Comprehensive processing, display and analysis for in vivo MR spectroscopic imaging.

Published

Journal Article

Image reconstruction for magnetic resonance spectroscopic imaging (MRSI) requires specialized spatial and spectral data processing methods and benefits from the use of several sources of prior information that are not commonly available, including MRI-derived tissue segmentation, morphological analysis and spectral characteristics of the observed metabolites. In addition, incorporating information obtained 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 paper, 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 allowing 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 the human brain.

Full Text

Duke Authors

Cited Authors

  • Maudsley, AA; Darkazanli, A; Alger, JR; Hall, LO; Schuff, N; Studholme, C; Yu, Y; Ebel, A; Frew, A; Goldgof, D; Gu, Y; Pagare, R; Rousseau, F; Sivasankaran, K; Soher, BJ; Weber, P; Young, K; Zhu, X

Published Date

  • June 2006

Published In

Volume / Issue

  • 19 / 4

Start / End Page

  • 492 - 503

PubMed ID

  • 16763967

Pubmed Central ID

  • 16763967

International Standard Serial Number (ISSN)

  • 0952-3480

Digital Object Identifier (DOI)

  • 10.1002/nbm.1025

Language

  • eng

Conference Location

  • England