Methods for determining meniscal size and shape and for devising treatment

• US 20040147927A1
• Filed: 11/07/2003
• Published: 07/29/2004
• Est. Priority Date: 11/07/2002
• Status: Active Grant

• Current Assignee: Conformis Incorporated
• Original Assignee: Imaging Therapeutics, Inc. (Conformis Incorporated)
• Inventors: Lang, Philipp, Linder, Barry J., Steines, Daniel, Vissa, Bhaskar Rao, Tsougarakis, Konstantinos
• Granted Patent: US 8,932,363 B2
• Time in Patent Office: Days
• US Class Current: 606/53
• CPC Class Codes: A61B 2034/108 Computer aided selection or customisation of medical implants or cutting guides
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• 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 5/4514 Cartilage
• CPC Class Codes: A61B 5/4528 Joints A61B5/4533, A61B5/4538 take precedence
• CPC Class Codes: A61F 2/30756 Cartilage endoprostheses A61F2/3603 takes precedence
• CPC Class Codes: A61F 2/30942 for designing or making customized prostheses, e.g. using templates, CT or NMR scans, finite-element analysis or CAD-CAM techniques
• CPC Class Codes: A61F 2/32 for the hip
• CPC Class Codes: A61F 2/34 Acetabular cups
• CPC Class Codes: A61F 2/36 Femoral heads ; Femoral endoprostheses
• CPC Class Codes: A61F 2/38 for elbows or knees
• CPC Class Codes: A61F 2/3804 for elbows
• CPC Class Codes: A61F 2/40 for shoulders
• CPC Class Codes: A61F 2/4202 for ankles
• CPC Class Codes: A61F 2/4241 for hands, e.g. fingers
• CPC Class Codes: A61F 2/4261 for wrists
• CPC Class Codes: A61F 2/44 for the spine, e.g. vertebrae, spinal discs
• CPC Class Codes: A61F 2002/30133 kidney-shaped or bean-shaped
• CPC Class Codes: A61F 2002/30894 inclined obliquely with respect to each other
• CPC Class Codes: A61F 2002/30943 using mathematical models
• CPC Class Codes: A61F 2002/30948 : using computerized tomography, i.e. CT scans
• CPC Class Codes: A61F 2002/30952 : using CAD-CAM techniques or NC-techniques
• CPC Class Codes: A61F 2230/0015 : Kidney-shaped, e.g. bean-shaped
• CPC Class Codes: G06T 7/0012 : Biomedical image inspection
• CPC Class Codes: Y10S 623/911 : Bone

Abstract

The present invention relates to methods for determining meniscal size and shape for use in designing therapies for the treatment of various joint diseases. The invention uses an image of a joint that is processed for analysis. Analysis can include, for example, generating a thickness map, a cartilage curve, or a point cloud. This information is used to determine the extent of the cartilage defect or damage and to design an appropriate therapy, including, for example, an implant. Adjustments to the designed therapy are made to account for the materials used.

Claims

1. A method to treat a defect in a joint comprising:

obtaining an image of a joint; and

generating at least one of a thickness map and a curvature map.

2. The method of claim 1 further comprising one or more of the steps of:

pre-processing the image obtained using a non-linear diffusion filter;

assigning a list of features to each oriented edge between at least two pixel boundaries;

converting the features into cost values; and

calculating a single cost value.

3. The method of claim 2 further comprising the step of:

determining the likelihood of a cost value being a part of a cartilage boundary.

4. The method of claim 1 or claim 3 further comprising the step of:

determining a contour of a cartilage object by selecting at least a first pixel and a second pixel.

5. The method of claim 4 wherein the first pixel and the second pixel are automatically selected.

6. The method of claim 4 wherein the first pixel and the second pixel are selected by an operator.

7. The method of claim 1 further comprising the step of calculating cartilage thickness.

8. The method of claim 7 wherein the step of calculating cartilage thickness is performed using a 3D Euclidean Transform.

9. The method of claim 7 wherein the step of calculating cartilage thickness is performed by decomposing the calculation into a series of three one-dimensional transformations.

10. The method of claim 9 further wherein the one-dimensional transforms are squared to obtain a set of distances.

11. The method of claim 8 wherein a thickness of cartilage for a point on an outer cartilage surface is calculated based on the square root of S_abc.

12. The method of claim 1 further wherein an implant is designed from the generated thickness map.

13. The method of claim 1 wherein the defect is a result of at least one of cartilage disease, bone damage, trauma, and degeneration.

14. The method of claim 9, 11, or 12 wherein the thickness is a measured thickness and is used to design an implant for treating the defect in the joint.

15. The method of claim 14 wherein the measured thickness is adjusted on at least a portion of the implant based on a quality of a material selected to manufacture the implant.

