A quality control method for blood cell testing in medical examination

Abstract

The present invention discloses a quality control method for blood cell testing in medical testing, which relates to the technical field of blood cell medical testing. The method includes obtaining the initial number of platelets in a sample to be tested by a resistance method; obtaining a two-dimensional scattering scatter plot of the sample to be tested based on a light scattering method; determining a total light intensity set based on the sum of the side scattered light intensities and the sum of the forward scattered light intensities in the two-dimensional scattering scatter plot; and performing a linear correction or a nonlinear correction on the initial number of platelets based on a preset correction rule. The present invention constructs a correction rule for platelet number based on experimental data of a blood sample set. For the initial number of platelets and the two-dimensional scattering scatter plot obtained by conventional blood testing, the method determines the corresponding light intensity interval and applies the corresponding correction rule to correct the initial number of platelets, thereby ensuring the accuracy of the platelet measurement result.

Description

Technical Field

[0001] The present invention relates to the technical field of blood cell medical examination, in particular to a quality control method for blood cell examination in medical examination. Background Art

[0002] Traditional hematology analyzers use the Coulter principle (resistance method) to count platelets in blood cells. The basic principle is to measure the volume and number of particles in the blood sample by the resistance change generated when the particles pass through the detection hole. However, in actual testing, the volume of small white blood cell fragments is very close to that of platelets. This volume similarity makes it difficult to distinguish the magnitude of the resistance change, which in turn causes counting deviations. Especially in samples with high white blood cell fragment concentrations, the number of white blood cell fragments can be mistaken for the number of platelets, resulting in a significant decrease in the accuracy of platelet counts.

[0003] To address this issue, some technologies have introduced scattered light methods, in which the forward scattered light (FSC) signal is used to characterize the size of the particles, while the side scattered light (SSC) signal reflects the complexity of the particles. However, the scattered light method still has obvious limitations in practical applications. The forward scattered light signal of small-volume white blood cell fragments is highly similar to that of platelets, resulting in the two still being unable to be effectively distinguished based on the FSC signal. Although side scattered light can characterize the internal complexity of the particles, the complexity of small-volume white blood cell fragments is low, and there is also significant overlap with the SSC signal of platelets, which limits the effectiveness of distinguishing them using a two-dimensional scatter plot (FSC-SSC plot).

[0004] These two methods still struggle to completely eliminate the interference of white blood cell fragments on platelet counts. Especially in large-scale testing scenarios, due to sample diversity and fluctuations in fragment ratios, the limitations of traditional methods are further magnified, making them unable to meet the requirements for platelet count accuracy and consistency. Summary of the Invention

[0005] 1) Technical problems solved

[0006] The present invention provides a quality control method for blood cell testing in medical examinations to solve the problem that in existing platelet count detection, small-volume white blood cell fragments are easily misjudged as platelets, thereby affecting the accuracy of platelet counting.

[0007] 2) Technical solution

[0008] To achieve the above object, the present invention provides the following technical solution: a quality control method for blood cell testing in medical testing, comprising:

[0009] Obtaining the initial number of platelets in the sample to be tested by the electrical resistance method;

[0010] Obtaining a two-dimensional scatter plot of the sample to be tested based on a light scattering method; wherein the horizontal axis of the two-dimensional scatter plot is the side scattered light intensity, and the vertical axis is the forward scattered light intensity;

[0011] In the two-dimensional scatter plot, determining a total light intensity set according to the sum of the side scattered light intensities and the sum of the forward scattered light intensities;

[0012] According to a preset correction rule, when the total light intensity set within the set area in the two-dimensional scatter plot is within a preset first light intensity interval, a linear correction is performed on the initial number of platelets;

[0013] When the total light intensity set within the set area is within a preset second light intensity interval, performing a nonlinear correction on the initial number of platelets;

[0014] The steps of constructing the correction rule include:

[0015] Obtaining blood sample sets, including patient sample sets and healthy sample sets;

[0016] Determine the first light intensity interval based on the total light intensity set of the set area in the two-dimensional scattered point map of the healthy sample set; determine the second light intensity interval based on the total light intensity set of the set area in the two-dimensional scattered point map of the patient sample set;

[0017] The number of leukocyte fragments in the blood sample set is determined by fluorescent staining, and a linear correction function is constructed according to the number of leukocyte fragments in the healthy sample set; a nonlinear correction function is constructed according to the number of leukocyte fragments in the patient sample set.

