Open AccessAddressing a systematic vibration artifact in diffusion‐weighted MRI
Author(s) -
Gallichan Daniel,
Scholz Jan,
Bartsch Andreas,
Behrens Timothy E.,
Robson Matthew D.,
Miller Karla L.
Publication year - 2010
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.20856
Subject(s) - artifact (error) , diffusion mri , voxel , signal (programming language) , diffusion , nuclear magnetic resonance , frequency domain , distortion (music) , acceleration , artificial intelligence , magnetic resonance imaging , physics , computer science , computer vision , radiology , medicine , programming language , thermodynamics , amplifier , optoelectronics , cmos , classical mechanics
We have identified and studied a pronounced artifact in diffusion‐weighted MRI on a clinical system. The artifact results from vibrations of the patient table due to low‐frequency mechanical resonances of the system which are stimulated by the low‐frequency gradient switching associated with the diffusion‐weighting. The artifact manifests as localized signal‐loss in images acquired with partial Fourier coverage when there is a strong component of the diffusion‐gradient vector in the left–right direction. This signal loss is caused by local phase ramps in the image domain which shift the apparent k‐space center for a particular voxel outside the covered region. The local signal loss masquerades as signal attenuation due to diffusion, severely disrupting the quantitative measures associated with diffusion‐tensor imaging (DTI). We suggest a way to improve the interpretation of affected DTI data by including a co‐regressor which accounts for the empirical response of regions affected by the artifact. We also demonstrate that the artifact may be avoided by acquiring full k‐space data, and that subsequent increases in TE can be avoided by employing parallel acceleration. Hum Brain Mapp, 2010. © 2009 Wiley‐Liss, Inc.