Measurement method, measurement device, and measurement program

Abstract

To provide a measurement method, a measurement device, and a measurement program for acquiring information on lipid particles contained in a measurement sample prepared using no fluorescent dye.SOLUTION: A measurement method for measuring the number of particles in a measurement sample prepared using no fluorescent dye includes the step of obtaining information on lipid particles included in the measurement sample based on a plurality of characteristics values related to light scattering in each particle acquired by a flow cytometer from each particle included in the measurement sample.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] This specification discloses a measurement method, a measurement device, and a measurement program. [Background technology]

[0002] Patent Document 1 describes that when blood cells are counted by a flow cytometer in an automated blood cell counter, blood cells that produce differences in fluorescence intensity are stained with a fluorescent dye, and bone marrow nucleated cells, erythroid cells, and leukocyte cells are classified and counted using the difference in intensity between scattered light and fluorescence. Patent Document 1 also describes that even if lipid particles are contained in a measurement sample, the lipid particles are not stained with the fluorescent dye, and therefore the difference in fluorescence intensity can be utilized to distinguish bone marrow nucleated cells, erythroid cells, and leukocyte cells from the lipid particles. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2002-223791 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, in a measurement mode that does not use a fluorescent dye, if lipid particles are contained in the measurement sample, the counting results of nucleated cells may be affected by the lipid particles. The present invention aims to provide a measurement method, a measurement device, and a measurement program that can provide accurate measurement results of the number of particles contained in a measurement sample, even if the measurement sample was prepared without using a fluorescent dye and contains lipid particles. [Means for solving the problem]

[0005] An embodiment of the present invention relates to a method for measuring the number of particles in a measurement sample prepared without using a fluorescent dye, the method comprising: acquiring information about lipid particles contained in the measurement sample based on a plurality of characteristic values ​​related to light scattering in each particle acquired from each particle contained in the measurement sample by a flow cytometer, as shown in FIG.

[0006] One embodiment of the present invention relates to a measurement device (200) that measures the number of particles in a measurement sample prepared without using a fluorescent dye. As shown in Fig. 7, the measurement device (200) includes a flow cytometer (230) and a processing unit (201). The processing unit (201) acquires information about lipid particles contained in the measurement sample based on a plurality of characteristic values ​​related to light scattering in each particle acquired by the flow cytometer (230) from each particle contained in the measurement sample.

[0007] An embodiment of the present invention relates to a measurement program for measuring the number of particles in a measurement sample prepared without using a fluorescent dye. As shown in Fig. 2, when the measurement program is executed by a computer, the measurement program executes a step of acquiring information about lipid particles contained in the measurement sample based on a plurality of characteristic values ​​related to light scattering in each particle acquired by a flow cytometer from each particle contained in the measurement sample.

[0008] According to these embodiments, information about lipid particles contained in a measurement sample can be obtained from a plurality of measurements of scattered light from each particle obtained by a flow cytometer. Effect of the Invention

[0009] According to the present invention, by obtaining information about lipid particles contained in a measurement sample based on characteristic values ​​related to light scattering, accurate particle count measurement results can be provided even when a measurement sample containing lipid particles is measured using a measurement mode that does not use a fluorescent dye. [Brief description of the drawings]

