Computer-aided-design of skeletal implants

• US 7,747,305 B2
• Filed: 12/09/2005
• Issued: 06/29/2010
• Est. Priority Date: 06/11/2003
• Status: Active Grant

• Current Assignee: Osteoplastics, LLC
• Original Assignee: Case Western Reserve University
• Inventors: Dean, David, Min, Kyoung-June, Ratcheson, Robert A.
• Primary Examiner(s): Smith; Ruth S
• Application Number:
  US11/299,138
• Publication Number:
  US 20060094951A1
• Time in Patent Office: 1,663 Days
• Field of Search: 600/407, 600/410, 600/416, 600/425, 382/128, 382/131, 345418-420, 345/581, 345/589, 345/619, 345/620, 345/625, 345/441, 345/442, 623/11.11, 623/16.11, 623/17.19, 623/23.64, 623/901, 703/1, 703/11
• US Class Current: 600/407
• CPC Class Codes: A61F 2/2875 Skull or cranium A61F2/2803 and A61F2/3099 take 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 2002/30943 using mathematical models
• CPC Class Codes: A61F 2002/30952 using CAD-CAM techniques or NC-techniques
• 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
• CPC Class Codes: G05B 2219/45168 Bone prosthesis
• CPC Class Codes: G06T 17/10 Constructive solid geometry [CSG] using solid primitives, e.g. cylinders, cubes
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: Y10S 623/901 Method of manufacturing prosthetic device

Abstract

The present invention is directed to a computer aided design method for producing an implant for a patient prior to operation comprising the steps of: generating data with a non-invasive 3D (3-dimensional) scan of the patient'"'"'s defect site that digitally represents the area that will receive the implant; designing and validating an implant on a computer based on digital data generated from a volume image of the patient; and fabricating the implant based solely on the implant design data generated on computer.

Claims

1. A computer-aided design method for producing an implant for a patient prior to operation, the method comprising:

generating digital image data with a non-invasive three-dimensional (3D) volume scan of an anatomical region of the patient comprising a defect site that is to receive the implant;

generating a polygonal-mesh 3D surface image representing the anatomical region of the patient based on the digital image data;

defining a defect margin crestline describing the external boundary of the patient'"'"'s defect based on a curvature estimation on the polygonal-mesh 3D surface image;

generating a digital template of desired anatomy associated with the anatomical region;

performing a two-pass thin plate spline (TPS) warp on the digital template to register the digital template specifically to the patient;

generating a prototype implant surface based on the defect margin crestline and the registered template of the anatomical region, the prototype implant surface defining an outer surface of a 3D digital model of the implant;

generating at least one internal surface and at least one connecting surface with respect to the prototype implant surface to generate the 3D digital model of the implant; and

fabricating the implant based on the 3D digital model of the implant.

2. The method of claim 1, wherein the polygonal-mesh 3D surface image is of an entirety of the anatomical region that is represented by the digital image data, the method further comprising:

determining a 3D region of interest (ROI) on the polygonal-mesh 3D surface image of the anatomical region that includes only a region of the polygonal-mesh 3D surface image immediately adjacent to and surrounding the defect site; and

extracting the 3D ROI from the polygonal-mesh 3D surface image to generate a polygonal-mesh 3D surface image file of the 3D ROI;

wherein defining the defect margin crestline comprises defining the defect margin crestline on the 3D ROI.

3. The method of claim 2, wherein determining the 3D ROI comprises:

placing a plurality of seed landmarks in the region of the polygonal-mesh 3D surface image immediately adjacent to the defect site such that the seed landmarks are coplanar to define a best-fitting plane;

connecting consecutive ones of the plurality of seed landmarks based on a line equation; and

defining the 3D ROI as a 3D area of the polygonal-mesh 3D surface image that is enclosed within the connected plurality of seed landmarks.

4. The method of claim 1, wherein defining the defect margin crestline comprises:

determining a 3D surface curvature at each respective 3D surface point of the polygonal-mesh 3D surface image to generate the curvature estimate; and

generating color values corresponding to a magnitude of the 3D surface curvature at each respective 3D surface point of the polygonal-mesh 3D surface image.

5. The method of claim 4, wherein determining the 3D surface comprises:

defining an arc length between predefined starting and ending points defining a specified arc length for a parametric space curve along the polygonal-mesh 3D surface image; and

calculating a unit vector perpendicular to a tangent of the parametric space curve at each respective 3D surface point.

6. The method of claim 4, further comprising redistributing the color values in a histogram over an entire intensity scale to ascertain contrasts between low and high curvature of the respective 3D surface points.

7. The method of claim 4, further comprising:

placing seed landmarks at 3D surface points having highest curvature magnitudes based on the color values;

forming sectors on the polygonal-mesh 3D surface image based on the seed landmarks; and

executing a minimum-cost path traversal algorithm in each sector to determine a series of points defining the defect margin crestline.

8. The method of claim 1, wherein generating the digital template of the anatomical region comprises generating the digital template based on one of left-right mirroring of the anatomical region and providing a digital template that is an average of the anatomical region imaged on a plurality of patients.

9. The method of claim 8, wherein generating the digital template comprises implementing left-right mirroring of the anatomical region in response to the defect site being unilateral with respect to a plane separating left and right sides of the patient.

10. The method of claim 8, wherein generating the digital template comprises providing an average of the anatomical region that is an appropriate size and reoriented for a reference frame of the patient in response to the defect site spanning a plane separating left and right sides of the patient.

11. The method of claim 1, wherein generating the at least one internal surface and the at least one connecting surface comprises extending the prototype implant surface such that it spans a thickness of a body structure of the patient underlying the defect margin crestline based on the polygonal-mesh 3D surface image.

12. The method of claim 11, wherein extending the prototype implant surface comprises:

casting geometric rays from each point of the defect margin crestline internally in a normal direction of a best-fitting plane of seed landmarks that defines a 3D region of interest (ROI) of the anatomical region that includes the defect site; and

calculating a Euclidean distance between an origin of each geometric ray and the best-fitting plane.

13. The method of claim 1, wherein the prototype implant surface is configured as a triangular-mesh isosurface image, the method further comprising:

resampling the prototype implant surface to uniformly shape and space triangles associated with the triangular-mesh isosurface image;

implementing a surface smoothing algorithm to remove slice-edge artifact from the resampled prototype implant surface; and

implementing an articulation algorithm to articulate the surface-smoothed and resampled prototype implant surface to fit the defect margin crestline.

14. The method of claim 13, wherein implementing the surface smoothing algorithm comprises removing slice edge artifact in response to volume image slices having an inter-slice dimension that is larger than an in-slice pixel dimension.

15. The method of claim 1, wherein generating the at least one internal surface and the at least one connecting surface comprises generating connecting surfaces between the prototype implant surface and the internal surface with a taper-fit surface that is tapered between the prototype implant surface and the internal surface.

16. The method of claim 15, further comprising validating the 3D digital model of the implant with respect to contact of the taper-fit surface and the internal surface with adjacent bone and soft tissue structures prior to fabricating the implant.

17. The method of claim 16, wherein validating the 3D digital model of the implant comprises implementing a collision detection algorithm to verify seating of the taper-fit surface with adjacent bone structure and to verify non-collision with adjacent had and soft tissues.

18. The method of claim 1, further comprising selecting the defect site of the patient from at least one of a hard tissue element and a soft tissue element.

19. The method of claim 1, further comprising selecting the defect site of the patient as a cranial defect associated with the skull of the patient.