WO2025138135A1 - Blood cell analyzer and blood cell analysis method - Google Patents

Abstract

A blood cell analyzer (100) and a blood cell analysis method (300). The blood cell analysis method (300) comprises: aspirating a blood sample to be tested; preparing a first assay sample, and obtaining first optical information; preparing a second assay sample, and obtaining second optical information; generating a first white blood cell classification scattergram and a second white blood cell classification scattergram; based on the first white blood cell classification scattergram and the second white blood cell classification scattergram, determining a first count result of neutrophils in the blood sample to be tested; determining an actual distribution region of neutrophils from the first white blood cell classification scattergram; based on a reference neutrophil distribution region of a reference white blood cell classification scattergram of a normal blood sample, determining a segmented granulocyte distribution region from the actual distribution region; determining a second count result of cells falling within the segmented granulocyte distribution region; based on the first count result and the second count result, determining a count result of band granulocytes in the blood sample to be tested.

Description

Blood cell analyzer and blood cell analyzing method Technical Field

The present application relates to the technical field of blood analysis, and in particular to a blood cell analyzer and a blood cell analysis method.

Background Art

Routine blood test is a basic clinical examination item. The test results generally include white blood cell count, red blood cell count, platelet count, hemoglobin concentration, reticulocyte count and other results. It also outputs scatter plots or histograms of white blood cell, red blood cell, platelet and reticulocyte tests to assist doctors in clinical diagnosis.

Existing blood cell analyzers perform optical measurement of white blood cells and optical measurement of reticulocytes (or optical measurement of platelets) based on fluorescent staining technology, wherein the count value and classification of white blood cells are obtained in the optical measurement of white blood cells, including the count value and classification of neutrophils (Neu), lymphocytes (Lym), monocytes (Mon), eosinophils (Eos) and basophils (Baso). In the optical measurement of reticulocytes, parameters such as red blood cell count value, optical platelet count value, and reticulocyte count value are obtained.

Neutrophils include segmented neutrophils and band-shaped neutrophils. Under normal circumstances, band-shaped neutrophils account for a small proportion of neutrophils, and segmented neutrophils are the main type. However, in abnormal conditions such as inflammation, the number of band-shaped neutrophils in the blood increases.

Therefore, determining whether there is an abnormal increase in band cells in a blood sample and determining the count of band cells in a blood sample can assist doctors in diagnosing abnormal conditions such as inflammation.

Summary of the invention

Based on this background, the present application aims to provide a blood cell analyzer and a blood cell analysis method, which can determine whether there is an abnormal increase in band-shaped nuclear granulocytes in a blood sample and/or determine the counting result of the band-shaped nuclear granulocytes in the blood sample.

According to a first aspect of an embodiment of the present application, there is provided a blood cell analyzer, comprising:

A sample suction device, used for sucking a blood sample to be tested;

a sample preparation device for mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and for mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes;

an optical detection device, comprising a flow cell, a light source, and a light detector, wherein the flow cell is used for allowing the first measurement sample and the second measurement sample to pass through the flow cell, respectively, the light source is used for irradiating the first measurement sample and the second measurement sample passing through the flow cell, respectively, with light, and the light detector is used for detecting first optical information and second optical information generated after the first measurement sample and the second measurement sample are irradiated with light when passing through the flow cell, respectively; and

A data processing device configured to:

generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information,

determining a first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram,

determining the actual distribution area of neutrophils from the first leukocyte classification scattergram,

determining the distribution area of segmented granulocytes from the actual distribution area based on a reference distribution area of neutrophils of a reference leukocyte classification scattergram of one or more normal blood samples, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light,

determining a second count result of cells falling within the segmented granulocyte distribution region, and

Based on the first counting result and the second counting result, it is determined whether to alarm for the abnormal increase of band cells in the blood sample to be tested, and/or the counting result of band cells in the blood sample to be tested is determined and outputted.

According to a second aspect of an embodiment of the present application, there is provided a blood cell analyzer, comprising:

A sample suction device, used for sucking a blood sample to be tested;

a sample preparation device for mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and for mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes;

an optical detection device, comprising a flow cell, a light source, and a light detector, wherein the flow cell is used for allowing the first measurement sample and the second measurement sample to pass through the flow cell, respectively, the light source is used for irradiating the first measurement sample and the second measurement sample passing through the flow cell, respectively, with light, and the light detector is used for detecting first optical information and second optical information generated after the first measurement sample and the second measurement sample are irradiated with light when passing through the flow cell, respectively; and

The data processing device is configured to: when it is determined that there is an abnormal increase in band-shaped nuclear granulocytes in the blood sample to be tested,

generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information,

determining a first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram,

determining the actual distribution area of neutrophils from the first leukocyte classification scattergram,

determining the distribution area of segmented granulocytes from the actual distribution area based on a reference distribution area of neutrophils of a reference leukocyte classification scattergram of one or more normal blood samples, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light,

determining a second count result of cells falling within the segmented granulocyte distribution region, and

Based on the first counting result and the second counting result, a counting result of band-shaped nuclear granulocytes in the blood sample to be tested is determined and output.

According to a third aspect of an embodiment of the present application, a blood cell analysis method is provided, comprising:

Draw the blood sample to be tested;

Mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and allowing particles in the first measurement sample to pass through an optical detection area irradiated with light one by one to obtain first optical information generated by the particles in the first measurement sample after being irradiated with light;

Mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes, and allowing particles in the second measurement sample to pass through an optical detection area irradiated with light one by one to obtain second optical information generated by the particles in the second measurement sample after being irradiated with light; and

When it is determined that the blood sample to be tested has an abnormal increase in band-shaped nuclear granulocytes:

generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information,

determining a first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram,

determining the actual distribution area of neutrophils from the first leukocyte classification scattergram,

Reference neutrophils based on a reference leukocyte differential scatter plot of one or more normal blood samples distribution area, determining the segmented granulocyte distribution area from the actual distribution area, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement sample for leukocyte classification prepared from a normal blood sample is irradiated with light,

determining a second count result of cells falling within the segmented granulocyte distribution region, and

Based on the first counting result and the second counting result, a counting result of band-shaped nuclear granulocytes in the blood sample to be tested is determined and output.

According to a fourth aspect of an embodiment of the present application, a blood cell analysis method is provided, comprising:

Draw the blood sample to be tested;

Mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and allowing particles in the first measurement sample to pass through an optical detection area irradiated with light one by one to obtain first optical information generated by the particles in the first measurement sample after being irradiated with light;

Mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes, and allowing particles in the second measurement sample to pass through an optical detection area irradiated with light one by one to obtain second optical information generated by the particles in the second measurement sample after being irradiated with light; and

When it is determined that the blood sample to be tested has an abnormal increase in band-shaped nuclear granulocytes:

generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information,

determining a first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram,

determining the actual distribution area of neutrophils from the first leukocyte classification scattergram,

determining the distribution area of segmented granulocytes from the actual distribution area based on a reference distribution area of neutrophils of a reference leukocyte classification scattergram of one or more normal blood samples, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light,

determining a second count result of cells falling within the segmented granulocyte distribution region, and

Based on the first counting result and the second counting result, a counting result of band-shaped nuclear granulocytes in the blood sample to be tested is determined and output.

