WO2018148946A1 - 红细胞碎片识别方法和装置、血液细胞分析仪及分析方法 - Google Patents

红细胞碎片识别方法和装置、血液细胞分析仪及分析方法 Download PDF

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WO2018148946A1
WO2018148946A1 PCT/CN2017/073992 CN2017073992W WO2018148946A1 WO 2018148946 A1 WO2018148946 A1 WO 2018148946A1 CN 2017073992 W CN2017073992 W CN 2017073992W WO 2018148946 A1 WO2018148946 A1 WO 2018148946A1
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Prior art keywords
blood cell
red blood
cell
particle group
scattered light
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PCT/CN2017/073992
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English (en)
French (fr)
Inventor
郑文波
叶波
祁欢
余珊
李秀娟
李朝阳
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深圳迈瑞生物医疗电子股份有限公司
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Priority to EP17896649.5A priority Critical patent/EP3584565B1/en
Priority to CN201780084848.9A priority patent/CN110226083B/zh
Priority to PCT/CN2017/073992 priority patent/WO2018148946A1/zh
Publication of WO2018148946A1 publication Critical patent/WO2018148946A1/zh
Priority to US16/537,674 priority patent/US11125687B2/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Electro-optical investigation, e.g. flow cytometers
    • G01N15/1456—Electro-optical investigation, e.g. flow cytometers without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals
    • G01N15/1459—Electro-optical investigation, e.g. flow cytometers without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals the analysis being performed on a sample stream
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/49—Scattering, i.e. diffuse reflection within a body or fluid
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64—Fluorescence; Phosphorescence
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G01N33/487—Physical analysis of biological material of liquid biological material
    • G01N33/49—Blood
    • G01N2015/012—
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N2015/1006—Investigating individual particles for cytology
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Electro-optical investigation, e.g. flow cytometers
    • G01N2015/1402—Data analysis by thresholding or gating operations performed on the acquired signals or stored data

Definitions

  • the invention relates to the field of blood detection, in particular to a method and a device for identifying red blood cell fragments, a blood cell analyzer and a blood cell analysis method.
  • red blood cell debris that is, the ratio of red blood cells to all red blood cells is less than 1%. Clinically, it is sometimes necessary to detect red blood cell debris in blood samples for medical reference. Therefore, it is required to count red blood cell fragments accurately and reliably.
  • the prior art provides a method for counting red blood cell fragments, which includes:
  • Nucleic acid dyes are used to stain blood cells. Cells pass through the detection area one by one to detect forward scattered light and fluorescence information of individual cells. Based on scattered light and fluorescence information, cells are divided into three categories: white blood cells, red blood cells, platelets, and red blood cell regions. The number of particles is denoted as A;
  • a method for identifying red blood cell fragments comprising the following steps:
  • a red blood cell debris particle group is distinguished from each cell particle.
  • a red blood cell debris identification device comprising:
  • An acquisition unit configured to acquire a side scattered light signal and a fluorescent signal of the cell particles in the sample liquid
  • the recognition unit is configured to distinguish and identify the red blood cell debris particle group from each of the cell particles according to the side scattered light signal and the fluorescence signal of the cell particle.
  • the red blood cell debris identification method and apparatus can accurately and accurately identify the red blood cell debris particle group from each cell particle by processing and analyzing the side scattered light signal and the fluorescence signal of the sample liquid. According to the fluorescence and side scatter light which characterize the nucleic acid content in the cell particles, the red blood cell debris can be accurately identified, and the accuracy of red blood cell debris recognition is improved.
  • a blood cell analyzer comprising:
  • a sampling device for collecting blood samples
  • a sample preparation device for processing the blood sample and reagent delivered by the sampling device to prepare a sample liquid; and detecting means for performing light irradiation on the sample liquid to collect each cell particle in the sample liquid Optical information generated by illumination, the optical information comprising a side scattered light signal and a fluorescent signal;
  • a conveying device for conveying the sample liquid in the sample preparation device to the detecting device, so that the cells in the sample liquid pass one by one through the detection area of the detecting device;
  • a processor configured to receive optical information obtained by the detecting device, according to The optical information distinguishes the red blood cell debris particle group from each cell particle.
  • a blood cell analysis method comprising the following steps:
  • optical information of the cell particles in the sample solution including a side scattered light signal and a fluorescence signal
  • a red blood cell debris particle group is distinguished from each of the cell particles based on the optical information.
  • the red blood cell debris particle group is distinguished from each cell particle based on the side scattered light signal and the fluorescence signal of the cell particle.
  • the obtained red blood cell fragment count accuracy is better than the prior art, and the error of the red blood cell debris particle group recognition count is reduced.
  • FIG. 1 is a microscopic blood cell diagram of a blood sample provided in the prior art
  • FIG. 2 is a two-dimensional scattergram of a forward scattered light signal and a fluorescent signal of the blood sample shown in FIG. 1;
  • FIG. 3 is a flowchart of a method for identifying red blood cell fragments according to an embodiment of the present invention
  • FIG. 4 is a flowchart of a method for identifying red blood cell fragments according to another embodiment of the present invention.
  • Figure 5 is a two-dimensional scattergram of a side-scattered light signal and a fluorescent signal of a normal blood sample provided in the present invention
  • 6 is a two-dimensional scattergram of a side-scattered light signal and a fluorescent signal of a blood sample of red blood cell debris provided in the present invention
  • FIG. 7 is a flowchart of a method for identifying red blood cell fragments according to still another embodiment of the present invention.
  • FIG. 9 is a schematic structural diagram of a red blood cell debris identification device according to an embodiment of the present invention.
  • FIG. 10 is a schematic structural diagram of a red blood cell debris identification device according to another embodiment of the present invention.
  • FIG. 11 is a schematic structural view of a red blood cell debris identifying device according to still another embodiment of the present invention.
  • Figure 13 is a graph showing the comparison of the red blood cell fragment count obtained from the two-dimensional scattergram of the side-scattered light signal and the fluorescence signal and the manual blood count of the four blood samples according to the four blood samples provided by the present invention
  • Figure 14 is a schematic structural view of a blood analyzer according to an embodiment of the present invention.
  • 15 is a flow chart of a blood cell analysis method according to an embodiment of the present invention.
  • Figure 16 is a flow chart showing a blood cell analysis method in another embodiment of the present invention.
  • FIG. 1 and FIG. 2 show through research that in the existing red blood cell debris identification method, when referring to FIG. 1 and FIG. 2, when using forward scattered light signals and fluorescent signals for identification, the forward scattered light is used to characterize the volume of the cells.
  • the sample has more small red blood cells due to certain diseases, the small red blood cells are small in size and easily confused with red blood cell debris, thereby disturbing the counting of red blood cell debris.
  • Figure 1 shows a schematic diagram of microscopic blood cells during artificial microscopy
  • Figure 2 shows a two-dimensional scatter plot of red blood cell debris based on forward scattered light signals and fluorescent signals. As shown in Fig.
  • the red blood cell fragments are helmet-shaped and angular, and the small red blood cells are spherical and crescent-shaped, and the red blood cells are easily confused with the red blood cell fragments, and the accuracy of recognition and counting is not high.
  • the red blood cell fragments of the blood sample are adjacent to the small red blood cell area, and there is a partial overlap phenomenon, and the count of the red blood cell fragments obtained by the Fig. 2 is 14.5%.
  • the number of red blood cell fragments obtained by artificial microscopy was 7.2%.
  • an embodiment of the present invention provides a method for identifying red blood cell fragments, the red blood cell
  • the fragment identification method includes the following steps:
  • S320 Obtain a side scattered light signal and a fluorescent signal of the cell particles in the sample liquid
  • the sample solution refers to a sample obtained by reacting a blood sample with a reagent.
  • the optical information of the cellular particles in the sample fluid is obtained by a blood cell analyzer.
  • the conveying device automatically controls the sample liquid to be sent to the detecting device of the blood cell analyzer, so that the cells in the sample liquid pass through the detecting area in the detecting device one by one, and collect the side scattered light signal and fluorescence of the cell particles in the sample liquid.
  • the signal wherein the sample liquid is automatically controlled and transported by the conveying device, reduces the influence of human factors and improves the recognition accuracy.
  • the optical information for detecting the collected cell particles includes a side scattered light signal and a fluorescent signal for identifying red blood cell fragments.
  • the optical information may further include other information required for detection. Not limited.
  • S330 distinguishing and identifying a red blood cell debris particle group from each cell particle according to the side scattered light signal and the fluorescence signal of the cell particle;
  • red blood cell debris is destroyed by the cell membrane, the non-specific binding of the protein on the cell membrane to the dye in the reagent is reduced, and the fluorescence signal is weakened. Therefore, the red blood cell debris will be weak. Fluorescent signal. At the same time, red blood cell debris is weakened by intracellular hemoglobin, and the side-scattering light signal characterizing the cell contents is attenuated. Therefore, red blood cell fragments generate weak side-scattering light signals.
  • the red blood cell debris particle group can be accurately identified from each cell particle, and the red blood cell debris can be identified.
  • the red blood cell debris identification method in the embodiment can accurately identify the red blood cell fragments according to the fluorescence and the side scattered light which characterize the nucleic acid content in the cell particles, and reduce the error of the red blood cell debris recognition and counting.
  • the step S330 includes:
  • S332 Obtain a first two-dimensional scattergram according to the side scattered light signal and the fluorescence signal of each cell particle;
  • the side-scattered light signals and fluorescent signals of the detected and collected cellular particles are converted to corresponding electrical signals.
  • the cell particle to be tested is detected by a photoelectric sensor
  • the light irradiation generates a side-scattered light signal and a fluorescent signal to be converted into a corresponding electrical signal, and then converts the electrical signal into a corresponding digital signal by using an A/D converter, thereby obtaining the side scattered light intensity of each cell particle and Fluorescence intensity, and the correspondence between the intensity of the side scattered light of the cell particles and the fluorescence intensity is established, and a first two-dimensional scattergram is obtained.
  • the predetermined area may be a blood sample that is compared with a normal human blood sample and a red blood cell fragment, and after statistical analysis, a specific area in the first two-dimensional scattergram is obtained. According to the parameters of the specific region, in the first two-dimensional scattergram of the unknown blood sample, the cell particle group expressed in the preset region is recognized as a red blood cell debris particle group.
  • the blood sample of the normal human blood sample and the red blood cell debris can also be compared, and after statistical analysis, the relative position function of the red blood cell particle group region and the normal human red blood cell particle group region, or other cell particle group regions can be obtained. Using the function, the predetermined region is determined based on the identified region of the red blood cell particle group in the first two-dimensional scatter of the unknown blood sample.