[0018] Furthermore, the fluorescent staining of the leukocyte fragments is specifically staining the nucleic acids in the leukocyte fragments.

[0019] Furthermore, the dilution concentration of each blood sample in the blood sample set is the same. After each blood sample is subjected to a light scattering method to obtain the two-dimensional scattering pattern, the white blood cell fragments are stained so that the white blood cell fragments have a fluorescent signal that is different from that of platelets, and the number of white blood cell fragments in each blood sample is calculated.

[0020] Furthermore, in the two-dimensional scatter plot, the total light intensity set within the set area is (I SSC , I FSC ), where I SSC is the sum of the side scattered light intensities of leukocyte fragments and platelets in the set area, I FSC It is the sum of the forward scattered light intensities of leukocyte fragments and platelets in the set area.

[0021] Furthermore, the step of determining the set area includes:

[0022] Obtaining a two-dimensional scatter plot of each blood sample in the healthy sample set;

[0023] In each two-dimensional scatter plot, the initial region was determined based on the intersection of the distribution areas of platelets and leukocyte fragments;

[0024] Calculate the total light intensity set (I) of the initial area in each two-dimensional scatter plot SSC , I FSC );

[0025] Based on the stability analysis method, the initial region where the total light intensity set has the highest consistency is used as the set region.

[0026] Furthermore, in the healthy sample set, the total light intensity set of the set area in the two-dimensional scatter plot of each blood sample is calculated, and the maximum total light intensity set is extracted from it. and the minimum total light intensity set The first light intensity range is:

[0027]

[0028] Wherein, Δ is the set margin.

[0029] Furthermore, in the patient sample set, the total light intensity set of the set area in the two-dimensional scatter plot of each blood sample is calculated, and the maximum total light intensity set is extracted from it. and the minimum total light intensity set The second light intensity range is:

[0030]

[0031] Wherein, Δ is the set margin.

[0032] 3) Beneficial effects:

[0033] Compared with the prior art, this invention has the following beneficial effects:

[0034] The present invention constructs a correction rule for platelet count based on experimental data from a blood sample set. The rule uses grouped experimental data from healthy samples and patient samples, and after fluorescently marking white blood cell fragments in the sample set to calculate the number of white blood cell fragments, a linear correction function and a nonlinear correction function are constructed. For blood samples before white blood cell fragment staining, a first light intensity range suitable for linear correction is determined based on the total light intensity set of a set area in a two-dimensional scatter plot of the healthy sample set. A second light intensity range suitable for nonlinear correction is determined based on the total light intensity set of a set area in the two-dimensional scatter plot of the patient sample set.

[0035] By performing routine blood tests on the blood sample to be tested and obtaining the initial platelet count and two-dimensional scatter plot, the total light intensity set of the set area in the two-dimensional scatter plot is calculated, the corresponding light intensity interval is determined and the corresponding correction rules are applied, and then the initial platelet count is corrected to ensure the accuracy of the platelet measurement results. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic flow chart of a quality control method for blood cell testing in a medical test provided by an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of a process for obtaining preset correction rules in a quality control method for blood cell testing in a medical test provided by an embodiment of the present invention;

[0038] Figure 3 A schematic diagram of a flow chart for defining a set area in a quality control method for blood cell testing in a medical test provided by an embodiment of the present invention;

[0039] Figure 4 A schematic diagram of the distribution of various types of blood cells in a two-dimensional scatter plot obtained in a quality control method for blood cell testing in a medical test provided by an embodiment of the present invention;

[0040] Figure 5 A schematic diagram of a set area A for defining platelets and leukocyte fragments in a two-dimensional scatter plot in a quality control method for blood cell testing in a medical test provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0042] In the description of the present invention, it should be understood that the terms "longitudinal", "transverse", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0043] In addition, the terms "first", "second", etc., if used, are merely used to distinguish and describe, and should not be understood as indicating or implying relative importance.

