Quality control methods for blood cell tests in medical testing

Abstract

This invention provides a method for quality control of blood cell tests in medical testing. [Solution] The method includes obtaining the initial number of platelets in a sample to be measured using the electrical resistance method, obtaining a two-dimensional scatter plot of the sample to be measured based on the scattered light method, determining the total light intensity set in the two-dimensional scatter plot based on the sum of the side scattered light intensities and the sum of the forward scattered light intensities, and performing a linear or nonlinear correction on the initial number of platelets according to a preset correction rule. The present invention constructs a correction rule suitable for the number of platelets based on experimental data of a blood sample set, determines the corresponding light intensity range for the initial number of platelets and the two-dimensional scatter plot obtained in a normal blood test, and corrects the initial number of platelets by applying an appropriate correction rule, thereby ensuring the accuracy of the platelet measurement results.

Description

Technical Field

[0001] The present invention relates to the technical field of blood cell medical examinations, and particularly to a quality control method for blood cell examinations in medical examinations.

Background Art

[0002] When measuring the number of platelets in blood, conventional blood cell analyzers detect using the Coulter principle (electrical resistance method). Its basic principle is to measure the volume and number of particles by utilizing the resistance change that occurs when particles in a blood sample pass through a detection hole. However, in actual detection, the volume of small-volume white blood cell fragments is very similar to the volume of platelets. Due to this similarity in volume, the width of the resistance change becomes difficult to distinguish, resulting in a counting error. Especially in samples with a high concentration of white blood cell fragments, the number of white blood cell fragments is misjudged as the number of platelets, and as a result, the accuracy of platelet counting is significantly reduced.

[0003] To solve this problem, the scattered light method has been introduced in some technologies. In this method, the forward scattered light (FSC) signal is used to represent the volume size of particles, and the side scattered light (SSC) signal reflects the complexity inside the particles. However, the scattered light method still has obvious limitations in actual applications. The forward scattered light signal of small-volume white blood cell fragments is very similar to that of platelets, and the two cannot be effectively distinguished by the FSC signal. On the other hand, although the side scattered light can represent the complexity inside the particles, the complexity of small-volume white blood cell fragments is low, and there is also a significant overlap with the SSC signal of platelets. Therefore, the discrimination effect using the two-dimensional scatter plot (FSC-SSC plot) is limited.

[0004] These two methods still cannot completely remove the interference caused by white blood cell fragments to platelet counting. Especially in large-scale detection scenarios, due to the diversity of samples and the variation of fragment ratios, the limitations of traditional methods become even more prominent, and the requirements for the accuracy and consistency of platelet counting cannot be met.

Summary of the Invention

Problems to be Solved by the Invention

[0005] 1) Technical problems to be solved This invention provides a quality control method for blood cell testing in medical examinations, and aims to solve the problem in conventional platelet count tests where small volumes of leukocyte fragments are easily misidentified as platelets, which in turn affects the accuracy of platelet counts. [Means for solving the problem]

[0006] 2) Technical plan To achieve the above objective, the present invention provides the following technical solution: A method for quality control of blood cell tests in medical testing, Using the electrical resistance method, the initial number of platelets in the sample to be measured is obtained, Based on the scattering method, a two-dimensional scattering scatter plot of the sample to be measured is obtained, where the horizontal axis of the two-dimensional scattering scatter plot represents the lateral scattered light intensity and the vertical axis represents the forward scattered light intensity. In the aforementioned two-dimensional scattering scatter plot, the total light intensity set is determined based on the sum of the side-scattered light intensities and the sum of the forward-scattered light intensities, According to a predetermined correction rule, if the total light intensity set within a set region in the two-dimensional scattering plot is located in a predetermined first light intensity interval, a linear correction is performed on the initial number of platelets. If the total light intensity set within the aforementioned setting region is located in a predetermined second light intensity interval, the method includes performing a nonlinear correction on the initial number of platelets. The process for constructing the aforementioned correction rule is as follows: Obtaining blood sample sets, which include patient sample sets and health sample sets, Based on the total light intensity set of the designated region in the two-dimensional scattering scatter plot of the health sample set, the first light intensity interval is determined, and based on the total light intensity set of the designated region in the two-dimensional scattering scatter plot of the patient sample set, the second light intensity interval is determined. This includes fluorescent staining of leukocyte fragments in the blood sample set, determining the number of leukocyte fragments in the blood sample set, constructing a linear correction function based on the number of leukocyte fragments in the healthy sample set, and constructing a nonlinear correction function based on the number of leukocyte fragments in the patient sample set.

