Quantitative structural assay of a nerve graft

Patent metadata

Field	Value
Publication number	US-9690975-B2
Application number	US-201514724359-A
Country	US
Kind code	B2
Filing date	May 28, 2015
Priority date	May 28, 2015
Publication date	Jun 27, 2017
Grant date	Jun 27, 2017

Abstract

Techniques are described for determining the quality of a nerve graft by assessing quantitative structural characteristics of the nerve graft. Aspects of the techniques include obtaining an image identifying laminin-containing tissue in the nerve graft; creating a transformed image using a transformation function of an image processing application on the image; using an analysis function of the image processing application, analyzing the transformed image to identify one or more structures in accordance with one or more recognition criteria; and determining one or more structural characteristics of the nerve graft derived from a measurement of the one or more structures.

First claim

What is claimed is:

1. A method for assessing the quality of a nerve graft, the method comprising:
obtaining an image identifying laminin-containing tissue in the nerve graft;
creating a transformed image using a transformation function of an image processing application on the image;
using an analysis function of the image processing application, analyzing the transformed image to identify one or more structures in accordance with one or more recognition criteria;
determining one or more structural characteristics of the nerve graft derived from a measurement of the one or more structures; and
assessing the quality of the nerve graft based on the determined one or more structural characteristics,
wherein the one or more recognition criteria comprises a size range of the one or more structures and wherein the size range is within a range from about 4.84 microns in diameter to about 16 microns in diameter.

2. The method of claim 1 , wherein, before creating the transformed image, the method further comprises selecting one or more of an area of interest and a sampling window to delineate a selected image area, wherein the analyzing of the transformed image is performed only on the selected image area.

3. The method of claim 2 , wherein the area of interest comprises a nerve fascicle.

4. The method of claim 1 , wherein the one or more structures comprise an endoneurial tube.

5. The method of claim 1 , wherein creating the transformed image comprises applying thresholding to the image.

6. The method of claim 5 , wherein applying the thresholding comprises applying one or more of a threshold method, a threshold color, a color space, and a dark background.

7. The method of claim 1 , wherein the one or more recognition criteria comprise a circularity range of the one or more structures.

8. The method of claim 7 , wherein the circularity range is from about 0.5 to about 1.0.

9. The method of claim 1 , wherein the one or more structural characteristics comprise the number of endoneurial tubes per area.

10. The method of claim 1 , wherein the one or more structural characteristics comprise the percent of endoneurial tube lumen per area.

11. The method of claim 1 , wherein the one or more structural characteristics comprise the total perimeter of endoneurial tube lumens per area.

12. The method of claim 1 , further comprising:
comparing the one or more structural characteristics to a qualitative assessment score.

13. The method of claim 1 , further comprising:
comparing the one or more structural characteristics to one or more reference ranges indicating an acceptable structural characteristic of the nerve graft.

14. The method of claim 1 , further comprising:
comparing the one or more structural characteristics to a bioassay result of the nerve graft.

15. A method for assessing the structural quality of a nerve graft, the method comprising:
obtaining an image of tissue, the image depicting a cross-section of the nerve graft, wherein the cross-section is treated with a stain that indicates the presence of laminin;
selecting, using an image processing application, one or more nerve fascicles on the image;
using the image processing application, creating a thresholded image, wherein the thresholded image distinguishes one or more visual aspects of the image;
using a particle analysis feature of the image processing application on the thresholded image, identifying one or more endoneurial tubes contained within the boundary of the one or more nerve fascicles, wherein the particle analysis feature identifies the one or more endoneurial tubes in accordance with one or more recognition criteria;
determining one or more structural characteristics of the nerve graft derived from a measurement of the one or more endoneurial tubes; and
assessing the structural quality of the nerve graft based on the determined one or more structural characteristics.

16. The method of claim 15 , wherein the one or more recognition criteria comprise a size range of the one or more endoneurial tubes, wherein the size range is from about 4.84 microns in diameter to about 16 microns in diameter.

17. The method of claim 15 , wherein the one or more recognition criteria comprise a circularity range of the one or more endoneurial tubes, wherein the circularity range is from about 0.5 to about 1.0.

18. The method of claim 15 , wherein the one or more structural characteristics is one or more of: the number of endoneurial tubes per area, the percent of endoneurial tube lumens per area, and the total perimeter of endoneurial tube lumens per area.

19. The method of claim 15 , further comprising:
comparing the one or more structural characteristics to one or more of:
a qualitative assessment score;
one or more reference ranges indicating an acceptable structural characteristic of the nerve graft; and
a bioassay result of the nerve graft.

20. The method of claim 15 , wherein the stain is an immunoperoxidase stain.

21. A method for assessing the quality of a nerve graft, the method comprising:
obtaining an image identifying laminin-containing tissue in the nerve graft;
creating a transformed image using a transformation function of an image processing application on the image;
using an analysis function of the image processing application, analyzing the transformed image to identify one or more structures in accordance with one or more recognition criteria;
determining one or more structural characteristics of the nerve graft derived from a measurement of the one or more structures; and
assessing the quality of the nerve graft based on the determined one or more structural characteristics, and
wherein the one or more recognition criteria comprise a circularity range of the one or more structures, and wherein the circularity range is within the range from about 0.5 to about 1.0.

22. A method for assessing the quality of a nerve graft, the method comprising:
obtaining an image identifying laminin-containing tissue in the nerve graft;
creating a transformed image using a transformation function of an image processing application on the image;
using an analysis function of the image processing application, analyzing the transformed image to identify one or more structures in accordance with one or more recognition criteria;
determining one or more structural characteristics of the nerve graft derived from a measurement of the one or more structures; and
assessing the quality of the nerve graft based on the determined one or more structural characteristics, and
wherein the one or more structural characteristics comprise the total perimeter of endoneurial tube lumens per area.

Assignees

• Axogen Inc
• Axogen Corp

Inventors

• Deister Curt

Classifications

• G06T2207/10056

  Microscopic image · CPC title

• G06T2207/30024

  Cell structures in vitro; Tissue sections in vitro · CPC title

• G06T7/62 Primary

  of area, perimeter, diameter or volume · CPC title

• G06T7/0012

  Biomedical image inspection · CPC title

• G06K9/0014

  Physics · mapped topic