Method and System for Functional Assessment of Renal Artery Stenosis from Medical Images

• US 20150065864A1
• Filed: 09/04/2014
• Published: 03/05/2015
• Est. Priority Date: 09/04/2013
• Status: Active Grant

• Current Assignee: Siemens Healthineers AG (Siemens AG)
• Original Assignee: Siemens Healthcare GMBH (Siemens AG)
• Inventors: Sharma, Puneet, Rapaka, Saikiran, Mihalef, Viorel, Kamen, Ali
• Granted Patent: US 9,629,563 B2
• Time in Patent Office: Days
• US Class Current: 600/416
• CPC Class Codes: A61B 2576/023 for the heart
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0263 using NMR
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: G01R 33/56316 involving phase contrast techniques
• CPC Class Codes: G01R 33/5635 Angiography, e.g. contrast-enhanced angiography [CE-MRA] or time-of-flight angiography [TOF-MRA]
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing

Abstract

A method and system for non-invasive assessment of renal artery stenosis is disclosed. A patient-specific anatomical model of at least a portion of the renal arteries and aorta is generated from medical image data of a patient. Patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries and aorta are estimated based on the patient-specific anatomical model. Blood flow and pressure are simulated in the portion of the renal arteries and aorta using the computational model based on the patient-specific boundary conditions. At least one hemodynamic quantity characterizing functional severity of a renal stenosis region is calculated based on the simulated blood flow and pressure in the portion of the renal arteries and aorta.

Claims

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

generating a patient-specific anatomical model of at least a portion of the renal arteries and aorta from medical image data of a patient;

estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries and aorta based on the patient-specific anatomical model;

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

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

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 and aorta.

3. The method of claim 2, wherein estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries and aorta based on the patient-specific anatomical model comprises:

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 and aorta.

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

measuring flow rates in each of a plurality of 2D flow slices corresponding to inlet and outlet positions of the portion of the renal arteries and aorta.

5. The method of claim 4, wherein the plurality of 2D flow slices comprise a first 2D flow slice that is a supra-renal cross-section of the aorta, a second 2D flow slice that is a infra-renal cross-section of the aorta, a third 2D flow slice that is a cross-section of a target renal artery distal to the renal stenosis region, and a fourth 2D flow slice that is a cross-section of a non-target renal artery.

6. The method of claim 4, wherein each of the plurality of 2D flow slices is a 2D phase-contrast magnetic resonance imaging (PCMRI) 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 and aorta comprises:

masking a flow image of the patient using the patient-specific anatomical model to obtain flow information in a lumen of the portion of the renal arteries and aorta.

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 and aorta based on 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 based on 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 based on 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 based on 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 based on the simulated blood flow and pressure in the portion of the renal arteries and aorta comprises:

calculating a pressure drop across the renal stenosis region based on 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 based on the simulated blood flow and pressure in the portion of the renal arteries and aorta comprises:

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

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

14. The method of claim 1, wherein the computational model comprises a reduced order stenosis pressure-drop model representing 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 sum of a viscous term, a turbulent term, and an inertance term.

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 microvascular beds, each coupled to a termination of a one-dimensional computational model representing a respective renal artery.

18. An apparatus for assessment of renal artery stenosis, comprising:

means for generating a patient-specific anatomical model of at least a portion of the renal arteries and aorta from medical image data of a patient;

means for estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries and aorta based on the patient-specific anatomical model;

means for simulating blood flow and pressure in the portion of the renal arteries and aorta using the computational model based on the patient-specific boundary conditions; and

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

19. The apparatus of claim 18, further comprising:

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

20. The apparatus of claim 19, wherein the means for estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries and aorta based on the patient-specific anatomical model comprises:

means for 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 and aorta.

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

means for measuring flow rates in each of a plurality of 2D flow slices corresponding to inlet and outlet positions of the portion of the renal arteries and aorta.

