Compartment segregation by pixel characterization using image data clustering

• US 20090034823A1
• Filed: 05/14/2008
• Published: 02/05/2009
• Est. Priority Date: 05/14/2007
• Status: Active Grant

• Current Assignee: Novartis Ag
• Original Assignee: HistoRx, Inc. (NeoGenomics, Inc.)
• Inventors: Christiansen, Jason H., Pinard, Robert, Gustavson, Mark, Reilly, Dylan M., Bourke, Brian
• Granted Patent: US 8,335,360 B2
• Time in Patent Office: Days
• US Class Current: 382/133
• CPC Class Codes: G01N 33/5082 Supracellular entities, e.g. tissue, organisms
• CPC Class Codes: G01N 33/57423 of lung
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06V 20/69 Microscopic objects, e.g. biological cells or cellular parts

Abstract

The present invention relates generally to improved methods of defining areas or compartments within which biomarker expression is detected and quantified. In particular, the present invention relates to automated methods for delineating marker-defined compartments objectively with minimal operator intervention or decision making. The method provides for precise definition of tissue, cellular or subcellular compartments particularly in histological tissue sections in which to quantitatively analyzing protein expression.

Claims

1. A method for defining a first marker-defined biological compartment relative to a second marker-defined biological compartment present in a biological sample of interest, comprising comparing the intensity in each of the pixel locations in a first high-resolution image of the first marker defined biological compartment with the intensity in each of the corresponding pixel locations of a second high-resolution image of the second marker-defined biological compartment, wherein the first high-resolution image was prepared using a first imaging agent that is specific for the first marker-defined biological compartment, and wherein the second high-resolution image was prepared using a second imaging agent that is specific for the second marker-defined biological compartment, wherein differences in pixel intensity define the first marker-defined biological compartment relative to the second marker-defined biological compartment.

2. The method of claim 1, wherein the method is automated.

3. The method of claim 2, wherein the method is implemented by a computer.

4. The method of claim 1, wherein the pixels of the two high resolution images are plotted, wherein the axes of the plot comprise the intensity of the first imaging agent and the intensity of the second imaging agent.

5. The method of claim 1, further comprising:

i) assigning pixels to a cluster characterized by high first imaging agent intensity and low second imaging agent intensity to the first compartment;

ii) assigning pixels to a cluster characterized by high second imaging agent intensity and low first imaging agent intensity to the second compartment; and

iii) assigning pixels to a cluster characterized by low first imaging agent intensity and low second imaging agent intensity to background and removing such pixels from further analysis.

6. The method of claim 5, wherein any of the assigning steps are performed using a clustering algorithm.

7. The method of claim 6, wherein any of the assigning steps are performed using k-means clustering method to determine a cluster membership for each pixel.

8. The method of claim 5, further comprising assigning remaining pixels with first imaging agent intensity and second imaging agent intensity to either the first compartment or the second compartment based on probability.

9. The method of claim 5, further comprising assigning those remaining pixels with first imaging agent intensity and second imaging agent intensity to neither the first compartment nor the second compartment.

10. The method of claim 1, wherein the biological compartment is selected from the group consisting of:

a cell type, sub-cellular compartment, a tissue compartment, and a localized cellular or tissue compartment.

11. The method of claim 10, wherein the biological compartment is a sub-cellular compartment selected from the group consisting of:

cell nucleus, cytoplasm, nuclear membrane, cellular membrane, mitochondria, endoplasmic reticulum, peroxisome and lysosome.

12. The method of claim 10, wherein the biological compartment is a tissue compartment selected from the group consisting of:

epithelium, stroma and mesothelia.

13. The method of claim 1, wherein the sample is a tissue sample, cell preparation or sub-cellular fraction.

14. The method of claim 1, further comprising defining a mask defined by the pixel intensity of the first and/or second imaging agent and defining compartment assignment for only those pixels within the mask.

