Shear wave velocity exhibits significant beat-to-beat variability in atrial fibrillation
Authors: Salerno N , Papangelopoulou K , Caenen A , Orlowska M , Youssef A , Wouters L , D'hooge J , Voigt J U 
Published: January 2025

Abstract

Background
Shear wave elastography (SWE), by measuring the propagation velocity of naturally occurring myocardial shear waves after mitral valve closure (MVC), provides real-time insights into myocardial stiffness. Previous studies have focused solely on patients with regular heart rhythm and investigated the impact of steady state loading conditions on shear wave velocities (SWV). However, the effect of beat-to-beat variations in loading due to changes in cardiac cycle length (CL) remains unknown.

Purpose
To investigate if SWV are influenced by beat-to-beat changes in cardiac CL.

Methods
30 consecutive patients were included: 20 with persistent/permanent atrial fibrillation (Afib) and 10 in sinus rhythm (SR). Conventional transthoracic echocardiographic images and high frame rate images (1133±90 fps) were obtained. For SWE, 5-10 consecutive cardiac cycles were recorded from parasternal long axis views. Offline analysis of SWV after MVC was performed by drawing an M-mode line along the interventricular septum and semi-automatically measuring the spatiotemporal slope of the wavefront on the M-mode displays, which were color coded for tissue acceleration (Figure A). Beat-to-beat relative variability in SWV and CL was assessed as: (highest value–lowest value)/highest valuex100%. Percentage variation from the mean value per patient was calculated as: (measured value-mean value)/mean valuex100%. The SWV variability index was calculated by normalizing the SWV measured after the longest cardiac cycle (SWVmaxRR) to the SWV measured after the shortest cardiac cycle (SWVminRR) using the formula: (SWVmaxRR- SWVminRR)/SWVmaxRRx100%. Multiple linear regression identified variables associated with the SWV variability index.

Results
Patients with Afib were older (72±8 years vs. 58±9 years, p&lt;0.001), with a larger left atrial volume index (LAVi) and a lower ejection fraction (EF). Significant differences were observed between patients with and without Afib in CL relative variability (43.0±10.5% vs. 4.2±3.3%, p&lt;0.0001; Figure B) and SWV relative variability (41.8±13.9% vs. 20.2±8.4%, p&lt;0.0001; Figure C). There was a moderate correlation between SWV and CL when normalized to the mean value per patient (r=0.5026, p&lt;0.0001; Figure D). Univariate linear regression analysis showed that age (p=0.001), EF (p=0.03), LAVi (p=0.03), and CL relative variability (p&lt;0.001) were significantly associated with the SWV variability index. In the multivariate model, only CL relative variability remained significantly associated with the SWV variability index (β=0.42; p&lt;0.001).

Conclusions
Afib leads to greater beat-to-beat variability in SWV measurements compared to SR, with moderate positive correlation between SWV and CL. We hypothesize that a longer filling time leads to increased preload, which is then reflected in higher end-diastolic stiffness of the myocardium. Invasive studies would be desirable to investigate this phenomenon further.