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Journal article

MOdulation‐Guided ENcoding (MOGEN) scheme for vessel‐encoded arterial spin labeling

Abstract:
Purpose

Vessel-encoded arterial spin labeling (VEASL) enables simultaneous, non-contrast imaging of multiple vascular territories that is useful for differential diagnosis and treatment monitoring of cerebrovascular diseases. However, the existing encoding methods are signal-to-noise ratio (SNR) inefficient.

Methods

We developed a MOdulation-Guided ENcoding (MOGEN) scheme that directly exploits the inversion spatial modulation profile to obtain SNR-efficient encoding matrix. Simulations, phantom tests, and healthy volunteer scans were performed to demonstrate its feasibility in multiple application scenarios.

Results

Simulation studies demonstrated that MOGEN achieves significantly higher theoretical SNR efficiency than previous methods for both four- and six-artery configurations. In healthy volunteers, MOGEN improved in vivo SNR by approximately 15% and provided more robust vessel decoding, particularly when the spatial modulation deviated from a cosine profile. In patients with Moyamoya disease, MOGEN enabled reliable visualization of collateral pathways even when scan time was reduced to ˜5 min for six arteries. Furthermore, by considering vessel size with multi-voxel vessel representation, MOGEN enhanced single-artery selectivity in vessel-encoded angiography. We also demonstrated that a straightforward approach of off-resonance correction for VEASL at ultra-high field was feasible by using MOGEN.

Conclusion

MOGEN offered several benefits for VEASL, including high SNR efficiency, flexible spatial modulation and PCASL parameters selection, vessel size consideration, and straightforward off-resonance correction, thereby substantially improving robustness and usability of VEASL across various applications.

Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1002/mrm.70335

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
St Catherine's College
Role:
Author
ORCID:
0000-0001-8258-0659
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
ORCID:
0000-0002-4851-7872


More from this funder
Funder identifier:
https://ror.org/029chgv08
Grant:
220204/Z/20/Z
203139/Z/16/Z
More from this funder
Funder identifier:
https://ror.org/01h0zpd94
Grant:
82302156
More from this funder
Funder identifier:
10.13039/501100012166
Grant:
2023YFF1204801


Publisher:
Wiley
Journal:
Magnetic Resonance in Medicine More from this journal
Place of publication:
United States
Publication date:
2026-03-07
Acceptance date:
2026-02-24
DOI:
EISSN:
1522-2594
ISSN:
0740-3194
Pmid:
41795084


Language:
English
Keywords:
Pubs id:
2387105
Local pid:
pubs:2387105
Source identifiers:
W7134189616
Deposit date:
2026-03-17
ARK identifier:

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