[0007] Furthermore, the fluorescent staining of leukocyte fragments specifically refers to staining the nucleic acids within the leukocyte fragments.

[0008] Furthermore, the dilution concentration of each blood sample in the blood sample set is the same. After obtaining the two-dimensional scatter plot for each blood sample using the light scattering method, the leukocyte fragments are stained so that they have a fluorescence signal that can be distinguished from platelets, and the number of leukocyte fragments in each blood sample is calculated.

[0009] Furthermore, in the two-dimensional scattering plot, the total light intensity set within the set region is The file is TIFF2026116781000002.tif9168, and here, TIFF2026116781000003.tif8168 is the sum of the lateral scattered light intensities of leukocyte fragments and platelets within the defined region. TIFF2026116781000004.tif7168 is the sum of the forward scattered light intensities of leukocyte fragments and platelets within the defined region.

[0010] Furthermore, the step of determining the setting area is: Obtain a two-dimensional scatter plot of each blood sample in the aforementioned health sample set, In each two-dimensional scatter plot, the initial region is determined based on the intersection of the distribution regions of platelets and leukocyte fragments, The initial region in each two-dimensional scatter plot. Total light intensity set To calculate and perform statistics on TIFF2026116781000005.tif9168, This includes defining the initial region with the highest consistency in total light intensity set, based on a stability analysis method, as the designated region.

[0011] Furthermore, in the healthy sample set, calculate the set of total light intensities in the set region in the two-dimensional scattering scatter diagram of each of the blood samples, and from among them the set of maximum total light intensities TIFF2026116781000006.tif9168 and the set of minimum total light intensities TIFF2026116781000007.tif9168 are extracted, and the first light intensity interval is given by the following formula: [Number] Here, TIFF2026116781000009.tif6168 is the set margin.

[0012] Furthermore, in the patient sample set, calculate the set of total light intensities in the set region in the two-dimensional scattering scatter diagram of each of the blood samples, and from among them the set of maximum total light intensities TIFF2026116781000010.tif10168 and the set of minimum total light intensities TIFF2026116781000011.tif9168 are extracted, and the second light intensity interval is given by the following formula: [Number] Here, TIFF2026116781000013.tif7168 is the set margin. [Advantages of the Invention]

[0013] (III) Beneficial Effects Compared with the prior art, the present invention has the following beneficial effects.

[0014] The present invention constructs a correction rule suitable for platelet count based on the experimental data of a blood sample set. Among them, using the group experimental data of healthy samples and patient samples, fluorescent staining labels are applied to the leukocyte fragments in the sample set, and after calculating the number of leukocyte fragments, a linear correction function and a non-linear correction function are constructed respectively. For the blood sample before leukocyte fragment staining treatment, a first light intensity interval for applying linear correction is determined based on the total light intensity set of the set area in the two-dimensional scatter plot of the healthy sample set, and a second light intensity interval for applying non-linear correction is determined based on the total light intensity set of the set area in the two-dimensional scatter plot of the patient sample set.

[0015] Perform a normal blood test on the blood sample to be measured. Using the obtained initial platelet count and two-dimensional scatter plot, calculate the total light intensity set of the set area in the two-dimensional scatter plot, determine the corresponding light intensity interval, and apply an appropriate correction rule to correct the initial platelet count and ensure the accuracy of the platelet measurement result.

