ArticleMagnetic resonance in medicine2023
Improving motion robustness of 3D MR fingerprinting with a fat navigator.
Article in Magnetic resonance in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Prospective motion correction with data reacquisition based on fat navigators for T1-weighted brain MRI at 3T.Medical & biological engineering & computing · 2026Article
- In Vivo Meso-Scale Whole-Brain Quantitative Imaging With Tailored MRF on the NexGen 7T Scanner.Magnetic resonance in medicine · 2026Article
- Contrast-optimized basis functions for self-navigated motion correction in quantitative MRI.Magnetic resonance in medicine · 2026Article
- Summary from the 2025 International Society for Magnetic Resonance in Medicine workshop on body MRI: Unsolved problems and unmet needs.Magnetic resonance in medicine · 2026Review
- "MR Fingerprinting for Imaging Brain Hemodynamics and Oxygenation".Journal of magnetic resonance imaging : JMRI · 2025Review
- Distortion-free steady-state diffusion-weighted imaging with magnetic resonance fingerprinting.Medical physics · 2025Article
- Time-resolved MR fingerprinting for TMagnetic resonance in medicine · 2025Article
- Acceleration of Simultaneous Multislice Magnetic Resonance Fingerprinting With Spatiotemporal Convolutional Neural Network.NMR in biomedicine · 2025Article
- Improving motion robustness of 3D MR fingerprinting with a fat navigator.Magnetic resonance in medicine · 2023Article
- Magnetic Resonance Fingerprinting of the Pediatric Brain.Magnetic resonance imaging clinics of North America · 2021Review
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Authors and funding
6 authors.
Funding
Abstract
purposeTo develop a 3D MR fingerprinting (MRF) method in combination with fat navigators to improve its motion robustness for neuroimaging.
methodsA rapid fat navigator was developed using the stack-of-spirals acquisition and non-Cartesian spiral GRAPPA. The fat navigator module was implemented in the 3D MRF sequence with high scan efficiency. The developed method was first validated in phantoms and five healthy subjects with intentional head motion. The method was further applied to infants with neonatal opioid withdrawal symptoms. The 3D MRF scans with fat navigators acquired with and without acceleration along the partition-encoding direction were both examined in the study.
resultsBoth phantom and in vivo results demonstrated that the added fat navigator modules did not influence the quantification accuracy in MRF. In combination with non-Cartesian spiral GRAPPA, a rapid fat navigator sampling with whole-brain coverage was achieved in ˜0.5 s at 3T, reducing its sensitivity to potential motion. Based on the motion waveforms extracted from fat navigators, the motion robustness of the 3D MRF was largely improved. With the proposed method, the motion-corrupted MRF datasets yielded T1 and T2 maps with significantly reduced artifacts and high correlations with measurements from the reference motion-free MRF scans.
conclusionWe developed a 3D MRF method coupled with rapid fat navigators to improve its motion robustness for quantitative neuroimaging. Our results demonstrate that (1) accurate tissue quantification was preserved with the fat navigator modules and (2) the motion robustness for quantitative tissue mapping was largely improved with the developed method.
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