Systems and Methods for Elastography Imaging

• US 20090221916A1
• Filed: 12/08/2006
• Published: 09/03/2009
• Est. Priority Date: 12/09/2005
• Status: Abandoned Application

• Current Assignee: Trustees Of Columbia University In The City Of New York (Columbia University)
• Original Assignee: Trustees Of Columbia University In The City Of New York (Columbia University)
• Inventors: Fung-Kee-Fung, Simon, Ginat, Daniel, Spalazzi, Jeff, Konofagou, Elisa E., Lu, Helen
• Application Number:
  US12/096,254
• Publication Number:
  US 20090221916A1
• Time in Patent Office: Days
• US Class Current: 600/443
• CPC Class Codes: A61B 2503/40 Animals
• CPC Class Codes: A61B 5/4514 Cartilage
• CPC Class Codes: A61B 5/4523 Tendons
• CPC Class Codes: A61B 5/4533 Ligaments
• CPC Class Codes: A61B 8/08 Detecting organic movements or changes, e.g. tumours, cysts, swellings A61B8/02 - A61B8/06 take precedence
• CPC Class Codes: A61F 2/08 Muscles; Tendons; Ligaments sutures A61B17/04
• 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 2/468 Testing instruments for artificial joints for testing non-implantable prostheses A61F2/76
• CPC Class Codes: G01R 33/56358 Elastography
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/32 using correlation-based methods

Abstract

Methods for obtaining information about the mechanical behaviour of structures associated with mammalian joints and tendons are provided. Embodiments of such methods include creating deformation in a joint structure (such as ligaments and articular cartilage) or tendon of interest, using an ultrasound scanner and a single element or array of elements to acquire sequences of ultrasound data of the joint structure or tendon, estimating one, two or three components of the resulting displacement and strain between a reference frame of ultrasound data and successive frames of ultrasound data, and using a cross-correlation algorithm to estimate the displacement and strain components. This information may be used to inform the design of tissue grafts. Tissue grafts produced using this information are also provided. The same method can be used in situ together with noninvasive or invasive procedures.

Claims

1. A method for obtaining information about the mechanical behaviour of structures associated with mammalian joints comprising:

(a) creating deformation in a joint structure of interest;

(b) using an ultrasound scanner in a linear array to acquire sequences of ultrasound data of the joint structure; and

(c) estimating a displacement component or displacement distribution between a reference frame of backscattered signals and a successive frame of backscattered signals, wherein said displacement component is estimated with a matching algorithm.

2. The method of claim 1, further comprising repeating step (c) until sufficient data is obtained to estimate strain distribution in the joint structure of interest.

3. The method of claim 2, wherein the joint structure of interest is selected from the group consisting of:

ligaments and articular cartilage and any combination thereof.

4. The method of claim 3, wherein the matching algorithm includes determining time-shifts between two RF signals by cross-correlating sliding windows over a 2D or 3D ultrasound image to provide an estimation of axial, lateral or elevational displacement components.

5. The method of claim 4, further comprising computing a strain or strain rate distribution.

6. The method of claim 5, wherein computing a strain or strain rate distribution comprises differentiating a displacement map along one of the principle directions.

7. The method of claim 6 wherein the said differentiating comprises numerical differentiation, wherein the numerical differentiation includes least-square regression.

8. The method of claim 1, wherein said estimation of the displacement component further includes a recorrelation algorithm.

9. The method of claim 1 or 8, further comprising the use of a window size between about 1 and about 5 mm and a window overlap between about 50 and about 99%.

10. The method of claim 1, wherein the joint structure of interest is associated with the tibiofemoral joint.

11. The method of claim 10, wherein the ligament is an anterior cruciate ligament.

12. The method of claim 10, wherein the ligament is a posterior cruciate ligament.

13. The method of claim 1, wherein the information is obtained in vitro.

14. The method of claim 1, wherein the information is obtained in vivo.

15. The method of claim 1, wherein the information is obtained in situ noninvasively.

16. The method of claim 1, wherein the information is obtained in situ during a minimally invasive procedure such as an arthroscopy.

17. The method of claim 1, wherein the information is obtained in situ during an invasive procedure such as hip surgery.

18. The method of claim 1, wherein the joint structure of interest is associated with a joint selected from the group consisting of:

foot, ankle, knee, hip, hand, wrist, elbow, shoulder and temporomandibular joint (TMJ).

19. The method of claim 1, wherein the mammal is selected from the group consisting of:

human, equine, canine and feline.

20. The method of claim 1 or 2, wherein said information is used to inform the design of tissue grafts.

21. A tissue graft produced using the information obtained by the method of claim 1 or 2.

32. The method of claim 1 or 22, wherein said deformation is selected from the group consisting of tension, compression and relaxation, or any combination thereof.

33. The method of claim 1 or 22, wherein said deformation is generated by the ultrasound probe itself.

34. The method of claim 1 or 22, wherein said deformation is generated by the scanned subject itself.

22. A method for obtaining information about the mechanical behaviour of mammalian tendons comprising:

(a) creating deformation in a tendon of interest;

(b) using an ultrasound scanner with a piezoelectric element or an array of piezoelectric elements to acquire sequences of ultrasound data of the tendon; and

(c) estimating the displacement between a reference frame of the ultrasound data and successive frames of the ultrasound data, wherein said displacement or displacement distribution is estimated with a cross-correlation algorithm.

23. The method of claim 22, further comprising repeating step (c) until sufficient data is obtained to estimate strain distribution in the tendon of interest.

24. The method of claim 22, wherein the cross-correlation algorithm includes determining time-shifts between two backscattered RF signals by cross-correlating sliding windows over a 2D or 3D ultrasound image to provide an estimation of axial, lateral or elevational displacement components ultrasound image.

25. The method of claim 24, wherein the cross-correlation algorithm includes determining time-shifts between two backscattered RF signals by cross-correlating sliding windows over a 2D or 3D ultrasound image to provide an estimation of axial, lateral or elevational displacement components ultrasound image.

26. The method of claim 24, wherein the cross-correlation algorithm includes determining time-shifts between two backscattered RF signals by cross-correlating sliding windows over a 3D ultrasound image to provide an estimation of axial, lateral or elevational displacement components ultrasound image.

27. The method of claim 23, further comprising computing a strain or strain rate distribution.

28. The method of claim 27, wherein computing a strain or strain rate distribution comprises differentiating a displacement map along the axial direction.

29. The method of claim 28 wherein said differentiating comprises numerical differentiation and wherein the numerical differentiation includes least-square regression.

30. The method of claim 22, wherein said estimation of axial displacement further includes a recorrelation algorithm.

31. The method of claim 23 or 28, further comprising the use of a window size between about 1 and 5 mm and a window overlap between about 50 and 99%.

35. The method of claim 22, wherein said piezoelectric element is embedded or is part of a surgical tool.