According to a fifth aspect of the embodiment of the present application, a blood cell analyzer is provided, comprising: a sample suction device for sucking a blood sample to be tested; a sample preparation device for mixing a portion of the blood sample to be tested, a hemolytic agent and a first measurement sample for leukocyte classification by mixing with a first fluorescent dye, and a second measurement sample for identifying platelets and/or reticulocytes by mixing with another part of the blood sample to be tested, a diluent, and a second fluorescent dye; an optical detection device, comprising a flow chamber, a light source, and a light detector, the flow chamber being used for allowing the first measurement sample and the second measurement sample to pass through respectively, the light source being used for irradiating the first measurement sample and the second measurement sample passing through the flow chamber respectively with light, and the light detector being used for detecting first optical information and second optical information generated by the first measurement sample and the second measurement sample after being irradiated with light when passing through the flow chamber respectively; and a data processing device, configured to: based on the first optical information and the second optical information, identify whether there is an abnormal increase in band cells in the blood sample to be tested, and/or provide a counting result of band cells in the blood sample to be tested.

According to a sixth aspect of an embodiment of the present application, a blood cell analysis method is provided, comprising: drawing a blood sample to be tested; mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for white blood cell classification, and allowing particles in the first measurement sample to pass through an optical detection area irradiated with light one by one, so as to obtain first optical information generated by the particles in the first measurement sample after being irradiated with light; mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes, and allowing particles in the second measurement sample to pass through an optical detection area irradiated with light one by one, so as to obtain second optical information generated by the particles in the second measurement sample after being irradiated with light; and based on the first optical information and the second optical information, identifying whether there is an abnormal increase in band cells in the blood sample to be tested, and/or providing a counting result of band cells in the blood sample to be tested.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which constitute a part of the specification, illustrate embodiments of the present application and, together with the description, serve to explain the principles of the present application.

The present application can be more clearly understood from the following detailed description with reference to the accompanying drawings, in which:

FIG1 is a schematic diagram of the structure of a blood cell analyzer according to some embodiments of the present application;

FIG2 shows a specific example of an optical detection device;

FIG3 shows a first leukocyte classification scatter plot of a blood sample of a dog without band cell excess abnormality according to some embodiments of the present application;

FIG4 shows a first leukocyte classification scatter plot of a blood sample of a cat without band cell excess abnormality according to some embodiments of the present application;

FIG5 shows a first leukocyte classification scatter plot of a blood sample of a dog with band cell excess abnormality according to some embodiments of the present application;

FIG6 shows a first leukocyte classification scatter plot of a blood sample of a cat with abnormal band cell increase according to some embodiments of the present application;

FIG7 shows a second leukocyte classification scattergram of a blood sample according to some embodiments of the present application;

FIG8 shows a scatter plot of a reticulocyte channel of a blood sample according to some embodiments of the present application;

FIG9 is a schematic diagram showing a reference distribution area according to some embodiments of the present disclosure;

FIG. 10 shows the distribution area of segmented granulocytes in the actual distribution area according to some embodiments of the present disclosure;

FIG11 is a schematic diagram showing a flow chart of a blood cell analysis method according to some embodiments of the present disclosure;

FIG. 12 is a schematic flow chart showing a blood cell analysis method according to other embodiments of the present disclosure.

It should be understood that the size of each part shown in the accompanying drawings is not necessarily drawn according to the actual proportional relationship. In addition, the same or similar reference numerals represent the same or similar components.

DETAILED DESCRIPTION

Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. The description of the exemplary embodiments is merely illustrative and is by no means intended to limit the present application and its application or use. The present application can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to make the present application thorough and complete and to fully express the scope of the present application to those skilled in the art. It should be noted that unless otherwise specifically stated, the relative arrangement of the parts and steps, the composition of the materials, the numerical expressions and the numerical values set forth in these embodiments should be interpreted as being merely exemplary, rather than as limitations.

The words "first", "second" and similar words used in this application do not indicate any order, quantity or importance, but are only used to distinguish different parts. The words "include" or "comprises" and similar words mean that the elements before the word include the elements listed after the word, and do not exclude the possibility of including other elements. "Up", "down" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

In the present application, when a specific component is described as being located between a first component and a second component, there may or may not be an intermediate component between the specific component and the first component or the second component. When a specific component is described as being connected to other components, the specific component may be directly connected to the other components without an intermediate component, or may not be directly connected to the other components but have an intermediate component.

All terms used in this application (including technical terms or scientific terms) have the same meaning as those commonly used in the field to which this application belongs. The meanings understood by technicians are the same unless otherwise specifically defined. It should also be understood that the terms defined in general dictionaries, such as general dictionaries, should be interpreted as having the meaning consistent with their meanings in the context of the relevant technology, and should not be interpreted in an idealized or extremely formal sense, unless explicitly defined herein.

Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

To facilitate the subsequent explanation, some of the terms involved below are briefly explained here:

1) Scatter plot: A two-dimensional or three-dimensional graph generated by a blood cell analyzer, on which the two-dimensional or three-dimensional characteristic information of multiple particles is distributed. The X-axis, Y-axis, and Z-axis of the scatter plot each represent a characteristic of each particle. For example, in a scatter plot, the X-axis represents the forward scatter (FS) signal intensity, the Y-axis represents the fluorescence (FL) signal intensity, and the Z-axis represents the side scatter (SS) signal intensity.

2) Cell group: a particle group formed by multiple particles with the same characteristics distributed in a certain area of the scatter plot, such as a leukocyte group, and a neutrophil group, a lymphocyte group, a monocyte group, an eosinophil group or a basophil group among the leukocytes.

3) Blood ghosts: fragments obtained by dissolving red blood cells and platelets in the blood with hemolytic reagents.

At present, blood cell analyzers can test samples such as human blood and blood of other mammals (such as dogs, cats, horses, etc.), poultry blood, fish blood, etc. Usually, blood cell analyzers count and classify white blood cells through the DIFF channel (white blood cell classification channel), for example, classifying white blood cells into five types of white blood cells: lymphocytes (Lym), monocytes (Mon), neutrophils (Neu), eosinophils (Eos) and basophils (Baso). In addition, blood cell analyzers obtain reticulocyte count values, red blood cell count values, platelet count values, etc. through the RET channel (reticulocyte detection channel or platelet optical detection channel).

The blood cell analyzer used in the embodiment of the present application classifies and counts the particles in the sample by combining the laser scattering method and the flow cytometry technology of fluorescent staining. For example, the white blood cell classification detection principle of the blood cell analyzer is as follows: first, a blood sample is drawn, and the sample is treated with a hemolytic agent and a fluorescent dye for white blood cell classification, wherein the red blood cells are destroyed and dissolved by the hemolytic agent, and the white blood cells are not dissolved, but the fluorescent dye can enter the nucleus of the white blood cells with the help of the hemolytic agent and bind to the nucleic acid substance in the nucleus; then the particles in the blood sample pass through the detection hole irradiated by the laser beam one by one. When the laser beam irradiates the particles, the characteristics of the particles themselves (such as volume, degree of staining, size and content of cell contents, cell nuclear density, etc.) can block or change the direction of the laser beam, thereby generating scattered light of various angles corresponding to its characteristics. After these scattered lights are received by the light detector, relevant information on the structure and composition of the particles can be obtained. Among them, the forward scattered light reflects the number and volume of the particles, and the side scattered light reflects the internal structure of the cells. The fluorescence reflects the complexity of the structure of the cell (such as intracellular particles or cell nucleus), and the content of nucleic acid in the cell. This optical information can be used to classify and count the particles in the sample.