  • the overall fluorescence intensity of the red blood cell debris group is smaller than that of the red blood cell population, and the overall side scattered light intensity is also smaller than the fluorescence intensity of the red blood cell population. That is, the preset area is located at the lower left of the red blood cell scatter group.
  • the overall fluorescence intensity of the red blood cell debris group is smaller than that of the red blood cell group, and the overall side scattered light intensity is also smaller than the fluorescence intensity of the red blood cell group, which means that the fluorescence intensity of all the cell particles in the red blood cell debris group is not
  • the intensity of the side scattered light is smaller than the fluorescence intensity of the cell particles in the red blood cell population and the intensity of the side scattered light.
  • the two-dimensional scattergram obtained by the side-scattered light signal and the fluorescence signal has a strong correlation with the occurrence of red blood cell fragments in the preset region.
  • red cell debris is destroyed by the cell membrane, and the specific binding of the protein and the reagent on the cell membrane is reduced, and the fluorescence signal is weakened. Therefore, the red blood cell debris generates a relatively weak fluorescent signal.
  • red blood cell debris is mechanically destroyed in the body, intracellular hemoglobin is lost, and the side-scattering light signal that characterizes the contents of the cell is weakened. Therefore, red blood cell debris A weak side-scattering light signal is produced.
  • FIG. 5 and FIG. 6 provide a two-dimensional scattergram of the side-scattered light signal and the fluorescence signal of the normal sample liquid (see FIG. 5); the side-scattered light signal of the red blood cell debris sample liquid and A two-dimensional scatter plot of the fluorescent signal (see Figure 6).
  • the abscissa is the fluorescence intensity of the cell particles
  • the ordinate is the side scattered light intensity of the cell particles.
  • the cell particle group appearing in the predetermined region is red blood cell debris.
  • Each cell particle in the sample solution is mapped to the first two-dimensional scattergram according to its fluorescence intensity and the intensity of the side scattered light, thereby distinguishing different cell particle populations.
  • the red blood cell fragments are identified based on the characteristic regions of the scattergram formed by the fluorescence and the side scattered light, and the obtained red blood cell fragment count accuracy is superior to the prior art.
  • a population of cell particles having a fluorescence intensity below the red blood cell particle group and a side scattered light intensity below the red blood cell particle group is recognized as a red blood cell debris particle group.
  • the cell particles located in the lower left region of the red blood cell scatter group are recognized as the red blood cell debris particle group.
  • the two-dimensional scattergram is not limited, and is not limited herein.
  • step S330 the method further comprises the steps of:
  • the counting method of the number of red blood cell debris particles can be obtained by a statistical method of cell particles known in the prior art, and the specific statistical principle thereof will not be described herein.
  • the red blood cell debris identification method further comprises the steps of:
  • the red blood cell fragments and other blood cells are visually distinguished to display a population of red blood cell debris particles, in particular, by way of, for example, color, shape, drawing boundaries or contours.
  • red blood cell debris particles for example, scatters that appear as different colors/shapes, or that draw respective boundaries or contours to distinguish different particle swarms.
  • the red blood cell debris identification method further includes:
  • Obtaining a count value of the red blood cell particle group in the sample liquid for example, obtaining a count value of the red blood cell particle group of the sample liquid from other measurement methods such as an impedance method;
  • the count ratio is obtained based on the count value of the red blood cell debris particle group and the count value of the red blood cell particle group.
  • the red blood cell debris identification method further includes:
  • the sample liquid can be irradiated by a flow blood cell analyzer, and the optical information of the cell particles in the blood can be collected one by one, while the forward scattered light signal of the cell particles in the sample liquid is simultaneously acquired, laterally Scattering light signals and fluorescent signals;
  • S360 classifying red blood cell particle groups according to forward light signals and fluorescent signals of the cell particles
  • S380 acquiring, according to the red blood cell debris particle group and the red blood cell particle group, a count value of the red blood cell debris particle group and a count value of the red blood cell particle group, and/or according to the red blood cell debris particle group and the red blood cell particle The group gets the count ratio.
  • the count values of the two kinds of particle groups can be obtained according to the red blood cell debris particle group and the red blood cell particle group, and the counting ratio of the two particle groups and the red blood cell particle group can be directly obtained, and the counting values of the two kinds of particles are not obtained.
  • the count values of the above two particle groups can also be obtained according to the red blood cell debris particle group and the red blood cell particle group, and the count ratio can be obtained.
  • the classification of the cell particles can be achieved by the forward scattered light signal and the fluorescent signal to distinguish the red blood cell particle population.
  • the side-scattered light signal generally characterizes the cellular contents, so that the red blood cell debris lost in the intracellular hemoglobin can be recognized by the side-scattering light signal and the fluorescent signal to identify the red blood cell debris particle group. Pass By accurately identifying the red blood cell particle population and the red blood cell debris particle group, the count value and/or the counting ratio of the red blood cell debris particle group and the red blood cell particle group can be obtained to obtain accurate and reliable diagnostic information related to the red blood cell debris.
  • step S340 and the step S320 can be performed simultaneously, and the step S330 distinguishes the red blood cell debris particle group from each cell particle according to the side scattered light signal and the fluorescence signal of the cell particle, and step S360, according to step S360
  • the forward scattered light signal and the fluorescent signal of the cell particle are classified into the cell particles in the sample liquid, and the order of distinguishing the red blood cell particle group is not limited.
  • the red blood cell particle may be classified first. The cluster then distinguishes the red blood cell debris particle population from each cell particle.
  • the method before step S380, the method further includes:
  • the number of cell particles in the red blood cell particle population and the number of cell particles in the red blood cell debris particle group are counted.
  • the ratio of the red blood cell debris particle group to the red blood cell particle population generally refers to the ratio of the number of red blood cell debris particles to the number of red blood cell particles.
  • the method for counting the number of red blood cell particles and the statistical method for the number of red blood cell particles can be obtained by statistical methods of cell particles known in the prior art, and the specific statistical principle is not described herein.
  • the identified red blood cell debris particle count value is recorded as Frag_num
  • the recognized red blood cell particle count value is Rbc_Total
  • the percentage of red blood cell debris ie, the ratio of the red blood cell debris particle group to the red blood cell particle group
  • FRC% the percentage of red blood cell debris
  • the percentage of the red blood cell debris particle group to the red blood cell can be calculated, and the calculation result obtained by the red blood cell fragment counting method in the present invention has a good consistency with the ratio of the red blood cell debris obtained manually under the microscope.
  • step S360 includes:
  • red blood cell particle populations are classified from each cell particle.
  • the classification and/or counting comprises at least one of reticulocytes, platelets, and white blood cells according to the second two-dimensional scattergram.
  • the red blood cell particle population can be counted by identifying and classifying red blood cell particle populations, reticulocyte particle populations, white blood cell particle populations, and platelet particle populations.
  • each of the cell particles in the sample fluid is mapped to the second two-dimensional scattergram based on its fluorescence intensity and forward scattered light intensity.
  • the mature red blood cells are located in the middle of the left side of the second two-dimensional scattergram to form a mature red blood cell group;
  • the platelets are located in the lower region of the second two-dimensional scattergram to form a platelet particle group;
  • the white blood cells are located in the second two-dimensional scattergram.
  • a cluster of white blood cells is formed on the right side of the area.
  • the identification and classification of the white blood cell particle group, the red blood cell particle group and the platelet particle group from each cell particle can be realized by the blood cell classification and recognition technology in the prior art, and the specific implementation principle thereof will not be described herein.
  • another embodiment of the present invention further provides a red blood cell debris identification device, the red blood cell debris identification device comprising:
  • the acquiring unit 904 is configured to acquire a side scattered light signal and a fluorescent signal of the cell particles in the sample liquid;
  • the identification unit 906 is configured to distinguish and identify the red blood cell debris particle group in each cell particle according to the side scattered light signal and the fluorescence signal of the cell particle.
  • the red blood cell debris identification device in this embodiment recognizes and obtains red blood cell fragments according to fluorescence and side scattered light formation analysis, and the red blood cell debris recognition and counting accuracy thus obtained is superior to the prior art.
  • the identification unit 906 includes:
  • the graphic generating unit 9062 is configured to obtain a first two-dimensional scattergram according to the side scattered light signal of each cell particle and the fluorescent signal;
  • the cell identification unit 9064 is configured to identify the cell particles represented in the preset region in the first two-dimensional scattergram as red blood cell fragments.
  • the cell identification unit is specifically configured to recognize a population of cell particles having a fluorescence intensity below the red blood cell particle group and a side scattered light intensity below the red blood cell particle group as the red blood cell debris particle group.
  • the fluorescence intensity on the X-axis and the two-dimensional intensity of the side-scattered light on the Y-axis On the scatter plot, the overall fluorescence intensity of the red blood cell debris group is smaller than that of the red blood cell population, and the overall side scattered light intensity is also smaller than that of the red blood cell group, that is, the predetermined region is located at the lower left of the red blood cell scatter group.
  • the cell identification unit has a smaller overall fluorescence intensity than the red blood cell group according to the first two-dimensional scattergram, and the overall side scattered light intensity is also smaller than the fluorescence intensity of the red blood cell group.
  • the cell particle population is identified as a population of red blood cell debris. In some other embodiments, it may not be limited to a scatter plot, for example, using only the fluorescence intensity of each cell and the side scattered light intensity formation data for analysis without generating a scatter plot.
  • the cell identification unit 9064 can accurately identify the red blood cell debris particle group according to the fluorescence signal characterizing the nucleic acid content in the cell particle and the side scattered light signal characterizing the cell content, by accurately identifying the red blood cell debris.
  • the particle swarm can accurately calculate the counting ratio related to the red blood cell debris particle group and reduce the error due to the recognition of red blood cell debris.
  • the acquiring unit 904 is further configured to acquire a forward scattered light signal of the cell particles in the sample liquid;
  • the identifying unit 906 is further configured to: according to the forward scattered light signal and the fluorescent signal of the cell particle, The cell particles in the sample liquid are classified to distinguish and identify the red blood cell particle group;
  • the red blood cell debris identification device further includes:
  • the counting unit 908 is configured to count the number of cell particles in the red blood cell particle population, and/or count the number of cell particles in the red blood cell debris particle group.
  • the red blood cell debris identifying device further comprises:
  • the calculating unit 910 is configured to obtain a counting ratio according to the count value of the red blood cell debris particle group and the count value of the red blood cell particle group, or to obtain a counting ratio according to the red blood cell debris particle group and the red blood cell particle group.
