IP Library Granted Patent US 12,029,494
Granted Patent B2
US 12,029,494 · App. 17/241,282 · Granted Jul 9, 2024

Method and system for image processing to determine blood flow

Inventor: Charles A. Taylor (Atherton, CA)
Assignee: HeartFlow, Inc.
A61B34/10A61B5/0035A61B5/004A61B5/0044A61B5/02A61B5/02007A61B5/02028A61B5/021A61B5/024A61B5/026A61B5/0263A61B5/029A61B5/055A61B5/1075A61B5/1118A61B5/22A61B5/4848A61B5/6852A61B5/7246A61B5/7275A61B5/7278A61B5/745A61B6/03A61B6/032A61B6/481A61B6/503A61B6/504A61B6/507A61B6/5205A61B6/5217A61B6/5229A61B8/02A61B8/04A61B8/06A61B8/065A61B8/481A61B8/5223A61B8/5261A61B34/25A61M5/007G01R33/5601G01R33/5635G01R33/56366G06F17/10G06F18/10G06F18/22G06F18/24G06F30/20G06F30/23G06F30/28G06G7/60G06T7/0012G06T7/0014G06T7/11G06T7/12G06T7/13G06T7/149G06T7/20G06T7/60G06T7/62G06T7/70G06T7/73G06T7/74G06T11/00G06T11/001G06T11/008G06T11/20G06T11/60G06T15/10G06T17/00G06T17/005G06T17/20G06V10/40G06V10/42G06V10/44G06V20/698G16B5/00G16B45/00G16H10/40G16H10/60G16H30/20G16H30/40G16H50/30G16H50/50G16H50/70G16H70/00A61B5/6868A61B2034/104A61B2034/105A61B2034/107A61B2034/108A61B2090/374A61B2090/3762A61B2090/3764A61B2576/00A61B2576/023G06T7/10G06T2200/04G06T2207/10012G06T2207/10072G06T2207/10081G06T2207/10088G06T2207/10104G06T2207/10108G06T2207/20036G06T2207/20124G06T2207/30016G06T2207/30048G06T2207/30104G06T2210/41G06T2211/404G06V10/467Y02A90/10
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Quick Facts
Patent No.
US 12,029,494
App. No.
17/241,282
Granted
Jul 9, 2024
Kind
B2
Abstract

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Claims (56)

1. A computer-implemented method of determining a risk of myocardial infarction associated with a coronary lesion of a patient, the method comprising:

generating a patient-specific coronary model of at least a portion of a vasculature of the patient, the patient-specific coronary model including a geometrical representation of one or more arterial segments;

the patient-specific coronary model including one or more characteristics associated with each arterial segment;

segmenting each lesion site disposed along at least one arterial segment of the one or more arterial segments into one or more sections, each lesion site including a lesion, the segmenting of each lesion site into the one or more sections being based on a location of the lesion of each lesion site relative to corresponding arterial segment;

determining one or more characteristics for at least one section of the one or more sections of each lesion site using at least the one or more characteristics associated with the at least one arterial segment, the one or more characteristics for the at least one section including one or more hemodynamic force characteristics, the one or more hemodynamic force characteristics for the at least one section including at least wall shear stress (WSS); and

determining one or more risk indices for each lesion site using at least the one or more hemodynamic force characteristics for the at least one section of each lesion site.

2. The method according to claim 1 , wherein:

the one or more sections for each lesion site includes a proximal section, wherein the proximal section is an inflow boundary of the corresponding arterial segment;

the one or more hemodynamic force characteristics is determined for at least the proximal section of each lesion site; and

the one or more risk indices for each lesion site is determined using the one or more hemodynamic force characteristics determined for at least the proximal section.

3. The method according to claim 1 , further comprising:

identifying one or more lesion sites disposed along the at least one arterial segment of the one or more arterial segments, each lesion site including the lesion;

wherein the one or more characteristics associated with each arterial segment and each lesion site includes one or more hemodynamic characteristics, the one or more hemodynamic characteristics including one or more pressure characteristics, the one or more pressure characteristics including a perfusion rate; and

wherein the one or more lesion sites is identified and/or the one or more risk indices is determined using at least the one or more pressure characteristics for the one or more sections of each lesion site and/or for each arterial segment.

4. The method according to claim 1 , wherein:

the determining the one or more risk indices includes comparing at least the one or more hemodynamic force characteristics for the at least one section of each lesion site to one or more thresholds.

5. The method according to claim 1 , further comprising:

generating a visualization of at least one lesion site; and

outputting the visualization.

6. The method according to claim 5 , wherein the visualization includes (i) the one or more risk indices associated with the at least one lesion site and/or (ii) the one or more characteristics associated with the at least one lesion site and/or the one or more arterial segments.

7. The method according to claim 1 , further comprising:

enabling an assessment of treatment options for each lesion site, based on the one or more risk indices and/or the one or more characteristics associated with the one or more sections of each lesion site.