Fig. 1 is a schematic diagram of the structure of a blood cell analyzer according to some embodiments of the present application. The blood cell analyzer 100 includes a sample suction device 110, a sample preparation device 120, an optical detection device 130 and a data processing device 140. The blood cell analyzer 100 also has a liquid path system (not shown) for connecting the sample suction device 110, the sample preparation device 120 and the optical detection device 130 so as to transport liquid between these devices.

The sample suction device 110 is used to suck the blood sample to be tested. The blood sample to be tested can be a human blood sample or an animal blood sample. The animal blood sample can be, but is not limited to, a blood sample of a mammal such as a cat or a dog.

In some embodiments, the sample suction device 110 has a sampling needle (not shown) for sucking the blood sample to be tested. In addition, the sample suction device 110 may also include a driving device, which is used to drive the sampling needle to quantitatively suck the blood sample to be tested through the needle mouth of the sampling needle. The sample suction device 110 can transport the collected blood sample to the sample preparation device 120.

The sample preparation device 120 is used to mix a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and is used to mix another portion of the blood sample to be tested, a diluent (for example, a low osmotic pressure diluent), and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes. Further, the second measurement sample can also be used to identify platelets, mature red blood cells, reticulocytes, and leukocytes.

In the embodiments of the present application, the hemolytic agent is used to dissolve the red blood cells in the blood and break the red blood cells into fragments, but can keep the morphology of the white blood cells basically unchanged.

In the embodiment of the present application, the first fluorescent dye is a fluorescent dye for dyeing DNA in white blood cells for realizing classification of white blood cells, for example, it can be a fluorescent dye capable of classifying white blood cells in a blood sample into five white blood cell subpopulations (neutrophils, lymphocytes, monocytes, eosinophils and basophils). The second fluorescent dye is different from the first fluorescent dye, and the second fluorescent dye is a fluorescent dye for dyeing DNA and RNA in reticulocytes for identifying platelets and/or reticulocytes in a blood sample (capable of distinguishing reticulocytes, red blood cells, platelets and white blood cells).

In some embodiments, the sample preparation device 120 may include at least one reaction pool and a reagent supply device (not shown in the figure). At least one reaction pool is used to receive the blood sample to be tested sucked by the sample suction device 110, and the reagent supply device provides the processing reagent (including hemolytic agent, first fluorescent dye, second fluorescent dye, etc.) to at least one reaction pool, so that the blood sample to be tested sucked by the sample suction device 110 and the processing reagent provided by the reagent supply device are mixed in the reaction pool to prepare the measurement sample (including the first measurement sample and the second measurement sample).

For example, at least one reaction pool may include a first reaction pool (or may also be referred to as a leukocyte reaction pool) and a second reaction pool (or may also be referred to as a reticulocyte reaction pool), and the reagent supply device may include a first reagent supply unit and a second reagent supply unit. The sample suction device 110 is used to partially distribute the sucked blood sample to be tested to the first reaction pool and the second reaction pool, respectively. The first reagent supply unit is used to provide a hemolytic agent and a first fluorescent dye to the first reaction pool, so that the portion of the blood sample to be tested allocated to the first reaction pool is mixed and reacted with the hemolytic agent and the first fluorescent dye to prepare a first measurement sample. The second reagent supply unit is used to provide a second fluorescent dye and an optional diluent (for example, for sphering red blood cells) to the second reaction pool, so that the portion of the blood sample to be tested allocated to the second reaction pool is mixed and reacted with the second fluorescent dye and an optional diluent to prepare a second measurement sample.

The optical detection device 130 includes a flow chamber, a light source, and a light detector. The flow chamber is used for allowing the first measurement sample and the second measurement sample to pass through, respectively. The light source is used to illuminate the first measurement sample and the second measurement sample passing through the flow chamber, respectively, with light. The light detector is used to detect the first optical information and the second optical information generated after the first measurement sample and the second measurement sample are illuminated by light when passing through the flow chamber, respectively.

It can be understood here that the detection channel for white blood cell classification (also called DIFF channel) refers to the detection of the first measurement sample prepared by the sample preparation device 120 by the optical detection device 130, while the detection channel for identifying platelets and/or reticulocytes (also called RET channel) refers to the detection of the second measurement sample prepared by the sample preparation device 120 by the optical detection device 130.

In this article, a flow chamber refers to a chamber of a focused liquid flow suitable for detecting light scattering signals and fluorescent signals. When a particle, such as a blood cell, passes through the detection hole of the flow chamber, the particle scatters the incident light beam directed to the detection hole from the light source in all directions. A light detector can be set at one or more different angles relative to the incident light beam to detect the light scattered by the particle, thereby obtaining a light scattering signal. Since different particles have different light scattering properties, light scattering signals can be used to distinguish different particle populations. Specifically, the light scattering signal detected near the incident light beam is generally referred to as a forward light scattering signal or a small-angle light scattering signal. In some embodiments, the forward light scattering signal can be detected from an angle of about 1° to about 10° with the incident light beam. In some other embodiments, the forward light scattering signal can be detected from an angle of about 2° to about 6° with the incident light beam. The light scattering signal detected at a direction of about 90° with the incident light beam is generally referred to as a side scattered light signal. In some embodiments, the side scattered light signal can be detected from an angle of about 65° to about 115° with the incident light beam. Typically, fluorescent signals from blood cells stained with fluorescent dyes are also detected at a direction of about 90° to the incident light beam.

In some embodiments, the light detector may include a forward scattered light detector for detecting a forward scattered light signal. The first optical information may include a forward scattered light signal, a side scattered light detector for detecting a side scattered light signal, and a fluorescence detector for detecting a fluorescence signal. Accordingly, the first optical information may include a forward scattered light signal, a side scattered light signal, and a fluorescence signal of particles in the first measurement sample, and the second optical information may include a forward scattered light signal, a side scattered light signal, and a fluorescence signal of particles in the second measurement sample.

FIG2 shows a specific example of an optical detection device 130. The optical detection device 130 has a light source 101, a beam shaping component 102, a flow chamber 103, and a forward scattered light detector 104, which are sequentially arranged in a straight line. A dichroic mirror 106 is arranged at a 45° angle to the straight line on one side of the flow chamber 103. A portion of the side light emitted by the particles in the flow chamber 103 passes through the dichroic mirror 106 and is captured by a fluorescence detector 105 arranged at a 45° angle behind the dichroic mirror 106; another portion of the side light is reflected by the dichroic mirror 106 and is captured by a side scattered light detector 107 arranged at a 45° angle in front of the dichroic mirror 106.

The data processing device 140 is used to process and calculate the data to obtain the required results. For example, a two-dimensional scatter plot or a three-dimensional scatter plot can be generated based on the various light signals collected, and particle analysis can be performed on the scatter plot based on the gating method. The data processing device 140 can also visualize the intermediate calculation results or the final calculation results, and then display them through the display device 150. In the embodiment of the present application, the data processing device 140 is configured to implement the method steps described in detail below.

In the application embodiment, the data processing device 140 includes but is not limited to a central processing unit (CPU), a microcontroller unit (MCU), a field-programmable gate array (FPGA), a digital signal data processing device (DSP), and other devices for interpreting computer instructions and processing data in computer software. For example, the data processing device 140 is used to execute various computer applications in a computer-readable storage medium, so that the blood cell analyzer 100 executes the corresponding detection process and analyzes the optical information or optical signal detected by the optical detection device 130 in real time.

