METHOD AND SYSTEM FOR DETERMINING TREATMENTS BY MODIFYING PATIENT-SPECIFIC GEOMETRICAL MODELS

• US 20140249790A1
• Filed: 03/01/2013
• Published: 09/04/2014
• Est. Priority Date: 03/01/2013
• Status: Active Grant

• Current Assignee: Heartflow Inc.
• Original Assignee: Heartflow Inc.
• Inventors: Grady, Leo, Spilker, Ryan, Eberle, David
• Granted Patent: US 9,042,613 B2
• Time in Patent Office: Days
• US Class Current: 703/11
• CPC Class Codes: A61B 2034/104 Modelling the effect of the tool, e.g. the effect of an implanted prosthesis or for predicting the effect of ablation or burring
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/107 Visualisation of planned trajectories or target regions
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06T 2207/20112 Image segmentation details
• CPC Class Codes: G06T 2207/30096 Tumor; Lesion
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 2207/30104 Vascular flow; Blood flow; Perfusion
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06V 10/40 Extraction of image or video features
• CPC Class Codes: G06V 10/467 Encoded features or binary features, e.g. local binary patterns [LBP]
• CPC Class Codes: G06V 30/194 References adjustable by an adaptive method, e.g. learning
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: Y02A 90/10 : Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

Systems and methods are disclosed for evaluating cardiovascular treatment options for a patient. One method includes creating a three-dimensional model representing a portion of the patient'"'"'s heart based on patient-specific data regarding a geometry of the patient'"'"'s heart or vasculature; and for a plurality of treatment options for the patient'"'"'s heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model. The method also includes determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and identifying one of the plurality of treatment options that solves a function of at least one of: the determined blood flow characteristics of the patient'"'"'s heart or vasculature, and one or more costs of each of the plurality of treatment options.

Claims

1. A system for evaluating cardiovascular treatment options for a patient, the system comprising:

at least one computer system configured to;

create a three-dimensional model representing at least a portion of the patient'"'"'s heart or vasculature based on patient-specific data regarding a geometry of the patient'"'"'s heart or vasculature;

for each of a plurality of treatment options for treating at least a portion of the patient'"'"'s heart, modify at least one of the three-dimensional model and a reduced order model based on the three-dimensional model;

determine, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and

identify one of the plurality of treatment options that solves a function of at least one of;

the determined blood flow characteristics of the patient'"'"'s heart or vasculature, and one or more costs of each of the plurality of treatment options.

2. The system of claim 1, wherein the computer system is configured to modify, for each of the plurality of treatment options, the three-dimensional model using a geometric modification technique.

3. The system of claim 1, wherein the computer system is configured to modify, for each of the plurality of treatment options, the three-dimensional model using a constructive solid geometry union.

4. The system of claim 1, wherein the computer system is configured to modify, for each of the plurality of treatment options, the three-dimensional model using an elastic deformation modification technique.

5. The system of claim 1, wherein the computer system is configured to modify, for each of the plurality of treatment options, the three-dimensional model based on a simulated location of an inserted stent or bypass graft.

6. The system of claim 1, wherein the computer system is configured to modify the three-dimensional model for a subset of each of the plurality of treatment options in locations that exhibit a predetermined threshold level of a blood flow characteristic.

7. The system of claim 1, wherein the computer system is configured to:

create the reduced order model relating to a blood flow characteristic of the patient'"'"'s heart or vasculature, based on the three-dimensional model; and

modify the reduced order model for each possible treatment option, using a resistance value estimated to be associated with a type and location of the respective possible treatment option.

8. The system of claim 1, wherein the computer system is configured to determine resistance values associated with possible treatment options from historical data of known resistance values associated with a known dimension or geometry of previously implemented treatment options.

9. The system of claim 1, wherein the objective function is configured to maximize blood flow or minimize pressure changes in a patient'"'"'s coronary vasculature.

