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

• US 20110214279A1
• Filed: 04/13/2011
• Published: 09/08/2011
• 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, Mishin, Oleg, Park, Ilwhan
• Granted Patent: US 8,617,171 B2
• Time in Patent Office: Days
• US Class Current: 29/592
• CPC Class Codes: A61B 17/122 Clamps or clips , e.g. for the umbilical cord for the vas deferens A61F6/206
• CPC Class Codes: A61B 17/1675 for the knee
• CPC Class Codes: A61B 17/1764 for the knee
• CPC Class Codes: A61B 2034/102 Modelling of surgical devices, implants or prosthesis
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• 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 6/505 for diagnosis of bone
• CPC Class Codes: A61F 2/3859 Femoral components
• CPC Class Codes: A61F 2/389 Tibial components A61F2/3868 takes precedence
• CPC Class Codes: A61F 2/4657 Measuring instruments used for implanting artificial joints for surgical instruments A61B90/06
• CPC Class Codes: A61F 2002/4633 for selection of endoprosthetic joints or for pre-operative planning
• CPC Class Codes: A61F 2002/4658 for measuring dimensions, e.g. length
• CPC Class Codes: A61F 2002/4668 for measuring angles
• CPC Class Codes: B33Y 80/00 Products made by additive manufacturing
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06T 19/00 Manipulating 3D models or images for computer graphics
• CPC Class Codes: G06T 19/20 Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/10088 : Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/20221 : Image fusion; Image merging
• CPC Class Codes: G06T 2207/30008 : Bone
• CPC Class Codes: G06T 2207/30052 : Implant; Prosthesis
• CPC Class Codes: G06T 2210/41 : Medical
• CPC Class Codes: G06T 2219/008 : Cut plane or projection plane definition
• CPC Class Codes: G06T 2219/2004 : Aligning objects, relative positioning of parts
• CPC Class Codes: G06T 5/50 : using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 7/0012 : Biomedical image inspection
• CPC Class Codes: G06T 7/33 : using feature-based methods
• CPC Class Codes: G06V 10/751 : Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
• CPC Class Codes: G06V 2201/03 : Recognition of patterns in medical or anatomical images
• CPC Class Codes: G06V 2201/033 : of skeletal patterns
• CPC Class Codes: Y10T 29/49 : Method of mechanical manufacture

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 a three dimensional femur bone model from MRI knee coil two dimensional images, wherein the knee coil images include a knee region of a patient;

identifying a hip center and a femur knee center in MRI body coil two dimensional images, wherein the body coil images include a hip region of the patient and the knee region of the patient;

causing the three dimensional femur bone model and hip center and femur knee center to generally correspond with each other with respect to location and orientation;

defining relative to the three dimensional femur bone model a femoral mechanical axis via the femur knee center and the hip center;

identifying a most distal condylar point of the three dimensional femur bone model;

defining a distal plane that is orthogonal to the femoral mechanical axis in a coronal view of the three dimensional femur bone model, wherein the distal plane also passes through the most distal condylar point;

defining a resection plane that is parallel to the distal plane and proximally offset from the distal plane; and

using data associated with the resection plane to define a resection guide in the custom arthroplasty resection guide.

2. The method of claim 1, wherein the three dimensional femur bone model includes at least one of a femur bone only model or a femur arthritic model.

3. The method of claim 1, wherein a proximal offset distance between the distal plane and the resection plane is based on a dimension of a candidate femoral implant.

4. The method of claim 1, wherein in causing the three dimensional femur bone model and hip center and femur knee center to generally correspond with each other with respect to location and orientation in the knee coil images, the method further includes:

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

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

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.

5. The method of claim 4, wherein the transformation employs an Iterative Closest Point algorithm or gradient descent optimization.

6. The method of claim 4, 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.

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

generating a three dimensional tibia bone model from MRI knee coil two dimensional images, wherein the knee coil images include a knee region of a patient;

identifying an ankle center and a tibia knee center in MRI body coil two dimensional images, wherein the body coil images include an ankle region of the patient and the knee region of the patient;

causing the three dimensional tibia bone model and ankle center and tibia knee center to generally correspond with each other with respect to location and orientation;

defining relative to the three dimensional tibia bone model a tibial mechanical axis via the tibia knee center and the ankle center;

identifying a condylar point of the three dimensional tibia bone model;

defining a proximal plane that is orthogonal to the tibial mechanical axis in a coronal view of the three dimensional tibia bone model, wherein the proximal plane also passes through a condylar point;

defining a resection plane that is parallel to the proximal plane and distally offset from the proximal plane; and

using data associated with the resection plane to define a resection guide in the custom arthroplasty resection guide.

8. The method of claim 7, wherein the three dimensional tibia bone model includes at least one of a tibia bone only model or a tibia arthritic model.

9. The method of claim 7, wherein a distal offset distance between the proximal plane and the resection plane is based on a dimension of a candidate tibial implant.

10. The method of claim 7, wherein in causing the three dimensional tibia bone model and ankle center and tibia knee center to generally correspond with each other with respect to location and orientation in the knee coil images, the method further includes:

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

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

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.

11. The method of claim 10, wherein the transformation employs an Iterative Closest Point algorithm or gradient descent optimization.

12. The method of claim 10, 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.

13. 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) via a method including;

defining a mechanical axis relative to the three dimensional knee model via a pair of points including the knee center and at least one of the hip center or ankle center; and

defining a resection plane parallel to, and offset from, a reference plane that;

     1) is orthogonal to the mechanical axis in a coronal view and

     2) extends through a condylar point on the three dimensional knee model; and

e) using data associated with the resection plane to define a resection guide in the custom arthroplasty resection guide.

14. The method of claim 13, further comprising generating the first set of two dimensional images via MRI body coil imaging.

15. The method of claim 14, further comprising generating the second set of two dimensional images via MRI knee coil imaging.

16. The method of claim 13, 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.

17. The method of claim 13, 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.

18. The method of claim 17, wherein the transformation employs an Iterative Closest Point algorithm or gradient descent optimization.

19. The method of claim 17, 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.

20. The method of claim 13, wherein the three dimensional knee model includes a three dimensional femur bone model and the mechanical axis is a femoral mechanical axis.

21. The method of claim 20, wherein the condylar point includes a most distal femoral condylar point.

22. The method of claim 13, wherein the three dimensional knee model includes a three dimensional tibia bone model and the mechanical axis is a tibial mechanical axis.

23. The method of claim 22, wherein the condylar point includes a tibial condylar point.

24. The method of claim 13, wherein the three dimensional knee model includes at least one of a bone-only model or an arthritic model.

25. The method of claim 24, wherein the arthritic model is an overestimated model.