Brief Description of the Drawings

[0016] [Figure 1] It is a schematic diagram of the flow of the quality control method for blood cell examination in medical examination provided by the embodiment of the present invention. [Figure 2] In the quality control method for blood cell examination in medical examination provided by the embodiment of the present invention, it is a schematic diagram of the flow for obtaining a preset correction rule. [Figure 3] In the quality control method for blood cell examination in medical examination provided by the embodiment of the present invention, it is a schematic diagram of the flow for defining a set area. [Figure 4] In the quality control method for blood cell examination in medical examination provided by the embodiment of the present invention, it is a schematic diagram of the distribution of each type of blood cell in the obtained two-dimensional scatter plot. [Figure 5] In the quality control method for blood cell examination in medical examination provided by the embodiment of the present invention, it is a schematic diagram for limiting the set area A of platelets and leukocyte fragments in the two-dimensional scatter plot.

Modes for Carrying Out the Invention

[0017] The technical solutions in embodiments of the present invention will be described clearly and completely below with reference to the drawings of the embodiments. Clearly, the embodiments described are only some, and not all, embodiments of the present invention. All other embodiments that can be obtained by those skilled in the art without creative work based on embodiments of the present invention are included within the scope of protection of the present invention.

[0018] In the description of this invention, terms relating to orientation or positional relationships, such as "vertical direction," "horizontal direction," "length," "width," "thickness," "top," "bottom," "front," "back," "left," "right," "perpendicular," "horizontal," "top," "bottom," "inside," and "outside," are based on the orientation or positional relationships shown in the drawings and are intended to facilitate the explanation and simplify understanding of the invention. They do not suggest or imply that the device or element in question must be configured and operated in a specific orientation. Therefore, these should not be construed as limitations on the invention.

[0019] Furthermore, terms such as "first" and "second" are merely descriptive for the purpose of distinction and cannot be understood as indicating or implying relative importance.

[0020] Furthermore, the features of the embodiments of the present invention can be combined with each other, as long as they do not contradict each other.

[0021] A diluted blood sample is introduced into a chamber with a tiny detection pore, and platelets in the blood cells are counted using electrical impedance (Coulter principle). As cells in the blood pass through the detection pore, they change impedance values, and the volume and number of cells are detected based on these changes.

[0022] When measuring platelets in blood cells using electrical impedance, the inventors discovered that leukocyte fragments are inevitably present in diluted blood samples. The volume ranges of leukocyte fragments and platelets are very close, typically between 2 μm and 4 μm. Since electrical impedance counts primarily based on particle volume, small-volume leukocyte fragments can be misidentified as platelets by the system, resulting in an overcount of platelets.

[0023] If the number of leukocyte fragments in a blood sample is small, the impact on the overall platelet count result is minimal. However, if the leukocyte count in the sample is high, or if the sample is affected by sample preparation factors such as vigorous shaking or hemolysis, the number of leukocyte fragments increases significantly, worsening the counting error.

[0024] To solve this problem, conventional techniques employ scattered light methods, combining optical detection and electrical resistance. In these techniques, the forward scattered light (FSC) signal in blood cell measurements reflects the particle volume size; typically, larger particles produce strong forward scattered light. Platelets and leukocyte fragments have similar volumes but subtle differences. The side scattered light (SSC) signal reflects the internal structure and complexity of the particle, such as the granular structure of the cell and the ratio of nucleus to cytoplasm. In practice, the volumes of small leukocyte fragments and platelets are usually very similar, so they appear almost identical in the FSC signal. Due to this similarity, the FSC axis (forward scattered light intensity) cannot effectively distinguish between leukocyte fragments and platelets in a two-dimensional scattering diagram. Leukocytes, especially leukocyte fragments, have high internal structural complexity, but their small volume results in a weak scattering signal and low complexity. Platelets typically lack a nucleus, so their SSC signal is relatively weak. However, there is some overlap between the SSC signals of leukocyte fragments and platelets, and especially with small volumes of fragments, the scattered light intensity is similar to that of platelets, making it difficult to distinguish between the two.

[0025] Considering the above issues, it is understandable that when a large number of leukocyte fragments are present in a sample, leukocyte fragments and platelets have a high degree of similarity in volume, making it difficult to directly distinguish their numerical relationship using Coulter's principle based on changes in electrical resistance or optical methods based on forward and side-scattered light intensity. In actual measurements, this misjudgment due to volume approximation is often difficult to eliminate with simple calibration or filtering algorithms. In particular, in samples with a high number of leukocyte fragments, such as blood cells from inflamed or diseased patients, the high content of leukocytes and leukocyte fragments means that the measurement results of existing platelet counting methods using electrical resistance are significantly affected by errors due to leukocyte fragments.

