IP Library Granted Patent US 11,017,904
Granted Patent B2
US 11,017,904 · App. 15/421,832 · Granted May 25, 2021

Systems and methods for simulation of occluded arteries and optimization of occlusion-based treatments

Inventors: Sethuraman Sankaran (Palo Alto, CA); Leo J. Grady (Millbrae, CA); Charles A. Taylor (Menlo Park, CA); Christopher K. Zarins (Menlo Park, CA)
Assignee: HeartFlow, Inc.
G16H50/50G06F17/18G06F19/00G16H20/40G16H40/67
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Quick Facts
Patent No.
US 11,017,904
App. No.
15/421,832
Granted
May 25, 2021
Kind
B2
Abstract

Systems and methods are disclosed for simulation of occluded arteries and/or optimization of occlusion-based treatments. One method includes obtaining a patient-specific anatomic model of a patient's vasculature; obtaining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model; obtaining a post-treatment computational model by modifying portions of the initial computational model based on an occlusion-based treatment; generating a pre-treatment blood flow characteristic using the initial computational model or computing a post-treatment blood flow using the post-treatment computational model; and outputting a representation of the pre-treatment blood flow characteristic or the post-treatment blood flow characteristic.

Claims (62)

1. A computer-implemented method of planning an occlusive procedure, the method comprising:

obtaining image data of at least a portion of a patient's vasculature;

generating a patient-specific anatomic model of the portion of the patient's vasculature based on the image data by reconstructing at least one centerline and at least one corresponding lumen of at least one blood vessel of the patient's vasculature visible in the image data;

determining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model, the initial computational model including a pre-treatment boundary condition;

determining a pre-treatment blood flow characteristic value by performing a calculation of blood flow using the initial computational model;

prior to treatment of the patient, obtaining a plurality of candidate sites for the occlusive procedure;

prior to treatment of the patient, and for each respective candidate site in the plurality of candidate sites:

determining a post-treatment boundary condition by modifying the patient-specific anatomic model to include one or more cross-sectional outlets, surfaces, or boundaries in modeled vasculature of the patient-specific anatomic model corresponding to an occlusion at the respective candidate site by removing a portion of the patient's vasculature from the patient-specific anatomical model that is downstream of a plane perpendicular to the at least one centerline at the respective candidate site;

updating the initial computational model based on the post-treatment boundary condition in the modified patient-specific anatomic model;

noninvasively determining a respective post-treatment blood flow characteristic value by performing a calculation of blood flow using the updated computational model;

determining a respective evaluation for the respective candidate site based on a comparison of the pre-treatment blood flow characteristic value and the respective post-treatment blood flow characteristic value; and

generating, based on a comparison of the respective evaluation of the plurality of candidate sites, a plan for the occlusive procedure that includes a recommendation for selection of a treatment site from amongst the plurality of candidate sites.

2. The computer-implemented method of claim 1 , wherein the calculation of blood flow includes Navier-Stokes equations, reduced order models, or machine learning methods.

3. The computer-implemented method of claim 1 , wherein the post-treatment boundary condition is based on circulatory resistance or organ demand at a location of the patient's vasculature associated with the respective candidate site.

4. The computer-implemented method of claim 1 , wherein the occlusive procedure includes an amputation, an embolization therapy, or a vascular resection.

5. The computer-implemented method of claim 1 , further comprising:

determining one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature created by stoppage of blood flow through the patient's vasculature or removal of a portion of the patient's vasculature at each respective candidate site, wherein the post-treatment boundary condition is a boundary condition of at least one of the determined one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature.

6. The computer-implemented method of claim 5 , wherein the one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature include one or more outlets, surfaces, or boundaries perpendicular to a centerline of the patient's vasculature.

7. The computer-implemented method of claim 5 , further comprising:

modifying the patient-specific anatomic model by modeling at least one of the one or more cross-sectional outlets, surfaces, or boundaries in the modeled vasculature of the patient-specific anatomic model; and

updating the initial computational model such that the updated initial computational model simulates blood flow through the modified patient-specific anatomic model.

8. The computer-implemented method of claim 1 , wherein the respective post-treatment blood flow characteristic value includes organ perfusion or blood pressure.

9. A system for planning an occlusive procedure, the system comprising:

at least one data storage device storing instructions for planning occlusion-based treatments; and

at least one processor configured to execute the instructions to perform operations including:

obtaining image data of at least a portion of a patient's vasculature;

generating a patient-specific anatomic model of the portion of the patient's vasculature based on the image data by reconstructing at least one centerline and at least one corresponding lumen of at least one blood vessel of the patient's vasculature visible in the image data;

determining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model, the initial computational model including a pre-treatment boundary condition;

determining a pre-treatment blood flow characteristic value by performing a calculation of blood flow using the initial computational model;

prior to treatment of the patient, obtaining a plurality of candidate sites for the occlusive procedure;

prior to treatment of the patient, and for each respective candidate site in the plurality of candidate sites:

determining a post-treatment boundary condition by modifying the patient-specific anatomic model to include one or more cross-sectional outlets, surfaces, or boundaries in modeled vasculature of the patient-specific anatomic model corresponding to an occlusion at the respective candidate site by removing a portion of the patient's vasculature from the patient-specific anatomical model that is downstream of a plane perpendicular to the at least one centerline at the respective candidate site;

updating the initial computational model based on the post-treatment boundary condition in the modified patient-specific anatomic model;

noninvasively determining a respective post-treatment blood flow characteristic value by performing a calculation of blood flow using the updated computational model;

determining a respective evaluation for the respective candidate site based on a comparison of the pre-treatment blood flow characteristic value and the respective post-treatment blood flow characteristic value; and

generating, based on a comparison of the respective evaluation of the plurality of candidate sites, a plan for the occlusive procedure that includes a recommendation for selection of a treatment site from amongst the plurality of candidate sites.

10. The system of claim 9 , wherein the calculation of blood flow includes Navier-Stokes equations, reduced order models, or machine learning methods.

11. The system of claim 9 , wherein the post-treatment boundary condition is based on circulatory resistance or organ demand at a location of the patient's vasculature associated with the respective candidate site.

12. The system of claim 9 , wherein the occlusive procedure includes an amputation, an embolization therapy, or a vascular resection.

13. The system of claim 9 , the operations further including:

determining one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature created by stoppage of blood flow through the patient's vasculature or removal of a portion of the patient's vasculature at each respective candidate site, wherein the post-treatment boundary condition is a boundary condition of at least one of the determined one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature.

14. The system of claim 13 , wherein the one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature include one or more outlets, surfaces, or boundaries perpendicular to a centerline of the patient's vasculature.

15. The system of claim 13 , the operations further including:

modifying the patient-specific anatomic model by modeling at least one of the one or more cross-sectional outlets, surfaces, or boundaries in the modeled vasculature of the patient-specific anatomic model; and

updating the initial computational model such that the updated initial computational model simulates blood flow through the modified patient-specific anatomic model.

16. The system of claim 9 , wherein the respective post-treatment blood flow characteristic value includes organ perfusion or blood pressure.

17. A non-transitory computer readable medium for use on a computer system containing computer-executable programming instructions for planning an occlusive procedure, the instructions executing operations comprising:

obtaining image data of at least a portion of a patient's vasculature;

generating a patient-specific anatomic model of the portion of the patient's vasculature based on the image data by reconstructing at least one centerline and at least one corresponding lumen of at least one blood vessel of the patient's vasculature visible in the image data;

determining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model, the initial computational model including a pre-treatment boundary condition;

determining a pre-treatment blood flow characteristic value by performing a calculation of blood flow using the initial computational model;

prior to treatment of the patient, obtaining a plurality of candidate sites for the occlusive procedure;

prior to treatment of the patient, and for each respective candidate site in the plurality of candidate sites:

determining a post-treatment boundary condition by modifying the patient-specific anatomic model to include one or more cross-sectional outlets, surfaces, or boundaries in modeled vasculature of the patient-specific anatomic model corresponding to an occlusion at the respective candidate site by removing a portion of the patient's vasculature from the patient-specific anatomical model that is downstream of a plane perpendicular to the at least one centerline at the respective candidate site;

updating the initial computational model based on the post-treatment boundary condition in the modified patient-specific anatomic model;

noninvasively determining a respective post-treatment blood flow characteristic value by performing a calculation of blood flow using the updated computational model;

determining a respective evaluation for the respective candidate site based on a comparison of the pre-treatment blood flow characteristic value and the respective post-treatment blood flow characteristic value; and

generating, based on a comparison of the respective evaluation of the plurality of candidate sites, a plan for the occlusive procedure that includes a recommendation for selection of a treatment site from amongst the plurality of candidate sites.

18. The non-transitory computer readable medium of claim 17 , wherein the calculation of blood flow includes Navier-Stokes equations, reduced order models, or machine learning methods.

19. The non-transitory computer readable medium of claim 17 , wherein the post-treatment boundary condition is based on circulatory resistance or organ demand at a location of the patient's vasculature associated with the respective candidate site.

20. The non-transitory computer readable medium of claim 17 , the operations further comprising:

determining one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature created by stoppage of blood flow through the patient's vasculature or removal of a portion of the patient's vasculature at each respective candidate site, wherein the post-treatment boundary condition is a boundary condition of at least one of the determined one or more cross-sectional outlets, surfaces, or boundaries of the patient's vasculature.

Assignments (5)
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 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 25, 2017
From: SANKARAN, SETHURAMAN; GRADY, LEO; TAYLOR, CHARLES A.; ZARINS, CHRISTOPHER K.
To: HEARTFLOW, INC.
Reel/Frame 042134/0396 →
Continuity (3)
Continuation 14598050 · Jan 15, 2015
Provisional Application 62074693 · Nov 4, 2014
Related Publication 20170147780A1 · May 25, 2017
Cited By (18)
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