[0010] [Figure 1] Examples of scattergrams are shown. (A) shows a scattergram of the pulse peak of the side scattered light signal (SSC) and the pulse peak of the forward scattered light signal (FSC). (B) shows a scattergram shown by the pulse width of the forward scattered light signal (FSCW) and the pulse peak of the forward scattered light signal (FSC). (C) shows a scattergram in which lipid particle dots are identified. [Diagram 2] An example of a method for acquiring information about lipid particles is shown. (A) shows a scattergram in which the x-axis direction is the pulse width (FSCW) of the forward scattered light signal and the y-axis direction is the pulse peak (FSC) of the forward scattered light signal. (B) shows a two-dimensional dot plot after conversion. (C) shows a histogram in which (B) is projected in the direction of the first principal component. [Diagram 3] (A) is an example of a histogram obtained from a measurement sample containing lipid particles, and (B) is an example of a histogram obtained from a measurement sample not containing lipid particles. [Figure 4] An example of displaying extracted lipid particle dot groups with different colors (contrast) is shown. [Diagram 5] (A) A scattergram of the pulse peak of the side scattered light signal (SSC) minus the pulse peak of the forward scattered light signal (FSC) in a specimen with a large number of nucleated cells. (B) A scattergram of the pulse width of the forward scattered light signal (FSCW) minus the pulse peak of the forward scattered light signal (FSC) in a specimen with a large number of nucleated cells. (C) A histogram of the scattergram in (B) rotated and projected. [Figure 6] 1 shows the external appearance of a measurement system 100. [Figure 7] 1 shows a hardware configuration of a measurement system 100. [Figure 8] 2 shows the configuration of the FCM detection unit 230. [Figure 9] 4 shows the process flow of the measurement program. [Figure 10] 4 shows the flow of analysis processing of the measurement program. [Figure 11] 1 shows a flow of a process for setting a lipid particle region and extracting lipid particle dots. [Figure 12] (A) shows the maximum maximum value, maximum value, and fractional position of each sample. (B) shows the scattergrams of the pulse peak of the side scattered light signal (SSC) - the pulse peak of the forward scattered light signal (FSC) before and after the treatment for four samples containing lipid particles. [Figure 13] (A) shows the frequency of lipid particle-positive specimens in each data group. (B) shows the side scattered light signal pulse peak (SSC) - forward scattered light signal pulse peak (FSC) scattergrams and the forward scattered light signal pulse width - forward scattered light signal pulse peak scattergrams for the specimen (#6) with the lowest lipid particle content and the specimen (#7) with the highest lipid particle content among the lipid particle-positive specimens. [Figure 14] For peripheral blood samples, the white blood cell count (WBC-D) measured in DIFF mode, the white blood cell count (before WBC-C correction) measured in normal CBC mode, and the white blood cell count after correction using the measurement method of this embodiment (after WBC-C correction) are shown. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] 1.Measurement method (1) Overview of measurement method One embodiment of the present invention relates to a measurement method for measuring the number of particles in a measurement sample. The measurement of the number of particles in this embodiment is performed using a measurement system 100, which is a fully automatic blood cell counter equipped with a flow cytometer (FCM) detection unit 230 shown in FIG. 8 described later. In this embodiment, the measurement of the number of particles is performed in a CBC measurement mode in the fully automatic blood cell counter, and the particles to be counted in this case are white blood cells. The measurement system 100 shown in FIG. 7 described later can count blood cells contained in a specimen by one or more measurement modes selected by a user from a plurality of measurement modes including a white blood cell differentiation (DIFF) measurement mode in addition to the CBC measurement mode. The measurement system 100 prepares a measurement sample using different reagents depending on the measurement mode by a sample preparation unit 220 included in the measurement device 200. The measurement sample prepared in the DIFF measurement mode contains a fluorescent dye for staining particles, specifically a polymethine dye, but the measurement sample for white blood cell measurement prepared in the CBC measurement mode does not contain a fluorescent dye. In this embodiment, an example is described in which the measurement system 100 prepares a measurement sample for white blood cell measurement that does not contain fluorescent dyes using the sample preparation unit 220 in CBC measurement mode, and separates the white blood cells and lipid particles contained in the measurement sample without using fluorescence parameters.

[0012] In this measurement method, a laser beam is irradiated onto particles in a measurement sample flowing through a flow cell 230j using an FCM detection unit 230 shown in FIG. 8, which will be described later, to detect light scattering caused by the particles and count the number of particles in the measurement sample. There are a number of parameters related to light scattering. The parameters include parameters defined by the scattering direction, such as forward scattered light and side scattered light. Forward scattered light refers to light scattered forward with respect to the traveling direction of the irradiated light when the light is irradiated onto a particle. Side scattered light refers to light scattered laterally with respect to the traveling direction of the irradiated light when the light is irradiated onto a particle. Another parameter related to light scattering is axial light loss. Axial light loss is a parameter that quantifies the decrease in the amount of light received by the light receiving unit due to light scattering when a particle crosses the laser. For each light scattering parameter, a waveform representing the change over time of the signal is obtained, and the shape of the pulse corresponding to each particle is analyzed to obtain values ​​such as the pulse peak (also called peak height) and pulse width (also called distribution width) as characteristic values. The pulse peak of the forward scattered light signal is a characteristic value that mainly represents the size of the particle. The pulse peak of the side scattered light signal is a characteristic value that represents the complexity of the particle's internal structure. The pulse width of the forward scattered light signal is a characteristic value that indicates the time that the particle passes through the area of ​​the flow cell where light is irradiated, and reflects the length of the particle.

[0013] The light scattering characteristic value obtained for each particle is shown as, for example, a scattergram (two-dimensional dot plot). FIG. 1(A) shows a scattergram of the pulse peak (SSC) of the side scattered light signal and the pulse peak (FSC) of the forward scattered light signal of a particle group measured in the CBC measurement mode by providing a white blood cell measurement sample prepared in the CBC measurement mode to the FCM detection unit 230. That is, each dot shows the coordinates of each particle when the x-axis direction is the pulse peak (SSC) of the side scattered light signal and the y-axis direction is the pulse peak (FSC) of the forward scattered light signal. The dots included in the area surrounded by the dotted line shown in FIG. 1(A) are shown in a light color and are counted as the "white blood cell count" in the CBC measurement mode. The area surrounded by the dotted line may be referred to as the "counting area" hereinafter. FIG. 1(B) shows a scattergram shown by the pulse width (FSCW) of the forward scattered light signal and the pulse peak (FSC) of the forward scattered light signal. That is, each dot indicates the coordinates of each particle when the X-axis direction is the pulse peak of the forward scattered light signal (FSCW) and the Y-axis direction is the pulse peak of the forward scattered light signal (FSC).

