AUTHOR=Sanatkhani Soroosh , Nedios Sotirios , Menon Prahlad G. , Saba Samir F. , Jain Sandeep K. , Federspiel William J. , Shroff Sanjeev G. 

TITLE=Subject-specific factors affecting particle residence time distribution of left atrial appendage in atrial fibrillation: A computational model-based study

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=10

YEAR=2023

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2023.1070498

DOI=10.3389/fcvm.2023.1070498

ISSN=2297-055X

ABSTRACT=<sec><title>Background</title><p>Atrial fibrillation (AF) is a prevalent arrhythmia, that causes thrombus formation, ordinarily in the left atrial appendage (LAA). The conventional metric of stroke risk stratification, CHA<sub>2</sub>DS<sub>2</sub>-VASc score, does not account for LAA morphology or hemodynamics. We showed in our previous study that residence time distribution (RTD) of blood-borne particles in the LAA and its associated calculated variables (i.e., mean residence time, <italic>t<sub>m</sub></italic>, and asymptotic concentration, <italic>C</italic><sub>∞</sub>) have the potential to improve CHA<sub>2</sub>DS<sub>2</sub>-VASc score. The purpose of this research was to investigate the effects of the following potential confounding factors on LAA <italic>t<sub>m</sub></italic> and <italic>C</italic><sub>∞</sub>: (1) pulmonary vein flow waveform pulsatility, (2) non-Newtonian blood rheology and hematocrit level, and (3) length of the simulation.</p></sec><sec><title>Methods</title><p>Subject-Specific data including left atrial (LA) and LAA cardiac computed tomography, cardiac output (CO), heart rate, and hematocrit level were gathered from 25 AF subjects. We calculated LAA <italic>t<sub>m</sub></italic> and <italic>C</italic><sub>∞</sub> based on series of computational fluid dynamics (CFD) analyses.</p></sec><sec><title>Results</title><p>Both LAA <italic>t<sub>m</sub></italic> and <italic>C</italic><sub>∞</sub> are significantly affected by the CO, but not by temporal pattern of the inlet flow. Both LAA <italic>t<sub>m</sub></italic> and <italic>C</italic><sub>∞</sub> increase with increasing hematocrit level and both calculated indices are higher for non-Newtonian blood rheology for a given hematocrit level. Further, at least 20,000 s of CFD simulation is needed to calculate LAA <italic>t<sub>m</sub></italic> and <italic>C</italic><sub>∞</sub> values reliably.</p></sec><sec><title>Conclusions</title><p>Subject-specific LA and LAA geometries, CO, and hematocrit level are essential to quantify the subject-specific proclivity of blood cell tarrying inside LAA in terms of the RTD function.</p></sec>