16. The method of claim 15 wherein the measured thickness is adjusted to a final implant thickness on at least a portion of the implant by a factor of from 0.2 to 1.5 of the measured thickness.

17. An implant suitable for treating a defect in a joint wherein the implant is designed by:

obtaining an image of a joint; and

generating at least one of a thickness map and a curvature map.

18. The method of claim 17 further comprising one or more of the steps of:

processing the image obtained using a non-linear diffusion filter;

assigning a list of features to each oriented edge between at least two pixel boundaries;

converting the features into cost values; and

calculating a single cost value.

19. The method of claim 18 further comprising the step of:

determining the likelihood of a cost value being a part of a cartilage boundary.

20. The method of claim 17 or claim 18 further comprising the step of:

determining a contour of a cartilage object by selecting at least a first pixel and a second pixel.

21. The method of claim 20 wherein the first pixel and the second pixel are automatically selected.

22. The method of claim 20 wherein the first pixel and the second pixel are selected by an operator.

23. The method of claim 17 further comprising the step of calculating cartilage thickness.

24. The method of claim 23 wherein the step of calculating cartilage thickness is performed using a 3D Euclidean Transform.

25. The method of claim 23 wherein the step of calculating cartilage thickness is performed by decomposing the calculation into a series of three one-dimensional transformations.

26. The method of claim 25 further wherein the one-dimensional transforms are squared to obtain a set of distances.

27. The method of claim 24 wherein a thickness of cartilage for a point on an outer cartilage surface is calculated based on the square root of S_abc.

28. The method of claim 17 wherein the defect is a result of at least one of cartilage disease, bone damage, trauma, and degeneration.

29. The method of claim 25, 27 or 28 wherein the thickness is a measured thickness and is used to design an implant for treating the defect in the joint.

30. The method of claim 29 wherein the measured thickness is adjusted on at least a portion of the implant based on a quality of a material selected to manufacture the implant.

31. The method of claim 29 wherein the measured thickness is adjusted to a final implant thickness on at least a portion of the implant by a factor of from 0.2 to 1.5 of the measured thickness.

32. A method to treat a defect in a joint comprising:

obtaining an image of a joint;

processing the image obtained using a non-linear diffusion filter; and

generating a cartilage curve.

33. The method of claim 32 further comprising the steps of:

fitting a local bi-cubic surface path to the cartilage curve.

34. The method of claim 32 wherein the bi-cubic surface patch is automatically selected.

35. The method of claim 32 wherein the bi-cubic surface patch is selected by an operator.

36. The method of claim 32 further comprising the step of calculating cartilage thickness.

37. The method of claim 36 wherein the step of calculating cartilage thickness is performed using a 3D Euclidean Transform.

38. The method of claim 36 wherein the step of calculating cartilage thickness is performed by decomposing the calculation into a series of three one-dimensional transformations.

39. The method of claim 38 further wherein the one-dimensional transforms are squared to obtain a set of distances.

40. The method of claim 37 wherein a thickness of cartilage for a point on an outer cartilage surface is calculated based on the square root of S_abc.

41. The method of claim 32 further wherein an implant is designed from the cartilage curve.

42. The method of claim 38, 40 or 41 wherein the thickness is a measured thickness and is used to design an implant for treating the defect in the joint.

43. The method of claim 42 wherein the measured thickness is adjusted on at least a portion of the implant based on a quality of a material selected to manufacture the implant.

44. The method of claim 42 wherein the measured thickness is adjusted to a final implant thickness on at least a portion of the implant by a factor of from 0.2 to 1.5 of the measured thickness.

45. An implant for correcting a defect in a joint wherein the implant size is determined by estimating meniscal dimensions based on measurements of at least one of cartilage and bone landmarks within the joint.

46. The implant of claim 45 wherein the joint is a knee joint.

47. The implant of claim 46 wherein the measurement is selected from the group consisting of:

a length of a medial meniscus;

a length of a medial femoral condyle;

a length of a lateral meniscus;

a length of a lateral femoral condyle;

a length of a medial tibial plateau;

a length of a lateral tibial plateau;

a width of a medial meniscus;

a width of a medial femoral condyle;

a width of a lateral meniscus;

a width of a lateral femoral condyle;

a width of a medial tibial plateau;

a width of a lateral tibial plateau;

a highest point of a medial meniscus;

a highest point of a medial tibial spine;

a highest point of a lateral meniscus;

a highest point of a lateral tibial spine;

a highest point of a femoral condyle; and

a highest point of a lateral femoral condyle, cartilage thickness and cartilage curvature and 3D cartilage shape.

