US-20260128178-A1 - COMPUTATIONAL CARDIAC DEPOLARIZATION AND REPOLARIZATION SIMULATION LIBRARY MAPPING FOR NON-INVASIVE ARRHYTHMIA RISK STRATIFICATION

Abstract

A non-invasive method for cardiac arrhythmia risk stratification may include identifying, based at least on an electrical recording of a patient, a cardiac depolarization simulation and a cardiac repolarization simulation corresponding to an electrical recording of a patient. One or more regions of increased spatial repolarization gradient in which a first area of a myocardium of the patient exhibits a first repolarization rate that differs from a second repolarization rate of a second area of the myocardium by an amount then divided by the spatial distance between the two regions, by a threshold value may be determined based on the cardiac depolarization simulation and the cardiac repolarization simulation. A risk of cardiac arrhythmia for the patient may be determined based a magnitude of the increased spatial repolarization gradient. Moreover, a treatment plan for the patient may be determined based on the magnitude and/or location of the increased spatial repolarization gradient.

Inventors

• David Krummen
• Kurt Hoffmayer
• Christopher Villongco

Assignees

• THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
• c/o The Vektor Group Inc.

Dates

Publication Date

20260507

Application Date

20250710

Claims (20)

1. 1 . A system, comprising: at least one processor; and at least one memory including program code which when executed by the at least one processor provides operations comprising: identifying, within a computational library, a cardiac depolarization simulation and a cardiac repolarization simulation corresponding to an electrical recording of a patient; determining, based at least on the cardiac depolarization simulation and the cardiac repolarization simulation, one or more regions exhibiting an increased spatial repolarization gradient in which a ratio of a difference between a first repolarization rate of a first area of a myocardium of the patient a second repolarization rate of a second area of the myocardium, and a spatial distance between the first region and the second region exceeds a threshold value; and determining, based at least on a magnitude of the increased spatial repolarization gradient, a risk of cardiac arrhythmia for the patient.
2. 2 . The system of claim 1 , wherein the operations further comprise determining, based at least on the magnitude of the increased spatial repolarization gradient, a treatment plan for the patient.
3. 3 . The system of claim 2 , wherein the treatment plan is determined to include, based at least the magnitude of the increased spatial repolarization gradient, a cardioverter-defibrillator implantation or an invasive electrophysiology study and ablation.
4. 4 . The system of claim 2 , wherein the treatment plan includes determining, based at least on a location of the one or more regions of increased spatial repolarization gradient, a location for a targeted therapy.
5. 5 . The system of claim 4 , wherein the targeted therapy includes catheter ablation and/or stereotactic ablative radiotherapy (SAbR).
6. 6 . The system of claim 1 , wherein the cardiac depolarization simulation comprises a ventricular activation simulation, and wherein the cardiac repolarization simulation comprises a ventricular recovery simulation.
7. 7 . The system of claim 1 , wherein the operations further comprise: generating the computational library to include a plurality of cardiac depolarization simulations and a plurality of cardiac repolarization simulations, the plurality of cardiac depolarization simulation and the plurality of cardiac repolarization simulation corresponding to a variety of cardiac geometries, cardiac orientations, scar configurations, degrees of cardiac fibrosis and scar, depolarization patterns, and/or activation types; and identifying, within the computational library, the cardiac depolarization simulation and the cardiac repolarization simulations corresponding to the electrical recording of the patient.
8. 8 . The system of claim 7 , wherein the operations further comprise: identifying, based at least on clinical data associated with the patient, a subset of simulations from the computational library that correspond to an anatomy of the patient; and identifying, within the subset of simulations corresponding to the anatomy of the patient, the cardiac depolarization simulation and the cardiac repolarization simulations corresponding to the electrical recording of the patient.
9. 9 . The system of claim 8 , wherein the clinical data includes patient demographics.
10. 10 . The system of claim 8 , wherein the clinical data includes cardiac imaging data indicating one or more locations of scar tissue, borderzone tissue, and normal tissue, cardiac chamber size, the presence of hypertrophy or dilation, locations of fibrosis, regions of normal and abnormal contractility, or regions of wall thinning.
11. 11 . The system of claim 1 , wherein the computational library is supplemented by clinical patient samples with known arrhythmia substrate source locations to provide additional data for comparison to the electrical recording of the patient.
12. 12 . The system of claim 1 , wherein the computational library includes clinical samples with known arrhythmia substrate source locations to serve as reference data for a comparison to the electrical recording of the patient.
13. 13 . The system of claim 8 , wherein the operations further comprise: in response to failing to identify the subset of simulations corresponding to the anatomy of the patient, generating, based at least on the clinical data of the patient, a custom computational library that includes one or more cardiac depolarization simulations and/or cardiac repolarization simulations specific to the anatomy of the patient.
14. 14 . The system of claim 1 , wherein the operations further comprise applying a machine learning model trained to determine that the cardiac repolarization simulation and the cardiac depolarization simulation match the electrical recording of the patient.
15. 15 . The system of claim 14 , wherein the machine learning model comprises a neural network, a regression model, an instance-based model, a regularization model, a decision tree, a random forest, a Bayesian model, a clustering model, an associative model, a dimensionality reduction model, and/or an ensemble model.
16. 16 . The system of claim 1 , wherein the operations further comprise applying, to the electrical recording of the patient, one or more of signal processing techniques.
17. 17 . The system of claim 16 , wherein the one or more signal processing techniques include recording, filtering, digitization, transformation, and/or spatial analysis.
18. 18 . The system of claim 1 , wherein the electrical recording comprises one or more of an electrogram, a vectorgram, an electrocardiogram, an electroencephalogram, or a vectorcardiogram.
19. 19 . The system of claim 18 , wherein the electrical recording further includes one or more body surface potential recordings.
20. 20 . The system of claim 1 , wherein the electrical recording comprises an electrocardiogramaging (ECGi) recording system including one or more body surface potential recordings.