22. The apparatus of claim 21, wherein the plurality of 2D flow slices comprise a first 2D flow slice that is a supra-renal cross-section of the aorta, a second 2D flow slice that is a infra-renal cross-section of the aorta, a third 2D flow slice that is a cross-section of a target renal artery distal to the renal stenosis region, and a fourth 2D flow slice that is a cross-section of a non-target renal artery.

23. The apparatus of claim 21, wherein each of the plurality of 2D flow slices is a 2D phase-contrast magnetic resonance imaging (PCMRI) image.

24. The apparatus of claim 19, wherein the means for quantifying at least one inflow and at least one outflow to the portion of the renal arteries and aorta comprises:

means for masking a flow image of the patient using the patient-specific anatomical model to obtain flow information in a lumen of the portion of the renal arteries and aorta.

25. The apparatus of claim 18, wherein the means for estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries and aorta based on the patient-specific anatomical model comprises:

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

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

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

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

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

means for estimating patient-specific boundary conditions for a hyperemic state based on the estimated patient-specific boundary conditions for the rest state.

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

means for calculating a pressure drop across the renal stenosis region based on the simulated blood flow and pressure.

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

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

30. The apparatus of claim 18, wherein computational model comprises one-dimensional computational models representing the renal arteries and aorta of the patient.

31. The method of claim 18, wherein the computational model comprises a reduced order stenosis pressure-drop model representing renal stenosis region coupled to a one-dimensional computational model representing a renal artery.

32. The apparatus of claim 31, wherein the reduced order stenosis pressure-drop model calculates a pressure drop across the renal stenosis region as a sum of a viscous term, a turbulent term, and an inertance term.

33. The apparatus of claim 18, 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.

34. The apparatus of claim 18, wherein the computational model comprises lumped models representing microvascular beds, each coupled to a termination of a one-dimensional computational model representing a respective renal artery.

35. A non-transitory computer readable medium storing computer program instructions for assessment of renal artery stenosis, the computer program instruction 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 renal arteries and aorta from medical image data of a patient;

estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries and aorta based on the patient-specific anatomical model;

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

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

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 and aorta.

37. The non-transitory computer readable medium of claim 36, wherein estimating patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries and aorta based on the patient-specific anatomical model comprises:

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 and aorta.

38. 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 and aorta comprises:

measuring flow rates in each of a plurality of 2D flow slices corresponding to inlet and outlet positions of the portion of the renal arteries and aorta.

39. The non-transitory computer readable medium of claim 38, wherein the plurality of 2D flow slices comprise a first 2D flow slice that is a supra-renal cross-section of the aorta, a second 2D flow slice that is a infra-renal cross-section of the aorta, a third 2D flow slice that is a cross-section of a target renal artery distal to the renal stenosis region, and a fourth 2D flow slice that is a cross-section of a non-target renal artery.

40. The non-transitory computer readable medium of claim 38, wherein each of the plurality of 2D flow slices is a 2D phase-contrast magnetic resonance imaging (PCMRI) 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 and aorta comprises:

masking a flow image of the patient using the patient-specific anatomical model to obtain flow information in a lumen of the portion of the renal arteries and aorta.

42. 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 and aorta based on the patient-specific anatomical model comprises:

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

43. The non-transitory computer readable medium of claim 42, 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 based on a respective patient-specific anatomic model extracted from medical image data acquired at each of the plurality of physiological states.

44. The non-transitory computer readable medium of claim 42, 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 based on 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 based on the estimated patient-specific boundary conditions for the rest state.

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 based on the simulated blood flow and pressure in the portion of the renal arteries and aorta comprises:

calculating a pressure drop across the renal stenosis region based on 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 based on the simulated blood flow and pressure in the portion of the renal arteries and aorta comprises:

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

47. The non-transitory computer readable medium of claim 35, wherein computational model comprises one-dimensional computational models representing the renal arteries and aorta 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 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 sum of a viscous term, a turbulent term, and an inertance term.

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 microvascular beds, each coupled to a termination of a one-dimensional computational model representing a respective renal artery.