Sample analyzer and sample analysis method

Abstract

A sample analyzer and a sample analysis method, the sample analyzer comprising: a sampling device for collecting a blood sample; a sample preparation device for mixing the blood sample with a hemolytic agent and a dye to prepare a to-be-tested sample liquid; an optical detection device for detecting a scattering light signal and a fluorescence signal generated by particles in the to-be-tested sample liquid after being irradiated by light; a processor for: acquiring the scattering light signal and the fluorescence signal, the scattering light signal at least including a side scattering light signal; generating a scatter plot based on at least the side scattering light signal and the fluorescence signal, acquiring a first predetermined characteristic region and a neutrophil group containing region of the scatter plot; wherein the side scattering light intensity corresponding to the center position of the first predetermined characteristic region is higher than the side scattering light intensity corresponding to the center position of the neutrophil group containing region; obtaining a primitive cell parameter of the blood sample based on the first predetermined characteristic region. The application can accurately measure the primitive cell parameter in the blood sample.

Description

Technical Field

[0001] This application relates to the field of blood analysis technology, and more specifically to a sample analyzer and a sample analysis method. Background Technology

[0002] The main cellular components of blood include platelets, white blood cells, and red blood cells. White blood cells are further divided into lymphocytes, monocytes, neutrophils, eosinophils, and basophils. These cells are generated in the bone marrow, differentiate from immature cells, mature, and then migrate to the peripheral blood. Immature white blood cells, such as blast cells, are not present in the peripheral blood of healthy individuals. However, immature white blood cells can be found in the peripheral blood of patients with leukemia, bone marrow metastases from cancer cells, and severe infections. Therefore, detecting blast cells in peripheral blood is of significant diagnostic value for leukemia. Summary of the Invention

[0003] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. This summary section is not intended to limit the key and essential technical features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0004] A first aspect of the present invention provides a sample analyzer, the sample analyzer comprising:

[0005] Sampling device for collecting blood samples;

[0006] A sample preparation apparatus includes a reaction chamber and a reagent supply unit. The reaction chamber receives a blood sample collected by a sampling device, and the reagent supply unit provides a hemolysin and a dye to the reaction chamber. The blood sample collected by the sampling device is mixed with the hemolysin and dye provided by the reagent supply unit in the reaction chamber to prepare a sample solution for testing.

[0007] An optical detection device includes a light source, a flow chamber, and an optical detector. The light source emits a light beam to illuminate the flow chamber. The flow chamber is connected to a reaction cell, and each particle in the sample solution to be tested can pass through the flow chamber one by one. The optical detector detects the scattered light signal and fluorescence signal generated by the particles passing through the flow chamber after being illuminated.

[0008] A processor configured to perform the following steps: acquiring scattered light signals and fluorescence signals of the sample solution to be tested from the optical detection device, wherein the scattered light signals include at least a side-scattered light signal; generating a scatter plot based at least on the side-scattered light signal and the fluorescence signal, and acquiring a first predetermined feature region and a region containing neutrophils from the scatter plot; wherein the intensity of the side-scattered light corresponding to the center position of the first predetermined feature region is higher than the intensity of the side-scattered light corresponding to the center position of the region containing neutrophils; and obtaining the raw cell parameters of the blood sample based on the first predetermined feature region.

[0009] In one embodiment, the processor is further configured to perform the following steps: acquiring a lymphocyte population region of the scatter plot, wherein the fluorescence intensity corresponding to the center position of the first predetermined feature region is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region.

[0010] In one embodiment, the region containing the neutrophil population is a region containing the leukocyte population, which includes a region containing the lymphocyte population, as well as regions containing the populations of neutrophils, eosinophils, and monocytes.

[0011] In one embodiment, the region containing the neutrophil population is a region containing the neutrophil population.

[0012] In one embodiment, the region containing the neutrophil population is a region containing populations of neutrophils, eosinophils, and monocytes.

[0013] In one embodiment, the original cell parameters include the particle concentration of the original cells, and the processor is further configured to perform the following steps: generating an alarm message when the particle concentration of the original cells exceeds a first preset threshold.

[0014] In one embodiment, the original cell parameters include the ratio of the particle concentration of the original cells to the particle concentration of white blood cells in the blood sample, and the processor is further configured to generate an alarm message when the ratio exceeds a second preset threshold.

[0015] In one embodiment, the processor is further configured to obtain the particle concentration of leukocytes in the blood sample by at least one of the following methods: receiving the particle concentration of leukocytes from an external input, obtaining the particle concentration of leukocytes based on other detection channels, and obtaining the particle concentration of leukocytes based on the scattered light signal and / or the fluorescence signal.

[0016] In one embodiment, the scattered light signal further includes a forward scattered light signal, and the processor is further configured to perform the following steps: obtaining nucleated red blood cell parameters and / or basophil parameters of the blood sample based on the forward scattered light signal and the fluorescence signal.

[0017] In one embodiment, obtaining the nucleated erythrocyte parameters and / or basophil parameters of the blood sample based on the forward-scattered light signal and the fluorescence signal includes: generating a two-dimensional scatter plot based on the forward-scattered light signal and the fluorescence signal, and obtaining the nucleated erythrocyte parameters and / or basophil parameters based on the two-dimensional scatter plot; or, generating a three-dimensional scatter plot based on the forward-scattered light signal, the side-scattered light signal, and the fluorescence signal, obtaining the nucleated erythrocyte parameters and / or basophil parameters based on the three-dimensional scatter plot, and obtaining the original cell parameters.

[0018] In one embodiment, the processor is further configured to perform the following steps: acquiring a second predetermined feature region of the scatter plot, wherein the intensity of lateral scattered light corresponding to the center position of the second predetermined feature region is higher than the intensity of lateral scattered light corresponding to the center position of the region containing neutrophils, and the fluorescence intensity corresponding to the center position of the second predetermined feature region is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region; and obtaining immature granulocyte parameters of the blood sample based on the second predetermined feature region.

[0019] A second aspect of the present invention provides a sample analyzer, the sample analyzer comprising:

[0020] Sampling device for collecting blood samples;

[0021] A sample preparation apparatus includes a reaction chamber and a reagent supply unit. The reaction chamber receives a blood sample collected by a sampling device, and the reagent supply unit provides a hemolysin and a dye to the reaction chamber. The blood sample collected by the sampling device is mixed with the hemolysin and dye provided by the reagent supply unit in the reaction chamber to prepare a test sample solution. The hemolysin is used to dissolve red blood cells, and the dye is used to stain organelles within the blood cells.

[0022] An optical detection device includes a light source, a flow chamber, and an optical detector. The light source emits a light beam to illuminate the flow chamber, which is connected to a reaction cell and allows individual particles in the sample solution to pass through the flow chamber one by one. The optical detector detects the scattered light signal and fluorescence signal generated by the particles passing through the flow chamber after illumination in a single test.

[0023] A processor configured to perform the following steps: acquiring scattered light signals and fluorescence signals of the sample solution to be tested from the optical detection device, the scattered light signals including forward scattered light signals and side scattered light signals; obtaining raw cell parameters of the blood sample based on the side scattered light signals and the fluorescence signals; and obtaining nucleated erythrocyte parameters and / or basophil parameters of the blood sample based on the forward scattered light signals and the fluorescence signals.

