U.S. patent application number 15/650105 was filed with the patent office on 2017-11-09 for cell analysis apparatus and cell analysis method.
This patent application is currently assigned to SYSMEX CORPORATION. The applicant listed for this patent is Sysmex Corporation. Invention is credited to Masakazu FUKUDA, Masaki ISHISAKA, Kazuki KISHI.
Application Number | 20170322159 15/650105 |
Document ID | / |
Family ID | 40590916 |
Filed Date | 2017-11-09 |
United States Patent
Application |
20170322159 |
Kind Code |
A1 |
ISHISAKA; Masaki ; et
al. |
November 9, 2017 |
CELL ANALYSIS APPARATUS AND CELL ANALYSIS METHOD
Abstract
A cell analyzing method includes measuring cells that are
nuclear stained, by a cytometric device, to obtain a histogram of a
parameter of a fluorescence signal, where the parameter indicates
an amount of DNA in a nucleus of a cell. A number of cells that are
distributed in an area where the parameter of the fluorescence
signal is larger than normal cells are obtained by a computer
having at least one processor. The possibility of cancer is
determined based on the obtained number of cells and the
histogram.
Inventors: |
ISHISAKA; Masaki;
(Himeji-shi, JP) ; KISHI; Kazuki; (Tokyo, JP)
; FUKUDA; Masakazu; (Kobe-shi, JP) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Sysmex Corporation |
Kobe-shi |
|
JP |
|
|
Assignee: |
SYSMEX CORPORATION
|
Family ID: |
40590916 |
Appl. No.: |
15/650105 |
Filed: |
July 14, 2017 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
14164773 |
Jan 27, 2014 |
9733186 |
|
|
15650105 |
|
|
|
|
12762703 |
Apr 19, 2010 |
9625388 |
|
|
14164773 |
|
|
|
|
PCT/JP2008/069338 |
Oct 24, 2008 |
|
|
|
12762703 |
|
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N 21/6486 20130101;
G01N 2015/1497 20130101; G01N 2015/0092 20130101; G01N 15/147
20130101 |
International
Class: |
G01N 21/64 20060101
G01N021/64; G01N 15/14 20060101 G01N015/14 |
Foreign Application Data
Date |
Code |
Application Number |
Oct 29, 2007 |
JP |
2007280738 |
Claims
1. A cell analyzing method comprising: measuring, by a cytometric
device, cells that are nuclear stained, to obtain a histogram of a
parameter of fluorescence signal, the parameter indicating an
amount of DNA in a nucleus of a cell; obtaining, by a computer
comprising at least one processor, a number of cells that are
distributed in an area where the parameter of the fluorescence
signal is larger than normal cells; and determining possibility of
cancer based on the obtained number of cells and the histogram.
2. The method according to claim 1, wherein the determination is
performed using a relative number of cells that are distributed in
an area where the parameter of the fluorescence signal is larger
than the normal cells.
3. The method according to claim 2, wherein the relative number is
a ratio of the obtained number of cells to a total number of
cells.
4. The method according to claim 1, further comprising displaying
the histogram on a display.
5. The method according to claim 1, wherein the parameter of the
fluorescence signal is a pulse area of the fluorescence signal.
6. The method according to claim 1, further comprising detecting a
peak of the normal cells from data of the histogram, wherein the
number of cells that are distributed in an area where the parameter
of the fluorescence signal is larger than the peak of the normal
cells are obtained.
7. The method according to claim 1, wherein the cells are
epithelial cells.
8. The method according to claim 2, wherein the possibility of
cancer is determined to be high when the relative number is greater
than a threshold value.
9. The method according to claim 1, wherein the measurement is
performed by measuring an intensity of fluorescence from each of
the cells that are nuclear stained.
10. A cell analyzing method comprising: measuring, by a cytometric
device, an intensity of fluorescence emitted from each of cells
that are nuclear stained to prepare a distribution of the cells
according to an amount of DNA in a nucleus of a cell; analyzing, by
a computer comprising at least one processor, the distribution of
the cells to calculate a ratio of abnormal cells which have an
amount of DNA greater than normal cells; and displaying the
calculated ratio.
11. A cell analyzer comprising: a cytometric device which measures
cells that are nuclear stained; a display which displays a
histogram of a parameter of fluorescence signal by using a result
of the measurement by the measuring portion, the parameter
indicating an amount of DNA in a nucleus in a cell; and a computer
comprising at least one processor configured to obtain a number of
cells that are distributed in an area where the parameter of the
fluorescence signal is larger than normal cells, and determine
possibility of cancer based on the obtained number of cells and the
histogram.
12. The analyzer according to claim 1, wherein the computer is
configured to determine the possibility of cancer based on a
relative number of cells that are distributed in an area where the
parameter of the fluorescence signal is larger than the normal
cells.
13. The analyzer according to claim 12, wherein the relative number
is a ratio of the obtained number of cells to a total number of
cells.
14. The analyzer according to claim 11, wherein the display is
configured to display the histogram and a determination result by
the computer.
15. The analyzer according to claim 11, wherein the parameter of
the fluorescence signal is a pulse area of the fluorescence
signal.
16. The analyzer according to claim 11, wherein the computer is
configured to detect a peak of the normal cells from data of the
histogram and obtain the number of cells that are distributed in an
area where the parameter of the fluorescence signal is larger than
the peak of the normal cells.
17. The analyzer according to claim 11, wherein the cells are
epithelial cells.
18. The analyzer according to claim 12, wherein the computer is
configured to determine the possibility of cancer to be high when
the relative number is greater than a threshold value.
19. The analyzer according to claim 11, wherein the cytometric
device comprises: a flow cell that accommodates a flow of cells
that are nuclear stained; a light source that emits light to the
cells flowing through the flow cell; and a fluorescence detector
that detects fluorescence from each of the cells flowing through
the flow cell and outputs a fluorescence signal.
20. The analyzer according to claim 11, wherein the cytometric
device is configured to measure an intensity of fluorescence from
each of the cells that are nuclear stained.
Description
RELATED APPLICATIONS
[0001] This application is a divisional application of U.S. Ser.
No. 14/164,773, filed Jan. 27, 2014, which is a continuation of
U.S. application Ser. No. 12/762,703 filed on Apr. 19, 2010, which
is a continuation of PCT/JP2008/069338 filed on Oct. 24, 2008,
which claims priority to Japanese Application No. 2007-280738 filed
on Oct. 29, 2007. The entire contents of these applications are
incorporated herein by reference.
TECHNICAL FIELD
[0002] The present invention relates to a cell analysis apparatus
and a cell analysis method. More particularly, the present
invention relates to a cell analysis apparatus and a cell analysis
method by which a measurement sample flowing in a flow cell is
illuminated with laser beam and the light from the measurement
sample is used to analyze cells in the measurement sample.
