MVP‐VSASL: measuring MicroVascular Pulsatility using velocity‐selective arterial spin labeling

• Published in: Magnetic resonance in medicine Vol. 93; no. 4; pp. 1516 - 1534
• Main Authors: Chen, Conan, Barnes, Ryan A., Bangen, Katherine J., Han, Fei, Pfeuffer, Josef, Wong, Eric C., Liu, Thomas T., Bolar, Divya S.
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.04.2025; John Wiley and Sons Inc
• Subjects: Adult; Aged; Algorithms; Blood flow; Blood Flow Velocity - physiology; Brain - blood supply; Brain - diagnostic imaging; Cerebral blood flow; Cerebrovascular Circulation - physiology; Cognitive ability; Data acquisition; Female; Heart; Humans; Image Processing, Computer-Assisted - methods; Imaging Methodology; In vivo methods and tests; Labeling; Magnetic Resonance Angiography - methods; Magnetic Resonance Imaging - methods; Male; microvascular; Microvasculature; Microvessels - diagnostic imaging; Microvessels - physiology; Middle Aged; Pulsatile Flow - physiology; pulsatility; Reproducibility; Reproducibility of Results; Signal-To-Noise Ratio; Spin labeling; Spin Labels; Substantia grisea; Velocity; velocity selective arterial spin labeling; VSASL ASL; Young Adult; microvascular; pulsatility; velocity selective arterial spin labeling; VSASL ASL
• ISSN: 0740-3194; 1522-2594; 1522-2594
• DOI: 10.1002/mrm.30370

Purpose By leveraging the small‐vessel specificity of velocity‐selective arterial spin labeling (VSASL), we present a novel technique for measuring cerebral MicroVascular Pulsatility named MVP‐VSASL. Theory and Methods We present a theoretical model relating the pulsatile, cerebral blood flow‐driven VSASL signal to the microvascular pulsatility index (PI$$ \mathrm{PI} $$), a widely used metric for quantifying cardiac‐dependent fluctuations. The model describes the dependence of the PI$$ \mathrm{PI} $$ of VSASL signal (denoted PIVS$$ {\mathrm{PI}}_{\mathrm{VS}} $$) on bolus duration τ$$ \tau $$ (an adjustable VSASL sequence parameter) and provides guidance for selecting a value of τ$$ \tau $$ that maximizes the SNR of the PIVS$$ {\mathrm{PI}}_{\mathrm{VS}} $$ measurement. The model predictions were assessed in humans using data acquired with retrospectively cardiac‐gated VSASL sequences over a broad range of τ$$ \tau $$ values. In vivo measurements were also used to demonstrate the feasibility of whole‐brain voxel‐wise pulsatility mapping, assess intrasession repeatability of PIVS$$ {\mathrm{PI}}_{\mathrm{VS}} $$, and illustrate the potential of this method to explore an association with age. Results The theoretical model showed excellent agreement to the empirical data in a gray matter region of interest (average R2$$ {\mathrm{R}}^2 $$ value of 0.898 ±$$ \pm $$ 0.107 across six subjects). We further showed excellent intrasession repeatability of the pulsatility measurement (ICC=0.960$$ \mathrm{ICC}=0.960 $$, p<0.001$$ p<0.001 $$) and the potential to characterize associations with age (r=0.554$$ r=0.554 $$, p=0.021$$ p=0.021 $$). Conclusion We have introduced a novel, VSASL‐based cerebral microvascular pulsatility technique, which may facilitate investigation of cognitive disorders where damage to the microvasculature has been implicated.