[0044] It should be noted that, in the absence of conflict, the features in the embodiments of the present invention may be combined with each other.

[0045] By introducing a diluted blood sample into a small chamber containing a tiny detection hole, the platelets in the blood cells are counted using the electrical impedance method (Coulter principle). When the cells in the blood pass through the detection hole, they change the electrical impedance value, and the volume and number of the cells are detected based on this change.

[0046] When using the electrical impedance method to measure platelets in blood cells, the inventors discovered that diluted blood samples inevitably contain white blood cell fragments. The volume range of white blood cell fragments and platelets is very similar, and the volume of both is usually around 2μm-4μm. Since the electrical impedance method mainly counts particles based on volume, some small white blood cell fragments may be mistakenly identified as platelets by the system, resulting in an elevated platelet count.

[0047] If the number of fragmented white blood cells in a blood sample is small, the overall impact on the platelet count result is minimal. However, if the number of white blood cells in the sample is high or is affected by sample preparation factors, such as severe shaking or hemolysis, the number of white blood cell fragments will increase significantly, exacerbating the counting error.

[0048] To address this issue, some existing technologies have introduced scattered light methods, combining optical detection with electrical resistance methods. In the results of scattered light methods for blood cells, the forward scattered light (FSC) signal reflects the size of the particles. Large particles generally produce stronger forward scattered light. Platelets and leukocyte fragments, while similar in size, exhibit slight differences. The side scattered light (SSC) signal, on the other hand, reflects the internal structure and complexity of the particles, such as the cell's granular structure and nucleocytoplasmic ratio. In practice, small leukocyte fragments and platelets often have very similar volumes, resulting in their FSC signals appearing almost identical. Due to this similarity, the FSC axis (forward scattered light intensity) cannot effectively distinguish leukocyte fragments from platelets in a two-dimensional scatter plot. Although leukocytes, and especially leukocyte fragments, have a relatively complex internal structure, their smaller size results in a weaker scattering signal and lower complexity. Platelets usually have no nucleus, so their SSC signals are relatively weak. However, there is still some overlap between the SSC signals of leukocyte fragments and platelets, especially small fragments, whose scattered light intensity may be close to that of platelets, resulting in unclear distinction between the two.

[0049] Based on the aforementioned issues, it is understandable that when a large number of white blood cell fragments are present in a sample, due to the high similarity in volume between white blood cell fragments and platelets, it is difficult to directly distinguish the quantitative relationship between the two, whether based on the Coulter principle of resistance change or optical methods based on the intensity of forward and side scattered light. In actual testing, misjudgments caused by this volume approximation are often difficult to eliminate through simple calibration or filtering algorithms, especially in samples with high white blood cell fragment counts, such as the blood cells of patients with inflammation or disease, which have high levels of white blood cells and white blood cell fragments. The existing resistance method for platelet counting will cause significant errors in the test results due to the white blood cell fragments.

[0050] Therefore, in order to solve the above-mentioned problems, the embodiment of the present invention provides a quality control method for blood cell testing in medical testing, specifically, referring to Figure 1 , Figure 1 This is a workflow diagram of a quality control method for blood cell testing in medical testing provided by the present invention.

[0051] First, S1 is performed: obtaining the initial number of platelets in the sample to be tested by the resistance method. In some embodiments of the present invention, based on the resistance method, an electrical impedance signal detected after the blood sample flows through the small hole is obtained.

[0052] First, collect an anticoagulated blood sample, such as a blood sample with EDTA anticoagulant added. Dilute the blood sample at a certain ratio, usually 1:1000 to 1:5000, and use a low-conductivity electrolyte, such as sodium chloride solution, to avoid cell aggregation or overlapping, thereby reducing cell density and ensuring that cells pass through the small hole in the form of single particles, thereby improving detection accuracy.