  • the calculating unit can obtain the counting ratio according to the counting of the red blood cell debris particle group and the red blood cell particle group.
  • the red blood cell debris particle group and the red blood cell particle group can be respectively counted according to the counting unit to obtain corresponding counting values, and the calculated count is calculated. proportion.
  • the count value of the red blood cell fragment can be obtained by recognizing the red blood cell particle count based on the forward scattered light signal and the fluorescence signal of the cell particle. Samples can also be obtained by, for example, other measurement methods such as impedance method.
  • the count value of the red blood cell particle group of the liquid is not limited herein.
  • the calculation unit can directly obtain the counting ratio according to the red blood cell debris particle group and the red blood cell particle group, and is not limited to obtaining the counting values of the two kinds of cell particles, and then the counting ratio is obtained.
  • the red blood cell debris counting device distinguishes the red blood cell debris particle group from each cell particle based on the side scattered light signal and the fluorescence signal of the cell particle.
  • the obtained red blood cell fragment count accuracy is better than the prior art, and the error of the red blood cell debris particle group recognition count is reduced.
  • the graphic generating unit 9062 is further configured to obtain a second two-dimensional scattergram according to the forward scattered light signal and the fluorescent signal of each cell particle;
  • the cell identification unit 9064 is further configured to classify the red blood cell particle population according to the second two-dimensional scattergram.
  • reticulocytes, platelets, and/or white blood cells are classified and/or counted according to the second two-dimensional scattergram.
  • the red blood cell particle population can be counted by identifying and classifying red blood cell particle populations, reticulocyte particle populations, white blood cell particle populations, and platelet particle populations.
  • FIG. 12 shows the first two samples of the blood samples selected in the first two-dimensional scattergram obtained by the graphic generating unit 9062 of the red blood cell debris counting device according to the embodiment of the present application.
  • Dimensional scattering point map; Figure 13 shows the comparison of the ratio of red blood cell fragments to the ratio of red blood cell artificial microscopy in the selected 4 blood samples.
  • the first two-dimensional scattering point map of the four blood samples has a good ratio of the ratio of the recognized red blood cell fragments to the red blood cells in the predetermined area, and the structure of the artificial microscopy has a good consistency.
  • Practice has further proved that the adverse effects of the error in recognition and counting on the diagnosis and treatment of diseases are reduced.
  • the red blood cell debris counting device can be a processor of a blood cell analyzer.
  • the red blood cell debris counting device may be another detecting device for detecting the counting ratio of the number of red blood cell debris particles and the number of red blood cell particles.
  • the acquiring unit is further configured to acquire a forward scattered light signal of the cell particles in the sample liquid
  • the identifying unit is further configured to classify, according to the forward scattered light signal and the fluorescent signal, a mesh At least one of red blood cells, platelets, and white blood cells.
  • the red blood cell debris identifying device further includes a display unit for displaying a population of red blood cell debris particles.
  • red blood cell fragments and other blood cells a population of red blood cell debris particles is displayed, for example, by way of color, shape, drawing a boundary or contour. More specifically, in the first two-dimensional scattergram or other two-dimensional and three-dimensional scattergrams described above, the red-cell and red blood cell fragments can be visually distinguished on the first two-dimensional scattergram according to the information characterizing the red blood cell fragments. For example, scatters displayed as different colors/shapes, or drawn with respective boundaries or contours to distinguish different particle swarms. More specifically, the display unit visually distinguishes between displaying red blood cell fragments and including at least one of red blood cells, reticulocytes, white blood cells, and platelets.
  • the present invention also provides a blood cell analyzer 14.
  • the blood cell analyzer 14 includes a sample preparation device 142, a detection device 144, a delivery device, and a processor 146.
  • a sample preparation device 142 is used to treat blood samples and reagents to prepare a sample solution.
  • the blood cell analyzer 14 further includes a sampling device 141 and a reagent injection device.
  • the sampling device 141 is for collecting a blood sample and delivering it to the sample preparation device 142 for injecting the reagent into the sample preparation device 142.
  • the sampling device 141 is a sampling needle
  • the sample preparation device 142 is configured to perform fluorescence dyeing treatment and spheroidization treatment on the blood sample, and can maintain the integrity of the red blood cell membrane and the internal structure of the white blood cell is not destroyed. It should be pointed out that spheroidization is not necessary, which is to spheroidize red blood cells and reticulocytes by surfactants to eliminate the influence of "directional noise" on the measurement.
  • the cell membrane of the red blood cells remains substantially intact.
  • the detecting device 144 is configured to irradiate light to the sample liquid flowing through the detection region, collect optical information generated by each particle in the sample liquid due to illumination, and output an electrical signal corresponding to the optical information of each particle.
  • the detecting device 144 collects optical information of each particle including side scattered light and a fluorescent signal to identify and distinguish the red blood cell debris particle group from each cell particle according to the optical information described above.
  • the detection device 144 includes a light source, a flow chamber as a detection region, a light collection device disposed on the optical axis and/or a side of the optical axis, and a photosensor.
  • the sample liquid passes through the flow chamber under the sheath of the sheath liquid, and the light beam emitted from the light source is irradiated to the detection area, and each of the cell particles in the sample liquid passes through one by one, and emits fluorescence and side scattered light after being irradiated by the light beam.
  • the light collecting device collects and shapes the fluorescent signal and the side scattered light signal of the cell particles one by one, and then irradiates the photoelectric sensor to convert the optical signal into a corresponding electrical signal output.
  • a conveying device for conveying the sample liquid in the sample preparation device 142 to the light detecting device 144.
  • the delivery device can include a delivery line and a control valve, and the sample fluid is delivered to the detection device 144 through the delivery line and the control valve.
  • the processor 146 is configured to receive the optical information detected by the detecting device 144, and distinguish the red blood cell debris particle group from each of the cell particles according to the optical information.
  • the processor 146 is specifically configured to count the number of cellular particles in a population of red blood cell debris particles.
  • the processor 146 is specifically configured to acquire a count value of the red blood cell particle group in the sample liquid, and obtain a count ratio according to the count value of the red blood cell debris particle group and the count value of the red blood cell particle group.
  • the processor 146 obtains the count value of the red blood cell particle population of the sample liquid by other measurement methods such as an impedance method.
  • the optical information includes forward scattered light
  • the processor 146 is specifically configured to classify the red blood cell particle group according to the forward scattered light signal and the fluorescent signal of the cell particle, and according to the red blood cell debris particle group and the The red blood cell particle group obtains a count value of the red blood cell debris particle group and a count value of the red blood cell particle group, and/or obtains a count ratio according to the red blood cell debris particle group and the red blood cell particle group.
  • the optical information comprises forward scattered light
  • the processor 146 is specifically configured to classify and/or count the forward scattered light signals and fluorescent signals according to the cellular particles, including reticulocytes, white blood cells, and platelets.
  • the blood cell analyzer 14 further includes a display device 148 coupled to the processor 146 for displaying red blood cell debris Slice particle group.
  • the red blood cell debris particle population is distinguished by visualization. For example, you can do things like color, shape, draw borders or outlines. More specifically, in the first two-dimensional scattergram or other two-dimensional and three-dimensional scattergrams described above, red blood cells and red blood cell fragments may be visually distinguished on the first two-dimensional scattergram according to the information of the red blood cell fragments.
  • the visualized display shows red blood cells, white blood cells, platelets, and/or reticulocytes, for example, scatters displayed in different colors/shapes, Or draw individual boundaries or outlines to distinguish between different particle swarms.
  • the present invention also provides a blood cell analysis method, the blood cell analysis method comprising the following steps:
  • the reagent is reacted with the blood sample in the sample preparation device 142 to obtain a sample solution.
  • the reagent includes a fluorescent dye and a spheroidizing component, which has cell permeability and can specifically stain the nucleic acid substance in the cell.
  • the spheroidizing component is capable of spheroidizing red blood cells, and the reagent does not contain a hemolytic agent, and can keep the erythrocyte membrane intact and does not damage the internal structure of the white blood cells.
  • the organic alcohol is added to the reagent to increase cell permeability and assist the fluorescent dye to enter the cell.
  • S1520 Obtain optical information of the cell particles in the sample solution, the optical information including a side scattered light signal and a fluorescent signal;
  • the delivery device delivers the sample fluid in the sample preparation device 142 to the detection device 144 such that the cells in the sample solution pass through the detection zone of the optical detection device 144 one by one.
  • the detecting device 144 irradiates the sample liquid with light, and detects the forward scattered light, the side scattered light signal, and the fluorescent signal of the cell particles in the collected sample liquid one by one.
  • the processor 146 is specifically configured to distinguish the red blood cell debris particle group from each cell particle according to the side scattered light signal and the fluorescence signal of the cell particle.
  • the step 1530 specifically includes the steps of:
  • the cell particles represented in the predetermined area in the first two-dimensional scattergram are recognized as a red blood cell debris particle group.
  • a population of cell particles having a fluorescence intensity below the red blood cell particle group and a side scattered light intensity below the red blood cell particle group is recognized as a red blood cell debris particle group.
  • the cell particles located in the lower left region of the red blood cell scatter group are recognized as the red blood cell debris particle group.
  • the two-dimensional scattergram is not limited, and is not limited herein.
  • the step S1530 further includes the following steps:
  • the number of cell particles in the red blood cell debris particle population is counted.
  • the count value is obtained by counting the number of cell particles in the red blood cell debris particle group.
  • the blood cell analysis method further comprises the steps of:
  • the processor obtains a count value of a red blood cell particle group of the sample liquid by other measurement methods such as an impedance method.
  • the count ratio is obtained based on the obtained count value of the red blood cell debris particle group and the count value of the red blood cell particle group.
  • the processor 146 calculates the counting ratio of the red blood cell debris particle group and the red blood cell particle group based on the count value of the red blood cell debris particle group and the count value of the red blood cell particle group.
  • the blood cell analysis method further comprises the steps of:
  • S1550 classifying red blood cell particle groups according to forward scattered light signals and fluorescent signals of the cell particles
  • S1560 Obtain a count value of the red blood cell debris particle group and a count value of the red blood cell particle group according to the red blood cell debris particle group and the red blood cell particle group, and/or according to the red blood cell fragment
  • the slice particle group and the red blood cell particle group obtain a count ratio.
  • the corresponding count value can be counted according to the red blood cell debris particle group and the red blood cell particle group, and the count ratio can be calculated. It is also possible to obtain only the count value by recognizing the red blood cell particle count based on the forward scattered light signal and the fluorescence signal to the cell particles.
