PREOPERATIVELY PLANNING AN ARTHROPLASTY PROCEDURE AND GENERATING A CORRESPONDING PATIENT SPECIFIC ARTHROPLASTY RESECTION GUIDE

• US 20100256479A1
• Filed: 04/14/2010
• Published: 10/07/2010
• Est. Priority Date: 12/18/2007
• Status: Active Grant

• Current Assignee: Howmedica Osteonics Corp. (Stryker Corporation)
• Original Assignee: Otismed Corporation (Stryker Corporation)
• Inventors: Santarella, Michael, Song, Keun, Park, Ilwhan, Mishin, Oleg
• Granted Patent: US 8,737,700 B2
• Time in Patent Office: Days
• US Class Current: 600/410
• CPC Class Codes: A61B 17/15 Guides therefor arrangements for guiding straight saw blades in general B23D51/025
• CPC Class Codes: A61B 17/155 Cutting femur
• CPC Class Codes: A61B 17/157 Cutting tibia
• CPC Class Codes: A61B 17/1703 using imaging means, e.g. by X-rays
• CPC Class Codes: A61B 17/1725 for applying transverse screws or pins through intramedullary nails or pins
• CPC Class Codes: A61B 17/1739 specially adapted for particular parts of the body
• CPC Class Codes: A61B 17/1742 for the hip
• CPC Class Codes: A61B 17/1757 for the spine
• CPC Class Codes: A61B 17/1764 for the knee
• CPC Class Codes: A61B 2034/108 Computer aided selection or customisation of medical implants or cutting guides
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/4528 Joints A61B5/4533, A61B5/4538 take precedence
• CPC Class Codes: A61B 5/4851 Prosthesis assessment or monitoring
• CPC Class Codes: A61B 6/03 Computed tomography [CT] echo-tomography A61B8/14
• CPC Class Codes: B33Y 50/00 Data acquisition or data processing for additive manufacturing
• CPC Class Codes: B33Y 80/00 Products made by additive manufacturing

Abstract

Methods of manufacturing a custom arthroplasty resection guide or jig are disclosed herein. For example, one method may include: generating MRI knee coil two dimensional images, wherein the knee coil images include a knee region of a patient; generating MRI body coil two dimensional images, wherein the body coil images include a hip region of the patient, the knee region of the patient and an ankle region of the patient; in the knee coil images, identifying first locations of knee landmarks; in the body coil images, identifying second locations of the knee landmarks; run a transformation with the first and second locations, causing the knee coil images and body coil images to generally correspond with each other with respect to location and orientation.

Claims

1. A method of manufacturing a custom arthroplasty resection guide, the method comprising:

generating MRI knee coil two dimensional images, wherein the knee coil images include a knee region of a patient;

generating MRI body coil two dimensional images, wherein the body coil images include a hip region of the patient, the knee region of the patient and an ankle region of the patient;

in the knee coil images, identifying first locations of knee landmarks;

in the body coil images, identifying second locations of the knee landmarks;

running a transformation with the first and second locations, causing the knee coil images and body coil images to generally correspond with each other with respect to location and orientation.

2. The method of claim 1, wherein the transformation employs an Iterative Closest Point algorithm or gradient descent optimization.

3. The method of claim 1, wherein the transformation causes the knee coil images to reposition in a global coordinate system to the location and orientation of the body coil images.

4. The method of claim 1, further comprising identifying in at least one coronal view of the body coil images a hip center, a knee center and an ankle center.

5. The method of claim 4, further comprising:

forming a three dimensional restored bone model from data associated with the knee coil images, the restored bone model being generally representative of the patient'"'"'s knee in a predeteriorated state;

performing preoperative planning with the restored bone model; and

updating the location of the hip center, knee center and ankle center relative to the restored bone model on account of a restored bone model position in a global coordinate system being impacted during the preoperative planning.

6. The method of claim 5, wherein the preoperative planning includes a joint analysis wherein the restored bone model position in the global coordinate system is manipulated to adjust a joint gap of the restored bone model.

7. The method of claim 5, further comprising:

a) providing to a medical professional in a two dimensional coronal view;

i) information associated with the updated hip, knee and ankle centers; and

ii) at least one of the restored bone model as preoperatively planned or a three dimensional implant model as preoperatively planned, wherein the medical professional is associated with the treatment of the patient; and

b) updating the preoperative planning based on feedback received from the medical professional regarding the two dimensional coronal view.

8. The method of claim 7, wherein the information associated with the updated hip, knee and ankle centers includes at least one of a femoral mechanical axis, a tibial mechanical axis, a hip center, a knee center or an ankle center.

9. The method of claim 7, further comprising employing data associated with the updated preoperative planning to manufacture the custom arthroplasty resection guide.

10. The method of claim 1, further comprising targeting MRI scanning near a center of at least one of a hip, knee or ankle.

11. The method of claim 10, wherein the center of the at least one of a hip, knee or ankle is determined from at least one of a sagittal or axial view.

