A digital twin approach for stroke risk assessment in Atrial Fibrillation Patients.

Atrial fibrillation (AF) is associated with a fivefold increased risk of cerebrovascular events, contributing to 15-18 % of all strokes. Stroke prevention in clinical practice is typically guided by the CHADS-VASc score, which depends on general clinical risk factors but falls short in predicting risk at an individual patient level. In this study, we introduce a digital twin model of the left atrium (LA) combined with computational fluid dynamics (CFD) simulations to enhance personalized stroke risk assessment.

Patient-specific left atrium contraction quantification associated with atrial fibrillation: A region-based approach.

Background And Objectives: Atrial fibrillation (AF) is a widespread cardiac arrhythmia that significantly impacts heart function. AF disrupts atrial mechanical contraction, leading to irregular, uncoordinated, and slow blood flow inside the atria which favors the formation of clots, primarily within the left atrium (LA). A standardized region-based analysis of the LA is missing, and there is not even any consensus about how to define the LA regions.

Preliminary findings on left atrial appendage occlusion simulations applying different endocardial devices.

Atrial fibrillation (AF) is one of the most investigated arrhythmias since it is associated with a five-fold increase in the risk of strokes. Left atrium dilation and unbalanced and irregular contraction caused by AF favour blood stasis and, consequently, stroke risk. The left atrial appendage (LAA) is the site of the highest clots formation, increasing the incidence of stroke in AF population.