IP Library Granted Patent US 12,142,384
Granted Patent B2
US 12,142,384 · App. 18/483,759 · Granted Nov 12, 2024

Systems and methods for assessing cardiovascular disease and treatment effectiveness from adipose tissue

Inventors: Mark Rabbat (Redwood City, CA); Charles Taylor (Atherton, CA); Michiel Schaap (Oegstgeest, NL); Timothy Fonte (San Francisco, CA); Leo Grady (Darien, CT)
Assignee: HeartFlow, Inc.
G16H50/30A61B5/02007A61B5/4848A61B5/7278G16H30/20G16H50/50
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Quick Facts
Patent No.
US 12,142,384
App. No.
18/483,759
Granted
Nov 12, 2024
Kind
B2
Abstract

Systems and methods are disclosed for assessing cardiovascular disease and treatment effectiveness based on adipose tissue. One method includes identifying a vascular bed of interest in a patient's vasculature; receiving a medical image of the patient's identified vascular bed of interest; identifying adipose tissue in the received medical image; receiving a geometric vascular model comprising a representation of the patient's identified vascular bed of interest; and computing an inflammation index associated with the geometric vascular model, using the identified adipose tissue.

Claims (43)

1. A computer-implemented method for determining a blood-flow metric based on adipose tissue, comprising:

receiving, by at least one processor, a medical image of a region of interest of a vascular system of a patient, wherein the medical image includes one or more of a Computed Tomography (CT) image, a Magnetic Resonance Image (MRI), or a Computed Tomography Angiography (CTA) image;

identifying, by the at least one processor, adipose tissue in the received medical image;

receiving, by the at least one processor, one or more of a geometric vascular model or a blood flow model that includes a representation of the region of interest;

computing, by the at least one processor, an inflammation index associated with the one or more of the geometric vascular model or the blood flow model, using the identified adipose tissue; and

modifying, by the at least one processor, a blood flow computation based on the computed inflammation index; and determining, based on the modified blood flow computation, a fractional flow reserve of the vascular system of the patient.

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

quantifying, by the at least one processor, the detected adipose tissue, wherein the inflammation index is computed based on the quantified detected adipose tissue.

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

generating, by the at least one processor, a patient disease assessment or treatment evaluation based on the computed inflammation index.

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

generating a patient-specific blood-flow metric threshold based on the computed inflammation index.

5. The computer-implemented method of claim 1 , wherein computing the inflammation index includes computing a plurality of inflammation indexes for a plurality of different locations in the vascular system of the patient.

6. The computer-implemented method of claim 1 , wherein modifying the blood flow computation includes modifying at least one aspect of the one or more of the geometric vascular model or the blood flow model based on the computed inflammation index.

7. A system for determining a blood-flow metric based on adipose tissue, comprising:

at least one memory storing instructions; and

at least one processor operatively connected to the at least one memory, and configured to execute the instructions to perform operations, including:

receiving a medical image of a region of interest of a vascular system of a patient, wherein the medical image includes one or more of a Computed Tomography (CT) image, a Magnetic Resonance Image (MRI), or a Computed Tomography Angiography (CTA) image;

identifying adipose tissue in the received medical image;

receiving one or more of a geometric vascular model or a blood flow model that includes a representation of the region of interest;

computing an inflammation index associated with the one or more of the geometric vascular model or the blood flow model, using the identified adipose tissue; and

modifying a blood flow computation based on the computed inflammation index; and determining, based on the modified blood flow computation, a fractional flow reserve of the vascular system of the patient.

8. The system of claim 7 , wherein the operations further include:

quantifying, by the at least one processor, the detected adipose tissue, wherein the inflammation index is computed based on the quantified detected adipose tissue.

9. The system of claim 7 , wherein the operations further include:

generating, by the at least one processor, a patient disease assessment or treatment evaluation based on the computed inflammation index.

10. The system of claim 7 , wherein the operations further include:

generating a patient-specific blood-flow metric threshold based on the computed inflammation index.

11. The system of claim 7 , wherein computing the inflammation index includes computing a plurality of inflammation indexes for a plurality of different locations in the vascular system of the patient.

12. The system of claim 7 , wherein modifying the blood flow computation includes modifying at least one aspect of the one or more of the geometric vascular model or the blood flow model based on the computed inflammation index.

13. A non-transitory computer-readable medium comprising instructions for determining a blood-flow metric based on adipose tissue, the instructions executable by at least one processor to perform operations, including:

receiving a medical image of a region of interest of a vascular system of a patient, wherein the medical image includes one or more of a Computed Tomography (CT) image, a Magnetic Resonance Image (MRI), or a Computed Tomography Angiography (CTA) image;

identifying adipose tissue in the received medical image;

receiving one or more of a geometric vascular model or a blood flow model that includes a representation of the region of interest;

computing an inflammation index associated with the one or more of the geometric vascular model or the blood flow model, using the identified adipose tissue; and

modifying a blood flow computation based on the computed inflammation index; and determining, based on the modified blood flow computation, a fractional flow reserve of the vascular system of the patient.

14. The non-transitory computer-readable medium of claim 13 , wherein the operations further include:

quantifying, by the at least one processor, the detected adipose tissue, wherein the inflammation index is computed based on the quantified detected adipose tissue; and

generating, by the at least one processor, a patient disease assessment or treatment evaluation based on the computed inflammation index.

15. The non-transitory computer-readable medium of claim 13 , wherein the operations further include:

generating a patient-specific blood-flow metric threshold based on the computed inflammation index.

16. The non-transitory computer-readable medium of claim 13 , wherein computing the inflammation index includes computing a plurality of inflammation indexes for a plurality of different locations in the vascular system of the patient.

17. The non-transitory computer-readable medium of claim 13 , wherein modifying the blood flow computation includes modifying at least one aspect of the one or more of the geometric vascular model or the blood flow model based on the computed inflammation index.

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 Nov 2, 2023
From: RABBAT, MARK; TAYLOR, CHARLES A.; SCHAAP, MICHIEL; FONTE, TIMOTHY; GRADY, LEO
To: HEARTFLOW, INC.
Reel/Frame 065441/0239 →
Cited By (1)
US 12,670,587