Ultrasonic blood vessel measurement apparatus and method

• US 7,727,153 B2
• Filed: 10/28/2004
• Issued: 06/01/2010
• Est. Priority Date: 04/07/2003
• Status: Active Grant

• Current Assignee: FUJIFILM SonoSite, Inc. (Fujifilm Holdings Corporation)
• Original Assignee: Sonosite Incorporated (Fujifilm Holdings Corporation)
• Inventors: Fritz, Helmuth, Fritz, Terry
• Primary Examiner(s): Casler; Brian
• Assistant Examiner(s): KISH, JAMES M
• Application Number:
  US10/975,616
• Publication Number:
  US 20050096528A1
• Time in Patent Office: 2,042 Days
• Field of Search: 600/407, 600/408, 600/410, 600/425, 600/431, 600/436, 600/473, 600/476, 600/479, 600/437, 600/438, 600/442, 600/443, 600/462, 382/128, 382130-131, 382168-172, 382286-288
• US Class Current: 600/449
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 5/1075 for measuring dimensions by non-invasive methods, e.g. for determining thickness of tissue layer A61B8/0858 takes precedence
• CPC Class Codes: A61B 8/0858 involving measuring tissue layers, e.g. skin, interfaces
• CPC Class Codes: A61B 8/0891 for diagnosis of blood vessels
• CPC Class Codes: A61B 8/463 characterised by displaying multiple images or images and diagnostic data on one display composite display in devices for short-range imaging with acoustic waves G01S7/52074
• CPC Class Codes: A61B 8/565 involving data transmission via a network
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/66 of image moments or centre of gravity

Abstract

Disclosed are systems and methods for identifying various tissue structure aspects, such as boundaries of arterial walls, within an image, such as an ultrasound image. Various measurements may be made using information with respect to the identified aspects of tissue structure. For example, intima-media thickness measurements may be made. Additionally or alternatively, tissue structure aspects, such as plaque within an artery, may be characterized, such as by determining a density thereof. Various information, such as measurement datums, used in identification of aspects of tissue structure in one image may be stored and applied to subsequent images, such as images of a video sequence.

Claims

1. A method for characterizing an aspect of a tissue structure present in an image, said method comprising:

analyzing said image to identify said aspect of said tissue structure;

normalizing intensity information of said image by applying an adjustment factor to said intensity information, said adjustment factor being dependent upon known densities of one or more landmarks in a subject of said image;

determining density information for said aspect using said normalized intensity information; and

characterizing said aspect using said density information.

2. The method of claim 1, wherein said analyzing said image comprises:

analyzing an intensity gradient within said image.

3. The method of claim 1, wherein said analyzing said image comprises:

identifying a datum using image intensity information.

4. The method of claim 1, wherein said analyzing said image comprises:

identifying a tissue boundary using image intensity information.

5. The method of claim 1, wherein said one or more landmarks have a relatively consistent density from image to image.

6. The method of claim 5, wherein said one or more landmarks includes a lumen of a blood vessel.

7. The method of claim 5, wherein said one or more landmarks includes an adventitia of a blood vessel.

8. The method of claim 1, wherein said determining density information comprises:

determining an average intensity of said image within an area identified as said aspect to provide an average density.

9. The method of claim 1, wherein said determining density information comprises:

determining a peak intensity of said image within an area identified as said aspect to provide a peak density.

10. The method of claim 1, wherein said determining density information comprises:

determining a maximum intensity within and area identified as said aspect minus a minimum intensity within said area identified as said aspect to provide a density extent.

11. The method of claim 1, wherein said determining density information comprises:

determining an intensity histogram with respect to intensities within an area identified as said aspect to provide a density histogram.

12. The method of claim 1, wherein said determining density information comprises:

determining a standard deviation of intensities within an area identified as said aspect to provide a density variance.

13. The method of claim 1, wherein said determining density information comprises:

determining a centroid of intensities within an area identified as said aspect to provide a density centroid.

14. The method of claim 1. wherein said determining density information comprises:

determining a region of highest intensity within an area identified as said aspect to provide a densest region.

15. The method of claim 1, wherein said characterizing said aspect comprises:

comparing a density value to a database of density values to determine a condition associated with said tissue structure.

16. The method of claim 1, wherein said characterizing said aspect comprises:

comparing at least one of a thickness of said aspect, a size of said aspect, and a location of said aspect to a database to determine a relative condition of said tissue structure.

17. The method of claim 1, wherein said characterizing said aspect comprises:

comparing a density value to a historical database of density values associated with a patient of which said tissue structure is a part of to determine a change in said patient'"'"'s condition,

18. The method of claim 1, wherein said change in said patient'"'"'s condition comprises a rate of calcification of plaque.

19. The method of claim 1, wherein said tissue structure comprises a blood vessel.

20. The method of claim 1, wherein said tissue structure comprises a carotid artery.

21. The method of claim 1, wherein said aspect comprises plaque.

22. The method of claim 1, further comprising:

determining a total area of said aspect, wherein said characterizing said aspect further uses information with respect to said total area.

23. The method of claim 1, further comprising:

determining a relative position of said aspect with respect to another aspect of said tissue structure, wherein said characterizing said aspect further uses information with respect to said relative position.

24. The method of claim 1 wherein said subject of said image comprises said tissue structure.

25. The method of claim 1 wherein at least said normalizing is performed by a processor-based computing device.

26. The method of claim 25 wherein said determining density information is performed by said processor-based computing device.

