Objectives: To visualize and quantify physiological blood flow of intracranial veins in vivo using time-resolved, 3D phase-contrast MRI (4D flow MRI), and to test measurement accuracy.
Methods: Fifteen healthy volunteers underwent repeated ECG-triggered 4D flow MRI (3 Tesla, 32-channel head coil). Intracranial venous blood flow was analysed using dedicated software allowing for blood flow visualization and quantification in analysis planes at the superior sagittal, straight, and transverse sinuses. MRI was evaluated for intra- and inter-observer agreement and scan-rescan reproducibility. Measurements of the transverse sinuses were compared with transcranial two-dimensional duplex ultrasound.
Results: Visualization of 3D blood flow within cerebral sinuses was feasible in 100 % and within at least one deep cerebral vein in 87 % of the volunteers. Blood flow velocity/volume increased along the superior sagittal sinus and was lower in the left compared to the right transverse sinus. Intra- and inter-observer reliability and reproducibility of blood flow velocity (mean difference 0.01/0.02/0.02 m/s) and volume (mean difference 0.0002/-0.0003/0.00003 l/s) were good to excellent. High/low velocities were more pronounced (8 % overestimation/9 % underestimation) in MRI compared to ultrasound.
Conclusions: Four-dimensional flow MRI reliably visualizes and quantifies three-dimensional cerebral venous blood flow in vivo and is promising for studies in patients with sinus thrombosis and related diseases.
Key Points: • 4D flow MRI can be used to visualize and quantify physiological cerebral venous haemodynamics • Flow quantification within cerebral sinuses reveals high reliability and accuracy of 4D flow MRI • Blood flow volume and velocity increase along the superior sagittal sinus • Limited spatial resolution currently precludes flow quantification in small cerebral veins.
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College of Marine Life Sciences, Ocean University of China, No. 5 Yushan Road, Qingdao 266003, China. Electronic address:
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Yale Cardiovascular Research Center, Yale School of Medicine, New Haven, CT 06511, USA.
Fluid shear stress (FSS) from blood flow sensed by vascular endothelial cells (ECs) determines vessel behavior, but regulatory mechanisms are only partially understood. We used cell state transition assessment and regulation (cSTAR), a powerful computational method, to elucidate EC transcriptomic states under low shear stress (LSS), physiological shear stress (PSS), high shear stress (HSS), and oscillatory shear stress (OSS) that induce vessel inward remodeling, stabilization, outward remodeling, or disease susceptibility, respectively. Combined with a publicly available database on EC transcriptomic responses to drug treatments, this approach inferred a regulatory network controlling EC states and made several notable predictions.
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