Blood cell analyzer and blood cell analysis method

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 analysis method Technical Field

[0001] 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

[0002] A 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, etc., and output scatter plots or histograms obtained from the white blood cell, red blood cell, platelet and reticulocyte tests to assist doctors in clinical diagnosis.

[0003] Existing hematology analyzers use fluorescence staining technology to perform optical leukocyte and reticulocyte measurements (or platelet measurements). The optical leukocyte measurement obtains the white blood cell count and classification, including the count and classification of neutrophils (Neu), lymphocytes (Lym), monocytes (Mon), eosinophils (Eos), and basophils (Baso). The optical reticulocyte measurement obtains parameters such as the red blood cell count, optical platelet count, and reticulocyte count.

[0004] Neutrophils include segmented neutrophils and band neutrophils. Under normal circumstances, band neutrophils make up a small proportion of neutrophils, with segmented neutrophils being the main component. However, in abnormal conditions such as inflammation, the number of band neutrophils in the blood increases.

[0005] 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.

[0006] Summary of the Invention

[0007] 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 cells in a blood sample and / or determine the count result of the band cells in the blood sample.

[0008] According to a first aspect of an embodiment of the present application, there is provided a blood cell analyzer, comprising:

[0009] A sample suction device, used for sucking a blood sample to be tested;

[0010] 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 differentiation, 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;

[0011] an optical detection device comprising a flow cell, a light source, and a light detector, wherein the flow cell is configured to allow the first and second measurement samples to pass through the flow cell, respectively; the light source is configured to illuminate the first and second measurement samples, respectively passing through the flow cell, with light; and the light detector is configured to detect first and second optical information generated by the first and second measurement samples being illuminated by the light while respectively passing through the flow cell; and

[0012] A data processing device configured to:

[0013] 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,

[0014] determining a first neutrophil counting result of the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram,

[0015] determining the actual distribution area of ​​neutrophils from the first leukocyte classification scattergram,

[0016] determining the segmented granulocyte distribution area from the actual distribution area based on a reference distribution area of ​​neutrophils in a reference leukocyte differential scattergram of one or more normal blood samples, wherein the reference leukocyte differential scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte differential prepared from a normal blood sample is irradiated with light;

[0017] determining a second count of cells falling within the segmented granulocyte distribution region, and

[0018] Based on the first counting result and the second counting result, it is determined whether to issue an alarm for abnormal increase in band cells in the blood sample to be tested, and / or a counting result of band cells in the blood sample to be tested is determined and output.

[0019] According to a second aspect of an embodiment of the present application, there is provided a blood cell analyzer, comprising:

[0020] A sample suction device, used for sucking a blood sample to be tested;

[0021] 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 differentiation, 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;

[0022] an optical detection device comprising a flow cell, a light source, and a light detector, wherein the flow cell is configured to allow the first and second measurement samples to pass through the flow cell, respectively; the light source is configured to illuminate the first and second measurement samples, respectively passing through the flow cell, with light; and the light detector is configured to detect first and second optical information generated by the first and second measurement samples being illuminated by the light while respectively passing through the flow cell; and

[0023] 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,

[0024] 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,

[0025] determining a first neutrophil counting result of the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram,

[0026] determining the actual distribution area of ​​neutrophils from the first leukocyte classification scattergram,

[0027] determining the segmented granulocyte distribution area from the actual distribution area based on a reference distribution area of ​​neutrophils in a reference leukocyte differential scattergram of one or more normal blood samples, wherein the reference leukocyte differential scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte differential prepared from a normal blood sample is irradiated with light;

[0028] determining a second count of cells falling within the segmented granulocyte distribution region, and

[0029] Based on the first counting result and the second counting result, a counting result of band cells in the blood sample to be tested is determined and output.

[0030] According to a third aspect of an embodiment of the present application, a blood cell analysis method is provided, comprising:

[0031] Draw a blood sample to be tested;

[0032] 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 differentiation, 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;

[0033] 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

[0034] When it is determined that the blood sample to be tested has an abnormal increase in band-shaped granulocytes:

[0035] 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,

[0036] determining a first neutrophil counting result of the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram,

[0037] determining the actual distribution area of ​​neutrophils from the first leukocyte classification scattergram,

[0038] determining the segmented granulocyte distribution area from the actual distribution area based on a reference distribution area of ​​neutrophils in a reference leukocyte differential scattergram of one or more normal blood samples, wherein the reference leukocyte differential scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte differential prepared from a normal blood sample is irradiated with light;

[0039] determining a second count of cells falling within the segmented granulocyte distribution region, and

[0040] Based on the first counting result and the second counting result, a counting result of band cells in the blood sample to be tested is determined and output.

[0041] According to a fourth aspect of the embodiments of the present application, a blood cell analysis method is provided, comprising:

[0042] Draw a blood sample to be tested;

[0043] 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 differentiation, 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;

[0044] 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

[0045] When it is determined that the blood sample to be tested has an abnormal increase in band-shaped granulocytes:

[0046] 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,

[0047] determining a first neutrophil counting result of the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram,

[0048] determining the actual distribution area of ​​neutrophils from the first leukocyte classification scattergram,

[0049] determining the segmented granulocyte distribution area from the actual distribution area based on a reference distribution area of ​​neutrophils in a reference leukocyte differential scattergram of one or more normal blood samples, wherein the reference leukocyte differential scattergram is generated based on reference optical information generated after a reference measurement specimen for leukocyte differential prepared from a normal blood sample is irradiated with light;

[0050] determining a second count of cells falling within the segmented granulocyte distribution region, and

[0051] Based on the first counting result and the second counting result, a counting result of band cells in the blood sample to be tested is determined and output.

[0052] According to a fifth aspect of an embodiment of the present application, a blood cell analyzer is provided, comprising: a sample aspirating device for aspirating 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 white blood cell 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 chamber for respectively passing the first and second measurement samples; a light source for irradiating the first and second measurement samples, respectively passing through the flow chamber, with light; and a light detector for detecting first and second optical information generated by the first and second measurement samples, respectively, when irradiated by light while passing through the flow chamber; and a data processing device configured to: identify whether the blood sample to be tested has an abnormal increase in band cells, and / or provide a count result of band cells in the blood sample to be tested, based on the first and second optical information.

[0053] 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 one by one through an optical detection area irradiated by light, so as to obtain first optical information generated by the particles in the first measurement sample after being irradiated by 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 one by one through an optical detection area irradiated by light, so as to obtain second optical information generated by the particles in the second measurement sample after being irradiated by 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

[0054] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present application and, together with the description, serve to explain the principles of the present application.

