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Simultaneous and synchronous characterization of blood and CSF flow dynamics using multiple Venc PC MRI
Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, WI, Madison, United States; Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, WI, Madison, United States.
Umeå University, Faculty of Medicine, Department of Diagnostics and Intervention. Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, WI, Madison, United States; Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, WI, Madison, United States.ORCID iD: 0000-0003-3181-785X
Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, WI, Madison, United States; Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, WI, Madison, United States.
Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, WI, Madison, United States.
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2025 (English)In: Imaging Neuroscience, E-ISSN 2837-6056, Vol. 3, article id imag_a_00521Article in journal (Refereed) Published
Abstract [en]

Neurofluid dynamics are crucial for maintaining brain homeostasis and facilitating the clearance of brain metabolites through the coupling of arterial and venous blood with cerebrospinal fluid (CSF). Two-dimensional phase contrast (PC) magnetic resonance imaging (MRI) is frequently used to study neurofluids; however, separate examinations are typically required for assessing blood and CSF flow, which can confound analyses due to asynchronous physiological measurements. To enable simultaneous assessment of neurofluid dynamics, we describe and evaluate a 2D PC MRI approach in human participant experiments. An interleaved multi-point velocity encoding scheme was integrated into a 2D golden angle spiral PC MRI scan to facilitate synchronous characterization of neurofluids. Two multi-point schemes, including interleaved dual-venc (DV) and triple-venc (MV) scans, were evaluated and compared with standard asynchronous single-venc (SV) scans. Data and repeated scans were collected on a clinical 3.0T scanner at the level of the C1/C2 vertebrae in 10 human participants. From cardiac-resolved images, the relationship between net blood flow and CSF flow pulsatile volume change was characterized using regression modeling. Temporal lags between cardiac-driven arterial blood (vertebral arteries (VAs) and internal carotid arteries (ICAs)) and spinal canal (SC) CSF were estimated with cross-correlation. SV, DV, and MV flow mean, range, and volume changes were studied and compared using linear mixed effect models, intraclass correlation coefficients, Bland–Altman, and Pearson correlations. A strong relationship was measured between net blood flow and CSF flow pulsatile volume change from SV (R2 = 0.71, P = 0.002), DV (R2 = 0.70, P = 0.003), and MV (R2 = 0.78, P < 0.001) scans. SC-VAs temporal lags were statistically longer than SC-ICAs lags across all scans (P < 0.001 for SV, DV, and MV). Bland–Altman analyses and repeatability coefficients indicated that DV and MV scans had the highest repeatability. MV scans generally underestimated SC CSF flow markers relative to SV and DV scans. A more pronounced flow offset in venous measures was identified between SV scans and the DV and MV scans. In conclusion, this study introduced a method for simultaneous imaging of cranio-spinal arterial, venous, and CSF flow, enabling the synchronous assessment of neurofluid dynamics. The results indicated that interleaved DV and MV scans could improve the evaluation of neurofluid coupling compared with asynchronous SV scans.

Place, publisher, year, edition, pages
MIT Press, 2025. Vol. 3, article id imag_a_00521
Keywords [en]
flow encoding, interleaved, multi-venc, neurofluids, phase contrast MRI
National Category
Radiology and Medical Imaging
Identifiers
URN: urn:nbn:se:umu:diva-242229DOI: 10.1162/imag_a_00521ISI: 001521324000001Scopus ID: 2-s2.0-105010266618OAI: oai:DiVA.org:umu-242229DiVA, id: diva2:1984913
Funder
NIH (National Institutes of Health), R01AG075788; R01AG027161; R01AG021155;R01AG082208; P30AG062715; R21AG077337; R21NS125094The Swedish Brain Foundation, PS2023-0047Available from: 2025-07-18 Created: 2025-07-18 Last updated: 2025-07-18Bibliographically approved

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Vikner, Tomas

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