BACKGROUND ART
[0003] Flow cytometry method for illuminating a measurement sample
including cells as a measuring object with laser beam and measuring
the size and shape of each cell by using scattered light and
fluorescence from the measurement sample, is disclosed in WO
publication No. 2006/103920 for example. According to this flow
cytometry method, a measurement sample including cells as a
measuring object is surrounded by sheath liquid and is squeezed in
a sheath flow cell to arrange the cells in one straight line to
pass the flow cell. In this manner, a plurality of cells are
suppressed from simultaneously passing through a detection region
in the sheath flow cell.
[0004] However, cells may aggregate in the measurement sample. The
existence of aggregating cells (a plurality of cells that
aggregate) makes it difficult to accurately measure the sizes and
shapes of the respective cells in the measurement sample for
example.
[0005] In view of the above, according to an analysis apparatus
disclosed in WO publication No. 2006/103920, forward-scattered
light from a measurement sample illuminated with laser beam is
detected. Then, a ratio between the difference integration value of
the signal waveform of the obtained forward-scattered light and the
peak value of the signal waveform is used to determine whether the
signal waveform includes a trough or not to thereby distinguish
between aggregating cells and non-aggregating cells (a plurality of
cells that do not aggregate and each of which exists as a single
cell).
SUMMARY
[0006] However, the signal waveform of the forward-scattered light
detected from cells has a height that changes depending on how the
cells aggregate and a direction to which the cells flow for
example. This consequently may cause a signal waveform of
forward-scattered light that has unclear peak and trough. Thus, the
analysis apparatus disclosed in WO publication No. 2006/103920 is
limited in the improvement of the accuracy of distinguishing
between aggregating cells and non-aggregating cells.
[0007] The present invention has been made in view of the situation
as described above. It is an objective of the present invention to
provide a cell analysis apparatus and a cell analysis method which
is capable of distinguishing between aggregating cells and
non-aggregating cells accurately.
[0008] The cell analysis apparatus according to a first aspect of
this invention is a cell analysis apparatus for analyzing measuring
object cells included in a biological sample, comprising: a
detection section for flowing a measurement sample obtained from
the biological sample and a pigment into a flow cell, irradiating
the measurement sample flowing in the flow cell with laser beam,
and detecting fluorescence from the measurement sample; a signal
processing section for obtaining, based on a fluorescence signal
outputted from the detection section, a value reflecting height of
a waveform of the fluorescence signal and a value reflecting length
of a ridge line of the waveform of the fluorescence signal; and an
analysis section for distinguishing between an aggregating cell
formed by aggregation of a plurality of cells and a non-aggregating
cell, based on the value reflecting the height of the waveform of
the fluorescence signal and the value reflecting the length of the
ridge line of the waveform of the fluorescence signal obtained by
the signal processing section.
[0009] The cell analysis apparatus according to a second aspect of
this invention is a cell analysis apparatus for analyzing measuring
object cells included in a biological sample, comprising: a
detection section for flowing a measurement sample obtained from
the biological sample and a pigment into a flow cell, irradiating
the measurement sample flowing in the flow cell with laser beam,
and detecting fluorescence from the measurement sample; a signal
processing section for obtaining, based on a fluorescence signal
outputted from the detection section, a first value reflecting
height of a waveform of the fluorescence signal, a second value
reflecting length of a ridge line of the waveform of the
fluorescence signal, and a third value reflecting DNA amount of a
nucleus of the measuring object cell; and an analysis section for
classifying an abnormal cell from the measuring object cells
included in the measurement sample, based on the first value, the
second value, and the third value obtained by the signal processing
section.
[0010] The cell analysis method according to a third aspect of this
invention is a cell analysis method, comprising: a first step of
preparing a measurement sample by mixing a biological sample with a
pigment; a second step of flowing the prepared measurement sample
into a flow cell, irradiating the measurement sample flowing in the
flow cell with laser beam, and detecting fluorescence from the
measurement sample; a third step of obtaining, based on a
fluorescence signal generated from the fluorescence, a value
reflecting height of a waveform of the fluorescence signal and a
value reflecting length of a ridge line of the waveform of the
fluorescence signal; and a fourth step of distinguishing between an
aggregating cell formed by aggregation of a plurality of cells and
a non-aggregating cell, based on the value reflecting the height of
the waveform of the fluorescence signal and the value reflecting
the length of the ridge line of the waveform of the fluorescence
signal.
[0011] The cell analysis method according to a fourth aspect of
this invention is a cell analysis method, comprising: a first step
of preparing a measurement sample by mixing a biological sample
with a pigment; a second step of flowing the prepared measurement
sample into a flow cell, irradiating the measurement sample flowing
in the flow cell with laser beam, and detecting fluorescence from
the measurement sample; a third step of obtaining, based on a
fluorescence signal generated from the fluorescence, a first value
reflecting height of a waveform of the fluorescence signal, a
second value reflecting length of a ridge line of the waveform of
the fluorescence signal, and a third value reflecting DNA amount of
a nucleus of the measuring object cell; and a fourth step of
classifying an abnormal cell from the measuring object cells
included in the measurement sample, based on the first value, the
second value, and the third value.
BRIEF DESCRIPTION OF THE DRAWING
[0012] FIG. 1 is a perspective view illustrating one embodiment of
a cell analysis apparatus of the present invention;
[0013] FIG. 2 is a block diagram illustrating the configuration of
the cell analysis apparatus shown in FIG. 1;
[0014] FIG. 3 is a block diagram illustrating a personal computer
configuring a system control section;
[0015] FIG. 4 illustrates the configuration of an optical detection
section;
[0016] FIG. 5 illustrates a cell passing through a beam spot;
[0017] FIG. 6 is a scattergram in which the vertical axis shows
values each of which is obtained by dividing a difference
integration value of a fluorescence signal waveform of a measuring
object cell by a peak value and the horizontal axis shows the pulse
widths of side-scattered light signals;
[0018] FIG. 7A shows a single cell (non-aggregating cell) C1;
[0019] FIG. 7B illustrates the signal waveform of a single
cell;
[0020] FIG. 8A shows aggregating cells C2 formed by aggregation of
three cells;
[0021] FIG. 8B illustrates the signal waveform of an aggregating
cell composed of two cells;
[0022] FIG. 9A shows aggregating cells C3 formed by aggregation of
three cells;
[0023] FIG. 9B illustrates the signal waveform of an aggregating
cell composed of three cells;
[0024] FIG. 10 is a scattergram in which the vertical axis shows
the peak values of forward-scattered light signals obtained from
the measurement sample and the horizontal axis shows the pulse
widths of the forward-scattered light signals;
[0025] FIG. 11 is a flowchart illustrating the flow of the
processing by the CPU of a system control section;
[0026] FIG. 12 is a flowchart illustrating the cell analysis
processing by the CPU of the system control section;
[0027] FIG. 13 is a side view illustrating an optical detection
section;
[0028] FIG. 14 is a top view illustrating the optical detection
section;
[0029] FIG. 15 is a histogram in which the horizontal axis shows
the pulse areas of lateral fluorescence signals obtained from the
measurement sample;
[0030] FIG. 16 is a flowchart illustrating the second cell analysis
processing by the CPU of the system control section;
[0031] FIG. 17 is a flowchart illustrating the third cell analysis
processing by the CPU of the system control section; and
[0032] FIG. 18 illustrates the beam shape in the direction to which
the measurement sample flows.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0033] The following section will describe in detail an embodiment
of a cell analysis apparatus and a cell analysis method of the
present invention with reference to the attached drawings.