[0055] The present application can be more clearly understood from the following detailed description with reference to the accompanying drawings, in which:

[0056] FIG1 is a schematic structural diagram of a blood cell analyzer according to some embodiments of the present application;

[0057] FIG2 shows a specific example of an optical detection device;

[0058] FIG3 shows a first leukocyte differential scatter plot of a blood sample of a dog without band cell excess according to some embodiments of the present application;

[0059] FIG4 shows a first leukocyte differential scatter plot of a blood sample of a cat without band cell excess according to some embodiments of the present application;

[0060] FIG5 shows a first leukocyte differential scatter plot of a blood sample of a dog with band cell excess according to some embodiments of the present application;

[0061] FIG6 shows a first leukocyte differential scatter plot of a blood sample of a cat with band cell abnormality according to some embodiments of the present application;

[0062] FIG7 shows a second leukocyte classification scattergram of a blood sample according to some embodiments of the present application;

[0063] FIG8 shows a scatter plot of the reticulocyte channel of a blood sample according to some embodiments of the present application;

[0064] FIG9 shows a schematic diagram of a reference distribution area according to some embodiments of the present disclosure;

[0065] FIG10 shows the distribution area of ​​segmented granulocytes in the actual distribution area according to some embodiments of the present disclosure;

[0066] FIG11 is a schematic diagram showing a process of a blood cell analysis method according to some embodiments of the present disclosure;

[0067] FIG12 is a schematic flow chart showing a blood cell analysis method according to other embodiments of the present disclosure.

[0068] It should be understood that the size of each part shown in the 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

[0069] 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 in no way 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 convey 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 limiting.

[0070] The terms "first," "second," and similar terms used in this application do not indicate any order, quantity, or importance, but are simply used to distinguish different parts. Terms such as "include" or "comprises" mean that the elements preceding the term include the elements listed after the term, and do not exclude the possibility of also including other elements. Terms such as "upper," "lower," 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.

[0071] In this 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 intervening component between the specific component and the first component or the second component. When a specific component is described as being connected to another component, the specific component may be directly connected to the other component without an intervening component, or may not be directly connected to the other component but may have an intervening component.

[0072] All terms (including technical or scientific terms) used in this application have the same meaning as those understood by ordinary technicians in the field to which this application belongs, unless otherwise specifically defined. It should also be understood that terms defined in general dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an idealized or highly formal sense, unless explicitly defined herein.

[0073] 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 part of the specification.

[0074] To facilitate the subsequent explanation, here is a brief explanation of some of the terms involved below:

[0075] 1) Scatterplot: A two-dimensional or three-dimensional graph generated by a hematology analyzer that displays the two-dimensional or three-dimensional characteristic information of multiple particles. The X, Y, and Z axes of the scatterplot each represent a characteristic of each particle. For example, in a scatterplot, the X axis represents the forward scattered light (FS) signal intensity, the Y axis represents the fluorescence (FL) signal intensity, and the Z axis represents the side scattered light (SS) signal intensity.

[0076] 2) Cell swarm: A particle cluster formed by multiple particles with the same characteristics distributed in a certain area of ​​the scatter plot, such as a leukocyte swarm, and a neutrophil swarm, lymphocyte swarm, monocyte swarm, eosinophil swarm, or basophil swarm among the leukocytes.

[0077] 3) Blood ghosts: fragments obtained by dissolving red blood cells and platelets in the blood with hemolytic reagents.

[0078] Currently, hematology analyzers can test samples of human blood, blood from other mammals (such as dogs, cats, and horses), poultry, and fish. Typically, hematology analyzers use the DIFF channel (white blood cell classification channel) to count and classify white blood cells, for example, into five types: lymphocytes (Lym), monocytes (Mon), neutrophils (Neu), eosinophils (Eos), and basophils (Baso). Furthermore, hematology analyzers use the RET channel (reticulocyte detection channel or platelet optical detection channel) to obtain reticulocyte counts, red blood cell counts, platelet counts, and other values.

[0079] The blood cell analyzer used in the embodiment of the present application classifies and counts particles in the sample by combining laser scattering and fluorescent staining flow cytometry. For example, the principle of white blood cell classification detection 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. Among them, the red blood cells are destroyed and lysed by the hemolytic agent, while the white blood cells are not lysed. However, 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 substances in the nucleus; then the particles in the blood sample pass through the detection hole illuminated by the laser beam one by one. When the laser beam illuminates the particles, the characteristics of the particles themselves (such as volume, staining degree, size and content of cell contents, cell nuclear density, etc.) can block or change the direction of the laser beam, thereby generating scattered light at various angles corresponding to their characteristics. After these scattered lights are received by the light detector, relevant information about the structure and composition of the particles can be obtained. Among them, the forward scattered light reflects the number and volume of the particles, the side scattered light reflects the complexity of the internal structure of the cell (such as intracellular granules or cell nuclei), and the fluorescence reflects the content of nucleic acid substances in the cell. Using this optical information, the particles in the sample can be classified and counted.

[0080] FIG1 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 aspirator 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 fluidic system (not shown) for connecting the sample aspirator 110, the sample preparation device 120, and the optical detection device 130 to facilitate fluid transfer between these devices.

[0081] The sample suction device 110 is used to suck a 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 from a mammal such as a cat or dog.

[0082] In some embodiments, the sample aspirating device 110 includes a sampling needle (not shown) for aspirating a blood sample to be tested. Furthermore, the sample aspirating device 110 may further include a drive mechanism for driving the sampling needle to quantitatively aspirate the blood sample to be tested through the needle tip of the sampling needle. The sample aspirating device 110 may transport the collected blood sample to the sample preparation device 120.

[0083] 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 white blood cell classification, and to mix another portion of the blood sample to be tested, a diluent (e.g., a hypotonic diluent), and a second fluorescent dye to prepare a second measurement sample for identifying platelets and / or reticulocytes. Furthermore, the second measurement sample can also be used to identify platelets, mature red blood cells, reticulocytes, and white blood cells.

[0084] In the embodiment of the present application, the hemolytic agent is used to dissolve the red blood cells in the blood, breaking the red blood cells into fragments, but being able to keep the morphology of the white blood cells basically unchanged.

