Preoperative planning and associated intraoperative registration for a surgical system

• US 10,357,315 B2
• Filed: 05/27/2016
• Issued: 07/23/2019
• Est. Priority Date: 05/27/2016
• Status: Active Grant

• Current Assignee: MAKO Surgical Corporation (Stryker Corporation)
• Original Assignee: MAKO Surgical Corporation (Stryker Corporation)
• Inventors: Otto, Jason Karl, Abbasi, Abdullah Zafar, Ikits, Milan, Perez, Daniel, Mu, Shang, Li, Xiping, Chang, Ta-Cheng
• Primary Examiner(s): Coley, Zade
• Application Number:
  US15/167,771
• Publication Number:
  US 20170340389A1
• Time in Patent Office: 1,152 Days
• 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 2034/108 Computer aided selection or customisation of medical implants or cutting guides
• CPC Class Codes: A61B 2034/2055 Optical tracking systems
• CPC Class Codes: A61B 2034/2068 using pointers, e.g. pointers having reference marks for determining coordinates of body points
• CPC Class Codes: A61B 2505/05 Surgical care
• CPC Class Codes: A61B 2576/02 specially adapted for a particular organ or body part
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 34/30 Surgical robots
• CPC Class Codes: A61B 34/32 operating autonomously
• CPC Class Codes: A61B 5/0037 Performing a preliminary scan, e.g. a prescan for identifying a region of interest
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• 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 5/1077 Measuring of profiles
• CPC Class Codes: A61F 2002/4662 for measuring penetration depth

Abstract

Aspects of the disclosure may involve a method of generating resection plane data for use in planning an arthroplasty procedure on a patient bone. The method may include: obtaining patient data associated with at least a portion of the patient bone, the patient data captured using a medical imaging machine; generating a three-dimensional patient bone model from the patient data, the patient bone model including a polygonal surface mesh; identifying a location of a posterior point on the polygonal surface mesh; creating a three-dimensional shape centered at or near the location; identifying a most posterior vertex of all vertices of the polygonal surface mesh that may be enclosed by the three-dimensional shape; using the most posterior vertex as a factor for determining a posterior resection depth; and generating resection data using the posterior resection depth, the resection data configured to be utilized by a navigation system during the arthroplasty procedure.

Claims

1. A method of generating resection plane data for use in planning an arthroplasty procedure on a patient bone, the method comprising:

obtaining patient data associated with at least a portion of the patient bone, the patient data captured using a medical imaging machine;

generating a three-dimensional patient bone model from the patient data, the patient bone model comprising a polygonal surface mesh;

identifying a location of a posterior point on the polygonal surface mesh;

creating a three-dimensional shape centered at or near the location;

identifying a most posterior vertex of all vertices of the polygonal surface mesh that are enclosed by the three-dimensional shape;

using the most posterior vertex as a factor for determining a posterior resection depth; and

generating resection data using the posterior resection depth, the resection data configured to be utilized by a navigation system during the arthroplasty procedure.

2. The method of claim 1, wherein the three-dimensional patient bone model is a three-dimensional patient femur model.

3. The method of claim 1, further comprising:

identifying a first location of a first posterior point on a first three-dimensional bone model; and

mapping the first location on the first three-dimensional bone model to the location on the three-dimensional patient bone model, wherein the first location is positionally correlated with the location.

4. The method of claim 3, wherein the first three-dimensional bone model is a generic bone model.

5. The method of claim 1, wherein the three-dimensional shape comprises a sphere with a radius of about 7 mm.

6. The method of claim 5, wherein the radius is multiplied by a scaling factor.

7. The method of claim 6, wherein the scaling factor is one of a medial-lateral or anterior-posterior size difference between the three-dimensional patient bone model and a generic bone model.

8. The method of claim 1, wherein the polygonal surface mesh is a triangular surface mesh.

9. The method of claim 1, wherein the three-dimensional shape comprises a sphere.

10. The method of claim 1, wherein the navigation system operates in conjunction with an autonomous robot or a surgeon-assisted device in performing the arthroplasty procedure.

11. A method of generating resection plane data for use in planning an arthroplasty procedure on a patient bone, the method comprising:

obtaining patient data associated with at least a portion of the patient bone, the patient data captured using a medical imaging machine;

generating a three-dimensional patient bone model from the patient data, the patient bone model comprising a polygonal surface mesh;

identifying a location of a distal point on the polygonal surface mesh;

creating a three-dimensional shape centered at or near the location;

identifying a most distal vertex of all vertices of the polygonal surface mesh that are enclosed by the three-dimensional shape;

determining if the most distal vertex is too close to a boundary of the three-dimensional shape;

using the most distal vertex as a basis for determining a distal resection depth if the most distal vertex is not too close to the boundary of the three-dimensional shape; and

generating resection data using the distal resection depth, the resection data configured to be utilized by a navigation system during the arthroplasty procedure.

12. The method of claim 11, wherein the three-dimensional shape comprises an ellipsoid oriented relative to the three-dimensional patient bone model such that Rx extends medial-lateral, Ry extends anterior-posterior, and Rz extends distal-proximal.

