Detection of circulating tumor cells using imaging flow cytometry

• US 8,131,053 B2
• Filed: 07/28/2008
• Issued: 03/06/2012
• Est. Priority Date: 01/25/1999
• Status: Expired due to Term

• Current Assignee: Cytek Biosciences Inc
• Original Assignee: Amnis Corporation (DiaSorin S.p.A.)
• Inventors: Ortyn, William, Basiji, David, Liang, Luchuan, Venkatachalam, Vidya, Morrissey, Philip
• Primary Examiner(s): BLACKMAN, ROCHELLE ANN J
• Application Number:
  US12/181,062
• Publication Number:
  US 20080317325A1
• Time in Patent Office: 1,317 Days
• Field of Search: 382/128, 382/133, 382/134, 600/410, 600/562, 356/451, 356/456, 356/326
• US Class Current: 382/133
• CPC Class Codes: G01N 15/1433 using image recognition
• CPC Class Codes: G01N 15/147 the analysis being performed on a sample stream
• CPC Class Codes: G01N 2021/6441 with two or more labels
• CPC Class Codes: G01N 21/6428 Measuring fluorescence of fluorescent products of reactions or of fluorochrome labelled reactive substances, e.g. measuring quenching effects, using measuring "optrodes" in vivo A61B5/00; immunoassay G01N33/53
• CPC Class Codes: G01N 21/6458 Fluorescence microscopy fluorescence microscopes per se G02B21/0076 and G02B21/16
• 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 33/505 involving T-cells

Abstract

Photometric and morphometric features derived from multi-mode imagery of cells in flow are used as a cell analyzer to determine if a marker corresponding to a cancer cell or precancerous cell is present in the population of cells imaged. An imaging system simultaneously acquires a plurality of images for each cell passing through the field of view of the imaging system. Acquiring a plurality of different images (i.e., bright field, dark field, and fluorescent images) facilitates the determination of different morphological and morphometric parameters. Simultaneously acquiring the plurality of images enables relatively large populations of cells to be rapidly imaged, so that relatively small numbers of cancer cells in a large population of cells can be detected. Initially, known cancer cells are imaged to enable a marker to be identified. Then, a sample that may include cancer cells is imaged to determine if the marker is present.

Claims

1. A method for detecting cancer or a precancerous condition from images collected from a population of cells present in a bodily fluid, comprising the steps of:

(a) providing a first population of abnormal cells and a second population of normal cells, the abnormal cells comprising at least one type of cells selected from the group consisting of cancer cells and cancer precursor cells;

(b) imaging the first population of cells in flow to collect first image data, and imaging the second population of cells in flow to collect second image data, such that the first and second image data for each cell in the respective populations of cells includes a plurality of simultaneously collected images, the plurality of simultaneously collected images for each cell comprising at least one of the following two types of images;

(i) multispectral images; and

(ii) multimodal images;

(c) analyzing the first and second image data to identify at least one cell characteristic that can be measured using the first and second image data and that enables the abnormal cells to be distinguished from the normal cells;

(d) collecting a bodily fluid comprising a third population of cells;

(e) imaging the third population of cells in flow to collect third image data, such that the third image data for each cell includes a plurality of simultaneously collected images, the plurality of simultaneously collected images comprising at least one of the following two types of images;

(i) multispectral images; and

(ii) multimodal images; and

(f) analyzing the third image data to determine if any abnormal cells are present in the third population, by determining if the at least one cell characteristic that enables the abnormal cells to be distinguished from the normal cells is present in the third image data, the presence of abnormal cells indicating the presence of cancer or a precancerous condition.

2. The method of claim 1, further comprising the step of staining at least one of the first population and the second population, to facilitate distinguishing the first image data from the second image data, even when the first population and the second population are combined before imaging.

3. The method of claim 1, wherein the step of identifying the at least one cell characteristic comprises the step of identifying a photometric parameter.

4. The method of claim 1, wherein the step of identifying the at least one cell characteristic comprises the step of identifying a morphometric parameter.

5. The method of claim 4, wherein the step of identifying the morphometric parameter comprises the step of identifying a cytoplasmic area.

6. The method of claim 5, wherein the step of identifying the cytoplasmic area comprises the steps of:

(a) using a bright field image to determine a cellular area;

(b) using a fluorescent image to determine a nuclear area; and

(c) defining the cytoplasmic area as a difference between the cellular area and the nuclear area.

7. The method of claim 1, wherein the step of identifying the at least one cell characteristic comprises the step of identifying at least one of the following characteristics:

(a) a scatter intensity;

(b) a scatter texture;

(c) a nuclear intensity; and

(d) a nuclear texture.

8. The method of claim 1, wherein the step of identifying the at least one cell characteristic comprises the step of identifying a mean scatter intensity, the mean scatter intensity being calculated using a total intensity divided by a cellular area.

9. The method of claim 1, wherein the step of identifying the at least one cell characteristic comprises the step of calculating a scatter intensity by removing a background intensity from a total intensity.

10. The method of claim 1, wherein the step of identifying the at least one cell characteristic comprises the step of calculating a scatter intensity by determining a total intensity of local scatter maxima.