[0085] In an embodiment of the present application, the first fluorescent dye is a fluorescent dye that stains DNA in white blood cells for white blood cell classification, for example, a fluorescent dye that can classify white blood cells in a blood sample into five white blood cell subsets (neutrophils, lymphocytes, monocytes, eosinophils, and basophils). The second fluorescent dye is different from the first fluorescent dye and is a fluorescent dye that stains 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).

[0086] In some embodiments, the sample preparation device 120 may include at least one reaction pool and a reagent supply device (not shown). The at least one reaction pool is used to receive the blood sample to be tested drawn by the sample aspirating device 110, and the reagent supply device provides processing reagents (including a hemolytic agent, a first fluorescent dye, a second fluorescent dye, etc.) to the at least one reaction pool, so that the blood sample to be tested drawn by the sample aspirating device 110 and the processing reagents provided by the reagent supply device are mixed in the reaction pool to prepare the measurement samples (including the first measurement sample and the second measurement sample).

[0087] For example, at least one reaction pool may include a first reaction pool (or may also be called a leukocyte reaction pool) and a second reaction pool (or may also be called 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 part 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 spherizing red blood cells) to the second reaction pool, so that the part of the blood sample to be tested allocated to the second reaction pool is mixed and reacted with the second fluorescent dye and the optional diluent to prepare a second measurement sample.

[0088] The optical detection device 130 includes a flow cell, a light source, and a light detector. The flow cell is used to allow a first measurement sample and a second measurement sample to pass through each flow cell. The light source is used to illuminate the first and second measurement samples passing through the flow cell. The light detector is used to detect first and second optical information generated by the first and second measurement samples being illuminated by the light as they pass through the flow cell.

[0089] 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.

[0090] As used herein, a flow cell refers to a chamber containing a focused fluid stream suitable for detecting light scattering and fluorescence signals. When a particle, such as a blood cell, passes through the detection aperture of the flow cell, the particle scatters an incident light beam directed from a light source into all directions. A light detector can be positioned at one or more different angles relative to the incident light beam to detect light scattered by the particle, thereby generating a light scattering signal. Because different particles have different light scattering properties, light scattering signals can be used to distinguish between different particle populations. Specifically, the light scattering signal detected near the incident light beam is typically referred to as a forward light scattering signal or a low-angle light scattering signal. In some embodiments, the forward light scattering signal can be detected at an angle of approximately 1° to approximately 10° relative to the incident light beam. In other embodiments, the forward light scattering signal can be detected at an angle of approximately 2° to approximately 6° relative to the incident light beam. The light scattering signal detected at approximately 90° relative to the incident light beam is typically referred to as a side scattering signal. In some embodiments, the side scattering signal can be detected at an angle of approximately 65° to approximately 115° relative to the incident light beam. Typically, fluorescent signals from blood cells stained with fluorescent dyes are also detected at a direction of approximately 90° to the incident light beam.

[0091] In some embodiments, the light detector may include a forward scattered light detector for detecting forward scattered light signals, a side scattered light detector for detecting side scattered light signals, and a fluorescence detector for detecting fluorescence signals. Accordingly, the first optical information may include the forward scattered light signals, side scattered light signals, and fluorescence signals of particles in the first measurement sample, and the second optical information may include the forward scattered light signals, side scattered light signals, and fluorescence signals of particles in the second measurement sample.

[0092] FIG2 illustrates a specific example of an optical detection device 130. This device comprises a light source 101, a beam shaping assembly 102, a flow cell 103, and a forward scattered light detector 104, arranged sequentially in a straight line. A dichroic mirror 106 is positioned on one side of the flow cell 103 at a 45° angle to the straight line. Sidelight emitted by particles in the flow cell 103 partially passes through the dichroic mirror 106 and is captured by a fluorescence detector 105 positioned behind the dichroic mirror 106 at a 45° angle. Another portion of the sidelight is reflected by the dichroic mirror 106 and captured by a side scattered light detector 107 positioned in front of the dichroic mirror 106 at a 45° angle.

[0093] The data processing device 140 is used to process and calculate data to obtain the required results. For example, it can generate a two-dimensional or three-dimensional scatter plot based on the various collected optical signals and perform particle analysis on the scatter plot using gating methods. The data processing device 140 can also visualize intermediate or final calculation results and then display them on 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.

[0094] In the embodiments of the application, 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 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 stored in a computer-readable storage medium, thereby enabling the blood cell analyzer 100 to perform the corresponding detection process and analyze the optical information or optical signals detected by the optical detection device 130 in real time.

[0095] The hematology analyzer 100 may also 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 within the second housing 170. The sample preparation device 120 may be disposed within the first housing 160, and the display device 150 may be disposed on an outer surface of the first housing 160 and is used to display the test results of the hematology analyzer 100.

[0096] The embodiments of the present application propose combining 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 cells in the blood sample to be tested, and / or provide a band cell count result to better assist doctors in making inflammation judgments.

[0097] According to the first embodiment of the present application, the data processing device 140 is configured to:

[0098] 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;

[0099] determining a first neutrophil counting result of the blood sample to be tested based on the first leukocyte differential scattergram and the second leukocyte differential scattergram;

[0100] Determine the actual distribution area of ​​neutrophils from the first leukocyte differential scatter plot;

[0101] determining the distribution area of ​​segmented granulocytes from the actual distribution area based on a reference distribution area of ​​neutrophils in a reference leukocyte differential scattergram of one or more normal blood samples, the reference leukocyte differential scattergram being generated based on reference optical information generated after a reference measurement specimen for leukocyte differential prepared from the normal blood sample is irradiated with light;

[0102] determining a second count result of cells falling within the segmented granulocyte distribution region; and

[0103] Based on the first counting result and the second counting result, it is determined whether to issue an alarm for abnormal increase in band cells in the blood sample to be tested, and / or a counting result of band cells in the blood sample to be tested is determined and output.

[0104] In the first embodiment of the present application, a first count result is first obtained by combining a leukocyte classification scatter plot obtained via the DIFF channel and a leukocyte classification scatter plot obtained via the RET channel. Then, a second count result is obtained based on the actual distribution area of ​​neutrophils in the test blood sample in the first leukocyte classification scatter plot and the reference distribution area of ​​neutrophils in a normal blood sample in the reference leukocyte classification scatter plot. Based on the first and second count results, it is possible to identify whether there is an abnormal increase in band cells in the test blood sample, and to provide an alarm if there is an abnormal increase in band cells. Alternatively, a count result of band cells in the test blood sample can be determined and output based on the first and second count results. This can better assist physicians in diagnosis.

