Abstract 14676: Landmark-based Functional Computed Tomography Reveals Diminished Left Atrial Appendage Contraction During Atrial Fibrillation

Abstract

Introduction: The formation of thrombus in the left atrial appendage (LAA) and risk for systemic embolization may result in part from stasis and poor blood volume emptying during atrial fibrillation (AF). Functional 4-dimensional computed tomography (4DCT) is a promising technique to measure LAA ejection fraction and blood volume emptying. Hypothesis: We hypothesize that the LAA ejection fraction measured by 4DCT is decreased during AF compared to sinus rhythm. Methods: 256-slice 4DCT scans obtained in patients for coronary artery imaging or pre-procedurally for AF, VT or SVT ablation procedures were analyzed retrospectively. In each patient, LAA volumes were measured at multiple phases during one cardiac cycle using segmentation software (ITK-SNAP and Osirix MD). LAA ejection fraction was calculated as the difference between minimum and maximum volumes and was analyzed using Wilcoxon rank sum. Results: Out of 54 patients, 37 patients were in sinus rhythm and 17 patients were in AF. Between NSR vs. AF, mean age was 69.1±12.8 vs 73.2±11.5 years (p=0.13), 28% vs 36% female (p=0.54), LVEF was 58±11% vs 60±9% (p=0.95), and echo-derived left atrial volume index was 29.5±6.1 ml/m2 vs 41.7±12.8 ml/m2 (p=0.06). Patients who were in sinus rhythm during their CT scan had a higher LAA ejection fraction than those who were in AF (58±13% vs. 29±9%, p<0.0001). For patients who were in AF during their CT scan, there was no difference in LAA ejection fraction between patients with a history of paroxysmal AF compared to patients with a history of persistent AF (30±10% vs. 28±10%, p=0.75). Conclusions: Analysis of the LAA volumes using functional cardiac CT is a feasible method to quantify blood volume emptying from the LAA. Patients in AF were observed to have significantly decreased LAA ejection fraction and blood volume emptying compared to patients in sinus rhythm. Further studies are needed to determine whether this technique may improve personalized risk stratification for stroke.