[0014] All dots in the area surrounded by the dashed line X in FIG. 1(A) are shown in a light color. The inventors discovered that, as shown in FIG. 1(C), an area including dots (called lipid particle dots) shown in a dark color that should be classified as lipid particles overlaps with the white blood cell count area. In FIG. 1(A), the lipid particle dots overlap with the white blood cell count area and cannot be distinguished. For this reason, there is a risk that the lipid particle dots will also be counted as white blood cells. Also, in FIG. 1(B), the lipid particle dots within the dashed line X overlap with the distribution area of ​​white blood cell dots shown by the dotted line Y.

[0015] In order to detect lipid particle dots that overlap the distribution area of ​​white blood cell dots, this measurement method first obtains multiple characteristic values ​​related to light scattering described above from each particle contained in the measurement sample, and then obtains information about the lipid particles contained in the measurement sample based on the obtained multiple characteristic values ​​related to light scattering.

[0016] An example of a method for acquiring information about lipid particles will be described with reference to Fig. 2. For convenience, the method for acquiring information about lipid particles will be described using the measured values ​​of the pulse width of the forward scattered light signal and the measured values ​​of the pulse peak of the forward scattered light signal.

[0017] Figure 2(A) is a scattergram in which the x-axis direction is the pulse width of the forward scattered light signal (FSCW) and the y-axis direction is the pulse peak of the forward scattered light signal (FSC). The coordinates of each dot shown in Figure 2(A) are expressed as (x, y) = (measured value of the pulse width of the forward scattered light signal, measured value of the pulse peak of the forward scattered light signal). In the first step, the two-dimensional coordinates (x, y) of each dot are transformed by a rotation matrix to obtain two-dimensional coordinates (x', y') after transformation.

[0018] The conversion formula is:

number

[0019] The rotation angle θ is set so that the variance of the transformed coordinate group is maximized. More specifically, θ is determined by dimensional transformation, preferably by principal component analysis. When dimensional transformation is performed by principal component analysis, the x'-axis direction represents the first principal component (PCA1), and the y'-axis direction represents the second principal component (PCA2).

[0020] In addition, while the scale of each axis of the 2D dot plot before conversion is represented by channels, for example, from 0 to 255, the scale of the x' axis after conversion limits the display range of channels, for example, from 0 to 255 to channels from 0 to 50.

[0021] The rotation angle θ may be determined for each measurement sample, or may be set in advance and the same rotation angle may be applied to all measurement samples. When the rotation angle θ is set in advance, it may be set to about 10.2° to 10.5°. When the rotation angle θ is a positive value, the rotation is intended to be counterclockwise, and when the rotation angle θ is a negative value, the rotation is intended to be clockwise.

[0022] The inventors discovered that by performing this type of transformation, the lipid particle dots that overlap with the white blood cell count region in Figure 2(A) can be separated into the white blood cell count region located on the high side of the x' axis relative to boundary line A and the lipid particle dot region located on the low side of the x' axis (towards the origin) relative to boundary line A by drawing boundary line A on the x' axis on a two-dimensional dot plot of the transformed two-dimensional coordinates (x', y') shown in Figure 2(B).

[0023] In the second step, the transformed two-dimensional dot plot is projected in the direction of the first principal component. Projecting in the direction of the first principal component is intended to set the y' of all dots to "0" in the transformed two-dimensional coordinates (x', y'). In this way, the histogram shown in FIG. 2(C) is obtained. By drawing the boundary line A on the histogram in FIG. 2(C), the white blood cell count region located on the high side of the x' axis and the lipid particle dot region located on the low side of the x' axis with respect to the boundary line A can be separated, and they can be distinguished more clearly than in the case of the two-dimensional dot plot shown in FIG. 2(B). Note that the boundary line A shown in FIG. 2(B) and the boundary line A shown in FIG. 2(C) are shown by a common dashed line as the boundary between the white blood cell count region and the lipid particle dot region.

[0024] In the third step, the histogram obtained in the second step is used to determine whether or not lipid particle groups are present. An example of the third step will be explained with reference to Fig. 3. Fig. 3(A) is an example of a histogram obtained from a measurement sample containing lipid particles, and Fig. 3(B) is an example of a histogram obtained from a measurement sample not containing lipid particles.

[0025] For example, on the right side of the histograms in Figures 3(A) and 3(B), peak (a) is analyzed for the histograms obtained in the second step. The ▼ shown in Figures 3(A) and 3(B) indicates the peak position obtained by peak analysis.

[0026] Next, in (b) shown at the left end (channel 0) of the histograms in Figures 3(A) and 3(B), the highest peak position is identified among the peak positions of the detected peaks. The highest peak position is the peak derived from the original target cell group. Next, a search is performed to see whether there is another peak Q between the left end (channel 0) of the histogram and the highest peak position. In Figure 3(A), since there is another peak Q between channel 0 and the channel with the highest peak position, it can be determined that there is a lipid particle group. Also, in Figure 3(B), since there is no another peak Q between channel 0 and the channel with the highest peak position, it can be determined that there is no lipid particle group.

