Computational localization of fibrillation sources
A system for computational localization of fibrillation sources is provided. In some implementations, the system performs operations comprising generating a representation of electrical activation of a patient's heart and comparing, based on correlation, the generated representation against one or more stored representations of hearts to identify at least one matched representation of a heart. The operations can further comprise generating, based on the at least one matched representation, a computational model for the patient's heart, wherein the computational model includes an illustration of one or more fibrillation sources in the patient's heart. Additionally, the operations can comprise displaying, via a user interface, at least a portion of the computational model. Related systems, methods, and articles of manufacture are also described.
1 . One or more computing systems comprising:
one or more computer-readable storage mediums that store computer-executable instructions for controlling the one or more computing systems to:
access a patient representation of electrical activation of a patient's heart;
access a library of stored representations of electrical activation of hearts that are each associated with a source location of an arrhythmia, the stored representations of electrical activation are derived from simulated electrical activations of computational models, the computational models representing a plurality of cardiac geometries, electrophysiological characteristics, and source locations, the computational models being not specific to the patient;
identify from the library a stored representation of electrical activation based on similarity to the patient representation of electrical activation; and
output an indication of the source location of the arrhythmia associated with the identified stored representation of electrical activation; and
one or more processors for controlling the one or more computing systems to execute one or more of the computer-executable instructions.
2 . The one or more computing systems of claim 1 wherein the arrhythmia is an atrial fibrillation or a ventricular fibrillation.
3 . The one or more computing systems of claim 1 wherein the patient representation of electrical activation and the stored representations of electrical activation are an electrocardiogram or a vectorcardiogram.
4 . The one or more computing systems of claim 1 wherein a computational model includes a mapping of electrical activation of a heart.
5 . The one or more computing systems of claim 1 wherein a computational model includes a three-dimensional mesh in the shape of a heart.
6 . One or more computing systems comprising:
one or more computer-readable storage mediums that store computer-executable instructions for controlling the one or more computing systems to:
access a patient representation of electrical activation of a patient's heart;
access a library of stored representations of electrical activation of hearts that are each associated with a source location of an arrhythmia, the stored representations of electrical activation are derived from simulated electrical activations of computational models;
identify from the library a stored representation of electrical activation based on similarity to the patient representation of electrical activation; and
output an indication of the source location of the arrhythmia associated with the identified stored representation of electrical activation;
wherein a first computational model includes one or more source locations and wherein the instructions further generate, based on that computational model, a second computational model with one or more of the source locations removed; and
one or more processors for controlling the one or more computing systems to execute one or more of the computer-executable instructions.
7 . The one or more computing systems of claim 6 wherein the instructions further determine a change in the arrhythmia between the first computational model and the second computational model.
8 . The one or more computing systems of claim 1 wherein the instructions further display a representation of a heart with the source location indicated.
9 . The one or more computing systems of claim 1 wherein the identification is based on a correlation factor between patient representation of electrical activation and the stored representation of electrical activation.
10 . A method comprising:
under control of one or more computing systems:
accessing a patient representation of electrical activation of the heart of a patient;
identifying a source location of an arrhythmia of the patient based on the patient representation of electrical activation and based on a library of stored representations of electrical activation, the library having stored representations of electrical activation of hearts that are each associated with a source location of an arrhythmia, the stored representations of electrical activation are derived from simulated electrical activations of computational models, the computational models representing a plurality of cardiac geometries, electrophysiological characteristics, and source locations, the computational models being not specific to the patient; and
displaying a graphical representation of a heart and an indication of the identified source location of the arrhythmia.
11 . A method comprising:
under control of one or more computing systems:
accessing a patient representation of electrical activation of the heart of a patient;
identifying a source location of an arrhythmia of the patient based on the patient representation of electrical activation and based on a library of stored representations of electrical activation, the library having stored representations of electrical activation of hearts that are each associated with a source location of an arrhythmia, the stored representations of electrical activation are derived from simulated electrical activations of computational models, wherein source locations are identified for multiple cycles of the patient representation of electrical activation; and
displaying a graphical representation of a heart and an indication of the identified source location of the arrhythmia wherein the graphical representation further indicates, for one or more areas of the heart, a coding that is based on a percent of source locations that are within that area; and
performing an ablation procedure on the patient targeting the source location of the arrhythmia.
12 . A method comprising:
under control of one or more computing systems:
accessing a patient representation of electrical activation of the heart of a patient;
identifying a source location of an arrhythmia of the patient based on the patient representation of electrical activation and based on a library of stored representations of electrical activation, the library having stored representations of electrical activation of hearts that are each associated with a source location of an arrhythmia, the stored representations of electrical activation are derived from simulated electrical activations of computational models, wherein the patient representation of electrical activation and the stored representations of electrical activation are an electrocardiogram or a vectorcardiogram; and
displaying a graphical representation of a heart and an indication of the identified source location of the arrhythmia; and
performing an ablation procedure on the patient targeting the source location of the arrhythmia.