12. A method of manufacturing a custom arthroplasty resection guide, the method comprising:

preoperatively plan in a three dimensional computer environment a proposed post surgical joint geometry for a joint, wherein the proposed post surgical joint geometry is a natural alignment joint geometry that is generally representative of the joint prior to degeneration;

provide a two dimensional view of the proposed post surgical joint geometry to a physician;

employ feedback received from the physician regarding the two dimensional view to arrive at a finalized post surgical joint geometry that is at least one of;

a) the natural alignment joint geometry;

b) a zero degree mechanical axis alignment joint geometry, or somewhere between a) and b).

13. The method of claim 12, wherein the two dimensional view includes a coronal view.

14. The method of claim 12, further comprising employing data associated with the finalized post surgical joint geometry to manufacture the custom arthroplasty resection guide.

15. The method of claim 12, wherein the joint includes a knee joint.

16. The method of claim 12, wherein the two dimensional coronal view of the proposed post surgical joint geometry includes at least one of a femoral mechanical axis, a tibial mechanical axis, a hip center, a knee center or an ankle center.

17. A method of manufacturing a custom arthroplasty resection guide, the method comprising:

a) identify in a computer environment hip, knee and ankle centers in a first set of two dimensional images;

b) generate in a computer environment a three dimensional knee model from a second set of two dimensional images;

c) cause the three dimensional knee model and hip, knee and ankle centers to be positioned relative to each other in a global coordinate system generally as if the three dimensional knee model were generated from the first set of two dimensional images;

d) preoperatively plan an arthroplasty procedure with the three dimensional knee model of step c); and

e) at least one of maintain or reestablish the positional relationship established in step c) between the three dimensional knee model and the hip, knee and ankle centers to address any positional changes in the global coordinate system for the three dimensional knee model during the preoperatively planning of step d).

18. The method of claim 17, further comprising generating the first set of two dimensional images via MRI body coil imaging.

19. The method of claim 18, further comprising generating the second set of two dimensional images via MRI knee coil imaging.

20. The method of claim 17, wherein the hip, knee and ankle centers are identified in step a) in at least one coronal view of the first set of two dimensional images.

21. The method of claim 17, wherein step c) includes:

determining a first set of locations in the first set of two dimensional images for a set of knee landmarks;

determining a second set of locations in the second set of two dimensional images for the set of knee landmarks; and

running a transformation process for the first and second sets of locations to generally positionally match the first and second sets of locations in the global coordinate system.

22. The method of claim 21, wherein the transformation employs an Iterative Closest Point algorithm or gradient descent optimization.

23. The method of claim 21, wherein the transformation causes the second set of two dimensional images to reposition in the global coordinate system to the location and orientation of the first set of two dimensional images.

24. The method of claim 17, wherein step c) includes:

determining a first set of locations in the first set of two dimensional images for a set of knee landmarks;

determining a second set of locations on the three dimensional knee model for the set of knee landmarks; and

running a transformation process for the first and second sets of locations to generally positionally match the first and second sets of locations in the global coordinate system.

25. The method of claim 24, wherein the transformation employs an Iterative Closest Point algorithm or gradient descent optimization.

26. The method of claim 24, wherein the transformation causes at least one of the second set of two dimensional images or the three dimensional knee model to reposition in the global coordinate system to the location and orientation of the first set of two dimensional images.

27. The method of claim 17, wherein step c) includes:

determining a first spline along a contour of a bone in the first set of two dimensional images; and

at least one of;

     1) determining a second spline along the contour of the bone in the second set of two dimensional images and running a transformation process for the first and second splines to generally positionally match the first and second splines in the global coordinate system;

or

     2) running a transformation process that causes a portion of the three dimensional knee model corresponding to the spline to generally positionally match the spline in the global coordinate system.

28. The method of claim 27, wherein the transformation employs an Iterative Closest Point algorithm or gradient descent optimization.

29. The method of claim 27, wherein the transformation causes at least one of the second set of two dimensional images or the three dimensional knee model to reposition in the global coordinate system to the location and orientation of the first set of two dimensional images.

30. The method of claim 17, wherein step c) includes:

determining a first image intensity variation in the first set of two dimensional images;

determining a second image intensity variation in the second set of two dimensional images; and

running a transformation process that causes a first image intensity variation to generally positionally match the second image intensity variation in the global coordinate system.

31. The method of claim 30, wherein the transformation employs an Iterative Closest Point algorithm or gradient descent optimization.

32. The method of claim 30, wherein the transformation causes at least one of the second set of two dimensional images or the three dimensional knee model to reposition in the global coordinate system to the location and orientation of the first set of two dimensional images.

33. The method of claim 17, further comprising:

generating a two dimensional coronal snapshot of the three dimensional knee model and information associated with the hip, knee and ankle centers in the positional relationship of step e);

providing the two dimensional snapshot to a physician for review;

receive physician input regarding a preoperative plan reflected in the two dimensional coronal snapshot; and

at least one of update or maintain the preoperative plan in view of the received physician input, resulting in a finalized preoperative plan.

34. The method of claim 33, further comprising employing data associated with the finalized preoperative plan to manufacture the custom arthroplasty resection guide.

35. The method of claim 33, wherein the preoperative planning of step d) results in a natural alignment joint geometry, and the finalized preoperative plan results in:

i) the natural alignment joint geometry;

ii) a neutral alignment joint geometry;

or iii) an joint alignment somewhere between i) and ii).