[0024] In one embodiment, obtaining the raw cell parameters of the blood sample based on the side-scattered light signal and the fluorescence signal includes: generating a scatter plot based on the side-scattered light signal and the fluorescence signal; obtaining a predetermined feature region and a region containing neutrophils from the scatter plot; wherein the intensity of the side-scattered light corresponding to the center position of the predetermined feature region is higher than the intensity of the side-scattered light corresponding to the center position of the region containing neutrophils; and obtaining the raw cell parameters of the blood sample based on the predetermined feature region.

[0025] In one embodiment, obtaining the raw cell parameters of the blood sample based on the side-scattered light signal and the fluorescence signal includes: generating a first two-dimensional scatter plot based on the side-scattered light signal and the fluorescence signal, and obtaining the raw cell parameters based on the first two-dimensional scatter plot; obtaining the nucleated erythrocyte parameters and / or basophil parameters of the blood sample based on the forward-scattered light signal and the fluorescence signal includes: generating a second two-dimensional scatter plot based on the forward-scattered light signal and the fluorescence signal, and obtaining the nucleated erythrocyte parameters and / or basophil parameters based on the second two-dimensional scatter plot.

[0026] In one embodiment, obtaining the raw cell parameters of the blood sample based on the side-scattered light signal and the fluorescence signal, and obtaining the nucleated erythrocyte parameters and / or basophil parameters of the blood sample based on the forward-scattered light signal and the fluorescence signal, includes: generating a three-dimensional scatter plot based on the forward-scattered light signal, the side-scattered light signal, and the fluorescence signal; obtaining the nucleated erythrocyte parameters and / or basophil parameters based on the three-dimensional scatter plot; and obtaining the raw cell parameters.

[0027] A third aspect of this invention provides a sample analysis method, the method comprising: acquiring a blood sample and mixing the blood sample with a hemolysin and a dye to prepare a test sample solution; detecting the scattered light signal and fluorescence signal generated by particles in the test sample solution after being irradiated by light; acquiring the scattered light signal and fluorescence signal of the test sample solution, wherein the scattered light signal includes at least a side-scattered light signal; generating a scatter plot based at least on the side-scattered light signal and the fluorescence signal, and acquiring a first predetermined feature region and a region containing neutrophils in the scatter plot; wherein the intensity of the side-scattered light corresponding to the center position of the first predetermined feature region is higher than the intensity of the side-scattered light corresponding to the center position of the region containing neutrophils; and obtaining the original cell parameters of the blood sample based on the first predetermined feature region.

[0028] In one embodiment, the method further includes: obtaining the lymphocyte population region of the scatter plot, wherein the fluorescence intensity corresponding to the center position of the first predetermined feature region is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region.

[0029] In one embodiment, the parameters of the original cell include the particle concentration of the original cell, and the method further includes generating an alarm message when the particle concentration of the original cell exceeds a first preset threshold.

[0030] In one embodiment, the parameters of the original cells include the ratio of the particle concentration of the original cells to the particle concentration of the white blood cells in the blood sample, and the method further includes generating an alarm message when the ratio exceeds a second preset threshold.

[0031] A fourth aspect of this invention provides a sample analysis method, the method comprising: acquiring a blood sample and mixing the blood sample with a hemolysin and a dye to prepare a test sample solution, wherein the hemolysin is used to dissolve red blood cells, and the dye is used to stain organelles in the blood cells; detecting, in a single test, the scattered light signal and fluorescence signal generated by particles in the test sample solution after being irradiated by light; acquiring the scattered light signal and fluorescence signal of the test sample solution, wherein the scattered light signal includes at least a forward scattered light signal and a side scattered light signal; obtaining the original cell parameters of the blood sample based on the side scattered light signal and the fluorescence signal; and obtaining the nucleated red blood cell parameters and / or basophil parameters of the blood sample based on the forward scattered light signal and the fluorescence signal.

[0032] The sample analyzer and sample analysis method of this invention generate a scatter plot based on side-scattered light signals and fluorescence signals. By analyzing the first predetermined feature region of the scatter plot, the original cell parameters of the blood sample can be accurately obtained. Attached Figure Description

[0033] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of the invention in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of the invention and form part of the specification. They are used together with the embodiments of the invention to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0034] Figure 1 A structural block diagram of a sample analyzer according to an embodiment of the present invention is shown;

[0035] Figure 2 A two-dimensional scatter plot of a blood sample containing primitive cells is shown according to an embodiment of the present invention;

[0036] Figure 3 A two-dimensional scatter plot of a normal blood sample according to an embodiment of the present invention is shown;

[0037] Figure 4 A two-dimensional scatter plot of a blood sample exhibiting PLT aggregation according to an embodiment of the present invention is shown.

[0038] Figure 5 A two-dimensional scatter plot of a blood sample with highly immature granulocytes according to an embodiment of the present invention is shown;

[0039] Figure 6 This illustrates a two-dimensional scatter plot generated based on forward-scattered light signals and fluorescence signals according to an embodiment of the present invention;

[0040] Figure 7 A three-dimensional scatter plot based on forward-scattered light signals, side-scattered light signals, and fluorescence signals is shown according to an embodiment of the present invention.

[0041] Figure 8 A comparison graph showing the original cell parameters obtained by the sample analysis instrument according to an embodiment of the present invention with reference values ​​of the original cell parameters is shown.

[0042] Figure 9 A schematic flowchart illustrating a sample analysis method according to an embodiment of the present invention is shown;

[0043] Figure 10 A structural block diagram of a sample analyzer according to another embodiment of the present invention is shown;

[0044] Figure 11 A schematic flowchart illustrating a sample analysis method according to another embodiment of the present invention is shown. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this application more apparent, exemplary embodiments according to this application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely a part of the embodiments of this application, and not all of the embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein. Based on the embodiments of the present invention described in this application, all other embodiments obtained by those skilled in the art without inventive effort should fall within the protection scope of this application.

[0046] The following description provides numerous specific details to offer a more thorough understanding of this application. However, it will be apparent to those skilled in the art that this application can be practiced without one or more of these details. In other instances, certain technical features well-known in the art have not been described to avoid confusion with this application.

[0047] It should be understood that this application can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. Rather, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of this application to those skilled in the art.

[0048] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising” and / or “including,” when used in this specification, identify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0049] To fully understand this application, a detailed structure will be presented in the following description to illustrate the technical solution proposed in this application. Optional embodiments of this application are described in detail below; however, in addition to these detailed descriptions, this application may have other implementation methods.

[0050] One method for detecting primitive cell parameters involves generating a first scatter plot based on forward-scattered and side-scattered light signals, and obtaining a first cell population within a predetermined region of the first scatter plot. A second scatter plot is then generated based on the forward-scattered and fluorescence signals, and a second cell population is obtained within a predetermined region of the second scatter plot. Cells belonging to both the first and second cell populations are considered primitive cells. This method requires simultaneous detection of three light signals, resulting in high costs. Furthermore, in cases of severe platelet (PLT) aggregation, the large number of PLT clusters can generate very high forward-scattered light, potentially contaminating both the first and second cell populations with aggregated PLT cells, leading to inaccurate measurements of primitive cell parameters.