15. The method of claim 1, further comprising incubating the sample with a first imaging agent that specifically labels the first marker-defined biological compartment, a second imaging agent that specifically labels a second marker-defined biological compartment

16. A computer implemented method for defining a first marker-defined biological compartment relative to a second marker-defined biological compartment present in a biological sample comprising:

a) incubating the sample with a first imaging agent that specifically labels the first marker-defined compartment, and a second imaging agent that specifically labels the second marker defined compartment;

b) obtaining a first high-resolution image of the first imaging agent labeled sample, and a second high-resolution image of the second imaging agent labeled sample;

c) determining a first and a second imaging agent intensity in each corresponding pixel location in the first and the second image;

d) performing a clustering analysis on each pixel based on the first and the second imaging agent intensity of each pixel in each of the pixel to calculate clusters;

e) assigning those pixels in the cluster characterized by high first imaging agent pixel intensity and low second imaging agent pixel intensity to the first compartment;

f) assigning those pixels in the cluster characterized by high second imaging agent pixel intensity and low first imaging agent pixel intensity to the second compartment; and

g) assigning those pixels in the cluster characterized by low first imaging agent pixel intensity and low second imaging agent pixel intensity to background and removing such pixels from further analysis,

thereby defining a first marker-defined sub-cellular compartment relative to a second marker defined-sub-cellular compartment.

17. A computer implemented method for localizing and quantitating a particular biomarker within a first marker-defined biological compartment relative to a second marker-defined biological compartment present in a biological sample comprising:

a) incubating the tissue sample with a first imaging agent that specifically labels the first marker-defined compartment, a second imaging agent that specifically labels a second marker-defined sub-cellular compartment, and a third imaging agent that specifically labels the biomarker;

b) obtaining a first high-resolution image of the first imaging agent labeled sample, a second high-resolution image of the second imaging agent labeled sample, and a third high-resolution image of the third imaging agent labeled sample;

c) determining the first and second imaging agent pixel intensity in each of the pixel locations in the first and the second image;

d) performing a clustering analysis on the pixels to assign pixels to the first marker-defined compartment or the second marker-defined compartment; and

e) analyzing in the third image the pixel locations assigned to the compartments so as to identify those pixel locations with an intensity value indicative of the third imaging agent, and determining the total intensity value of the third imaging at the pixel locations assigned to each of the first and second compartments,

so as to thereby localize and quantitate the biomarker in the first compartment relative to the second compartment.

18. The method of claim 17, wherein the high-resolution images are obtained using an upright or inverted optical microscope.

19. The method of claim 17, wherein the cluster analysis is performed using reiterative k-means clustering on the first and the second pixel intensity in each of the pixel locations to calculate three centroids using Euclidean or log-likelihood distances.

20. The method of claim 19, further comprising:

i) plotting the pixel locations and the calculated centroids where the axes of the plot comprise the intensity of the first imaging agent and the intensity of the second imaging agent at pixel locations for the first compartment and the second compartment;

ii) connecting the centroids to define a triangle;

iii) assigning those pixel locations having an intensity not within the area of the triangle;

(1) to the first compartment if the pixel intensity is substantially indicative of the first imaging agent;

(2) to the second compartment if the pixel intensity is substantially indicative of the second imaging agent, or (3) to neither compartment if the pixel intensity is substantially indicative of background; and

iv) assigning those pixel locations within the area of the triangle the first compartment or the second compartment based upon a value corresponding to the probability that the pixel originates from the first or the second compartment.

21. The method of claim 17, wherein the biomarker is selected from the group consisting of:

a protein, a peptide, a nucleic acid, a lipid and a carbohydrate.

22. The method of claim 17, wherein each of the first, the second and the third imaging agents comprise a fluorophore.

23. The method of claim 17, wherein the quantitation of the biomarker present within the first or the second compartment comprises summing the intensity values of the third imaging agent at the pixel locations within the compartment and dividing the sum by the number of pixels in the compartment.

24. The method of claim 17, wherein a pixel location not assigned to the first or the second compartment is assigned to a third compartment.

25. The method of claim 17, wherein the sample is a tissue sample with a thickness of about five microns.

26. The method of claim 17, wherein the first compartment is a cellular membrane and the second compartment is a cell nucleus.

