IP Library Granted Patent US 12,558,015
Granted Patent B2
US 12,558,015 · App. 17/418,642 · Granted Feb 24, 2026

Enhanced computational heart simulations

Inventors: David Krummen (San Diego, CA); Christopher Villongco (San Diego, CA)
Assignees: THE VEKTOR GROUP, INC.; The Regents of the University of California
A61B5/361A61B5/349A61B5/7264G16H50/20
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Quick Facts
Patent No.
US 12,558,015
App. No.
17/418,642
Granted
Feb 24, 2026
Kind
B2
Abstract

Methods to enhance the computational localization of cardiac arrhythmia sources are provided. A method may include receiving, from a first user, clinical data associated with a clinical case. The clinical data may include a patient anatomic information, diagnostic and/or treatment modalities, treatment parameters, treatment outcome, and medical literature. The clinical case may be indexed based on a first plurality of characteristics associated with the clinical data. The indexing may include associating at least a portion of the clinical data with a computational simulation of cardiac arrhythmia having a second plurality of characteristics matching the first plurality of characteristics. At least a portion of the clinical data associated with the indexed case may be provided to a second user in response to a query from the user. Related systems and articles of manufacture are also provided.

Claims (40)

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:

generating a library of computational simulations that are each associated with characteristics including a source location of an arrhythmia and a simulated cardiogram by, for each computational simulation, simulating voltage solutions of a heart based on at least some of the characteristics, generating a simulated cardiogram based on the simulated voltage solutions, and associating with the computational simulations the simulated cardiogram;

for each of a plurality of clinical cases,

receiving clinical data associated with that clinical case, the clinical data including a clinical cardiogram; and

indexing, based at least on a first plurality of characteristics associated with that clinical data, the clinical case, the indexing includes associating at least a portion of the clinical data of that clinical case with a computational simulation of an arrhythmia of the library, the indexing based on one or more characteristics matching one or more of the first plurality of characteristics, the matching one or more of characteristics include matching the clinical cardiogram and the simulated cardiogram of that computational simulation;

receiving a query that includes patient characteristics associated with a patient that include a patient cardiogram; and

responding to the query by providing at least a portion of the clinical data associated with an indexed clinical case associated with a simulated cardiogram matching the patient cardiogram and providing an indication of the source location of the computational simulation to which the indexed clinical case is indexed;

wherein the patient is treated with an ablation to treat an arrhythmia of the patient based on the provided portion of the indexed clinical case and the provided indication of the source location.

2 . The system of claim 1 , wherein the clinical data includes patient anatomic information, diagnostic and/or treatment modalities, treatment parameters, treatment outcome, and medical literature.

3 . The system of claim 1 , wherein the first plurality of characteristics and the patient characteristics include patient demographics, medical history, and treatment plan.

4 . The system of claim 1 , wherein the indexing includes determining, for each of a plurality of computational simulations of arrhythmias included in a library, a similarity score indicative of a closeness of match between the first plurality of characteristics associated with the clinical data and the patient characteristics associated with each of the plurality of computational simulations, and wherein the indexing further includes associating at least the portion of the data with one of the plurality of computational simulations having a highest similarity score.

5 . A method, comprising:

under control of a system having a processor and a memory,

accessing a library generated based on computational simulations, each computational simulation associated with library characteristics that include a library cardiogram generated from that computational simulation, the library characteristics including a source location of an arrhythmia;

for each of a plurality of first users,

receiving clinical data associated with a clinical case of that first user, the clinical data including a clinical cardiogram; and

indexing, based at least on a first plurality of characteristics associated with the clinical data, the clinical case, the indexing includes associating at least a portion of the clinical data of that clinical case with a computational simulation of an arrhythmia of the library, the indexing based on one or more library characteristics matching one or more of the first plurality of characteristics, the matching one or more of characteristics include a cardiogram;

receiving a query that includes patient characteristics associated with a patient that include a patient cardiogram; and

responding to the query by providing at least a portion of the clinical data associated with an indexed clinical case associated with a library cardiogram matching the patient cardiogram and providing the source location associated with the computational simulation associated with the indexed clinical case; and

performing an ablation to treat an arrhythmia of the patient based on the provided source location.

6 . The method of claim 5 , wherein the clinical data includes patient anatomic information, diagnostic and/or treatment modalities, treatment parameters, treatment outcome, and medical literature.

7 . The method of claim 5 , wherein the first plurality of characteristics and the patient characteristics include patient demographics, medical history, and treatment plan.

8 . The method of claim 5 , wherein the indexing includes determining, for each of a plurality of computational simulations of arrhythmias included in a library, a similarity score indicative of a closeness of match between the first plurality of characteristics associated with the clinical data and the patient characteristics associated with each of the plurality of computational simulations, and wherein the indexing further includes associating at least the portion of the data with one of the plurality of computational simulations having a highest similarity score.

9 . 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:

generating a library of computational simulations that are each associated with cardiac characteristics that include a source location of an arrhythmia and a simulated cardiogram by, for each computational simulation, generating a simulated cardiogram based on simulated voltage solutions of a computational simulation of a heart having those cardiac characteristics and associating the simulated cardiogram with the computational simulation;

receiving patient data collected during an electrophysiology study;

modifying, based at least on the patient data, one or more of the computational simulations;

determining, based at least on the modified one or more computational simulations, a source location of an arrhythmia; and

providing an indication of the source location of the arrhythmia to inform treatment based on the patient data

wherein the patient is treated with an ablation based on the indicated source location.

10 . The system of claim 9 , wherein the patient data includes at least one of an action potential duration restitution data, conduction velocity restitution data, patient anatomical geometry, voltage mapping, intracardiac ultrasound data, transthoracic ultrasound data, cone-beam computed tomography data, fluoroscopy data, patient demographics, cardiac activation pattern, regional conduction velocity, and electrogram characteristics.

11 . The system of claim 9 , wherein the modifying includes applying, to the one or more computational simulations, a patient-specific enhancement including at least one of a geometrical morphing and/or rotating, imposing a voltage and/or electrogram information onto the one or more computational simulations, indicating an activation information, adding global and/or regional information regarding a thickness of cardiac structure walls, and incorporating global and/or geographical information regarding the position and morphology of papillary muscles, pulmonary veins, and/or left and right atrial appendages.

12 . The system of claim 9 , wherein the modifying is performed in real time or near real time, and wherein the modified one or more computational simulations of arrhythmia are returned to a user for clinical use.

13 . The system of claim 9 , wherein the one or more computational simulations are non-patient specific computational simulations.

14 . The system of claim 9 , further comprising:

initiating, based at least on one or more arrhythmia solutions associated with the modified one or more computational simulations of arrhythmia, an arrhythmia simulation to generate a patient-tailored arrhythmia cardiogram library for use in a computational arrhythmia mapping process.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 27, 2025
From: VEKTOR MEDICAL, INC.
To: THE VEKTOR GROUP, INC.
Reel/Frame 073265/0864 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 26, 2025
From: VILLONGCO, CHRISTOPHER T.
To: VEKTOR MEDICAL, INC.
Reel/Frame 072121/0138 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 11, 2021
From: KRUMMEN, DAVID
To: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Reel/Frame 057756/0630 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 11, 2021
From: VILLONGCO, CHRISTOPHER T.
To: VEKTOR MEDICAL, INC.
Reel/Frame 057756/0635 →
Continuity (2)
Provisional Application 62786973 · Dec 31, 2018
Related Publication 20220061732A1 · Mar 3, 2022
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