Entire Configuration of Cell Analysis Apparatus
[0034] FIG. 1 is a perspective view illustrating a cell analysis
apparatus 10 according to one embodiment of the present invention.
The cell analysis apparatus 10 is used for the following process.
Specifically, a measurement sample including cells collected from a
patient is caused to flow into a flow cell. Then, the measurement
sample flowing in the flow cell is irradiated with laser beam.
Then, the light from the measurement sample (e.g.,
forward-scattered light or lateral fluorescence) is detected and
analyzed to thereby determine whether the cells include cancer and
atypical cells or not. Specifically, the cell analysis apparatus 10
is used for screening a cervical cancer by using epithelial cells
of the endocervix. The cell analysis apparatus 10 includes: an
apparatus main body 12 that measures a sample for example; and a
system control section 13 that is connected to the apparatus main
body 12 and that analyzes the measurement result for example.
[0035] As shown in FIG. 2, the apparatus main body 12 of the cell
analysis apparatus 10 includes: an optical detection section 3 for
detecting from the measurement sample the information such as cell
or nucleus size information; a signal processing circuit 4; a
measurement control section 16; a driving section 17 such as a
motor, an actuator, and a valve; and various sensors 18. The signal
processing circuit 4 includes: an analog signal processing circuit
that subjects the result obtained by amplifying the output from the
optical detection section 3 by a preamplifier (not shown) to an
amplification processing or a filter processing or the like; an A/D
converter that converts the output from the analog signal
processing circuit to a digital signal; and a digital signal
processing circuit that subjects the digital signal to a
predetermined waveform processing. The measurement control section
16 controls the operation of the driving section 17 while
processing the signal from the sensor 18 to thereby providing the
suction and measurement of the measurement sample. The screening of
a cervical cancer can be performed by preparing a measurement
sample obtained by subjecting cells collected from the endocervix
of the patient (epithelial cells) to known processings such as
centrifugation (concentration), dilution (cleaning), agitation
(tapping), or PI staining. The prepared measurement sample is
stored in a test tube and the test tube is placed under a pipette
(not shown) of the apparatus main body 12. Then, the sample is
sucked by the pipette and is supplied to a flow cell. The PI
staining is performed by propidium iodide (PI) that is fluorescence
staining liquid including pigments. The PI staining can selectively
stain a nucleus, thus allowing the detection of the fluorescence
from the nucleus.
Configuration of Measurement Control Section
[0036] The measurement control section 16 includes, for example, a
microprocessor 20, a storage section 21, an I/O controller 22, a
sensor signal processing section 23, a driving section control
driver 24, and an external communication controller 25. The storage
section 21 is composed of ROM, RAM or the like. The ROM stores
therein a control program for controlling the driving section 17
and the data required to execute the control program. The
microprocessor 20 can load the control program to the RAM or can
directly execute the control program from the ROM.
[0037] The microprocessor 20 receives the signal from the sensor 18
via the sensor signal processing section 23 and the I/O controller
22. The microprocessor 20 can execute the control program to
thereby control, in accordance with the signal from the sensor 18,
the driving section 17 via the I/O controller 22 and the driving
section control driver 24.
[0038] The data processed by the microprocessor 20 and the data
required for the processing by the microprocessor 20 are exchanged
via the external communication controller 25 with an external
apparatus such as the system control section 13.
Configuration of System Control Section
[0039] FIG. 3 is a block diagram illustrating the system control
section 13. The system control section 13 is composed of a personal
computer for example and is mainly composed of a main body 27, a
display section 28, and an input section 29. The main body 27 is
mainly composed of a CPU 27a, a ROM 27b, a RAM 27c, a hard disk
27d, a reading apparatus 27e, an input/output interface 27f, and an
image output interface 27g that are connected by a bus 27h so that
communication can be provided thereamong.
[0040] The CPU 27a can execute a computer program stored in the ROM
27b and a computer program loaded to the RAM 27c. The ROM 27b is
configured by a mask ROM, PROM, EPROM, or EEPROM for example. The
ROM 27b stores therein a computer program executed by the CPU 27a
and the data used for the computer program. The RAM 27c is
configured by a SRAM or DRAM or the like. The RAM 27c is used to
read computer programs recorded in the ROM 27b and the hard disk
27d and is also used as a work area of the CPU 27a for executing
these computer programs.
[0041] In the hard disk 27d, there are installed various computer
programs to be executed by the CPU 27a such as an operating system
and an application program, and data used to execute the computer
programs. For example, in the hard disk 27d, there is installed an
operating system providing a graphical user interface environment
such as Windows.RTM. manufactured and sold by US Microsoft
Corporation. In the hard disk 27d, there are installed a computer
program for determining aggregating particles and non-aggregating
particles and the data used to execute the computer program.
[0042] In the hard disk 27d, there is also installed operation
programs for sending a measurement order (operation instruction) to
the measurement control section 16 of the cell analysis apparatus
10, receiving and processing the measurement result of the
measurement by the apparatus main body 12, and displaying the
processed analysis result for example. This operation program
operates on the operating system.
[0043] The reading apparatus 27e is configured by a flexible disk
drive, a CD-ROM drive, or a DVD-ROM drive for example and can read
the computer program or data recorded in a portable recording
medium. The input/output interface 27f is configured, for example,
by a serial interface such as USB, IEEE 1394 or RS-232C, a parallel
interface such as SCSI, IDE, or IEEE 1284, and an analog interface
such as a D/A converter or A/D converter. The input/output
interface 27f is connected with the input section 29 composed of a
keyboard and a mouse. A user can use the input section 29 to input
data to the personal computer. The input/output interface 27f is
also connected to the apparatus main body 12 and can exchange data
with the apparatus main body 12 for example.
