Methods for determining meniscal size and shape and for devising treatment
View Patent ↗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.
1. A method for designing a system for repairing a joint of a patient comprising:
acquiring at least one of an isotropic image data set or near isotropic image data set for the joint;
segmenting data of at least one articular surface of the joint; and
converting the segmented image data into a patient-specific portion of a component of the system, wherein the patient-specific portion includes at least one patient-specific dimension or shape parameter.
2. The method of claim 1 , wherein the patient specific portion is a computer-readable model.
3. The method of claim 1 , further including creating a computer-readable model of the component.
4. The method of claim 1 , wherein the articular surface includes a subchondral bone surface.
5. The method of claim 1 , wherein the articular surface includes a cartilage surface.
6. The method of claim 5 , wherein the cartilage surface includes a diseased or damaged cartilage surface.
7. The method of claim 1 , wherein the joint is a knee joint and the system includes a tibial implant for repairing the knee joint.
8. The method of claim 1 , wherein the joint is a knee joint and the system includes a femoral implant for repairing the knee joint.
9. The method of claim 1 , wherein the joint is a hip joint and the system includes an implant for repairing the hip joint.
10. A method for designing a system for repairing a knee joint of a patient comprising:
acquiring at least one of an isotropic image data set or near isotropic image data set for the knee joint;
segmenting data of at least one articular surface of the knee joint; and
converting the segmented image data into a patient-specific portion of a component of the system, wherein the patient-specific portion includes at least one patient-specific dimension or shape parameter of a tibia, a femur, or both of the knee joint.
11. The method of claim 10 , wherein the patient-specific dimension or shape parameter includes a medio-lateral width of one or both femoral condyles of the knee joint.
12. The method of claim 11 , wherein the patient-specific dimension or shape parameter includes a medio-lateral width of the lateral femoral condyle of the knee joint.
13. The method of claim 11 , wherein the patient-specific dimension or shape parameter includes a medio-lateral width of the lateral femoral condyle of the knee joint.
14. The method of claim 10 , wherein the patient-specific dimension or shape parameter includes a measurement of a tibial plateau of the knee joint.
15. The method of claim 10 , wherein the patient-specific dimension or shape parameter includes a measurement of a tibial spine of the knee joint.
16. The method of claim 10 , wherein the patient-specific dimension or shape parameter is selected from the group consisting of: a tibial bone dimension, a tibial cartilage measurement including thickness and/or shape, a femoral condyle bone dimension, a femoral cartilage measurement including thickness and/or shape, a patellar bone dimension, a patellar cartilage dimension including thickness and/or shape, a measurement of a ligament of the knee joint, and any combination thereof.
17. The method of claim 16 , wherein the tibial bone dimension is selected from the group consisting of a maximum anterior-posterior distance, a maximum medial-lateral distance, a maximum distance from the tibial spine to the edge, a width of a tibial spine, a height of a tibial spines, an area of tibial plateau occupied a tibial spine, a depth of a tibial plateau, a 2D shape of a tibial plateau, a 3D shape of a tibial plateau, and any combination thereof.
18. The method of claim 16 , wherein the femoral bone dimension is selected from the group consisting of a maximum anterior-posterior distance, a maximum superior-inferior distance, a maximum medial-lateral distance, a maximum distance from a trochlea to the medial or lateral edge; a width of an intercondylar notch, a depth of an intercondylar notch, a curvature at a select region along one or both femoral condyles, a 2D of a femoral condyle, a 3D shape of a femoral condyle, and any combination thereof.
19. The method of claim 16 , wherein the measurement of the ligament of the knee joint includes a size, length, or shape of the ligament.
20. A method for selecting a system for repairing a joint of a patient comprising:
acquiring at least one of an isotropic image data set or near isotropic image data set for the joint;
segmenting data of at least one articular surface of the joint;
converting the segmented image data into a patient-specific portion of a component of the system, wherein the patient-specific portion includes at least one patient-specific dimension or shape parameter, and
selecting a component from pre-made components having a corresponding portion that closely matches the patient-specific portion.
21. The method of claim 20 , wherein the step of selecting includes selecting a computer-readable model of the selected component from pre-made components.