[0051] To accurately measure primitive cell parameters, this invention proposes a sample analyzer and a sample analysis method that measure primitive cell parameters based on side-scattered light signals and forward-scattered light signals. First, referring to… Figure 1 To describe the sample analyzer according to embodiments of the present invention, Figure 1 A structural block diagram of a sample analyzer 100 according to one embodiment of this application is shown. Figure 1 As shown, the sample analyzer 100 includes at least a sampling device 110, a sample preparation device 120, an optical detection device 130, and a processor 140. Furthermore, the sample analyzer 100 may also include a display device for displaying the sample analysis results obtained by the processor 140.

[0052] The sampling device 110 is used to collect blood samples. Exemplarily, the sampling device 110 has a suction tube (e.g., a sampling needle) with a suction nozzle and a driving unit for driving the suction tube to quantitatively draw the blood sample to be tested through the suction nozzle. For example, the sampling needle moves under the drive of the driving unit to draw the blood sample to be tested from a sample container containing the blood sample.

[0053] The sample preparation apparatus 120 has at least one reaction chamber and a reagent supply unit, wherein the reaction chamber is used to receive blood samples collected by the sampling device, and the reagent supply unit provides hemolysin and dye to the reaction chamber, so that the blood sample collected by the sampling device is mixed with the hemolysin and dye provided by the reagent supply unit in the reaction chamber to prepare a sample solution to be tested.

[0054] For example, the hemolytic agent includes a surfactant selected from at least one of cationic and nonionic surfactants. The hemolytic agent can cause micro-damage to the cell membranes of leukocytes and primitive cells, creating pores that facilitate staining with dye. Leukocytes include basophils, lymphocytes, etc., and different cell types have different cellular characteristics. After actual treatment, the degree of cell membrane damage varies, resulting in different amounts of dye entering the cell. Furthermore, the organelles differ in size between different cell types. Therefore, the dye binding to different types of leukocytes also differs, leading to different light signals produced by different types of leukocytes. The hemolytic agent can also dissolve and destroy red blood cells and platelets in the blood sample. Some incompletely destroyed red blood cells also form red blood cell shadows, which have little impact on subsequent scattered light and fluorescence signals.

[0055] The dyes in this invention can specifically bind to organelles within cells; this binding is also known as staining. After staining, cells irradiated with light of a specific wavelength will produce varying levels of fluorescence signals depending on the degree of dye binding. Different cell types possess different cell structures and volumes, and their size changes to varying degrees after reacting with reagents, resulting in different levels of scattered light signals. Side-scattered light signals primarily reflect differences in intracellular morphology or complexity, fluorescence signals primarily reflect differences in the dye-binding ability of different cells, and forward-scattered light signals primarily reflect differences in cell size.

[0056] An optical detection device 130 is used to detect a sample solution prepared by a sample preparation device 120 to obtain an optical signal. In some embodiments, the optical detection device 130 includes a light source, a flow chamber, and an optical detector. The light source emits a light beam to illuminate the flow chamber, which is connected to a reaction cell, and each particle in the sample solution can pass through the flow chamber one by one. The optical detector is used to detect the scattered light signal and fluorescence signal generated by the particles passing through the flow chamber after being illuminated. Exemplarily, the optical detection device has a light source, a beam shaping assembly, and a flow chamber arranged sequentially in a straight line. A dichroic mirror is obliquely arranged on one side of the flow chamber. A portion of the lateral light emitted by the cells in the flow chamber passes through the dichroic mirror and is captured by a fluorescence detector obliquely arranged behind the dichroic mirror, thereby obtaining a fluorescence signal. Another portion of the lateral light is reflected by the dichroic mirror and captured by a lateral scattering light detector obliquely arranged in front of the dichroic mirror, thereby obtaining a lateral scattering light signal. Optionally, the optical detection apparatus also includes a forward photodetector arranged in a straight line with the light source, beam shaping assembly and flow chamber for capturing forward scattered light signals.

[0057] The processor 140 is configured to perform the following steps: acquiring scattered light and fluorescence signals from the optical detection device 130, wherein the scattered light signals include at least a side-scattered light signal; generating a scatter plot based at least on the side-scattered light signal and the fluorescence signal, and acquiring a first predetermined feature region and a region containing neutrophils (NEU) from the scatter plot; wherein the intensity of the side-scattered light corresponding to the center position of the first predetermined feature region is higher than the intensity of the side-scattered light corresponding to the center position of the region containing neutrophils; and obtaining blast cell parameters of the blood sample based on the first predetermined feature region. Further, the processor 140 is also configured to control a display device to display the obtained blast cell parameters.

[0058] In some embodiments, the processor 140 includes at least a processing component, RAM, ROM, a communication interface, a memory, and an I / O interface. The processing component, RAM, ROM, communication interface, memory, and I / O interface communicate via a bus. The processing component can be a CPU, GPU, or other chip with computing power. The memory stores various computer programs, such as operating systems and application programs, for the processor component to execute, as well as the data required to execute these computer programs. Additionally, during sample analysis, any data requiring local storage can be stored in the memory. The I / O interface consists of serial interfaces such as USB, IEEE 1394, or RS-232C; parallel interfaces such as SCSI, IDE, or IEEE 1284; and analog signal interfaces such as D / A converters and A / D converters. Input devices, such as keyboards, mice, touchscreens, or other control buttons, can be connected to the I / O interface, allowing users to directly input data into the processor 140. Furthermore, a display device with display capabilities, such as an LCD screen, touchscreen, or LED display, can also be connected to the I / O interface. The processor 140 can output the processed data as image display data to a display device for display, such as sample analysis data, instrument operating parameters, etc. The communication interface can be any known communication protocol. The communication interface communicates with the outside world via a network. The processor 140 can transmit data with any device connected to the network via the communication interface using a specific communication protocol.

[0059] The processor 140 receives the side-scattered light signal and fluorescence signal output by the optical detection device 130, and uses the side-scattered light signal and fluorescence signal of each particle as a characteristic data set to characterize that particle. Through analysis and processing of the particle characteristic data, the blood sample is analyzed. Specifically, the processor 140 generates the required scatter plot based on the characteristic data set of each particle, and detects the original cell parameters based on the scatter plot. For example, the processor 140 can count the number of original cell particles within a predetermined characteristic region, thereby obtaining the particle concentration of the original cells.

[0060] A scatter plot is a collection of characteristic data sets of individual cells and particles. It can be a two-dimensional scatter plot or a three-dimensional scatter plot plotted using forward-scattered light. Cells mapped onto the scatter plot are called particles. Cells of the same type tend to cluster together in the scatter plot due to their similar optical signal characteristics, forming a particle swarm. Scatter plots can be presented not as a graph, but as a data array of optical signal values ​​(e.g., a two-dimensional data array). The following description uses a graphical scatter plot as an example. Figures 2 to 5 An exemplary two-dimensional scatter plot generated by processor 140 based on fluorescence intensity information and side-scatter light intensity information of each cell is shown.

[0061] The applicant discovered through research that a first predetermined characteristic region exists in the scatter plot generated based on side-scattered light signals and fluorescence signals. If primitive cells are present in the blood sample, the particle swarm of primitive cells stably appears within this first predetermined characteristic region. The intensity of side-scattered light corresponding to the center position of the first predetermined characteristic region is higher than the intensity of side-scattered light corresponding to the center position of the region containing neutrophil swarms. The reason for this may be that when the blood sample reacts with the hemolysin and dye, the hemolysin mainly destroys the cytoplasm of the primitive cells, while maintaining the original state of the organelles. The dye used in this embodiment of the invention mainly stains organelles. Since primitive cells are relatively immature cells, the proportion of organelles in primitive cells is greater than that in neutrophils. Therefore, the intensity of the side-scattered light signal generated by primitive cells is greater than that generated by neutrophils.