[0105] 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, output an alarm indicating that an abnormal increase in band cells is present 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 cells in the blood sample to be tested.

[0106] 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 cells in the blood sample to be tested:

[0107] 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;

[0108] Determining a first neutrophil counting result of the blood sample to be tested based on the first leukocyte differential scattergram and the second leukocyte differential scattergram;

[0109] Determine the actual distribution area of ​​neutrophils from the first leukocyte differential scatter plot;

[0110] determining the distribution area of ​​segmented granulocytes from the actual distribution area based on a reference distribution area of ​​neutrophils in a reference leukocyte differential scattergram of one or more normal blood samples, the reference leukocyte differential scattergram being generated based on reference optical information generated after a reference measurement specimen for leukocyte differential prepared from the normal blood sample is irradiated with light;

[0111] determining a second count result of cells falling within the segmented granulocyte distribution region; and

[0112] Based on the first counting result and the second counting result, a counting result of band cells in the blood sample to be tested is determined and output.

[0113] In a second embodiment of the present application, when an abnormal increase in band cells is determined in a blood sample to be tested, a first count result is first obtained by combining a leukocyte differential scatter plot obtained via the DIFF channel and a leukocyte differential scatter plot obtained via the RET channel. A second count result is then obtained based on the actual distribution area of ​​neutrophils in the blood sample to be tested in the first leukocyte differential scatter plot and the reference distribution area of ​​neutrophils in a normal blood sample in a reference leukocyte differential scatter plot. Finally, a count result of band cells in the blood sample to be tested is determined and output based on the first and second count results. This can better assist doctors in diagnosis.

[0114] It will be appreciated that the difference between the first embodiment and the second embodiment of the present application lies in whether the data processing device 140 has already determined the presence of abnormal band cell counts in the blood sample to be tested (e.g., the presence of abnormal band cell counts in the blood sample to be tested has been determined through other testing processes) before performing the corresponding operation. If the presence of abnormal band cell counts in the blood sample to be tested has been determined, the data processing device 140 only needs to determine and output the count result of the band cells in the blood sample to be tested, without further performing the operation of issuing an alarm regarding the presence of abnormal band cell counts in the blood sample to be tested.

[0115] To facilitate understanding, some scatter plots are provided below to further illustrate this.

[0116] In the first white blood cell classification scatter plot shown in Figures 3 and 4, there are clear 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 first white blood cell classification scatter plot of the DIFF channel can be used to accurately classify the white blood cells in the blood sample into five categories, 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). The white blood cell count value is equal to the value after subtracting the blood ghost particles from all particles.

[0117] It can be understood that the first leukocyte differential scattergram of the blood sample without abnormal band cell increase in FIG. 3 and FIG. 4 can be used as a reference leukocyte differential scattergram of a normal blood sample.

[0118] In contrast, the first white blood cell differential scatter plots shown in Figures 5 and 6 show no clear demarcation between the lymphocyte (DIFF_Lym) population, the monocyte (DIFF_Mon) population, and the neutrophil (DIFF_Neu) population. In other words, if a blood sample contains an abnormal increase in band cells, it is difficult to accurately determine the lymphocyte (DIFF_Lym), monocyte (DIFF_Mon), and neutrophil (DIFF_Neu) classification results using the first white blood cell differential scatter plot.

[0119] 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.

[0120] It can also be understood that the first leukocyte classification scatter plot is a leukocyte classification scatter plot obtained through the DIFF channel.

[0121] Based on the above description, it can be seen that when the blood sample to be tested has an abnormal increase in band-shaped granulocytes, it is difficult to accurately obtain the neutrophil count result (also referred to as the first count result) of the blood sample to be tested directly based on the first white blood cell classification scatter plot. Furthermore, it is also difficult to directly determine the band-shaped granulocyte count result based on the first white blood cell classification scatter plot.

[0122] Based on this, the embodiment of the present application can accurately determine the first neutrophil count result of the blood sample to be tested based on the first white blood cell classification scatter plot and the second white blood cell classification scatter plot. It should be understood that the first count result can include the neutrophil percentage and / or the neutrophil count value.

[0123] In some implementations, the data processing device 140 can 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, identify white blood cells based on the reticulocyte channel scatter plot, and then generate a second white blood cell differential 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 will be understood that the second white blood cell differential scatter plot is the white blood cell differential scatter plot obtained through the RET channel.

[0124] In the second white blood cell classification scatter plot shown in FIG7 , regardless of whether the blood sample under test has an abnormal increase in band cells, there is a clear boundary between the lymphocyte (RET_Lym) population, the monocyte (RET_Mon) population, and the granulocyte (RET_Gran) population. Here, granulocytes include neutrophils and eosinophils.

[0125] In this case, the percentages of the leukocyte groups can be calculated by the second leukocyte classification scatter plot, namely, the lymphocyte percentage (RET_Lym%), the monocyte percentage (RET_Mon%), and the granulocyte percentage (RET_Gran%).

[0126] In the reticulocyte channel scatter plot shown in Figure 8, 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, parameters such as the optical red blood cell count, optical platelet count, reticulocyte count, low-fluorescence reticulocytes, medium-fluorescence reticulocytes, and high-fluorescence reticulocytes can be determined.

[0127] As can be seen from the above description, regardless of whether the blood sample to be tested has abnormal band cell increase, the data processing device 140 can accurately determine the first neutrophil counting result of the blood sample to be tested based on the first white blood cell classification scattergram and the second white blood cell classification scattergram.

[0128] Some implementations of determining a first neutrophil counting result of a blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram are given below.

[0129] In some implementations, the data processing device 140 may be configured to determine the eosinophil count and the white blood cell count of the blood sample to be tested based on the first white blood cell differential scatter plot, and to determine the granulocyte percentage (i.e., RET_Gran%) of the blood sample to be tested based on the second white blood cell differential scatter plot. Granulocytes include neutrophils and eosinophils. Then, a first neutrophil count result of the blood sample to be tested may be determined based on the eosinophil count, the white blood cell count, and the granulocyte percentage.

[0130] The foregoing description has described how the data processing device 140 accurately obtains the first neutrophil counting result of the blood sample to be tested.

[0131] In order to detect the counting results of band-shaped granulocytes in a blood sample, the data processing device 140 of each embodiment of the present application is further configured to determine the actual distribution area of ​​neutrophils from the first leukocyte classification scattergram, and determine the distribution area of ​​segmented granulocytes 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.