[0053] Based on the Coulter principle, cells are passed one by one through a small hole, also called a detection hole. The diameter of the hole typically ranges from 50μm to 100μm (optimized for platelet counts). Highly sensitive electrodes are placed on both sides of the hole, and a stable DC electric field is applied. Cells, acting as insulators, move through the hole, instantaneously changing the resistance within the hole, causing a change in the electrical signal. This instantaneous signal of resistance change is captured through high-frequency sampling.

[0054] Perform S2: obtain a two-dimensional scattering scatter plot of the sample to be tested based on the light scattering method; wherein the horizontal axis of the two-dimensional scattering scatter plot is the side scattered light intensity, and the vertical axis is the forward scattered light intensity.

[0055] In some embodiments of the present invention, a two-dimensional scatter plot of a blood sample is obtained using the light scattering system of a hematology analyzer. Specifically, a laser source (typically a laser diode) in the light scattering instrument emits a laser beam that is irradiated into a flowing blood sample. When the laser beam strikes different cells in the blood sample (e.g., platelets, white blood cells, red blood cells, etc.), the cells scatter the light, generating scattered light signals at different angles. Forward scattered light (FSC) refers to the light signal generated in the direction of laser beam propagation after the laser beam penetrates the blood sample. The FSC signal primarily reflects the size of cell particles; larger cells or particles scatter stronger forward light signals. Side scattered light (SSC) refers to the scattered light signal perpendicular to the direction of laser beam propagation generated when the laser beam interacts with cells in the blood sample. The SSC signal reflects the internal complexity of the particles (e.g., cell structure, particle density, etc.). Cells with complex structures (e.g., white blood cells) scatter stronger side light.

[0056] The light scattering instrument uses a photodetector (such as a photodiode) to collect scattered light signals. The detector converts the scattered light signals into electrical signals, which are then converted into digital signals and compared with reference standards to obtain the intensity value of the scattered light.

[0057] For the two-dimensional scatter plot obtained in S2, the horizontal axis represents the side scattered light intensity (SSC) and the complexity of the cell particles, indicating the internal structure and complexity of the cell particles. Complex cells such as white blood cells will have a higher scattered light intensity in this dimension. The vertical axis represents the forward scattered light intensity (FSC) and the size of the particles. Larger particles (such as large white blood cells) will produce a stronger forward scatter signal, that is, larger blood cells are distributed in the area with a larger FSC in the two-dimensional scatter plot, while smaller particles (such as platelets) will produce a weaker signal, that is, smaller blood cells are distributed in the area with a smaller FSC in the two-dimensional scatter plot.

[0058] Based on these signals, a two-dimensional scatter plot (i.e., FSC-SSC plot) is generated, which is referenced here. Figure 4 , this scatter plot shows the scatter distribution of various types of cells (platelets, white blood cells, red blood cells, etc.) in the blood sample in two dimensions of FSC and SSC.

[0059] S3: In the two-dimensional scatter plot, determine the total light intensity set according to the sum of the side scattered light intensities and the sum of the forward scattered light intensities. It can be understood that in the two-dimensional scatter plot, the total light intensity set in the set area is (I SSC , I FSC ), where I SSC is the sum of the side scattered light intensities of leukocyte fragments and platelets in the set area, I FSC It is the sum of the forward scattered light intensities of leukocyte fragments and platelets in the set area.

[0060] It's understandable that decomposing the total intensity value into the lateral and forward total light intensity components preserves the independent characteristics of each direction, rather than simply merging them into a single value. This facilitates separate analysis of the lateral and forward contributions. Furthermore, two-dimensional scatter plot analysis in the laboratory is essentially based on computational logic based on two-dimensional coordinates. Representing the total light intensity in two dimensions naturally better aligns with this analytical model, and the two-dimensional total intensity representation provides a more detailed description of the overlapping characteristics of platelet and leukocyte fragments.

[0061] Perform S4: according to a preset correction rule, when the total light intensity set in the set area in the two-dimensional scatter plot is located in a preset first light intensity interval, perform a linear correction on the initial number of platelets.

