IP Library Granted Patent US 11,638,609
Granted Patent B2
US 11,638,609 · App. 17/644,762 · Granted May 2, 2023

Systems and methods for risk assessment and treatment planning of arterio-venous malformation

Inventors: Sethuraman Sankaran (Palo Alto, CA); Christopher Zarins (Austin, TX); Leo Grady (Darien, CT)
Assignee: HeartFlow, Inc.
A61B34/10A61B5/02007A61B5/4848A61B5/7275G06T7/0012G06T7/20G06T11/003G16H30/40G16H50/30G16H50/50A61B5/0035A61B5/0073A61B5/055A61B2034/105A61B2505/05G06T2207/10081G06T2207/10088G06T2207/30104
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Quick Facts
Patent No.
US 11,638,609
App. No.
17/644,762
Granted
May 2, 2023
Kind
B2
Abstract

A computer implemented method for assessing an arterio-venous malformation (AVM) may include, for example, receiving a patient-specific model of a portion of an anatomy of a patient; using a computer processor to analyze the patient-specific model for identifying one or more blood vessels associated with the AVM, in the patient-specific model; and estimating a risk of an undesirable outcome caused by the AVM, by performing computer simulations of blood flow through the one or more blood vessels associated with the AVM in the patient-specific model.

Claims (65)

1. A computer implemented method for assessing an arterio-venous malformation (AVM), the method comprising:

receiving image data of at least a portion of a vascular system of a patient, including one or more blood vessels associated with the AVM;

generating a patient-specific three-dimensional anatomic model of the portion of the vascular system of the patient, using the received image data;

performing a blood flow simulation through the one or more blood vessels associated with the AVM;

identifying, using a computer processor, one or more larger blood vessels among the one or more blood vessels associated with the AVM; and

generating a treatment recommendation for treating the AVM, based on the performed blood flow simulation and the identified one or more larger blood vessels.

2. The method of claim 1 , further comprising:

using the blood flow simulation and a stress equilibrium equation, calculating a vessel wall property of one or more vessel walls of the one or more blood vessels; and

evaluating one or more treatments of the AVM based on the calculated vessel wall properties and based on the identified one or more larger blood vessels.

3. The method of claim 2 , wherein evaluating the one or more treatments includes:

determining an effect on blood flow caused by the one or more treatments; and

assessing a change in a risk of an undesirable outcome based on the determined effect.

4. The method of claim 2 , wherein the vessel wall property includes a vessel wall thickness, vessel wall structure, or vessel wall composition.

5. The method of claim 1 , wherein performing the blood flow simulation includes determining a blood flow characteristic at one or more points of the patient-specific three-dimensional anatomic model.

6. The method of claim 1 , wherein generating the treatment recommendation includes weighing a list of factors comprising one or more of:

anatomical risk factors, including Spetzler-Martin grade;

functional risk factors;

a difference in a venous pressure post- and pre-treatment;

a difference in tissue perfusion before and after treatment; and

a prediction of a remodeled blood vessel radius and thickness.

7. The method of claim 1 , further comprising modeling a stiffness of tissues surrounding the AVM.

8. The method of claim 1 , further comprising calculating a displacement of the AVM and one or more forces exerted on tissues surrounding the AVM.

9. The method of claim 1 , wherein generating the treatment recommendation includes predicting an increase or decrease in (a) a radius of the AVM or (b) a radius of the one or more blood vessels associated with the AVM.

10. A system for assessing an arterio-venous malformation (AVM), the system comprising:

at least one data storage device storing instructions for assessing the AVM; and

at least one processor configured to execute the instructions to perform a method comprising:

receiving image data of at least a portion of a vascular system of a patient, including one or more blood vessels associated with the AVM;

generating a patient-specific three-dimensional anatomic model of the portion of the vascular system of the patient, using the received image data;

performing a blood flow simulation through the one or more blood vessels associated with the AVM;

identifying, using a computer processor, one or more larger blood vessels among the one or more blood vessels associated with the AVM; and

generating a treatment recommendation for treating the AVM, based on the performed blood flow simulation and the identified one or more larger blood vessels.

11. The system of claim 10 , wherein the method further comprises:

using the blood flow simulation and a stress equilibrium equation, calculating a vessel wall property of one or more vessel walls of the one or more blood vessels; and

evaluating one or more treatments of the AVM based on the calculated vessel wall properties and based on the identified one or more larger blood vessels.

12. The system of claim 11 , wherein evaluating the one or more treatments includes:

determining an effect on blood flow caused by the one or more treatments; and

assessing a change in a risk of an undesirable outcome based on the determined effect.

13. The system of claim 10 , wherein generating the treatment recommendation includes weighing a list of factors comprising one or more of:

anatomical risk factors, including Spetzler-Martin grade;

functional risk factors;

a difference in a venous pressure post- and pre-treatment;

a difference in tissue perfusion before and after treatment; and

a prediction of a remodeled blood vessel radius and thickness.

14. The system of claim 10 , wherein the method further comprises modeling a stiffness of tissues surrounding the AVM.

15. The system of claim 10 , wherein the method further comprises:

calculating a displacement of the AVM and one or more forces exerted on tissues surrounding the AVM.

16. The system of claim 10 , wherein generating the treatment recommendation includes predicting an increase or decrease in (a) a radius of the AVM or (b) a radius of the one or more blood vessels associated with the AVM.

17. A non-transitory computer readable medium storing computer- executable programming instructions for performing a method of non-invasively assessing a patient, the method comprising:

receiving image data of at least a portion of a vascular system of the patient, including one or more blood vessels associated with an arterio-venous malformation (AVM);

generating a patient-specific three-dimensional anatomic model of the portion of the vascular system of the patient, using the received image data;

performing a blood flow simulation through the one or more blood vessels associated with the AVM;

identifying, using a computer processor, one or more larger blood vessels among the one or more blood vessels associated with the AVM; and

generating a treatment recommendation for treating the AVM, based on the performed blood flow simulation and the identified one or more larger blood vessels.

18. The non-transitory computer readable medium of claim 17 , wherein the method further comprises:

using the blood flow simulation and a stress equilibrium equation, calculating a vessel wall property of one or more vessel walls of the one or more blood vessels; and

evaluating one or more treatments of the AVM based on the calculated vessel wall properties and based on the identified one or more larger blood vessels.

19. The non-transitory computer readable medium of claim 18 , wherein evaluating the one or more treatments includes:

determining an effect on blood flow caused by the one or more treatments; and

assessing a change in a risk of an undesirable outcome based on the determined effect.

20. The non-transitory computer readable medium of claim 17 , wherein generating the treatment recommendation includes weighing a list of factors comprising one or more of:

anatomical risk factors, including Spetzler-Martin grade;

functional risk factors;

a difference in a venous pressure post- and pre-treatment;

a difference in tissue perfusion before and after treatment; and

a prediction of a remodeled blood vessel radius and thickness.

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 Dec 17, 2021
From: SANKARAN, SETHURAMAN; ZARINS, CHRISTOPHER; GRADY, LEO
To: HEARTFLOW, INC.
Reel/Frame 058416/0456 →
Continuity (7)
Continuation 16999618 · Aug 21, 2020
Continuation 16376366 · Apr 5, 2019
Continuation 15977140 · May 11, 2018
Continuation 15807394 · Nov 8, 2017
Continuation 14842960 · Sep 2, 2015
Provisional Application 62150701 · Apr 21, 2015
Related Publication 20220110690A1 · Apr 14, 2022
Cited By (27)
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