Calibration of simulated cardiograms
Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.
1 . A method performed by one or more computing systems for identifying a simulated cardiogram that matches a patient cardiogram of a patient, the method comprising:
accessing a library of simulated cardiograms, each simulated cardiogram being derived from simulated electromagnetic output generated based on a simulation of electrical activity of a heart, each simulated cardiogram associated with a simulated source configuration of a heart;
identifying simulated cardiograms that have simulated source configurations that are similar to a patient source configuration of the heart of the patient;
generating a transformation between the identified simulated cardiograms and the patient cardiogram; and
identifying a simulated cardiogram that is similar to the patient cardiogram factoring in the generated transformation; and
outputting an indication of the identified simulated cardiogram that is similar to the patient cardiogram.
2 . The method of claim 1 wherein a simulated source configuration includes a source location of an arrhythmia and further comprising outputting an indication of a source location of the simulation source configuration associated with the identified simulated cardiogram that is similar to the patient cardiogram.
3 . The method of claim 1 wherein the transformation is a linear transformation.
4 . The method of claim 1 wherein the identifying of simulated cardiograms that have simulated source configurations that are similar to the patient source configuration is further based on morphology of the simulated cardiograms and the patient cardiogram.
5 . The method of claim 1 wherein the generating of the transformation between the identified simulated cardiogram and the patient cardiogram includes performing machine learning training.
6 . One or more computing systems for identifying a simulated cardiogram that matches a patient cardiogram of a patient, the 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:
identify simulated cardiograms associated with simulated source configurations of a heart that are similar to a patient source configuration of the heart of the patient;
generate a transformation between at least one of the identified simulated cardiograms and the patient cardiogram; and
select at least one of the simulated cardiograms that are similar to the patient cardiogram factoring in the generated transformation; and
output an indication of a selected simulated cardiogram; and
one or more processors for controlling the one or more computing systems to execute one or more of the computer-executable instructions.
7 . A method performed by one or more computing systems for identifying a simulated cardiogram that matches a patient cardiogram of a patient, the method comprising:
identifying pacing-similar simulated cardiograms associated with simulated pacings that are similar to patient pacing used when collecting the patient cardiogram;
generating patient vectors for cycle phases of cardiac cycles of the patient cardiogram, the patient vectors representing electrical activity of a cycle phase and associated with a pacing and cycle phase;
for each pacing-similar simulated cardiogram,
generating simulated vectors for cycle phases of cardiac cycles of that pacing-similar simulated cardiogram, the simulated vectors representing electrical activity of a cycle phase and associated with a pacing and a cycle phase; and
calculating orientation differences between the patient vectors and the simulated vectors for that pacing-similar simulated cardiogram; and
outputting an indication of one or more pacing-similar simulated cardiograms based on the calculated orientation differences.
8 . The method of claim 7 wherein the calculating of the orientation differences includes generating a rotation matrix representing difference between the patient vectors and simulated vectors.
9 . The method of claim 8 wherein the generating of the rotation matrix includes applying a least-squares fit of the patient vectors and the simulated vectors.
10 . The method of claim 7 wherein the cycle phases include one or more of a QRS complex, T-wave, and P-wave of a cardiogram.
11 . The method of claim 7 wherein the outputting is based on calculated orientation differences that are smallest.
12 . A method performed by one or more computing systems for identifying a simulated cardiogram that matches a patient cardiogram of a patient, the method comprising:
accessing a library of simulated cardiograms, each simulated cardiogram being derived from simulated electromagnetic output generated based on a simulation of electrical activity of a heart, each simulated cardiogram associated with a simulated pacing;
identifying pacing-similar simulated cardiograms of the library with simulated pacings that are similar to patient pacing used when collecting the patient cardiogram;
generating a normalized patient cardiogram by normalizing magnitude of the patient cardiogram;
for each of a plurality of the pacing-similar simulated cardiograms,
generating a normalized pacing-similar simulated cardiogram by normalizing magnitude of that pacing-similar simulated cardiogram; and
calculating an electrophysiological similarity between that normalized pacing-similar simulated cardiogram and the normalized patient cardiogram based on magnitude and deflection of coordinates of the normalized pacing-similar simulated cardiogram and the normalized patient cardiogram;
selecting one or more pacing-similar simulated cardiograms based on the calculated electrophysiological similarity; and
outputting an indication of the selected one or more selected pacing-similar simulated cardiograms.
13 . The method of claim 12 wherein at least some of the simulated cardiograms are associated with a source location of an arrhythmia and further comprising outputting on indication of a source location associated with a selected pacing-similar simulated cardiogram.
14 . The method of claim 12 further comprising adjusting a simulated cardiogram based on one or more of cardiac geometry of the patient, bulk myocardial conductivity parameter of the patient, and a parameter of an ionic model that governs duration of action potential of the patient.
15 . The method of claim 12 wherein the electrophysiological similarity is based on action potential.
16 . The method of claim 15 further comprising normalizing time of the identified pacing-similar simulated cardiogram and the patient cardiogram.
17 . The method of claim 12 wherein the electrophysiological similarity is based on conduction velocity.
18 . One or more computing systems for identifying a simulated cardiogram that matches a patient cardiogram of a patient, the 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:
identify a simulated cardiogram of a library of simulated cardiograms that is similar to the patient cardiogram;
generate a normalized patient cardiogram by normalizing magnitude and/or time of the patient cardiogram;
generate a normalized simulated cardiogram by normalizing magnitude and/or time of the identified simulated cardiogram; and
calculate an electrophysiological similarity of the normalized simulated cardiogram and the normalized patient cardiogram; and
output an indication of the identified simulated cardiogram based on the electrophysiological similarity indicating that the normalized simulated cardiogram and the normalized patient cardiogram are electrophysiologically similar; and
one or more processors for controlling the one or more computing systems to execute one or more of the computer-executable instructions.
