Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation

Abstract

Background Atrial fibrillation (AF) has been linked to left atrial (LA) enlargement. Whereas most studies focused on 2D-based estimation of static LA volume (LAV), we used a fully-automatic convolutional neural network (CNN) for time-resolved (CINE) volumetry of the whole LA on cardiac MRI (cMRI). Aim was to investigate associations between functional parameters from fully-automated, 3D-based analysis of the LA and current classification schemes in AF. Methods We retrospectively analyzed consecutive AF patients who underwent cMRI on 1.5T systems including a stack of oblique-axial CINE series covering the whole LA. The LA was automatically segmented by a validated CNN. In the resulting volume-time curves, maximum, minimum and LAV before atrial contraction were automatically identified. Active, passive and total LA emptying fractions (LAEF) were calculated and compared to clinical classifications (AF Burden score (AFBS), increased stroke risk (CHA2DS2VASc≥2), AF type (paroxysmal/persistent), EHRA score, and AF risk factors). Moreover, multivariable linear regression models (mLRM) were used to identify associations with AF risk factors. Results Overall, 102 patients (age 61±9 years, 17% female) were analyzed. Active LAEF (LAEF_active) decreased significantly with an increase of AFBS (minimal: 44.0%, mild: 36.2%, moderate: 31.7%, severe: 20.8%, p<0.003) which was primarily caused by an increase of minimum LAV. Likewise, LAEF_active was lower in patients with increased stroke risk (30.7% vs. 38.9%, p = 0.002). AF type and EHRA score did not show significant differences between groups. In mLRM, a decrease of LAEF_active was associated with higher age (per year: -0.3%, p = 0.02), higher AFBS (per category: -4.2%, p<0.03) and heart failure (-12.1%, p<0.04). Conclusions Fully-automatic morphometry of the whole LA derived from cMRI showed significant relationships between LAEF_active with increased stroke risk and severity of AFBS. Furthermore, higher age, higher AFBS and presence of heart failure were independent predictors of reduced LAEF_active, indicating its potential usefulness as an imaging biomarker.

Left atrial substrate characterization based on bipolar voltage electrograms acquired with multipolar, focal and mini-electrode catheters– the CHAZE-Substrate study

“…1 This substrate for AF initiation and perpetuation can be quantified using anatomical (echocardiographic, e.g. indexed left atrial (LA) volume (LAVI)), functional, 2 structural (LGE MRI) or electrocardiographic measurement techniques for pre-procedural characterization. In order to demarcate diseased from healthy myocardium, invasive electrocardiographic measurements during the procedure are commonly performed using local bipolar voltage measurement from the electrodes of the catheters.…”

Atrial substrate characterization based on bipolar voltage electrograms acquired with multipolar, focal and mini-electrode catheters

“…Atrial fibrillation (AF) is associated with remodeling of the atrial myocardium. 1 This substrate for AF initiation and perpetuation can be quantified using anatomical, 2 functional, 3 structural, 4 or electrocardiographic measurement techniques 5 for pre-procedural characterization. In order to demarcate diseased from healthy myocardium, invasive electrocardiographic measurements during the procedure are commonly performed using local bipolar voltage (BV) measurement from the electrodes of the catheters.…”