Joint and cartilage diagnosis, assessment and modeling

• US 20070015995A1
• Filed: 04/25/2006
• Published: 01/18/2007
• Est. Priority Date: 09/14/1998
• Status: Active Grant

• Current Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford University)
• Original Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford University)
• Inventors: Lang, Philipp, Steines, Daniel, Alexander, Eugene, Andriacchi, Thomas
• Granted Patent: US 9,289,153 B2
• Time in Patent Office: Days
• US Class Current: 600/407
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2576/02 specially adapted for a particular organ or body part
• CPC Class Codes: A61B 5/0036 including treatment, e.g., using an implantable medical device, ablating, ventilating
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• 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 5/1078 by moulding
• CPC Class Codes: A61B 5/4514 Cartilage
• CPC Class Codes: A61B 5/4528 Joints A61B5/4533, A61B5/4538 take precedence
• CPC Class Codes: A61B 5/4585 Evaluating the knee
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: G01R 33/50 based on the determination of relaxation times , e.g. T1 measurement by IR sequences; T2 measurement by multiple-echo sequences
• CPC Class Codes: G01R 33/56 Image enhancement or correction, e.g. subtraction or averaging techniques , e.g. improvement of signal-to-noise ratio and resolution
• CPC Class Codes: G01R 33/5608 Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels image data processing or generation, in general G06T
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/187 involving region growing; involving region merging; involving connected component labelling

Abstract

Methods are disclosed for assessing the condition of a cartilage in a joint and assessing cartilage loss, particularly in a human knee. The methods include converting an image such as an MRI to a three dimensional map of the cartilage. The cartilage map can be correlated to a movement pattern of the joint to assess the affect of movement on cartilage wear. Changes in the thickness of cartilage over time can be determined so that therapies can be provided. The amount of cartilage tissue that has been lost, for example as a result of arthritis, can be estimated.

Claims

1. A method of assessing a joint disease, the method comprising:

obtaining an electronic image of a joint;

electronically evaluating said image to obtain at least one of volume, area, thickness, curvature, geometry, shape, biochemical contents, signal intensity and relaxation time of normal and/or diseased tissue; and

determining one or more axes related to said joint.

2. The method according to claim 1, wherein said axis is an anatomic axis.

3. The method according to claim 1, wherein said axis is a biomechanical axis.

4. The method according to claim 1, wherein obtaining an electronic image includes performing an MRI.

5. The method according to claim 1, wherein obtaining an electronic image includes performing a CT.

6. The method according to claim 5, wherein performing said CT includes performing a spiral CT.

7. The method according to claim 1, wherein obtaining an electronic image includes performing an ultrasound.

8. The method according to claim 1, wherein obtaining an electronic image includes performing an x-ray.

9. The method according to claim 1, wherein obtaining an electronic image includes using a contrast agent.

10. The method according to claim 1, further comprising creating at least one of a cast or physical model or mold of all or portions of said joint.

11. The method of claim 1, further comprising guiding a treatment as a function of said electronically evaluating and said determining an axis.

12. The method of claim 10, wherein said guiding includes optimizing the alignment of a treatment.

13. The method of claim 11, wherein said optimizing of the alignment optimizes biomechanical forces applied to the joint.

14. A method of assessing a joint disease, the method comprising:

obtaining an electronic image of a joint;

electronically evaluating said image to obtain at least one of volume, area, thickness, curvature, geometry, shape, biochemical contents, signal intensity and relaxation time of normal and/or diseased tissue;

creating at least one of a cast, a physical model, and a mold of all or a portion of said joint; and

evaluating one or more movement patterns of said joint.

15. The method of claim 14, wherein said evaluating of said movement pattern includes testing said joint in at least one or more flexion angles.

16. The method of claim 14, wherein said evaluating of said movement pattern includes testing said joint in at least one or more extension angles.

17. The method of claim 14, wherein said evaluating of said movement pattern includes testing said joint in at least one or more abduction angles.

18. The method of claim 14, wherein said evaluating of said movement pattern includes testing said joint in at least one or more adduction angles.

19. The method of claim 14, wherein said evaluating of said movement pattern includes testing said joint in at least one or more rotation angles.

20. A method of assessing a joint disease, the method comprising:

obtaining an electronic image of a joint;

electronically evaluating said image to obtain at least one of volume, area, thickness, curvature, geometry, shape, biochemical contents, signal intensity and relaxation time of normal and/or diseased cartilage; and

creating at least one of a cast, physical model, and a mold of all or a portion of said joint.

21. A method of assessing a joint disease, the method comprising:

obtaining an electronic image of a joint;

electronically evaluating said image to obtain at least one of volume, area, thickness, curvature, geometry, shape, biochemical contents, signal intensity and relaxation time of normal and/or diseased cartilage and subchondral bone; and

creating at least one of a cast, a physical model, and a mold of all or a portion of said joint.

22. A method of assessing a joint disease, the method comprising:

obtaining an electronic image of a joint;

electronically evaluating said image to obtain at least one of volume, area, thickness, curvature, geometry, shape, biochemical contents, signal intensity or relaxation time of said joint;

segmenting cartilage or subchondral bone associated with the joint; and

creating at least one of a cast, physical model and mold of all or a portion of said joint.

23. The method of claim 22, wherein said segmention includes using at least one of an active contour algorithm, a livewire algorithm, thresholding, a seed growing algorithm, a texture based algorithm and a model based segmentation algorithm.