Literature DB >> 31982580

Cardiac and respiration-induced brain deformations in humans quantified with high-field MRI.

Jacob Jan Sloots1, Geert Jan Biessels2, Jaco J M Zwanenburg3.   

Abstract

Microvascular blood volume pulsations due to the cardiac and respiratory cycles induce brain tissue deformation and, as such, are considered to drive the brain's waste clearance system. We have developed a high-field magnetic resonance imaging (MRI) technique to quantify both cardiac and respiration-induced tissue deformations, which could not be assessed noninvasively before. The technique acquires motion encoded snapshot images in which various forms of motion and confounders are entangled. First, we optimized the motion sensitivity for application in the human brain. Next, we isolated the heartbeat and respiration-related deformations, by introducing a linear model that fits the snapshot series to the recorded physiological information. As a result, we obtained maps of the physiological tissue deformation with 3mm isotropic spatial resolution. Heartbeat and respiration-induced volumetric strain were significantly different from zero in the basal ganglia (median (25-75% interquartile range): 0.85·10-3 (0.39·10-3-1.05·10-3), p ​= ​0.0008 and -0.28·10-3 (-0.41·10-3-0.06·10-3), p ​= ​0.047, respectively. Smaller volumetric strains were observed in the white matter of the centrum semi ovale (0.28·10-3 (0-0.59·10-3) and -0.06·10-3 (-0.17·10-3-0.20·10-3)), which was only significant for the heartbeat (p ​= ​0.02 and p ​= ​0.7, respectively). Furthermore, heartbeat-induced volumetric strain was about three times larger than respiration-induced volumetric strain. This technique opens a window on the driving forces of the human brain clearance system.
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Brain; Deformation; Magnetic resonance imaging; Microvasculature; Single-shot DENSE; Small vessel disease; Tissue strain; Waste clearance

Mesh:

Year:  2020        PMID: 31982580     DOI: 10.1016/j.neuroimage.2020.116581

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   7.400


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