Detection and characterization of physiological network interactions in pulsatile motion of cranial blood vessels using real-time MRI.

Abstract

We present a robust method to assess pulsatile motion of larger cranial blood vessels in the human brain from high spatiotemporal-resolution real-time magnetic resonance (MR) imaging data. Together with percentile-based thresholding in combination with a border-detection algorithm and other empirical selection criteria, we are able to extract area time series from the pulsatile motion of blood vessels. In a proof of concept, we apply our method to the left and right vertebral arteries in a cohort of healthy subjects and extract heart and breathing rates from their pulsatile motion. Comparison to mean physiological reference values measured simultaneously with a photoplethysmogram and a breathing belt shows no differences within the scope of the measurement accuracy. Intra-subject differences for breathing rates detected in the left and right vertebral artery are high but not significant. Our findings suggest that the proposed method is suitable for assessing arterial pulsations in larger cranial vessels driven by heart or breathing rates, as part of the complex physiological network of heart-brain interactions.