[0026] Therefore, in order to address the above-mentioned problems, embodiments of the present invention provide a method for quality control of blood cell tests in medical testing. Specifically, referring to Figure 1, Figure 1 is a workflow diagram of the method for quality control of blood cell tests in medical testing provided by the present invention.

[0027] First, perform S1: obtain the initial number of platelets in the sample to be measured using the electrical resistance method. In some embodiments of the present invention, based on the resistance method, obtain the electrical resistance signal detected after the blood sample has passed through the pore.

[0028] First, an anticoagulant blood sample, such as a blood sample to which an anticoagulant like EDTA has been added, is collected. The blood sample is then diluted in a specific ratio (usually 1:1000 to 1:5000), and a low-conductivity electrolyte such as sodium chloride solution is used to prevent cell aggregation and overlapping, thereby reducing cell density and ensuring that cells can pass through micropores as single particles, thereby improving detection accuracy.

[0029] Based on the Coulter principle, cells are passed through micropores (detection pores) one by one. The typical diameter of the micropores is in the range of 50 μm to 100 μm (optimized range for platelet counting). High-sensitivity electrodes are placed on both sides of the micropore, and a stable DC electric field is applied. The cells act as insulators, and as they move through the micropores, they instantaneously change the resistance within the micropores, causing a change in the electrical signal. High-frequency sampling captures the instantaneous signal of the resistance change.

[0030] Perform S2: Based on the scattering method, a two-dimensional scattering scatter plot of the sample to be measured is obtained, where the horizontal axis of the two-dimensional scattering scatter plot is the lateral scattering intensity and the vertical axis is the forward scattering intensity.

[0031] 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 blood analyzer. Specifically, a laser light source (usually a laser diode) of a light scattermeter is used to emit a laser beam and irradiate a flowing blood sample. When the laser beam irradiates different cells in the blood sample (platelets, white blood cells, red blood cells, etc.), the cells scatter the light, generating scattered light signals at different angles. Of these, forward scatter (FSC) refers to the signal generated in the direction of laser beam propagation by the light signals scattered by the cells after the laser beam has passed through the blood sample, and the FSC signal mainly reflects the volume size of the cell particles. Larger cells or particles scatter strong forward scatter signals. Side scatter (SSC) refers to the scattering signals generated perpendicular to the direction of laser beam propagation 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 strong side scatter.

[0032] A light scattermeter uses a photoelectron detector (e.g., a photodiode) to collect scattered light signals. The detector converts the scattered light signals into electrical signals, which are then converted into digital signals. By comparing these digital signals with a reference standard, the intensity value of the scattered light is obtained.

[0033] In the two-dimensional scatter plot obtained in S2, the horizontal axis represents the side scatter intensity (SSC), which is related to the complexity of the cell particle and indicates the internal structure and complexity of the cell particle. Among these, complex cells such as leukocytes show a larger scatter intensity in this dimension. The vertical axis represents the forward scatter intensity (FSC) and the volume size of the particle. Larger particles (e.g., macroleukocytes) produce a stronger forward scatter signal; that is, large blood cells are distributed in a region with a larger FSC in the two-dimensional scatter plot. On the other hand, small particles (e.g., platelets) produce a weak signal; that is, small blood cells are distributed in a region with a small FSC in the two-dimensional scatter plot.

[0034] Based on these signals, a two-dimensional scatter plot (FSC-SSC plot) is generated. Referring to Figure 4, this scatter plot shows how various cells in the blood sample (platelets, white blood cells, red blood cells, etc.) are scattered in the two dimensions of FSC and SSC.

[0035] Perform S3: In the two-dimensional scatter plot, the total light intensity set is determined based on the sum of the side scattered light intensities and the sum of the forward scattered light intensities. Here, in the two-dimensional scatter plot, the total light intensity set within the set region is The file is TIFF2026116781000014.tif10168, and here, TIFF2026116781000015.tif9168 is the sum of the lateral scattered light intensities of leukocyte fragments and platelets within the defined region. TIFF2026116781000016.tif8168 is the sum of the forward scattered light intensities of leukocyte fragments and platelets within the defined region.