[0132] Here, the reference leukocyte differential scattergram is generated based on reference optical information generated by irradiating a reference measurement sample for leukocyte differential prepared from a normal blood sample. A normal blood sample is a blood sample that does not exhibit abnormal band cell counts. In other words, the reference leukocyte differential scattergram is a leukocyte differential scattergram of a normal blood sample obtained using the DIFF channel.

[0133] After determining the segmented neutrophil distribution area from the actual distribution area of ​​neutrophils in the first leukocyte differential scattergram, the data processing device 140 is further configured to determine a count result (also referred to as a second count result) of cells falling within the segmented neutrophil distribution area. The second count result may include the percentage of cells falling within the segmented neutrophil distribution area relative to the cells within the actual distribution area and / or the count value of cells falling within the segmented neutrophil distribution area.

[0134] Because the majority of neutrophils in normal blood samples are segmented, and the distribution of segmented neutrophils in the leukocyte differential scatter plots in the DIFF channel is similar between different blood samples, a segmented neutrophil distribution region that can approximately represent the distribution of segmented neutrophils can be determined from the actual distribution region based on the reference distribution region of neutrophils in the reference leukocyte differential scatter plots of normal blood samples. In this case, the second count result for cells falling within the segmented neutrophil distribution region can be considered to be the segmented neutrophil count result of the blood sample being tested.

[0135] Therefore, the data processing device 140 can determine the counting result of the band cells 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 within the segmented neutrophil distribution area, and determine whether the blood sample to be tested has a band cell abnormality based on the counting result of the band cells.

[0136] 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 cells in the blood sample to be tested, and determine whether the blood sample to be tested has abnormal band cell increase based on whether the determined band cell counting result is greater than a preset threshold, thereby determining whether to alarm for the abnormal band cell increase in the blood sample to be tested and / or whether to output the counting result of the band cells in the blood sample to be tested.

[0137] For example, the data processing device 140 is configured to output an alarm indicating an abnormal increase in band cells in the blood sample to be tested and / or output the band cell count result 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 not to output an alarm indicating an abnormal increase in band cells in the blood sample to be tested and / or not output the band cell count result in the blood sample to be tested when the difference between the first counting result and the second counting result is not greater than the preset threshold.

[0138] Some embodiments of the data processing device 140 determining 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.

[0139] In some embodiments, the one or more normal blood samples are from the same species as the blood sample to be tested. For example, if the blood sample to be tested is from a cat, the one or more normal blood samples are also from a cat.

[0140] Because the distribution of segmented granulocytes in different blood samples from the same species is more similar in the white blood cell differential scattergram obtained from the DIFF channel, a segmented granulocyte distribution region that more closely represents the distribution of segmented granulocytes can be determined from the actual distribution region based on a reference white blood cell differential scattergram of a normal blood sample from the same species as the test blood sample. In this case, the second count result for cells falling within the segmented granulocyte distribution region can more accurately represent the segmented granulocyte count result, thereby more accurately determining the band cell count result in the test blood sample based on the first and second count results.

[0141] In some implementations, the blood cell analyzer 100 is configured to pre-store reference white blood cell differential scatter plots of a plurality of normal blood samples of different species. For example, these reference white blood cell differential scatter plots may be stored in a data storage device (not shown in FIG. 1 ), or may be directly stored in the data processing device 140 .

[0142] In these implementations, the data processing device 140 can be configured to select reference leukocyte classification scatter plots 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 plots.

[0143] 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, so as 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.

[0144] It is understandable that there are certain differences in the reference distribution areas of neutrophils in different normal blood samples in the reference leukocyte classification scatter plot.

[0145] In the above embodiment, a reference distribution region with the highest shape similarity to the actual distribution region is selected from multiple reference distribution regions of multiple normal blood samples as the final reference distribution region. Based on the final reference distribution region, the segmented granulocyte distribution region is determined from the actual distribution region. In this manner, a segmented granulocyte distribution region that more closely represents the segmented granulocyte distribution can be determined from the actual distribution region. Thus, the second count result for cells falling within the segmented granulocyte distribution region can more accurately represent the segmented granulocyte count result, thereby enabling a more accurate determination of the band cell count result in the blood sample under test based on the first and second count results.

[0146] In some implementations, the first leukocyte differential scattergram and the reference leukocyte differential scattergram each comprise 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 between the reference distribution area and the actual distribution area of ​​each normal blood sample in the plurality of normal blood samples in the following manner.

[0147] First, each reference distribution area is divided 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.

[0148] Taking the reference white blood cell classification scatter plot with fluorescence signal intensity on the vertical axis and side scattered light signal intensity on the horizontal axis as an example, each reference distribution area can be divided into two parts along the horizontal dashed line shown in Figure 9. The fluorescence signal intensity corresponding to the dashed line is the preset fluorescence signal intensity. The part above the dashed line belongs to the first part, and the part below the dashed line belongs to the second part.

[0149] Then, the second part of each reference distribution area is shape-matched with the actual distribution area to select the final reference distribution area.

[0150] 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.

[0151] Because the fluorescence signal intensity of band-shaped granulocytes is generally greater than that of segmented granulocytes, only the second portion of the reference distribution region, where the fluorescence signal intensity is lower, is shape-matched with the actual distribution region. This facilitates accurately selecting, from among multiple reference distribution regions, the reference distribution region with the segmented granulocyte distribution that most closely resembles the segmented granulocyte distribution in the actual distribution region as the final reference distribution region. In this manner, based on the first and second count results, a more accurate determination of the band-shaped granulocyte count in the blood sample to be tested can be made.

[0152] 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.

[0153] First, 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 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.

[0154] For example, in a first white blood cell classification scatterplot with fluorescence signal intensity on the vertical axis and side scattered light signal intensity on the horizontal axis, the actual distribution area can be divided into two parts along a dashed line similar to that in Figure 9 . The fluorescence signal intensity corresponding to the dashed line is the preset fluorescence signal intensity. Similarly, the area above the dashed line belongs to the third part, and the area below the dashed line belongs to the fourth part.

[0155] Then, 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.