[0062] Since the location of the neutrophil population region is relatively stable, in this embodiment of the invention, the location of the first predetermined feature region is described using the region containing the neutrophil population as a reference. In one embodiment, the region containing the neutrophil population can be a region with a single neutrophil population, and the processor 140 can obtain the neutrophil parameters of the blood sample based on this region.

[0063] Optionally, the region containing the neutrophil population may also include other cell populations besides neutrophils. In one embodiment, the region containing the neutrophil population may be a region containing white blood cells (WBCs), referring to a region of normal white blood cells, specifically including a region containing lymphocytes (LYMs), as well as regions containing neutrophils, eosinophils (EOS), and monocytes (MONs). In another embodiment, the region containing the neutrophil population is a region containing neutrophils, eosinophils, and monocytes, but does not include a region containing lymphocytes. Figures 2 to 5 The region shown contains a population of neutrophils, eosinophils, and monocytes.

[0064] See Figure 2 , Figure 3 In a fluorescence-side-scatter scatter plot, the first predetermined characteristic region is located above the region containing the neutrophil population. It is understood that the scatter plot generated from the fluorescence signal and the side-scatter signal can also be a side-scatter-fluorescence scatter plot, in which the first predetermined characteristic region would be located to the right of the region containing the neutrophil population. The first predetermined characteristic region can be elliptical, circular, rectangular, or other suitable shapes.

[0065] In such Figure 2 , Figure 3 In the example shown, the fluorescence intensity corresponding to the center of the first predetermined feature region is lower than the fluorescence intensity corresponding to the center of the neutrophil population region. However, in other embodiments, if the reagents or lighting conditions change, the fluorescence intensity corresponding to the center of the first predetermined feature region may be higher than the fluorescence intensity corresponding to the center of the region containing the neutrophil population.

[0066] In one embodiment, the location and size of the first predetermined feature region can be fixed, i.e., the intensity of its corresponding fluorescence signal and the intensity of its side-scattered light signal are predetermined. In some embodiments, the fluorescence signal and side-scattered light signal of a normal blood sample without primitive cells and an abnormal blood sample containing primitive cells can be measured separately in the same detection system, and a scatter plot can be generated. By comparing the two scatter plots, a certain region will be found above the region containing neutrophil populations (taking the fluorescence-side-scattered light scatter plot as an example). Particle populations appear in this region of the abnormal blood sample, while no particle populations appear in this region of the normal blood sample, thereby identifying this region as the predetermined feature region.

[0067] In another embodiment, the position and size of the first predetermined feature region can also be floating. For example, the position of the first predetermined feature region can be dynamically adjusted according to certain rules based on the position of the neutrophil-containing region in the scatter plot. In this embodiment, after generating the scatter plot, the processor 140 needs to determine the first predetermined feature region in the scatter plot based at least on the neutrophil-containing region, and then obtain the original cell parameters based on the first predetermined feature region. Exemplarily, in addition to the neutrophil-containing region, the processor 140 can also determine the position and size of the first predetermined feature region based on the regions of other cell populations in the scatter plot.

[0068] In some embodiments, the processor 140 is further configured to acquire a lymphocyte population region for a scatter plot, wherein the fluorescence intensity corresponding to the center of the first predetermined characteristic region is higher than the fluorescence intensity corresponding to the center of the lymphocyte population region. The processor 140 can determine the location of the first predetermined characteristic region based on both the lymphocyte population region and the region containing neutrophils. (Continuing to refer to...) Figure 2In the fluorescence-lateral scattering scatter plot, the lymphocyte population region is located to the left of the first predetermined characteristic region. In, for example... Figure 2 In the example shown, the intensity of lateral scattered light corresponding to the center position of the first predetermined feature region is higher than the intensity of lateral scattered light corresponding to the center position of the lymphocyte population region. In other embodiments, the intensity of lateral scattered light corresponding to the center position of the first predetermined feature region may also be lower than the intensity of lateral scattered light corresponding to the center position of the lymphocyte population region.

[0069] See also Figure 2 , Figure 3 ,in Figure 2 A fluorescence-side scattering scatter plot of a blood sample containing primitive cells. Figure 3 This is a fluorescence-side scatter plot of a normal blood sample. (Comparison) Figure 2 and Figure 3 For normal blood samples, no particle clusters appeared in the first predetermined feature region. For blood samples containing primitive cells, particle clusters with primitive cells appeared in the first predetermined feature region. It can be seen that analyzing the scatter points in the first predetermined feature region can obtain the primitive cell parameters.

[0070] Further, see Figure 4 , Figure 4 A fluorescence-lateral scattering scatter plot of blood samples showing PLT aggregation is shown. Figure 4 As can be seen, since the original cell parameters are obtained from the scatter plot generated by the fluorescence signal and the side-scattered light signal in the embodiments of the present invention, the PLT aggregation region does not overlap with the first predetermined feature region. Therefore, the PLT aggregation will not affect the measurement results of the original cell parameters.

[0071] Since primitive cells do not appear in normal peripheral blood samples, in a further embodiment, the processor 140 can also determine whether to generate a primitive cell positive alarm message based on the detected primitive cell parameters. The alarm message includes, but is not limited to, alarm messages in the form of text, sound, light, or pop-up windows.

[0072] In one embodiment, the processor 140 can determine whether to generate an alarm message based on the particle concentration of the original cells. Specifically, the processor 140 is configured to perform the following steps: generating an alarm message when the particle concentration of the original cells exceeds a first preset threshold. The first preset threshold may be an empirical value obtained from experimental statistics, but it is understood that the first preset threshold can be adjusted according to actual circumstances.

[0073] In another embodiment, the processor 140 can also determine whether to generate an alarm message based on the ratio of the particle concentration of the original cells to the particle concentration of white blood cells in the blood sample. Specifically, the processor 140 is configured to perform the following steps: generating an alarm message when the ratio of the particle concentration of the original cells to the particle concentration of white blood cells exceeds a second preset threshold. The second preset threshold can be an empirical value obtained from experimental statistics, or it can be adjusted according to actual conditions.

[0074] The white blood cell particle concentration refers to the white blood cell particle concentration of the same blood sample used to detect the original cell parameters. The processor 140 can receive the externally input white blood cell particle concentration and can obtain the white blood cell particle concentration based on other detection channels of the sample analyzer, including but not limited to the white blood cell classification channel (DIFF). The processor 140 can also simultaneously obtain the particle concentration of the original cell parameters and the particle concentration of the white blood cell parameters through the same detection channel. That is, after obtaining the scattered light signal and the fluorescence signal, a scatter plot can be generated based on the scattered light signal and the fluorescence signal, and the white blood cell particle concentration can be obtained based on the scatter plot. This same detection channel can be the WNB (white blood cell, basophil, and nucleated red blood cell) channel.