[0044] The image output interface 27g is connected with the display
section 28 composed of LCD or CRT for example. The image output
interface 27g outputs to the display section 28 a video signal
depending on the image data given from the CPU 27a. In accordance
with the input video signal, the display section 28 displays an
image (screen).
Configuration of Optical Detection Section
[0045] FIG. 4 illustrates the configuration of the optical
detection section 3. In FIG. 4, a lens system (optical system) 52
collects the laser beam emitted from a semiconductor laser 53 as a
light source to the measurement sample flowing in a flow cell 51. A
light collection lens 54 causes the forward-scattered light from
the cell in the measurement sample to be collected in a photodiode
55 as a scattered light detector. Although the lens system 52 is
shown as a single lens for simplicity, the lens system 52 can be
configured more specifically as shown in FIG. 13 and FIG. 14 as a
lens group composed of, in an order from the semiconductor laser
53, a collimator lens 52a, a cylinder lens system (a plane-convex
cylinder lens 52b+a biconcave cylinder lens 52c), and a condenser
lens system (a condenser lens 52d+a condenser lens 52e).
[0046] As shown in FIG. 13, when the optical detection section 3 is
seen from a side face, the radial laser beam emitted from the
semiconductor laser 53 is converted by a collimator lens 52a to
parallel light. The parallel light passes the plane-convex cylinder
lens 52b and the biconcave cylinder lens 52c without being bent.
Then, the light is caused by the condenser lens 52d and the
condenser lens 52e to be collected at the first light collection
point A in the measurement sample flowing in the flow cell 51.
[0047] When the optical detection section 3 is seen from the upper
side as shown in FIG. 14 on the other hand, the radial laser beam
emitted from the semiconductor laser 53 is converted by the
collimator lens 52a to parallel light. Then, the parallel light is
caused by the plane-convex cylinder lens 52b to converge in a
direction orthogonal to the direction to which the measurement
sample flows. Then, the light is caused by the biconcave cylinder
lens 52c to diverge in a direction orthogonal to the direction to
which the measurement sample flows. Then, the light is collected by
the condenser lens 52d and the condenser lens 52e at the second
light collection point B at the rear side of the flow cell 51.
[0048] By the lens system 52 as described above, the beam shape at
the first light collection point A (the beam shape seen from the
semiconductor laser 53-side) is caused to converge in the direction
to which the measurement sample flows. Then, the beam shape is a
long ellipse-like shape extending in the direction orthogonal to
the direction to which the measurement sample flows. Specifically,
the beam spot having a diameter of 3 to 8 .mu.m in the direction to
which the measurement sample flows in the flow cell 51 and having a
diameter of 300 to 600 .mu.m in the direction orthogonal to the
direction to which the measurement sample flows is emitted to the
measurement sample flowing in the flow cell 51 while forming the
first light collection point A on a plane passing the direction to
which the measurement sample flows.
[0049] The lens system 52 is not limited to the above configuration
and also may be changed appropriately.
[0050] Another light collection lens 56 collects the
lateral-scattered light and the lateral fluorescence from the cell
or the nucleus in the cell at a dichroic mirror 57. The dichroic
mirror 57 reflects the lateral-scattered light to a photomultiplier
58 as a scattered light detector and transmits the lateral
fluorescence to a photomultiplier 59 as a fluorescence detector.
These lights reflect the features of the cell and nucleus in the
measurement sample. Then, the photodiode 55, the photomultiplier
58, and the photomultiplier 59 convert the detected light to
electric signals to output a forward-scattered light signal (FSC),
a lateral-scattered light signal (SSC), and a lateral fluorescence
signal (SFL), respectively. These signals are amplified by a
preamplifier (not shown). Then, the signals are sent to the
above-described signal processing circuit 4 (see FIG. 2).
[0051] As shown in FIG. 2, the forward-scattered light data (FSC),
the lateral-scattered light data (SSC), and the lateral
fluorescence data (SFL) obtained by being subjected by the signal
processing circuit 4 to a signal processing such as filter
processing and AID conversion processing are sent by the
microprocessor 20 to the above-described system control section 13
via the external communication controller 25. Based on the
forward-scattered light data (FSC), the lateral-scattered light
data (SSC), and the lateral fluorescence data (SFL), the system
control section 13 prepares a scattergram and a histogram for
analyzing the cell and the nucleus.
[0052] Although the light source may be gas laser instead of the
semiconductor laser, semiconductor laser is preferably used from
the viewpoints of low cost, small size, and low power consumption.
The use of semiconductor laser can reduce the product cost and also
can provide the apparatus with a smaller size and power saving. In
the present embodiment, blue semiconductor laser having a short
wavelength is used that is advantageous in narrowing beam. The blue
semiconductor laser is also advantageous to a fluorescence
excitation wavelength such as PI. Among semiconductor lasers, red
semiconductor laser also may be used that is low-cost and
long-life, and that is stably supplied from manufacturers.
[0053] In the present embodiment, the lens system 52 (FIG. 4) as an
optical system is used to form a beam spot having a predetermined
size. Specifically, such a substantially-elliptical beam spot that
has a diameter of 3 to 8 .mu.m in the direction to which the
measurement sample flows in the flow cell 51 and a diameter of 300
to 600 .mu.m in the direction orthogonal to the direction to which
the measurement sample flows is formed on the measurement sample.
FIG. 5 illustrates the cell passing through the beam spot. In FIG.
5, the up-and-down direction is the direction to which the
measurement sample flows in the flow cell. In FIG. 5, the right
beam spot is a beam spot in a conventional general apparatus used
to detect red blood cells and white blood cells in blood. The left
beam spot is a beam spot formed by an optical system of a cell
analysis apparatus according to the present embodiment. For the
convenience of the drawing, the longitudinal size of the beam spot
is reduced when compared to the size in the orthogonal direction
(in the up-and-down direction). However, an actual beam spot of the
present embodiment has a very long and thin cross-sectional
shape.
