Methods for determining meniscal size and shape and for devising treatment

• US 20040153079A1
• Filed: 11/07/2003
• Published: 08/05/2004
• Est. Priority Date: 11/07/2002
• Status: Active Grant

• Current Assignee: Conformis Incorporated
• Original Assignee: Imaging Therapeutics, Inc. (Conformis Incorporated)
• Inventors: Lang, Philipp, Linder, Barry J., Steines, Daniel, Vissa, Bhaskar Rao, Tsougarakis, Konstantinos
• Granted Patent: US 7,796,791 B2
• Time in Patent Office: Days
• US Class Current: 606/77
• 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 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 5/4514 Cartilage
• CPC Class Codes: A61B 5/4528 Joints A61B5/4533, A61B5/4538 take precedence
• CPC Class Codes: A61F 2/30756 Cartilage endoprostheses A61F2/3603 takes 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 2/32 for the hip
• CPC Class Codes: A61F 2/34 Acetabular cups
• CPC Class Codes: A61F 2/36 Femoral heads ; Femoral endoprostheses
• CPC Class Codes: A61F 2/38 for elbows or knees
• CPC Class Codes: A61F 2/3804 for elbows
• CPC Class Codes: A61F 2/40 for shoulders
• CPC Class Codes: A61F 2/4202 for ankles
• CPC Class Codes: A61F 2/4241 for hands, e.g. fingers
• CPC Class Codes: A61F 2/4261 for wrists
• CPC Class Codes: A61F 2/44 for the spine, e.g. vertebrae, spinal discs
• CPC Class Codes: A61F 2002/30133 kidney-shaped or bean-shaped
• CPC Class Codes: A61F 2002/30894 inclined obliquely with respect to each other
• CPC Class Codes: A61F 2002/30943 using mathematical models
• CPC Class Codes: A61F 2002/30948 : using computerized tomography, i.e. CT scans
• CPC Class Codes: A61F 2002/30952 : using CAD-CAM techniques or NC-techniques
• CPC Class Codes: A61F 2230/0015 : Kidney-shaped, e.g. bean-shaped
• CPC Class Codes: G06T 7/0012 : Biomedical image inspection
• CPC Class Codes: Y10S 623/911 : Bone

Abstract

The present invention relates to methods for determining meniscal size and shape for use in designing therapies for the treatment of various joint diseases. The invention uses an image of a joint that is processed for analysis. Analysis can include, for example, generating a thickness map, a cartilage curve, or a point cloud. This information is used to determine the extent of the cartilage defect or damage and to design an appropriate therapy, including, for example, an implant. Adjustments to the designed therapy are made to account for the materials used.

Claims

1. A technique for designing an anatomically correct interpositional arthroplasty system for a joint comprising the following steps:

fusion of at least two imaging planes for the joint; and

segmenting data of one or more meniscal surfaces of the joint.

2. The technique of claim 1 further including at least one of the following steps:

combining at least one of cartilage surface data and meniscal surface data to serve as a model for at least one surface of an implant;

compressing at least one section of a meniscal surface by a factor ranging from 0.2 to 0.99;

converting a point cloud data for a superior implant surface and an inferior implant surface into parametric surface data; and

cutting a parametric surface data set to determine a shape of an implant.

3. A technique for designing an anatomically correct arthroplasty system for a joint comprising the following steps:

fusion at least two imaging planes for the joint; and

segmenting data of one or more cartilage surfaces of the joint.

4. The technique of claim 3 further including at least one of the following steps:

combining at least one of cartilage surface data and meniscal surface data to serve as a model for at least one surface of an implant;

compressing at least one section of a meniscal surface by a factor ranging from 0.2 to 0.99;

converting a point cloud data for a superior implant surface and an inferior implant surface into parametric surface data; and

cutting a parametric surface data set to determine a shape of an implant.

5. A technique for designing an anatomically correct articular repair system for a joint comprising the following steps:

fusion of at least two imaging planes for the joint; and

segmenting data of at least one bone surface of the joint.

6. The technique of claim 5 further including at least one of the following steps:

combining at least one of cartilage surface data and meniscal surface data to serve as a model for at least one surface of an implant;

compressing at least one section of a meniscal surface by a factor ranging from 0.2 to 0.99;

converting a point cloud data for a superior implant surface and an inferior implant surface into parametric surface data; and

cutting a parametric surface data set to determine a shape of an implant.

7. A technique for designing an anatomically correct interpositional arthroplasty system for a joint comprising the following steps:

acquiring one of an isotropic data set and near isotropic data set for the joint; and

segmenting data of at least one meniscal surface of the joint.

8. The technique of claim 7 further including at least one of the following steps:

combining at least one of cartilage surface data and meniscal surface data to serve as a model for at least one surface of an implant;

compressing at least one section of a meniscal surface by a factor ranging from 0.2 to 0.99;

converting a point cloud data for a superior implant surface and an inferior implant surface into parametric surface data; and

cutting a parametric surface data set to determine a shape of an implant.

9. A technique for designing an anatomically correct arthroplasty system for a joint comprising the following steps:

acquiring at least one of an isotropic data set and a near isotropic data set for the joint; and

segmenting data of at least one cartilage surface of the joint.

10. The technique of claim 9 further including at least one of the following steps:

combining at least one of cartilage surface data and meniscal surface data to serve as a model for at least one surface of an implant;

compressing at least one section of a meniscal surface by a factor ranging from 0.2 to 0.99;

converting a point cloud data for a superior implant surface and an inferior implant surface into parametric surface data; and

cutting a parametric surface data set to determine a shape of an implant.

11. A technique for designing an anatomically correct articular repair system for a joint comprising the following steps:

acquiring at least one of an isotropic data set or near isotropic data set for the joint;

segmenting data of at least one bone surface of the joint.

12. The technique of claim 11 further including at least one of the following steps:

combining at least one of cartilage surface data and meniscal surface data to serve as a model for at least one surface of an implant;

compressing at least one section of a meniscal surface by a factor ranging from 0.2 to 0.99;

converting a point cloud data for a superior implant surface and an inferior implant surface into parametric surface data; and

cutting a parametric surface data set to determine a shape of an implant.