[0027] Furthermore, when it is determined that there is a lipid particle group in (b) shown at the left end (channel 0) of the histograms in Figures 3(A) and (B), a bottom (minimum value) for separating the cell group and the lipid particle group is searched for in (c) shown between the left end (channel 0) and the right end of the histogram in Figure 3(A). The search for the bottom (minimum value) is preferably performed between the channel at the highest peak position and the channel at the position of another peak Q detected in the search in (b) shown at the left end (channel 0) of the histogram in Figure 3(A). By setting the bottom (minimum value) as the separation position, it is possible to extract the lipid particle dot group from the two-dimensional dot plot before conversion.

[0028] In the fourth step, information on lipid particles is generated for the lipid particle dot group extracted in the third step. FIG. 4 shows an example in which the extracted lipid particle dot group is displayed with different shading in a two-dimensional dot plot of the pulse peak (SSC) of the side scattered light signal and the pulse peak (FSC) of the forward scattered light signal. The lipid particle dot group overlapping the white blood cell count region is shown in a dark color and can be identified. By counting these identified lipid particle dots, information on lipid particles is generated. The information on lipid particles includes qualitative, semi-quantitative, or quantitative information on the presence or absence or content of lipid particles in the measured particle group. Preferably, the information on lipid particles is the presence ratio of lipid particles in the measured particle group, or the number of lipid particles.

[0029] In the fifth step, based on the information about the lipid particles, information based on the determination result as to whether or not lipid particles are present, or a corrected value of the white blood cell count obtained by excluding the count of lipid particle dot groups from the white blood cell count, is generated.

[0030] The information based on the determination result of whether or not lipid particles are present is information on the reliability of the measured value of the white blood cell count. The information on the reliability of the measured value of the white blood cell count is a label indicating whether or not the measured value of the white blood cell count includes a count of lipid particles. The information on the reliability of the measured value of the white blood cell count may be a label indicating the amount of lipid particles contained in the counted white blood cells semi-quantitatively or quantitatively. Semi-quantitative can be expressed, for example, as the lipid particle content being "high" or "low". Alternatively, the information on the reliability of the measured value of the white blood cell count may be the reliability of the measured value of the white blood cell count according to the information on the lipid particles. For example, when lipid particles are not detected or are low, a label indicating "high reliability" can be displayed. When lipid particles are medium to high, a label indicating "low reliability" can be displayed.

[0031] The information on the reliability of the measured value of the white blood cell count is output when the ratio of the lipid particles is a preset value, for example, 3% or more of the total particles detected, or when the number of the lipid particles is a predetermined ratio, for example, 3% or more, to the white blood cell count. Preferably, the information on the reliability of the measured value of the white blood cell count is output when the number of lipid particles is 50 or more and the ratio of the lipid particles is 3% or more of the total particle number, or when the number of the lipid particles is 3% or more of the white blood cell count.

[0032] (2) Variations When detecting lipid particle groups as shown in the third step above, as shown in Figures 5(A) and 5(B), if the number of nucleated cells contained in the measurement sample is large, especially if the number of lymphocytes is large, it may be difficult to distinguish between the peak of the lymphocyte count region and the lipid particle peak (see Figure 5(C)). In this case, it is preferable to limit the search range to a preset range when searching for the lipid particle peak and generate information about the lipid particles. Since lipid particle peaks often appear on the lower side of the PCA1 axis than the region where lymphocyte peaks appear, the search range for the lipid particle peak may be limited to the lower side of the lymphocyte maximum value region.

[0033] Furthermore, in a two-dimensional dot plot of the pulse width (FSCW) of the forward scattered light signal and the pulse peak (FSC) of the forward scattered light signal, red blood cells infected with malaria parasites may appear in the area where lipid particle dots appear. Red blood cells infected with malaria parasites can be distinguished from other particles in a two-dimensional dot plot of the pulse peak (FSC) of the side scattered light signal and the pulse peak (SSC) of the forward scattered light signal, and can be counted, so information about lipid particles can be obtained by subtracting the count of red blood cells infected with malaria parasites from the count of lipid particles.

[0034] 2. Measurement System 2-1. Measurement system configuration One embodiment of the present invention relates to a measurement system 100 (hereinafter simply referred to as "measurement system 100") that measures the number of cells in a measurement sample containing blood cells. FIG. 6 shows the appearance of the measurement system 100 of this embodiment. The measurement system 100 includes a measurement device 200 and a touch panel display 300. FIG. 7 shows the hardware configuration of the measurement system 100. The measurement system 100 is connected to the display 300, which includes an input unit 311 and an output unit 312.

[0035] (2) Hardware Configuration of Measuring Device 200 In the measuring device 200, a specimen aspirating section 210, a sample preparing section 220, an FCM detecting section 230, a processing section 201, a memory section 202, an input interface (I / F) 206, and an output interface (I / F) 207 are communicatively connected to each other via a bus 209. The memory section 202 stores the measurement values, the rotation angle θ of the rotation matrix, an algorithm for calculating the rotation angle θ, and a measurement program 202b including a peak analysis program.