[0075] Reference Figure 4 In this embodiment of the invention, although the first predetermined feature region does not contain PLT particle clusters and will not affect the detection results of the original cell parameters, PLT particle clusters may affect the detection results of white blood cell parameters. PLT is part of the blood shadow, which is a cell fragment structure formed after the cell membrane of red blood cells or platelets in a blood sample is ruptured due to low osmotic pressure or reagent treatment. PLT aggregation can occur in some samples, interfering with the detection of white blood cells. Therefore, when calculating the ratio of the particle concentration of the original cells to the particle concentration of white blood cells in the blood sample, if the processor 140 obtains the particle concentration of white blood cells based on the same detection channel or other detection channels, it is necessary to remove the interference caused by PLT aggregation on the measurement of white blood cell ion parameters.

[0076] Research has found that particles passing through the detection area generate a pulse, and the pulse width reflects the time it takes for the particle to pass through the detection area, thus characterizing the particle size. At a constant flow rate, smaller particles take less time to pass through the detection area, resulting in a smaller pulse width; larger particles take longer to pass through the detection area, resulting in a larger pulse width. In samples with platelet aggregation, the pulse width generated by aggregated particles passing through the detection area is relatively large. Theoretically, the pulse width can distinguish between platelet aggregation particles and leukocytes. However, due to the varying number of aggregated platelets and the wide size distribution of platelet clusters, some larger platelet aggregation particles may overlap with leukocyte clusters. Therefore, pulse width alone cannot effectively distinguish between leukocytes and platelet aggregation particles. Therefore, in this embodiment of the invention, based on the difference in pulse width between interfering particles and leukocyte particles, a new enhanced signal is formed by combining the optical signal and the pulse width signal. The significant difference in the enhanced signal between leukocyte particles and platelet particles allows for the differentiation between them.

[0077] Specifically, firstly, the pulse width of at least one optical signal is acquired, and an enhanced signal is obtained based on its pulse width and the combined optical signal. The combined optical signal can be selected from any optical signal, and this combination calculation increases the difference between leukocyte particles and interfering particles in the enhanced signal compared to the difference between the two in the combined optical signal. The optical signal used to calculate the pulse width and the combined optical signal can be the same optical signal or different optical signals. Then, a new scatter plot is constructed based on the enhanced signal and other signals. The other signals can be at least one optical signal different from the combined optical signal, or other enhanced signals. Leukocyte particles and interfering particles are distinguished based on the new scatter plot. Since the enhanced signal increases the difference between leukocyte particles and interfering particles in the enhanced signal compared to the difference between the two in the combined optical signal, leukocyte particles and interfering particles can be distinguished on the scatter plot based at least on the enhanced signal.

[0078] For example, an enhanced signal can be obtained based on the fluorescence signal and the pulse width signal. A new scatter plot can be formed based on the enhanced signal and the forward scattered light signal or the side scattered light signal to distinguish leukocyte particles and platelet aggregates. The pulse width signal can be any one of the fluorescence signal, the forward scattered light signal, and the side scattered light signal.

[0079] Alternatively, an enhanced signal can be obtained based on the forward-scattered light signal and the pulse width signal. A new scatter plot can be formed based on the enhanced signal and the side-scattered light signal or the fluorescence signal to distinguish between leukocyte particles and platelet aggregates. The pulse width signal can be any of the following: fluorescence signal, forward-scattered light signal, and side-scattered light signal.

[0080] Alternatively, an enhanced signal can be obtained based on the side-scattered light signal and the pulse width signal. A new scatter plot can be formed based on the enhanced signal and the forward-scattered light signal or the fluorescence signal to distinguish between leukocyte particles and platelet aggregates. The pulse width signal can be any of the following: fluorescence signal, forward-scattered light signal, and side-scattered light signal.

[0081] After obtaining the particle concentrations of leukocytes and primitive cells, processor 140 calculates the ratio of the particle concentration of primitive cells to the particle concentration of leukocytes. For example, the particle concentration of leukocytes is denoted as WBC_Count, and the particle concentration of primitive cells is denoted as Blast_Count. The percentage of the particle concentration of primitive cells to the particle concentration of leukocytes, Blast%, is then:

[0082]

[0083] When Blast% exceeds the second preset threshold, the processor 140 generates an alarm message.

[0084] In addition to the parameters of the original cells, the sample analyzer 100 of this embodiment can also simultaneously detect the parameters of other cells. Furthermore, the sample analyzer 100 of this embodiment can obtain the parameters of the original cells and other cells in a single test through the same detection channel. In one embodiment, the processor 140 can obtain the forward-scattered light signal collected by the optical detection device 130, and obtain the nucleated red blood cell (NRBC) parameters and basophil (BASO) parameters of the blood sample based on the forward-scattered light signal and fluorescence signal, or simultaneously obtain the nucleated red blood cell parameters and basophil parameters. Nucleated red blood cells, also known as immature red blood cells, are normally present in the bone marrow. Peripheral blood samples from normal individuals do not contain nucleated red blood cells. The presence of nucleated red blood cells in blood samples is due to the release of immature bone marrow erythroid cells into the blood sample. Simultaneous detection of nucleated red blood cell parameters and original cell parameters is beneficial for comprehensive analysis of both.

[0085] For example, such as Figure 6 As shown, the processor 140 can generate a two-dimensional scatter plot based on forward-scattered light signals and fluorescence signals, and obtain nucleated erythrocyte parameters and basophil parameters based on the two-dimensional scatter plot. Specifically, the processor 140 can obtain nucleated erythrocyte parameters of a blood sample based on the nucleated erythrocyte population region in the two-dimensional scatter plot, and obtain basophil parameters of a blood sample based on the basophil population region in the two-dimensional scatter plot. The basophil population region is located within the leukocyte population region; because the nuclei of nucleated erythrocytes undergo condensation after reagent treatment, the amount of fluorescent dye bound is less, resulting in a lower fluorescence signal. Therefore, the fluorescence intensity corresponding to the center of the nucleated erythrocyte population region is lower than the fluorescence intensity corresponding to the center of the leukocyte population region.

[0086] Alternatively, processor 140 can generate a three-dimensional scatter plot based on forward-scattered light signals, side-scattered light signals, and fluorescence signals, and obtain nucleated erythrocyte parameters, basophil parameters, and primitive cell parameters from the three-dimensional scatter plot. See also Figure 7 The processor 140 can obtain nucleated red blood cell parameters of a blood sample based on the nucleated red blood cell population region in the three-dimensional scatter plot, obtain basophil parameters of a blood sample based on the basophil population region in the three-dimensional scatter plot, and obtain raw cell parameters of a blood sample based on a first predetermined feature region in the three-dimensional scatter plot.

[0087] In some embodiments, the processor 140 can acquire both raw cell parameters and immature granulocyte parameters of the blood sample in the same test. Immature granulocytes are also immature white blood cells, and simultaneously detecting immature granulocyte parameters and raw cell parameters facilitates comprehensive analysis of both. Specifically, the processor 140 is configured to acquire a second predetermined feature region of a scatter plot and obtain the immature granulocyte parameters of the blood sample based on the second predetermined feature region. (Refer to...) Figure 2 The intensity of the lateral scattered light corresponding to the center position of the second predetermined feature region is higher than the intensity of the lateral scattered light corresponding to the center position of the region containing neutrophils, and the fluorescence intensity corresponding to the center position of the second predetermined feature region is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region.

