Method for quantitative analysis of blood vessel structure

• US 20020086347A1
• Filed: 01/07/2002
• Published: 07/04/2002
• Est. Priority Date: 06/23/1999
• Status: Active Grant

• Current Assignee: Ventana Medical Systems Incorporated (Roche Holding AG)
• Original Assignee: Icoria, Inc. (Abbvie Incorporated)
• Inventors: Johnson, Peter C., Fuhrman, Michael G., Shah, Sujal, Del Brady, Mary, Abdul-Karim, Othman A.
• Granted Patent: US 6,993,170 B2
• Time in Patent Office: Days
• US Class Current: 435/40.5
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• 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 5/418 lymph vessels, ducts or nodes
• CPC Class Codes: G01N 33/50 Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing measuring or testing processes involving enzymes or microorganisms, compositions or test papers therefor; processes for forming such compositions, condition responsive control in microbiological or enzymological processes C12Q
• CPC Class Codes: G01N 33/5005 involving human or animal cells immunoassay G01N33/56966; immunoassays of protozoa G01N33/56905; protozoa in screening assays C12Q1/025
• CPC Class Codes: G01N 33/6803 General methods of protein analysis not limited to specific proteins or families of proteins
• CPC Class Codes: G06T 2207/10056 Microscopic image
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/155 involving morphological operators
• CPC Class Codes: G06T 7/62 of area, perimeter, diameter or volume
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

We disclose quantitative geometrical analysis enabling the measurement of several features of images of tissues including perimeter, area, and other metrics. Automation of feature extraction creates a high throughput capability that enables analysis of serial sections for more accurate measurement of tissue dimensions. Measurement results are input into a relational database where they can be statistically analyzed and compared across studies. As part of the integrated process, results are also imprinted on the images themselves to facilitate auditing of the results. The analysis is fast, repeatable and accurate while allowing the pathologist to control the measurement process.

Claims

1. A method to facilitate visualization of a feature in a tissue comprising the steps of:

(a) obtaining an image of a tissue specimen;

(b) using objectively-defined criteria to locate a feature of interest in the image;

(c) using mathematical algorithms to construct boundaries of the feature; and

(d) using objectively-defined criteria to establish self-consistency.

2. The method of claim 1, wherein the tissue specimen is a section of blood vessel tissue, liver tissue, kidney tissue, bile duct tissue, gastrointestinal tract tissue, lymphatic vessel tissue, bronchial tissue.

3. The method of claim 2, wherein the tissue specimen is a blood vessel section.

4. The method of claim 3, wherein the feature of interest comprise adventitia, media, internal elastic lamina and intima.

5. A method for quantitative determination of geometry of a given blood vessel comprising the steps of:

(a) imaging a cross section of the given blood vessel to capture an image;

(b) extracting features of the image to identify different boundary segments based on intensity, color and morphology of the image;

(c) applying image processing algorithms and computing boundary segment perimeters and areas after step (b);

(d) determining said blood vessel geometry based on said boundary segment perimeters and areas,

6. The method of claim 5, wherein different boundary segments comprise adventitia, media, internal elastic lamina and intima.

7. The method of claim 5, wherein the boundary segment perimeters comprise perimeter of the vessel, adventitia, media and lumen.

8. The method of claim 5, wherein the boundary segment areas comprise area of the vessel, lumen, media and neointima.

9. The method of claim 5, wherein values computed are imprinted such that said values are viewed as part of the image.

10. A method for rapidly localizing a fractured boundary segment in a blood vessel image and generating a contour connecting the fractured ends, the method comprising the steps of:

(a) processing a cross section of the blood vessel defining a target for imaging;

(b) imaging the target to capture image of the entire target;

(c) identifying different boundary segments including the fractured boundary segment by using an image processing algorithm

(d) computing boundary segment perimeters and areas after step (c); and

(e) generating a contour connecting the fractured ends based on the boundary segment perimeters and areas

11. The method of claim 10, wherein the different boundary segments are adventitia, media, internal elastic lamina and intima.

12. The method of claim 11, wherein the fractured boundary segment is internal elastic lamina.

13. The method of claim 12, wherein the boundary segment perimeters comprise perimeter of the vessel, adventitia, media and lumen.

14. The method of claim 13, wherein the boundary segment areas comprise area of the vessel, lumen, media and neointima.

16. The method of claim 15, wherein the ratio is neointimal area/vessel area.

17. The method of claim 15, wherein the ratio is neointimal area/vessel area.

18. The method of claim 15, wherein the ratio is (neointimal area/vessel area)/(fracture length/vessel perimeter).

19. The method of claim 15, wherein values computed are imprinted such that said values are viewed as part of the image.

20. The method of claim 15, wherein the fracture boundary segment is internal elastic lamina.

15. A method for determining the extent of restenosis in a given blood vessel with a fractured boundary segment, the method comprising the steps of:

(a) imaging a cross section of the given blood vessel to capture an image;

(b) extracting features of the image to identify different boundary segments based on intensity, color and morphology of the image;

(c) applying image processing algorithms and computing fracture length of the fractured boundary segment, and perimeters and areas of the given blood vessel, lumen, media and neointima after step (b);

(d) determining the extent of restenosis in the given blood vessel by computing a ratio selected from the group consisting of

(i) neointimal area/vessel area

(ii) neointimal area/medial area

(iii) (neointimal area/vessel area)/(fracture length/vessel perimeter).