title: Reducing distortions in diffusion-weighted echo planar imaging with a dual-echo blip-reversed sequence.
abstract: The inherent distortions in echo-planar imaging that arise due to inhomogeneities in the static magnetic field can lead to difficulties when attempting to obtain structurally accurate diffusion-tensor imaging data. Parallel acceleration techniques can reduce the magnitude of these distortions but do not remove them entirely. Images can be corrected using a measured field map, but this is prone to error. One approach to correcting for these distortions, referred to here as "blip-reversed" echo-planar imaging, involves collecting a second set of images with the phase encoding reversed. Here, a novel approach to collecting blip-reversed echo-planar imaging data for diffusion-tensor imaging is presented: a dual-echo sequence is used in which the phase-encoding direction of the second echo is swapped compared to the first echo. This allows benefits of the blip-reversed approach to be exploited, with only a modest increase in scan time and, due to the extra data acquired, no significant loss of signal-to-noise efficiency. A novel approach to recombining blip-reversed data is also presented, which involves refining the measured field map, using an algorithm to minimize the difference between the corrected images. The field map refinement is also applicable to conventionally acquired blip-reversed sequences.
authors.affiliation: Centre for Functional Magnetic Resonance Imaging of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, UK. daniel.gallichan@uniklinik-freiburg.de
authors.forename: Daniel
authors.initials: D
authors.lastname: Gallichan
authors.forename: Jesper L R
authors.initials: JL
authors.lastname: Andersson
authors.forename: Mark
authors.initials: M
authors.lastname: Jenkinson
authors.forename: Matthew D
authors.initials: MD
authors.lastname: Robson
authors.forename: Karla L
authors.initials: KL
authors.lastname: Miller
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D016000:Cluster Analysis; D003196:Computer Graphics; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D017352:Echo-Planar Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009716:Numerical Analysis, Computer-Assisted; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface