Achieving robust labeling above the circle of Willis with vessel‐encoded arterial spin labeling

Purpose To improve the robustness of noninvasive vessel‐selective perfusion imaging and angiography using vessel‐encoded arterial spin labeling (VEASL) when applied to complex vascular geometries, such as above the circle of Willis (CoW) in the brain. Methods Our proposed improved optimized encoding...

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Published inMagnetic resonance in medicine Vol. 94; no. 4; pp. 1415 - 1431
Main Authors Li, Hongwei, Ji, Yang, Wang, He, Chen, Zhensen, Qian, Tiansheng, Liao, Yujun, Wang, Jian, Woods, Joseph G., Suzuki, Yuriko, Okell, Thomas W.
Format Journal Article
LanguageEnglish
Published United States Wiley Subscription Services, Inc 01.10.2025
John Wiley and Sons Inc
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Abstract Purpose To improve the robustness of noninvasive vessel‐selective perfusion imaging and angiography using vessel‐encoded arterial spin labeling (VEASL) when applied to complex vascular geometries, such as above the circle of Willis (CoW) in the brain. Methods Our proposed improved optimized encoding scheme (IOES) better accounts for vascular geometry and the VEASL encoding process, leading to more SNR‐efficient encodings than previous approaches. Pseudo‐continuous arterial spin labeling (PCASL) parameters were optimized for a thinner labeling region, allowing tortuous vessels to be more accurately treated as single points within the labeling plane. Our optimized approach was compared to the original OES method above the CoW in healthy volunteers, with preliminary application in two Moyamoya patients. Results In simulation, the IOES improved SNR efficiency by approximately 10% and used longer wavelength encodings that are less sensitive to subject motion. The effective labeling thickness was reduced using optimized PCASL parameters, which maintained high labeling efficiency. In healthy volunteers, these improvements allowed for the separation of at least nine arteries and their downstream tissues, with more accurate vessel decoding and closer alignment between the measured VEASL signal modulation and the encoding design. Vascular territories consistent with angiography were found in the Moyamoya patients. Conclusions Combining IOES with optimized PCASL parameters, the vessel‐decoding efficacy in a region with complex vascular geometry above the CoW was improved. The automated encoding design process and scan times under 6 min make it feasible to observe flow patterns above the CoW in clinical settings, particularly for studies of collateral circulation.
AbstractList Purpose To improve the robustness of noninvasive vessel‐selective perfusion imaging and angiography using vessel‐encoded arterial spin labeling (VEASL) when applied to complex vascular geometries, such as above the circle of Willis (CoW) in the brain. Methods Our proposed improved optimized encoding scheme (IOES) better accounts for vascular geometry and the VEASL encoding process, leading to more SNR‐efficient encodings than previous approaches. Pseudo‐continuous arterial spin labeling (PCASL) parameters were optimized for a thinner labeling region, allowing tortuous vessels to be more accurately treated as single points within the labeling plane. Our optimized approach was compared to the original OES method above the CoW in healthy volunteers, with preliminary application in two Moyamoya patients. Results In simulation, the IOES improved SNR efficiency by approximately 10% and used longer wavelength encodings that are less sensitive to subject motion. The effective labeling thickness was reduced using optimized PCASL parameters, which maintained high labeling efficiency. In healthy volunteers, these improvements allowed for the separation of at least nine arteries and their downstream tissues, with more accurate vessel decoding and closer alignment between the measured VEASL signal modulation and the encoding design. Vascular territories consistent with angiography were found in the Moyamoya patients. Conclusions Combining IOES with optimized PCASL parameters, the vessel‐decoding efficacy in a region with complex vascular geometry above the CoW was improved. The automated encoding design process and scan times under 6 min make it feasible to observe flow patterns above the CoW in clinical settings, particularly for studies of collateral circulation.
To improve the robustness of noninvasive vessel-selective perfusion imaging and angiography using vessel-encoded arterial spin labeling (VEASL) when applied to complex vascular geometries, such as above the circle of Willis (CoW) in the brain.PURPOSETo improve the robustness of noninvasive vessel-selective perfusion imaging and angiography using vessel-encoded arterial spin labeling (VEASL) when applied to complex vascular geometries, such as above the circle of Willis (CoW) in the brain.Our proposed improved optimized encoding scheme (IOES) better accounts for vascular geometry and the VEASL encoding process, leading to more SNR-efficient encodings than previous approaches. Pseudo-continuous arterial spin labeling (PCASL) parameters were optimized for a thinner labeling region, allowing tortuous vessels to be more accurately treated as single points within the labeling plane. Our optimized approach was compared to the original OES method above the CoW in healthy volunteers, with preliminary application in two Moyamoya patients.METHODSOur proposed improved optimized encoding scheme (IOES) better accounts for vascular geometry and the VEASL encoding process, leading to more SNR-efficient encodings than previous approaches. Pseudo-continuous arterial spin labeling (PCASL) parameters were optimized for a thinner labeling region, allowing tortuous vessels to be more accurately treated as single points within the labeling plane. Our optimized approach was compared to the original OES method above the CoW in healthy volunteers, with preliminary application in two Moyamoya patients.In simulation, the IOES improved SNR efficiency by approximately 10% and used longer wavelength encodings that are less sensitive to subject motion. The effective labeling thickness was reduced using optimized PCASL parameters, which maintained high labeling efficiency. In healthy volunteers, these improvements allowed for the separation of at least nine arteries and their downstream tissues, with more accurate vessel decoding and closer alignment between the measured VEASL signal modulation and the encoding design. Vascular territories consistent with angiography were found in the Moyamoya patients.RESULTSIn simulation, the IOES improved SNR efficiency by approximately 10% and used longer wavelength encodings that are less sensitive to subject motion. The effective labeling thickness was reduced using optimized PCASL parameters, which maintained high labeling efficiency. In healthy volunteers, these improvements allowed for the separation of at least nine arteries and their downstream tissues, with more accurate vessel decoding and closer alignment between the measured VEASL signal modulation and the encoding design. Vascular territories consistent with angiography were found in the Moyamoya patients.Combining IOES with optimized PCASL parameters, the vessel-decoding efficacy in a region with complex vascular geometry above the CoW was improved. The automated encoding design process and scan times under 6 min make it feasible to observe flow patterns above the CoW in clinical settings, particularly for studies of collateral circulation.CONCLUSIONSCombining IOES with optimized PCASL parameters, the vessel-decoding efficacy in a region with complex vascular geometry above the CoW was improved. The automated encoding design process and scan times under 6 min make it feasible to observe flow patterns above the CoW in clinical settings, particularly for studies of collateral circulation.
To improve the robustness of noninvasive vessel-selective perfusion imaging and angiography using vessel-encoded arterial spin labeling (VEASL) when applied to complex vascular geometries, such as above the circle of Willis (CoW) in the brain. Our proposed improved optimized encoding scheme (IOES) better accounts for vascular geometry and the VEASL encoding process, leading to more SNR-efficient encodings than previous approaches. Pseudo-continuous arterial spin labeling (PCASL) parameters were optimized for a thinner labeling region, allowing tortuous vessels to be more accurately treated as single points within the labeling plane. Our optimized approach was compared to the original OES method above the CoW in healthy volunteers, with preliminary application in two Moyamoya patients. In simulation, the IOES improved SNR efficiency by approximately 10% and used longer wavelength encodings that are less sensitive to subject motion. The effective labeling thickness was reduced using optimized PCASL parameters, which maintained high labeling efficiency. In healthy volunteers, these improvements allowed for the separation of at least nine arteries and their downstream tissues, with more accurate vessel decoding and closer alignment between the measured VEASL signal modulation and the encoding design. Vascular territories consistent with angiography were found in the Moyamoya patients. Combining IOES with optimized PCASL parameters, the vessel-decoding efficacy in a region with complex vascular geometry above the CoW was improved. The automated encoding design process and scan times under 6 min make it feasible to observe flow patterns above the CoW in clinical settings, particularly for studies of collateral circulation.
