Proton magnetic resonance spectroscopic imaging (MRSI) allows the in vivo determination regional distribution of various neurochemicals. The pathologic specificity and inherently quantitative information provided by MRSI should help understand the mechanisms involved in various neurological disorders and improve patient management. In spite of its demonstrated use, MRSI is not routinely used because of lack of fast and automatic MRSI analysis tools. In order to overcome these limitations and exploit the power of MRSI, this application proposes to develop a fast and automated software package for determining the absolute concentrations of brain metabolites that are observed on proton MRS. The proposed fast, robust, and automated analysis software package will be freely available to users. This software is based on artificial neural networks. It has been demonstrated to be fast and robust. In order to account for the contribution of multiple tissues to a given spectroscopic voxel, the software includes fast image segmentation technique and combines it with the MRSI analysis software. The fast segmentation technique is based on phase sensitive inversion recovery imaging sequence that allows the reconstruction of images in phase sensitive and magnitude modes that exhibit dramatically different tissue contrasts. For wider use by the neuroimaging community, this software will be developed on a PC platform and distributed.

Public Health Relevance

This proposed application is in response to the RFA for the development of Neuroinformatic tools to serve the neuroimaging community. The proposed software would allow both neuroscientists and clinicians to analyze the proton MRSI data to determine how various neurological disorders affect the regional metabolic distribution in brain. This information would be important for gaining an insight into the disease processes and also serve as diagnostic tool for improved patient management.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Small Research Grants (R03)
Project #
1R03EB008084-01A1
Application #
7500550
Study Section
Special Emphasis Panel (ZRG1-MDCN-G (50))
Program Officer
Cohen, Zohara
Project Start
2009-06-01
Project End
2011-02-28
Budget Start
2009-06-01
Budget End
2011-02-28
Support Year
1
Fiscal Year
2009
Total Cost
$150,000
Indirect Cost
Name
University of Texas Health Science Center Houston
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
800771594
City
Houston
State
TX
Country
United States
Zip Code
77225