Method and system for patient-specific modeling of blood flow

• US 9,449,147 B2
• Filed: 07/29/2015
• Issued: 09/20/2016
• Est. Priority Date: 08/12/2010
• Status: Active Grant

• Current Assignee: Heartflow Inc.
• Original Assignee: Heartflow Inc.
• Inventors: Taylor, Charles A.
• Primary Examiner(s): Clow, Lori A
• Application Number:
  US14/812,882
• Publication Number:
  US 20150332015A1
• Time in Patent Office: 419 Days
• Field of Search: None
• US Class Current: 1/1
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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

1. A method for assessment of renal artery stenosis of a patient, comprising:

generating a patient-specific anatomical model of at least a portion of the patient'"'"'s renal arteries from medical image data of the patient;

generating a computational model of blood flow through the portion of the renal arteries represented by the patient-specific anatomical model, the computational model of blood flow comprising patient-specific boundary conditions;

estimating the patient-specific boundary conditions of the computational model of blood flow in the portion of the renal arteries using the patient-specific anatomical model;

simulating blood flow and pressure in the portion of the renal arteries using the computational model incorporating the patient-specific boundary conditions; and

calculating at least one hemodynamic quantity characterizing functional severity of a renal stenosis region using the simulated blood flow and pressure in the portion of the renal arteries.

2. The method of claim 1, further comprising:

quantifying at least one inflow and at least one outflow to the portion of the renal arteries.

3. The method of claim 2, further comprising:

determining inlet and outlet boundary conditions using the quantified at least one inflow and at least one outflow to the portion of the renal arteries.

4. The method of claim 2, wherein quantifying at least one inflow and at least one outflow to the portion of the renal arteries comprises:

measuring flow rates corresponding to inlet and outlet positions of the portion of the renal arteries and aorta.

5. The method of claim 4, wherein the flow rates are measured using cross-sectional areas of the portion of the renal arteries and the aorta.

6. The method of claim 4, wherein the medical image data comprises a magnetic resonance imaging (MRI) image.

7. The method of claim 2, wherein quantifying at least one inflow and at least one outflow to the portion of the renal arteries comprises:

determining flow information in a lumen of the portion of the renal arteries using the patient-specific anatomical model.

8. The method of claim 1, wherein estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries using the patient-specific anatomical model comprises:

estimating patient-specific boundary conditions of the computational model for a plurality of physiological states of the patient.

9. The method of claim 8, wherein estimating patient-specific boundary conditions of the computational model for a plurality of physiological states of the patient comprises:

estimating the patient-specific boundary conditions for each of the plurality of physiological states using a respective patient-specific anatomic model extracted from medical image data acquired at each of the plurality of physiological states.

10. The method of claim 8, wherein estimating patient-specific boundary conditions of the computational model for a plurality of physiological states of the patient comprises:

estimating patient-specific boundary conditions for a rest state using the patient-specific anatomical model extracted from medical image data acquired at a rest state; and

estimating patient-specific boundary conditions for a hyperemic state using the estimated patient-specific boundary conditions for the rest state.

11. The method of claim 1, wherein calculating at least one hemodynamic quantity characterizing functional severity of a renal stenosis region using the simulated blood flow and pressure in the portion of the renal arteries comprises:

calculating a pressure drop across the renal stenosis region using the simulated blood flow and pressure.

12. The method of claim 1, wherein calculating at least one hemodynamic quantity characterizing functional severity of a renal stenosis region using the simulated blood flow and pressure in the portion of the renal arteries comprises:

calculating fractional flow reserve (FFR) for the renal stenosis region using the simulated blood flow and pressure.

13. The method of claim 1, wherein the computational model comprises one-dimensional computational models representing the renal arteries of the patient.

14. The method of claim 1, wherein the computational model comprises a reduced order stenosis pressure-drop model representing the renal stenosis region coupled to a one-dimensional computational model representing a renal artery.

15. The method of claim 14, wherein the reduced order stenosis pressure-drop model calculates a pressure drop across the renal stenosis region as a function of the velocity through the stenosis region.

16. The method of claim 1, wherein the computational model comprises a full-order three-dimensional computational model of the renal stenosis region, coupled to a one-dimensional computational model representing a renal artery.