[0156] In other words, in these implementations, rather than performing shape matching on the second portion of the reference distribution area with the entire actual distribution area, shape matching is performed on only the second portion of the reference distribution area, where the fluorescence signal intensity is relatively low, with the fourth portion of the actual distribution area. This facilitates more accurately selecting, from among multiple reference distribution areas, the reference distribution area whose distribution of segmented granulocytes most closely resembles that of segmented granulocytes in the actual distribution area as the final reference distribution area. In this way, the count of band-shaped granulocytes in the blood sample to be tested can be more accurately determined based on the first and second count results. Furthermore, this facilitates improving the efficiency of shape matching, allowing for faster determination of the segmented granulocyte distribution area.

[0157] In some embodiments, the preset fluorescence signal intensity is between 90% and 110% of the average of the maximum and minimum fluorescence signal intensities of the reference distribution region. This allows the intervals of fluorescence signal intensities corresponding to the first and second portions to be substantially equivalent, thereby facilitating more accurately selecting, from among the multiple reference distribution regions, the reference distribution region with the most similar distribution of segmented granulocytes to that of the actual distribution region as the final reference distribution region. Furthermore, based on the first and second count results, a more accurate determination of the band cell count result in the blood sample under test can be made.

[0158] 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 in the reference distribution area.

[0159] It is understood that the preset fluorescence signal intensities of the multiple reference distribution regions may be the same or different. In some preferred implementations, the preset fluorescence signal intensities of the multiple reference distribution regions are the same. This eliminates the need to set a corresponding preset fluorescence signal intensity for each reference distribution region, thereby simplifying processing.

[0160] In some embodiments, the data processing device 140 is further configured to, after selecting the final reference distribution area, map the final reference distribution area to the actual distribution area of ​​the first white blood cell differential scattergram, thereby determining the mapped area of ​​the final reference distribution area as the segmented granulocyte distribution area (see FIG10 ). For example, the final reference distribution area can be mapped to the actual distribution area of ​​the first white blood cell differential scattergram according to its position in the corresponding reference white blood cell differential scattergram.

[0161] As shown in FIG11 , the embodiment of the present application further provides a blood cell analysis method 200, comprising:

[0162] S210, drawing a blood sample to be tested;

[0163] 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 white blood cell differentiation, 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;

[0164] S230, 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;

[0165] S240 , 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.

[0166] As some embodiments, step S240 includes the following as shown in FIG11 :

[0167] 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;

[0168] S242, determining a first neutrophil counting result of the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram;

[0169] S243, determining the actual distribution area of ​​neutrophils from the first leukocyte differential scattergram;

[0170] S244, determining a 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 the normal blood sample is irradiated with light;

[0171] S245, determining a second counting result of cells falling within the segmented granulocyte distribution area; and

[0172] S246 , based on the first counting result and the second counting result, determining whether to issue an alarm regarding the 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.

[0173] In some embodiments, in step S246, when the difference between the first count result and the second count result is greater than a preset threshold, an alarm is output indicating an abnormal increase in band cells in the blood sample to be tested. In other embodiments, in step S246, when the difference between the first count result and the second count result is greater than a preset threshold, the difference between the first count result and the second count result is output as the count result of band cells in the blood sample to be tested.

[0174] In other embodiments, when it is determined that there is an abnormal increase in band cells in the blood sample to be tested, step S240 is executed. In this case, referring to the blood cell analysis method 300 shown in FIG12 , step S240 includes:

[0175] 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;

[0176] S242, determining a first neutrophil counting result of the blood sample to be tested based on the first leukocyte classification scattergram and the second leukocyte classification scattergram;

[0177] S243, determining the actual distribution area of ​​neutrophils from the first leukocyte differential scattergram;

[0178] S244, determining a 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 the normal blood sample is irradiated with light;

[0179] S245, determining a second counting result of cells falling within the segmented granulocyte distribution area; and

[0180] S247 , based on the first counting result and the second counting result, determining and outputting a counting result of band-shaped granulocytes in the blood sample to be tested.

[0181] In some embodiments, the one or more normal blood samples and the test blood sample are from the same species.

[0182] In some embodiments, in step S241, the eosinophil count and white blood cell count of the blood sample to be tested are determined based on the first white blood cell classification scatter plot, and the granulocyte percentage of the blood sample to be tested is determined based on the second white blood cell classification scatter plot. Granulocytes include neutrophils and eosinophils. Then, a first counting result is determined based on the eosinophil count, white blood cell count, and granulocyte percentage.

[0183] In some embodiments, in step S244, shape matching is performed on the reference distribution area of ​​each normal blood sample in the plurality of normal blood samples with the actual distribution area, so that a reference distribution area with the highest shape similarity to the actual distribution area is selected from the plurality of reference distribution areas of the plurality of normal blood samples as a final reference distribution area. Then, based on the final reference distribution area, the segmented granulocyte distribution area is determined from the actual distribution area.

[0184] In some implementations, both the first white blood cell differential scattergram and the reference white blood cell differential scattergram are composed of at least fluorescence signal intensity and scattered light signal intensity. In these implementations, each reference distribution region can be divided into a first portion and a second portion, and the second portion of each reference distribution region is shape-matched with the actual distribution region to select a final reference distribution region. Here, the fluorescence signal intensity of any cell within the first portion is no less than a preset fluorescence signal intensity, and the fluorescence signal intensity of any cell within the second portion is no greater than the preset fluorescence signal intensity.

[0185] As some preferred implementations, the actual distribution area can be divided into a third portion and a fourth portion, and the second portion of each reference distribution area is shape-matched with the fourth portion of the actual distribution area to select a final reference distribution area. Here, the fluorescence signal intensity of any cell within the third portion is no less than a preset fluorescence signal intensity, and the fluorescence signal intensity of any cell within the fourth portion is no greater than the preset fluorescence signal intensity.

[0186] 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.

[0187] In some embodiments, the preset fluorescence signal intensities of the multiple reference distribution regions are the same.

[0188] More embodiments and advantages of the blood cell analysis method 200 / 300 proposed in the embodiments of the present application can be found in the above description of the blood cell analyzer 100, which will not be repeated here.

[0189] The features or feature combinations mentioned above in the specification, drawings, and claims may be used in any combination or individually, as long as they are meaningful and not mutually inconsistent within the scope of this application. The advantages and features described with reference to the blood cell analyzer provided in the embodiments of this application apply in a corresponding manner to the blood cell analysis method provided in the embodiments of this application, and vice versa.

