Handling macromolecule signals in the quantification of the neurochemical profile.

Details

Serval ID
serval:BIB_5948A40DF81C
Type
Article: article from journal or magazin.
Publication sub-type
Review (review): journal as complete as possible of one specific subject, written based on exhaustive analyses from published work.
Collection
Publications
Institution
Title
Handling macromolecule signals in the quantification of the neurochemical profile.
Journal
Journal of Alzheimer's Disease
Author(s)
Cudalbu C., Mlynárik V., Gruetter R.
ISSN
1875-8908 (Electronic)
ISSN-L
1387-2877
Publication state
Published
Issued date
2012
Volume
31
Number
Suppl 3
Pages
S101-S115
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't ; Review Publication Status: ppublish
Abstract
In vivo localized proton magnetic resonance spectroscopy (1H MRS) became a powerful and unique technique to non-invasively investigate brain metabolism of rodents and humans. The main goal of 1H MRS is the reliable quantification of concentrations of metabolites (neurochemical profile) in a well-defined region of the brain. The availability of very high magnetic field strengths combined with the possibility of acquiring spectra at very short echo time have dramatically increased the number of constituents of the neurochemical profile. The quantification of spectra measured at short echo times is complicated by the presence of macromolecule signals of particular importance at high magnetic fields. An error in the macromolecule estimation can lead to substantial errors in the obtained neurochemical profile. The purpose of the present review is to overview methods of high field 1H MRS with a focus on the metabolite quantification, in particular in handling signals of macromolecules. Three main approaches of handling signals of macromolecules are described, namely mathematical estimation of macromolecules, measurement of macromolecules in vivo, and direct acquisition of the in vivo spectrum without the contribution of macromolecules.
Keywords
Algorithms, Brain Chemistry/physiology, Electromagnetic Fields, Humans, Macromolecular Substances/chemistry, Magnetic Resonance Imaging, Magnetic Resonance Spectroscopy/methods, Models, Statistical
Pubmed
Web of science
Create date
29/04/2013 10:41
Last modification date
20/08/2019 15:12
Usage data