Purpose To improve the robustness of noninvasive vessel‐selective perfusion imaging and angiography using vessel‐encoded arterial spin labeling (VEASL) when applied to complex vascular geometries, such as above the circle of Willis (CoW) in the brain. Methods Our proposed improved optimized encoding scheme (IOES) better accounts for vascular geometry and the VEASL encoding process, leading to more SNR‐efficient encodings than previous approaches. Pseudo‐continuous arterial spin labeling (PCASL) parameters were optimized for a thinner labeling region, allowing tortuous vessels to be more accurately treated as single points within the labeling plane. Our optimized approach was compared to the original OES method above the CoW in healthy volunteers, with preliminary application in two Moyamoya patients. Results In simulation, the IOES improved SNR efficiency by approximately 10% and used longer wavelength encodings that are less sensitive to subject motion. The effective labeling thickness was reduced using optimized PCASL parameters, which maintained high labeling efficiency. In healthy volunteers, these improvements allowed for the separation of at least nine arteries and their downstream tissues, with more accurate vessel decoding and closer alignment between the measured VEASL signal modulation and the encoding design. Vascular territories consistent with angiography were found in the Moyamoya patients. Conclusions Combining IOES with optimized PCASL parameters, the vessel‐decoding efficacy in a region with complex vascular geometry above the CoW was improved. The automated encoding design process and scan times under 6 min make it feasible to observe flow patterns above the CoW in clinical settings, particularly for studies of collateral circulation.
Author Chen, Zhensen
Wang, Jian
Ji, Yang
Wang, He
Liao, Yujun
Suzuki, Yuriko
Okell, Thomas W.
Li, Hongwei
Qian, Tiansheng
Woods, Joseph G.
AuthorAffiliation 2 Wellcome Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences University of Oxford Oxford UK
5 Department of Neurosurgery Fudan University Huashan Hospital Shanghai People's Republic of China
3 Department of Electronic Engineering and Information Science, School of Information Science and Technology University of Science and Technology of China Hefei People's Republic of China
6 Clinical Medical Center of Neurosurgery Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration Shanghai People's Republic of China
4 MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence Fudan University Shanghai People's Republic of China
1 Institute of Science and Technology for Brain‐inspired Intelligence Fudan University Shanghai People's Republic of China
7 Department of Neurosurgery, The Second People's Hospital of Changzhou The Third Affiliated Hospital of Nanjing Medical University, Changzhou Medical Center C
AuthorAffiliation_xml – name: 1 Institute of Science and Technology for Brain‐inspired Intelligence Fudan University Shanghai People's Republic of China
– name: 7 Department of Neurosurgery, The Second People's Hospital of Changzhou The Third Affiliated Hospital of Nanjing Medical University, Changzhou Medical Center Changzhou People's Republic of China
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– name: 4 MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence Fudan University Shanghai People's Republic of China
– name: 3 Department of Electronic Engineering and Information Science, School of Information Science and Technology University of Science and Technology of China Hefei People's Republic of China
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Issue 4
Keywords encoding scheme
vessel‐selective
vascular territory
SNR efficiency
vessel‐encoded arterial spin labeling (VEASL)
Language English
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Snippet Purpose To improve the robustness of noninvasive vessel‐selective perfusion imaging and angiography using vessel‐encoded arterial spin labeling (VEASL) when...
To improve the robustness of noninvasive vessel-selective perfusion imaging and angiography using vessel-encoded arterial spin labeling (VEASL) when applied to...
Purpose To improve the robustness of noninvasive vessel‐selective perfusion imaging and angiography using vessel‐encoded arterial spin labeling (VEASL) when...
SourceID pubmedcentral
proquest
pubmed
crossref
wiley
SourceType Open Access Repository
Aggregation Database
Index Database
Publisher
StartPage 1415
SubjectTerms Adult
Algorithms
Angiography
Arteries
Blood vessels
Brain - blood supply
Brain - diagnostic imaging
Cerebrovascular Circulation
Circle of Willis - diagnostic imaging
Coding
Computer Simulation
Effectiveness
encoding scheme
Female
Flow distribution
Healthy Volunteers
Humans
Image Processing, Computer-Assisted - methods
Imaging Methodology
Labeling
Magnetic Resonance Angiography - methods
Male
Medical imaging
Moyamoya Disease - diagnostic imaging
Neuroimaging
Parameters
Signal-To-Noise Ratio
SNR efficiency
Spin labeling
Spin Labels
vascular territory
vessel‐encoded arterial spin labeling (VEASL)
vessel‐selective
Title Achieving robust labeling above the circle of Willis with vessel‐encoded arterial spin labeling
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fmrm.30542
https://www.ncbi.nlm.nih.gov/pubmed/40590250
https://www.proquest.com/docview/3234675406
https://www.proquest.com/docview/3226350542
https://pubmed.ncbi.nlm.nih.gov/PMC12309872
Volume 94
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