[0062] If the total light intensity set within the set area in the two-dimensional scatter plot does not belong to the first light intensity interval, perform S5: when the total light intensity set within the set area is within the preset second light intensity interval, perform nonlinear correction on the initial number of platelets.

[0063] In the above two steps, refer to Figure 2 The flowchart of obtaining the preset correction rules is shown in FIG. 1 . Regarding the establishment of the preset rules, the specific operation process is as follows.

[0064] First, S41 is performed: a blood sample set is obtained, including a patient sample set and a healthy sample set. The experimental data required for constructing the correction rule includes the healthy sample set and the patient sample set. The healthy sample set and the patient sample set have different characteristics and are used to establish the linear correction rule and the nonlinear correction rule, respectively.

[0065] The healthy sample set is composed of blood samples from healthy individuals, and is characterized by a relatively stable ratio of platelets and white blood cell fragments, and generally exhibits a linear distribution characteristic in the set area. Healthy individuals without infection, inflammation or other diseases that affect blood characteristics can be selected. The patient sample set comes from individuals with specific diseases (such as inflammation, infection or blood disease), and is characterized by a significant increase in the number of white blood cell fragments compared to the healthy sample set, and platelets and white blood cell fragments may exhibit nonlinear distribution characteristics in the set area. It should be noted here that the dilution concentration of each blood sample in the blood sample set is the same.

[0066] Perform S42: determine a first light intensity interval based on the total light intensity set of the set area in the two-dimensional scattered point map of the healthy sample set; determine a second light intensity interval based on the total light intensity set of the set area in the two-dimensional scattered point map of the patient sample set.

[0067] In some embodiments of the present invention, reference Figure 3 As shown in the flowchart, defining the set area for platelets and leukocyte fragments includes the following steps.

[0068] First, S421 is performed: a two-dimensional scatter plot of each blood sample in the healthy sample set is obtained.

[0069] S422 is performed: in each two-dimensional scatter plot, an initial region is determined based on the intersection of the distribution areas of platelets and white blood cell fragments. In each two-dimensional scatter plot, the distribution range where platelets and white blood cell fragments overlap is determined based on existing experimental experience or characteristic curves in the literature, and the initial region is delineated.

[0070] Perform S423: calculate and count the total light intensity set (I SSC , I FSC ). That is, in each two-dimensional scatter plot, all scattered point data in the initial area are counted, and the total light intensity set of the horizontal axis (lateral light intensity) and the vertical axis (forward light intensity) is calculated.

[0071] S424 is performed: Based on the stability analysis method, the initial region with the highest consistency of the total light intensity set is used as the set region. This can be understood as analyzing the stability of the light intensity distribution of the scattered points in the initial region of the two-dimensional scatter plot of the healthy sample set to determine a region with high statistical consistency as the final set region, that is, Figure 5 Region A in the figure is used for subsequent calibration of platelet and leukocyte fragments. The highest consistency of the total light intensity set refers to the initial region with the most concentrated and stable light intensity distribution. Selecting such a region as the set region through stability analysis (such as mean and standard deviation calculation) can significantly improve the reliability and accuracy of the calibration method.

[0072] Now let's go back to S42. In the healthy sample set, the platelet count and the white blood cell fragment count show linear distribution characteristics within the physiological range, and the light intensity distribution of these two components is relatively stable within the set area in the two-dimensional scatter plot. Since healthy samples are not affected by pathological factors, the total light intensity set in the set area has smaller volatility and higher consistency. This consistency allows the light intensity range calculated in the healthy sample set (i.e., the first light intensity interval) to be used as a benchmark for subsequent analysis and correction.

[0073] It should be noted here that the healthy sample set usually covers normal individuals of different genders, ages and physiques, and its statistical results are more universal and representative. The determined first light intensity interval can adapt to the normal blood characteristics of most individuals and provide a standardized basis for subsequent analysis.