[0036] By decomposing the total intensity value into two parts—lateral total light intensity and forward total light intensity—independent characteristics of each direction can be preserved rather than directly integrating them into a single value. This is understood to be helpful in analyzing the lateral and forward contributions separately. Furthermore, since the analysis of two-dimensional scatter plots in the laboratory is essentially a calculation logic based on two-dimensional coordinates, representing total light intensity in a two-dimensional format is more naturally suited to this mode of analysis, and the two-dimensional total intensity format can describe the overlapping characteristics of platelets and leukocyte fragments in more detail.

[0037] Perform S4: According to a pre-defined correction rule, if the total light intensity set within the defined region in the two-dimensional scatter plot is located in a pre-defined first light intensity interval, a linear correction is applied to the initial number of platelets.

[0038] If the total light intensity set within the set region in the two-dimensional scatter plot does not belong to the first light intensity interval, perform S5; if the total light intensity set within the set region is located in the pre-defined second light intensity interval, perform a nonlinear correction on the initial number of platelets.

[0039] Referring to the pre-configured correction rule acquisition flow diagram shown in Figure 2 for the two processes described above, the specific operation flow for establishing the pre-configured rules is as follows:

[0040] First, perform S41: obtain a blood sample set, which includes both a patient sample set and a healthy sample set. The experimental data necessary for constructing the correction rules includes both the healthy sample set and the patient sample set. The two sets have different characteristics and will be used to establish linear and nonlinear correction rules, respectively.

[0041] A healthy sample set consists of blood samples from healthy individuals and is characterized by a relatively stable ratio of platelets to leukocyte fragments, typically exhibiting a linear distribution within the set range. Healthy individuals without infection, inflammation, or other diseases affecting blood properties can be selected. A patient sample set, on the other hand, is taken from individuals with specific diseases (such as inflammation, infection, or blood disorders) and may exhibit a significantly increased number of leukocyte fragments compared to a healthy sample set. Furthermore, platelets and leukocyte fragments may exhibit a non-linear distribution within the set range. It is important to note that the dilution concentration of each blood sample within the blood sample set is identical.

[0042] Perform S42: Determine the first light intensity interval based on the total light intensity set of the set region in the two-dimensional scattering scatter plot of the healthy sample set, and determine the second light intensity interval based on the total light intensity set of the set region in the two-dimensional scattering scatter plot of the patient sample set.

[0043] In some embodiments of the present invention, referring to the flowchart shown in Figure 3, the definition of the platelet and leukocyte fragment setting regions includes the following steps.

[0044] First, perform S421: obtain a two-dimensional scatter plot of each blood sample in the health sample set.

[0045] Perform S422: In each two-dimensional scatter plot, determine the initial region based on the intersection of the distribution regions of platelets and leukocyte fragments. In each two-dimensional scatter plot, determine the distribution range where platelets and leukocyte fragments overlap based on existing experimental experience or characteristic curves in the literature, and define the initial region.

[0046] Perform S423: Initial region in each two-dimensional scatter plot Total light intensity set The TIFF2026116781000017.tif10168 data is calculated and statistically analyzed. Specifically, in each two-dimensional scatter plot, all scatter point data within the initial region is statistically analyzed, and the total light intensity set on the horizontal axis (lateral light intensity) and vertical axis (forward light intensity) is calculated.

[0047] Perform S424: Based on stability analysis, the initial region with the highest consistency in total light intensity set is designated as the setting region. By analyzing the stability of the light intensity distribution of scattered points within the initial region in the two-dimensional scatter plot of the healthy sample set, a region with statistically high consistency is determined as the final setting region, i.e., region A in Figure 5, and can be used for subsequent setting region correction of platelets and leukocyte fragments. Here, the highest consistency in total light intensity set refers to the initial region where the light intensity distribution is most concentrated and stable. By selecting such a region as the setting region through stability analysis (calculation of mean and standard deviation, etc.), the reliability and accuracy of the correction method can be greatly improved.

