PREOPERATIVE PLANNING AND ASSOCIATED INTRAOPERATIVE REGISTRATION FOR A SURGICAL SYSTEM

• US 20190321105A1
• Filed: 06/10/2019
• Published: 10/24/2019
• 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
• Granted Patent: US 11,229,485 B2
• Time in Patent Office: 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 implant position and orientation data for use in planning an arthroplasty procedure on a patient bone comprising a lateral femur area, proximal femur area, and a posterior femur area, the method comprising:

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

generating a three-dimensional patient femur model from the patient data, the patient femur model comprising a surface boundary and a cortex region, the patient femur model being in a three-dimensional coordinate system with an X-axis in a medial-lateral direction, a Y-axis in an anterior-posterior direction with the +Y-axis pointing towards the posterior femur area, and a Z-axis in a superior-inferior direction with the +Z axis pointing towards the proximal femur area;

obtaining a three-dimensional femoral implant model comprising an anterior flange portion having a superior edge and an anterior bone resection contact surface being planar and adjacent the superior edge;

determining a position and orientation of the femoral implant model relative to the patient femur model;

extending a haptic plane coplanar with the anterior bone resection contact surface, the haptic plane comprising a superior boundary positioned superior of the superior edge of the anterior flange portion of the femoral implant model;

identifying a series of points on the superior boundary of the haptic plane;

projecting a vector along the Y-axis from each of the series of points to a corresponding surface of the surface boundary of the patient femur model;

determining that notching occurs based on a length and a direction of a smallest of the vectors; and

generating implant component position and orientation data based on the determined position and orientation of the femoral implant model relative to the patient femur model, the implant component position and orientation data configured to be utilized by a navigation system during the arthroplasty procedure.

2. The method of claim 1, wherein notching occurs when:

the length of the smallest of the vectors is equal to or greater than 0 mm; and

the direction of the smallest of the vectors is opposite of the +Y-axis of the coordinate system.

3. The method of claim 1, wherein no notching occurs when:

the length of the smallest of the vectors is greater than 0 mm; and

the direction of the smallest of the vectors is in a same direction as the +Y-axis of the coordinate system.

4. The method of claim 1, wherein the length is based on a perceivable depth of notching.

5. The method of claim 1, wherein the series of points are equally spaced along the superior boundary of the haptic plane.

6. The method of claim 5, wherein the series of points are equally spaced based upon a radius of curvature at or near the cortex region of the patient femur model.

7. The method of claim 5, wherein the series of points are equally spaced based upon a clinically relevant depth of perceivable notching.

8. The method of claim 5, wherein the series of points are equally spaced based upon:

a radius of curvature at or near the cortex region of the patient femur model; and

a clinically relevant depth of perceivable notching.

9. The method of claim 1, wherein the series of points are equally spaced about 3.15 mm apart.

10. The method of claim 1, wherein the patient data is captured using a medical imaging machine.

11. 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.

12. A method of generating implant position and orientation data for use in planning an arthroplasty procedure on a patient bone comprising a lateral femur area, proximal femur area, and a posterior femur area, 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 femur model from the patient data;

obtaining a three-dimensional femoral implant model comprising an anterior flange portion having an associated haptic resection object having a superior boundary edge;

determining a position and orientation of the femoral implant model relative to the patient femur model;

determining that notching occurs based on an intersection of the superior boundary edge and the three-dimensional patient femur model; and

generating implant component position and orientation data based on the determined position and orientation of the femoral implant model relative to the patient femur model, the implant component position and orientation data configured to be utilized by a navigation system during the arthroplasty procedure.

13. The method of claim 12, wherein the three-dimensional patient femur model comprises a surface boundary and a cortex region, the patient femur model being in a three-dimensional coordinate system with an X-axis in a medial-lateral direction, a Y-axis in an anterior-posterior direction with the +Y-axis pointing towards the posterior femur area, and a Z-axis in a superior-inferior direction with the +Z axis pointing towards the proximal femur area;

the method further comprising;

identifying a series of points on the superior boundary edge of the haptic resection object;

projecting a vector along the Y-axis from each of the series of points to a corresponding surface of the surface boundary of the patient femur model; and

determining that notching occurs based on a length and a direction of a smallest of the vectors.

14. The method of claim 13, wherein notching occurs when:

the length of the smallest of the vectors is equal to or greater than 0 mm; and

the direction of the smallest of the vectors is opposite of the +Y-axis of the coordinate system.

15. The method of claim 13, wherein no notching occurs when:

the length of the smallest of the vectors is greater than 0 mm; and

the direction of the smallest of the vectors is in a same direction as the +Y-axis of the coordinate system.

16. The method of claim 13, wherein the length is based on a perceivable depth of notching.

17. The method of claim 13, wherein the series of points are equally spaced along the superior boundary edge.

18. The method of claim 17, wherein the series of points are equally spaced based upon a radius of curvature at or near the cortex region of the patient femur model.

19. The method of claim 17, wherein the series of points are equally spaced based upon a clinically relevant depth of perceivable notching.

20. The method of claim 17, wherein the series of points are equally spaced based upon:

a radius of curvature at or near the cortex region of the patient femur model; and

a clinically relevant depth of perceivable notching.

21. The method of claim 13, wherein the series of points are equally spaced about 3.15 mm apart.

22. The method of claim 12, wherein the navigation system operates in conjunction with an autonomous robot or a surgeon-assisted device in performing the arthroplasty procedure.