Quality control method for blood cell examination in medical examination

Abstract

The invention discloses a quality control method for blood cell examination in medical examination, and relates to the technical field of blood cell medical examination, and the method comprises the following steps: obtaining the initial number of platelets in a sample to be detected through a resistance method; obtaining a two-dimensional scatter diagram of the to-be-detected sample based on a light scattering method; in the two-dimensional scattering scatter diagram, a total light intensity set is determined according to the sum of the lateral scattering light intensity and the sum of the forward scattering light intensity; and performing linear correction or nonlinear correction on the initial number of the platelets according to a preset correction rule. According to the method, a correction rule suitable for the number of platelets is constructed based on experimental data of a blood sample set, for the initial number of platelets and a two-dimensional scatter diagram obtained through conventional blood detection, the initial number of the platelets is corrected by judging the corresponding light intensity interval and applying the corresponding correction rule, and the initial number of the platelets is obtained. And the accuracy of platelet measurement results is ensured.

Description

Technical Field

[0001] The 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] For platelet counts in blood cells, traditional blood cell analyzers use the Coulter principle (resistance method) for detection. The basic principle is to measure the volume and number of particles through the resistance change generated when the particles in the blood sample pass through the detection hole. However, in actual detection, the volume of small-volume white blood cell fragments is very close to that of platelets. This volume similarity makes it difficult to distinguish the amplitude of resistance change, which in turn causes counting deviations. Especially in samples with a high concentration of white blood cell fragments, the number of white blood cell fragments will be misjudged as the number of platelets, resulting in a significant decrease in the accuracy of platelet counting.

[0003] To solve this problem, some technologies have introduced the scattered light method, in which the forward scattered light (FSC) signal is used to characterize the size of the particles, and the side scattered light (SSC) signal reflects the complexity inside 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 in terms of FSC signals. Although side scattered light can characterize the internal complexity of 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 using a two-dimensional scatter plot (FSC-SSC plot).

[0004] These two methods still have difficulty in completely eliminating the interference of white blood cell fragments on platelet counts. Especially in large-scale testing scenarios, due to the diversity of samples and fluctuations in the proportion of fragments, the limitations of traditional methods will be further magnified and cannot meet the requirements for platelet count accuracy and consistency. Summary of the invention

[0005] 1) Technical issues solved

[0006] The present invention provides a quality control method for blood cell testing in medical testing to solve the problem that in the 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 scattering scatter plot of the sample to be tested based on a 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;

[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 in the set area in the two-dimensional scatter plot is located in a preset first light intensity interval, a linear correction is performed on the initial number of platelets;

[0013] When the total light intensity set in the set area is in a preset second light intensity interval, a nonlinear correction is performed 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 according to the total light intensity set of the set area in the two-dimensional scatter plot of the healthy sample set; determine the second light intensity interval according to the total light intensity set of the set area in the two-dimensional scatter plot 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 acid 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 diagram, 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] Further, in the two-dimensional scatter plot, the total light intensity set in the set area is (I SSC , I FSC ), where I SSC I is the sum of the side scattered light intensities of leukocyte fragments and platelets in the set area. 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 of the blood samples 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 interval is:

[0027]

[0028] Among them, 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 interval is:

[0030]

[0031] Among them, Δ is the set margin.

[0032] 3) Beneficial effects:

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

[0034] The present invention constructs a correction rule for the number of platelets based on experimental data of a blood sample set, wherein a linear correction function and a nonlinear correction function are respectively constructed through grouping experimental data of healthy samples and patient samples, and after the number of white blood cell fragments is calculated by fluorescently staining and marking the white blood cell fragments in the sample set; for the blood sample before the white blood cell fragments are stained, a first light intensity interval suitable for linear correction is determined based on the total light intensity set of a set area in a two-dimensional scattering scatter plot of the healthy sample set; and a second light intensity interval suitable for nonlinear correction is determined based on the total light intensity set of a set area in a two-dimensional scattering scatter plot of the patient sample set.

