IP Library Granted Patent US 11,107,587
Granted Patent B2
US 11,107,587 · App. 13/464,452 · Granted Aug 31, 2021

Method for tuning patient-specific cardiovascular simulations

Inventors: Ryan Leonard Spilker (Stanford, CA); Charles Anthony Taylor, Jr. (Menlo Park, CA)
Assignee: The Board of Trustees of the Leland Stanford Junior University
G16H50/50
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Quick Facts
Patent No.
US 11,107,587
App. No.
13/464,452
Granted
Aug 31, 2021
Kind
B2
Abstract

Computational methods are used to create cardiovascular simulations having desired hemodynamic features. Cardiovascular modeling methods produce descriptions of blood flow and pressure in the heart and vascular networks. Numerical methods optimize and solve nonlinear equations to find parameter values that result in desired hemodynamic characteristics including related flow and pressure at various locations in the cardiovascular system, movements of soft tissues, and changes for different physiological states. The modeling methods employ simplified models to approximate the behavior of more complex models with the goal of to reducing computational expense. The user describes the desired features of the final cardiovascular simulation and provides minimal input, and the system automates the search for the final patient-specific cardiovascular model.

Claims (65)

1. A computer system for determining cardiovascular information from patient-specific image data, to predict a hemodynamic result of a medical intervention for a patient, the computer system comprising:

a data storage device storing received patient-specific image data and instructions for processing the received patient-specific image data for determining cardiovascular information including predictions of hemodynamic results for a patient; and

a processing device configured to execute the stored instructions for processing the received patient-specific image data, the instructions executing a method comprising:

receiving patient-specific image data regarding a geometry of an anatomical structure of the patient;

creating, based on the patient-specific image data, a three-dimensional model representing at least a portion of the anatomical structure of the patient, the three-dimensional model including portions representing at least one inlet and at least one outlet of blood flow;

determining one or more boundary condition parameters for at least one of the at least one inlet or the at least one outlet of the three-dimensional model;

executing, using the at least one computer system, a three-dimensional simulation on the three-dimensional model, based on the determined one or more boundary condition parameters, to determine a blood flow characteristic within the anatomical structure of the patient;

creating, based on the executed three-dimensional simulation, a reduced-order model that is computationally faster than the three-dimensional model and that represents at least part of the portion of the anatomical structure of the patient represented by the three-dimensional model;

determining a medical intervention to be simulated using the reduced-order model; and

predicting a hemodynamic result of the medical intervention for the patient by solving the reduced-order model to determine an update to the blood flow characteristic.

2. The computer system of claim 1 , wherein the reduced-order model reproduces, within a tolerance, the blood flow characteristic determined using the three-dimensional model.

3. The computer system of claim 1 , wherein the processing device is further configured to determine the blood flow characteristic within the anatomical structure of the patient using the reduced order model.

4. The computer system of claim 3 , wherein the processing device is further configured to:

compare the blood flow characteristic determined using the three-dimensional model with the blood flow characteristic determined using the reduced-order model; and

determine whether to adjust the reduced-order model based on the comparison.

5. The computer system of claim 4 , wherein the processing device is further configured to determine whether to adjust the reduced-order model based on whether differences between the blood flow characteristic determined using the three-dimensional model and the blood flow characteristic determined using the reduced-order model are outside a tolerance.

6. The computer system of claim 5 , wherein the processing device is further configured to adjust the reduced-order model by increasing the level of detail of the reduced-order model when the differences are outside the tolerance.

7. The computer system of claim 4 , wherein the processing device is further configured to adjust the reduced-order model by adjusting the level of detail of the reduced-order model.

8. The computer system of claim 1 , wherein the processing device is further configured to determine whether to adjust the reduced-order model to include a lower level of detail while reproducing, within a tolerance, the blood flow characteristic determined using the three-dimensional model.

9. The computer system of claim 1 , wherein:

the three-dimensional model includes a three-dimensional mesh; and

the reduced-order model has less than three dimensions.

10. The computer system of claim 1 , wherein:

the three-dimensional model includes a three-dimensional mesh; and

the reduced-order model is created based on a mesh that is less refined than the three-dimensional mesh.

11. The computer system of claim 1 , wherein the processing device is further configured to determine the blood flow characteristic within the anatomical structure of the patient by solving equations governing blood flow using the reduced-order model, the initial blood flow model being associated with a more complete polynomial basis for solving the equations governing blood flow than the reduced-order model.

12. The computer system of claim 1 , wherein:

the initial boundary condition parameters represent flow in the at least one blood vessel using an elastance-based model of the patient's cardiac chamber; and

the reduced-order model includes a prescribed flow in the at least one blood vessel in the anatomical structure of the patient.

13. The computer system of claim 1 , wherein the processing device is further configured to:

determine the blood flow characteristic by solving a system of differential equations with numerical methods for temporal integration using the initial boundary condition parameters; and

determine the blood flow characteristic by solving a system of differential equations with Fourier analysis using the reduced-order model.

14. The computer system of claim 1 , wherein the reduced-order model includes a model assuming vascular walls that are more rigid than the corresponding vascular walls of the initial blood flow model.

