A stitching method for dynamic field monitoring using NMR probes: validation in simulation and human experiments

Motivation: Last year we proposed and demonstrated a stitching method that can be used to characterize sequences with higher resolution or longer readout. Goal(s): To validate our stitching method by image reconstruction based on an extended signal model using simulation and real data experiments. Approach: Image reconstruction and MR simulation incorporating higher-order field terms were devised by expanding MRIReco.jl and KomaMRI.jl. Human brain scans with spiral readouts were also conducted at 7 Tesla. Results: In simulation, using stitching monitored field dynamics resulted in better image reconstruction. Likewise, using our stitching method in in-vivo experiments outperformed the standard field monitoring approach, especially at higher resolution. Impact: Validated with both simulation and real data experiments, our proposed stitching method capable of characterizing challenging imaging gradients using commercially available hardware is believed to have a promise to advance many ultrahigh resolution MRI applications at ultrahigh field.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/3293
Primary Topic
NMR spectroscopy and applications
Type
article
Field-Weighted Citation Impact
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article

A stitching method for dynamic field monitoring using NMR probes: validation in simulation and human experiments

Zhentao Zuo, Yan Zhuo, Alexander Bratch, Edward J. Auerbach et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
NMR spectroscopy and applications
article

A stitching method for dynamic field monitoring using NMR probes: validation in simulation and human experiments

Zhentao Zuo, Yan Zhuo, Alexander Bratch, Edward J. Auerbach, Kâmil Uǧurbil, Xiaoping Wu, Andrea Grant, Rong Xue, Zihao Zhang, Jinyuan Zhang, Jing An, Colbert E. Cushing
article en

Abstract

Motivation: Last year we proposed and demonstrated a stitching method that can be used to characterize sequences with higher resolution or longer readout. Goal(s): To validate our stitching method by image reconstruction based on an extended signal model using simulation and real data experiments. Approach: Image reconstruction and MR simulation incorporating higher-order field terms were devised by expanding MRIReco.jl and KomaMRI.jl. Human brain scans with spiral readouts were also conducted at 7 Tesla. Results: In simulation, using stitching monitored field dynamics resulted in better image reconstruction. Likewise, using our stitching method in in-vivo experiments outperformed the standard field monitoring approach, especially at higher resolution. Impact: Validated with both simulation and real data experiments, our proposed stitching method capable of characterizing challenging imaging gradients using commercially available hardware is believed to have a promise to advance many ultrahigh resolution MRI applications at ultrahigh field.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 90%
NMR spectroscopy and applications
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A stitching method for dynamic field monitoring using NMR probes: validation in simulation and human experiments — Zhentao Zuo, Yan Zhuo, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2025) | TGRS Research Map | TGRS