Method for quantitative analysis of blood vessel structure

• US 6,993,170 B2
• Filed: 01/07/2002
• Issued: 01/31/2006
• Est. Priority Date: 06/23/1999
• Status: Expired due to Term

• 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.
• Primary Examiner(s): Allen, Marianne P.
• Application Number:
  US10/041,254
• Publication Number:
  US 20020086347A1
• Time in Patent Office: 1,485 Days
• Field of Search: 702/19, 702/21, 382/128, 382130-134, 382190-195, 382256-257, 382/266
• US Class Current: 382/128
• 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 for quantitative determination of overall shape of a blood vessel and the spatial relationship of different structures within a given blood vessel comprising the steps of:

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

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

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

(d) determining the blood vessel overall shape and spatial relationship of different structures within the blood vessel based on the boundary segment perimeters and areas.

2. The method of claim 1, wherein different boundary segments comprise adventitia, media, internal elastic lamina and intima.

3. The method of claim 1, wherein the boundary segment perimeters comprise perimeter of the vessel, adventitia, media and lumen.

4. The method of claim 1, wherein the boundary segment areas comprise area of the vessel, lumen, media and neointima.

5. The method of claim 1 wherein the computed boundary segment perimeters and areas are imprinted such that the perimeters and areas are viewed as part of the image.