[0088] Similarly, the position and size of the second predetermined feature region can be fixed, meaning that the intensity of its corresponding fluorescence signal and the intensity of its side-scattered light signal are predetermined. Alternatively, the position and size of the second predetermined feature region can also be floating; for example, the position of the second predetermined feature region can be dynamically adjusted according to certain rules based on the positions of the neutrophil population region and the lymphocyte population region in the scatter plot.

[0089] In some embodiments, the processor 140 may also generate an alarm message when the particle concentration of immature granulocytes exceeds a third preset threshold, or when the ratio of the particle concentration of immature granulocytes to the particle concentration of white blood cells exceeds a fourth preset threshold.

[0090] To further confirm the effectiveness of the sample analyzer provided in this embodiment of the invention in detecting raw cell parameters, more than 50 blood samples were randomly selected and the following tests were performed:

[0091] 1. Each blood sample is tested using the sample analyzer of this embodiment of the invention to obtain the ratio (Blast%) of the particle concentration of the original cells to the particle concentration of the white blood cells in each blood sample.

[0092] 2. Manually examine the blast cells under a microscope, analyze each blood sample individually, and manually count at least 100 white blood cells. Record the white blood cell count as WBC_Total_Manual. Obtain the number of blast cells among all counted white blood cells in each blood sample, recorded as Blast_num_Manual. Then, obtain a reference value for the blast cell percentage (i.e., the ratio of blast cell count to white blood cell count), recorded as Blast%_Manual. Where:

[0093]

[0094] The results of the comparative analysis of the measured value of the primitive cell proportion with the reference value of the primitive cell proportion are as follows: Figure 8 As shown. The proportion of primitive cells measured by the sample analyzer provided in this embodiment of the invention has a good correlation with the proportion of primitive cells obtained manually under a microscope, with a correlation coefficient of 0.95. That is, the sample analyzer of this embodiment of the invention can accurately measure the proportion of primitive cells in blood samples.

[0095] The sample analyzer 100 of this invention generates a scatter plot based on side-scattered light signals and fluorescence signals. By analyzing the first predetermined feature region of the scatter plot, the original cell parameters of the blood sample can be accurately obtained.

[0096] refer to Figure 9 This invention also provides a sample analysis method 900, comprising the following steps:

[0097] In step S910, a blood sample is obtained and the blood sample is mixed with a hemolysin and a dye to prepare a test sample solution;

[0098] In step S920, the scattered light signal and fluorescence signal generated by the particles in the sample solution to be tested after being irradiated by light are detected;

[0099] In step S930, the scattered light signal and fluorescence signal of the sample liquid to be tested are acquired, wherein the scattered light signal includes at least the side-scattered light signal;

[0100] In step S940, a scatter plot is generated based at least on the side-scattered light signal and the fluorescence signal, and a first predetermined feature region and a region containing neutrophil populations are obtained from the scatter plot.

[0101] In step S950, the raw cell parameters of the blood sample are obtained based on the first predetermined feature region.

[0102] In one embodiment, the lymphocyte population region of the scatter plot is obtained, and the fluorescence intensity corresponding to the center position of the first predetermined feature region is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region.

[0103] For example, the region containing the neutrophil population is a region containing the leukocyte population, which includes a region containing the lymphocyte population, as well as regions containing populations of neutrophils, eosinophils, and monocytes. The region containing the neutrophil population can also be a region containing only the neutrophil population. Alternatively, the region containing the neutrophil population can be a region containing populations of neutrophils, eosinophils, and monocytes.

[0104] In one embodiment, the original cell parameters include the particle concentration of the original cells, and the method further includes generating an alarm message when the particle concentration of the original cells exceeds a first preset threshold. The original cell parameters may also include the ratio of the particle concentration of the original cells to the particle concentration of white blood cells in the blood sample, and the method further includes generating an alarm message when the ratio exceeds a second preset threshold.

[0105] The particle concentration of white blood cells in a blood sample can be obtained by at least one of the following methods: receiving the particle concentration of white blood cells from an external input, obtaining the particle concentration of white blood cells based on other detection channels of a sample analyzer, and obtaining the particle concentration of white blood cells based on the scattered light signal and / or the fluorescence signal.

[0106] In one embodiment, the scattered light signal further includes a forward scattered light signal, and the method further includes: obtaining nucleated red blood cell parameters and / or basophil parameters of the blood sample based on the forward scattered light signal and the fluorescence signal.

[0107] Specifically, obtaining the nucleated erythrocyte parameters and / or basophil parameters of the blood sample based on the forward-scattered light signal and the fluorescence signal includes: generating a two-dimensional scatter plot based on the forward-scattered light signal and the fluorescence signal, and obtaining the nucleated erythrocyte parameters and / or basophil parameters based on the two-dimensional scatter plot; or, generating a three-dimensional scatter plot based on the forward-scattered light signal, the side-scattered light signal, and the fluorescence signal, obtaining the nucleated erythrocyte parameters and / or basophil parameters based on the three-dimensional scatter plot, and obtaining the original cell parameters.

[0108] In one embodiment, the method further includes: obtaining a second predetermined feature region of the scatter plot, wherein the intensity of lateral scattered light corresponding to the center position of the second predetermined feature region is higher than the intensity of lateral scattered light corresponding to the center position of the region containing neutrophils, and the fluorescence intensity corresponding to the center position of the second predetermined feature region is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region; and obtaining immature granulocyte parameters of the blood sample based on the second predetermined feature region.

[0109] The sample analysis method 900 of this application can be executed by the sample analyzer 100 described above. Those skilled in the art can understand the detailed process of the sample analysis method 900 according to the embodiments of the present invention in conjunction with the foregoing description. For the sake of brevity, only some main operations are described here, and more details can be found in the relevant descriptions above.

[0110] The sample analysis method 900 of this invention generates a scatter plot based on side-scattered light signals and fluorescence signals. By analyzing the first predetermined feature region of the scatter plot, the original cell parameters of the blood sample can be accurately obtained.

[0111] Another aspect of the present invention provides a sample analyzer, with reference to Figure 10 The sample analyzer 1000 includes a sampling device 1010, a sample preparation device 1020, an optical detection device 1030, and a processor 1040. The sample analyzer 1000 of this embodiment has a similar structure to the sample analyzer 100 described above. The following only describes the main functions of each component of the sample analyzer 1000; for more details, please refer to the relevant description of the sample analyzer 100 above.

[0112] Specifically, the sampling device 1010 is used to collect blood samples. The sample preparation device 1020 has a reaction chamber and a reagent supply unit, wherein the reaction chamber is used to receive the blood sample collected by the sampling device, and the reagent supply unit provides a hemolysin and a dye to the reaction chamber, thereby mixing the blood sample collected by the sampling device with the hemolysin and dye provided by the reagent supply unit in the reaction chamber to prepare a test sample solution; wherein the hemolysin is used to dissolve red blood cells, and the dye is used to stain organelles in blood cells. The optical detection device 1030 includes a light source, a flow chamber, and an optical detector, wherein the light source is used to emit a light beam to illuminate the flow chamber, the flow chamber is connected to the reaction chamber, and each particle in the test sample solution can pass through the flow chamber one by one, and the optical detector is used to detect the scattered light signal and fluorescence signal generated by the particles passing through the flow chamber after being illuminated in a single test.