[0054] In the present embodiment, the fluorescence from the
measurement sample flowing in the flow cell is detected by the
photomultiplier 59. Based on the fluorescence signal output from
the photomultiplier 59, the signal processing circuit 4 acquires a
peak value (PEAK) of the fluorescence signal waveform as a value
reflecting the height of the signal waveform. The signal processing
circuit 4 also acquires a difference integration value (DIV) of the
signal waveform as a value reflecting the length of the ridge line
of the signal waveform. FIG. 9B illustrates the signal waveform of
a cell C3 of FIG. 9A in which the vertical axis shows the detected
light intensity and the horizontal axis shows the time at which an
optical signal is detected. As shown in FIG. 9B, the peak value
(PEAK) of the fluorescence signal waveform (chain line) shows the
maximum intensity of the detected fluorescence (PEAK in FIG. 9B)
and the difference integration value (DIV) of the fluorescence
signal waveform shows the length of the fluorescence signal
waveform having a higher intensity than the base line (Base Line 1)
(total of the lengths of the waveform from the point S to the point
T, the waveform from the point U to the point V, and the waveform
from the point W to the point X). The system control section 13
receives the lateral fluorescence data including the difference
integration value (DIV) of the fluorescence signal waveform and the
peak value (PEAK) of the fluorescence signal waveform via the
external communication controller 25. Then, the system control
section 13 compares a value (DIV/PEAK) obtained by dividing the
difference integration value (DIV) of the fluorescence signal
waveform by the peak value (PEAK) of the fluorescence signal
waveform with a predetermined threshold value to thereby determine
whether the cell is an aggregating cell or a non-aggregating
cell.
[0055] A difference integration value is a value obtained by
subjecting signal waveforms to differentiation to add up the
resulting the absolute values. A difference integration value of a
signal having no trough in the waveform is approximately equal to a
value obtained by doubling the peak value of the signal. On the
other hand, a difference integration value of a signal having a
trough in the waveform is higher than a value obtained by doubling
the peak value of the signal. An increase in the trough in the
waveform and a deeper trough cause a larger difference from a value
obtained by doubling the peak value.
[0056] In view of the above, the system control section 13
considers the noise superposed on the signal for example, and
"2.6", which is a value slightly higher than "2", is used as the
above "predetermined threshold value" functioning as a reference
value for determining whether a measuring object cell is an
aggregating cell or a non-aggregating cell. Although the
predetermined threshold value is not limited to 2.6, the
predetermined threshold value is preferably within a range from 2.2
to 3. When a value (DIV/PEAK) obtained by dividing the difference
integration value (DIV) of the fluorescence signal waveform by the
peak value (PEAK) of the fluorescence signal waveform is higher
than the predetermined threshold value, it means that the
fluorescence signal waveform includes at least one trough. Thus,
the measuring object cell can be classified as an aggregating cell
which is an aggregation of a plurality of cells.
[0057] FIG. 6 is a (DIV/PEAK)-SSCW scattergram in which the
vertical axis shows the value (DIV/PEAK) obtained by dividing the
difference integration value (DIV) of the fluorescence signal
waveform of the measuring object cell by the peak value (PEAK) and
the horizontal axis shows the pulse width (SSCW) of the signal
waveform of the lateral-scattered light. In FIG. 6, the cells
distributed in the region shown by A have values on the vertical
axis (difference integration value of fluorescence signal
waveform/peak value (DIV/PEAK)) in a range from about 2 to 2.6.
These cells are single cells (non-aggregating cells) C1 as shown in
FIG. 7A. FIG. 7B illustrates the signal waveform of the cell C1. As
shown in FIG. 7B, in the case of a single cell, the signal waveform
peak is one, but the fluorescence signal waveform (chain line)
shows a clearer peak when compared with the signal waveform of the
forward-scattered light (solid line) and the signal waveform of the
lateral-scattered light (broken line).
[0058] In FIG. 6, the cells distributed in the region shown by B
have values on the vertical axis within a range from about 3.5 to
4.2. These samples are aggregating cells C2 formed by aggregation
of two cells as shown in FIG. 8A. In FIG. 6, the cells distributed
in the region shown by C have values on the vertical axis within a
range from about 4.5 to 7. These cells are aggregating cells C3
formed by aggregation of three cells as shown in FIG. 9A. FIG. 8B
illustrates the signal waveform of the cell C2. As shown in FIG. 8B
and FIG. 9B, the waveform of the fluorescence signal shows clearer
peak and trough parts when compared with the signal waveform of the
forward-scattered light and the signal waveform of the
lateral-scattered light.
[0059] As described above, when compared with the signal waveform
of the forward-scattered light and the signal waveform of the
lateral-scattered light, the fluorescence signal waveform has
clearer peak and trough parts. Thus, whether an aggregating cell or
a non-aggregating cell can be determined accurately.
[0060] In the present embodiment, the beam spot has a diameter of 3
to 8 .mu.m in the direction to which the measurement sample flows.
Thus, the nucleus detection can have an improved S/N ratio. In the
present embodiment, a nucleus is subjected to PI staining and a
fluorescence signal from the nucleus is used. The PI staining
causes a slightly-stained cell membrane in addition to the stained
nucleus and also causes the rest of the dye used for the staining
to be flowed in the flow cell, thus causing fluorescence from parts
other than the nucleus. Therefore, the photomultiplier 59 (FIG. 4)
as a fluorescence detector detects the fluorescence as noise from
parts other than the nucleus. However, the lens system 52 of the
optical detection section 3 reduces the diameter in the beam spot
in the direction to which the measurement sample flows to 3 to 8
.mu.m. Thus, a clearer distinction can be made between the
fluorescence from the nucleus and the fluorescence from parts other
than the nucleus. Specifically, by reducing the beam spot diameter
to 3 to 8 .mu.m in consideration of the nucleus size (5 to 7
.mu.m), noise can be reduced to provide a sharp rise of the
fluorescence signal pulse to thereby make the peak clear.
[0061] To make the diameter in the beam spot in the above flowing
direction smaller than 3 .mu.m, the lens system 52 must have a
shorter focal length to cause a shallow region in which the laser
beam has a stable intensity (focal depth). FIG. 18 illustrates the
beam shape in the direction to which the measurement sample flows.
As shown in FIG. 18, the focal depth shows a region covering up to
a point at which the beam diameter becomes 1.1 times larger than
the beam diameter D in the beam spot. As the beam diameter
increases, the light intensity weakens. When the focal depth is
shallow, laser beam cannot be stably emitted to the nucleus of the
cell having a size of about 20 to 100 .mu.m. On the other hand,
when the diameter in the above flow direction is larger than 8
.mu.m, the detection ratio of fluorescence as noise generated from
parts other than the nucleus is increased. Thus, the rise of the
fluorescence signal pulse is smooth to cause an obscure range of
the pulse width of the fluorescence signal, thus deteriorating
measurement accuracy. Furthermore, a plurality of cell nucleuses
simultaneously pass through the beam spot with a higher frequency
and the measurement accuracy deteriorates also from this point.
Thus, it is preferable to select, in consideration of the above
focal depth, the diameter in the beam spot in the direction to
which the measurement sample flows. Specifically, the beam spot is
preferably formed so that the laser beam narrowed in the direction
to which the measurement sample flows has a focal depth of 20 to
110 .mu.m. In order to stably emit laser beam to the nucleus, the
beam spot diameter in the flow direction is preferably 3.5 to 7.5
.mu.m and is more preferably 4 to 7 .mu.m.