27. The method of claim 17, wherein the biological sample is a fixed tissue section.

28. The method of claim 17, wherein the first or the second imaging agent reacts with a marker that is selected from the group consisting of:

cytokeratin, beta catenin, alpha catenin and vimentin.

29. The method of claim 17, wherein at least one of the first, the second or the third imaging agents comprises a fluorophore selected from the group consisting of:

4′

,6-diamidino-2-phenylindole (DAPI), Cy3, Cy-5-tyramide and Alexa fluor dyes.

30. The method of claim 17, wherein the biomarker is selected from the group consisting of:

Her-2/neu, estrogen receptor, progesterone receptor, epidermal growth factor receptor, PTEN and ERCC1.

31. The method of claim 17, wherein a mask is applied to the first, the second and the third high-resolution images, and only pixels within the mask are analyzed.

32. A computer readable medium comprising the computer readable instructions stored thereon for execution by a processor to perform a method for determining an optimal dilution of a reagent for use in a quantitative immunoassay comprising the steps of:

receiving a plurality of dilution sets, each dilution set having a different respective dilution value and comprising a respective plurality of immunoassay staining intensity values;

determining for each of the plurality of dilution sets a respective dynamic range metric related to the respective plurality of immunoassay staining intensity values; and

identifying the dilution set having the numerically greatest dynamic range metric, the dilution value of the identified dilution set being representative of an optimal dilution level of the reagent for use in the quantitative immunoassay.

33. An electromagnetic signal carrying computer-readable instructions for determining an optimal dilution of a reagent for use in a quantitative immunoassay comprising the steps of:

receiving a plurality of dilution sets, each dilution set having a different respective dilution value and comprising a respective plurality of immunoassay staining intensity values;

determining for each of the plurality of dilution sets a respective dynamic range metric related to the respective plurality of immunoassay staining intensity values; and

identifying the dilution set having the numerically greatest dynamic range metric, the dilution value of the identified dilution set being representative of an optimal dilution level of the reagent for use in the quantitative immunoassay.

34. A computer implemented method for defining a first marker defined sub-cellular compartment relative to a second marker defined sub-cellular compartment present in individual cells of interest contained in a tissue sample comprising:

a) incubating the tissue sample with a first stain that specifically labels the first marker defined sub-cellular compartment, a second stain that specifically labels a second marker defined sub-cellular compartment,

b) obtaining a high resolution image of each of the first and the second stain in the tissue sample using a microscope so as to obtain;

i) a first image of the first marker defined sub-cellular compartment;

ii) a second image of the second marker defined sub-cellular compartment; and

c) determining the first and second stain intensity in each of the pixel locations in the first and the second image;

d) plotting the pixels, where the axes of the plot comprise the intensity of the first stain and the intensity of the second stain;

e) performing reiterative k-means clustering on the first and the second stain intensity in each of the pixel locations to calculate three clusters;

f) assigning those pixels in the cluster characterized by high first stain intensity and low second stain intensity to the first compartment;

g) assigning those pixels in the cluster characterized by high second stain intensity and low first stain intensity to the second compartment;

h) assigning those pixels in the cluster characterized by low first stain intensity and low second stain intensity to background and removing such pixels from further analysis;

i) assigning those pixels with first stain intensity and second stain intensity to either the first compartment or the second compartment based upon based on probability

thereby defining a first marker defined sub-cellular compartment relative to a second marker defined sub-cellular compartment.

35. A computer implemented method for defining a first marker defined sub-cellular compartment relative to a second marker defined sub-cellular compartment present in individual cells of interest contained in a tissue sample comprising:

a) incubating the tissue sample with a first stain that specifically labels the first marker defined sub-cellular compartment, a second stain that specifically labels a second marker defined sub-cellular compartment,

b) obtaining a high resolution image of each of the first and the second stain in the tissue sample using a microscope so as to obtain;

i) a first image of the first marker defined sub-cellular compartment;

ii) a second image of the second marker defined sub-cellular compartment; and

c) determining the first and second stain intensity in each of the pixel locations in the first and the second image;

d) plotting the pixels, where the axes of the plot comprise the intensity of the first stain and the intensity of the second stain;