[0190] The above description is only a preferred embodiment of the present application and does not limit the patent scope of the present application. All equivalent transformation schemes made by using the contents of the present application description and drawings under the inventive concept of the present application, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A blood cell analyzer, comprising: A sampling device for aspirating a blood sample to be tested; A sample preparation device for mixing a part of the blood sample to be tested, a lysing agent and a first fluorescent staining agent to prepare a first measurement sample for white blood cell classification, and for mixing another part of the blood sample to be tested, a diluent and a second fluorescent staining agent to prepare a second measurement sample for identifying platelets and / or reticulocytes; An optical detection device, including a flow cell, a light source and a light detector, the flow cell for allowing the first measurement sample and the second measurement sample to pass through respectively, the light source for irradiating the first measurement sample and the second measurement sample passing through the flow cell with light, and the light detector for detecting first optical information and second optical information generated after the first measurement sample and the second measurement sample are irradiated by light when passing through the flow cell respectively; And A data processing device configured to: Generate a first white blood cell classification scatter plot based on the first optical information and generate a second white blood cell classification scatter plot based on the second optical information, Determine a first count result of neutrophils in the blood sample to be tested based on the first white blood cell classification scatter plot and the second white blood cell classification scatter plot, Determine the actual distribution area of neutrophils from the first white blood cell classification scatter plot, Based on the reference distribution area of neutrophils in the reference white blood cell classification scatter plot of one or more normal blood samples, determine the segmented neutrophil distribution area from the actual distribution area, the reference white blood cell classification scatter plot being generated based on reference optical information generated after a reference measurement sample for white blood cell classification prepared from a normal blood sample is irradiated by light, Determine a second count result of cells falling within the segmented neutrophil distribution area, and Based on the first count result and the second count result, determine whether to alarm for an abnormal increase in band neutrophils in the blood sample to be tested, and / or determine and output the count result of band neutrophils in the blood sample to be tested.

2. 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 count result and the second count result is greater than a preset threshold, output an alarm for an abnormal increase in band neutrophils in the blood sample to be tested, and / or Output the difference between the first count result and the second count result as the count result of band neutrophils in the blood sample to be tested.

3. A blood cell analyzer, comprising: A sampling device for aspirating a blood sample to be tested; A sample preparation device for mixing a part of the blood sample to be tested, a lysing agent and a first fluorescent staining agent to prepare a first measurement sample for white blood cell classification, and for mixing another part of the blood sample to be tested, a diluent and a second fluorescent staining agent 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. The flow cell is configured to allow a first measurement sample and a second measurement sample to pass through respectively. The light source is configured to irradiate the first measurement sample and the second measurement sample passing through the flow cell with light. The light detector is configured to detect 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: when it is determined that there is an abnormality of increased band neutrophils in the blood sample to be tested, generate a first white blood cell classification scatter plot based on the first optical information and generate a second white blood cell classification scatter plot based on the second optical information, determine a first count result of neutrophils in the blood sample to be tested based on the first white blood cell classification scatter plot and the second white blood cell classification scatter plot, determine an actual distribution area of neutrophils from the first white blood cell classification scatter plot, determine a segmented neutrophil distribution area from the actual distribution area based on a reference distribution area of neutrophils in a reference white blood cell classification scatter plot of one or more normal blood samples. The reference white blood cell classification scatter plot is generated based on reference optical information generated after a reference measurement sample for white blood cell classification prepared from a normal blood sample is irradiated with light, determine a second count result of cells falling within the segmented neutrophil distribution area, and determine and output a count result of band neutrophils in the blood sample to be tested based on the first count result and the second count result.

4. The blood cell analyzer according to any one of claims 1-3, characterized in that, The data processing device is further configured to: perform shape matching with the actual distribution area for the reference distribution area of each normal blood sample among multiple normal blood samples, so as to select a reference distribution area with the highest shape similarity to the actual distribution area from the multiple reference distribution areas of the multiple normal blood samples as the final reference distribution area; and determine the segmented neutrophil distribution area from the actual distribution area based on the final reference distribution area.

5. The blood cell analyzer according to claim 4, wherein, Both the first white blood cell classification scatter plot and the reference white blood cell classification scatter plot are at least composed of fluorescence signal intensity and scattered light signal intensity; The data processing device is further configured to: divide each reference distribution area into a first part and a second part, where 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 perform shape matching between the second part of each reference distribution area and the actual distribution area to select the final reference distribution area.

6. The blood cell analyzer according to claim 5, characterized in that, The data processing device is further configured to: divide the actual distribution area into a third part and a fourth part, where 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 Shape-match the second part of each reference distribution region with the fourth part of the actual distribution region to select the final reference distribution region.

7. The blood cell analyzer according to claim 5 or 6, characterized in that, The preset fluorescence signal intensity is between 90% and 110% of the average of the maximum fluorescence signal intensity and the minimum fluorescence signal intensity in the reference distribution region, and preferably is the average value.

8. The blood cell analyzer according to any one of claims 5-7, characterized in that, The preset fluorescence signal intensities of the plurality of reference distribution regions are the same.

9. The blood cell analyzer according to any one of claims 1-8, characterized in that, The data processing device is further configured to: Based on the first white blood cell classification scatter plot, determine the eosinophil count value and the white blood cell count value of the blood sample to be tested; Based on the second white blood cell classification scatter plot, determine the granulocyte percentage of the blood sample to be tested, where the granulocytes include neutrophils and eosinophils; And Based on the eosinophil count value, the white blood cell count value, and the granulocyte percentage, determine the first counting result.

10. The blood cell analyzer according to any one of claims 1-9, characterized in that, The one or more normal blood samples and the blood sample to be tested are from the same species.

11. A blood cell analysis method, comprising: Aspirate a blood sample to be tested; Mix a part of the blood sample to be tested, a hemolytic agent, and a first fluorescent stain to prepare a first measurement sample for white blood cell classification, and make the particles in the first measurement sample pass through the optically detected area irradiated by light one by one to obtain the first optical information generated by the particles in the first measurement sample after being irradiated by light; Mix another part of the blood sample to be tested, a diluent, and a second fluorescent stain to prepare a second measurement sample for identifying platelets and / or reticulocytes, and make the particles in the second measurement sample pass through the optically detected area irradiated by light one by one to obtain the second optical information generated by the particles in the second measurement sample after being irradiated by light; Generate a first white blood cell classification scatter plot based on the first optical information, and generate a second white blood cell classification scatter plot based on the second optical information; Based on the first white blood cell classification scatter plot and the second white blood cell classification scatter plot, determine the first counting result of neutrophils in the blood sample to be tested; Determine the actual distribution region of neutrophils from the first white blood cell classification scatter plot; Based on the reference distribution region of neutrophils in the reference white blood cell classification scatter plot of one or more normal blood samples, determine the segmented neutrophil distribution region from the actual distribution region, where the reference white blood cell classification scatter plot is generated based on the reference optical information generated after the reference measurement sample for white blood cell classification prepared from the normal blood sample is irradiated by light; Determine the second counting result of the cells falling within the segmented neutrophil distribution region; And Based on the first counting result and the second counting result, determine whether to alarm for the abnormality of increased band neutrophils in the blood sample to be tested, and / or determine and output the counting result of band neutrophils in the blood sample to be tested.