10. The system of claim 1, wherein the objective function is configured to penalize one or more of:

increasing numbers of stents or bypass grafts;

decreasing of FFR values in larger vessels, as opposed to smaller vessels;

increasing proximity of inserted stents;

treatment costs; and

the existence or number of bifurcations.

11. The system of claim 1, wherein the three-dimensional model representing at least the portion of the patient'"'"'s heart or vasculature includes at least a portion of an aorta and at least a portion of a plurality of coronary arteries emanating from the portion of the aorta.

12. The system of claim 1, wherein:

the blood flow characteristic indicates a ratio between a pressure in the aorta and a pressure at a location in the plurality of coronary arteries; and

the at least one computer system is configured to determine the blood flow characteristic at a plurality of locations in the plurality of coronary arteries.

13. The system of claim 1, wherein the patient-specific data includes imaging data provided by computer tomography or magnetic resonance imaging techniques.

14. The system of claim 1, wherein the reduced order model includes at least one lumped parameter model representing a blood flow through boundaries of the three-dimensional model.

15. The system of claim 1, wherein the at least one computer system is configured to determine the blood flow characteristic using a parameter associated with at least one of a level of hyperemia, a level of exercise, or a medication.

16. A method for evaluating cardiovascular treatment options for a patient, the method comprising:

creating a three-dimensional model representing at least a portion of the patient'"'"'s heart or vasculature based on patient-specific data regarding a geometry of the patient'"'"'s heart or vasculature;

for each of a plurality of treatment options for treating at least a portion of the patient'"'"'s heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model;

determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and

identifying one of the plurality of treatment options that solves a function of at least one of;

the determined blood flow characteristics of the patient'"'"'s heart or vasculature, and one or more costs of each of the plurality of treatment options,

17. The method of claim 16, further comprising modifying, for each of the plurality of treatment options, the three-dimensional model using at least one of:

a geometric modification technique;

a constructive solid geometry union; and

an elastic deformation modification technique.

18. The method of claim 16, further comprising modifying, for each of the plurality of treatment options, the three-dimensional model based on a simulated location of an inserted stent or bypass graft.

19. The method of claim 16, further comprising modifying the three-dimensional model for a subset of each of the plurality of treatment options in locations that exhibit a predetermined threshold level of a blood flow characteristic.

20. The method of claim 16, further comprising:

creating the reduced order model relating to a blood flow characteristic of the patient'"'"'s heart or vasculature, based on the three-dimensional model; and

modifying the reduced order model for each possible treatment option, using a resistance value estimated to be associated with a type and location of the respective possible treatment option.

21. The method of claim 16, further comprising determining resistance values associated with possible treatment options from historical data of known resistance values associated with a known dimension or geometry of previously implemented treatment options.

22. The method of claim 16, wherein the objective function is configured to maximize blood flow or minimize pressure changes in a patient'"'"'s coronary vasculature.

23. The method of claim 16, wherein the objective function is configured to penalize one or more of:

increasing numbers of stents or bypass grafts;

decreasing of FFR values in larger vessels, as opposed to smaller vessels;

increasing proximity of inserted stents;

treatment costs; and

the existence or number of bifurcations.

24. The method of claim 16, wherein the three-dimensional model representing at least the portion of the patient'"'"'s heart includes at least a portion of an aorta and at least a portion of a plurality of coronary arteries emanating from the portion of the aorta.

25. The method of claim 16, wherein:

the blood flow characteristic indicates a ratio between a pressure in the aorta and a pressure at a location in the plurality of coronary arteries; and

the at least one computer system is configured to determine the blood flow characteristic at a plurality of locations in the plurality of coronary arteries.

26. The method of claim 16, wherein the patient-specific data includes imaging data provided by computer tomography or magnetic resonance imaging techniques.

27. The method of claim 16, wherein the reduced order model includes at least one lumped parameter model representing a blood flow through boundaries of the three-dimensional model.

28. The method of claim 16, further comprising determining the blood flow characteristic using a parameter associated with at least one of a level of hyperemia, a level of exercise, or a medication.