e) performing reiterative k-means clustering on the first and the second stain intensity in each of the pixel locations to calculate three clusters;

f) assigning those pixels in the cluster characterized by high first stain intensity and low second stain intensity to the first compartment;

g) assigning those pixels in the cluster characterized by high second stain intensity and low first stain intensity to the second compartment;

h) assigning those pixels in the cluster characterized by low first stain intensity and low second stain intensity to background and removing such pixels from further analysis;

i) assigning those pixels with first stain intensity and second stain intensity to neither the first compartment or the second compartment;

thereby defining a first marker defined sub-cellular compartment relative to a second marker defined sub-cellular compartment.

36. A computer implemented method for localizing and quantitating a particular biomarker within a first marker defined sub-cellular compartment relative to a second marker defined sub-cellular compartment present in individual cells of interest contained in a tissue sample comprising:

a) incubating the tissue sample with a first stain that specifically labels the first marker defined sub-cellular compartment, a second stain that specifically labels a second marker defined sub-cellular compartment, and a third stain that specifically labels the biomarker;

b) obtaining a high resolution image of each of the first, the second, and the third stain in the tissue sample using an upright or inverted optical microscope so as to obtain;

i) a first image of the first marker defined sub-cellular compartment;

ii) a second image of the second marker defined sub-cellular compartment; and

iii) a third image of the biomarker,

c) determining the first and second stain intensity in each of the pixel locations in the first and the second image;

d) performing reiterative k-means clustering on the first and the second stain intensity in each of the pixel locations to assign pixels to the first marker defined sub-cellular compartment of the second marker defined sub-cellular compartment;

e) analyzing in the third image the pixel locations assigned to the first sub-cellular compartment, the second sub-cellular compartment, or both compartments in step (f) and step (g) so as to identify those pixel locations having an intensity value indicative of the third stain, and determining the total intensity value of the third stain at the pixel locations assigned to each of the first and second sub-cellular compartment;

so as to thereby localize and quantitate the biomarker in the first sub-cellular compartment relative to the second sub-cellular compartment

37. A computer implemented method for localizing and quantitating a particular biomarker within a first marker defined sub-cellular compartment relative to a second marker defined sub-cellular compartment present in individual cells of interest contained in a tissue sample comprising:

a) incubating the tissue sample with a first stain that specifically labels the first marker defined sub-cellular compartment, a second stain that specifically labels a second marker defined sub-cellular compartment, and a third stain that specifically labels the biomarker;

b) obtaining a high resolution image of each of the first, the second, and the third stain in the tissue sample using an upright or inverted optical microscope so as to obtain;

i) a first image of the first marker defined sub-cellular compartment;

ii) a second image of the second marker defined sub-cellular compartment; and

iii) a third image of the biomarker,

c) determining the first and second stain intensity in each of the pixel locations in the first and the second image;

d) performing reiterative k-means clustering on the first and the second stain intensity in each of the pixel locations to calculate three centroids using Euclidean or log-likelihood distances;

e) plotting the pixel locations and the calculated centroids where the axes of the plot comprise the intensity of the first stain and the intensity of the second stain pixel locations for the first compartment and the second compartment.

f) connecting the centroids to define a triangle,

g) assigning those pixel locations having an intensity not within the area of the triangle;

(1) to the first compartment if the pixel intensity is substantially indicative of the first stain;

(2) to the second compartment if the pixel intensity is substantially indicative of the second stain, or (3) to neither compartment if the pixel intensity is substantially indicative of background;

h) assigning those pixel locations within the area of the triangle the first compartment or the second compartment based upon a value corresponding to the probability that the pixel originates from the first or the second compartment;

i) analyzing in the third image the pixel locations assigned to the first sub-cellular compartment, the second sub-cellular compartment, so as to identify those pixel locations having an intensity value indicative of the third stain, and determining the total intensity value of the third stain at the pixel locations assigned to each of the first and second sub-cellular compartment;

so as to thereby localize and quantitate the biomarker in the first sub-cellular compartment relative to the second sub-cellular compartment.