In addition, the blood cell analyzer 100 may further include a first housing 160 and a second housing 170. The display device 150 may be, for example, a user interface. The optical detection device 130 and the data processing device 140 are disposed inside the second housing 170. The sample preparation device 120 is, for example, disposed inside the first housing 160, and the display device 150 is, for example, disposed on the outer surface of the first housing 160 and is used to display the detection result of the blood cell analyzer 100.

The embodiments of the present application propose to combine the first optical information obtained through the DIFF channel and the second optical information obtained through the RET channel to identify whether there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested, and/or provide a counting result of the band-shaped granulocytes, so as to better assist doctors in making inflammation judgments.

According to the first embodiment of the present application, the data processing device 140 is configured as follows:

A first leukocyte classification scatter plot is generated based on the first optical information, and a second leukocyte classification scatter plot is generated based on the second optical information. Cell classification scatter plot;

Determine a first counting result of neutrophils of the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram;

Determine the actual distribution area of neutrophils from the first leukocyte classification scatter plot;

determining the distribution area of segmented granulocytes from the actual distribution area based on the reference distribution area of neutrophils of a reference leukocyte classification scattergram of one or more normal blood samples, the reference leukocyte classification scattergram being generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light;

determining a second count result of cells falling within the segmented granulocyte distribution region; and

Based on the first counting result and the second counting result, it is determined whether to alarm if there is an abnormal increase in band cells in the blood sample to be tested, and/or the counting result of band cells in the blood sample to be tested is determined and outputted.

In the first embodiment of the present application, the first counting result is first obtained by combining the leukocyte classification scatter plot obtained through the DIFF channel and the leukocyte classification scatter plot obtained through the RET channel, and then the second counting result is obtained according to the actual distribution area of the neutrophils of the blood sample to be tested in the first leukocyte classification scatter plot and the reference distribution area of the neutrophils of the normal blood sample in the reference leukocyte classification scatter plot. Based on the first counting result and the second counting result, it can be identified whether there is an abnormal increase in the number of band-shaped nuclear granulocytes in the blood sample to be tested, and an alarm prompt is given when there is an abnormal increase in the number of band-shaped nuclear granulocytes. Alternatively, the counting result of the band-shaped nuclear granulocytes in the blood sample to be tested can be determined and output based on the first counting result and the second counting result. This can better assist doctors in diagnosis.

As some implementations of the first embodiment, the data processing device 140 is further configured to: when the difference between the first counting result and the second counting result is greater than a preset threshold value: output an alarm indicating that there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested, and/or output the difference between the first counting result and the second counting result as the counting result of band-shaped granulocytes in the blood sample to be tested.

According to the second embodiment of the present application, the data processing device 140 is configured to, when determining that there is an abnormal increase in band-shaped nuclear granulocytes in the blood sample to be tested:

generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information;

Determine a first counting result of neutrophils of the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram;

Determine the actual distribution area of neutrophils from the first leukocyte classification scatter plot;

determining the distribution area of segmented granulocytes from the actual distribution area based on the reference distribution area of neutrophils of a reference leukocyte classification scattergram of one or more normal blood samples, the reference leukocyte classification scattergram being generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light;

determining a second count result of cells falling within the segmented granulocyte distribution region; and

Based on the first counting result and the second counting result, a counting result of band-shaped nuclear granulocytes in the blood sample to be tested is determined and output.

In the second embodiment of the present application, when it is determined that there is an abnormal increase in band-shaped nuclear granulocytes in the blood sample to be tested, the first counting result is first obtained by combining the white blood cell classification scatter plot obtained through the DIFF channel and the white blood cell classification scatter plot obtained through the RET channel, and then the second counting result is obtained according to the actual distribution area of the neutrophils in the blood sample to be tested in the first white blood cell classification scatter plot and the reference distribution area of the neutrophils in the normal blood sample in the reference white blood cell classification scatter plot; finally, the counting result of the band-shaped nuclear granulocytes in the blood sample to be tested is determined and output based on the first counting result and the second counting result. This can better assist doctors in diagnosis.

It can be understood that the difference between the first embodiment and the second embodiment of the present application lies in whether the data processing device 140 has determined that there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested (for example, it has been determined that there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested through other detection processes) before performing the corresponding operation. In the case where it has been determined that there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested, the data processing device 140 only needs to determine and output the counting result of the band-shaped granulocytes in the blood sample to be tested, and there is no need to perform the operation of alarming the abnormal increase in band-shaped granulocytes in the blood sample to be tested.

To facilitate understanding, some scatter plots are provided below to further illustrate this.

In the first white blood cell classification scatter plot shown in Figures 3 and 4, there are obvious boundaries between the lymphocyte (DIFF_Lym) group, the monocyte (DIFF_Mon) group, the neutrophil (DIFF_Neu) group, the eosinophil (DIFF_Eos) group, the basophil (DIFF_Baso) group, and the blood ghost particle group. At this time, the white blood cells in the blood sample can be accurately classified into five categories through the first white blood cell classification scatter plot of the DIFF channel, that is, the white blood cells are classified into neutrophils (DIFF_Neu), lymphocytes (DIFF_Lym), monocytes (DIFF_Mon), eosinophils (DIFF_Eos) and basophils (DIFF_Baso), and the white blood cell count value is equal to the value after subtracting the blood ghost particles from all particles.

It can be understood that the first leukocyte classification scatter plot of the blood sample without abnormal band cell increase in FIG. 3 and FIG. 4 can be used as a reference leukocyte classification scatter plot of a normal blood sample.

However, in the first leukocyte classification scatter plots shown in Figures 5 and 6, there is no clear boundary between the lymphocyte (DIFF_Lym) group, the monocyte (DIFF_Mon) group, and the neutrophil (DIFF_Neu) group. In other words, when there is an abnormal increase in band nuclei in the blood sample, it is difficult to accurately give the classification results of lymphocytes (DIFF_Lym), monocytes (DIFF_Mon), and neutrophils (DIFF_Neu) through the first leukocyte classification scatter plot.

It can be understood that in the case shown in Figures 5 and 6, the white blood cell count value is still equal to the value after subtracting the blood ghost particles from all particles, and the eosinophil percentage (DIFF_Eos%) and basophil percentage (DIFF_Baso%) can still be determined by the first white blood cell classification scatter plot.

It can also be understood that the first leukocyte classification scatter plot is a leukocyte classification scatter plot obtained through the DIFF channel.

Based on the above description, it can be seen that when there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested, it is difficult to accurately obtain the neutrophil counting result (also referred to as the first counting result) of the blood sample to be tested directly based on the first white blood cell classification scatter plot, and further it is also difficult to directly determine the band-shaped granulocyte counting result based on the first white blood cell classification scatter plot.

Based on this, the embodiment of the present application can accurately determine the first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scatter plot and the second leukocyte classification scatter plot. It should be understood that the first counting result may include the neutrophil percentage and/or the neutrophil count value.

As some implementations, the data processing device 140 may be configured to first generate a reticulocyte channel scatter plot as shown in FIG8 based on the forward scattered light signal and the fluorescence signal in the second optical information and identify white blood cells according to the reticulocyte channel scatter plot, and then generate a second white blood cell classification scatter plot as shown in FIG7 based on the side scattered light signal and the forward scattered light signal of the identified white blood cells. It can be understood that the second white blood cell classification scatter plot is the white blood cell classification scatter plot obtained through the RET channel.

In the second leukocyte classification scatter plot shown in FIG7 , no matter whether the blood sample to be tested has abnormal increase in band nuclei, there is a clear boundary between the lymphocyte (RET_Lym) group, the monocyte (RET_Mon) group, and the granulocyte (RET_Gran) group. Here, granulocytes include neutrophils and eosinophils.

