Digital twinning of cardiac electrophysiology models from the surface ECG: a geodesic backpropagation approach

The eikonal equation has become an indispensable tool for modeling cardiac electrical activation accurately and efficiently. In principle, by matching clinically recorded and eikonal-based electrocardiograms (ECGs), it is possible to build patient-specific models of cardiac electrophysiology in a purely non-invasive manner. Nonetheless, the fitting procedure remains a challenging task. The present study introduces a novel method, Geodesic-BP, to solve the inverse eikonal problem. Geodesic-BP is well-suited for GPU-accelerated machine learning frameworks, allowing us to optimize the parameters of the eikonal equation to reproduce a given ECG. We show that Geodesic-BP can reconstruct a simulated cardiac activation with high accuracy in a synthetic test case, even in the presence of modeling inaccuracies. Furthermore, we apply our algorithm to a publicly available dataset of a rabbit model, with very positive results. Given the future shift towards personalized medicine, Geodesic-BP has the potential to help in future functionalizations of cardiac models meeting clinical time constraints while maintaining the physiological accuracy of state-of-the-art cardiac models.Comment: 9 pages, 5 figure

Shape of my heart: Cardiac models through learned signed distance functions

The efficient construction of an anatomical model is one of the major challenges of patient-specific in-silico models of the human heart. Current methods frequently rely on linear statistical models, allowing no advanced topological changes, or requiring medical image segmentation followed by a meshing pipeline, which strongly depends on image resolution, quality, and modality. These approaches are therefore limited in their transferability to other imaging domains. In this work, the cardiac shape is reconstructed by means of three-dimensional deep signed distance functions with Lipschitz regularity. For this purpose, the shapes of cardiac MRI reconstructions are learned from public databases to model the spatial relation of multiple chambers in Cartesian space. We demonstrate that this approach is also capable of reconstructing anatomical models from partial data, such as point clouds from a single ventricle, or modalities different from the trained MRI, such as electroanatomical mapping, and in addition, allows us to generate new anatomical shapes by randomly sampling latent vectors

Anatomically-induced Fibrillation in a 3D model of the Human Atria

International audienceAtrial fibrillation (AF) requires both a trigger and a sub-strate that can maintain a complex reentrant activity. In patients and in experimental models this substrate is provided by both electrical and structural remodeling. Since these processes overlap in time it is impossible to assess their individual contributions to AF maintenance experimentally. Therefore we studied the effect of electrical re-modeling alone on AF initiation in a realistic numerical model of the human atria. We attempted to initiate AF by rapid pacing in 10 different locations, both with and without electrical remodeling. The protocols were repeated twice, with small variations in calcium conductivity, so that in total 30 simulations with and 30 simulations without remodeling were performed. In models with electrical remodeling, functional conduction block at structural in-homogeneities induced AF in 27 % of the simulations. In models without electrical remodeling, AF could not be induced. We conclude that in the complex anatomy of the atria electrical remodeling alone increases the probability of AF substantially. This finding supports a mechanism whereby electrical remodeling, which occurs relatively fast, accelerates the slower but irreversible structural remodeling process

Fibrosis explains atrial fibrillation recurrences after pulmonary vein isolations. A simulation study

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Acute Changes in P-Wave Morphology by Pulmonary Vein Isolation in Atrial Fibrillation Patients

International audiencePulmonary vein (PV) plays an important role in atrial fibrillation (AF) initiation, progression, and stability. Successful PV isolation (PVI), either by radiofrequency catheter or Cryoballoon ablation, may terminate AF and prevent its recurrence. Whereas, incomplete PV isolation or reconnection of isolated PVs underlies mechanisms of AF recurrence. Hence, defining parameters able to predict a successful PVI and detect reconnections can assist clinicians in treatment of AF patients. Here, we developed a highly detailed human atrial model to simulate PVI and its acute effect on the P-wave morphology. Afterwards, the simulation results were compared and validated by recorded ECGs from patients before and after PVI procedure. In both simulation data and clinical recordings, we observed morphological changes in P-wave after PVI. More importantly our simulation helped us to find electrode positions in which the differences in P-wave morphology before and after PVI were more pronounced

Left Atrial Appendage Electrical Isolation Reduces Atrial Fibrillation Recurrences: a simulation study

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