[0035] By performing routine blood tests on the blood samples to be tested to obtain the initial number of platelets and the 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 number of platelets 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 flow chart 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", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" etc., indicating orientations or positional relationships, are 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, and do not indicate or imply 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 a limitation on the present invention.

[0043] In addition, the terms “first”, “second”, etc., if used, are merely used to distinguish between the descriptions 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] The platelets in the blood cells are counted using the electrical impedance method (Coulter principle) by introducing the diluted blood sample into a small chamber containing tiny detection holes. When the cells in the blood pass through the detection holes, they change the electrical impedance value, and the volume and number of the cells are detected based on this change.

[0046] When using the impedance method to measure platelets in blood cells, the inventors found that white blood cell fragments are inevitably present in the diluted blood sample. The volume range of white blood cell fragments and platelets is very close, and the volume of both is usually around 2μm-4μm. Since the impedance method mainly counts based on the volume of particles, some small-volume white blood cell fragments will be misjudged as platelets by the system, resulting in a high platelet count value.

[0047] If the number of fragmented white blood cells in the blood sample is small, the overall effect on the platelet count result is small. However, when the number of white blood cells in the sample is high or 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 solve this problem, some existing technologies have introduced the scattered light method, combining optical detection with the resistance method. Among them, in the results obtained by the scattered light method for blood cells, the forward scattered light (FSC) signal reflects the size of the particles. Generally, large particles will produce stronger forward scattered light. Although platelets and leukocyte fragments are similar in size, there are still slight differences. The side scattered light (SSC) signal reflects the internal structure and complexity of the particles, such as the granular structure of the cell, the nuclear-cytoplasmic ratio, etc. Usually, in actual operation, the volume of small-volume leukocyte fragments is very similar to that of platelets, resulting in their almost identical performance in the FSC signal. Due to this similarity, in the two-dimensional scattering diagram, the FSC axis (forward scattered light intensity) cannot effectively distinguish leukocyte fragments from platelets. For leukocytes, especially leukocyte fragments, although their internal structure is more complex, their scattering signals are weaker and less complex due to the small size of the fragments. Platelets usually have no nucleus inside, so their SSC signals are relatively weak, but there is still a certain overlap in the SSC signals of white blood cell 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 above-mentioned problems, it is understandable that when there are a large number of white blood cell fragments in the 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 the optical method based on the intensity of forward and side scattered light. In actual detection, the misjudgment caused by this volume approximation is often difficult to eliminate through simple calibration or filtering algorithms, especially in samples with a high number of white blood cell fragments, such as blood cells of patients with inflammation or disease, whose white blood cells and white blood cell fragments are high. Based on the existing resistance method for counting platelets, the test results will be affected by the large error of white blood cell fragments.

[0050] Therefore, in order to solve the above-mentioned problems, an embodiment of the present invention provides a quality control method for blood cell testing in medical testing. Figure 1 , Figure 1 The present invention provides a flow chart of a quality control method for blood cell testing in medical testing.

