ArticleMedical image analysis2018
A work flow to build and validate patient specific left atrium electrophysiology models from catheter measurements.
Article in Medical image analysis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Towards mechanisms-driven strategy for persistent atrial fibrillation ablation: Leveraging digital twins.Journal of precision medicine (Amsterdam, Netherlands) · 2026Article
- Rapid calibration of atrial electrophysiology models using Gaussian process emulators in the ensemble Kalman filter.Scientific reports · 2026Article
- The effect of clinically relevant changes in extracellular electrolyte concentrations on human atrial arrhythmias.Communications medicine · 2025Article
- Impact of effective refractory period personalization on arrhythmia vulnerability in patient-specific atrial computer models.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024Article
- Credibility assessment of in silico clinical trials for medical devices.PLoS computational biology · 2024Review
- [Developments of ex vivo cardiac electrical mapping and intelligent labeling of atrial fibrillation substrates].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024Review
- A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data.Arrhythmia & electrophysiology review · 2024Review
- Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds.Scientific reports · 2022Article
- Credibility assessment of patient-specific computational modeling using patient-specific cardiac modeling as an exemplar.PLoS computational biology · 2022Article
- Computational electrophysiology of the coronary sinus branches based on electro-anatomical mapping for the prediction of the latest activated region.Medical & biological engineering & computing · 2022Article
- Computational models of atrial fibrillation: achievements, challenges, and perspectives for improving clinical care.Cardiovascular research · 2021Review
- Characterizing the arrhythmogenic substrate in personalized models of atrial fibrillation: sensitivity to mesh resolution and pacing protocol in AF models.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2021Article
- A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation.Frontiers in physiology · 2021Article
- Constructing a Human Atrial Fibre Atlas.Annals of biomedical engineering · 2021Article
- CVAR-Seg: An Automated Signal Segmentation Pipeline for Conduction Velocity and Amplitude Restitution.Frontiers in physiology · 2021Article
- Translational applications of computational modelling for patients with cardiac arrhythmias.Heart (British Cardiac Society) · 2020Review
- Calibration of ionic and cellular cardiac electrophysiology models.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Gaussian process manifold interpolation for probabilistic atrial activation maps and uncertain conduction velocity.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020Article
- An audit of uncertainty in multi-scale cardiac electrophysiology models.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020Review
- Creation and application of virtual patient cohorts of heart models.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020Article
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Authors and funding
6 authors.
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Abstract
Biophysical models of the atrium provide a physically constrained framework for describing the current state of an atrium and allow predictions of how that atrium will respond to therapy. We propose a work flow to simulate patient specific electrophysiological heterogeneity from clinical data and validate the resulting biophysical models. In 7 patients, we recorded the atrial anatomy with an electroanatomical mapping system (St Jude Velocity); we then applied an S1-S2 electrical stimulation protocol from the coronary sinus (CS) and the high right atrium (HRA) whilst recording the activation patterns using a PentaRay catheter with 10 bipolar electrodes at 12 ± 2 sites across the atrium. Using only the activation times measured with a PentaRay catheter and caused by a stimulus applied in the CS with a remote catheter we fitted the four parameters for a modified Mitchell-Schaeffer model and the tissue conductivity to the recorded local conduction velocity restitution curve and estimated local effective refractory period. Model parameters were then interpolated across each atrium. The fitted model recapitulated the S1-S2 activation times for CS pacing giving a correlation ranging between 0.81 and 0.98. The model was validated by comparing simulated activations times with the independently recorded HRA pacing S1-S2 activation times, giving a correlation ranging between 0.65 and 0.96. The resulting work flow provides the first validated cohort of models that capture clinically measured patient specific electrophysiological heterogeneity.
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