Methods of predicting musculoskeletal disease

• US 8,818,484 B2
• Filed: 11/17/2010
• Issued: 08/26/2014
• Est. Priority Date: 09/16/2002
• Status: Expired due to Term

• Current Assignee: Imatx, Inc. (Conformis Incorporated)
• Original Assignee: Imatx, Inc. (Conformis Incorporated)
• Inventors: Liew, Siau-Way, Steines, Daniel, Lang, Philipp
• Primary Examiner(s): Roy, Baisakhi
• Application Number:
  US12/948,276
• Publication Number:
  US 20110105885A1
• Time in Patent Office: 1,378 Days
• Field of Search: 600/407, 600/410, 600/425, 382/128, 382/110, 382/131, 382/132, 606/72
• US Class Current: 600/407
• CPC Class Codes: A61B 6/482 involving multiple energy imaging
• CPC Class Codes: A61B 6/505 for diagnosis of bone
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: A61B 6/583 using calibration phantoms
• CPC Class Codes: A61B 8/0875 for diagnosis of bone A61B5/4504 takes precedence
• CPC Class Codes: A61B 8/5223 for extracting a diagnostic or physiological parameter from medical diagnostic data for algorithms to analyse biomedical images G06T7/0012
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/20104 Interactive definition of region of interest [ROI]
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 5/00 Image enhancement or restoration
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

This invention is directed to methods of predicting bone or joint disease in a subject. The invention is also directed to methods of determining the effect of a candidate agent on any subject'"'"'s risk of developing bone or joint disease.

Claims

1. A method for assessing bone condition in a subject by obtaining information regarding one or more bone parameters from an image of the subject in a computer system, the method comprising:

(a) obtaining the image comprising image of a bone of the subject;

(b) defining two or more regions of interest (ROIs) in the image;

(c) analyzing a plurality of positions in the ROIs to determine one or more bone microarchitecture parameters and one or more bone macro-anatomy parameters;

(d) combining the parameters into a numerical index; and

(e) comparing the numerical index against a reference database.

2. The method of claim 1, wherein the ROIs are overlapping.

3. The method of claim 1, wherein the positions analyzed in the ROIs are at regular intervals in the image.

4. The method of claim 1, wherein the positions analyzed in the ROIs are at irregular intervals in the image.

5. The method of claim 1, wherein the positions analyzed are at regular intervals.

6. The method of claim 1, further including determining one or more biomechanical parameters of the bone of the subject.

7. The method of claim 1, wherein the image is two-dimensional.

8. The method of claim 7, wherein image is an x-ray image.

9. The method of claim 1, wherein the image is three-dimensional.

10. The method of claim 1, wherein the image is an electronic image.

11. The method of claim 1, wherein the subject is an osteoporosis subject.

12. A method of generating a map of one or more bone parameters, comprising:

(a) obtaining information on bone parameters according to the method of claim 1; and

(b) identifying regions of the image that exhibit similar parameter characteristics, thereby creating a parameter map of the image.

13. A method of predicting a fracture path in a subject, comprising:

(a) generating two or more parameter maps according to the method of claim 12;

(b) generating a composite parameter map from the two or more parameter maps of step (a); and

(c) analyzing the composite parameter map to identify possible fracture paths.

14. A method of determining the risk of fracture in a subject comprising:

(a) predicting a fracture path according to the method of claim 13; and

(b) evaluating one or more selected bone parameters along the predicted fracture path, thereby estimating the risk of fracture.

15. A method of predicting the risk of fracture in a subject comprising:

(a) generating a finite element model from one or more parameter maps obtained according to the method of claim 12;

(b) applying simulated force vectors that would occur during a fracture incident to the finite element model generated in step (a); and

(c) determining the minimum forces required for fracture to occur, thereby estimating the risk of fracture.