[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 the 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 through a small hole one by one, also called a detection hole. The diameter of the hole is typically in the range of 50μm-100μm (optimized for platelet count). Highly sensitive electrodes are set on both sides of the hole, and a stable DC electric field is applied. When cells act as insulators and move in the hole, the resistance in the hole is instantly changed, causing the electrical signal to change. The instantaneous signal of the 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 light scattering system of a blood analyzer is used to obtain a two-dimensional scattering scattergram of a blood sample. Specifically, a laser source (usually a laser diode) of a light scattering instrument is used to emit a laser beam and irradiate the flowing blood sample. When the laser beam irradiates different cells in the blood sample (such as platelets, white blood cells, red blood cells, etc.), the cells will scatter the light and generate scattered light signals at different angles. Among them, forward scattered light (FSC) refers to the signal generated by the light signal scattered by the cells in the direction of laser beam propagation after the laser beam penetrates the blood sample. The FSC signal mainly reflects the size of the cell particles. Larger cells or particles will scatter stronger forward light signals. Side scattered light (SSC) refers to the scattering signal perpendicular to the propagation direction of the laser beam generated when the laser beam interacts with the cells in the blood sample. The SSC signal reflects the internal complexity of the particles (such as the structure of the cells, the density of the particles, etc.). Cells with complex structures (such as white blood cells) will 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, its 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, among which complex cells such as white blood cells will have a larger scattered light intensity in this dimension. Its 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 stronger forward scatter signals, that is, larger blood cells are distributed in the area with larger FSC in the two-dimensional scatter plot, while smaller particles (such as platelets) will produce weaker signals, that is, smaller blood cells are distributed in the area with 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 referred to here Figure 4 , this scatter plot shows the scattered 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 scattering 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 here that in the two-dimensional scattering scatter plot, the total light intensity set in the set area is (I SSC , I FSC ), where I SSC I is the sum of the side scattered light intensities of leukocyte fragments and platelets in the set area. FSC It is the sum of the forward scattered light intensities of leukocyte fragments and platelets in the set area.

[0060] It is understandable that decomposing the total intensity value into the lateral total light intensity and the forward total light intensity can retain the independent characteristics of each direction instead of directly merging them into a single value, which helps to analyze the contributions of the lateral and forward directions separately. In addition, the two-dimensional scatter plot analysis in the laboratory is essentially based on the calculation logic of two-dimensional coordinates. Representing the total light intensity in a two-dimensional form is naturally more in line with this analysis mode, and the two-dimensional total intensity form can more carefully describe 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 flow 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 a healthy sample set and a patient sample set. The two have different characteristics and are used to establish a linear correction rule and a 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 leukocyte fragments, and generally exhibits a linear distribution characteristic in a 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 in that the number of leukocyte fragments may be significantly increased compared to the healthy sample set, and platelets and leukocyte fragments may exhibit nonlinear distribution characteristics in a 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 according to a total light intensity set of a set area in the two-dimensional scatter plot of the healthy sample set; determine a second light intensity interval according to a total light intensity set of a set area in the two-dimensional scatter plot 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 platelet 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, the initial region is determined according to the intersection of the distribution areas of platelets and leukocyte fragments. In each two-dimensional scatter plot, the distribution range where platelets and leukocyte fragments overlap is determined according to the characteristic curve in the existing experimental experience or the literature, and the initial region is delineated.

[0070] S423: Calculate and count the total light intensity set (I) of the initial area in each two-dimensional scattering dot map. 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 setting region. It can be understood that by analyzing the stability of the light intensity distribution of the scattered points in the initial region of the two-dimensional scattering scatter diagram of the healthy sample set, a region with high statistical consistency is determined as the final setting region, that is, Figure 5 The A region in the figure is used for subsequent calibration of the set region for platelets and leukocyte fragments. The total light intensity set with the highest consistency refers to the initial region with the most concentrated and stable light intensity distribution. By selecting such a region as the set region through stability analysis (such as mean and standard deviation calculation), the reliability and accuracy of the calibration method can be significantly improved.

[0072] Now let's go back to S42. In the healthy sample set, the number of platelets and the number of leukocyte fragments 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 leukocyte fragments may increase significantly due to pathological conditions (such as inflammation, immune response, etc.), the distribution of platelets and leukocyte fragments in the set area presents nonlinear characteristics. The total light intensity set of the set area is calculated through the scatter plot of the patient sample set, which 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 light 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 light intensity interval is that it dynamically reflects pathological characteristics, adapts to complex distributions, and provides optimization directions for the correction model. The combination of the two realizes the complementarity of benchmarks and dynamics, and constructs more accurate and adaptable correction rules.