27. The method of claim 26 wherein said analyzing is performed by said processor-based computing device.

28. The method of claim 27 wherein said characterizing is performed by said processor-based computing device.

29. The method of claim 1 wherein said image is generated by one of an ultrasound system, a magnetic resonance imaging system, and a radio frequency imaging system.

30. A method for characterizing an aspect of a tissue structure present in an image, said method comprising:

analyzing said image to identify said aspect of said tissue structure;

determining density information for said aspect by applying an adjustment factor to intensity information associated with said image, said adjustment factor being dependent upon known densities of one or more landmarks in said image that have a relatively consistent density from image to image; and

characterizing said aspect using said density information, said characterizing providing information with respect to a severity of a condition associated with said aspect of said tissue structure.

31. The method of claim 30, wherein said determining density information comprises:

determining an average intensity of said image within an area identified as said aspect to provide an average density.

32. The method of claim 30, wherein said determining density information comprises:

determining a peak intensity of said image within an area identified as said aspect to provide a peak density.

33. The method of claim 30, wherein said determining density information comprises:

determining a maximum intensity within and area identified as said aspect minus a minimum intensity within said area identified as said aspect to provide a density extent.

34. The method of claim 30, wherein said determining density information comprises:

determining an intensity histogram with respect to intensities within an area identified as said aspect to provide a density histogram.

35. The method of claim 30, wherein said determining density information comprises:

determining a standard deviation of intensities within an area identified as said aspect to provide a density variance.

36. The method of claim 30, wherein said determining density information comprises:

determining a centroid of intensities within an area identified as said aspect to provide a density centroid.

37. The method of claim 30, wherein said determining density information comprises:

determining a region of highest intensity within an area identified as said aspect to provide a densest region.

38. The method of claim 30, wherein said density information comprises information with respect to a hardness of said aspect of said tissue structure.

39. The method of claim 38, wherein said hardness is associated with calcification of said aspect of said tissue structure.

40. The method of claim 30, wherein said characterizing said aspect comprises:

referencing a database of similar aspects of tissue structure.

41. The method of claim 30, wherein said characterizing said aspect comprises:

referencing historical information to provide said information with respect to a severity of a condition.

42. The method of claim 30, wherein said analyzing said image comprises:

analyzing an intensity gradient within said image.

43. The method of claim 30, wherein said analyzing said image comprises:

identifying a datum using image intensity information.

44. The method of claim 30, wherein said analyzing said image comprises:

identifying a tissue boundary using image intensity information.

45. The method of claim 30 wherein said adjustment factor is dependent upon known densities of said one or more landmarks in a subject of said image.

46. The method of claim 45 wherein said known densities of said one or more landmarks comprise known densities of at least one of the following landmarks present in the subject of the image:

lumen of a blood vessel and adventitia of a blood vessel.

47. The method of claim 45 wherein said subject of said image comprises said tissue structure.

48. The method of claim 45 wherein said subject comprises at least a portion of a person to whom the image pertains, and wherein said subject has a relatively consistent density from person to person.

49. The method of claim 30 wherein at least one of said analyzing, determining, and characterizing is performed by a processor-based computing device.

50. The method of claim 49 wherein said image is generated by one of an ultrasound system, a magnetic resonance imaging system, and a radio frequency imaging system.

51. A system for characterizing an aspect of a tissue structure present in an image, said system comprising:

a processor-based system accepting input of a digital representation of said image, said processor-based system including circuitry operable to normalize intensity information of said digital representation of said image by applying an adjustment factor to said intensity information, said adjustment factor being dependent upon known densities of one or more landmarks in said image that have a relatively consistent density across a plurality of image subjects, said processor-based system also including circuitry operable to identify said aspect of said tissue structure within said digital representation of said image, said processor-based system also including circuitry operable to determine density information with respect to said aspect of said tissue structure using said normalized intensity information, and said processor-based system also including circuitry operable to characterize said aspect of said tissue structure as a function of said density information.

52. The system of claim 51, further comprising:

a display outputting said density information to a user.

53. The system of claim 51, further comprising:

a printer outputting said density information as a hard-copy report.

54. The system of claim 51, wherein said aspect of said tissue structure comprises an area of plaque.

55. The system of claim 54, wherein said plaque is characterized as a function of hardness.

56. The system of claim 51, wherein said tissue structure comprises a blood vessel

57. The system of claim 51, wherein said tissue structure comprises a carotid artery.

58. The system of claim 51, wherein said density information indicates a hardness of said aspect of said tissue structure.

59. The system of claim 51, wherein said characterization of said aspect of said tissue structure provides information with respect to a severity of a condition associated with said aspect of said tissue structure.

60. The system of claim 51, wherein said characterization of said aspect of said tissue structure correspond to a risk level associated with said aspect of said tissue structure.

61. The system of claim 51, further comprising:

a database of normalized intensity information for aspects of tissue structure associated with a plurality of individuals.

62. The system of claim 61, wherein said database further includes event history associated with said aspects of tissue structure.

63. The system of claim 61, wherein said normalized intensity information for aspects of tissue structure is normalized plaque values.

64. The system of claim 51 wherein said plurality of image subjects comprise a plurality of different persons.

65. The system of claim 51 wherein said known densities of said one or more landmarks comprise known densities of at least one of the following landmarks present in the image subject:

lumen of a blood vessel and adventitia of a blood vessel.

66. The system of claim 51 wherein said image is generated by one of an ultrasound system, a magnetic resonance imaging system, and a radio frequency imaging system.