  • the counting ratio can be directly obtained according to the red blood cell debris particle group and the red blood cell particle group, and is not limited to obtaining the counting values of the two kinds of cell particles, and then the counting ratio is obtained.
  • the blood cell analysis method further comprises the steps of:
  • Sorting and/or counting according to the forward scattered light signal of the cell particles and the fluorescent signal includes at least one of reticulocytes, white blood cells, and platelets.
  • step S1510 specifically includes:
  • the blood sample is subjected to fluorescent staining treatment to form a sample liquid; wherein the cell membrane of the red blood cells in the sample liquid remains substantially intact.
  • step S1510 the method further includes the steps of:
  • the blood sample is spheroidized.
  • the blood cell analysis method further comprises the steps of:
  • red blood cell fragments and other blood cells a population of red blood cell debris particles is displayed, for example, by way of color, shape, drawing a boundary or contour. More specifically, in the first two-dimensional scattergram or other two-dimensional and three-dimensional scattergrams described above, red blood cells and red blood cell fragments may be visually distinguished on the first two-dimensional scattergram according to the information of the red blood cell fragments. For example, scatters displayed as different colors/shapes, or drawn with respective boundaries or contours to distinguish different particle swarms.
  • the blood cell analysis method further comprises the steps of:
  • the detection device 144 of the blood analyzer may collect a forward scattered light signal, a side scattered light signal, and a fluorescent signal for obtaining cell particles in the sample liquid
  • the processor 146 may be
  • the aforementioned optical information of the cell particles identifies one, two or more kinds of cell particles such as a red blood cell particle group, a red blood cell debris particle group, a platelet, a white blood cell, and a reticulocyte.
  • the display device can display the obtained scattergram and visually distinguish between red blood cell fragments and at least one of red blood cells, reticulocytes, white blood cells, and platelets in a scattergram.
  • the display device is visually displayed not limited to a scatter plot, but may be other two-dimensional or three-dimensional maps. That is to say, the blood analyzer can simultaneously collect various optical information of the cell particles and separately detect and identify different cell particles, which is different from the processor 146 of the conventional blood cell analyzer in that it can be based on the side scattered light signal and The fluorescence signal is detected to identify the red blood cell debris particle group, and then the count value and/or the counting ratio of the red blood cell debris particle group and the red blood cell particle group are obtained.
  • the step of obtaining the side scattered light signal and the fluorescent signal of the cell particles in the sample liquid may be performed in a software manner or in a hardware manner, for example, by irradiating the cell particles in the sample liquid by a light detecting device. And detecting and collecting the side scattered light signals and fluorescent signals of the cell particles.
  • the disclosed apparatus and method may be implemented in other manners.
  • the embodiments of the foregoing device are merely illustrative.
  • the division of a unit is only a division of a logical function.
  • multiple units may be combined or may be Integrated in one system.
  • the functions of the unit can be stored in a computer readable storage medium if it is implemented in the form of a software functional unit and sold or used as a standalone product. Based on such understanding, the part of the technical solution of the present invention that substantially or contributes to the prior art can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium and includes instructions for causing a computer device to perform all or part of the steps of the methods described in various embodiments of the present invention.
  • the foregoing storage medium may be any medium that can store program codes, such as a USB flash drive, a mobile hard disk, a read only memory, or a random access memory.

Abstract

一种红细胞碎片识别方法，该方法包括：获取样本液中细胞粒子的侧向散射光信号及荧光信号（S320）；根据细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群（S330）。通过对样本液的侧向散射光信号及荧光信号进行处理与分析，能够从各细胞粒子中识别出红细胞碎片粒子群。本申请还进一步提供红细胞碎片识别装置、血液细胞分析仪及分析方法。根据表征细胞粒子内核酸含量的荧光与侧向散射光能识别出红细胞碎片，降低了识别计数的误差。

Description

红细胞碎片识别方法和装置、血液细胞分析仪及分析方法 技术领域
本发明涉及血液检测领域，特别是涉及一种红细胞碎片识别方法和装置、血液细胞分析仪及血液细胞分析方法。
背景技术
正常人外周血红细胞碎片(Schistocytes)，即裂红细胞占所有红细胞的比例小于1％。临床上有时需要检测血液样本中的红细胞碎片，供医生参考。因此，要求计数红细胞碎片准确、可靠。
近年来，应用流式细胞计数原理对血液细胞进行计数和分类的血液细胞分析仪相继问世。由于其操作简单、快速，大大促进了血液检测技术发展。
现有技术提供了一种计数红细胞碎片识别方法，其包括：
(1)核酸染料对血细胞进行染色处理，细胞逐个通过检测区域，检测单个细胞的前向散射光和荧光信息，基于散射光和荧光信息将细胞分为三类：白细胞、红细胞、血小板，红细胞区域的粒子数记为A；