[0048] Returning to S42, in the healthy sample set, platelet count and leukocyte fragment count exhibit linear distribution characteristics within the physiological range, and within the defined region in the two-dimensional scatter plot, the light intensity distribution of these two components is relatively stable. Since healthy samples are not affected by pathological factors, the total light intensity set within the defined region has less variability and higher consistency, and this consistency allows the light intensity range calculated for the healthy sample set (i.e., the first light intensity interval) to be used as a standard for subsequent analysis and correction.

[0049] It should be noted that health sample sets typically cover normal individuals of different sexes, ages, and constitutions, making their statistical results more universal and representative. The determined first light intensity interval can be adapted to the normal blood characteristics of the majority of individuals, providing a standardized criterion for subsequent analyses.

[0050] In patient sample sets, the number of leukocyte fragments can increase significantly due to pathological conditions (e.g., inflammation, immune response). Therefore, platelets and leukocyte fragments exhibit nonlinear characteristics in their distribution within the defined region. By calculating the total light intensity set of the defined region using a scatter plot of the patient sample set, the light intensity distribution in pathological conditions can be accurately reflected, providing a basis for correcting abnormal samples.

[0051] What can be understood here is that the advantage of selecting a healthy sample set to determine the first light intensity interval is that the data is stable, provides a universal standard, and helps 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 features, adapts to complex distributions, and provides an optimization direction for the correction model. By combining both, we achieve mutual complementarity between the standard and dynamic characteristics, and build more accurate and adaptable correction rules.

[0052] More specifically, in a health sample set, the total light intensity set of a defined region in the two-dimensional scattering scatter plot of each blood sample is calculated, and from there... Maximum total light intensity cluster TIFF2026116781000018.tif9168 and Minimum total light intensity cluster Extracting TIFF2026116781000019.tif9168, the first light intensity interval is given by the following equation:

number

[0053] Set margin Regarding TIFF2026116781000024.tif8168, in some embodiments of the present invention, the calculation of mean and standard deviation is introduced, that is, by statistically calculating the mean and standard deviation of each dimensional value in the total light intensity set, light intensity intervals based on the data distribution can be defined. This allows for a better reflection of the distribution characteristics of the data. When the data has large fluctuations or a heterogeneous distribution, statistically based intervals can more effectively capture the actual range of fluctuation in the data and improve the accuracy of the correction rules.

[0054] Similarly, in the patient sample set, the total light intensity set of the set region in the two-dimensional scattering scatter plot of each blood sample is calculated, and from there, Maximum total light intensity cluster TIFF2026116781000025.tif11168 and Minimum total light intensity cluster Extracting TIFF2026116781000026.tif10168, the second light intensity interval is given by the following equation:

number

[0055] Specifically, light intensity intervals are used to define two different correction strategies. If the total light intensity set of the defined region falls within the first light intensity interval, it can be determined that the influence of leukocyte fragments in the sample on platelets is small. In this case, correcting the platelet count obtained from this blood sample is relatively straightforward. Due to the minimal interference from leukocyte fragments, in some feasible examples of the present invention, when the influence of leukocyte fragments on platelets is small, the platelet count obtained is corrected using a linear model or linear function. This is because the interference between platelet count and leukocyte fragments exhibits a relatively simple linear relationship, and linear correction can adjust the platelet count quickly and effectively while maintaining the simplicity and efficiency of the correction process. Furthermore, the linear correction method is easy to calculate, fast to process, suitable for large-scale data processing, does not impose excessive adjustments on platelet counts, and can strike a good balance between accuracy and efficiency in situations where detection results are demanding.

[0056] When the total light intensity set of the defined region falls within the second light intensity interval, the influence of leukocyte fragments exhibits a complex nonlinear relationship, requiring the adoption of a more complex correction function. In some feasible examples of the present invention, the platelet count obtained is corrected using a nonlinear model or nonlinear function. This correction method allows for more accurate adjustment of the platelet count and avoids the shortcomings of linear correction.

[0057] The above method effectively defines the light intensity ranges for the first and second light intensity intervals, allowing for the application of different correction strategies to regions with varying degrees of influence, thereby ensuring the accuracy and reliability of platelet counting.

