Arc-ZTE: Incoherent k-space sampling in time using continuously-slewed gradients for flexible, dynamic, quiet Zero TE MRI

Motivation: Existing Zero TE methods are constrained due to gradient slew limits between spokes, which hinders their use in dynamic imaging applications. Goal(s): We aim to improve temporal k-space sampling in time by increasing the possible angular distance between consecutive spokes via continuously-slewed gradients, while still maintaining minimal gradient refocusing and minimal acoustic noise. Approach: We parameterize the k-space trajectory using sequential rotations of an arc in k-space, then optimize the rotation angles over metrics for sampling uniformity and refocusing. Results: We demonstrate a proof-of-concept of this trajectory and show improvement over radial ZTE in k-space coverage metrics and reconstructions for various temporal resolutions. Impact: By improving temporal k-space sampling for Zero-TE MRI, our work enables quiet, dynamic imaging with flexible temporal resolution. Potential applications include quiet DCE or respiratory motion-resolved imaging for neonates and other sound-sensitive populations.

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
2024-11-26
DOI
https://doi.org/10.58530/2024/0950
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Arc-ZTE: Incoherent k-space sampling in time using continuously-slewed gradients for flexible, dynamic, quiet Zero TE MRI

Tobias Wood, Michael Lustig, Guoqing Zhang, Shreya Ramachandran
1 links
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
Advanced MRI Techniques and Applications
article

Arc-ZTE: Incoherent k-space sampling in time using continuously-slewed gradients for flexible, dynamic, quiet Zero TE MRI

Tobias Wood, Michael Lustig, Guoqing Zhang, Shreya Ramachandran
article en

Abstract

Motivation: Existing Zero TE methods are constrained due to gradient slew limits between spokes, which hinders their use in dynamic imaging applications. Goal(s): We aim to improve temporal k-space sampling in time by increasing the possible angular distance between consecutive spokes via continuously-slewed gradients, while still maintaining minimal gradient refocusing and minimal acoustic noise. Approach: We parameterize the k-space trajectory using sequential rotations of an arc in k-space, then optimize the rotation angles over metrics for sampling uniformity and refocusing. Results: We demonstrate a proof-of-concept of this trajectory and show improvement over radial ZTE in k-space coverage metrics and reconstructions for various temporal resolutions. Impact: By improving temporal k-space sampling for Zero-TE MRI, our work enables quiet, dynamic imaging with flexible temporal resolution. Potential applications include quiet DCE or respiratory motion-resolved imaging for neonates and other sound-sensitive populations.

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 63%
Advanced MRI Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.