[0036] The specimen aspirating unit 210 aspirates the specimen from a specimen container containing the specimen through a nozzle, and dispenses the specimen into a reaction tank provided in the sample preparing unit 220. The sample preparing unit 220 prepares a measurement specimen by supplying a reagent to the reaction tank and mixing the specimen with the reagent. The reagent used by the sample preparing unit 220 differs depending on the measurement mode. The sample preparing unit 220 mixes a diluent and a hemolytic agent as reagents with the specimen to prepare a measurement specimen for counting white blood cells in the CBC measurement mode. The sample preparing unit 220 mixes a diluent, a hemolytic agent, and a fluorescent dye as reagents with the specimen to prepare a measurement specimen for classifying and counting white blood cells in the DIFF measurement mode. The measurement specimen prepared in the CBC measurement mode does not contain a fluorescent dye.

[0037] The processing unit 201 is a CPU of the measurement device 200. The processing unit 201 may cooperate with a GPU. The processing unit 201 cooperates with an operation system (OS) 202a stored in the storage unit 202 to execute a measurement program 202b, and processes acquired data.

[0038] The storage unit 202 is composed of a hard disk. A measurement program 202b executed by the processing unit 201 and data used therefor are recorded in the storage unit 202. The ROM stores a boot program executed by the processing unit 201 when the measuring device 200 is started up, and programs and settings related to the operation of the hardware of the measuring device 200.

[0039] The input I / F 206 is composed of a serial interface, a parallel interface, an analog interface, etc. The input I / F 206 accepts character input, clicks, voice input, etc. from the input unit 311. The accepted input contents are stored in the storage unit 202.

[0040] The input unit 311 is composed of a touch panel, a keyboard, a mouse, a pen tablet, a microphone, etc., and is used to input characters or voice to the measurement device 200. The input unit 311 may be connected to the measurement device 200 from outside, or may be integrated with the measurement device 200.

[0041] The output I / F 207 is configured, for example, from an interface similar to that of the input I / F 206. The output I / F 207 outputs information generated by the processing unit 201 to the output unit 312. The output I / F 207 outputs information generated by the processing unit 201 and stored in the storage unit 202 to the output unit 312.

[0042] The output unit 312 is composed of, for example, a display, a printer, etc., and displays the detection results sent from the FCM detection unit 230, various operation windows in the measurement device 200, analysis results, etc.

[0043] An operation system that provides a graphical user interface environment, such as Windows (registered trademark) manufactured and sold by Microsoft Corporation, is installed in the storage unit 202. The application program according to the present embodiment runs on the operating system. In other words, the measurement device 200 may be a personal computer or the like.

[0044] The FCM detection unit 230 of the measurement device 200 constituting the measurement system 100 may be located at a different location, and these may be connected via a network.

[0045] (3) FCM detection section 8 shows a hardware configuration of the FCM detection unit 230. The FCM detection unit 230 may be referred to as a flow cytometer 230 in this specification. As shown in FIG. 8, the FCM detection section 230 includes a flow cell 230j, a detection section 230a, an irradiation optical system 230e, a light receiving optical system 230k, and a signal processing circuit 230p.

[0046] Flow cell 230j allows the measurement sample prepared by sample preparation section 220 to flow. Laser light emitted from laser diode 230i is irradiated onto the measurement sample flowing through flow cell 230j. When the measurement sample is irradiated with the laser light, light is generated from particles in the measurement sample. Photodetectors 230b to 230d of detection section 230a receive forward scattered light (FSC), side scattered light (SSC), and side fluorescent light (SFL) generated from the particles in the measurement sample, respectively, to acquire optical information from the particles in the measurement sample irradiated with the laser light.

[0047] The irradiation optical system 230e includes a collimator lens 230f and a condenser lens 230g. The collimator lens 230f converts the laser light emitted from the laser diode 230i into parallel light. The condenser lens 230g condenses the laser light converted into parallel light and irradiates the flow cell 230j with the parallel light. In this manner, the irradiation optical system 230e irradiates the measurement sample flowing through the flow cell 230j with the laser light emitted from the laser diode 230i. When the measurement sample is irradiated with the laser light, forward scattered light (FSC) and side scattered light (SSC) are generated from particles in the measurement sample.

[0048] The light receiving optical system 230k includes a beam stopper 230l, a condenser lens 230m, a dichroic mirror 230n, and a spectral filter 230o. The beam stopper 230l blocks the laser light that is transmitted through the flow cell 230j without being irradiated to a particle, among the laser light irradiated to the flow cell 230j. The photodetector 230b is a photodiode. The photodetector 230b receives forward scattered light (FSC) and outputs an electrical signal according to the intensity of the forward scattered light (FSC).

[0049] The condenser lens 230m condenses the side scattered light (SSC). The dichroic mirror 230n reflects the side scattered light (SSC). The photodetector 230c is a photodiode. The photodetector 230c receives the side scattered light (SSC) and outputs an electrical signal according to the intensity of the side scattered light (SSC). The photodetector 230d is an avalanche photodiode. In this manner, the light receiving optical system 230k guides the light generated from the measurement sample to the photodetectors 230b to 230d of the detection unit 230a. Here, the photodetectors 230b to 230d may be photomultiplier tubes.