13 . A method comprising:
under control of one or more computing systems:
accessing a patient representation of electrical activation of the heart of a patient, wherein the patient representation of electrical activation is a patient electrocardiogram;
converting the patient electrocardiogram to a patient vectorcardiogram;
identifying a source location of an arrhythmia of the patient based on the patient representation of electrical activation and based on a library of stored representations of electrical activation, the stored representations of electrical activation are stored vectorcardiograms, the library having stored representations of electrical activation of hearts that are each associated with a source location of an arrhythmia, the stored representations of electrical activation are derived from simulated electrical activations of computational models; and
displaying a graphical representation of a heart and an indication of the identified source location of the arrhythmia; and
performing an ablation procedure on the patient targeting the source location of the arrhythmia.
14 . A method comprising:
under control of one or more computing systems:
accessing a patient representation of electrical activation of the heart of a patient;
identifying a source location of an arrhythmia of the patient based on the patient representation of electrical activation and based on a library of stored representations of electrical activation, the library having stored representations of electrical activation of hearts that are each associated with a source location of an arrhythmia, the stored representations of electrical activation are derived from simulated electrical activations of computational models, wherein the identifying includes applying a machine learning algorithm to identify a source location, the machine learning algorithm being trained using the stored representations of electrical activation and the associated source locations; and
displaying a graphical representation of a heart and an indication of the identified source location of the arrhythmia; and
performing an ablation procedure on the patient targeting the source location of the arrhythmia.
15 . A method comprising:
accessing an electrocardiogram of a patient;
identifying a source location of an arrhythmia of the patient based on the electrocardiogram and based on a library of stored representations of electrical activation, the library having stored representations of electrical activation of hearts that are each associated with a source location of an arrhythmia, the stored representations of electrical activation are derived from simulated electrical activations of computational models, the computational models representing a plurality of cardiac geometries, electrophysiological characteristics, and source locations, the computational models being not specific to the patient; and
displaying a graphical representation of a heart and an indication of the identified source location of the arrhythmia.
16 . The one or more computing systems of claim 1 wherein the computer executable instructions further control the one or more computing systems to:
for each of the plurality of cardiac geometries, electrophysiological characteristics, and source locations,
run a simulation of electrical activations of a heart based on the cardiac geometry, the electrophysiological characteristics, and the source location;
generate a representation of the electrical activations; and
store in the library the representation of electrical activations in association with the source location.
17 . The one or more computing systems of claim 1 wherein the identification of the stored representation is further based on similarity of the cardiac geometries and electrophysiological characteristics of the computational models to the cardiac geometry and electrophysiological characteristics of the patient.
18 . The one or more computing systems of claim 1 wherein an ablation is performed targeting the source location of the arrhythmia.
19 . The method of claim 10 further comprising, under control of the one or more computing systems:
for each of the plurality of cardiac geometries, electrophysiological characteristics, and source locations,
running a simulation of electrical activations of a heart based on the cardiac geometry, the electrophysiological characteristics, and the source location;
generating a representation of the electrical activations; and
storing in the library the representation of electrical activations in association with the source location.
20 . The method of claim 10 wherein the identification of the stored representation is further based on similarity of the cardiac geometries and electrophysiological characteristics of the computational models to the cardiac geometry and electrophysiological characteristics of the patient.
21 . The method of claim 10 further comprising performing an ablation procedure on the patient targeting the source location of the arrhythmia.
22 . A method comprising:
under control of one or more computing systems:
accessing a patient representation of electrical activation of the heart of a patient;
identifying a source location of an arrhythmia of the patient based on the patient representation of electrical activation and based on a library of stored representations of electrical activation, the library having stored representations of electrical activation of hearts that are each associated with a source location of an arrhythmia, wherein the stored representations of electrical activation are derived from simulated electrical activations of computational models, the computational models represent a plurality of cardiac geometries, electrophysiological characteristics, and source locations, and the computational models are not specific to the patient;
displaying a graphical representation of a heart and an indication of the identified source location of the arrhythmia; and
performing an ablation procedure on the patient targeting the source location of the arrhythmia.
23 . The method of claim 15 further comprising performing an ablation procedure on the patient targeting the source location of the arrhythmia.
24 . The method of claim 15 further comprising:
for each of the plurality of cardiac geometries, electrophysiological characteristics, and source locations,
running a simulation of electrical activations of a heart based on the cardiac geometry, the electrophysiological characteristics, and the source location;
generating a representation of the electrical activations; and
storing in the library the representation of electrical activations in association with the source location.
25 . The method of claim 24 wherein the identification of the stored representation is further based on similarity of the cardiac geometries and electrophysiological characteristics of the computational models to the cardiac geometry and electrophysiological characteristics of the patient.