Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging.

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dc.contributor.author Holdsworth, Samantha en
dc.contributor.author Aksoy, Murat en
dc.contributor.author Newbould, Rexford D en
dc.contributor.author Yeom, Kristen en
dc.contributor.author Van, Anh T en
dc.contributor.author Ooi, Melvyn B en
dc.contributor.author Barnes, Patrick D en
dc.contributor.author Bammer, Roland en
dc.contributor.author Skare, Stefan en
dc.date.accessioned 2018-11-13T23:13:48Z en
dc.date.issued 2012-10 en
dc.identifier.issn 1053-1807 en
dc.identifier.uri http://hdl.handle.net/2292/44210 en
dc.description.abstract To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high-quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts.We implemented an in-house built generalized autocalibrating partially parallel acquisitions (GRAPPA)-accelerated diffusion tensor (DT) echo-planar imaging (EPI) sequence at 1.5T and 3T on 1600 patients between 1 month and 18 years old. To reconstruct the data, we developed a fully automated tailored reconstruction software that selects the best GRAPPA and ghost calibration weights; does 3D rigid-body realignment with importance weighting; and employs phase correction and complex averaging to lower Rician noise and reduce phase artifacts. For select cases we investigated the use of an additional volume rejection criterion and b-matrix correction for large motion.The DTI image reconstruction procedures developed here were extremely robust in correcting for motion, failing on only three subjects, while providing the radiologists high-quality data for routine evaluation.This work suggests that, apart from the rare instance of continuous motion throughout the scan, high-quality DTI brain data can be acquired using our proposed integrated sequence and reconstruction that uses a retrospective approach to motion correction. In addition, we demonstrate a substantial improvement in overall image quality by combining phase correction with complex averaging, which reduces the Rician noise that biases noisy data. en
dc.format.medium Print-Electronic en
dc.language eng en
dc.relation.ispartofseries Journal of magnetic resonance imaging : JMRI en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.subject Brain en
dc.subject Humans en
dc.subject Image Interpretation, Computer-Assisted en
dc.subject Diffusion Magnetic Resonance Imaging en
dc.subject Image Enhancement en
dc.subject Artifacts en
dc.subject Sensitivity and Specificity en
dc.subject Retrospective Studies en
dc.subject Reproducibility of Results en
dc.subject Movement en
dc.subject Algorithms en
dc.subject Motion en
dc.subject Models, Biological en
dc.subject Pattern Recognition, Automated en
dc.subject Adolescent en
dc.subject Child en
dc.subject Child, Preschool en
dc.subject Infant en
dc.subject Infant, Newborn en
dc.subject Male en
dc.title Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging. en
dc.type Journal Article en
dc.identifier.doi 10.1002/jmri.23710 en
pubs.issue 4 en
pubs.begin-page 961 en
pubs.volume 36 en
dc.rights.holder Copyright: The author en
dc.identifier.pmid 22689498 en
pubs.end-page 971 en
pubs.publication-status Published en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype Research Support, Non-U.S. Gov't en
pubs.subtype research-article en
pubs.subtype Journal Article en
pubs.subtype Research Support, N.I.H., Extramural en
pubs.elements-id 683329 en
pubs.org-id Medical and Health Sciences en
pubs.org-id Medical Sciences en
pubs.org-id Anatomy and Medical Imaging en
dc.identifier.eissn 1522-2586 en
pubs.record-created-at-source-date 2012-09-18 en
pubs.dimensions-id 22689498 en

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