# Alteration of cerebrovascular haemodynamic patterns due to atrial fibrillation: an in silico investigation

## TL;DR

This study uses in silico models to investigate how atrial fibrillation alters cerebrovascular haemodynamics, revealing significant changes in pressure and flow patterns that could link AF to dementia risk.

## Contribution

It introduces a novel computational approach combining cardiovascular and cerebral circulation models to analyze AF's impact on brain haemodynamics.

## Key findings

- Reduced signal correlation in cerebral blood flow during AF
- Increased probability of extreme haemodynamic events in AF
- Altered pressure and flow patterns in microcirculation during AF

## Abstract

There has recently been growing evidence that atrial fibrillation (AF), the most common cardiac arrhythmia, is independently associated with the risk of dementia. This represents a very recent frontier with high social impact for the number of individuals involved and for the expected increase in AF incidence in the next 40 years. Although a number of potential haemodynamic processes, such as microembolisms, altered cerebral blood flow, hypoperfusion and microbleeds, arise as connecting links between the two pathologies, the causal mechanisms are far from clear. An in silico approach is proposed that combines in sequence two lumped-parameter schemes, for the cardiovascular system and the cerebral circulation. The systemic arterial pressure is obtained from the cardiovascular system and used as the input for the cerebral circulation, with the aim of studying the role of AF on the cerebral haemodynamics with respect to normal sinus rhythm (NSR), over a 5000 beat recording. In particular, the alteration of the haemodynamic (pressure and flowrate) patterns in the microcirculation during AF is analysed by means of different statistical tools, from correlation coefficients to autocorrelation functions, crossing times, extreme values analysis and multivariate linear regression models. A remarkable signal alteration, such as a reduction in signal correlation (NSR, about 3 s; AF, less than 1 s) and increased probability (up to three to four times higher in AF than in NSR) of extreme value events, emerges for the peripheral brain circulation. The described scenario offers a number of plausible cause-effect mechanisms that might explain the occurrence of critical events and the haemodynamic links relating to AF and dementia.