Abstract

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union's Horizon 2020 research and innovation program under the ERA-NET co-fund action No. 680969 with ANR (ERA-CVD SICVALVES) and Agence Nationale de la Recherche Background Extracellular volume (ECV) determined by magnetic resonance imaging (MRI) is considered a marker of myocardial fibrosis and a predictor of mortality. In addition to diffuse fibrosis, aortic stenosis (AS) patients present increased ECV. However, the impact of regional ECV differences on ventricular conduction in AS patients has not been assessed. Purpose To investigate regional ECV differences in AS patients and to determine their impact on ventricular conduction. Methods MRI was performed in 22 AS patients (11 males, 11 females) before and 3 months after aortic valve replacement (AVR). Regional differences in ECV were determined between mid-ventricular and basal planes. To investigate the impact of these differences on conduction, a computational model of ventricular tissue (9x1x1 cm) was developed with human fiber orientation and transmural/apicobasal electrophysiology. The model was divided in two regions (Fig 1A), each representing tissue with different ECV. Extracellular conductivities (GE) in each region were adjusted to the patient with the highest difference in ECV between the planes (male 75y, post-AVR, ECV mid 25.5%, ECV base 31.3%) so that GE was 26.4% less for ECV of 31.3% compared to 25.5%. A model with uniform ECV of 25.5% was used as a control. The models were paced from the apical face with a S1-S2 protocol (S1: 750 ms, n=10, S2: 700-350 ms, n=1). To compare the results to conduction slowing from diffuse myocardial fibrosis, the simulations were repeated with an additional GE reduction by 40% in both regions to mimic conduction delays observed in fibrotic hearts. Ventricular conduction was compared between the models by analyzing conduction velocity (CV) measured between two points at the endocardium (Fig 1A, blue dots) and the occurrence of abnormalities in the form of non-uniform conduction, and/or conduction block after S2 (Fig 1B). Results Significantly higher ECV was found in the basal plane of AS patients when compared to the mid-ventricular plane before and after AVR (Fig 2), with the largest ECV found after AVR (mid-ventricular: p=0.0021; basal: p=0.0048). No sex-specific differences were found. The model representing the patient with the largest regional ECV difference showed slightly lower CV than the model with uniform ECV (92.9 vs. 96.0 cm/s, S2=500 ms). By contrast, myocardial fibrosis had a larger impact on CV slowing (92.9 vs. 79.2 cm/s, S2=500 ms, patient model, Fig 1C). Conduction block and non-uniform conduction occurred at comparable cycle lengths for all models (Fig 1D). Conclusion Regional differences in ECV were found in the ventricles of AS patients, but computer simulations suggest that these differences have a minimal effect on ventricular conduction when compared to diffuse fibrosis. Although the results suggest a limited electrophysiological relevance, additional studies are necessary to investigate whether these ECV differences have a more significant impact on cardiac mechanics.

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