[0113] The processor 1040 is configured to perform the following steps: acquiring scattered light signals and fluorescence signals of the sample solution to be tested from the optical detection device 1030, the scattered light signals including forward scattered light signals and side scattered light signals; obtaining the raw cell parameters of the blood sample based on the side scattered light signals and the fluorescence signals; and obtaining nucleated red blood cell parameters and / or basophil parameters of the blood sample based on the forward scattered light signals and the fluorescence signals.

[0114] Furthermore, the sample analyzer 1000 may also include a display device for displaying the sample analysis results obtained by the processor 140.

[0115] Similar to sample analyzer 100, sample analyzer 1000 in this embodiment also obtains the raw cell parameters of a blood sample based on fluorescence signals and side-scattered light signals. Simultaneously, sample analyzer 1000 also obtains nucleated erythrocyte parameters and / or basophil parameters of the blood sample based on forward-scattered light signals and fluorescence signals. The aforementioned forward-scattered light signal, side-scattered light signal, and fluorescence signal are light signals obtained from a single test sample solution in the same test; that is, raw cell parameters, nucleated erythrocyte parameters, and basophil parameters can be simultaneously obtained from the light signals obtained from a single test sample solution in the same test.

[0116] In one embodiment, the sample analyzer 1000 can obtain raw cell parameters using the same method as the sample analyzer 100. Specifically, the processor 1040 generates a scatter plot based on the side-scattered light signal and the fluorescence signal, and obtains a predetermined feature region and a region containing neutrophils from the scatter plot. The side-scattered light intensity corresponding to the center of the predetermined feature region is higher than the side-scattered light intensity corresponding to the center of the region containing neutrophils. The processor 1040 can obtain the raw cell parameters of the blood sample based on the predetermined feature region. The specific method for obtaining the raw cell parameters can be referred to above and will not be repeated here. Exemplarily, the processor 1040 can also generate an alarm message when the raw cell parameters exceed a preset threshold.

[0117] In one embodiment, the processor 1040 can generate different two-dimensional scatter plots and obtain different cell parameters based on the different two-dimensional scatter plots. Specifically, the processor 1040 can generate a first two-dimensional scatter plot based on side-scattered light signals and fluorescence signals, and obtain the original cell parameters based on the first two-dimensional scatter plot; and generate a second two-dimensional scatter plot based on forward-scattered light signals and fluorescence signals, and obtain at least one of nucleated erythrocyte parameters and basophil parameters based on the second two-dimensional scatter plot. Figure 2 and Figure 6 Exemplary first two-dimensional scatter plots and second two-dimensional scatter plots are shown respectively.

[0118] In another embodiment, the processor 1040 can generate a three-dimensional scatter plot based on forward-scattered light signals, side-scattered light signals, and fluorescence signals, and obtain nucleated erythrocyte parameters, basophil parameters, and primitive cell parameters from the three-dimensional scatter plot. See also Figure 7The processor 1040 can obtain nucleated red blood cell parameters of a blood sample based on the nucleated red blood cell population region in the three-dimensional scatter plot, obtain basophil parameters of a blood sample based on the basophil population region in the three-dimensional scatter plot, and obtain raw cell parameters of a blood sample based on a first predetermined feature region in the three-dimensional scatter plot.

[0119] In some embodiments, the processor 1040 can acquire the parameters of immature granulocytes in a blood sample simultaneously with the acquisition of raw cell parameters, nucleated erythrocyte parameters, and basophil parameters. Specifically, the processor 1040 can acquire a predetermined feature region corresponding to immature granulocytes in a first two-dimensional scatter plot, and obtain the immature granulocyte parameters of the blood sample based on the predetermined feature region corresponding to immature granulocytes. For example, the lateral scattered light intensity corresponding to the center position of the predetermined feature region corresponding to immature granulocytes is higher than the lateral scattered light intensity corresponding to the center position of the region containing neutrophils, and the fluorescence intensity corresponding to the center position of the predetermined feature region corresponding to immature granulocytes is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region.

[0120] Furthermore, the sample analyzer 1000 can also obtain the classification and count of white blood cells based on the light signal obtained in the same test. The method for obtaining the classification and count of white blood cells can be the pulse width signal-based method described above, but is not limited to it. The processor 1040 can also directly generate a scatter plot based on the light signal and obtain the classification and count of white blood cells based on the scatter plot.

[0121] Depending on the pretreatment of the blood sample (e.g., different reaction reagents), the sample analyzer can divide the blood sample testing process into different detection channels, such as the white blood cell differential (DIFF) channel, the basophil (BASO) channel, and the nucleated red blood cell (NRBC) channel. The sample analyzer 1000 of this embodiment can detect raw cell parameters through the WNB (white blood cell, basophil, and nucleated red blood cell) channel, simultaneously obtaining raw cell parameters, basophil parameters, nucleated red blood cell parameters, and white blood cell parameters in a single test.

[0122] The sample analyzer 1000 of this invention can obtain nucleated red blood cell parameters and / or basophil parameters of a blood sample while obtaining raw cell parameters.

[0123] refer to Figure 11 The present invention also provides a sample analysis method 1100, comprising the following steps:

[0124] In step S1110, a blood sample is obtained and the blood sample is mixed with a hemolysin and a dye to prepare a test sample solution, wherein the hemolysin is used to dissolve red blood cells and the dye is used to stain organelles in blood cells;

[0125] In step S1120, the scattered light signal and fluorescence signal generated by the particles in the sample liquid to be tested after being irradiated by light are detected in a single test;

[0126] In step S1130, the scattered light signal and fluorescence signal of the sample liquid to be tested are acquired, wherein the scattered light signal includes at least the forward scattered light signal and the side scattered light signal;

[0127] In step S1140, the raw cell parameters of the blood sample are obtained based on the side-scattered light signal and the fluorescence signal;

[0128] In step S1150, based on the forward-scattered light signal and the fluorescence signal, the nucleated red blood cell parameters and / or basophil parameters of the blood sample are obtained.

[0129] The sample analysis method 1100 of this application can be executed by the sample analyzer 1000 described above. Those skilled in the art can understand the detailed process of the sample analysis method 1100 according to the embodiments of the present invention in conjunction with the foregoing description. For the sake of brevity, only some main operations are described here, and more details can be found in the relevant descriptions above.

[0130] In one embodiment, obtaining raw cell parameters of a blood sample based on side-scattered light signals and fluorescence signals includes: generating a scatter plot based on side-scattered light signals and fluorescence signals; obtaining a predetermined feature region and a region containing neutrophils from the scatter plot; wherein the intensity of side-scattered light corresponding to the center position of the predetermined feature region is higher than the intensity of side-scattered light corresponding to the center position of the region containing neutrophils; and obtaining raw cell parameters of the blood sample based on the predetermined feature region.

[0131] In one embodiment, obtaining raw cell parameters of a blood sample based on side-scattered light signals and fluorescence signals includes: generating a first two-dimensional scatter plot based on side-scattered light signals and fluorescence signals, and obtaining raw cell parameters based on the first two-dimensional scatter plot; obtaining nucleated erythrocyte parameters and / or basophil parameters of a blood sample based on forward-scattered light signals and fluorescence signals includes: generating a second two-dimensional scatter plot based on forward-scattered light signals and fluorescence signals, and obtaining nucleated erythrocyte parameters and / or basophil parameters based on the second two-dimensional scatter plot.

