Optimizing the acceleration and resolution of three-dimensional fat image navigators for high-resolution motion correction at 7T
Publication year
2016Source
Magnetic Resonance in Medicine, (2016)ISSN
Publication type
Article / Letter to editor
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Organization
PI Group MR Techniques in Brain Function
Journal title
Magnetic Resonance in Medicine
Subject
150 000 MR Techniques in Brain FunctionAbstract
PURPOSE: To investigate the effect of spatial resolution and parallel imaging acceleration factor on the quality of the motion estimates derived from image navigators with a three-dimensional (3D) gradient-recalled echo (GRE) acquisition with fat excitation (3D FatNavs) for neuroimaging at 7T. METHODS: Six healthy subjects were scanned for 10 min, during which time repeated GRE volumes were acquired during small movements-alternating between fat and water excitations (WaterNavs)-allowing retrospective decimation of the data to simulate a variety of combinations of image resolution and acceleration factor. Bias and error in the motion estimates were then compared across navigator parameters. RESULTS: The 2-mm, 4 x 4 accelerated data (TRvolume = 1.2 s) provided motion estimates that were almost indistinguishable from those from the full original acquisition (2 mm, 2 x 2, TRvolume = 5.2 s). For faster navigators, it was found that good accuracy and precision were achievable with TRvolume = 144 ms, using a lower spatial resolution (4 mm, 6 x 6 acceleration) to avoid the bias observed at exceptionally high acceleration factors (8 x 8 or higher). Parameter estimates from WaterNavs and FatNavs showed close agreement with FatNavs, with better performance at exceptionally high acceleration factors. CONCLUSION: Our data help to guide the parameter choice for 3D FatNavs when a compromise must be reached between the quality of the motion estimates and the available scan time. Magn Reson Med, 2016. (c) 2016 Wiley Periodicals, Inc.
This item appears in the following Collection(s)
- Academic publications [243984]
- Donders Centre for Cognitive Neuroimaging [3983]
- Electronic publications [130695]
- Open Access publications [104970]
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