In this case, the percentages of the leukocyte groups can be calculated by the second leukocyte classification scatter plot, which are lymphocyte percentage (RET_Lym%), monocyte percentage (RET_Mon%) and granulocyte percentage (RET_Gran%).

In the reticulocyte channel scatter plot shown in FIG8 , from left to right in the FL direction are mature red blood cells, low-fluorescence reticulocytes, medium-fluorescence reticulocytes, high-fluorescence reticulocytes, and white blood cells. Based on the reticulocyte channel scatter plot, the optical red blood cell count result, the optical platelet count result, and the reticulocyte count result can be determined. The results showed that the number of reticulocytes with low fluorescence intensity, reticulocytes with medium fluorescence intensity and reticulocytes with high fluorescence intensity were significantly higher than that of the control group.

It can be seen from the above description that regardless of whether the blood sample to be tested has abnormal increase in band nuclei, the data processing device 140 can accurately determine the first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram.

Some implementations of determining a first counting result of neutrophils in a blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram are given below.

As some implementations, the data processing device 140 can be configured to determine the eosinophil count value and the leukocyte count value of the blood sample to be tested based on the first leukocyte classification scatter plot of the blood sample to be tested, and determine the granulocyte percentage (i.e., RET_Gran%) of the blood sample to be tested based on the second leukocyte classification scatter plot. Granulocytes include neutrophils and eosinophils. Then, the first counting result of the neutrophils of the blood sample to be tested can be determined based on the eosinophil count value, the leukocyte count value, and the granulocyte percentage.

The foregoing description has described how the data processing device 140 accurately obtains the first counting result of the neutrophils in the blood sample to be tested.

In order to detect the counting results of band-shaped neutrophils in a blood sample, the data processing device 140 of each embodiment of the present application is also configured to determine the actual distribution area of neutrophils from the first white blood cell classification scatter plot, and determine the segmented neutrophil distribution area from the actual distribution area based on the reference distribution area of neutrophils in the reference white blood cell classification scatter plot of one or more normal blood samples.

Here, the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement sample for leukocyte classification prepared from a normal blood sample is irradiated with light. The normal blood sample is a blood sample that does not have an abnormal increase in band-shaped nuclear granulocytes. In other words, the reference leukocyte classification scattergram is a leukocyte classification scattergram of a normal blood sample obtained through the DIFF channel.

After determining the segmented neutrophil distribution area from the actual distribution area of neutrophils in the first leukocyte classification scattergram, the data processing device 140 is further configured to determine the counting result (also referred to as the second counting result) of cells falling within the segmented neutrophil distribution area. The second counting result may include the percentage of cells falling within the segmented neutrophil distribution area to cells within the actual distribution area and/or the counting value of cells falling within the segmented neutrophil distribution area.

Since most of the neutrophils in normal blood samples are segmented granulocytes, and the distribution of segmented granulocytes in different blood samples in the leukocyte classification scatter plot under the DIFF channel is similar, the segmented granulocyte distribution area that can approximately represent the distribution of segmented granulocytes can be determined from the actual distribution area based on the reference distribution area of neutrophils in the reference leukocyte classification scatter plot of normal blood samples. The second counting result of the cells in the segmented granulocyte distribution area can be approximately regarded as the counting result of the segmented granulocytes of the blood sample to be tested.

Therefore, the data processing device 140 can determine the counting result of the band-shaped neutrophils in the blood sample to be tested based on the first counting result of the neutrophils in the blood sample to be tested and the second counting result of the cells falling into the segmented neutrophil distribution area, and determine whether the blood sample to be tested has an abnormal increase in band-shaped neutrophils through the counting result of the band-shaped neutrophils.

In some embodiments, the data processing device 140 can be configured to use the difference between the first counting result and the second counting result as the counting result of the band-shaped nuclear granulocytes in the blood sample to be tested, and determine whether there is an abnormal increase in band-shaped nuclear granulocytes in the blood sample to be tested based on whether the determined counting result of the band-shaped nuclear granulocytes is greater than a preset threshold, thereby determining whether to alarm for the abnormal increase in band-shaped nuclear granulocytes in the blood sample to be tested, and/or whether to output the counting result of the band-shaped nuclear granulocytes in the blood sample to be tested.

For example, the data processing device 140 is configured to output an alarm indicating that there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested and/or output the counting result of band-shaped granulocytes in the blood sample to be tested when the difference between the first counting result and the second counting result is greater than a preset threshold. For another example, the data processing device 140 is configured to not output an alarm indicating that there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested and/or not output the counting result of band-shaped granulocytes in the blood sample to be tested when the difference between the first counting result and the second counting result is not greater than a preset threshold.

Some embodiments of the method in which the data processing device 140 determines the distribution area of segmented neutrophils from the actual distribution area based on the reference distribution area of neutrophils in the reference leukocyte classification scattergram of one or more normal blood samples are described below.

In some embodiments, one or more normal blood samples are from the same species as the blood sample to be tested. For example, in the case where the blood sample to be tested is from a cat, one or more normal blood samples are also from a cat.

Since the distribution of segmented granulocytes of different blood samples of the same species in the leukocyte classification scatter plot obtained from the DIFF channel is more similar, based on the reference leukocyte classification scatter plot of a normal blood sample from the same species as the blood sample to be tested, a segmented granulocyte distribution area that can more closely represent the distribution of segmented granulocytes can be determined from the actual distribution area. In this case, the second counting result of cells falling into the segmented granulocyte distribution area can more accurately represent the counting result of segmented granulocytes, so that the counting result of band-shaped granulocytes in the blood sample to be tested can be more accurately determined based on the first counting result and the second counting result.

As some implementations, the blood cell analyzer 100 is configured to pre-store reference leukocyte classification scatter plots of multiple normal blood samples of different species. For example, these reference leukocyte classification scatter plots can be stored in the graph 1, or may be directly stored in the data processing device 140.

In these implementations, the data processing device 140 can be configured to select a reference leukocyte classification scatter plot of multiple normal blood samples from the same species as the blood sample to be tested from pre-stored reference leukocyte classification scatter plots, so as to determine the segmented granulocyte distribution area from the actual distribution area based on the selected reference leukocyte classification scatter plot.

In some embodiments, the data processing device 140 is configured to perform shape matching with the actual distribution area for each reference distribution area of a plurality of normal blood samples, respectively, to select a reference distribution area with the highest shape similarity with the actual distribution area from the plurality of reference distribution areas of the plurality of normal blood samples as the final reference distribution area, and determine the segmented granulocyte distribution area from the actual distribution area based on the final reference distribution area.

It can be understood that there are certain differences in the reference distribution areas of neutrophils in different normal blood samples in the reference leukocyte classification scatter plot.

In the above embodiment, a reference distribution area with the highest shape similarity to the actual distribution area is selected from multiple reference distribution areas of multiple normal blood samples as the final reference distribution area, and the segmented granulocyte distribution area is determined from the actual distribution area based on the final reference distribution area. In this way, a segmented granulocyte distribution area that can more closely represent the segmented granulocyte distribution can be determined from the actual distribution area. In this way, the second counting result of cells falling into the segmented granulocyte distribution area can more accurately represent the counting result of the segmented granulocytes, so that the counting result of the rod-shaped granulocytes in the blood sample to be tested can be more accurately determined based on the first counting result and the second counting result.

