Why the study?
Device-related thrombosis occurs in up to 4% of patients undergoing LAAO and carries substantial morbidity and mortality, but its pathophysiology and predictors remain unclear.
Do flow dynamic parameters (TAWSS, OSI, ECAP) correlate with device-related thrombosis in patients undergoing left atrial appendage occlusion?
Do flow dynamic parameters (TAWSS, OSI, ECAP) correlate with device-related thrombosis in patients undergoing left atrial appendage occlusion?
Computational fluid dynamic parameters, specifically lower time-averaged wall shear stress, higher oscillatory shear index, and higher endothelial cell activation potential, are significantly associated with device-related thrombosis after left atrial appendage occlusion.
May support flow simulations for post-LAAO thrombosis risk; hypothesis-generating and requires prospective validation.
Background: Device-related thrombosis (DRT) occurs in up to 4% of patients undergoing left atrial appendage occlusion (LAAO) and is associated with substantial morbidity and mortality. However, its pathophysiology, predictors, and optimal management remain unclear. Objectives: This study aims to assess flow dynamic factors correlating to DRT. Methods: A multicenter registry of patients who underwent LAAO and had pre- and post-computed tomography imaging was used. Patient-specific 3-dimensional digital models of the left atrium were created, and finite element simulations were performed to implant an LAAO device into each model in a position that matched the clinical deployment. Computational fluid dynamic simulations were performed to quantify the following flow dynamic parameters: time averaged wall shear stress, oscillatory shear index, and endothelial cell activation potential. Results: < 0.001 for all). Thrombus locations identified from in-vivo images correlated well with the flow dynamic parameters tested. Conclusions: Flow dynamic parameters may be able to predict the risk of DRT after LAAO. Further investigation with a larger patient cohort and long-term follow-up is needed to assess the role of computational fluid dynamics in the risk stratification of patients considered for LAAO.
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Vogl et al. (2024) studied this question.
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