[0074] In the patient sample set, since the number of white blood cell fragments may increase significantly due to pathological conditions (such as inflammation, immune response, etc.), the distribution of platelets and white blood cell fragments in the set area presents nonlinear characteristics. Calculating the total light intensity set of the set area through the scatter plot of the patient sample set can truly reflect the light intensity distribution under pathological conditions and provide a basis for the correction of abnormal samples.

[0075] It can be understood that the advantage of selecting a healthy sample set to determine the first intensity interval is that the data is stable, providing a universal benchmark and helping to define normal distribution characteristics. The advantage of selecting a patient sample set to determine the second intensity interval is that it dynamically reflects pathological characteristics, adapts to complex distributions, and provides optimization direction for the correction model. Combining the two, the benchmark and dynamic complementarity are achieved, constructing a more accurate and adaptable correction rule.

[0076] More specifically, in the healthy sample set, the total light intensity set of the set area in the two-dimensional scatter plot of each blood sample is calculated, and the maximum total light intensity set is extracted from it and the minimum total light intensity set The first light intensity range is:

[0077]

[0078] in, and are the minimum and maximum values ​​of the side scattered light intensity, representing the interval range of the horizontal axis respectively; and are the minimum and maximum values ​​of the forward scattered light intensity, respectively representing the interval range of the vertical axis; Δ is the set margin.

[0079] Regarding the margin Δ, some embodiments of the present invention incorporate the calculation of mean and standard deviation. This statistical calculation of the mean and standard deviation of each dimension within the total light intensity set allows for the definition of a light intensity range based on the data distribution, better reflecting the data's distribution characteristics. When data exhibit significant fluctuations or a non-uniform distribution, statistically based intervals can more effectively capture the actual fluctuation range, thereby improving the accuracy of the correction rule.

[0080] Similarly, in the patient sample set, the total light intensity set of the set area in the two-dimensional scatter plot of each blood sample is calculated, and the maximum total light intensity set is extracted from it and the minimum total light intensity set The second light intensity range is:

[0081]

[0082] in, and are the minimum and maximum values ​​of the side scattered light intensity, representing the interval range of the horizontal axis respectively; and are the minimum and maximum values ​​of the forward scattered light intensity, respectively representing the interval range of the vertical axis; Δ is the set margin.

[0083] Specifically, the light intensity interval is used to define two different correction strategies. If the total light intensity set of the set area is in the first light intensity interval, at this time, it can be judged that the influence of the white blood cell fragments in the sample on the platelets is small. In this case, the correction of the platelet count obtained from the blood sample is relatively simple. Because the interference of white blood cell fragments is less, in some feasible examples of the present invention, when the influence of such white blood cell fragments on platelets is small, the obtained platelet count is corrected by a linear model or a linear function. This is because the platelet count and the interference of white blood cell fragments show a relatively simple linear relationship. The linear correction can quickly and effectively adjust the platelet count and maintain the simplicity and efficiency of the correction process. In addition, the linear correction method is simple to calculate and fast, suitable for large-scale data processing, and will not cause excessive adjustment of the platelet count. For scenarios with high requirements for test results, linear correction can better balance accuracy and efficiency.

[0084] If the total light intensity of the set area is within the second light intensity range, the influence of white blood cell fragmentation exhibits a complex nonlinear relationship, necessitating a more complex correction function. In some feasible embodiments of the present invention, a nonlinear model or function is used to correct the obtained platelet count. This correction method can more accurately adjust the platelet count and avoid the shortcomings of linear correction.

[0085] In this way, the light intensity ranges of the first light intensity interval and the second light intensity interval are effectively defined, so that different correction strategies can be adopted for areas with different impact levels, thereby ensuring the accuracy and reliability of platelet counting.

[0086] Regarding how to perform linear correction or nonlinear correction on the platelet count value, in some feasible embodiments of the present invention, S43 is performed: the number of white blood cell fragments in the blood sample set is determined by fluorescent staining the white blood cell fragments in the blood sample set, and a linear correction function is constructed based on the number of white blood cell fragments in the healthy sample set; a nonlinear correction function is constructed based on the number of white blood cell fragments in the patient sample set.

