Method and apparatus for cell counting and cell classification

• US 5,962,238 A
• Filed: 09/16/1996
• Issued: 10/05/1999
• Est. Priority Date: 02/17/1993
• Status: Expired due to Term

• Current Assignee: Biometric Imaging, Inc. (Becton, Dickinson & Co)
• Original Assignee: Biometric Imaging, Inc. (Becton, Dickinson & Co)
• Inventors: Sizto, Ning L., Dietz, Louis J.
• Primary Examiner(s): Wortman, Donna C.
• Application Number:
  US08/715,050
• Time in Patent Office: 1,114 Days
• Field of Search: 435/7.2, 435/7.21, 435/7.24, 435/7.25, 435/5, 435/968, 435/973, 436/172
• US Class Current: 435/7.24
• CPC Class Codes: G01N 15/1468 with spatial resolution of the texture or inner structure of the particle
• CPC Class Codes: G06V 20/69 Microscopic objects, e.g. biological cells or cellular parts
• CPC Class Codes: Y10S 435/968 High energy substrates, e.g. fluorescent, chemiluminescent, radioactive
• CPC Class Codes: Y10S 435/973 Simultaneous determination of more than one analyte
• CPC Class Codes: Y10S 436/805 Optical property

Abstract

A method and an apparatus for analyzing a material within a container, such as blood within a capillary in a volumetric cytometry system provides for detecting the edges of the container, counting the cells within the container, characterizing the cells within the container, and evaluating channels of data which contain information relevant to more than one of the detectable characteristics of the cells. A scanner scans a container of material including certain cells. Sampling circuitry is coupled to the scanner to generate scanned images of the material in the container. Two or more scanned images are generated based on fluorescence data from dyes that have overlapping spectra. The two scanned images are processed using a linear regression analysis among corresponding pixels in the scanned images near certain cells to characterize relative contents of two fluorescing dyes in a target cell. Target cells are identified from the scanned images using processing resources which identify a peak sample within a neighborhood, and compare the amplitude of the peak with the amplitude of pixels on the perimeter of the neighborhood. Upon identifying a target cell in this manner, data from the plurality of scanned images corresponding to the identified cell are saved for further analysis.

Claims

1. A method of detecting peak events indicative of target components in a fluid sample contained in a sample holder, the method comprising:

positioning an objective lens at a plurality of locations in a first direction along the sample;

focusing the objective lens in a second direction substantially perpendicular to the first direction at each of the plurality of locations to find a position of optimal fluorescence in the second direction corresponding to each of the plurality of locations;

scanning the sample in at least the first direction to detect peak events while adjusting the objective lens in the second direction to a focal length that is determined from at least one position of optimal fluorescence.

2. The method of claim 1, wherein the sample is scanned in a two dimensional plane substantially perpendicular to the second direction.

3. The method of claim 1, wherein the step of scanning includes adjusting the objective lens to a focal length determined from a linear interpolation of at least two positions of maximum fluorescence from the plurality of locations.

4. The method of claim 1, wherein the sample holder is a scan capillary.

5. The method of claim 4, wherein the first direction is substantially parallel to an axial length of the scan capillary.

6. The method of claim 1, wherein the position of optimal fluorescence is a position in the second direction at which fluorescence is maximum.

7. The method of claim 1, wherein the sample is further scanned in a third direction perpendicular to the first and second direction.

8. The method of claim 1, further comprising a step of identifying and enumerating the target components in the sample.

9. The method of claim 1, wherein the sample is a blood sample and the target components are fluorescently labeled white blood cells.

10. A method of analyzing a sample of cells in a sample holder, the sample of cells having detectable fluorescent characteristics, the method comprising:

scanning the sample to generate a stream of data sets that is representative of fluorescence in the sample holder;

processing the stream of data sets to calculate a background index;

analyzing the stream of data sets to identify a subset of data values which exceed a first threshold determined as a function of the background index; and

analyzing the subset of data values to characterize each subset of data values, wherein a second threshold based upon the background index is used to identify a subset of data values as a target cell.

11. The method of claim 10, wherein the sample holder is a fixed volume capillary.

12. The method of claim 10, wherein the sample is whole blood.

13. A method of analyzing a capillary containing a sample of cells having detectable fluorescent characteristics, the method comprising:

scanning a capillary to generate first and second streams of data sets that are representative of fluorescence in the capillary at a first and second range of wavelengths respectively;

processing the first and second streams of data sets to calculate a background index;

analyzing the first and second streams of data sets for peak events identified as first and second subsets of data values in the respective first and second streams of data sets which exceed a first threshold determined as a function of the background index; and

analyzing the first and second subsets of data values corresponding to each peak event, wherein a second threshold based upon the background index is used to identify each peak event as a target cell.

14. The method of claim 13, further comprising the steps of determining a correlation coefficient between the first subset of data values and the second subset of data values for each peak event and ignoring the peak events having a correlation coefficient less than 0.8.

15. The method of claim 13, further comprising the steps of determining a correlation coefficient between the first subset of data values and the second subset of data values for each peak event and ignoring peak events having a correlation coefficient less than 0.9.

16. The method of claim 13, further comprising the steps of filtering the first subset of data values and the second subset of data values to eliminate background characteristics and generate a respective first and second intensity value for each peak event and comparing the first and second intensity value to the second threshold to classify peak events that have intensity values that exceed the second threshold as target cells.

17. A method of analyzing a sample containing fluorescent labeled target cells in a sample holder that contains a fluorescent background which exhibits background characteristics, the method comprising the steps of:

scanning the sample to generate a first set of data values representing fluorescence in a first wavelength range and a second set of data values representing fluorescence in a second wavelength range;

analyzing the first and second sets of data values to identify peak events;

saving a first subset of data values from the first set of data values and a second subset of data values from the second set of data values for each peak event;

identifying each peak event as a target cell based upon a correlation coefficient between the first subset of data values and the second subset of data values for each peak event; and

classifying each target cell into a cell population by comparing the first set of data values with the second set of data values for each peak event.

18. The method of claim 17, further comprising the step of filtering the first subset of data values and the second subset of data values to eliminate the background characteristics and generate a respective first and second intensity value for each peak event, wherein the step of classifying each target cell further includes classifying the target cells into a cell population based upon the first intensity value relative to a magnitude of the second intensity value.

19. The method of claim 18, wherein the step of filtering is performed after the step of classifying the target cells.

20. The method of claim 17, wherein the sample holder has edges and a first set of data values has information relevant to the edges of the sample holder, the method further comprising processing the first set of data values to detect the edges of the sample holder, wherein the first subset of data values does not include data values outside the edges of the sample holder.

21. The method of claim 17, wherein the target cells are blood cells.

22. The method of claim 17, wherein the target cells are leukocytes and the sample contains red blood cells.

23. The method of claim 17 further comprising the step of calculating a background index from the first and second sets of data values, wherein:

the step of analyzing the first and second sets of data values includes identifying as target cells first and second sets of data values which exceed a first threshold determined as a function of the background index; and

the step of classifying includes generating a first and second intensity value corresponding to the first and second subsets of data and comparing the first and second intensity value for each target cell to a second threshold based upon the background index to classify each target cell into a subset class.

24. The method of claim 17, wherein the sample holder is a capillary.

25. The method of claim 17, further comprising the step of ignoring peak events whose correlation coefficient is less than 0.8.

26. The method of claim 17, further comprising the step of ignoring peak events whose correlation coefficient is less than 0.9.