48. The implant of claim 45 wherein the joint is an ankle joint.

49. The implant of claim 48 wherein the measurement is selected from the group consisting of:

the diameter of a talus, the length of a talus, the width of a talus, the curvature of a talus, the cartilage thickness of a talus, the subchondral bone thickness of a talus, the diameter of a calcaneus, the length of a calcaneus, the width of a calcaneus, the curvature of a calcaneus, the cartilage thickness of a calcaneus, the subchondral bone thickness of a calcaneus.

50. The implant of claim 45 wherein the joint is a hip joint.

51. The implant of claim 50 wherein the measurement is selected from the group consisting of the mediolateral diameter of an acetabular fossa, the anteroposterior diameter of the acetabular fossa, the superoinferior diameter of the acetabular fossa, the curvature of the acetabular fossa anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the thickness of the articular cartilage of the acetabular fossa anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the thickness of the subchondral bone of the acetabular fossa anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the mediolateral diameter of a femoral head, the anteroposterior diameter of the femoral head, the superoinferior diameter of the femoral head, the curvature of the femoral head anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the thickness of the articular cartilage of the femoral head anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the thickness of the subchondral bone of the femoral head anteriorly, posteriorly, superiorly, inferiorly, medially or laterally.

52. The implant of claim 45 wherein the joint is a shoulder joint.

53. The implant of claim 52 wherein the measurement is selected from the group consisting of the mediolateral diameter of a glenoid fossa, the anteroposterior diameter of the glenoid fossa, the superoinferior diameter of the glenoid fossa, the curvature of the glenoid fossa anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the thickness of the articular cartilage of the glenoid fossa anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the thickness of the subchondral bone of the glenoid fossa anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the mediolateral diameter of a humeral head, the anteroposterior diameter of the humeral head, the superoinferior diameter of the humeral head, the curvature of the humeral head anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the thickness of the articular cartilage of the humeral head anteriorly, posteriorly, superiorly, inferiorly, medially or laterally, the thickness of the subchondral bone of the humeral head anteriorly, posteriorly, superiorly, inferiorly, medially or laterally.

54. The implant of claim 45 wherein the joint is an elbow joint.

55. The implant of claim 54 wherein the measurement is selected from the group consisting of the diameter of a distal humerus, the depth of a distal humerus, the width of a distal humerus, the curvature of a distal humerus, the cartilage thickness of a distal humerus, the subchondral bone thickness of a distal humerus, the diameter of a radius, the depth of a radius, the width of a radius, the curvature of a radius, the cartilage thickness of a radius, the subchondral bone thickness of a radius, the diameter of an ulna, the depth of an ulna, the width of an ulna, the curvature of an ulna, the cartilage thickness of an ulna, the subchondral bone thickness of an ulna

56. The implant of claim 45 wherein the joint is a wrist joint.

57. The implant of claim 56 wherein the measurement is selected from the group consisting of the diameter of a radius, the depth of a radius, the width of a radius, the curvature of a radius, the cartilage thickness of a radius, the subchondral bone thickness of a radius, the diameter of an ulna, the depth of an ulna, the width of an ulna, the curvature of an ulna, the cartilage thickness of an ulna, the subchondral bone thickness of an ulna, the diameter of a proximal carpal row, the depth of a proximal carpal row, the width of a proximal carpal row, the curvature of a proximal carpal row, the cartilage thickness of a proximal carpal row, the subchondral bone thickness of a proximal carpal row, the diameter of a scaphoid or lunate, the depth of a scaphoid or lunate, the width of a scaphoid or lunate, the curvature of a scaphoid or lunate, the cartilage thickness of a scaphoid or lunate, the subchondral bone thickness of a scaphoid or lunate, the diameter of a triangular fibrocartilage, the depth of a triangular fibrocartilage, the width of a triangular fibrocartilage, the curvature of a triangular fibrocartilage, the thickness of a triangular fibrocartilage.

58. The implant of claim 45 wherein the joint is a finger joint.

60. The implant of claim 45 wherein the joint is in the spine.

61. The implant of claim 60 wherein the measurement is selected from the group consisting of the anteroposterior vertebral dimension, the mediolateral vertebral dimension, the height of the vertebral body anteriorly, centrally or posteriorly, the diameter of the pedicle(s), the width of the pedicle(s), the length of the pedicle(s), the diameter or radius of a facet joint(s), the volume of a facet joint(s), the 3D shape of a facet joint(s), the curvature of a facet joint(s), the dimensions of the posterior elements, the dimensions of the spinal canal, the 3D shape of the vertebral body.

59. The implant of claim 59 wherein the measurement is selected from the group consisting of the depth of a phalanx or metacarpal, the width of a phalanx or metacarpal, the diameter of a phalanx or metacarpal, the curvature of a phalanx or metacarpal, the cartilage thickness of a phalanx or metacarpal, the subchondral bone thickness of a phalanx or metacarpal.