(2)在荧光和前向散射光组成的二维散点图的预设区域识别红细胞碎片，红细胞碎片区域的粒子数记为B；
(3)在荧光和前向散射光组成的二维散点图建立小红细胞区域，小红细胞区域的粒子数记为C；
(4)获得最终的红细胞碎片计数，与红细胞的比例记为FRC％，其计算方法如下所示：
Figure PCTCN2017073992-appb-000001
Figure PCTCN2017073992-appb-000002
其中a为常数，α位于1％-3％之间。
然而，经研究发现，当小红细胞与红细胞碎片交叠严重时，按照上述方法获得的FRC％与人工镜检的误差较大。
发明内容
基于此，有必要提供一种红细胞碎片识别准确性高的红细胞碎片识别方法和装置、血液细胞分析仪及血液细胞分析方法。
一种红细胞碎片识别方法，包括以下步骤：
获取样本液中细胞粒子的侧向散射光信号及荧光信号；
根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群。
一种红细胞碎片识别装置，包括：
获取单元，用于获取样本液中的细胞粒子的侧向散射光信号及荧光信号；
识别单元，用于根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群。
上述红细胞碎片识别方法和装置，通过对样本液的侧向散射光信号及荧光信号进行处理与分析，可以从各细胞粒子中准确地识别出红细胞碎片粒子群。根据表征细胞粒子内核酸含量的荧光与侧向散射光可准确识别获得红细胞碎片，提高了红细胞碎片识别的准确性。
一种血液细胞分析仪，包括：
采样装置，用于采集血液样本；
制样装置，用于将由所述采样装置输送的所述血液样本和试剂处理，以制备成样本液；检测装置，用于对所述样本液进行光照射，收集所述样本液中各细胞粒子因光照产生的光学信息，所述光学信息包括侧向散射光信号及荧光信号；
输送装置，用于将所述制样装置中的样本液输送到所述检测装置，使所述样本液中的细胞逐个通过所述检测装置的检测区；
处理器，所述处理器用于接收所述检测装置检测获得的光学信息，根据 所述光学信息从各细胞粒子中区分识别出红细胞碎片粒子群。
一种血液细胞分析方法，包括以下步骤：
处理血液样本，形成样本液；
获取所述样本液中的细胞粒子的光学信息，所述光学信息包括侧向散射光信号及荧光信号；
根据所述光学信息从各细胞粒子中区分识别出红细胞碎片粒子群。
上述血液细胞分析仪及血液细胞分析方法，根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群。获得的红细胞碎片计数准确性优于现有技术，降低了红细胞碎片粒子群识别计数的误差。
本发明的一个或多个实施例的细节在下面的附图和描述中提出。本发明的其它特征、目的和优点将从说明书、附图以及权利要求书变得明显。
附图说明
图1为现有技术中提供的一血液样本的显微镜下的血细胞图；
图2为图1所示的血液样本的前向散射光信号与荧光信号的二维散点图；
图3为本发明一实施例中的红细胞碎片识别方法的流程图；
图4为本发明另一实施例中的红细胞碎片识别方法的流程图；
图5为本发明中提供的正常的血液样本的侧向散射光信号与荧光信号的二维散点图；
图6为本发明中提供的红细胞碎片血液样本的侧向散射光信号与荧光信号的二维散点图；
图7为本发明又一实施例中的红细胞碎片识别方法的流程图；
图8为本发明中提供的红细胞碎片血液样本的前向散射光信号与荧光信号的二维散点图；
图9为本发明一实施例中的红细胞碎片识别装置的结构示意图；
图10为本发明另一实施例中的红细胞碎片识别装置的结构示意图；
图11为本发明又一实施例中的红细胞碎片识别装置的结构示意图；
图12为本发明中提供的4例血液样本的侧向散射光信号与荧光信号的二维散点图；
图13为本发明提供的4例血液样本根据侧向散射光信号与荧光信号的二维散点图获得的红细胞碎片计数与该4例血液样本人工计数的对比结果图；
图14为本发明一实施例中的血液分析仪的结构示意图；
图15为本发明一实施例中的血液细胞分析方法的流程图；
图16为本发明另一实施例中的血液细胞分析方法的流程图。
具体实施方式
为了便于理解本发明，下面将参照相关附图对本发明进行更全面的描述。附图中给出了本发明的较佳的实施例。但是，本发明可以以许多不同的形式来实现，并不限于本文所描述的实施例。相反地，提供这些实施例的目的是使对本发明的公开内容的理解更加透彻全面。
本申请的发明人经研究发现，现有红细胞碎片识别方法中，请结合参阅图1和图2，采用前向散射光信号及荧光信号进行识别时，由于前向散射光表征细胞的体积，当样本由于某种疾病出现较多的小红细胞时，小红细胞体积较小，容易与红细胞碎片混淆，从而对红细胞碎片的计数产生干扰。图1示出了人工镜检过程中镜下血细胞的示意图，图2示出了根据前向散射光信号及荧光信号识别红细胞碎片的二维散点图。从图1所示，红细胞碎片呈盔形、角形，小红细胞呈球形、新月形，小红细胞容易与红细胞碎片混淆，而造成识别与计数的准确性不高。从图2所示，该血液样本的红细胞碎片与小红细胞区域相邻，存在部分重叠现象，由该图2获得的红细胞碎片的计数为14.5％。而人工镜检得出的红细胞碎片的计数为7.2％。
因此需要提供一种新的方法提高红细胞碎片的识别准确性，以提高红细胞碎片计数的准确性。
如图3所示，本发明一实施例提供一种红细胞碎片识别方法，该红细胞 碎片识别方法包括以下步骤：
S320：获取样本液中细胞粒子的侧向散射光信号及荧光信号；
其中，样本液是指血液样本与试剂反应后得到的样本。在一个实施方式中，通过血液细胞分析仪获取样本液中的细胞粒子的光学信息。具体地，输送装置将样本液自动控制输送至血液细胞分析仪的检测装置，使样本液中的细胞逐个通过检测装置中的检测区，收集样本液中的细胞粒子的侧向散射光信号及荧光信号，其中通过输送装置将样本液自动控制进行输送，减少了人为因素的影响，提高了识别精度。
在本实施例中，检测收集细胞粒子的光学信息包括侧向散射光信号及荧光信号，以用于识别红细胞碎片，具体实施时，该光学信息还可包括其他为检测所需要的信息，在此不作限定。
S330：根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群；
虽然不希望受理论约束，申请人在研究中发现红细胞碎片由于细胞膜遭到破坏，其细胞膜上的蛋白与试剂中的染料发生非特异性结合减少，荧光信号减弱，因此，红细胞碎片会产生比较微弱的荧光信号。与此同时，红细胞碎片由于细胞内血红蛋白丢失，表征细胞内容物的侧向散射光信号减弱，因此，红细胞碎片会产生微弱的侧向散射光信号。经过反复的研究与验证发现，通过对样本液的侧向散射光信号及荧光信号进行处理与分析，可以从各细胞粒子中准确地识别出红细胞碎片粒子群，进而识别出红细胞碎片。本实施例中的红细胞碎片识别方法，根据表征细胞粒子内核酸含量的荧光与侧向散射光可准确识别获得红细胞碎片，降低了红细胞碎片识别计数的误差。
在一个实施例中，如图4所示，该步骤S330包括：
S332：根据各细胞粒子的所述侧向散射光信号及荧光信号获得第一二维散点图；
在一个实施方式中，将检测并收集到的细胞粒子的侧向散射光信号和荧光信号，转换为对应的电信号。具体地，通过光电传感器将待测细胞粒子因 光照射产生侧向散射光信号及荧光信号转换为对应的电信号，再利用A/D转换器将所述电信号转换成对应的数字信号，从而获得每个细胞粒子的侧向散射光强度及荧光强度，并建立细胞粒子的侧向散射光强度与荧光强度之间的对应关系，获得第一二维散点图。
S334：将所述第一二维散点图中表现在预设区域内的细胞粒子识别为红细胞碎片粒子群；
其中，预设区域可以是经过对比正常人血液样本和红细胞碎片血液样本，统计分析后，得到在第一二维散点图中的特定区域。根据该特定区域的参数，在未知血液样本的第一二维散点图中，表现在预设区域中的细胞粒子群识别为红细胞碎片粒子群。
在另一实施方式中，也可对比正常人血液样本与红细胞碎片血液样本，统计分析后，得到红细胞碎片粒子群区域与正常人的红细胞粒子群区域，或其他细胞粒子群区域的相对位置函数，利用该函数，在未知血液样本的第一二维散点中，根据识别出的红细胞粒子群区域，确定该预设区域。
在X轴为荧光强度，Y轴为侧向散射光强度的散点图上，红细胞碎片群总体荧光强度比红细胞群的荧光强度小，总体侧向散射光强度也比红细胞群的荧光强度小，也即该预设区域位于红细胞散点群的左下方。需要说明的是，红细胞碎片群总体荧光强度比红细胞群的荧光强度小，总体侧向散射光强度也比红细胞群的荧光强度小，是指并不是红细胞碎片群中的所有细胞粒子的荧光强度与侧向散射光强度，小于红细胞群中的细胞粒子的荧光强度与侧向散射光强度。
通过侧向散射光信号与荧光信号得到的二维散点图在预设区域内出现的粒子群数与红细胞碎片的出现具有较强的相关性。
其中，红细胞碎片由于细胞膜遭到破坏，其细胞膜上的蛋白与试剂发生特异性结合减少，荧光信号减弱，因此，红细胞碎片会产生比较微弱的荧光信号。与此同时，红细胞碎片由于细胞在机体内遭到机械性的破坏，细胞内血红蛋白丢失，表征细胞内容物的侧向散射光信号减弱，因此，红细胞碎片 会产生微弱的侧向散射光信号。通过对样本液的侧向散射光信号及荧光信号进行处理与分析，在根据侧向散射光信号和荧光信号得到的二维散点图中，将预设区域出现细胞粒子群确认为红细胞碎片粒子群。
为了便于说明，请结合参见图5和图6，提供了正常样本液的侧向散射光信号与荧光信号的二维散点图(见图5)；红细胞碎片样本液的侧向散射光信号与荧光信号的二维散点图(见图6)。其中，横坐标为细胞粒子的荧光强度，纵坐标为细胞粒子的侧向散射光强度。从图5及图6所示可知，在预设区域出现的细胞粒子群为红细胞碎片。样本液中每一个细胞粒子根据其荧光强度及侧向散射光强度会映射到第一二维散点图中，从而区分出不同的细胞粒子群。
如此，根据荧光与侧向散射光形成的散点图的特征区域识别红细胞碎片，获得的红细胞碎片计数准确性优于现有技术。
应当理解的是，本发明中将荧光强度在红细胞粒子群以下、并且侧向散射光强度在红细胞粒子群以下的细胞粒子群识别为红细胞碎片粒子群。具体到前述的实施方式中，在第一二维散点图中，将位于红细胞散点群的左下方的区域内的细胞粒子识别为红细胞碎片粒子群。但在其他一些实施方式中，也可不局限于二维散点图，在此不作限定。
在一个实施例中，在步骤S330之后还包括步骤：
计数红细胞碎片粒子群中的细胞粒子数。
具体地，红细胞碎片粒子数的计数方法均可以采用现有技术中已知的细胞粒子的统计方法获得，其具体的统计原理在此不赘述。
在一个实施例中，该红细胞碎片识别方法还包括步骤：
显示红细胞碎片粒子群。
在一个实施方式中，通过可视化地区分红细胞碎片与其他血液细胞，以显示红细胞碎片粒子群，具体地，可通过如颜色，形状，绘制边界或轮廓等方式。例如在前述的第一二维散点图、或其他二维、三维散点图中，可根据表征红细胞碎片信息，在第一二维散点图上可视化地区分显示红细胞和红细 胞碎片，例如显示为不同的颜色/形状的散点，或绘制各自的边界或轮廓区分不同的粒子群。
在一个实施例中，该红细胞碎片识别方法还包括：
根据步骤S330识别出红细胞碎片粒子群，获得红细胞碎片粒子群的计数值；
获取样本液中的红细胞粒子群的计数值，例如从阻抗法等其他测量方法获得样本液的红细胞粒子群的计数值；
根据所述红细胞碎片粒子群的计数值及所述红细胞粒子群的计数值得到计数比例。
在另一个实施例中，请参阅图7，该红细胞碎片识别方法还包括：
S340：获取样本液中细胞粒子的前向散射光信号；
在一个实施方式中，可通过流式血液细胞分析仪对样本液进行照射，并逐个检测收集血液中细胞粒子的光学信息，而同时获取样本液中的细胞粒子的前向散射光信号、侧向散射光信号及荧光信号；
S360：根据所述细胞粒子的前向散射光信号及荧光信号，分类红细胞粒子群；
S380：根据所述红细胞碎片粒子群及所述红细胞粒子群获取所述红细胞碎片粒子群的计数值与所述红细胞粒子群的计数值，和/或根据所述红细胞碎片粒子群及所述红细胞粒子群获取计数比例。