[0062] Since the beam spot diameter is within a range from 300 to
600 .mu.m in the direction orthogonal to the direction to which the
measurement sample flows, the entire epithelial cell of endocervix
(about 60 .mu.m) can pass a stable region of laser beam (a region
in which the intensity is 0.95 or more when assuming that the laser
beam forming the Gaussian distribution has a peak intensity of 1).
As a result, stable scattered light can be obtained from the cell
and the size of the cell can be measured accurately. Since the
diameter in the direction orthogonal to the flow is 300 .mu.m or
more, the stable region of laser beam is increased and thus stable
scattered light from the cell can be obtained. On the other hand,
the diameter in the direction orthogonal to the flow of 600 .mu.m
or less increases the intensity of the laser beam close to the
center and thus stable scattered light can be obtained. In order to
obtain stable scattered light from the cell, the diameter in the
direction orthogonal to the direction to which the measurement
sample flows is preferably 350 to 550 .mu.m.
Classification of Abnormal Cell
[0063] When cells changes to cancer and atypical cells, the cell
division is activated to consequently cause the DNA amount to be
higher than that of a normal cell. Thus, this DNA amount can be
used as an indicator of cancer and atypical cells. As a value
reflecting the DNA amount in the nucleus, an area of the pulse of a
fluorescence signal from a measuring object cell irradiated with
laser beam (fluorescence amount) (SFLI) can be used. As shown in
FIG. 9B, the area of the pulse of the fluorescence signal
(fluorescence amount) (SFLI) shows the area surrounded by the base
line (Base Line 1) and the fluorescence signal waveform. The signal
processing circuit 4 acquires, based on the fluorescence signal
output from the photomultiplier 59, the area of the pulse of the
fluorescence signal (fluorescence amount) (SFLI) as a value
reflecting the DNA amount of the nucleus of the measuring object
cell. Then, the system control section 13 determines whether this
fluorescence amount is equal to or higher than a predetermined
threshold value or not. When this fluorescence amount is equal to
or higher than the predetermined threshold value, the object cell
is classified as a cancer and atypical cell having an abnormal DNA
amount.
[0064] The most part of the sample used in the screening of a
cervical cancer is composed of normal cells. Thus, when the
histogram as shown in FIG. 15 is drawn in which the horizontal axis
shows the area of the pulse of the fluorescence signal
(fluorescence amount), a peak appears at a position corresponding
to normal cells. The fluorescence amount at this peak position
shows the DNA amount of normal cells. Thus, the system control
section 13 classifies as abnormal cells those cells showing a 2.5
times or higher fluorescence amount than that of normal cells.
[0065] When two or more cells pass the beam spot of the laser beam
while aggregating to one another, the fluorescence from a plurality
of nucleuses is detected by the photomultiplier 59. Thus, a pulse
having the entire large area is presumably output. However, as
described above, according to the present embodiment, a value
obtained by dividing the difference integration value of the
fluorescence signal waveform by the peak value (DIV/PEAK) can be
used to accurately exclude the data due to aggregating cells. This
can consequently increase the classification accuracy of abnormal
cells (cancer and atypical cells). Specifically, regarding those
cells measured as having a high DNA amount because the cells are
aggregating cells, these cells can be prevented from being
mistakenly classified as abnormal cells.
[0066] A measurement sample may include, in addition to a measuring
object cell, debris such as mucus, the remaining blood, and pieces
of cells. When this debris is included in a high amount in the
measurement sample, the fluorescence from the debris is detected as
noise to thereby deteriorate the measurement accuracy. In this
case, since the debris has a smaller size compared with the
measuring object cell, the signal processing circuit 4 acquires,
from the forward-scattered light signal outputted from the
photodiode 55, the signal waveform pulse width of the
forward-scattered light (FSCW) and the signal waveform peak value
of the forward-scattered light (FSCP) as a plurality of parameters
reflecting the sizes of particles including the measuring object
cell. As shown in FIG. 7B, the signal waveform peak value of the
forward-scattered light (FSCP) shows the maximum intensity of the
detected forward-scattered light (FSCP in FIG. 7B). The signal
waveform pulse width of the forward-scattered light (FSCW) shows a
signal waveform width of the forward-scattered light having a
higher intensity than the base line (Base Line 2). The system
control section 13 receives the forward-scattered light data
including the signal waveform pulse width of the forward-scattered
light (FSCW) and the signal waveform peak value of the
forward-scattered light (FSCP) from the apparatus main body 12 via
the external communication controller 25. Then, the system control
section 13 prepares a scattergram using the signal waveform pulse
width of the forward-scattered light (FSCW) and the signal waveform
peak value of the forward-scattered light (FSCP) to thereby
distinguish, based on the scattergram, between a measuring object
cell and particles other than the measuring object cell
(debris).
[0067] FIG. 10 is a FSCW-FSCP scattergram in which the horizontal
axis shows the signal waveform pulse width of the forward-scattered
light (FSCW) and the vertical axis shows the signal waveform peak
value of the forward-scattered light (FSCP). Since a debris has a
smaller size when compared with a measuring object cell, the signal
waveform peak value of the forward-scattered light (FSCP) and the
signal waveform pulse width of the forward-scattered light (FSCW),
each of which reflects the size of particles, are smaller than the
measuring object cell. In FIG. 10, one group distributed at the
lower-left part shows debris. Thus, by assuming the cells in the
region G as an analysis target in the subsequent process, the
determination of an abnormal cell can be performed with a further
higher accuracy.
Cell Analysis Method
[0068] Next, the following section will describe an embodiment of a
cell analysis method using the cell analysis apparatus 10 (see FIG.
1).
[0069] First, a measurement sample to be flowed in a flow cell is
manually prepared by a user. Specifically, a cell (epithelial cell)
collected from the endocervix of a patient is subjected to known
processes such as centrifugation (concentration), dilution
(cleaning), agitation (tapping), or PI staining, thereby preparing
a measurement sample.
[0070] Then, the user stores the prepared measurement sample in a
test tube (not shown) and positions the test tube at the lower side
of a pipette (not shown) of the apparatus main body.
[0071] Next, the following section will describe the flow of the
processing by the system control section 13 with reference to FIG.
11 and FIG. 12.
[0072] First, when the power source of the system control section
13 is turned ON, the CPU 27a of the system control section 13
initializes a computer program stored in the system control section
13 (Step S1). Next, the CPU 27a determines whether a measurement
instruction from the user is received or not (Step S2). When the
measurement instruction is received, the CPU 27a sends a
measurement start signal to the apparatus body 12 via an I/O
interface 27f (Step S3). When the measurement instruction is not
received, the CPU 27a proceeds to the processing of Step S6.
