Partnership for MR spectroscopic Imaging Data Processing

Image reconstruction for MR Spectroscopic Imaging (MRSI) requires specialized spatial and spectral data processing methods, and benefits from the use of several sources of prior information that is not commonly available, including MRI-derived tissue segmentation, morphological analysis, and spectral characteristics of the observed metabolites. In addition, incorporating information from MRI data can enhance the display of low-resolution metabolite images, and multiparametric and regional statistical analysis methods can improve detection of altered metabolite distributions. As a result, full MRSI processing and analysis can involve multiple processing steps and several different data types. In this report a processing environment is described that integrates and automates these data processing and analysis functions for imaging of proton metabolite distributions in the normal human brain. The capabilities include normalization of metabolite signal intensities and transformation into a common spatial reference frame, thereby enabling the formation of a database of MR-measured human metabolite values as a function of acquisition, spatial, and subject parameters. This development is carried out under the MIDAS project (Metabolite Imaging and Data Analysis System), which provides an integrated set of MRI and MRSI processing functions. It is anticipated that further development and distribution of these capabilities will facilitate more widespread use of MRSI for diagnostic imaging; encourage the development of standardized MRSI acquisition, processing, and analysis methods; and enable improved mapping of metabolite distributions in human brain.

PI: Andrew A. Maudsley, PhD.
Project Leader: Norbert Schuff, PhD.
Funding Source: NIH
Link: http://midas.med.miami.edu ***