1
Patient-Specific Heart Model Towards Atrial
Fibrillation
Jiyue He, Arkady Pertsov, Sanjay Dixit, Katie Walsh, Eric Toolan, Rahul Mangharam
Abstract—Atrial fibrillation is a heart rhythm disorder that
affects tens of millions people worldwide. The most effective
treatment is catheter ablation. This involves irreversible heat-
ing of abnormal cardiac tissue facilitated by electroanatomical
mapping. However, it is difficult to consistently identify the
triggers and sources that may initiate or perpetuate atrial
fibrillation due to its chaotic behavior. We developed a patient-
specific computational heart model that can accurately reproduce
the activation patterns to help in localizing these triggers and
sources. Our model has high spatial resolution, with whole-
atrium temporal synchronous activity, and has patient-specific
accurate electrophysiological activation patterns. A total of 15
patients data were processed: 8 in sinus rhythm, 6 in atrial
flutter and 1 in atrial tachycardia. For resolution, the average
simulation geometry voxel is a cube of 2.47 mm length. For
synchrony, the model takes in about 1,500 local electrogram
recordings, optimally fits parameters to the individual’s atrium
geometry and then generates whole-atrium activation patterns.
For accuracy, the average local activation time error is 5.47 ms
for sinus rhythm, 10.97 ms for flutter and tachycardia; and the
average correlation is 0.95 for sinus rhythm, 0.81 for flutter and
tachycardia. This promising result demonstrates our model is
an effective building block in capturing more complex rhythms
such as atrial fibrillation to guide physicians for effective ablation
therapy.
Index Terms—medical cyber-physical systems, patient-specific,
computational heart model, cardiac electrophysiology modeling,
electroanatomical mapping, Mitchell-Schaeffer model
I. INTRODUCTION
Atrial Fibrillation (AF) is a heart rhythm disorder where
the normal beating in the two atria is irregular, and blood
does not flow well to the ventricles. While the underlying
mechanism of AF is not clearly understood, it largely is due
to the spatial variation in the conduction properties of the atrial
myocardium. This causes the single wavefront propagating
across the atria to being split into multiple wavefronts resulting
in chaotic depolarization of the heart tissue and irregularly fast
rhythm. AF increases the risk of stroke and heart failure. If
left untreated, it will become worse [1].
One of the most effective treatments for AF is catheter
ablation. This involves irreversible radiofrequency heating of
the sources that initiate or perpetuate AF. The common current
ablation protocol involves standard lesion locations for all
patients. For example, in the Pulmonary Vein Isolation (PVI)
Jiyue He, Rahul Mangharam: Department of Electrical and Sys-
tems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
jiyuehe@seas.upenn.edu. Arkady Pertsov: Department of Pharmacology, Up-
state Medical University, Syracuse, USA. Sanjay Dixit, Katie Walsh: Depart-
ment of Cardiac Electrophysiology, Hospital of the University of Pennsylva-
nia, Philadelphia, PA, USA. Eric Toolan: Biosense Webster, Lansdowne, PA,
USA. May 19, 2021.
approach, ablation lesions encircle the pulmonary veins to
prevent abnormal activations originated in the veins travel into
the atria.
Another common protocol involves PVI with additional ab-
lation of non-pulmonary vein triggers and putative arrhythmia
substrate [2]. While paroxysmal-AF (i.e. spontaneous onset
and termination) can be eliminated in 70-75% of patients with
a single ablation procedure, persistent-AF can be eliminated
in only about 50% of patients with a single procedure [3].
The reason is there are triggers other than pulmonary veins
that cause fibrillation for the persistent-AF. Electroanatomical
mapping captures the heart geometry and tissue conductivity
which are essential in identifying those trigger [4].
The central challenge is to capture high-resolution synchro-
nized electrograms across the entire atrium and analyze these
data to identify potential triggers as ablation candidates to ter-
minate AF. We developed a high spatial resolution, temporally
synchronous and patient-specific atrium model which captures
electrophysiologic and anatomic parameters unique to each
patient.
Figure 1 shows the overall process of constructing the
heart model. First, a high resolution electroanatomical map
is exported from the Carto3 System, which contains atrium
3D triangular mesh, electrograms, and electrode locations.
The mesh is processed to remove geometry defects, such as
deep concave holes, intersecting triangular faces, and non-
referenced vertices. The mitral valve and 4 pulmonary veins
are cut out. Then a 3D Cartesian grid is generated and wrapped
around the mesh for computing simulation. Then, these are put
into the electrophysiological heart model, and patient-specific
parameters are fitted via an optimization process. As a result
of fitting parameters at every locations on the mesh, the heart
model becomes whole-atrium synchronous. Lastly, the heart
model is validated over 15 patients data by comparing Local
Activation Time (LAT) between patient data and simulation
data.
This model demonstrates the ability to accurately produce
the activation patterns for an individual patient that can better
identify AF sources.
II. RELATED WORK
Several research groups had developed patient specific high
resolution computational heart models [5]. Cabrera-Lozoya et
al developed a model constructed from 3D Delayed-Enhanced
Magnetic Resonance Imaging (DE-MRI) to simulate patient-
specific post-infarction Ventricular Tachycardia (VT) abnor-
mal electrograms. From DE-MRI data, they segmented the
arXiv:2210.12825v1 [physics.med-ph] 23 Oct 2022