11. The method of claim 1, wherein the step of identifying the at least one cell characteristic comprises the step of identifying a scatter texture using at least one technique selected from the group consisting of:

(a) identifying an intensity profile gradient metric; and

(b) identifying a variance of pixel intensities.

12. The method of claim 1, wherein the plurality of simultaneously collected images acquired for the first, second, and third populations comprise extended depth of field images.

13. The method of claim 1, wherein the plurality of simultaneously collected images acquired for the first, second, and third populations comprise at least two types of images selected from the group consisting of:

a bright field image, a dark field image, and a fluorescent image.

14. An imaging system configured to acquire and analyze image data collected from a population of cells, to enable a cancerous or precancerous condition to be detected, comprising:

(a) an image acquisition subsystem configured to simultaneously acquire a plurality of images of individual cells from the population of cells, while there is relative movement between the image acquisition subsystem and an individual cell, the plurality of images comprising at least two types of images selected from the group consisting of;

(i) a bright field image;

(ii) a dark field image; and

(iii) a fluorescent image;

(b) a database including at least one cell characteristic indicative of an abnormal condition, where the abnormal condition comprises at least one condition selected from the group consisting of a cancerous condition, and a precancerous condition, and where the at least one cell characteristic can be measured using the plurality of images acquired by the image acquisition subsystem; and

(c) a processor configured to analyze the plurality of images of individual cells to determine if the at least one cell characteristic is present in the population of cells.

15. The system of claim 14, wherein the at least one characteristic comprises a photometric parameter.

16. The system of claim 14, wherein the at least one characteristic comprises a morphometric parameter.

17. The system of claim 16, wherein the morphometric parameter comprises cytoplasmic area.

18. The system of claim 15, wherein the at least one characteristic comprises at least one element selected from a group consisting of:

(a) a scatter intensity;

(b) a scatter texture;

(c) a nuclear intensity; and

(d) a nuclear texture.

19. The system of claim 15, wherein the at least one characteristic comprises at least one element selected from a group consisting of:

(a) a mean scatter intensity, the mean scatter intensity being calculated using a total intensity divided by a cellular area;

(b) a scatter intensity calculated by removing a background intensity from a total intensity; and

(c) a scatter intensity calculated by determining a total intensity of local scatter maxima.

20. An imaging system configured to acquire and analyze image data collected from a population of cells, where the image data include a plurality of images of individual cells that are acquired simultaneously, to enable a cancerous or precancerous condition to be detected, comprising:

(a) a collection lens disposed so that light traveling from an individual cell passes through the collection lens and travels along a collection path;

(b) a spectral separation element disposed in the collection path so as to spectrally separate light that has passed through the collection lens, thereby producing spectrally separated light;

(c) an imaging lens disposed to focus the spectrally separated light, producing focused spectrally separated light;

(d) a detector disposed to receive the focused spectrally separated light, such that the focused spectrally separated light incident on the detector simultaneously comprises a plurality of images of the individual cell, the plurality of images comprising the image data, the plurality of images being dispersed across the detector such that the plurality of images do not overlap, and the plurality of images being dispersed in a direction orthogonal to a direction of motion of the plurality of images across the detector when there is relative movement between the individual cell and the imaging system; and

(e) a processor configured to analyze the image data for the plurality of images collected for individual cells in the population of cells, to determine if the image data indicate that any individual cell in the population of cells exhibits the cancerous or precancerous condition.

21. A method for detecting cancer or a precancerous condition from images collected from a population of cells present in a bodily fluid, comprising the steps of:

(a) providing a first population of abnormal cells and a second population of normal cells, the abnormal cells comprising at least one type of cells selected from the group consisting of cancer cells and cancer precursor cells;

(b) imaging each cell in the first population of cells while each cell is in flow to collect first image data, and imaging each cell in the second population of cells while each cell is in flow to collect second image data, such that the step of imaging each cell comprises the steps of;

(i) spectrally dispersing light from the cell into a plurality of light beams having different spectral content; and

(ii) directing focused light from each of the plurality of light beams having different spectral content onto a different region of a pixilated detector, thereby simultaneously acquiring a plurality of different images of the cell on the pixilated detector, each different image being formed from a different one of the plurality of light beams having different spectral content, the plurality of simultaneously collected images for each cell comprising at least one of the following two types of images;

(A) multispectral images; and

(B) multimodal images;

(c) analyzing the first and second image data to identify at least one cell characteristic that can be measured using the first and second image data and that enables the abnormal cells to be distinguished from the normal cells;

(d) collecting a bodily fluid comprising a third population of cells;

(e) imaging the third population of cells in flow to collect third image data, such that the third image data for each cell includes a plurality of simultaneously collected images, the plurality of simultaneously collected images comprising at least one of the following two types of images;

(i) multispectral images; and

(ii) multimodal images; and

(f) analyzing the third image data to determine if any abnormal cells are present in the third population, by determining if the at least one cell characteristic that enables the abnormal cells to be distinguished from the normal cells is present in the third image data, the presence of abnormal cells indicating the presence of cancer or a precancerous condition.