[0073] When the measurement start signal is sent to the apparatus
main body 12, the measurement sample stored in the test tube is
sucked by a pipette in the apparatus main body 12 and is supplied
to the flow cell 51 shown in FIG. 4. Then, the measurement sample
flowing in the flow cell 51 is irradiated with laser beam. Then,
the forward-scattered light from the measurement sample is detected
by the photodiode 55, the lateral-scattered light is detected by
the photomultiplier 58, and the lateral fluorescence is detected by
the photomultiplier 59.
[0074] Next, the forward-scattered light signal (FSC), the
lateral-scattered light signal (SSC), and the fluorescence signal
(SFL) outputted from the optical detection section 3 are sent to
the signal processing circuit 4. Then, measurement data obtained by
subjecting the signals to a predetermined processing by the signal
processing circuit 4 is sent to the system control section 13 via
the external communication controller 25.
[0075] On the other hand, the CPU 27a of the system control section
13 determines whether the measurement data (forward-scattered light
data (FSC), the lateral-scattered light data (SSC), and the lateral
fluorescence data (SFL)) is received from the apparatus main body
12 via the external communication controller 25 or not (Step S4).
When the measurement data is received, the CPU 27a stores the
measurement data in the hard disk 27d to subsequently execute a
cell analysis processing (Step S5). When the measurement data is
not received, the CPU 27a proceeds to the processing of Step
S6.
[0076] After the cell analysis processing, the CPU 27a determines
whether a shutdown instruction is received or not (Step S6). When
the shutdown instruction is received, the CPU 27a completes the
processing. When the shutdown instruction is not received, the CPU
27a returns to the processing of Step S2.
[0077] Next, the following section will describe the cell analysis
processing of Step S5 with reference to FIG. 12.
[0078] First, the CPU 27a reads, from among the forward-scattered
light data received from the apparatus main body 12, the signal
waveform pulse width of the forward-scattered light (FSCW) and the
signal waveform peak value of the forward-scattered light (FSCP)
from the hard disk 27d and stores them into the RAM 27c (Step
S501). Then, the CPU 27a prepares a FSCW-FSCP scattergram shown in
FIG. 10 in which the horizontal axis shows the read pulse width
(FSCW) and the vertical axis shows the peak value (FSCP) (Step
S502). Then, the CPU 27a assumes the cells in the region G of this
scattergram as an analysis target in the subsequent process. As a
result, particles at the exterior of the region G are removed as
the debris other than the measuring object cell.
[0079] Next, the CPU 27a reads, from among the lateral fluorescence
data of the analysis object cell, the difference integration value
of the fluorescence signal waveform (DIV) and the peak value of the
fluorescence signal waveform (PEAK) from the hard disk 27d and
stores them into the RAM 27c. Then, the CPU 27a acquires a value
(DIV/PEAK) obtained by dividing the difference integration value of
the fluorescence signal waveform (DIV) by the peak value of the
fluorescence signal waveform (PEAK). The CPU 27a also reads, from
among the lateral-scattered light data of the analysis target
particles, the signal waveform pulse width of the lateral-scattered
light (SSCW) from the hard disk 27d and stores them into the RAM
27c (Step S503). As shown in FIG. 8B, the signal waveform pulse
width of the lateral-scattered light (SSCW) shows the signal
waveform width of the lateral-scattered light having a higher
intensity than the base line (Base Line 3). The CPU 27a prepares a
(DIV/PEAK)-SSCW scattergram shown in FIG. 6 in which the vertical
axis shows the value (DIV/PEAK) obtained by dividing the difference
integration value of the fluorescence signal waveform by the peak
value and the horizontal axis shows the signal waveform pulse width
of the lateral-scattered light (SSCW) (Step S504).
[0080] Then, the CPU 27a compares the value (DIV/PEAK) obtained by
dividing the difference integration value of the fluorescence
signal waveform (DIV) by the peak value of the fluorescence signal
waveform (PEAK) with the threshold value of 2.6 to thereby
determine whether the analysis target cell is an aggregating cell
or a non-aggregating cell. When the following formula (1) is
established, the cell is non-aggregating cell. When the formula (1)
is not established, the cell is an aggregating cell.
DIV/PEAK.ltoreq.2.6 (1)
[0081] Then, the CPU 27a counts the respective number of
non-aggregating cells and aggregating cells (Step S505).
[0082] Next, the CPU 27a reads, from among the lateral fluorescence
data of the analysis object cell, the fluorescence amount (SFLI)
that is a value reflecting the DNA amount of the nucleus of the
measuring object cell and that shows the area of the pulse of the
fluorescence signal from the hard disk 27d and stores them into the
RAM 27c (Step S506). Then, the CPU 27a prepares a histogram shown
in FIG. 15 in which the horizontal axis shows the area of the pulse
of the fluorescence signal (fluorescence amount) (SFLI) (Step
S507). In this histogram, a peak appears at a position
corresponding to a normal cell.
[0083] Next, the CPU 27a determines whether or not the fluorescence
amount (SFLI) of the analysis object cell is 2.5 times or more
higher than the fluorescence amount (SFLIP) at the position in the
histogram of FIG. 15 at which the peak appears, i.e., whether the
following formula (2) is established or not.
SFLI.gtoreq.SFLIP.times.2.5 (2)
[0084] Then, when the formula (2) is established, the CPU 27a
classifies the cell as an abnormal-DNA-amount cell in which the DNA
amount of the nucleus is abnormal. When the formula (2) is not
established, the CPU 27a classifies the cell as a normal cell.
Then, the CPU 27a counts those cells classified as
abnormal-DNA-amount cells (Step S508). Next, the CPU 27a deducts
the number of aggregating cells acquired in Step S505 from the
number of abnormal-DNA-amount cells acquired in Step S508 to
thereby acquire the number of abnormal cell (Step S509).
[0085] Next, the CPU 27a calculates a ratio between the number of
non-aggregating cells acquired in Step S505 and the number of
abnormal cells acquired in Step S509 to thereby acquire an abnormal
cell ratio (Step S510). This abnormal cell ratio is a value
functioning as an indicator for determining whether or not a sample
analyzed by the cell analysis apparatus 10 includes therein a
predetermined number or more of cancer and atypical cells. When the
abnormal cell ratio is 1% or more for example, this means that the
sample includes therein a predetermined number or more of cancer
and atypical cells. Thus, the subject can know that he or she has a
cancer with a high probability.
