Association of Left Atrial Local Conduction Velocity With Late Gadolinium Enhancement on Cardiac Magnetic Resonance in Patients With Atrial Fibrillation

Abstract

Background: Prior studies have demonstrated regional left atrial late gadolinium enhancement (LGE) heterogeneity on magnetic resonance imaging. Heterogeneity in regional conduction velocities is a critical substrate for functional reentry. We sought to examine the association between left atrial conduction velocity and LGE in patients with atrial fibrillation.

Methods and results: LGE imaging and left atrial activation mapping were performed during sinus rhythm in 22 patients before pulmonary vein isolation. The locations of 1468 electroanatomic map points were registered to the corresponding anatomic sites on 469 axial LGE image planes. The local conduction velocity at each point was calculated using previously established methods. The myocardial wall thickness and image intensity ratio defined as left atrial myocardial LGE signal intensity divided by the mean left atrial blood pool intensity was calculated for each mapping site. The local conduction velocity and image intensity ratio in the left atrium (mean ± SD) were 0.98 ± 0.46 and 0.95 ± 0.26 m/s, respectively. In multivariable regression analysis, clustered by patient, and adjusting for left atrial wall thickness, conduction velocity was associated with the local image intensity ratio (0.20 m/s decrease in conduction velocity per increase in unit image intensity ratio, P<0.001).

Conclusions: In this clinical in vivo study, we demonstrate that left atrial myocardium with increased gadolinium uptake has lower local conduction velocity. Identification of such regions may facilitate the targeting of the substrate for reentrant arrhythmias.

Keywords: arrhythmias, cardiac; atrial fibrillation; fibrosis; magnetic resonance imaging; regression analysis.

Figure 1

Endocardial and epicardial LA contours and registration of EAM data to LGE-MRI in a representative case. A: The endocardial (red) and epicardial (green) contours were drawn on LGE-MRI axial planes. LA myocardium between the two contours was divided into 20 sectors and the mean pixel intensity and wall thickness of each sector were calculated. B: Location data of EAM (white square dots) were registered to the MRI by using custom software. In this example, EAM points a, b, c, d, e, f, and g correspond to the sectors 6, 7, 7, 8, 8, 9, and 9, respectively. LAA = left atrial appendage, RSPV = right superior pulmonary vein

Figure 1

Endocardial and epicardial LA contours and registration of EAM data to LGE-MRI in a representative case. A: The endocardial (red) and epicardial (green) contours were drawn on LGE-MRI axial planes. LA myocardium between the two contours was divided into 20 sectors and the mean pixel intensity and wall thickness of each sector were calculated. B: Location data of EAM (white square dots) were registered to the MRI by using custom software. In this example, EAM points a, b, c, d, e, f, and g correspond to the sectors 6, 7, 7, 8, 8, 9, and 9, respectively. LAA = left atrial appendage, RSPV = right superior pulmonary vein

Figure 2

Three-dimensional maps in a representative case. The upper and lower panels show the anterior and posterior projections of three-dimensional LA images merged with the data of local activation time, local CV, IIR, and wall thickness, respectively. Left atrial appendage was excluded from the figures.

Figure 3

Forest Plot of Beta Estimates for the Association of IIR with CV – The forest plot summarizes multivariable-adjusted beta estimates for the association of IIR with CV. Models were clustered by patient and adjusted for regional thickness. The association of IIR with CV was accentuated in patients with persistent AF. In contrast, while the direction of association was consistent, the magnitude of association was lower and statistical significance was absent in the subgroup with paroxysmal AF.