As some implementations, the first leukocyte classification scattergram and the reference leukocyte classification scattergram are both composed of at least fluorescence signal intensity and scattered light signal intensity (e.g., side scattered light signal intensity). In these implementations, the data processing device 140 is further configured to perform shape matching of the reference distribution area and the actual distribution area of each normal blood sample in the multiple normal blood samples in the following manner.

First, each reference distribution area is divided into a first part and a second part. Here, the fluorescence signal intensity of any cell in the first part is not less than a preset fluorescence signal intensity, and the fluorescence signal intensity of any cell in the second part is not greater than the preset fluorescence signal intensity.

Taking the reference leukocyte classification scatter plot with the vertical axis being the fluorescence signal intensity and the horizontal axis being the side scattered light signal intensity as an example, each reference distribution area can be divided into two parts along the horizontal dotted line shown in FIG9 , and the fluorescence signal intensity corresponding to the dotted line is the preset fluorescence signal intensity. The part above the dotted line belongs to the first part, and the part below the dotted line belongs to the second part.

Then, the second part of each reference distribution area is shape-matched with the actual distribution area to select the final reference distribution area.

In other words, in these embodiments, rather than performing shape matching between the entire reference distribution area and the actual distribution area, only the second portion of the reference distribution area with a smaller fluorescence signal intensity is shape matched between the actual distribution area.

Since the fluorescence signal intensity of the band-shaped granulocytes is usually greater than that of the lobed granulocytes, only the second part of the reference distribution area with a smaller fluorescence signal intensity is matched with the actual distribution area in shape, which is conducive to accurately selecting the reference distribution area whose distribution of lobed granulocytes is most similar to that of the lobed granulocytes in the actual distribution area from multiple reference distribution areas as the final reference distribution area. In this way, the counting result of the band-shaped granulocytes in the blood sample to be tested can be determined more accurately based on the first counting result and the second counting result.

As some implementations, the data processing device 140 is further configured to perform shape matching between the second portion of each reference distribution area and the actual distribution area in the following manner.

First, the actual distribution area is divided into a third part and a fourth part. Here, the fluorescence signal intensity of any cell in the third part is not less than a preset fluorescence signal intensity, and the fluorescence signal intensity of any cell in the fourth part is not greater than the preset fluorescence signal intensity.

For example, taking the first leukocyte classification scatter plot with the vertical axis being the fluorescence signal intensity and the horizontal axis being the side scattered light signal intensity as an example, the actual distribution area can be divided into two parts along a dotted line similar to FIG. 9 , and the fluorescence signal intensity corresponding to the dotted line is the preset fluorescence signal intensity. Similarly, the part above the dotted line belongs to the third part, and the part below the dotted line belongs to the fourth part.

Then, the second portion of each reference distribution area is shape matched with the fourth portion of the actual distribution area to select the final reference distribution area.

In other words, in these implementations, the second part of the reference distribution area is not shape-matched with the entire actual distribution area, but only the second part of the reference distribution area with a smaller fluorescence signal intensity is shape-matched with the fourth part of the actual distribution area. This is conducive to more accurately selecting the reference distribution area whose distribution of lobed granulocytes is most similar to the distribution of lobed granulocytes in the actual distribution area from multiple reference distribution areas as the final reference distribution area. In this way, the counting result of the band-shaped granulocytes in the blood sample to be tested can be more accurately determined based on the first counting result and the second counting result. In addition, this is also conducive to improving the efficiency of shape matching so as to determine the lobed granulocyte distribution area more quickly.

In some embodiments, the preset fluorescence signal intensity is between the maximum fluorescence signal intensity and the minimum fluorescence signal intensity in the reference distribution area. The fluorescence signal intensity is between 90% and 110% of the average value. In this way, the intervals of the fluorescence signal intensity corresponding to the first part and the second part can be made substantially equivalent, so as to facilitate more accurately selecting the reference distribution area whose distribution of segmented granulocytes is most similar to the distribution of segmented granulocytes in the actual distribution area from multiple reference distribution areas as the final reference distribution area, and furthermore, based on the first counting result and the second counting result, more accurately determine the counting result of the band-shaped granulocytes in the blood sample to be tested.

In some preferred embodiments, the preset fluorescence signal intensity is an average value of the maximum fluorescence signal intensity and the minimum fluorescence signal intensity of the reference distribution area.

It is understood that the preset fluorescence signal intensities of the multiple reference distribution areas may be the same or different. As some preferred implementations, the preset fluorescence signal intensities of the multiple reference distribution areas are the same. In this way, there is no need to set a corresponding preset fluorescence signal intensity for each reference distribution area, thereby simplifying the processing.

In some embodiments, the data processing device 140 is further configured to map the final reference distribution area to the actual distribution area of the first leukocyte classification scatter plot after selecting the final reference distribution area, thereby determining the mapping area of the final reference distribution area as the segmented nuclear granulocyte distribution area (see FIG. 10 ). For example, the final reference distribution area can be mapped to the actual distribution area of the first leukocyte classification scatter plot according to its position in the corresponding reference leukocyte classification scatter plot.

As shown in FIG. 11 , the embodiment of the present application further provides a blood cell analysis method 200, comprising:

S210, drawing a blood sample to be tested;

S220, mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and allowing particles in the first measurement sample to pass through an optical detection area irradiated with light one by one to obtain first optical information generated by the particles in the first measurement sample after being irradiated with light;

S230, mixing another portion of the blood sample to be tested, the diluent, and the second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes, and allowing particles in the second measurement sample to pass through an optical detection area irradiated with light one by one to obtain second optical information generated by the particles in the second measurement sample after being irradiated with light;

S240, based on the first optical information and the second optical information, identifying whether there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested, and/or providing a counting result of band-shaped granulocytes in the blood sample to be tested.

As some embodiments, step S240 includes the following as shown in FIG. 11:

S241, generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information;

S242, determining the blood sample to be tested based on the first leukocyte classification scatter plot and the second leukocyte classification scatter plot The first neutrophil count results;

S243, determining the actual distribution area of neutrophils from the first leukocyte classification scattergram;

S244, determining a distribution area of segmented neutrophils from an actual distribution area based on a reference distribution area of neutrophils in a reference leukocyte classification scattergram of one or more normal blood samples, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light;

S245, determining a second counting result of cells falling within the segmented granulocyte distribution area; and

S246, based on the first counting result and the second counting result, determining whether to alarm for the abnormal increase of band cells in the blood sample to be tested, and/or determining and outputting the counting result of band cells in the blood sample to be tested.

In some embodiments, in step S246, when the difference between the first counting result and the second counting result is greater than a preset threshold, an alarm is outputted indicating that there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested. In other embodiments, in step S246, when the difference between the first counting result and the second counting result is greater than a preset threshold, the difference between the first counting result and the second counting result is outputted as the counting result of band-shaped granulocytes in the blood sample to be tested.

As some other embodiments, when it is determined that there is an abnormal increase in band nucleus cells in the blood sample to be tested, step S240 is performed. In this case, referring to the blood cell analysis method 300 shown in FIG. 12 , step S240 includes:

S241, generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information;

S242, determining a first counting result of neutrophils of the blood sample to be tested based on the first leukocyte classification scatter plot and the second leukocyte classification scatter plot;

S243, determining the actual distribution area of neutrophils from the first leukocyte classification scattergram;

S244, determining a distribution area of segmented neutrophils from an actual distribution area based on a reference distribution area of neutrophils in a reference leukocyte classification scattergram of one or more normal blood samples, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light;

S245, determining a second counting result of cells falling within the segmented granulocyte distribution area; and

S247, based on the first counting result and the second counting result, determining and outputting the counting result of the band-shaped nuclear granulocytes in the blood sample to be tested.

