM) tool was used to study hippocampal data from 101 subjects in three categories, Alzheimer's, Semantic Dementia, and control subjects.

High-resolution structural MRI brain scans at one BIRN site were segmented at a second BIRN site, then the datasets were accessed, aligned, and processed at the CIS site with the LDDMM tool, using TeraGrid computing resources. The mapping tool computes a mathematical description of which shapes are similar and different by computing distances in the space of anatomical images, allowing direct comparison and quantitative characterization of differences in brain structure shapes.

Because the computations are demanding, the researchers wanted to run on resources beyond those of any one center. In a textbook case of TeraGrid use, and helped by TeraGrid staff at SDSC, the researchers were able to access sufficient computing resources by running some 130,000 CPU hours on TeraGrid resources at both SDSC and NCSA. This was feasible because the researchers were able to use the General Parallel File System- Wide Area Network (GPFS-WAN) to move 29 terabytes of output in some four million files between NCSA and their data store at SDSC, as well as other sites.

Using GPFS-WAN, CIS researchers at Johns Hopkins were also able to use local software applications on the remote data. This allows researchers to work in their native environment and make use of tools such as ParaView for visualization, giving them an effective method to explore very large datasets without incurring huge data transfer costs.

Hippocampal timestep deformation from a control subject to an Alzheimers patient, computed using the Large Deformation Diffeomorphic Metric Mapping tool. The large image shows velocity vector information which highlights signifi cant deformation areas or brain regions that differ between the control and Alzheimers scans. Image courtesy of Timothy Brown, BIRN, and CIS at Johns Hopkins University. Created with ParaView and MayaVi.

More News Releases

Top