其中，可根据红细胞碎片粒子群及红细胞粒子群获取上述两种粒子群的计数值，也可根据红细胞碎片粒子群及红细胞粒子群直接获得两者的计数比例，而不获得两种粒子的计数值。当然，还可根据红细胞碎片粒子群及红细胞粒子群获取上述的两种粒子群的计数值，并获取计数比例。
由于前向散射光通常表征细胞的体积，因此可通过前向散射光信号及荧光信号实现对细胞粒子的分类，以区分识别出红细胞粒子群。侧向散射光信号通常表征细胞内容物，因此可通过侧向散射光信号及荧光信号实现对细胞内血红蛋白丢失的红细胞碎片的识别，以识别区分出红细胞碎片粒子群。通 过准确的识别区分出红细胞粒子群和红细胞碎片粒子群，可以获得红细胞碎片粒子群与红细胞粒子群的计数值和/或计数比例，以获得与红细胞碎片相关的准确、可靠的诊断信息。
应当理解的是，该步骤S340与步骤S320可同时进行，步骤S330根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群，与步骤S360，根据所述细胞粒子的前向散射光信号及荧光信号，对样本液中的细胞粒子进行分类，区分识别出红细胞粒子群的顺序不作限定，例如，在另一实施例中，也可以先分类红细胞粒子群，然后从各细胞粒子中区分识别出红细胞碎片粒子群。
在一个实施例中，步骤S380之前还包括：
计数所述红细胞粒子群中的细胞粒子数及所述红细胞碎片粒子群中的细胞粒子数。
红细胞碎片粒子群与所述红细胞粒子群的计数比例通常是指红细胞碎片粒子数与红细胞粒子数的比值。其中，红细胞粒子数的计数方法和红细胞碎片粒子数的统计方法均可以采用现有技术中已知的细胞粒子的统计方法获得，其具体的统计原理在此不赘述。将识别出的红细胞碎片粒子计数值记为Frag_num，识别出的红细胞粒子计数值为Rbc_Total，红细胞碎片的百分比(即红细胞碎片粒子群与所述红细胞粒子群的计数比例)记为FRC％，则计算公式为：
Figure PCTCN2017073992-appb-000003
如此，可计算出红细胞碎片粒子群占红细胞的百分比含量，本发明中的红细胞碎片计数方法获得的计算结果与手工在显微镜下获得的红细胞碎片比例具有良好的一致性。
在一个实施例中，步骤S360包括：
根据各细胞粒子的所述前向散射光信号及荧光信号，获得第二二维散点图；
根据所述第二二维散点图，从各细胞粒子中分类红细胞粒子群。
在一个实施方式中，根据该第二二维散点图，分类和/或计数包括网织红细胞、血小板和白细胞中的至少一种。通过识别并分类红细胞粒子群、网织红细胞粒子群、白细胞粒子群及血小板粒子群，可对红细胞粒子群进行计数。参考图8，样本液中每一个细胞粒子根据其荧光强度及前向散射光强度会映射到该第二二维散点图中。其中，成熟红细胞位于第二二维散点图的左侧中间位置，形成成熟红细胞群；血小板位于第二二维散点图的下方区域，形成血小板粒子群；白细胞位于第二二维散点图的右侧区域，形成白细胞粒子群。其中，从各细胞粒子中识别分类出白细胞粒子群、红细胞粒子群及血小板粒子群可以通过现有技术中的血液细胞分类识别技术实现，其具体实现原理在此不再赘述。
如图9所示，本发明另一实施例还提供一种红细胞碎片识别装置，该红细胞碎片识别装置包括：
获取单元904，用于获取样本液中的细胞粒子的侧向散射光信号及荧光信号；
识别单元906，用于根据所述细胞粒子的侧向散射光信号及荧光信号，各细胞粒子中区分识别出红细胞碎片粒子群。
本实施例中的红细胞碎片识别装置，根据荧光与侧向散射光形成分析识别获得红细胞碎片，如此获得的红细胞碎片识别计数准确性优于现有技术。
在一个实施例中，如图10所示，该识别单元906包括：
图形生成单元9062，用于根据各细胞粒子的所述侧向散射光信号及所述荧光信号获得第一二维散点图；
细胞识别单元9064，用于将所述第一二维散点图中表现在预设区域内的细胞粒子识别为红细胞碎片。
在一个实施方式中，该细胞识别单元具体用于将荧光强度在红细胞粒子群以下、并且侧向散射光强度在所述红细胞粒子群以下的细胞粒子群识别为所述红细胞碎片粒子群。在X轴为荧光强度，Y轴为侧向散射光强度的二维 散点图上，红细胞碎片群总体荧光强度比红细胞群的荧光强度小，总体侧向散射光强度也比红细胞群的荧光强度小，也即该预设区域位于红细胞散点群的左下方。
应当理解的是，本实施例中，该细胞识别单元根据第一二维散点图，将总体荧光强度比红细胞群的荧光强度小，总体侧向散射光强度也比红细胞群的荧光强度小的细胞粒子群识别为红细胞碎片粒子群。在其他一些实施例中，也可不局限于在散点图，例如仅仅利用每个细胞的荧光强度和侧向散射光强度形成数据进行分析，而不生成散点图。
以上实施例所提供的红细胞碎片识别装置，细胞识别单元9064根据表征细胞粒子内核酸含量的荧光信号与表征细胞内容物的侧向散射光信号可准确识别获得红细胞碎片粒子群，通过准确识别红细胞碎片粒子群可以准确计算得到红细胞碎片粒子群相关的计数比例，降低因红细胞碎片识别的误差。
在一个实施例中，该获取单元904还用于获取样本液中的细胞粒子的前向散射光信号；该识别单元906还用于根据所述细胞粒子的前向散射光信号及荧光信号，对样本液中的细胞粒子进行分类，区分识别出红细胞粒子群；
在一个实施例中，请参阅图11，该红细胞碎片识别装置还包括：
计数单元908，用于计数所述红细胞粒子群中的细胞粒子数，和/或计数红细胞碎片粒子群中的细胞粒子数。
在一个实施例中，该红细胞碎片识别装置还包括：
计算单元910，用于根据所述红细胞碎片粒子群的计数值及所述红细胞粒子群的计数值得到计数比例，或用于根据所述红细胞碎片粒子群及所述红细胞粒子群获取计数比例。
应当理解的是，该计算单元可根据红细胞碎片粒子群及红细胞粒子群的计数得到计数比例，例如，可根据计数单元对红细胞碎片粒子群及红细胞粒子群分别计数得到相应的计数值，计算得到计数比例。其中，该红细胞碎片的计数值可通过根据对细胞粒子的前向散射光信号及荧光信号识别出红细胞粒子群计数而得到计数值。也可通过例如从阻抗法等其他测量方法获得样本 液的红细胞粒子群的计数值，在此不作限定。当然，该计算单元还可根据红细胞碎片粒子群及红细胞粒子群直接获取计数比例，而不局限于得到两种细胞粒子的计数值后再得到计数比例。
本发明提供的红细胞碎片计数装置，根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群。获得的红细胞碎片计数准确性优于现有技术，降低了红细胞碎片粒子群识别计数的误差。
在一个实施例中，该图形生成单元9062还用于根据各细胞粒子的所述前向散射光信号及荧光信号，获得第二二维散点图；
细胞识别单元9064还用于根据所述第二二维散点图，分类红细胞粒子群。
具体地，根据该第二二维散点图，分类和/或计数网织红细胞、血小板和/或白细胞。通过识别并分类红细胞粒子群、网织红细胞粒子群、白细胞粒子群及血小板粒子群，可对红细胞粒子群进行计数。
请参阅图12和图13，图12示出了根据本申请实施例所提供的红细胞碎片计数装置的图形生成单元9062获得的第一二维散点图中选取的4例血液样本的第一二维散射点图；图13示出了选择的4例血液样本的红细胞碎片比例与红细胞人工镜检比例的对比结果。从图12及图13可见，四例血液样本的第一二维散射点图在预设区域内的识别的红细胞碎片与红细胞的计数比例，与人工镜检的结构具有良好的一致性，从而经过实践进一步证明降低了因识别计数的误差对疾病诊断及治疗造成的不良影响。
优选的，该红细胞碎片计数装置可以为血液细胞分析仪的处理器。具体实施时，该红细胞碎片计数装置也可以为其它用于检测红细胞碎片粒子数与红细胞粒子数的计数比例的检测装置。
在一个实施例中，该获取单元还用于获取样本液中的细胞粒子的前向散射光信号，该识别单元还用于根据所述前向散射光信号和所述荧光信号，分类包括网织红细胞、血小板和白细胞中的至少一种。
在一个实施例中，该红细胞碎片识别装置还包括显示单元，该显示单元用于显示红细胞碎片粒子群。
具体地，通过可视化地区分红细胞碎片与其他血液细胞，显示红细胞碎片粒子群，例如，可通过如颜色，形状，绘制边界或轮廓等方式。更具体地，在上述的第一二维散点图或其他二维、三维散点图中，可根据表征红细胞碎片的信息，在第一二维散点图上可视化地区分显示红细胞和红细胞碎片，例如显示为不同的颜色/形状的散点，或绘制各自的边界或轮廓区分不同的粒子群。更具体地，该显示单元通过可视化地区别显示红细胞碎片和包括红细胞、网织红细胞、白细胞、血小板中的至少一种。
作为实现本红细胞碎片计数装置的一种具体实施方式，如图14所示，本发明还提供一种血液细胞分析仪14。该血液细胞分析仪14包括制样装置142、检测装置144、输送装置及处理器146。
制样装置142用于将血液样本和试剂处理，以制备成样本液。在一个施例中，血液细胞分析仪14还包括采样装置141和试剂注入装置。采样装置141用于采集血液样本并输送至制样装置142，试剂注入装置用于将试剂注入制样装置142。本实施例中，该采样装置141为采样针，该制样装置142用于对血液样本进行荧光染色处理及球形化处理，且能保持红细胞膜的完整性及白细胞内部结构不被破坏。需要指出，球形化处理并不是必须的，其是通过表面活性剂将红细胞和网织红细胞球形化，以消除“方向性噪音”对测定的影响。
如此，在血液样本进行荧光染色处理形成样本液中，红细胞的细胞膜基本保持完整。
检测装置144用于对流经其检测区域的样本液进行光照射，收集样本液中各粒子因光照产生的光学信息，并输出与各粒子的光学信息对应的电信号。本实施例中，该检测装置144收集各粒子的光学信息包括侧向散射光及荧光信号，以根据前述的光学信息，从各细胞粒子中识别区分出红细胞碎片粒子群。
在一个实施方式中，该检测装置144包括光源、作为检测区域的流动室、设置在光轴上和/或光轴侧边的光收集装置和光电感应器。样本液在鞘液的裹挟下通过流动室，光源发射的光束照射到检测区域，样本液中的各细胞粒子逐个经过，并经光束照射后发出荧光及侧向散射光。光收集装置逐个对细胞粒子的荧光信号及侧向散射光信号进行收集整形，然后照射到光电传感器，光电传感器将光信号转换为对应的电信号输出。
输送装置，用于将制样装置142中的样本液输送到光检测装置144中去。具体地，该输送装置可包括输送管路和控制阀，样本液通过输送管路和控制阀输送到检测装置144中去。
该处理器146用于接收检测装置144检测获得的光学信息，根据所述光学信息从各细胞粒子中区分识别出红细胞碎片粒子群。
在一个实施例中，该处理器146具体用于计数红细胞碎片粒子群中的细胞粒子数。
在一个实施例中，该处理器146具体用于获取所述样本液中的红细胞粒子群的计数值，并根据所述红细胞碎片粒子群的计数值及所述红细胞粒子群的计数值得到计数比例。
例如，该处理器146通过阻抗法等其他测量方法获得样本液的红细胞粒子群的计数值。
在一个实施例中，该光学信息包括前向散射光，该处理器146具体用于根据该细胞粒子的前向散射光信号与荧光信号分类红细胞粒子群，并根据所述红细胞碎片粒子群及所述红细胞粒子群获取所述红细胞碎片粒子群的计数值与所述红细胞粒子群的计数值，和/或根据所述红细胞碎片粒子群及所述红细胞粒子群获取计数比例。
在一个实施例中，该光学信息包括前向散射光，该处理器146具体用于根据该细胞粒子的前向散射光信号与荧光信号分类和/或计数包括网织红细胞、白细胞和血小板中的至少一种。在一个实施例中，该血液细胞分析仪14还包括显示装置148，所述显示装置148与所述处理器146连接，用于显示红细胞碎 片粒子群。具体地，通过可视化地区分红细胞碎片粒子群。例如，可通过如颜色，形状，绘制边界或轮廓等方式。更具体地，在上述的第一二维散点图或其他二维、三维散点图中，可根据表征红细胞碎片信息，在第一二维散点图上可视化地区分显示红细胞和红细胞碎片，例如显示为不同的颜色/形状的散点，或绘制各自的边界或轮廓区分不同的粒子群。或者在上述的第二二维散点图或其他二维、三维散点图中，可视化地区分显示红细胞、白细胞、血小板和/或网织红细胞，例如显示为不同的颜色/形状的散点，或绘制各自的边界或轮廓区分不同的粒子群。