Description

RELATED APPLICATIONS This application is a continuation of U.S. application Ser. No. 17/784,975, entitled “COMPUTATIONAL CARDIAC DEPOLARIZATION AND REPOLARIZATION SIMULATION LIBRARY MAPPING FOR NON-INVASIVE ARRHYTHMIA RISK STRATIFICATION”, and filed on Jun. 13, 2022, which is a national phase application of International Application No. PCT/US21/56311, entitled “COMPUTATIONAL CARDIAC DEPOLARIZATION AND REPOLARIZATION SIMULATION LIBRARY MAPPING FOR NON-INVASIVE ARRHYTHMIA RISK STRATIFICATION” and filed on Oct. 22, 2021, which claims priority to U.S. Provisional Application No. 63/104,930, entitled “COMPUTATIONAL CARDIAC DEPOLARIZATION AND REPOLARIZATION SIMULATION LIBRARY MAPPING FOR NON-INVASIVE ARRHYTHMIA RISK STRATIFICATION” and filed on Oct. 23, 2020, the disclosure of which is incorporated herein by reference in its entirety. TECHNICAL FIELD The subject matter described herein relates generally to computational modeling and simulations, and more specifically to simulation library mapping for non-invasive arrhythmia mapping and risk stratification. BACKGROUND Cardiac arrhythmias are common medical disorders in which abnormal electrical signals in the heart cause the heart to contract in a suboptimal manner. The resulting abnormal heartbeat, or arrhythmia, can occur in the atria of the heart (e.g., atrial fibrillation (AF)) and/or the ventricles of the heart (e.g., ventricular tachycardia (VT) or ventricular fibrillation (VF)). Treatments for cardiac arrhythmias attempt to address the mechanisms driving sustained and/or clinically significant episodes including, for example, stable electrical rotors, recurring electrical focal sources, reentrant electrical circuits, and/or the like. Left untreated, cardiac arrhythmias may cause serious health complications such as morbidity (e.g., syncope, stroke, and/or the like) and mortality (e.g. sudden cardiac death (SCD)). SUMMARY Systems, methods, and articles of manufacture, including computer program products, are provided for computational cardiac depolarization and repolarization simulation library mapping for non-invasive arrhythmia risk stratification. In one aspect, there is provided a system for non-invasive arrhythmia risk stratification. The system may include at least one processor and at least one memory storing instructions that cause operations when executed by the at least one processor. The operations may include: identifying, within a computational library, a cardiac depolarization simulation and a cardiac repolarization simulation corresponding to an electrical recording of a patient; determining, based at least on the cardiac depolarization simulation and the cardiac repolarization simulation, one or more regions of increased spatial repolarization gradient in which a first area of a myocardium of the patient exhibits a first repolarization rate that differs from a second repolarization rate of a second area of the myocardium by an amount then divided by the spatial distance between the two regions, by a threshold value; and determining, based at least on a magnitude of the increased spatial repolarization gradient, a risk of cardiac arrhythmia or sudden cardiac death (SCD) for the patient. In some variations, one or more features disclosed herein including the following features can optionally be included in any feasible combination. The operations may further include determining, based at least on the magnitude of the increased spatial repolarization gradient, a treatment plan for the patient. In some variations, the treatment plan may be determined to include, based at least the magnitude of the increased spatial repolarization gradient, a cardioverter-defibrillator implantation or an invasive electrophysiology study and ablation. In some variations, the treatment plan may include determining, based at least on a location of the one or more regions of increased spatial repolarization gradient, a location for a targeted therapy such as radiofrequency catheter ablation, cryoablation, high-frequency ultrasound ablation, laser therapy, or pulsed field ablation. In some variations, the targeted therapy may include catheter ablation and/or stereotactic ablative radiotherapy (SAbR). In some variations, the cardiac depolarization simulation may include a ventricular activation simulation, and wherein the cardiac repolarization simulation comprises a ventricular recovery simulation. In some variations, the operations may further include: generating the computational library to include a plurality of cardiac depolarization simulation and a plurality of cardiac repolarization simulations, the plurality of cardiac depolarization simulation and the plurality of cardiac repolarization simulation corresponding to a variety of cardiac geometries, cardiac orientations, scar configurations, degrees of cardiac fibrosis and scar, depolarization patterns, and/or activation types; and identifying, within the computational library, the cardiac depolarization simulat