15. The computer system of claim 1 , wherein:

the initial boundary condition parameters are associated with a model assuming rigid vascular walls; and

the reduced-order model includes a model assuming vascular walls that are less rigid than the corresponding vascular walls associated with the initial boundary condition parameters.

16. The computer system of claim 1 , wherein:

the anatomical structure includes at least a portion of a plurality of coronary arteries emanating from the aorta; and

the portion of the anatomical structure represented by the three-dimensional model includes at least a portion of the plurality of coronary arteries, the three-dimensional model representing at least one fluid flow inlet and at least one fluid flow outlet.

17. The computer system of claim 1 , wherein the blood flow characteristic includes at least one of blood flow or pressure within the anatomical structure of the patient.

18. A computer-implemented method for determining cardiovascular information from patient-specific image data to predict a hemodynamic result of a medical intervention for a patient using at least one computer system, the method comprising:

receiving, at the at least one computer system, patient-specific image data regarding a geometry of an anatomical structure of the patient;

creating, using the at least one computer system and based on the patient-specific image data, a three-dimensional model representing at least a portion of the anatomical structure of the patient, the three-dimensional model including portions representing at least one inlet and at least one outlet for blood flow;

determining one or more boundary condition parameters for the at least one of the at least one inlet or the at least one outlet of the three-dimensional model;

executing, using the at least one computer system, a three-dimensional simulation on the three-dimensional model, based on the determined one or more boundary condition parameters, to determine a blood flow characteristic within the anatomical structure of the patient;

creating, based on the executed three-dimensional simulation, a reduced-order model that is computationally faster than the three-dimensional model and that represents at least part of the portion of the anatomical structure of the patient represented by the three-dimensional model;

determining a medical intervention to be simulated using the reduced-order model; and

predicting a hemodynamic result of the medical intervention for the patient by solving the reduced-order model to determine an update to the blood flow characteristic.

19. The method of claim 18 , wherein the reduced-order model reproduces, within a tolerance, the blood flow characteristic determined using the three-dimensional model.

20. The method of claim 18 , further including determining, using the at least one computer system, the blood flow characteristic within the anatomical structure of the patient using the reduced-order model.

21. A non-transitory computer readable medium for use on at least one computer system containing computer-executable programming instructions for performing a method for determining patient-specific cardiovascular information from received patient-specific image data to predict a hemodynamic result of a medical intervention for a patient, the method comprising:

receiving patient-specific image data regarding a geometry of an anatomical structure of the patient;

creating, based on the patient-specific image data, a three-dimensional model representing at least a portion of the anatomical structure of the patient, the three-dimensional model including portions representing at least one inlet and at least one outlet for blood flow;

determining one or more boundary condition parameters for the three-dimensional model for the at least one inlet or at least one outlet of the three-dimensional model;

executing, using the at least one computer system, a three-dimensional simulation on the three-dimensional model, based on the determined one or more boundary condition parameters, to determine a blood flow characteristic within the anatomical structure of the patient;

creating, based on the executed three-dimensional simulation, a reduced-order model that is computationally faster than the three-dimensional model and that represents at least part of the portion of the anatomical structure of the patient represented by the three-dimensional model;

determining a medical intervention to be simulated using the reduced-order model; and

predicting a hemodynamic result of the medical intervention for the patient by solving the reduced-order model to determine an update to the blood flow characteristic.

22. The non-transitory computer readable medium of claim 21 , wherein the reduced-order model reproduces, within a tolerance, the blood flow characteristic determined using the three-dimensional model.

23. The non-transitory computer readable medium of claim 22 , the method further including determining, using the at least one computer system, the blood flow characteristic within the anatomical structure of the patient using the reduced-order model.

24. The non-transitory computer readable medium of claim 23 , the method further including:

comparing the blood flow characteristic determined using the three-dimensional model with the blood flow characteristic determined using the reduced-order model; and

determining whether to adjust the reduced-order model based on the comparison.

25. The non-transitory computer readable medium of claim 24 , the method further including:

determining whether to adjust the reduced-order model based on whether differences between the blood flow characteristic determined using the three-dimensional model and the blood flow characteristic determined using the reduced-order model are outside a tolerance.

Assignments (6)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 3, 2026
From: SPILKER, RYAN; TAYLOR, CHARLES
To: THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY
Reel/Frame 073948/0102 →
RELEASE OF SECURITY INTEREST Recorded Sep 11, 2025
From: HAYFIN SERVICES LLP
To: HEARTFLOW, INC.
Reel/Frame 072876/0775 →
RELEASE OF SECURITY INTEREST Recorded Jun 21, 2024
From: HAYFIN SERVICES LLP
To: HEARTFLOW, INC.
Reel/Frame 067801/0032 →
SECURITY INTEREST Recorded Jun 18, 2024
From: HEARTFLOW, INC.
To: HAYFIN SERVICES LLP
Reel/Frame 067775/0966 →
SECURITY INTEREST Recorded Jan 20, 2021
From: HEARTFLOW, INC.
To: HAYFIN SERVICES LLP
Reel/Frame 055037/0890 →
CONFIRMATORY LICENSE Recorded Jul 17, 2015
From: STANFORD UNIVERSITY
To: NATIONAL SCIENCE FOUNDATION
Reel/Frame 036129/0573 →