[0086] Then, the CPU 27a displays, on the display section 28 of the
system control section 13 (see FIG. 1), the FSCW-FSCP scattergram
prepared in Step S502, the (DIV/PEAK)-SSCW scattergram prepared in
Step S504, and the histogram prepared in Step S507 as well as the
abnormal cell ratio acquired in Step S510 via the image output
interface 27g (FIG. 3) (Step S511). In the manner as described
above, the cell analysis processing is executed by the CPU 27a.
[0087] The disclosed embodiment should be considered as
illustrative in all points and should not be considered as limited.
The scope of the present invention is defined not by the above
description of the embodiment but by the claims, including the
equivalents of the claims and all modifications within the
scope.
[0088] For example, although the present embodiment has determined
whether or not a sample collected from the subject includes therein
a predetermined number or more of cancer and atypical cells of the
endocervix, the cell analysis apparatus of the present invention is
not limited to this. The present invention also can be used to
determine whether or not a sample collected from the subject
includes a predetermined number or more of cancer and atypical
cells of buccal cells, other epithelial cells of bladder or throat
for example, and an organ.
[0089] Although the present embodiment has displayed the abnormal
cell ratio on the display section, the cell analysis apparatus of
the present invention is not limited to this. The display section
also can display not only the abnormal cell ratio but also a
comment showing whether the subject has a cancer or not. This
allows the subject to more easily know whether he or she has a
cancer or not with a high probability.
[0090] Although the present embodiment has acquired the number of
aggregating cells to subsequently acquire the number of
abnormal-DNA-amount cells and deducted the number of aggregating
cells from the number of abnormal-DNA-amount cells to thereby
acquire the number of abnormal cells (cancer and atypical cells),
the embodiment of the present invention is not limited to this.
FIG. 16 is a flowchart illustrating the second cell analysis
processing by the CPU 27a of the system control section 13. The
following section will describe the second cell analysis processing
with reference to FIG. 16.
[0091] In the second cell analysis processing, the CPU 27a in Steps
S5001 to S5004 executes the same processes as those of Steps S501
to S504 of the cell analysis processing shown in FIG. 12.
[0092] Next, the CPU 27a determines whether the formula (1) is
established or not with regard to the cell as an analysis target in
Step S5003. When the formula (1) is established, then the CPU 27a
counts the cell as a non-aggregating cell (Step S5005).
[0093] Next, the CPU 27a reads the fluorescence amount (SFLI) of
the non-aggregating cell for which the formula (1) is established
from the hard disk 27d and stores them into the RAM 27c (Step
S5006). Then, the CPU 27a prepares a histogram in which the
horizontal axis shows the fluorescence amount (SFLI) (Step
S5007).
[0094] Next, the CPU 27a classifies, as an abnormal cell (cancer
and atypical cell), a cell showing a 2.5 times or more fluorescence
amount than the fluorescence amount (SFLIP) at a position at which
the peak appears in the histogram prepared in Step S5007 and counts
the cell (Step S5008).
[0095] Next, the CPU 27a in Step S5009 executes the same processing
as Step S510 of the cell analysis processing shown in FIG. 12 to
acquire an abnormal cell ratio. Then, the CPU 27a displays,
together with the FSCW-FSCP scattergram prepared in Step S5002, the
(DIV/PEAK)-SSCW scattergram prepared in Step S5004, and the
histogram prepared in Step S5007, the abnormal cell ratio acquired
in Step S5009 on the display section 28 of the system control
section 13 (see FIG. 1) (Step S5010) via the image output interface
27g (FIG. 3). In the manner as described above, the second cell
analysis processing is executed by the CPU 27a.
[0096] FIG. 17 is a flowchart illustrating the third cell analysis
processing by the CPU 27a of the system control section 13. The
following section will describe the third cell analysis processing
with reference to FIG. 17.
[0097] In the third cell analysis processing, the CPU 27a in Steps
S50001 and S50002 executes the same processes as Steps S501 and
S502 of the cell analysis processing shown in FIG. 12.
[0098] Next, the CPU 27a reads, from among the lateral fluorescence
data of the cell as an analysis target in Step S50002, the
difference integration value of the fluorescence signal waveform
(DIV), the peak value of the fluorescence signal waveform (PEAK),
and the fluorescence amount (SFLI) as the area of the pulse of the
fluorescence signal from the hard disk 27d and stores them into the
RAM 27c. Then, the CPU 27a acquires the value (DIV/PEAK) obtained
by dividing the difference integration value of the fluorescence
signal waveform (DIV) by the peak value of the fluorescence signal
waveform (PEAK). The CPU 27a also reads, from among the
lateral-scattered light data of the analysis object cell, the
signal waveform pulse width of the lateral-scattered light (SSCW)
from the hard disk 27d and stores them into the RAM 27c (Step
S50003). Then, the CPU 27a prepares a (DIV/PEAK)-SSCW scattergram
in which the vertical axis shows the value (DIV/PEAK) obtained by
dividing the difference integration value of the fluorescence
signal waveform by the peak value and the horizontal axis shows the
signal waveform pulse width of the lateral-scattered light (SSCW)
and a histogram in which the horizontal axis shows the area of the
pulse of the fluorescence signal (fluorescence amount) (SFLI) (Step
S50004).
[0099] Next, the CPU 27a determines whether the formula (1) and the
formula (2) are both established or not. When the formula (1) and
the formula (2) are both established, the CPU 27a classifies the
cell as an abnormal cell (cancer and atypical cell) and counts the
cell (Step S50005). In the processing of this step, the CPU 27a
counts the cell for which the formula (1) is established as a
non-aggregating cell.
[0100] Next, the CPU 27a in Step S50006 executes the same
processing as Step S510 of the cell analysis processing shown in
FIG. 12 and acquires an abnormal cell ratio. Next, the CPU 27a
displays, together with the FSCW-FSCP scattergram prepared in Step
S50002 as well as the (DIV/PEAK)-SSCW scattergram and the histogram
prepared in Step S50004, the abnormal cell ratio acquired in Step
S50006 on the display section 28 of the system control section 13
(see FIG. 1) (Step S50007) via the image output interface 27g (FIG.
3). In the manner as described above, the third cell analysis
processing is executed by the CPU 27a.
[0101] In the cell analysis apparatus 10, pigments for staining the
nucleus of a measuring object cell is used to prepare a measurement
sample and the fluorescence from the nucleus is detected by the
detection section. As described above, the signal waveform of the
forward-scattered light from the cell may have an unclear peak or
trough part depending on the cell aggregating status or the cell
flowing direction for example. However, the fluorescence signal
waveform has clear peak and trough parts. Thus, the fluorescence
from the nucleus can be used to accurately determine whether the
cell is an aggregating cell or a non-aggregating cell.
* * * * *