Head motion measurement and correction using FID navigators.
Algorithms
Artifacts
Brain
/ diagnostic imaging
Computer Simulation
Head
/ diagnostic imaging
Head Movements
Healthy Volunteers
Humans
Image Enhancement
/ methods
Image Processing, Computer-Assisted
Imaging, Three-Dimensional
/ methods
Magnetic Resonance Imaging
Phantoms, Imaging
Reference Values
Reproducibility of Results
FID navigators
MRI motion measurement
coil sensitivity profile
motion correction
Journal
Magnetic resonance in medicine
ISSN: 1522-2594
Titre abrégé: Magn Reson Med
Pays: United States
ID NLM: 8505245
Informations de publication
Date de publication:
01 2019
01 2019
Historique:
received:
15
12
2017
revised:
18
04
2018
accepted:
08
05
2018
pubmed:
31
7
2018
medline:
31
12
2019
entrez:
31
7
2018
Statut:
ppublish
Résumé
To develop a novel framework for rapid, intrinsic head motion measurement in MRI using FID navigators (FIDnavs) from a multichannel head coil array. FIDnavs encode substantial rigid-body motion information; however, current implementations require patient-specific training with external tracking data to extract quantitative positional changes. In this work, a forward model of FIDnav signals was calibrated using simulated movement of a reference image within a model of the spatial coil sensitivities. A FIDnav module was inserted into a nonselective 3D FLASH sequence, and rigid-body motion parameters were retrospectively estimated every readout time using nonlinear optimization to solve the inverse problem posed by the measured FIDnavs. This approach was tested in simulated data and in 7 volunteers, scanned at 3T with a 32-channel head coil array, performing a series of directed motion paradigms. FIDnav motion estimates achieved mean absolute errors of 0.34 ± 0.49 mm and 0.52 ± 0.61° across all subjects and scans, relative to ground-truth motion measurements provided by an electromagnetic tracking system. Retrospective correction with FIDnav motion estimates resulted in substantial improvements in quantitative image quality metrics across all scans with intentional head motion. Quantitative rigid-body motion information can be effectively estimated using the proposed FIDnav-based approach, which represents a practical method for retrospective motion compensation in less cooperative patient populations.
Identifiants
pubmed: 30058216
doi: 10.1002/mrm.27381
pmc: PMC6258267
mid: NIHMS966825
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
258-274Subventions
Organisme : NIBIB NIH HHS
ID : R01 EB019483
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS079788
Pays : United States
Organisme : NIMH NIH HHS
ID : R44 MH086984
Pays : United States
Informations de copyright
© 2018 International Society for Magnetic Resonance in Medicine.
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