[0058] Regarding how to perform linear or nonlinear corrections to platelet counts, in some implementable examples of the present invention, S43 is performed: fluorescent staining is performed on leukocyte fragments in the blood sample set; the number of leukocyte fragments in the blood sample set is determined; a linear correction function is constructed based on the number of leukocyte fragments in the healthy sample set; and a nonlinear correction function is constructed based on the number of leukocyte fragments in the patient sample set.

[0059] In some embodiments of the present invention, fluorescent staining of leukocyte fragments specifically refers to staining the nucleic acids in the leukocyte fragments. The selection of a fluorescent dye is key when performing specific nucleic acid staining on leukocytes. It is necessary to select a dye that is highly specific to leukocyte fragments and does not interfere with platelets. In some feasible examples of the present invention, leukocyte fragments are labeled by conjugating a CD45 antibody with a fluorescent dye. CD45 is a marker molecule for leukocytes, and almost all leukocytes express CD45. By using a fluorescent dye conjugated with a CD45 antibody (e.g., FITC, PE, or APC dye), leukocytes and their fragments can be specifically labeled. In other feasible examples of the present invention, Hoechst 33342 or DAPI dyes are used. These dyes can bind to nuclear DNA and are typically used to label all leukocyte fragments or nucleic acids, helping to identify leukocyte fragments that possess nucleic acid material.

[0060] A specific fluorescent dye (e.g., FITC dye labeled with CD45 antibody) is added to a diluted blood sample, and the fluorescence signal is acquired using a device such as a flow cytometer or fluorescence microscope.

[0061] It can be observed that leukocyte fragments fluoresce at specific wavelengths after staining, while platelets do not exhibit a fluorescent signal. After staining the leukocyte fragments, their number can be calculated using a flow cytometer, imaging flow cytometer, or fully automated blood analyzer.

[0062] Based on the fluorescence staining statistical data of leukocyte fragments, linear and nonlinear correction functions are constructed, respectively. Specifically, the blood sample sets are divided into healthy sample sets and patient sample sets. The number of leukocyte fragments obtained by fluorescence staining is as follows: TIFF2026116781000031.tif10168 The initial number of platelets This is denoted as TIFF2026116781000032.tif11168. In a two-dimensional scatter plot, the number of leukocyte fragments and platelets cannot be directly distinguished within the defined region, so a correction function is needed to estimate the number of leukocyte fragments and platelets within the defined region.

[0063] A linear correction function is constructed based on a healthy sample set. Specifically, each blood sample in the healthy sample set is subjected to fluorescent staining. Number of white blood cell fragments TIFF2026116781000033.tif11168 and Initial number of platelets We will statistically analyze TIFF2026116781000034.tif9168. In blood samples from a healthy sample set, leukocyte fragments and platelets show a linear proportional relationship within the set region:

number

[0064] Based on the total light intensity signal of a defined region in a two-dimensional scatter plot, the ratio of leukocyte fragments to platelets is determined using distribution statistics, and then k1 is obtained by fitting data from a healthy sample set.

[0065] Therefore, the linear correction function between platelet count and leukocyte fragment count is given by the following equation:

number

[0066] Note that the initial platelet count here is the initial number of platelets in the sample being measured, obtained by the electrical resistance method.

[0067] A nonlinear correction function is constructed based on the patient sample set. Specifically, each blood sample in the patient sample set is subjected to fluorescent staining. Number of white blood cell fragments TIFF2026116781000039.tif12168 and Initial number of platelets We will statistically analyze TIFF2026116781000040.tif11168. In some laboratory examples, in patient sample sets, leukocyte fragments and platelets show an exponential relationship within a set region.

[0068] Experimental data analysis revealed that the number of leukocyte fragments and platelets within a defined region in patient samples satisfies the following relationship:

number

[0069] The correction functions for exponential functions are as follows:

number

[0070] Furthermore, in some embodiments of the present invention, it is considered that if the total light intensity set of a set region in the sample under measurement exceeds the value of the second light intensity interval, the influence of leukocyte fragments in the sample under measurement on the platelet count is too great, and conventional platelet counting methods may not be able to provide accurate results. This situation may indicate that there are many leukocyte fragments in the blood sample, or that the scattering spectral characteristics of the fragments overlap so much with those of platelets that they cannot be effectively distinguished by conventional correction methods. Therefore, for such samples, it is necessary to take measures to re-detect in order to ensure the accuracy of the platelet count.

