Literature DB >> 25463455

Quantitative water content mapping at clinically relevant field strengths: a comparative study at 1.5 T and 3 T.

Zaheer Abbas1, Vincent Gras2, Klaus Möllenhoff2, Ana-Maria Oros-Peusquens2, Nadim Joni Shah3.   

Abstract

PURPOSE: Quantitative water content mapping in vivo using MRI is a very valuable technique to detect, monitor and understand diseases of the brain. At 1.5 T, this technology has already been successfully used, but it has only recently been applied at 3T because of significantly increased RF field inhomogeneity at the higher field strength. To validate the technology at 3T, we estimate and compare in vivo quantitative water content maps at 1.5 T and 3T obtained with a protocol proposed recently for 3T MRI.
METHODS: The proposed MRI protocol was applied on twenty healthy subjects at 1.5 T and 3T; the same post-processing algorithms were used to estimate the water content maps. The 1.5 T and 3T maps were subsequently aligned and compared on a voxel-by-voxel basis. Statistical analysis was performed to detect possible differences between the estimated 1.5 T and 3T water maps.
RESULTS: Our analysis indicates that the water content values obtained at 1.5 T and 3T did not show significant systematic differences. On average the difference did not exceed the standard deviation of the water content at 1.5 T. Furthermore, the contrast-to-noise ratio (CNR) of the estimated water content map was increased at 3T by a factor of at least 1.5.
CONCLUSIONS: Vulnerability to RF inhomogeneity increases dramatically with the increasing static magnetic field strength. However, using advanced corrections for the sensitivity profile of the MR coils, it is possible to preserve quantitative accuracy while benefiting from the increased CNR at the higher field strength. Indeed, there was no significant difference in the water content values obtained in the brain at 1.5 T and 3T.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Clinical field strength; Parametric mapping; Proton density; Quantitative imaging; Water content

Mesh:

Substances:

Year:  2014        PMID: 25463455     DOI: 10.1016/j.neuroimage.2014.11.017

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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