[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 interval is:

[0077]

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

[0079] Regarding the set margin Δ, in some embodiments of the present invention, by introducing the calculation of the mean and standard deviation, that is, statistically calculating the mean and standard deviation of each dimension value in the total light intensity set, a light intensity interval based on data distribution can be defined, which can better reflect the distribution characteristics of the data. When the data has large fluctuations or non-uniform distribution, the interval based on statistics can more effectively capture the actual fluctuation range of the data, 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 range of the horizontal axis; and are the minimum and maximum values ​​of the forward scattered light intensity, respectively representing the range of the ordinate; 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 number of platelets 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 white blood cell fragments on platelets is small, the number of platelets obtained is corrected by a linear model or a linear function. This is because the number of platelets and the interference of white blood cell fragments present a relatively simple linear relationship. Linear correction can quickly and effectively adjust the number of platelets, maintaining 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 set of the set area is in the second light intensity interval, in this case, the influence of the white blood cell fragments presents a complex nonlinear relationship, so a more complex correction function is required. In some feasible examples of the present invention, a nonlinear model or a nonlinear function is used to correct the obtained platelet count. This correction method can adjust the platelet count more accurately and avoid the shortcomings of linear correction.

[0085] Through the above method, 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 degrees, 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 according to the number of white blood cell fragments in the healthy sample set; a nonlinear correction function is constructed according to 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 specific nucleic acid staining of leukocytes, and dyes with strong specificity for leukocyte fragments and no interference 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 the leukocyte fragments emit fluorescence at a specific wavelength after staining, while platelets have no fluorescence signal, the number of leukocyte fragments can be counted by using a flow cytometer, an image flow cytometer, and a fully automatic blood analyzer after staining the leukocyte 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. 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 dot plot, the set areas of white blood cell fragments and platelets cannot ,directly distinguish the number of the two ,numbers, and the number of white blood cell fragments and platelets in the set area needs to ,estimate the number of white blood cell fragments and platelets in the set area 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 respectively. 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 number of platelets here is the initial number of platelets in the sample to be tested obtained by the 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 respectively. WBC，P and the initial number of platelets is N′ PLT In some laboratory embodiments, it was found that the number of set areas of leukocyte fragments and platelets in a patient sample set 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 satisfied 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] In addition, in some embodiments of the present invention, it is also considered that if the total light intensity set of the set area measured in some samples to be tested is greater than the value in the second light intensity interval, it means that the white blood cell fragments in the sample to be tested have too great an impact on the platelet count, and the traditional platelet counting method is difficult to provide accurate results. This situation may indicate that there are a large number of white blood cell fragments in the blood sample, or that the characteristics of the fragments in the scattering spectrum are highly overlapped with the platelets, so that they cannot be effectively distinguished by conventional correction methods. Therefore, for such samples, re-testing measures must be taken to ensure the accuracy of the platelet count.

[0105] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. The patent protection scope of the present invention shall be based on the claims. All equivalent structural changes made using the contents of the description and drawings of the present invention should also be included in the protection scope 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 scattering scatter plot of the sample to be tested based on a 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; 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 in the set area in the two-dimensional scatter plot is located in a preset first light intensity interval, a linear correction is performed on the initial number of platelets; When the total light intensity set in the set area is in a preset second light intensity interval, a nonlinear correction is performed 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 according to the total light intensity set of the set area in the two-dimensional scatter plot of the healthy sample set; determine the second light intensity interval according to the total light intensity set of the set area in the two-dimensional scatter plot 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 acid in the leukocyte fragments.

3. The quality control method for blood cell testing in medical testing according to claim 1, characterized in that: The dilution concentration of each blood sample in the blood sample set is the same. After the light scattering method is performed on each blood sample to obtain the two-dimensional scattering diagram, 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 in the set area is (I SSC , I FSC ), where I SSC I is the sum of the side scattered light intensities of leukocyte fragments and platelets in the set area. 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 of the blood samples 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 therefrom. And the minimum total light intensity set The first light intensity interval is: Among them, 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 therefrom. And the minimum total light intensity set The second light intensity interval is: Among them, Δ is the set margin.

Images