IP Library Granted Patent US 10,786,308
Granted Patent B2
US 10,786,308 · App. 16/376,366 · Granted Sep 29, 2020

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

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Quick Facts
Patent No.
US 10,786,308
App. No.
16/376,366
Granted
Sep 29, 2020
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 (66)

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 having at least one vessel wall 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;

identifying, using a computer processor, a blood vessel of the patient-specific three-dimensional anatomic model;

determining a vessel wall property of the identified blood vessel;

determining one or more treatment modalities for treating the AVM;

performing a blood flow simulation through the identified blood vessel, based on the determined vessel wall property, the three-dimensional anatomic model, and the determined treatment modalities;

identifying one or more largest blood vessels associated with the AVM; and

generating a treatment recommendation for treating AVM of the identified blood vessel based on the performed blood flow simulation and based on the identified largest blood vessels associated with the AVM.

2. The method of claim 1 , further comprising:

computing one or more forces acting on a vessel wall of the identified blood vessel; and

performing the blood flow simulation further based on the one or more computed forces.

3. The method of claim 1 , wherein the vessel wall property may include a vessel wall thickness, vessel wall structure, or vessel wall composition.

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

5. The method of claim 1 , further comprising:

determining an effect on blood flow caused by treatment of the identified blood vessel.

6. The method of claim 5 , wherein the treatment includes one or more of embolization of the one or more blood vessels, ablation of the one or more blood vessels, surgical removal of all or part of the AVM, or radiosurgery.

7. 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;

difference in venous pressure post and pre treatment;

difference in tissue perfusion before and after treatment; and

a prediction of the a remodeled blood vessel radius and thickness.

8. The method of claim 1 , further comprising:

predicting, for the identified blood vessel, a homeostatic vessel state.

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

a data storage device storing instructions for assessing an arterio-venous malformation (AVM); and

a processor configured to execute the instructions to perform a method comprising the steps:

receiving image data of at least a portion of a vascular system of a patient, including one or more blood vessels having at least one vessel wall 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;

identifying, using a computer processor, a blood vessel of the patient-specific three-dimensional anatomic model;

determining a vessel wall property of the identified blood vessel;

determining one or more treatment modalities for treating the AVM;

performing a blood flow simulation through the identified blood vessel, based on the determined vessel wall property, the three-dimensional anatomic model, and the determined treatment modalities; and

identifying one or more largest blood vessels associated with the AVM; and

generating a treatment recommendation for treating AVM of the identified blood vessel based on the performed blood flow simulation and based on the identified largest blood vessels associated with the AVM.

10. The system of claim 9 , further comprising:

computing one or more forces acting on a vessel wall of the identified blood vessel; and

performing the blood flow simulation further based on the one or more computed forces.

11. The system of claim 9 , wherein the vessel wall property may include a vessel wall thickness, vessel wall structure, or vessel wall composition.

12. The system of claim 9 , wherein the blood flow simulation includes determining a blood flow characteristic at one or more points of the patient-specific three-dimensional anatomic model.

13. The system of claim 9 , wherein the processor is further configured for:

determining an effect on blood flow caused by treatment of the identified blood vessel.

14. The system of claim 13 , wherein the treatment includes one or more of embolization of the one or more blood vessels, ablation of the one or more blood vessels, surgical removal of all or part of the AVM, or radiosurgery.

15. The system of claim 9 , 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;

difference in venous pressure post and pre treatment;

difference in tissue perfusion before and after treatment; and

a prediction of the a remodeled blood vessel radius and thickness.

16. The system of claim 9 , wherein the system is further configured for:

predicting, for the identified blood vessel, a homeostatic vessel state.

17. A non-transitory computer-readable medium storing instructions that, when executed by a computer, cause the computer to perform a 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 having at least one vessel wall 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;

identifying, using a computer processor, a blood vessel of the patient-specific three-dimensional anatomic model;

determining a vessel wall property of the identified blood vessel;

determining one or more treatment modalities for treating the AVM;

performing a blood flow simulation through the identified blood vessel, based on the determined vessel wall property, the three-dimensional anatomic model, and the determined treatment modalities; and

identifying one or more largest blood vessels associated with the AVM; and

generating a treatment recommendation for treating AVM of the identified blood vessel based on the performed blood flow simulation and based on the identified largest blood vessels associated with the AVM.

18. The computer-readable medium of claim 17 , further comprising:

computing one or more forces acting on a vessel wall of the identified blood vessel; and

performing the blood flow simulation further based on the one or more computed forces.

19. The computer-readable medium of claim 17 , wherein the vessel wall property may include a vessel wall thickness, vessel wall structure, or vessel wall composition.

20. The computer-readable medium of claim 17 , wherein the blood flow simulation includes determining a blood flow characteristic at one or more points of the patient-specific three-dimensional anatomic model.

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 May 3, 2019
From: SANKARAN, SETHURAMAN; ZARINS, CHRISTOPHER; GRADY, LEO
To: HEARTFLOW, INC.
Reel/Frame 049071/0788 →