[0087] In some embodiments of the present invention, fluorescent staining of leukocyte fragments is specifically staining of nucleic acids in leukocyte fragments. The selection of fluorescent dyes is key to the specific nucleic acid staining of leukocytes. Dyes that are highly specific to leukocyte fragments and do not interfere with platelets should be selected. In some feasible embodiments of the present invention, CD45 antibodies are used in combination with fluorescent dyes to mark leukocyte fragments. CD45 is a marker molecule of leukocytes, and almost all leukocytes express CD45. By using fluorescent dyes (such as FITC, PE or APC dyes) that bind to CD45 antibodies, leukocytes and their fragments can be specifically marked. In other feasible embodiments of the present invention, Hoechst33342 or DAPI dyes are used. These dyes can bind to nuclear DNA and are generally used to mark all leukocyte fragments or nucleic acids, which can help identify leukocyte fragments with nucleic acid substances.

[0088] For the diluted blood sample, a specific fluorescent dye (such as FITC dye labeled with CD45 antibody) is added to the blood sample, and the fluorescent signal is obtained using equipment such as a flow cytometer or a fluorescence microscope.

[0089] It is understandable that since white blood cell fragments emit fluorescence at a specific wavelength after staining, while platelets do not emit a fluorescent signal, the number of white blood cell fragments can be counted using flow cytometers, image flow cytometers, and fully automated hematology analyzers after staining the white blood cell fragments.

[0090] Based on the statistical data of fluorescence staining of leukocyte fragments, linear correction functions and nonlinear correction functions are constructed respectively. Specifically, the blood sample set is divided into a healthy sample set and a patient sample set, and the number of leukocyte fragments obtained by fluorescence staining is recorded as N. WBC，P , the initial number of platelets is N PLT ,In the two-dimensional scatter plot, the set areas of white blood cell fragments and platelets cannot ,directly distinguish the number of the two, and the number of white ,blood cell fragments and platelets in the set area needs to ,be estimated through a correction function.

[0091] A linear correction function is constructed based on the healthy sample set. Specifically, each blood sample in the healthy sample set is fluorescently stained and the number of white blood cell fragments N is counted. WBC，P and the initial number of platelets is N PLT , in the blood samples of the healthy sample set, white blood cell fragments and platelets are linearly proportional within the set area:

[0092] N WBCP,lap =k1N PLT,lap

[0093] N WBCP,lap N is the number of white blood cell fragments in the set area.PLT,lap is the number of platelets in the set area, and k1 is the linear correction coefficient.

[0094] According to the total light intensity signal of the set area in the two-dimensional scatter plot, the distribution statistics are used to determine the quantitative ratio of white blood cell fragments and platelets, and then k1 is obtained by fitting the data in the healthy sample set.

[0095] Then the linear correction function between the number of platelets and the number of white blood cell fragments is obtained:

[0096] Corrected platelet count = initial platelet count × (1-k1)

[0097] It should be noted that the initial platelet count here is the initial platelet count in the sample to be tested obtained by the electrical resistance method.

[0098] A nonlinear correction function is constructed based on the patient sample set. Specifically, each blood sample in the patient sample set is fluorescently stained and the number of white blood cell fragments N is counted. ' WBCP and the initial number of platelets is N ' PLT In some laboratory experiments, it was found that the number of leukocyte fragments and platelets in a set of patient samples was exponentially related.

[0099] Through experimental data analysis, it was found that the number of white blood cell fragments and platelets in the set area of ​​the patient sample satisfies the following relationship:

[0100]

[0101] Wherein, α and b are nonlinear parameters to be fitted, and a nonlinear fitting algorithm (such as the least squares method) is used to fit α and b to obtain their determined values.

[0102] The correction function for the exponential function is:

[0103]

[0104] Among them, N PLT，correct is the corrected platelet count, N PLT，initial is the initial number of platelets, N' WBCP，lap is the number of white blood cell fragments in the set area.