[0050] The signal processing circuit 230p performs a predetermined signal processing on the electric signals output from the photodetectors 230b to 230d to obtain characteristic values ​​corresponding to the forward scattered light (FSC) signal and the side scattered light (SSC) signal, that is, the pulse peak and pulse width. Specifically, the signal processing circuit 230p performs A / D conversion on the forward scattered light signal output over time from the photodetector 230b to generate a signal waveform of digital values ​​with the received light intensity on the first axis and the time lapse on the second axis, and cuts out pulse waveforms corresponding to individual particles from the generated digital signal waveform. The signal processing circuit 230p outputs the peak height of the cut-out pulse waveform as the pulse peak value of the forward scattered light (FSC) signal, and the width of the part of the pulse waveform that exceeds the threshold as the pulse width of the forward scattered light (FSC) signal. Similarly, the signal processing circuit 230p outputs the pulse peak value of the side scattered light (SSC) of each particle based on the side scattered light (SSC) signal output over time from the photodetector 230c.

[0051] 3. Measurement Program An embodiment of the present invention relates to a measurement program 202b for measuring the number of cells in a measurement sample containing blood cells. The process flow of the measurement program 202b will be described with reference to Figs.

[0052] In step S1 shown in Fig. 9, the processing unit 201 of the measuring device 200 shown in Fig. 7 controls the sample preparation unit 220 (see Fig. 7) to prepare a measurement sample by mixing a specimen with a reagent that does not contain a fluorescent dye. Next, in step S2 shown in Fig. 9, the processing unit 201 controls the FCM detection unit 230 (see Fig. 7) to irradiate the measurement sample flowing through the flow cell 230j (see Fig. 8) with laser light. Then, in step S3, the processing unit 201 performs an analysis process based on optical information acquired from particles in the measurement sample irradiated with the laser light.

[0053] The process of step S3 will be described in more detail with reference to FIG. In step S10, the processing unit 201 acquires measurement values ​​of multiple parameters related to scattered light for each particle from the FCM detection unit 230. This process is started when the operator inputs a request to start treatment from the input unit 311 and the processing unit 201 accepts this input.

[0054] In step S11, the processing unit 201 stores in the storage unit 202 the feature values ​​related to light scattering for each particle acquired in step S10.

[0055] In step S12, the processing unit 201 generates a scattergram based on the feature values ​​generated in step S11.

[0056] In step S13, the white blood cell count region and other regions are separated from the scattergram, and the number of particles present in the white blood cell count region is counted.

[0057] In step S14, the processing unit 201 sets a lipid region and extracts lipid particle dots.

[0058] The process of step S14 will be described in more detail with reference to FIG. In step S141, the processing unit 201 extracts a group of dots of particles included in a region to be analyzed from the scattergram.

[0059] In step S142, the processing unit 201 applies a rotation matrix to the extracted dot group to convert the coordinates on the scattergram, and further projects the coordinates of each dot in the axis direction corresponding to the first principal component. This process corresponds to the first and second steps described in 1 above.

[0060] In step S143, the processing unit 201 searches whether or not there are multiple peaks in the histogram obtained in step S142, and if there are multiple peaks, determines the fractionation position for extracting the lipid particle group. This process corresponds to the first stage of the third step described in 1 above.

[0061] In step S144, the processing unit 201 determines the lipid particle group based on the peak in the region to the left of the fractionation position determined in step S143. This process corresponds to the latter stage of the third step described in 1 above.

[0062] Returning to FIG. 10, the processing of the measurement program 202b will be further explained. In step S15, the processing unit 201 judges whether or not lipid particles are interfering with the white blood cell region. If lipid particle groups are detected within a predetermined range in step S14, it can be determined that lipid particles are interfering with the white blood cell region. The conditions for determining that lipid particle groups have been detected within a predetermined range are the same as the conditions for outputting information regarding the reliability of the measured white blood cell count in 1 above.

[0063] If the determination result is "NO" in step S15, the processing unit 201 proceeds to step S19, outputs the white blood cell count to the output unit 312, and ends the process.

[0064] If the determination result in step S15 is "YES", the processing unit 201 proceeds to step S16 and outputs auxiliary information, which is information based on the determination result as to whether or not lipid particles are present, to the output unit 312. This step corresponds to the fourth step described in 1 above.

[0065] Next, the processing unit 201 proceeds to step S17, where it counts the number of particles determined to be lipid particles in step S14, and generates information about lipid particles.

[0066] Furthermore, the processing unit 201 proceeds to step S18, where the processing unit 201 generates a corrected value of the white blood cell count by excluding the count of the lipid particle dot group from the white blood cell count. This step corresponds to the fifth step shown in 1 above. The processing unit 201 proceeds to step S19, and outputs the corrected value of the white blood cell count from the output unit 312.

[0067] 4. Storage media that record computer programs A computer program for executing the processes of steps S10 to S19 and steps S141 to S144 may be provided as a program product such as a storage medium. The computer program is stored in a storage medium such as a hard disk, a semiconductor memory device such as a flash memory, an optical disk, etc. The storage format of the program in the storage medium is not limited as long as the control unit can read the program.