如图15所示，本发明还提供一种血液细胞分析方法，该血液细胞分析方法包括以下步骤：
S1510：处理血液样本，形成样本液；
在一个实施方式中，在制样装置142内将试剂与血液样本进行反应，获得样本液。该试剂包括荧光染料及球形化组分，该荧光染料具有细胞通透性，可对细胞内核酸物质特异性染色。该球形化组分能够对红细胞球形化，该试剂不含溶血剂，能保持红细胞膜完整且不对白细胞的内部结构产生破坏作用。优选地，该试剂中可增加有机醇，能增加细胞通透性，协助荧光染料进入细胞内。
S1520：获取所述样本液中的细胞粒子的光学信息，所述光学信息包括侧向散射光信号及荧光信号；
在一个实施方式中，输送装置将制样装置142中的样本液输送到检测装置144，使样本液中的细胞逐个通过光学检测装置144的检测区。检测装置144对样本液进行光照射，逐个检测收集样本液中的细胞粒子的前向散射光、侧向散射光信号及荧光信号。
S1530：根据所述光学信息从各细胞粒子中区分识别出红细胞碎片粒子群；
在一个实施方式中，该处理器146具体用于根据细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群。
在一个实施例中，该步骤1530具体包括步骤：
根据各细胞粒子的所述侧向散射光信号及荧光信号获得第一二维散点图；
将所述第一二维散点图中表现在预设区域内的细胞粒子识别为红细胞碎片粒子群。
在一个实施中，将荧光强度在红细胞粒子群以下、并且侧向散射光强度在红细胞粒子群以下的细胞粒子群识别为红细胞碎片粒子群。具体地，在第一二维散点图中，将位于红细胞散点群的左下方的区域内的细胞粒子识别为红细胞碎片粒子群。但在其他一些实施方式中，也可不局限于二维散点图，在此不作限定。在一个实施例中，该步骤S1530之后还包括步骤：
计数所述红细胞碎片粒子群中的细胞粒子数。
具体地，通过对红细胞碎片粒子群中的细胞粒子数进行计数而获得计数值。
在一个实施例中，该血液细胞分析方法还包括步骤：
获取所述样本液中的红细胞粒子群的计数值；
例如，该处理器通过阻抗法等其他测量方法获得样本液的红细胞粒子群的计数值。
根据获得的所述红细胞碎片粒子群的计数值及所述红细胞粒子群的计数值得到计数比例。
具体地，该处理器146根据红细胞碎片粒子群的计数值及红细胞粒子群的计数值计算所述红细胞碎片粒子群与所述红细胞粒子群的计数比例。
如图16所示，在另一个实施例中，该血液细胞分析方法还包括步骤：
S1540：获取样本液中的细胞粒子的前向散射光信号；
S1550：根据所述细胞粒子的前向散射光信号及荧光信号，分类红细胞粒子群；
S1560：根据所述红细胞碎片粒子群及所述红细胞粒子群获取所述红细胞碎片粒子群的计数值与所述红细胞粒子群的计数值，和/或根据所述红细胞碎 片粒子群及所述红细胞粒子群获取计数比例。
其中，可根据红细胞碎片粒子群及红细胞粒子群分别计数得到相应的计数值，并计算得到计数比例。也可通过根据对细胞粒子的前向散射光信号及荧光信号识别出红细胞粒子群计数而仅得到计数值。当然，还可根据红细胞碎片粒子群及红细胞粒子群直接获取计数比例，而不局限于得到两种细胞粒子的计数值后再得到计数比例。
在一个实施例中，该血液细胞分析方法还包括步骤：
获取样本液中细胞粒子的前向散射光信号；
根据所述细胞粒子的前向散射光信号与所述荧光信号分类和/或计数包括网织红细胞、白细胞和血小板中的至少一种。
在一个实施例中，该步骤S1510中具体包括：
对血液样本进行荧光染色处理，形成样本液；其中，所述样本液中的红细胞的细胞膜基本保持完整。
在一个实施例中，该步骤S1510中，还包括步骤：
对血液样本进行球形化处理。
在一个实施例中，该血液细胞分析方法，还包括步骤：
显示所述红细胞碎片粒子群；
具体地，通过可视化地区分红细胞碎片与其他血液细胞，显示红细胞碎片粒子群，例如，可通过如颜色，形状，绘制边界或轮廓等方式。更具体地，在上述的第一二维散点图或其他二维、三维散点图中，可根据表征红细胞碎片信息，在第一二维散点图上可视化地区分显示红细胞和红细胞碎片，例如显示为不同的颜色/形状的散点，或绘制各自的边界或轮廓区分不同的粒子群。
在一个实施例中，该血液细胞分析方法还包括步骤：
根据各细胞粒子的所述前向散射光信号及荧光信号，获得第二二维散点图；
可视化地在所述第二散点图上区别显示红细胞碎片和包括红细胞、网织红细胞、白细胞、血小板中的至少一种。
应当理解的是，在实际的检测应用中，该血液分析仪的检测装置144可收集获得样本液中细胞粒子的前向散射光信号、侧向散射光信号及荧光信号，该处理器146可根据细胞粒子的前述光学信息识别红细胞粒子群、红细胞碎片粒子群、血小板、白细胞、网织红细胞等细胞粒子中的一种、两种或多种。该显示装置可显示得到的散点图，并在散点图中可视化地区别显示红细胞碎片和包括红细胞、网织红细胞、白细胞、血小板中的至少一种。当然，该显示装置可视化地显示也不局限于散点图，也可为其他的二维、三维图。也就是说，该血液分析仪可同时采集细胞粒子的多种光学信息，并分别检测识别不同的细胞粒子，与传统的血液细胞分析仪的处理器146不同在于，可根据侧向散射光信号及荧光信号而检测识别红细胞碎片粒子群，进而获取红细胞碎片粒子群与红细胞粒子群的计数值和/或计数比例。
应当理解的是，本领域技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及方法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。其中的功能究竟以硬件还是软件的方式来执行，取决于技术方案特定应用和设计的约束条件，专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但这种实现不应被认为超出本发明的范围。
例如，步骤获取样本液中细胞粒子的侧向散射光信号及荧光信号，可以以软件的方式执行，也可以硬件的方式来执行，例如，通过光检测装置对样本液中的细胞粒子进行光照射，而检测收集获得细胞粒子的侧向散射光信号及荧光信号。
在本申请所提供的实施例中，所揭露的装置和方法，可以通过其他的方式实现。例如，前面所描述的装置的实施例仅仅是示意性的，例如，单元的划分，仅仅为一种逻辑功能的划分，实际实现时可以有另外的划分方法，例如，多个单元可以结合或者可以集成于一个系统中。
单元的功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明的技术方案实质上或者说对现有技术做出贡献的部分可以以软件产品形式体现出来。该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备执行本发明各个实施例所述方法的全部或部分步骤。
其中，前述的存储介质，可以为U盘、移动硬盘、只读存储器或随机存储存储器等各种可以储存程序代码的介质。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本发明的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变形和改进，这些都属于本发明的保护范围。因此，本发明专利的保护范围应以所附权利要求为准。

Claims (33)

  1. 一种红细胞碎片识别方法，其特征在于，包括以下步骤：
    获取样本液中细胞粒子的侧向散射光信号及荧光信号；
    根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群。
  2. 根据权利要求1所述的红细胞碎片识别方法，其特征在于，所述根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群的步骤包括：
    根据各细胞粒子的所述侧向散射光信号及荧光信号获得第一二维散点图；
    将所述第一二维散点图中表现在预设区域内的细胞粒子识别为红细胞碎片粒子群。
  3. 根据权利要求1所述的红细胞碎片识别方法，其特征在于，所述根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群的步骤包括：
    根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中将荧光强度在红细胞粒子群以下、并且侧向散射光强度在所述红细胞粒子群以下的细胞粒子群识别为所述红细胞碎片粒子群。
  4. 根据权利要求1～3任意一项所述的红细胞碎片识别方法，其特征在于，所述根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群的步骤之后还包括：
    计数所述红细胞碎片粒子群中的细胞粒子数。
  5. 根据权利要求1～3所述的红细胞碎片识别方法，其特征在于，所述红细胞碎片识别方法还包括步骤：
    获取样本液中细胞粒子的前向散射光信号；
    根据所述细胞粒子的前向散射光信号及荧光信号，分类红细胞粒子群；
    根据所述红细胞碎片粒子群及所述红细胞粒子群获取所述红细胞碎片粒 子群的计数值与所述红细胞粒子群的计数值，和/或根据所述红细胞碎片粒子群及所述红细胞粒子群获取计数比例。
  6. 根据权利要求5所述的红细胞碎片识别方法，其特征在于，所述根据所述细胞粒子的前向散射光信号及荧光信号，分类红细胞粒子群的步骤具体包括：
    根据各细胞粒子的所述前向散射光信号及荧光信号，获得第二二维散点图；
    根据所述第二二维散点图，分类红细胞粒子群。
  7. 根据权利要求1-6任意一项所述的红细胞碎片识别方法，其特征在于，所述红细胞碎片识别方法还包括步骤：
    获取样本液中细胞粒子的前向散射光信号；
    根据所述前向散射光信号和所述荧光信号，分类和/或计数包括网织红细胞、血小板和白细胞中的至少一种。
  8. 根据权利要求1～7任意一项所述的红细胞碎片识别方法，其特征在于，所述红细胞碎片识别方法还包括步骤：
    可视化地区别显示所述红细胞碎片粒子群。
  9. 一种红细胞碎片识别装置，其特征在于，包括：
    获取单元，用于获取样本液中的细胞粒子的侧向散射光信号及荧光信号；
    识别单元，用于根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中区分识别出红细胞碎片粒子群。
  10. 根据权利要求9所述的红细胞碎片识别装置，其特征在于，所述识别单元包括：
    图形生成单元，用于根据各细胞粒子的所述侧向散射光信号及所述荧光信号获得第一二维散点图；
    细胞识别单元，用于将所述第一二维散点图中表现在预设区域内的细胞粒子识别为红细胞碎片。
  11. 根据权利要求9所述的红细胞碎片识别装置，其特征在于，所述识 别单元具体用于将荧光强度在红细胞粒子群以下、并且侧向散射光强度在所述红细胞粒子群以下的细胞粒子群识别为所述红细胞碎片粒子群。
  12. 根据权利要求9～11任意一项所述的红细胞碎片识别装置，其特征在于，所述获取单元还用于获取样本液中的细胞粒子的前向散射光信号；所述识别单元还用于根据所述细胞粒子的前向散射光信号及荧光信号分类红细胞粒子群。
  13. 根据权利要求12所述的红细胞碎片识别装置，其特征在于，所述红细胞碎片识别装置还包括：
    计数单元，用于计数所述红细胞粒子群中的细胞粒子数，和/或计数所述红细胞碎片粒子群中的细胞粒子数。
  14. 根据权利要求12所述的红细胞碎片识别装置，其特征在于，所述红细胞碎片识别装置还包括：计算单元，用于根据所述红细胞碎片粒子群的计数值及所述红细胞粒子群的计数值得到计数比例，或用于根据所述红细胞碎片粒子群及所述红细胞粒子群获取计数比例。
  15. 根据权利要求12所述的红细胞碎片识别装置，其特征在于，所述图形生成单元还用于根据各细胞粒子的所述前向散射光信号及荧光信号，获得第二二维散点图；