[0105] Furthermore, in some embodiments of the present invention, if the total light intensity measured in a set area of ​​a certain sample exceeds the value in the second light intensity range, this indicates that the white blood cell fragments in the sample are significantly impacting the platelet count, making it difficult for traditional platelet counting methods to provide accurate results. This may indicate that the blood sample contains a large number of white blood cell fragments, or that the fragments' scattering spectrum characteristics overlap significantly with those of platelets, making them indistinguishable using conventional correction methods. Therefore, for such samples, retesting is necessary to ensure accurate platelet counts.

[0106] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. The scope of patent protection of the present invention shall be based on the claims. Any equivalent structural changes made using the description and drawings of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A quality control method for blood cell testing in medical testing, characterized in that: include: Obtaining the initial number of platelets in the sample to be tested by the electrical resistance method; Obtaining a two-dimensional scatter plot of the sample to be tested based on a light scattering method, wherein the horizontal axis of the two-dimensional scatter plot is the side scattered light intensity and the vertical axis is the forward scattered light intensity; In the two-dimensional scatter plot, determining a total light intensity set according to the sum of the side scattered light intensities and the sum of the forward scattered light intensities; According to a preset correction rule, when the total light intensity set within the set area in the two-dimensional scatter plot is within a preset first light intensity interval, a linear correction is performed on the initial number of platelets; When the total light intensity set within the set area is within a preset second light intensity interval, performing a nonlinear correction on the initial number of platelets; The steps of constructing the correction rule include: Obtaining blood sample sets, including patient sample sets and healthy sample sets; Determine the first light intensity interval based on the total light intensity set of the set area in the two-dimensional scattered point map of the healthy sample set; determine the second light intensity interval based on the total light intensity set of the set area in the two-dimensional scattered point map of the patient sample set; The number of leukocyte fragments in the blood sample set is determined by fluorescent staining, and a linear correction function is constructed according to the number of leukocyte fragments in the healthy sample set; a nonlinear correction function is constructed according to the number of leukocyte fragments in the patient sample set.

2. The quality control method for blood cell testing in medical testing according to claim 1, characterized in that: The fluorescent staining of the leukocyte fragments is specifically staining the nucleic acids in the leukocyte fragments.

3. The quality control method for blood cell testing in medical testing according to claim 1, characterized in that: Each blood sample in the blood sample set has the same dilution concentration. After performing a light scattering method on each blood sample to obtain the two-dimensional scatter plot, the white blood cell fragments are stained so that the white blood cell fragments have a fluorescent signal that is different from platelets, and the number of white blood cell fragments in each blood sample is calculated.

4. The quality control method for blood cell testing in medical testing according to claim 1, characterized in that: In the two-dimensional scatter plot, the total light intensity set within the set area is (I SSC , I FSC ), where I SSC is the sum of the side scattered light intensities of leukocyte fragments and platelets in the set area, I FSC It is the sum of the forward scattered light intensities of leukocyte fragments and platelets in the set area.

5. The quality control method for blood cell testing in medical testing according to claim 4, characterized in that: The step of determining the set area includes: Obtaining a two-dimensional scatter plot of each blood sample in the healthy sample set; In each two-dimensional scatter plot, the initial region was determined based on the intersection of the distribution areas of platelets and leukocyte fragments; Calculate the total light intensity set (I) of the initial area in each two-dimensional scatter plot SSC , I FSC ); Based on the stability analysis method, the initial region where the total light intensity set has the highest consistency is used as the set region.

6. The quality control method for blood cell testing in medical testing according to claim 5, characterized in that: In the healthy sample set, the total light intensity set of the set area in the two-dimensional scatter plot of each blood sample is calculated, and the maximum total light intensity set is extracted from it. and the minimum total light intensity set The first light intensity range is: Wherein, Δ is the set margin.

7. The quality control method for blood cell testing in medical testing according to claim 5, characterized in that: In the patient sample set, the total light intensity set of the set area in the two-dimensional scatter plot of each blood sample is calculated, and the maximum total light intensity set is extracted from it. and the minimum total light intensity set The second light intensity range is: Wherein, Δ is the set margin.

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