[0068] FIG. 12 shows the results of applying the measurement method of this embodiment to peripheral blood specimens #1, #2, #3, #4, and #5. Specimen #5 did not contain lipid particles, and all the others contained lipid particles. FIG. 12(A) shows the maximum local maximum value (peak indicating white blood cells), local maximum value (peak indicating lipid particles), and fractionation position (minimum local minimum value) of each specimen. The maximum local maximum value was channel 14 in all five specimens. Furthermore, the local maximum value was channel 10 or 9 in four specimens containing lipid particles. The fractionation position was channel 11 in all four specimens containing lipid particles. FIG. 12(B) shows scattergrams of the pulse peak (SSC) of the side scattered light signal and the pulse peak (FSC) of the forward scattered light signal of four specimens containing lipid particles before and after the countermeasure. After the countermeasure, the lipid particle dots overlapping the white blood cell fraction were identified and displayed.

[0069] FIG. 13(A) shows the frequency of lipid particle-positive specimens in each data group. FIG. 13(B) shows a scattergram of the pulse peak (SSC) of the side scattered light signal - the pulse peak (FSC) of the forward scattered light signal, and a scattergram of the pulse width (FSCW) of the forward scattered light signal - the pulse peak (FSC) of the forward scattered light signal for the specimen (#6) with the lowest lipid particle content and the specimen (#7) with the highest lipid particle content among the lipid particle-positive specimens. The lipid particle content ratio of #6 was 1.4%, and the number of lipid particles was 53. The lipid particle content ratio of #7 was 14.3%, and the number of lipid particles was 2295. From this, it was considered that auxiliary information, which is information based on the determination result of whether or not lipid particles are present, can be output if the number of lipid particles is at least 50. In addition, since the simultaneous reproducibility of white blood cell counts is less than 3%, it was considered that the threshold value of the lipid content for outputting auxiliary information is 3%.

[0070] 14 shows the white blood cell counts (WBC-D) measured in the DIFF mode for fluorescent staining for peripheral blood specimens #1, #2, #3, and #4, the white blood cell counts (before WBC-C correction) measured in the normal CBC mode, and the white blood cell counts (after WBC-C correction) corrected by the measurement method of this embodiment. For specimens other than #1, the values ​​before WBC-C correction were significantly different from the reference WBC-D value, but the values ​​after WBC-C correction were close to the WBC-D value. The increase rate of the values ​​after WBC-C correction was 0.3% to 2.5% of the WBC-D value, which was considered to be within a fully acceptable range considering that the upper limit of the simultaneous reproducibility of WBC is 3%.

[0071] As described above, according to this embodiment, white blood cells and lipid particles can be separated without using a fluorescent dye. As a result, the number of white blood cells in a patient sample containing lipid particles can be accurately counted or a notification that the sample contains lipid particles can be added to the measurement results, regardless of the DIFF measurement mode using a fluorescent dye, and accurate test results can be provided for samples containing lipid particles while keeping testing costs down.

[0072] In this specification, the measurement method is not limited. For example, information on lipid particles contained in a measurement sample may be obtained using a scattergram shown by the pulse width (FSCW) of the forward scattered light signal and the pulse peak (FSC) of the forward scattered light signal shown in FIG. 1(B). In this case, information on lipid particles can be obtained by gating the area shown by the dotted line in FIG. 1(B) where the lipid particle dots in the dashed line are shown, and counting the particles that appear in the gate.

[0073] As another example, information on lipid particles contained in a measurement sample may be obtained from a two-dimensional dot plot of two-dimensional coordinates obtained by transforming the scattergram of the pulse width (FSCW) of the forward scattered light signal and the pulse peak (FSC) of the forward scattered light signal shown in Fig. 2(A) using a rotation matrix. In this case, by drawing a boundary line A on Fig. 2(B), which is a two-dimensional dot plot of two-dimensional coordinates (x', y'), it is possible to separate the white blood cell count region located on the high value side of the x' axis relative to the boundary line A from the lipid particle dot region located on the low value side of the x' axis relative to the boundary line A.

[0074] In this specification, the present invention is not limited to an example in which blood cells contained in a sample are counted by one or more measurement modes selected by a user from a plurality of measurement modes including the CBC measurement mode and the DIFF measurement mode. For example, blood cells contained in a sample may be counted only by the CBC measurement mode.

[0075] In this specification, the rotation angle θ is not limited and may be, for example, about 8° to 12°, preferably about 9° to 11°, more preferably about 9.5° to 10.8°, and further preferably about 10.0° to 10.6°.

[0076] In this specification, the measurement sample is not limited. For example, it may include undiluted specimens of blood (peripheral blood, arterial blood, venous blood, etc.) and body fluids (bone marrow fluid, cerebrospinal fluid, synovial fluid, etc.), or dilutions of the specimens. It is preferable that blood is collected in the presence of an anticoagulant.