12. The method according to claim 11, wherein Based on the first counting result and the second counting result, determine whether to alarm for an abnormal increase in banded granulocytes in the blood sample to be tested, and / or determine and output the counting result of banded granulocytes in the blood sample to be tested, including: When the difference between the first counting result and the second counting result is greater than a preset threshold, output an alarm for an abnormal increase in banded 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 banded granulocytes in the blood sample to be tested.

13. A blood cell analysis method, including: Aspirate a blood sample to be tested; Mix a part of the blood sample to be tested, a hemolytic agent, and a first fluorescent stain to prepare a first measurement sample for white blood cell classification, and make the particles in the first measurement sample pass through an optically detected area irradiated by light one by one, so as to obtain first optical information generated after the particles in the first measurement sample are irradiated by light; Mix another part of the blood sample to be tested, a diluent, and a second fluorescent stain to prepare a second measurement sample for identifying platelets and / or reticulocytes, and make the particles in the second measurement sample pass through an optically detected area irradiated by light one by one, so as to obtain second optical information generated after the particles in the second measurement sample are irradiated by light; And When it is determined that there is an abnormal increase in banded granulocytes in the blood sample to be tested: Generate a first white blood cell classification scatter plot based on the first optical information, and generate a second white blood cell classification scatter plot based on the second optical information, Based on the first white blood cell classification scatter plot and the second white blood cell classification scatter plot, determine the first counting result of neutrophils in the blood sample to be tested ; Determine the actual distribution area of neutrophils from the first white blood cell classification scatter plot, Based on the reference distribution area of neutrophils in the reference white blood cell classification scatter plots of one or more normal blood samples, determine the segmented neutrophil distribution area from the actual distribution area, and the reference white blood cell classification scatter plots are generated based on reference optical information generated after the reference measurement samples for white blood cell classification prepared from normal blood samples are irradiated by light; Determine the second counting result of the cells falling into the segmented neutrophil distribution area, and Based on the first counting result and the second counting result, determine and output the counting result of banded granulocytes in the blood sample to be tested.

14. The method according to any one of claims 11 - 13, characterized in that Based on the reference distribution area of neutrophils in the reference white blood cell classification scatter plots of one or more normal blood samples, determining the segmented neutrophil distribution area from the actual distribution area includes: For the reference distribution area of each normal blood sample among multiple normal blood samples, respectively perform shape matching with the actual distribution area, so as to select a reference distribution area with the highest shape similarity to the actual distribution area from the multiple reference distribution areas of the multiple normal blood samples as the final reference distribution area; and Based on the final reference distribution region, determine the segmented neutrophil distribution region from the actual distribution region.

15. The method according to claim 14, wherein Both the first white blood cell classification scatter plot and the reference white blood cell classification scatter plot are composed of at least a fluorescence signal intensity and a scattered light signal intensity; For the reference distribution region of each normal blood sample among a plurality of normal blood samples, perform shape matching with the actual distribution region respectively, including: Divide each reference distribution region into a first part and a second part, where 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 Perform shape matching between the second part of each reference distribution region and the actual distribution region to select the final reference distribution region.

16. The method according to claim 15, wherein Performing shape matching between the second part of each reference distribution region and the actual distribution region to select the final reference distribution region includes: Divide the actual distribution region into a third part and a fourth part, where 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 Perform shape matching between the second part of each reference distribution region and the fourth part of the actual distribution region to select the final reference distribution region.

17. The method according to claim 15 or 16, 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 region, and is preferably the average value.

18. The method according to any one of claims 15-17, characterized in that, The preset fluorescence signal intensities of the plurality of reference distribution regions are the same.

19. The method according to any one of claims 11-18, characterized in that, Based on the first white blood cell classification scatter plot and the second white blood cell classification scatter plot, determining a first count result of neutrophils in the blood sample to be tested includes: Based on the first white blood cell classification scatter plot, determine the eosinophil count value and the white blood cell count value of the blood sample to be tested; Based on the second white blood cell classification scatter plot, determine the granulocyte percentage of the blood sample to be tested, where the granulocytes include neutrophils and eosinophils; and Determine the first count result based on the eosinophil count value, the white blood cell count value, and the granulocyte percentage.

20. The method according to any one of claims 11-19, characterized in that The one or more normal blood samples and the blood sample to be tested are from the same species.

21. A blood cell analyzer, comprising: A sampling device for sucking a blood sample to be tested; A sample preparation device for mixing a part of the blood sample to be tested, a hemolytic agent, and a first fluorescent stain to prepare a first measurement sample for white blood cell classification, and for mixing another part of the blood sample to be tested, a diluent, and a second fluorescent stain 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 configured to allow the first measurement sample and the second measurement sample to pass through respectively, the light source is configured to irradiate the first measurement sample and the second measurement sample passing through the flow cell with light, and the light detector is configured to detect 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: based on the first optical information and the second optical information, identify whether there is an abnormality of increased band neutrophils in the blood sample to be tested, and / or give a count result of band neutrophils in the blood sample to be tested.

22. A blood cell analysis method, comprising: aspirating a blood sample to be tested; mixing a part of the blood sample to be tested, a hemolytic agent and a first fluorescent stain to prepare a first measurement sample for white blood cell classification, and causing the particles in the first measurement sample to pass through an optically detected area irradiated with light one by one, so as to obtain first optical information generated after the particles in the first measurement sample are irradiated with light; mixing another part of the blood sample to be tested, a diluent and a second fluorescent stain to prepare a second measurement sample for identifying platelets and / or reticulocytes, and causing the particles in the second measurement sample to pass through an optically detected area irradiated with light one by one, so as to obtain second optical information generated after the particles in the second measurement sample are irradiated with light; and based on the first optical information and the second optical information, identifying whether there is an abnormality of increased band neutrophils in the blood sample to be tested, and / or giving a count result of band neutrophils in the blood sample to be tested.

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