A new computational model for quantifying blood flow dynamics across myogenically-active cerebral arterial networks
Alberto Coccarelli, Ioannis Polydoros, Alex Drysdale, Osama F. Harraz,, and Chennakesava Kadapa

TL;DR
This paper introduces a novel computational model to analyze blood flow regulation in cerebral arteries, accounting for vessel mechanics and pressure responses, aiding understanding of cerebral autoregulation mechanisms.
Contribution
The work presents a new coupled computational framework for simulating blood flow and vessel mechanics in cerebral arteries, with analysis of coupling strategies and pressure response effects.
Findings
Weak coupling provides accurate results with lower computational cost.
The model effectively captures pressure redistribution in vascular networks.
The framework can simulate responses to upstream pressure surges.
Abstract
Cerebral autoregulation plays a key physiological role by limiting blood flow changes in the face of pressure fluctuations. Although the involved cellular processes are mechanically driven, the quantification of haemodynamic forces in in-vivo settings remains extremely difficult and uncertain. In this work, we propose a novel computational framework for evaluating the blood flow dynamics across networks of myogenically active cerebral arteries, which can modulate their muscular tone to stabilize flow (and perfusion pressure) as well as to limit vascular intramural stress. The introduced framework is built on contractile (myogenically active) vascular wall mechanics and blood flow dynamics models, which can be numerically coupled in either a weak or strong way. We investigate the time dependency of the vascular wall response to pressure changes at both single vessel and network levels.…
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Taxonomy
TopicsTraumatic Brain Injury and Neurovascular Disturbances · Optical Imaging and Spectroscopy Techniques · Cerebrospinal fluid and hydrocephalus