[0077] In the present specification, the particle is not limited. For example, the particle may include a cell and a non-cellular particle. The cell is intended to mean a cell derived from a subject from whom a measurement sample is taken. The cell may include red blood cells, white blood cells, platelets, immature red blood cells, immature white blood cells, immature lymphocytes, micromegakaryocytes, tumor cells (e.g., leukemia cells, malignant lymphoma cells, multiple myeloma, etc.), malaria-infected red blood cells, etc. The non-cellular particle may include lipid particles, bacteria, fungi (e.g., yeast), etc.

[0078] In this specification, the "plurality" of the plurality of characteristic values ​​related to light scattering is not limited. For example, the "plurality" is not limited as long as it is 2 or more.

[0079] In the present specification, an embodiment has been described by showing an example in which the processing unit 201 that executes the measurement program 202b is mounted on the measuring device 200. However, the measurement program 202b may be executed on a separate computer that does not include the flow cytometer 230. For example, via a network such as the cloud, the separate computer may acquire measured values ​​of multiple parameters related to scattered light for each particle from the flow cytometer 230, and the processing unit of the separate computer may execute the measurement program 202b. [Explanation of symbols]

[0080] 201 Processing section 202 Storage section 230j Flow Cell 311 Input section 312 Output section 230a Detector 230b~230d Detector 230e Irradiation optical system 230k receiving optical system 230p signal processing circuit 220 Sample Preparation Department 230 FCM detector (flow cytometer) 100 Measurement System 200 Measuring Equipment 300 Display

Claims

1. A method for measuring the number of particles in a measurement sample prepared without using a fluorescent dye, comprising the steps of: and acquiring information about lipid particles contained in the measurement sample based on a plurality of characteristic values ​​related to light scattering in each particle acquired from each particle contained in the measurement sample by a flow cytometer; a measurement method in which the plurality of feature values ​​relating to light scattering are values ​​indicating a width of a pulse waveform of a forward scattered light signal corresponding to each particle and a peak height of the pulse waveform of a forward scattered light signal in different coordinate axis directions.

2. The method according to claim 1 , further comprising the step of counting the number of nucleated cells in the measurement sample based on scattered light generated by irradiating light onto the individual particles.

3. The measurement method according to claim 1 or 2, further comprising: determining whether or not lipid particles have an effect on the particle number measurement based on the information about the lipid particles; and outputting information based on the determination result.

4. The measurement method according to claim 1 , wherein the information about the lipid particles is information about reliability of a measurement value of a white blood cell count.

5. The measurement method according to claim 1 , further comprising correcting a measurement value of the particle count based on the information about the lipid particles, and outputting the corrected value as a measurement value of the white blood cell count.

6. 2. The measurement method according to claim 1, wherein the information about the lipid particles is generated by extracting coordinates indicating the lipid particles from the transformed coordinates obtained by transforming, using a rotation matrix, coordinates indicated by the width of the pulse waveform of the forward scattered light signal and the peak height of the pulse waveform of the forward scattered light signal obtained from each particle.

7. The measurement method according to claim 6 , wherein the information about the lipid particles is generated by peak analysis of a histogram projected in an axial direction corresponding to a first principal component in coordinates transformed by the rotation matrix.

8. The measurement method according to claim 7 , further comprising correcting peak values ​​in the peak analysis of the histogram to generate information about the lipid particles.

9. The measurement method according to claim 7 or 8, further comprising limiting a peak search range in the peak analysis of the histogram to generate information about the lipid particles.

10. The measurement method according to claim 1 , wherein the information about the lipid particles is an abundance ratio of the lipid particles in a particle group, or a number of the lipid particles.

11. When the ratio of the lipid particles is equal to or greater than a predetermined value, or When the number of the lipid particles is equal to or greater than a predetermined value relative to the measured particle number, The method according to claim 4 , further comprising outputting information regarding the reliability of the measured value of the white blood cell count.

12. The measurement method according to claim 1 , further comprising excluding coordinates of particles corresponding to malaria-infected cells from coordinates indicating the lipid particles, and obtaining information about the lipid particles.

13. A measuring device for measuring the number of cells in a measurement sample prepared without using a fluorescent dye, The measuring device includes a flow cytometer and a processing unit, The processing unit includes: acquiring information about lipid particles contained in the measurement sample based on a plurality of characteristic values ​​related to light scattering in each particle acquired from each particle contained in the measurement sample by the flow cytometer; the plurality of feature values ​​relating to light scattering are values ​​indicating a width of a pulse waveform of a forward scattered light signal corresponding to each particle and a peak height of a pulse waveform of a forward scattered light signal in different coordinate axis directions, Measuring equipment.

14. When run on a computer, The method includes performing a step of acquiring information about lipid particles contained in a measurement sample based on a plurality of characteristic values ​​related to light scattering in each particle acquired by a flow cytometer from individual particles contained in the measurement sample prepared without using a fluorescent dye, the plurality of feature values ​​relating to light scattering are values ​​indicating a width of a pulse waveform of a forward scattered light signal corresponding to each particle and a peak height of a pulse waveform of a forward scattered light signal in different axial directions, A measurement program for measuring the number of cells in the measurement sample.

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