19 . The one or more computing systems of claim 18 wherein the instructions further output an indication of a source location of an arrhythmia associated with the identified simulated cardiogram.
20 . The one or more computing systems of claim 18 wherein instructions further output an indication of an ablation pattern associated with the identified simulated cardiogram.
21 . The one or more computing systems of claim 18 wherein the electrophysiological similarity is based on action potential.
22 . The one or more computing systems of claim 18 wherein the electrophysiological similarity is based on conduction velocity.
23 . A method for treating arrhythmia of a patient, the method comprising:
under control of one or more computing systems,
accessing a library of simulated cardiograms, each simulated cardiogram being derived from simulated electromagnetic output generated based on a simulation of electrical activity of a heart, each simulated cardiogram associated with a simulated source configuration of a heart;
identifying simulated cardiograms that have simulated source configurations that are similar to a patient source configuration of the heart of the patient;
generating a transformation between the identified simulated cardiograms and the patient cardiogram; and
identifying a simulated cardiogram that is similar to the patient cardiogram factoring in the generated transformation; and
outputting an indication of the identified simulated cardiogram that is similar to the patient cardiogram; and
treating the arrhythmia of the patient based on the identified simulated cardiogram.
24 . The method of claim 23 wherein a simulated source configuration includes a source location of an arrhythmia and further comprising outputting on indication of a source location of the simulation source configuration associated with the identified simulated cardiogram that is similar to the patient cardiogram and wherein the treating of the arrhythmia is performing an ablation based on the source location.
25 . The method of claim 23 wherein the transformation is a linear transformation.
26 . The method of claim 23 wherein the identifying of simulated cardiograms that have simulated source configurations that are similar to the patient source configuration is further based on morphology of the simulated cardiograms and the patient cardiogram.
27 . The method of claim 23 wherein the generating of the transformation between the identified simulated cardiogram and the patient cardiogram includes performing machine learning training.
28 . A method for treating an arrhythmia of a patient, the method comprising:
providing a patient cardiogram collected from the patient to one or more computing systems for identifying a simulated cardiogram that matches the patient cardiogram of a patient, the identifying comprising,
identifying pacing-similar simulated cardiograms associated with simulated pacings that are similar to patient pacing used when collecting the patient cardiogram;
generating patient vectors for cycle phases of cardiac cycles of the patient cardiogram, the patient vectors representing electrical activity of a cycle phase and associated with a pacing and cycle phase;
for each pacing-similar simulated cardiogram,
generating simulated vectors for cycle phases of cardiac cycles of that pacing-similar simulated cardiogram, the simulated vectors representing electrical activity of a cycle phase and associated with a pacing and a cycle phase; and
calculating orientation differences between the patient vectors and the simulated vectors for that pacing-similar simulated cardiogram; and
outputting an indication of one or more pacing-similar simulated cardiograms based on the calculated orientation differences; and
treating the arrhythmia of the patient based on the one or more pacing-similar simulated cardiograms.
29 . The method of claim 28 wherein the calculating of the orientation differences includes generating a rotation matrix representing difference between the patient vectors and simulated vectors.
30 . The method of claim 29 wherein the generating of the rotation matrix includes applying a least-squares fit of the patient vectors and the simulated vectors.
31 . The method of claim 28 wherein the cycle phases include one or more of a QRS complex, T-wave, and P-wave of a cardiogram.
32 . The method of claim 28 wherein the outputting is based on calculated orientation differences that are smallest.
33 . A method for treating an arrhythmia of a patient, the method comprising:
providing a patient cardiogram collected from the patient to one or more computing systems for identifying a simulated cardiogram that matches a patient cardiogram of a patient, the identifying comprising:
accessing a library of simulated cardiograms, each simulated cardiogram being derived from simulated electromagnetic output generated based on a simulation of electrical activity of a heart, each simulated cardiogram associated with a simulated pacing;
identifying pacing-similar simulated cardiograms of the library with simulated pacings that are similar to patient pacing used when collecting the patient cardiogram;
generating a normalized patient cardiogram by normalizing magnitude of the patient cardiogram;
for each of a plurality of the pacing-similar simulated cardiograms,
generating a normalized pacing-similar simulated cardiogram by normalizing magnitude of that pacing-similar simulated cardiogram; and
calculating an electrophysiological similarity between that normalized pacing-similar simulated cardiogram and the normalized patient cardiogram based on magnitude and deflection of coordinates of the normalized pacing-similar simulated cardiogram and the normalized patient cardiogram;
selecting one or more pacing-similar simulated cardiograms based on the calculated electrophysiological similarity; and
outputting an indication of the selected one or more selected pacing-similar simulated cardiograms;
treating the arrhythmia of the patient based on the one or more selected pacing-similar simulated cardiograms.
34 . The method of claim 33 wherein at least some of the simulated cardiograms are associated with a source location of an arrhythmia and further comprising outputting on indication of a source location associated with a selected pacing-similar simulated cardiogram and wherein the treating includes performing an ablation based on the source location.
35 . The method of claim 33 further comprising adjusting a simulated cardiogram based on one or more of cardiac geometry of the patient, bulk myocardial conductivity parameter of the patient, and a parameter of an ionic model that governs duration of action potential of the patient.
36 . The method of claim 33 wherein the electrophysiological similarity is based on action potential.
37 . The method of claim 36 further comprising normalizing time of the identified pacing-similar simulated cardiogram and the patient cardiogram.
38 . The method of claim 33 wherein the electrophysiological similarity is based on conduction velocity.