17. The method of claim 1, wherein the computational model comprises lumped models representing microvasculature, each lumped model being coupled to a termination of a computational model representing a respective renal artery.

18. An apparatus for assessment of renal artery stenosis of a patient, the apparatus executing a method comprising:

generating a patient-specific anatomical model of at least a portion of the patient'"'"'s renal arteries from medical image data of the patient;

generating a computational model of blood flow through the portion of the renal arteries represented by the patient-specific anatomical model, the computational model of blood flow comprising patient-specific boundary conditions;

estimating the patient-specific boundary conditions of the computational model of blood flow in the portion of the renal arteries using the patient-specific anatomical model;

simulating blood flow and pressure in the portion of the renal arteries using the computational model incorporating the patient-specific boundary conditions; and

calculating at least one hemodynamic quantity characterizing functional severity of a renal stenosis region based on using the simulated blood flow and pressure in the portion of the renal arteries.

19. The apparatus of claim 18, further comprising:

quantifying at least one inflow and at least one outflow to the portion of the renal arteries.

20. The apparatus of claim 19, further comprising:

determining inlet and outlet boundary conditions using the quantified at least one inflow and at least one outflow to the portion of the renal arteries.

21. The apparatus of claim 19, wherein quantifying at least one inflow and at least one outflow to the portion of the renal arteries further comprises:

measuring flow rates corresponding to inlet and outlet positions of the portion of the renal arteries and aorta.

22. The apparatus of claim 21 wherein the flow rates are measured using cross-sectional areas of the portion of the renal arteries and the aorta.

23. The apparatus of claim 22, wherein estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries using the patient-specific anatomical model further comprises:

estimating patient-specific boundary conditions of the computational model for a plurality of physiological states of the patient.

24. The apparatus of claim 23, wherein estimating patient-specific boundary conditions of the computational model for a plurality of physiological states of the patient further comprises:

estimating the patient-specific boundary conditions for each of the plurality of physiological states using a respective patient-specific anatomic model extracted from medical image data acquired at each of the plurality of physiological states.

25. The apparatus of claim 23, wherein estimating patient-specific boundary conditions of the computational model for a plurality of physiological states of the patient further comprises:

estimating patient-specific boundary conditions for a rest state using the patient-specific anatomical model extracted from medical image data acquired at a rest state; and

estimating patient-specific boundary conditions for a hyperemic state using the estimated patient-specific boundary conditions for the rest state.

26. The apparatus of claim 22, wherein calculating at least one hemodynamic quantity characterizing functional severity of a renal stenosis region using the simulated blood flow and pressure in the portion of the renal arteries further comprises:

calculating fractional flow reserve (FFR) for the renal stenosis region using the simulated blood flow and pressure.

27. The apparatus of claim 22, wherein the computational model comprises one-dimensional computational models representing the renal arteries of the patient.

28. The apparatus of claim 22, wherein the computational model comprises a reduced order stenosis pressure-drop model representing the renal stenosis region coupled to a one-dimensional computational model representing a renal artery.

29. The apparatus of claim 22, wherein the reduced order stenosis pressure-drop model calculates a pressure drop across the renal stenosis region as a function of the velocity through the stenosis region.

30. The apparatus of claim 22, wherein the computational model comprises a full-order three-dimensional computational model of the renal stenosis region, coupled to a one-dimensional computational model representing a renal artery.

31. The apparatus of claim 22, wherein the computational model comprises lumped models representing microvasculature, each lumped model being coupled to a termination of a computational model representing a respective renal artery.

32. The apparatus of claim 21, wherein the medical image data comprises a magnetic resonance imaging (MRI) image.

33. The apparatus of claim 32, wherein quantifying at least one inflow and at least one outflow to the portion of the renal arteries further comprises:

determining flow information in a lumen of the portion of the renal arteries using the patient-specific anatomical model.

34. The apparatus of claim 18, wherein calculating at least one hemodynamic quantity characterizing functional severity of a renal stenosis region using the simulated blood flow and pressure in the portion of the renal arteries and aorta further comprises:

calculating a pressure drop across the renal stenosis region using the simulated blood flow and pressure.