In some embodiments, one or more normal blood samples and the test blood sample are from the same species.

In some embodiments, in step S241, the eosinophil count value and the leukocyte count value of the blood sample to be tested are determined based on the first leukocyte classification scatter plot, and the granulocyte percentage of the blood sample to be tested is determined based on the second leukocyte classification scatter plot. Granulocytes include neutrophils and eosinophils. Then, based on the eosinophil count value, the leukocyte count value and the granulocyte percentage, a first counting result is determined.

In some embodiments, in step S244, shape matching is performed with the actual distribution area for each reference distribution area of the multiple normal blood samples, so as to select a reference distribution area with the highest shape similarity with the actual distribution area from the multiple reference distribution areas of the multiple normal blood samples as the final reference distribution area. Then, based on the final reference distribution area, the segmented granulocyte distribution area is determined from the actual distribution area.

As some implementations, the first leukocyte classification scattergram and the reference leukocyte classification scattergram are both composed of at least fluorescence signal intensity and scattered light signal intensity. In these implementations, each reference distribution area can be divided into a first part and a second part, and the second part of each reference distribution area is shape-matched with the actual distribution area to select the final reference distribution area. Here, the fluorescence signal intensity of any cell in the first part is not less than the preset fluorescence signal intensity, and the fluorescence signal intensity of any cell in the second part is not greater than the preset fluorescence signal intensity.

As some preferred implementations, the actual distribution area can be divided into a third part and a fourth part, and the second part of each reference distribution area is shape-matched with the fourth part of the actual distribution area to select the final reference distribution area. Here, the fluorescence signal intensity of any cell in the third part is not less than the preset fluorescence signal intensity, and the fluorescence signal intensity of any cell in the fourth part is not greater than the preset fluorescence signal intensity.

In some embodiments, the preset fluorescence signal intensity is between 90% and 110% of the average value of the maximum fluorescence signal intensity and the minimum fluorescence signal intensity in the reference distribution area, preferably the average value.

In some embodiments, the preset fluorescence signal intensities of the multiple reference distribution regions are the same.

More embodiments and advantages of the blood cell analysis method 200/300 proposed in the embodiments of the present application can be referred to the above description of the blood cell analyzer 100, which will not be repeated here.

The features or feature combinations mentioned in the specification, drawings and claims above, as long as they are meaningful within the scope of the present application and do not contradict each other, can be used in any combination or alone. The advantages and features described with reference to the blood cell analyzer provided in the embodiment of the present application are applicable to the blood cell analysis method provided in the embodiment of the present application in a corresponding manner, and vice versa.

The above description is only a preferred embodiment of the present application, and does not limit the scope of the present application. Any equivalent transformation scheme made by using the contents of the present application specification and drawings under the inventive concept of the present application, or directly/indirectly Applications in other related technical fields are all included in the patent protection scope of this application.

Claims (22)

