Detection of circulating tumor cells using imaging flow cytometry

• US 8,548,219 B2
• Filed: 02/14/2012
• Issued: 10/01/2013
• Est. Priority Date: 01/25/1999
• Status: Expired due to Fees

• Current Assignee: Cytek Biosciences Inc
• Original Assignee: Amnis Corporation (DiaSorin S.p.A.)
• Inventors: Basiji, David, Liang, Luchuan, Venkatachalam, Vidya, Morrissey, Philip, Ortyn, William
• Primary Examiner(s): BLACKMAN, ROCHELLE ANN J
• Application Number:
  US13/396,333
• Publication Number:
  US 20120148142A1
• Time in Patent Office: 595 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 an abnormal condition of cells included in a sample of cells, comprising:

(a) comparing image data for a plurality of simultaneously collected images of individual known normal cells with image data for a plurality of simultaneously collected images of individual known abnormal cells to identify at least one characteristic that can be measured and which distinguishes a known abnormal cell from a known normal cell;

(b) imaging the sample of cells to collect sample imaging data for a plurality of simultaneously collected images of individual cells in the sample cells, wherein the simultaneously collected images for the known normal cells, the known abnormal cells, and the sample cells each include at least one of the following two types of images;

(i) multispectral images; and

(ii) multimodal images; and

(c) analyzing the sample image data to determine if any cells in the sample of cells exhibit the abnormal condition, by detecting the at least one cell characteristic that distinguishes the known abnormal cells from the known normal cells.

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

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

4. The method of claim 3, wherein identifying the morphometric parameter comprises identifying a cytoplasmic area.

5. The method of claim 4, wherein identifying a cytoplasmic area comprises:

(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.

6. The method of claim 1, wherein identifying the at least one cell characteristic comprises 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.

7. The method of claim 6, wherein if the at least one cell characteristic that is identified includes the scatter intensity, identifying the scatter intensity comprises determining a mean scatter intensity by dividing a total intensity by a cellular area.

8. The method of claim 6, wherein if the at least one cell characteristic that is identified includes the scatter intensity, identifying the scatter intensity comprises calculating the scatter intensity by removing a background intensity from a total intensity.

9. The method of claim 6, wherein if the at least one cell characteristic that is identified includes the scatter intensity, identifying the scatter intensity comprises calculating the scatter intensity by determining a total intensity of local scatter maxima.

10. The method of claim 6, wherein if the at least one cell characteristic that is identified includes the scatter texture, identifying the scatter texture comprises at least one selected from the group of:

(a) identifying an intensity profile gradient metric; and

(b) identifying a variance of pixel intensities.

11. The method of claim 1, wherein each of the simultaneously collected images for the known normal cells, the known abnormal cells, and the sample cells comprise extended depth of field images.

12. The method of claim 1, wherein each of the simultaneously collected images for the known normal cells, the known abnormal cells, and the sample cells comprise at least two types of images selected from the group consisting of:

(a) a bright field image;

(b) a dark field image; and

(c) a fluorescent image.

13. An imaging system configured to acquire and analyze image data collected from a sample of cells, where the image data include a plurality of images of individual cells that are acquired simultaneously, to enable detection of any cells within the sample in which an abnormal condition exists, comprising:

(a) an image acquisition subsystem that simultaneously produces a plurality of images of individual cells in the sample of cells, the plurality images including at least one of the following types of images;

(i) multispectral images; and

(ii) multimodal images;

(b) data identifying at least one cell characteristic indicative of the abnormal condition, where the at least one cell characteristic can be measured using the plurality of images produced by the image acquisition subsystem; and

(c) a computing device used to analyze the plurality of images of individual cells to determine if the at least one cell characteristic is exhibited by any cells in the sample of cells.

14. The imaging system of claim 13, wherein the at least one characteristic comprises a photometric parameter.

15. The imaging system of claim 13, wherein the at least one characteristic comprises a morphometric parameter.

16. The imaging system of claim 15, wherein the morphometric parameter comprises cytoplasmic area.

17. The imaging system of claim 13, wherein the at least one characteristic comprises at least one characteristic selected from the group consisting of:

(a) a scatter intensity;

(b) a scatter texture;

(c) a nuclear intensity; and

(d) a nuclear texture.

18. The imaging system of claim 17, wherein if the at least one characteristic includes scatter intensity, the scatter intensity includes at least one element selected from the 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.

19. An imaging system for determining whether any cells in a sample of cells exhibit an abnormal condition, comprising:

(a) a plurality of lenses for collecting and focusing light from an individual cell in a plurality of cells included within the sample;

(b) a spectral separation element that spectrally separates the light from the individual cell into a plurality of different spectral channels;

(c) a light detector that receives the light in the different spectral channels, at least one of the plurality of lenses imaging the light in each different spectral channel on a different portion of the detector, so that the detector simultaneously produces image data for a plurality of images comprising the light in the plurality of different spectral channels; and

(d) a computing device that analyzes the images data to determine if the image data indicates that the individual cell exhibits the abnormal condition.

20. The imaging system of claim 19, wherein the plurality of images include at least two types of images selected from the group consisting of:

(a) a bright field image;

(b) a dark field image; and

(c) a fluorescent image.