62. An implant for treating a joint wherein the implant size is determined by estimating articular dimensions based on measurements of cartilage or bone landmarks within the joint.

63. A technique for designing an anatomically correct interpositional arthroplasty system for a joint comprising the following steps:

obtaining data of a cartilage or bone surface of the joint;

obtaining data of one or more meniscal surface(s);

combination of cartilage or bone surface data and meniscal surface data.

64. The method of claim 63 wherein data for existing bone joints is used to adjust the size of the meniscal model.

65. A method to treat a defect in a joint comprising:

obtaining an image of a joint; and

measuring at least one of curvature and thickness.

66. The method of claim 65 further comprising one or more of the steps of:

pre-processing the image obtained using a non-linear diffusion filter;

assigning a list of features to each oriented edge between at least two pixel boundaries;

converting the features into cost values; and

calculating a single cost value.

67. The method of claim 66 further comprising the step of:

determining the likelihood of a cost value being a part of a cartilage boundary.

68. The method of claim 65 or claim 67 further comprising the step of:

determining a contour of a cartilage object by selecting at least a first pixel and a second pixel.

69. The method of claim 68 wherein the first pixel and the second pixel are automatically selected.

70. The method of claim 68 wherein the first pixel and the second pixel are selected by an operator.

71. The method of claim 65 further wherein the step of measuring thickness is performed by calculating cartilage thickness.

72. The method of claim 71 wherein the step of calculating cartilage thickness is performed using a 3D Euclidean Transform.

73. The method of claim 71 wherein the step of calculating cartilage thickness is performed by decomposing the calculation into a series of three one-dimensional transformations.

74. The method of claim 73 further wherein the one-dimensional transforms are squared to obtain a set of distances.

75. The method of claim 72 wherein a thickness of cartilage for a point on an outer cartilage surface is calculated based on the square root of S_abc.

76. The method of claim 65 further wherein an implant is designed from the measurement of at least one of curvature and thickness.

77. The method of claim 65 wherein the defect is a result of at least one of cartilage disease, bone damage, trauma, and degeneration.

78. The method of claim 73, 75 or 76 wherein the thickness is a measured thickness and is used to design an implant for treating the defect in the joint.

79. The method of claim 78 wherein the measured thickness is adjusted on at least a portion of the implant based on a quality of a material selected to manufacture the implant.

80. The method of claim 79 wherein the measured thickness is adjusted to a final implant thickness on at least a portion of the implant by a factor of from 0.2 to 1.5 of the measured thickness.

81. An implant suitable for treating a defect in a joint wherein the implant is designed by:

obtaining an image of a joint; and

measuring at least one of curvature and thickness.

82. The method of claim 81 further comprising one or more of the steps of:

processing the image obtained using a non-linear diffusion filter;

assigning a list of features to each oriented edge between at least two pixel boundaries;

converting the features into cost values; and

calculating a single cost value.

83. The method of claim 82 further comprising the step of:

determining the likelihood of a cost value being a part of a cartilage boundary.

84. The method of claim 81 or claim 82 further comprising the step of:

determining a contour of a cartilage object by selecting at least a first pixel and a second pixel.

85. The method of claim 84 wherein the first pixel and the second pixel are automatically selected.

86. The method of claim 84 wherein the first pixel and the second pixel are selected by an operator.

87. The method of claim 81 further comprising the step of calculating cartilage thickness.

88. The method of claim 87 wherein the step of calculating cartilage thickness is performed using a 3D Euclidean Transform.

89. The method of claim 87 wherein the step of calculating cartilage thickness is performed by decomposing the calculation into a series of three one-dimensional transformations.

90. The method of claim 89 further wherein the one-dimensional transforms are squared to obtain a set of distances.

91. The method of claim 88 wherein a thickness of cartilage for a point on an outer cartilage surface is calculated based on the square root of S_abc.

92. The method of claim 81 wherein the defect is a result of at least one of cartilage disease, bone damage, trauma, and degeneration.

93. The method of claim 89, 91 or 92 wherein the thickness is a measured thickness and is used to design an implant for treating the defect in the joint.

94. The method of claim 93 wherein the measured thickness is adjusted on at least a portion of the implant based on a quality of a material selected to manufacture the implant.

95. The method of claim 93 wherein the measured thickness is adjusted to a final implant thickness on at least a portion of the implant by a factor of from 0.2 to 1.5 of the measured thickness.

96. An implant for correcting a defect in a joint wherein the implant size is determined by estimating meniscal dimensions based on measurements of at least one of a thickness and curvature.

97. An implant for correcting a defect in a joint wherein the implant size is determined by estimating meniscal dimensions based on measurements of at least one of a thickness map and a curvature map.