13. The method of claim 12, wherein Rx is about 7 mm, Ry is about 10 mm, and Rz is about 7 mm.

14. The method of claim 13, wherein the most distal vertex is too close to the boundary of the ellipsoid if a location of the most distal vertex is greater than 0.65 for the ellipsoid function:

f=x^2/a^2+y^2/b^2+z^2/c^2, wherein x is a difference in an x-direction between the first location and the most distal vertex, y is a difference in a y-direction between the first location and the most distal vertex, z is a difference in a z-direction between the first location and the most distal vertex, a is Rx, b is Ry, and c is Rz.

15. The method of claim 11, wherein the three-dimensional patient bone model is a three-dimensional patient femur model.

16. The method of claim 11, wherein the three-dimensional shape comprises an ellipsoid, a sphere, a prism, a cube, or a cylinder.

17. The method of claim 11, wherein the navigation system operates in conjunction with an autonomous robot or a surgeon-assisted device in performing the arthroplasty procedure.

18. A method of generating resection plane data for use in planning an arthroplasty procedure on a patient bone, the method comprising:

obtaining patient data associated with at least a portion of the patient bone, the patient data captured using a medical imaging machine;

generating a three-dimensional patient bone model from the patient data, the patient bone model comprising a polygonal surface mesh;

identifying a location of a distal point on the polygonal surface mesh;

creating a first three-dimensional shape centered at or near the location;

identifying a most distal vertex of all vertices of the polygonal surface mesh that are enclosed by the first three-dimensional shape;

determining if the most distal vertex is located on an osteophyte;

using the most distal vertex or an adjusted location of the most distal vertex as a basis for determining a distal resection depth based on whether or not the most distal vertex is located on the osteophyte; and

generating resection data using the distal resection depth, the resection data configured to be utilized by a navigation system during the arthroplasty procedure.

19. The method of claim 18, wherein determining if the most distal vertex is located on an osteophyte comprises creating a second three-dimensional shape positioned between the most distal vertex and the location.

20. The method of claim 19, further comprises identifying particular vertices of the polygonal surface mesh that are enclosed by the second three-dimensional shape, and using information associated with the particular vertices to determine if the distal vertex is located on an osteophyte.

21. The method of claim 20, wherein the information is a minimum and a maximum value in a direction associated with a presence of an osteophyte protruding from an articular surface.

22. The method of claim 19, further comprises identifying particular vertices of the polygonal surface mesh that are enclosed by the second three-dimensional shape, and using a minimum vertex value of one of the particular vertices enclosed by the second three-dimensional shape in a certain coordinate direction and a maximum vertex value of another one of the particular vertices enclosed by the second three-dimensional shape in the certain coordinate direction to determine if the distal vertex is located on an osteophyte.

23. The method of claim 22, further comprising determining the difference between the maximum vertex value and the minimum vertex value, and using the difference to determine the presence of an osteophyte.

24. The method of claim 23, further comprising using the difference to determine whether to increase or decrease a size of the sphere.

25. The method of claim 19, wherein the second three-dimensional shape comprises a sphere having a radius of about 2 mm and is centered 1 mm towards the location from the most distal vertex.

26. The method of claim 25, further comprising identifying particular vertices of the polygonal surface mesh that are enclosed by a boundary of the sphere, and determining a difference between a maximum vertex value of one of the particular vertices enclosed by the boundary in a certain coordinate direction and a minimum vertex value of another one of the particular vertices enclosed by the boundary in the certain coordinate direction.

27. The method of claim 19, wherein the second three-dimensional shape comprises a sphere.

28. The method of claim 18, wherein the first three-dimensional shape comprises an ellipsoid.

29. The method of claim 18, wherein the navigation system operates in conjunction with an autonomous robot or a surgeon-assisted device in performing the arthroplasty procedure.

30. A method of generating resection plane data for use in planning an arthroplasty procedure on a patient bone, the method comprising:

obtaining patient data associated with at least a portion of the patient bone;

generating a three-dimensional patient bone model from the patient data, the patient bone model oriented in a three-dimensional coordinate system and comprising a polygonal surface mesh;

identifying a particular direction in the three-dimensional coordinate system associated with a resection plane;

identifying a location on the polygonal surface mesh;

creating a surface at or near the location;

identifying a particular vertex of all vertices of the polygonal surface mesh that extends furthest beyond the surface in the particular direction;

using the particular vertex as a factor for determining a particular resection depth; and

generating resection data using the particular resection depth, the particular resection data configured to be utilized by a navigation system during the arthroplasty procedure.

31. The method of claim 30, wherein the surface is a plane.

32. The method of claim 30, wherein the surface is a three-dimensional shape.

33. The method of claim 32, wherein the three-dimensional shape is a sphere, ellipsoid, prism, or cube.

34. The method of claim 30, further comprising identifying a first location of a first posterior point on a first three-dimensional bone model;

and mapping the first location on the first three-dimensional bone model to the location on the three-dimensional patient bone model, wherein the first location is positionally correlated with the location.

35. The method of claim 34, wherein the first three-dimensional bone model is a generic bone model.

36. The method of claim 30, wherein the surface comprises a sphere with a radius of about 7 mm.

37. The method of claim 36, wherein the radius is multiplied by a scaling factor.

38. The method of claim 37, wherein the scaling factor is one of a medial-lateral or anterior-posterior size difference between the three-dimensional patient bone model and a generic bone model.

39. The method of claim 30, wherein the navigation system operates in conjunction with an autonomous robot or a surgeon-assisted device in performing the arthroplasty procedure.