    所述细胞识别单元还用于根据所述第二二维散点图，分类红细胞粒子群。
  16. 根据权利要求9-15任意一项所述的红细胞碎片识别装置，其特征在于，所述获取单元还用于获取样本液中的细胞粒子的前向散射光信号，所述识别单元还用于根据所述前向散射光信号和所述荧光信号，分类包括网织红细胞、血小板和白细胞中的至少一种。
  17. 根据权利要求9-16任意一项所述的红细胞碎片识别装置，其特征在于，所述红细胞碎片识别装置还包括显示单元，所述显示单元用于可视化区别显示所述红细胞碎片粒子群，优选的在所述第一二维散点图上，可视化区别显示所述红细胞碎片粒子群。
  18. 一种血液细胞分析仪，其特征在于，包括：采样装置，用于采集血 液样本；
    制样装置，用于将由所述采样装置输送的所述血液样本和试剂处理，以制备成样本液；检测装置，用于对所述样本液进行光照射，收集所述样本液中各细胞粒子因光照产生的光学信息，所述光学信息包括侧向散射光信号及荧光信号；
    输送装置，用于将所述制样装置中的样本液输送到所述检测装置，使所述样本液中的细胞逐个通过所述检测装置的检测区；
    处理器，所述处理器用于接收所述检测装置检测获得的光学信息，根据所述光学信息从各细胞粒子中区分识别出红细胞碎片粒子群。
  19. 根据权利要求18所述的血液细胞分析仪，其特征在于，所述处理器具体用于计数所述红细胞碎片粒子群中的细胞粒子数。
  20. 根据权利要求18所述的血液细胞分析仪，其特征在于，所述光学信息还包括前向散射光，所述处理器具体用于根据所述细胞粒子的前向散射光信号与所述荧光信号分类红细胞粒子群，并根据所述红细胞碎片粒子群及所述红细胞粒子群获取所述红细胞碎片粒子群的计数值与所述红细胞粒子群的计数值，和/或根据所述红细胞碎片粒子群及所述红细胞粒子群获取计数比例。
  21. 根据权利要求18所述的血液细胞分析仪，其特征在于，所述样本液中，细胞被荧光染色处理，红细胞的细胞膜基本保持完整。
  22. 根据权利要求18所述的血液细胞分析仪，其特征在于，所述光学信息还包括前向散射光，所述处理器具体用于根据所述细胞粒子的所述前向散射光信号与所述荧光信号分类和/或计数包括网织红细胞、血小板和白细胞中的至少一种。
  23. 根据权利要求18所述的血液细胞分析仪，其特征在于，所述血液细胞分析仪还包括显示装置，所述显示装置与所述处理器连接，用于可视化地区别显示所述红细胞碎片粒子群；优选通过颜色、形状、绘制边界和/或轮廓可视化地区别显示所述红细胞碎片粒子群。
  24. 一种血液细胞分析方法，其特征在于，包括以下步骤：
    处理血液样本，形成样本液；
    获取所述样本液中的细胞粒子的光学信息，所述光学信息包括侧向散射光信号及荧光信号；
    根据所述光学信息从各细胞粒子中区分识别出红细胞碎片粒子群。
  25. 根据权利要求24所述的血液细胞分析方法，其特征在于，所述根据所述光学信息从各细胞粒子中区分识别出红细胞碎片粒子群的步骤具体包括：
    根据各细胞粒子的所述侧向散射光信号及荧光信号获得第一二维散点图；
    将所述第一二维散点图中表现在预设区域内的细胞粒子识别为红细胞碎片粒子群。
  26. 根据权利要求24所述的血液细胞分析方法，其特征在于，所述根据所述光学信息从各细胞粒子中区分识别出红细胞碎片粒子群的步骤具体包括：
    根据所述细胞粒子的侧向散射光信号及荧光信号，从各细胞粒子中将荧光强度在红细胞粒子群以下、并且侧向散射光强度在所述红细胞粒子群以下的细胞粒子群识别为所述红细胞碎片粒子群。
  27. 根据权利要求24所述的血液细胞分析方法，其特征在于，所述根据所述光学信息从各细胞粒子中区分识别出红细胞碎片粒子群之后还包括：
    计数所述红细胞碎片粒子群中的细胞粒子数。
  28. 根据权利要求27所述的血液细胞分析方法，其特征在于，还包括步骤：
    获取所述样本液中的红细胞粒子群的计数值；
    根据所述红细胞碎片粒子群的计数值及所述红细胞粒子群的计数值得到计数比例。
  29. 根据权利要求24所述的血液细胞分析方法，其特征在于，还包括步 骤：
    获取样本液中细胞粒子的前向散射光信号；
    根据所述细胞粒子的前向散射光信号及荧光信号，分类红细胞粒子群；
    根据所述红细胞碎片粒子群及所述红细胞粒子群获取所述红细胞碎片粒子群的计数值与所述红细胞粒子群的计数值，和/或根据所述红细胞碎片粒子群及所述红细胞粒子群获取计数比例。
  30. 根据权利要求24所述的血液细胞分析方法，其特征在于，还包括步骤：
    获取样本液中细胞粒子的前向散射光信号；
    根据所述细胞粒子的前向散射光信号及荧光信号，分类和/或计数包括网织红细胞、血小板和白细胞中的至少一种。
  31. 根据权利要求29或30所述的血液细胞分析方法，其特征在于，所述血液细胞分析方法还包括步骤：
    根据各细胞粒子的所述前向散射光信号及荧光信号，获得第二二维散点图；
    可视化地在所述第二散点图上区别显示红细胞碎片和包括红细胞、网织红细胞、白细胞、血小板中的至少一种。
  32. 根据权利要求24所述的血液细胞分析方法，其特征在于，所述处理血液样本，形成样本液的步骤具体包括：
    对血液样本进行荧光染色处理，形成样本液；其中，所述样本液中的红细胞的细胞膜基本保持完整。
  33. 根据权利要求24所述的血液细胞分析方法，其特征在于，所述血液细胞分析方法还包括步骤：
    可视化地区别显示所述红细胞碎片粒子群；优选通过颜色、形状、绘制边界和/或轮廓可视化地区别显示所述红细胞碎片粒子群。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110226083A (zh) * 2017-02-17 2019-09-10 深圳迈瑞生物医疗电子股份有限公司 红细胞碎片识别方法和装置、血液细胞分析仪及分析方法

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111781168B (zh) * 2020-06-17 2023-06-13 迈克医疗电子有限公司 红细胞碎片识别区域的调整方法、装置、设备和介质
CN111812068B (zh) * 2020-06-29 2023-08-08 迈克医疗电子有限公司 异型淋巴细胞确定方法、装置和细胞分析仪
CN111812070B (zh) * 2020-06-30 2023-08-11 迈克医疗电子有限公司 核左移以及取值范围的确定方法、装置和细胞分析仪

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5264369A (en) * 1991-07-29 1993-11-23 Toa Medical Electrics Co., Ltd. Method of preparing specimen for counting subpopulations of leukocytes and erythroblasts
US20010053551A1 (en) * 2000-06-20 2001-12-20 Meiyi Jiang Method for quantitatively analyzing fragmented red blood cells
CN103076311A (zh) * 2011-10-25 2013-05-01 希森美康株式会社 活化嗜中性粒细胞的检测方法及装置
CN103472034A (zh) * 2013-08-23 2013-12-25 深圳中科强华科技有限公司 一种血细胞分析芯片、分析仪及分析方法
CN104297135A (zh) * 2013-07-16 2015-01-21 成都深迈瑞医疗电子技术研究院有限公司 血液样本中粒子的识别方法、系统及血液细胞分析仪
CN104749144A (zh) * 2013-12-31 2015-07-01 深圳迈瑞生物医疗电子股份有限公司 血细胞检测试剂及血细胞处理方法和识别方法

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
PL2166353T3 (pl) * 2007-06-25 2019-01-31 Sysmex Corporation Odczynnik i zestaw odczynników do analizy prymitywnego leukocytu
CN102539291B (zh) * 2010-12-31 2016-06-08 深圳迈瑞生物医疗电子股份有限公司 粒子分析装置及方法
WO2012151103A2 (en) * 2011-05-04 2012-11-08 Abbott Laboratories Nucleated red blood cell analysis system and method
CN103364324A (zh) * 2012-03-27 2013-10-23 嘉善加斯戴克医疗器械有限公司 一种用于血液细胞分析仪的自适应分类计算方法
CN110226083B (zh) * 2017-02-17 2022-12-20 深圳迈瑞生物医疗电子股份有限公司 红细胞碎片识别方法和装置、血液细胞分析仪及分析方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5264369A (en) * 1991-07-29 1993-11-23 Toa Medical Electrics Co., Ltd. Method of preparing specimen for counting subpopulations of leukocytes and erythroblasts
US20010053551A1 (en) * 2000-06-20 2001-12-20 Meiyi Jiang Method for quantitatively analyzing fragmented red blood cells
CN103076311A (zh) * 2011-10-25 2013-05-01 希森美康株式会社 活化嗜中性粒细胞的检测方法及装置
CN104297135A (zh) * 2013-07-16 2015-01-21 成都深迈瑞医疗电子技术研究院有限公司 血液样本中粒子的识别方法、系统及血液细胞分析仪
CN103472034A (zh) * 2013-08-23 2013-12-25 深圳中科强华科技有限公司 一种血细胞分析芯片、分析仪及分析方法
CN104749144A (zh) * 2013-12-31 2015-07-01 深圳迈瑞生物医疗电子股份有限公司 血细胞检测试剂及血细胞处理方法和识别方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3584565A4 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110226083A (zh) * 2017-02-17 2019-09-10 深圳迈瑞生物医疗电子股份有限公司 红细胞碎片识别方法和装置、血液细胞分析仪及分析方法
US11125687B2 (en) 2017-02-17 2021-09-21 Shenzhen Mindray Bio-Medical Electronics Co., Ltd. Method and device for identifying fragmented red blood cells, blood cell analyzer and analysis method

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