Year: 2020
Type: article
Abstract: Atrial anisotropy affects electrical propagation patterns, anchor locations of atrial reentrant drivers, and atrial mechanics. However, patient-specific atrial fibre fields and anisotropy measurements are not currently available, and consequently assigning fibre fields to atrial models is challenging. We aimed to construct an atrial fibre atlas from a high-resolution DTMRI dataset that optimally reproduces electrophysiology simulation predictions corresponding to patient-specific fibre fields, and to develop a methodology for automatically assigning fibres to patient-specific anatomies. We extended an atrial coordinate system to map the pulmonary veins, vena cava and appendages to standardised positions in the coordinate system corresponding to the average location across the anatomies. We then expressed each fibre field in this atrial coordinate system and calculated an average fibre field. To assess the effects of fibre field on patient-specific modelling predictions, we calculated paced activation time maps and electrical driver locations during AF. In total, 756 activation time maps were calculated (7 anatomies with 9 fibre maps and 2 pacing locations, for the endocardial, epicardial and bilayer surface models of the LA and RA). Patient-specific fibre fields had a relatively small effect on average paced activation maps (range of mean local activation time difference for LA fields: 2.67-3.60 ms, and for RA fields: 2.29-3.44 ms), but had a larger effect on maximum LAT differences (range for LA 12.7-16.6%; range for RA 11.9-15.0%). A total of 126 phase singularity density maps were calculated (7 anatomies with 9 fibre maps for the LA and RA bilayer models). The fibre field corresponding to anatomy 1 had the highest median PS density map correlation coefficient for LA bilayer simulations (0.44 compared to the other correlations, ranging from 0.14 to 0.39), while the average fibre field had the highest correlation for the RA bilayer simulations (0.61 compared to the other correlations, ranging from 0.37 to 0.56). For sinus rhythm simulations, average activation time is robust to fibre field direction; however, maximum differences can still be significant. Patient specific fibres are more important for arrhythmia simulations, particularly in the left atrium. We propose using the fibre field corresponding to DTMRI dataset 1 for LA simulations, and the average fibre field for RA simulations as these optimally predicted arrhythmia properties.
Source: Annals of Biomedical Engineering
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,860
Funders: American Heart Association, Wellcome Trust, National Institute for Health and Care Research, British Heart Foundation, Agence Nationale de la Recherche, Fondation Leducq, King's Health Partners, Medical Research Council, Engineering and Physical Sciences Research Council, Centre For Medical Engineering, King’s College London, National Heart, Lung, and Blood Institute
Awards: G1054121244, G1190480411, G1247657515, G1251496372, G1271318647, G133457142, Personalised Model Based Optimal Lead Guidance in Cardiac Resynchronisation Therapy, G2417159676, G2607942624, Uncertainty Quantification in Prospective and Predictive Patient Specific Cardiac Models, Predicting Atrial Fibrillation Mechanisms Through Deep Learning, G3273634535, G3773670102, G3780594362, G49213722, L'Institut de Rythmologie et modélisation Cardiaque, G5296857752, G5893523844, G597271902, G6562481342, The role of scar morphology and location in arrhythmogenic risk following cardiac resynchronisation therapy in patients with ischaemic heart disease, G7240651115, The interdependence of anatomy and function in atrial fibrillation, Simulation Guidance of Ablation Therapy for Persistent Atrial Fibrillation, High-resolution imaging and modeling approaches to study infarct-related arrhythmias, G7650934720, Repolarization HeterogeneitY imaging for personalised Therapy of Heart ArrhythMia, G8303168876, G8775246936, G938335843, G961285871
OpenAlex ID: W3032510290