[0071] The above describes only preferred embodiments of the present invention and does not limit the invention. The scope of protection of the present invention is subject to the claims, and equivalent structural modifications made based on the description and drawings of the present invention should similarly be included within the scope of protection of the present invention.

Claims

1. A method for quality control of blood cell tests in medical testing, Using the electrical resistance method, the initial number of platelets in the sample to be measured is obtained, Based on the scattering method, a two-dimensional scattering scatter plot of the sample to be measured is obtained, where the horizontal axis of the two-dimensional scattering scatter plot represents the lateral scattered light intensity and the vertical axis represents the forward scattered light intensity. In the aforementioned two-dimensional scattering scatter plot, the total light intensity set is determined based on the sum of the side-scattered light intensities and the sum of the forward-scattered light intensities, According to a predetermined correction rule, if the total light intensity set within a set region in the two-dimensional scattering plot is located in a predetermined first light intensity interval, a linear correction is performed on the initial number of platelets. If the total light intensity set within the aforementioned setting region is located in a predetermined second light intensity interval, the method includes performing a nonlinear correction on the initial number of platelets. The process for constructing the aforementioned correction rule is as follows: Obtaining blood sample sets, which include patient sample sets and health sample sets, Based on the total light intensity set of the designated region in the two-dimensional scattering scatter plot of the health sample set, the first light intensity interval is determined, and based on the total light intensity set of the designated region in the two-dimensional scattering scatter plot of the patient sample set, the second light intensity interval is determined. A method for quality control of blood cell tests in medical testing, characterized by comprising: fluorescent staining of leukocyte fragments in the blood sample set; determining the number of leukocyte fragments in the blood sample set; constructing a linear correction function based on the number of leukocyte fragments in the healthy sample set; and constructing a nonlinear correction function based on the number of leukocyte fragments in the patient sample set.

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

3. A method for quality control of 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, a two-dimensional scattering scatter plot is obtained for each blood sample by light scattering, the leukocyte fragments are stained so that the leukocyte fragments have a fluorescence signal that can be distinguished from platelets, and the number of leukocyte fragments in each blood sample is calculated.

4. In the two-dimensional scattering scatter plot, the total light intensity set within the set region is And here, This is the sum of the lateral scattered light intensities of leukocyte fragments and platelets within the set region. A method for quality control of blood cell testing in medical testing according to claim 1, characterized in that is the sum of the forward scattered light intensities of leukocyte fragments and platelets within a set region.

5. The step of determining the aforementioned setting area is: Obtain a two-dimensional scatter plot of each blood sample in the aforementioned health sample set, In each two-dimensional scatter plot, the initial region is determined based on the intersection of the distribution regions of platelets and leukocyte fragments, The total light intensity of the initial region in each two-dimensional scatter plot. Calculating and statistically analyzing, A method for quality control of blood cell testing in medical testing according to claim 4, characterized in that, based on a stability analysis method, the initial region having the highest consistency in total light intensity aggregation is designated as the setting region.

6. In the aforementioned health sample set, the total light intensity set of the specified region in the two-dimensional scattering scatter plot of each blood sample is calculated, and the largest total light intensity set is selected from among them. 【number】 and minimum total light intensity cluster 【number】 The first light intensity interval is given by the following equation: [Math 1] Here, 【number】 The method for quality control of blood cell testing in medical testing according to claim 5, characterized in that the set margin is.

7. In the patient sample set, the total light intensity set of the specified region in the two-dimensional scatter plot of each blood sample is calculated, and the maximum total light intensity set is selected from among them. 【number】 and minimum total light intensity cluster 【number】 The second light intensity interval is given by the following equation: [Math 2] Here, 【number】 The method for quality control of blood cell testing in medical testing according to claim 5, characterized in that the set margin is.

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