8. The method according to claim 1 , further comprising:

receiving patient data of the patient, the patient data including medical image data of the patient acquired by a medical image acquisition device, the medical image data including one or more arterial segments and surrounding area;

generating the patient-specific coronary model using the patient data, the coronary model including the geometrical representation of the one or more arterial segments from the medical image data, boundaries for each arterial segment, boundary conditions for each arterial segment, geometrical information for each boundary, and geometrical information;

wherein the generating includes generating the one or more characteristics for each arterial segment; and

wherein the one or more characteristics for each arterial segment includes one or more flow field characteristics and one or more hemodynamic characteristics.

9. A system for determining a risk of myocardial infarction associated with a coronary lesion of a patient, the system comprising:

at least one processor; and

at least one memory storing instructions that, when executed by the at least one processor, perform operations comprising:

generating a patient-specific coronary model of at least a portion of a vasculature of the patient, the patient-specific coronary model including a geometrical representation of one or more arterial segments;

the patient-specific coronary model including one or more characteristics associated with each arterial segment;

segmenting each lesion site disposed along at least one arterial segment of the one or more arterial segments into one or more sections, each lesion site including a lesion, the segmenting of each lesion site into the one or more sections being based on a location of the lesion of each lesion site relative to corresponding arterial segment;

determining one or more characteristics for at least one section of the one or more sections of each lesion site using at least the one or more characteristics associated with the at least one arterial segment, the one or more characteristics for the at least one section including one or more hemodynamic force characteristics, the one or more hemodynamic force characteristics for the at least one section including at least wall shear stress (WSS); and

determining one or more risk indices for each lesion site using at least the one or more hemodynamic force characteristics for the at least one section of each lesion site.

10. The system according to claim 9 , wherein:

the one or more sections for each lesion site includes a proximal section, wherein the proximal section is an inflow boundary of the corresponding arterial segment;

the one or more hemodynamic force characteristics is determined for at least the proximal section of each lesion site; and

the one or more risk indices for each lesion site is determined using the one or more hemodynamic force characteristics determined for at least the proximal section.

11. The system according to claim 9 , wherein the operations further comprise:

identifying one or more lesion sites disposed along the at least one arterial segment of the one or more arterial segments, each lesion site including the lesion;

wherein the one or more characteristics associated with each arterial segment and each lesion site includes one or more hemodynamic characteristics, the one or more hemodynamic characteristics including one or more pressure characteristics, the one or more pressure characteristics including a perfusion rate; and

wherein the one or more lesion sites is identified and/or the one or more risk indices is determined using at least the one or more pressure characteristics for the one or more sections of each lesion site and/or for each arterial segment.

12. The system according to claim 9 , wherein:

the determining the one or more risk indices includes comparing at least the one or more hemodynamic force characteristics for the at least one section of each lesion site to one or more thresholds.

13. The system according to claim 9 , the operations further comprising:

generating a visualization of at least one lesion site; and

outputting the visualization.

14. The system according to claim 13 , wherein the visualization includes (i) the one or more risk indices associated with the at least one lesion site and/or (ii) the one or more characteristics associated with the at least one lesion site and/or the one or more arterial segments.

15. The system according to claim 9 , the operations further comprising:

enabling an assessment of treatment options for each lesion site, based on the one or more risk indices and/or the one or more characteristics associated with the one or more sections of each lesion site.

16. The system according to claim 9 , the operations further comprising:

receiving patient data of the patient, the patient data including medical image data of the patient acquired by a medical image acquisition device, the medical image data including the one or more arterial segments and surrounding area;

generating the patient-specific coronary model using the patient data, the coronary model including the geometrical representation of the one or more arterial segments from the medical image data, boundaries for each arterial segment, boundary conditions for each arterial segment, geometrical information for each boundary, and geometrical information;

wherein the generating includes generating the one or more characteristics for each arterial segment; and

wherein the one or more characteristics for each arterial segment includes one or more flow field characteristics and one or more hemodynamic characteristics.

Assignments (3)
RELEASE OF SECURITY INTEREST Recorded Sep 11, 2025
From: HAYFIN SERVICES LLP
To: HEARTFLOW, INC.
Reel/Frame 072876/0775 →
SECURITY INTEREST Recorded Jun 18, 2024
From: HEARTFLOW, INC.
To: HAYFIN SERVICES LLP
Reel/Frame 067775/0966 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 25, 2021
From: TAYLOR, CHARLES A.
To: HEARTFLOW, INC.
Reel/Frame 056337/0021 →
Continuity (13)
Continuation 15812329 · Nov 14, 2017
Continuation 15092393 · Apr 6, 2016
Continuation 14866098 · Sep 25, 2015
Continuation 14276442 · May 13, 2014
Continuation 13658739 · Oct 23, 2012
Continuation 13014835 · Jan 27, 2011
Division 13013561 · Jan 25, 2011
Provisional Application 61404429 · Oct 1, 2010
Provisional Application 61402345 · Aug 27, 2010
Provisional Application 61402308 · Aug 26, 2010
Provisional Application 61401915 · Aug 20, 2010
Provisional Application 61401462 · Aug 12, 2010
Related Publication 20210244475A1 · Aug 12, 2021
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