Abstract
Atrial fibrillation (AF) is the most common arrhythmia that leads to thrombus formation, mostly in the left atrial appendage (LAA). The current standard of stratifying stroke risk, based on the CHA2DS2-VASc score, does not consider LAA morphology, and the clinically accepted LAA morphology-based classification is highly subjective. The aim of this study was to determine whether LAA blood-borne particle residence time distribution and the proposed quantitative index of LAA 3D geometry can add independent information to the CHA2DS2-VASc score. Data were collected from 16 AF subjects. Subject-specific measurements included left atrial (LA) and LAA 3D geometry obtained by cardiac computed tomography, cardiac output, and heart rate. We quantified 3D LAA appearance in terms of a novel LAA appearance complexity index (LAA-ACI). We employed computational fluid dynamics analysis and a systems-based approach to quantify residence time distribution and associated calculated variable (LAA mean residence time, tm) in each subject. The LAA-ACI captured the subject-specific LAA 3D geometry in terms of a single number. LAA tm varied significantly within a given LAA morphology as defined by the current subjective method and it was not simply a reflection of LAA geometry/appearance. In addition, LAA-ACI and LAA tm varied significantly for a given CHA2DS2-VASc score, indicating that these two indices of stasis are not simply a reflection of the subjects' clinical status. We conclude that LAA-ACI and LAA tm add independent information to the CHA2DS2-VASc score about stasis risk and thereby can potentially enhance its ability to stratify stroke risk in AF patients.
Highlights
Atrial fibrillation (AF) is the most common arrhythmia, affecting three to six million US patients a year
We have presented a novel index for quantifying the left atrial appendage (LAA) geometry (LAA-appearance complexity index (ACI)) and an approach for quantifying LAA residence time distribution and associated calculated variables using the subject-specific morphology, cardiac output, and heart rate with a hemodynamic model
Both the appearance index (i.e., left atrial appendage (LAA)-appearance complexity index (ACI)) and the hemodynamics-based index (i.e., LAA tm) add independent information to the CHA2DS2VASc score about subject-specific stasis risk and thereby can potentially enhance its ability to stratify stroke risk in Atrial fibrillation (AF) patients
Summary
Atrial fibrillation (AF) is the most common arrhythmia, affecting three to six million US patients a year. This number is rapidly increasing with 12.1 million AF patients expected by 2030 (Virani et al, 2020). LAA Residence Time in AF (Reddy et al, 2013) These thrombi are known to cause stroke in AF patients. The CHA2DS2-VASc score is the most commonly used index for making clinical decisions regarding the management of AF patients. While this index is based on clinical data, it does not incorporate the role of LA–LAA geometry or local hemodynamics in the thromboembolic risk assessment
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