[0132] In one embodiment, raw cell parameters of a blood sample are obtained based on side-scattered light signals and fluorescence signals; nucleated erythrocyte parameters and / or basophil parameters of a blood sample are obtained based on forward-scattered light signals and fluorescence signals, including: generating a three-dimensional scatter plot based on forward-scattered light signals, side-scattered light signals and fluorescence signals, obtaining nucleated erythrocyte parameters and / or basophil parameters from the three-dimensional scatter plot, and obtaining raw cell parameters.

[0133] The sample analysis method 1100 of this invention can obtain nucleated red blood cell parameters and / or basophil parameters of a blood sample while obtaining the original cell parameters.

[0134] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of this application. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of this application. All such changes and modifications are intended to be included within the scope of this application as claimed in the appended claims.

[0135] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0137] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0138] Similarly, it should be understood that, in order to streamline this application and aid in understanding one or more of the various inventive aspects, features of this application may sometimes be grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of this application. However, this approach should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with features fewer than all features of a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0139] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or apparatus so disclosed can be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0140] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0141] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some modules in the article analysis device according to embodiments of the present invention. This application can also be implemented as an apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such an implementation of this application can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0142] It should be noted that the above embodiments are illustrative of this application and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0143] The above description is merely a specific embodiment or illustration of the embodiments of this application. The scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. The scope of protection of this application shall be determined by the scope of the claims.

Claims

1. A sample analyzer, characterized in that, The sample analyzer includes: Sampling device for collecting blood samples; A sample preparation apparatus includes a reaction chamber and a reagent supply unit. The reaction chamber receives a blood sample collected by a sampling device, and the reagent supply unit provides a hemolysin and a dye to the reaction chamber. The blood sample collected by the sampling device is mixed with the hemolysin and dye provided by the reagent supply unit in the reaction chamber to prepare a sample solution for testing. An optical detection device includes a light source, a flow chamber, and an optical detector. The light source emits a light beam to illuminate the flow chamber. The flow chamber is connected to a reaction cell, and each particle in the sample solution to be tested can pass through the flow chamber one by one. The optical detector detects the scattered light signal and fluorescence signal generated by the particles passing through the flow chamber after being illuminated. The processor is configured to perform the following steps: The scattered light signal and fluorescence signal of the sample liquid to be tested are acquired from the optical detection device, wherein the scattered light signal includes at least a side-scattered light signal; A scatter plot is generated based at least on the side-scattered light signal and the fluorescence signal to obtain a first predetermined feature region and a region containing neutrophils in the scatter plot; wherein the intensity of the side-scattered light corresponding to the center position of the first predetermined feature region is higher than the intensity of the side-scattered light corresponding to the center position of the region containing neutrophils. The raw cell parameters of the blood sample are obtained based on the first predetermined feature region.

2. The sample analyzer as described in claim 1, characterized in that, The processor is also configured to perform the following steps: The lymphocyte population region of the scatter plot is obtained, and the fluorescence intensity corresponding to the center position of the first predetermined feature region is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region.

3. The sample analyzer as described in claim 1, characterized in that, The region containing the neutrophil population is a region containing the leukocyte population, which includes a lymphocyte population region, as well as regions containing neutrophils, eosinophils, and monocytes.

4. The sample analyzer as described in claim 1, characterized in that, The region containing the neutrophil population is the region containing the neutrophil population.

5. The sample analyzer as described in claim 1, characterized in that, The region containing the neutrophil population is a region containing populations of neutrophils, eosinophils, and monocytes.

6. The sample analyzer as described in claim 1, characterized in that, The original cell parameters include the particle concentration of the original cells, and the processor is further configured to perform the following steps: generating an alarm message when the particle concentration of the original cells exceeds a first preset threshold.

7. The sample analyzer as described in claim 1, characterized in that, The original cell parameters include the ratio of the particle concentration of the original cells to the particle concentration of white blood cells in the blood sample. The processor is also used to generate an alarm message when the ratio exceeds a second preset threshold.

8. The sample analyzer as described in claim 7, characterized in that, The processor is also configured to obtain the particle concentration of white blood cells in the blood sample by at least one of the following methods: The system receives externally inputted leukocyte particle concentration, obtains leukocyte particle concentration based on other detection channels, and obtains leukocyte particle concentration based on the scattered light signal and / or the fluorescence signal.

9. The sample analyzer as described in claim 1, characterized in that, The scattered light signal also includes a forward scattered light signal, and the processor is further configured to perform the following steps: The parameters of nucleated red blood cells and / or basophils in the blood sample are obtained based on the forward-scattered light signal and the fluorescence signal.

10. The sample analyzer as described in claim 9, characterized in that, The process of obtaining nucleated erythrocyte parameters and / or basophil parameters of the blood sample based on the forward-scattered light signal and the fluorescence signal includes: A two-dimensional scatter plot is generated based on the forward scattered light signal and the fluorescence signal, and the nucleated red blood cell parameters and / or basophil parameters are obtained based on the two-dimensional scatter plot. Alternatively, a three-dimensional scatter plot can be generated based on the forward-scattered light signal, the side-scattered light signal, and the fluorescence signal. The nucleated red blood cell parameters and / or basophil parameters can be obtained from the three-dimensional scatter plot, and the original cell parameters can be obtained.

11. The sample analyzer as described in claim 1, characterized in that, The processor is also configured to perform the following steps: Obtain a second predetermined feature region of the scatter plot, wherein the intensity of the lateral scattered light corresponding to the center position of the second predetermined feature region is higher than the intensity of the lateral scattered light corresponding to the center position of the region containing neutrophils, and the fluorescence intensity corresponding to the center position of the second predetermined feature region is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region. The immature granulocyte parameters of the blood sample are obtained based on the second predetermined feature region.

12. A sample analysis method, characterized in that, The method includes: Obtain a blood sample and mix the blood sample with a hemolysin and dye to prepare a test sample solution; The scattered light signal and fluorescence signal generated by particles in the sample solution after being irradiated by light are detected. Acquire the scattered light signal and fluorescence signal of the sample liquid to be tested, wherein the scattered light signal includes at least the side-scattered light signal; A scatter plot is generated based at least on the side-scattered light signal and the fluorescence signal to obtain a first predetermined feature region and a region containing neutrophils in the scatter plot; wherein the intensity of the side-scattered light corresponding to the center position of the first predetermined feature region is higher than the intensity of the side-scattered light corresponding to the center position of the region containing neutrophils. The raw cell parameters of the blood sample are obtained based on the first predetermined feature region.

13. The sample analysis method as described in claim 12, characterized in that, The method further includes: The lymphocyte population region of the scatter plot is obtained, and the fluorescence intensity corresponding to the center position of the first predetermined feature region is higher than the fluorescence intensity corresponding to the center position of the lymphocyte population region.

14. The sample analysis method as described in claim 12, characterized in that, The parameters of the original cell include the particle concentration of the original cell, and the method further includes generating an alarm message when the particle concentration of the original cell exceeds a first preset threshold.

15. The sample analysis method as described in claim 12, characterized in that, The parameters of the original cells include the ratio of the particle concentration of the original cells to the particle concentration of the white blood cells in the blood sample. The method further includes generating an alarm message when the ratio exceeds a second preset threshold.

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