A blood cell analyzer, comprising: A sample suction device, used for sucking a blood sample to be tested; a sample preparation device for mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and for mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes; an optical detection device, comprising a flow cell, a light source, and a light detector, wherein the flow cell is used for allowing the first measurement sample and the second measurement sample to pass through the flow cell, respectively, the light source is used for irradiating the first measurement sample and the second measurement sample passing through the flow cell, respectively, with light, and the light detector is used for detecting first optical information and second optical information generated after the first measurement sample and the second measurement sample are irradiated with light when passing through the flow cell, respectively; and A data processing device configured to: generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information, determining a first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram, determining the actual distribution area of neutrophils from the first leukocyte classification scattergram, determining the distribution area of segmented granulocytes from the actual distribution area based on a reference distribution area of neutrophils of a reference leukocyte classification scattergram of one or more normal blood samples, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light, determining a second count result of cells falling within the segmented granulocyte distribution region, and Based on the first counting result and the second counting result, it is determined whether to alarm for the abnormal increase of band cells in the blood sample to be tested, and/or the counting result of band cells in the blood sample to be tested is determined and outputted. The blood cell analyzer according to claim 1, characterized in that the data processing device is further configured to: When the difference between the first counting result and the second counting result is greater than a preset threshold, an alarm is outputted indicating that there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested, and/or The difference between the first counting result and the second counting result is output as the counting result of the band-shaped nuclear granulocytes in the blood sample to be tested. A blood cell analyzer, comprising: A sample suction device, used for sucking a blood sample to be tested; a sample preparation device for mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and for mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes; an optical detection device, comprising a flow cell, a light source, and a light detector, wherein the flow cell is used for allowing the first measurement sample and the second measurement sample to pass through the flow cell, respectively, the light source is used for irradiating the first measurement sample and the second measurement sample passing through the flow cell, respectively, with light, and the light detector is used for detecting first optical information and second optical information generated after the first measurement sample and the second measurement sample are irradiated with light when passing through the flow cell, respectively; and The data processing device is configured to: when it is determined that there is an abnormal increase in band-shaped nuclear granulocytes in the blood sample to be tested, generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information, determining a first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram, determining the actual distribution area of neutrophils from the first leukocyte classification scattergram, determining the distribution area of segmented granulocytes from the actual distribution area based on a reference distribution area of neutrophils of a reference leukocyte classification scattergram of one or more normal blood samples, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light, determining a second count result of cells falling within the segmented granulocyte distribution region, and Based on the first counting result and the second counting result, a counting result of band-shaped nuclear granulocytes in the blood sample to be tested is determined and output. The blood cell analyzer according to any one of claims 1 to 3, characterized in that the data processing device is further configured to: For each of the reference distribution regions of the multiple normal blood samples, shape matching with the actual distribution region is performed respectively, so as to select a reference distribution region having the highest shape similarity with the actual distribution region from the multiple reference distribution regions of the multiple normal blood samples as a final reference distribution region; and The segmented granulocyte distribution area is determined from the actual distribution area based on the final reference distribution area. The blood cell analyzer according to claim 4, characterized in that the first leukocyte classification scattergram and the reference leukocyte classification scattergram are both composed of at least fluorescence signal intensity and scattered light signal intensity; The data processing device is further configured to: Dividing each reference distribution area into a first part and a second part, wherein the fluorescence signal intensity of any cell in the first part is not less than a preset fluorescence signal intensity, and the fluorescence signal intensity of any cell in the second part is not greater than the preset fluorescence signal intensity; and The second portion of each reference distribution area is shape-matched with the actual distribution area to select the final reference distribution area. The blood cell analyzer according to claim 5, characterized in that the data processing device is further configured to: The actual distribution area is divided into a third part and a fourth part, wherein the fluorescence signal intensity of any cell in the third part is not less than the preset fluorescence signal intensity, and the fluorescence signal intensity of any cell in the fourth part is not greater than the preset fluorescence signal intensity; and The second portion of each reference distribution area is shape-matched with the fourth portion of the actual distribution area to select the final reference distribution area. The blood cell analyzer according to claim 5 or 6 is characterized in that the preset fluorescence signal intensity is between 90% and 110% of the average value of the maximum fluorescence signal intensity and the minimum fluorescence signal intensity in the reference distribution area, preferably the average value. The blood cell analyzer according to any one of claims 5 to 7, characterized in that the preset fluorescence signal intensities of the multiple reference distribution areas are the same. The blood cell analyzer according to any one of claims 1 to 8, characterized in that the data processing device is further configured to: Determining the eosinophil count value and the leukocyte count value of the blood sample to be tested based on the first leukocyte classification scatter plot; Determining the percentage of granulocytes in the blood sample to be tested based on the second leukocyte classification scattergram, wherein the granulocytes include neutrophils and eosinophils; and The first count result is determined based on the eosinophil count value, the white blood cell count value, and the granulocyte percentage. The blood cell analyzer according to any one of claims 1 to 9, characterized in that the one or more normal blood samples and the blood sample to be tested are from the same species. A blood cell analysis method, comprising: Draw the blood sample to be tested; Mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and allowing particles in the first measurement sample to pass through an optical detection area irradiated with light one by one to obtain first optical information generated by the particles in the first measurement sample after being irradiated with light; Mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes, and allowing particles in the second measurement sample to pass through an optical detection area irradiated with light one by one to obtain second optical information generated by the particles in the second measurement sample after being irradiated with light; generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information; Determining a first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram; determining the actual distribution area of neutrophils from the first leukocyte classification scattergram; Determining the distribution area of segmented granulocytes from the actual distribution area based on a reference distribution area of neutrophils in a reference leukocyte classification scattergram of one or more normal blood samples, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light; determining a second count result of cells falling within the segmented granulocyte distribution region; and Based on the first counting result and the second counting result, it is determined whether to alarm for the abnormal increase of band cells in the blood sample to be tested, and/or the counting result of band cells in the blood sample to be tested is determined and outputted. The method according to claim 11, characterized in that, based on the first counting result and the second counting result, determining whether to alarm for the presence of an abnormal increase in band cells in the blood sample to be tested, and/or determining and outputting the counting result of band cells in the blood sample to be tested, comprises: When the difference between the first counting result and the second counting result is greater than a preset threshold, an alarm is outputted indicating that there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested, and/or The difference between the first counting result and the second counting result is output as the counting result of the band-shaped nuclear granulocytes in the blood sample to be tested. A blood cell analysis method, comprising: Draw the blood sample to be tested; Mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and allowing particles in the first measurement sample to pass through an optical detection area irradiated with light one by one to obtain first optical information generated by the particles in the first measurement sample after being irradiated with light; Mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes, and allowing particles in the second measurement sample to pass through an optical detection area irradiated with light one by one to obtain second optical information generated by the particles in the second measurement sample after being irradiated with light; and When it is determined that the blood sample to be tested has an abnormal increase in band-shaped nuclear granulocytes: generating a first leukocyte classification scattergram based on the first optical information, and generating a second leukocyte classification scattergram based on the second optical information, Based on the first leukocyte classification scatter plot and the second leukocyte classification scatter plot, the blood to be tested is determined First count result of neutrophils in fluid sample, determining the actual distribution area of neutrophils from the first leukocyte classification scattergram, determining the distribution area of segmented granulocytes from the actual distribution area based on a reference distribution area of neutrophils of a reference leukocyte classification scattergram of one or more normal blood samples, wherein the reference leukocyte classification scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte classification prepared from a normal blood sample is irradiated with light, determining a second count result of cells falling within the segmented granulocyte distribution region, and Based on the first counting result and the second counting result, a counting result of band-shaped nuclear granulocytes in the blood sample to be tested is determined and output. The method according to any one of claims 11 to 13, characterized in that, based on the reference distribution area of neutrophils in the reference leukocyte classification scattergram of one or more normal blood samples, determining the distribution area of segmented neutrophils from the actual distribution area comprises: For each of the reference distribution regions of the multiple normal blood samples, shape matching with the actual distribution region is performed respectively, so as to select a reference distribution region having the highest shape similarity with the actual distribution region from the multiple reference distribution regions of the multiple normal blood samples as a final reference distribution region; and The segmented granulocyte distribution area is determined from the actual distribution area based on the final reference distribution area. The method according to claim 14, characterized in that the first leukocyte classification scattergram and the reference leukocyte classification scattergram are both composed of at least fluorescence signal intensity and scattered light signal intensity; For each of the reference distribution areas of the multiple normal blood samples, shape matching with the actual distribution area is performed respectively, including: Dividing each reference distribution area into a first part and a second part, wherein the fluorescence signal intensity of any cell in the first part is not less than a preset fluorescence signal intensity, and the fluorescence signal intensity of any cell in the second part is not greater than the preset fluorescence signal intensity; and The second portion of each reference distribution area is shape-matched with the actual distribution area to select the final reference distribution area. The method according to claim 15, characterized in that the second part of each reference distribution area is shape matched with the actual distribution area to select the final reference distribution area, comprising: The actual distribution area is divided into a third part and a fourth part, wherein the fluorescence signal intensity of any cell in the third part is not less than the preset fluorescence signal intensity, and the fluorescence signal intensity of any cell in the fourth part is not greater than the preset fluorescence signal intensity; and The second portion of each reference distribution area is shape-matched with the fourth portion of the actual distribution area to select the final reference distribution area. The method according to claim 15 or 16 is characterized in that the preset fluorescence signal intensity is between 90% and 110% of the average value of the maximum fluorescence signal intensity and the minimum fluorescence signal intensity in the reference distribution area, preferably the average value. The method according to any one of claims 15-17 is characterized in that the preset fluorescence signal intensities of the multiple reference distribution areas are the same. The method according to any one of claims 11 to 18, characterized in that determining a first counting result of neutrophils in the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram comprises: Determining the eosinophil count value and the leukocyte count value of the blood sample to be tested based on the first leukocyte classification scatter plot; Determining the percentage of granulocytes in the blood sample to be tested based on the second leukocyte classification scattergram, wherein the granulocytes include neutrophils and eosinophils; and The first count result is determined based on the eosinophil count value, the white blood cell count value, and the granulocyte percentage. The method according to any one of claims 11-19 is characterized in that the one or more normal blood samples and the blood sample to be tested are from the same species. A blood cell analyzer, comprising: A sample suction device, used for sucking a blood sample to be tested; a sample preparation device for mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and for mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes; an optical detection device, comprising a flow cell, a light source, and a light detector, wherein the flow cell is used for allowing the first measurement sample and the second measurement sample to pass through the flow cell, respectively, the light source is used for irradiating the first measurement sample and the second measurement sample passing through the flow cell, respectively, with light, and the light detector is used for detecting first optical information and second optical information generated after the first measurement sample and the second measurement sample are irradiated with light when passing through the flow cell, respectively; and The data processing device is configured to: identify whether there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested based on the first optical information and the second optical information, and/or provide a counting result of the band-shaped granulocytes in the blood sample to be tested. A blood cell analysis method, comprising: Draw the blood sample to be tested; Mixing a portion of the blood sample to be tested, a hemolytic agent, and a first fluorescent dye to prepare a first measurement sample for leukocyte classification, and allowing particles in the first measurement sample to pass through an optical detection area irradiated with light one by one to obtain first optical information generated by the particles in the first measurement sample after being irradiated with light; Mixing another portion of the blood sample to be tested, a diluent, and a second fluorescent dye to prepare a second measurement sample for identifying platelets and/or reticulocytes, and allowing particles in the second measurement sample to pass through an optical detection area irradiated with light one by one to obtain second optical information generated by the particles in the second measurement sample after being irradiated with light; and Based on the first optical information and the second optical information, it is identified whether there is an abnormal increase in band-shaped granulocytes in the blood sample to be tested, and/or a counting result of band-shaped granulocytes in the blood sample to be tested is given.