35. A non-transitory computer readable medium storing computer program instructions for assessment of renal artery stenosis of a patient, the computer program instructions that, when executed by a processor, cause the processor to perform operations comprising:

generating a patient-specific anatomical model of at least a portion of the patient'"'"'s renal arteries from medical image data of the patient;

generating a computational model of blood flow through the portion of the renal arteries represented by the patient-specific anatomical model, the computational model of blood flow comprising patient-specific boundary conditions;

estimating the patient-specific boundary conditions of the computational model of blood flow in the portion of the renal arteries using the patient-specific anatomical model;

simulating blood flow and pressure in the portion of the renal arteries using the computational model incorporating the patient-specific boundary conditions; and

calculating at least one hemodynamic quantity characterizing functional severity of a renal stenosis region using the simulated blood flow and pressure in the portion of the renal arteries.

36. The non-transitory computer readable medium of claim 35, wherein the operations further comprise:

quantifying at least one inflow and at least one outflow to the portion of the renal arteries.

37. The non-transitory computer readable medium of claim 36, further comprising:

determining inlet and outlet boundary conditions using the quantified at least one inflow and at least one outflow to the portion of the renal arteries.

38. The non-transitory computer readable medium of claim 37, wherein the flow rates are measured using cross-sectional areas of the portion of the renal arteries and the aorta.

39. The non-transitory computer readable medium of claim 36, wherein quantifying at least one inflow and at least one outflow to the portion of the renal arteries comprises:

measuring flow rates corresponding to inlet and outlet positions of the portion of the renal arteries and aorta.

40. The non-transitory computer readable medium of claim 36, wherein the medical image data comprises a magnetic resonance imaging (MRI) image.

41. The non-transitory computer readable medium of claim 36, wherein quantifying at least one inflow and at least one outflow to the portion of the renal arteries comprises:

determining flow information in a lumen of the portion of the renal arteries using the patient-specific anatomical model.

42. The non-transitory computer readable medium of claim 41, wherein estimating patient-specific boundary conditions of the computational model for a plurality of physiological states of the patient comprises:

estimating the patient-specific boundary conditions for each of the plurality of physiological states using a respective patient-specific anatomic model extracted from medical image data acquired at each of the plurality of physiological states.

43. The non-transitory computer readable medium of claim 41, wherein estimating patient-specific boundary conditions of the computational model for a plurality of physiological states of the patient comprises:

estimating patient-specific boundary conditions for a rest state using the patient-specific anatomical model extracted from medical image data acquired at a rest state; and

estimating patient-specific boundary conditions for a hyperemic state using the estimated patient-specific boundary conditions for the rest state.

44. The non-transitory computer readable medium of claim 35, wherein estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries using the patient-specific anatomical model comprises:

estimating patient-specific boundary conditions of the computational model for a plurality of physiological states of the patient.

45. The non-transitory computer readable medium of claim 35, wherein calculating at least one hemodynamic quantity characterizing functional severity of a renal stenosis region using the simulated blood flow and pressure in the portion of the renal arteries comprises:

calculating a pressure drop across the renal stenosis region using the simulated blood flow and pressure.

46. The non-transitory computer readable medium of claim 35, wherein calculating at least one hemodynamic quantity characterizing functional severity of a renal stenosis region using the simulated blood flow and pressure in the portion of the renal arteries comprises:

calculating fractional flow reserve (FFR) for the renal stenosis region using the simulated blood flow and pressure.

47. The non-transitory computer readable medium of claim 35, wherein the computational model comprises one-dimensional computational models representing the renal arteries of the patient.

48. The non-transitory computer readable medium of claim 35, wherein the computational model comprises a reduced order stenosis pressure-drop model representing the renal stenosis region coupled to a one-dimensional computational model representing a renal artery.

49. The non-transitory computer readable medium of claim 48, wherein the reduced order stenosis pressure-drop model calculates a pressure drop across the renal stenosis region as a function of the velocity through the stenosis region.

50. The non-transitory computer readable medium of claim 35, wherein the computational model comprises a full-order three-dimensional computational model of the renal stenosis region, coupled to a one-dimensional computational model representing a renal artery.

51. The non-transitory computer readable medium of claim 35, wherein the computational model comprises lumped models representing microvasculature, each lumped model being coupled to a termination of a computational model representing a respective renal artery.