Cell sorting method, sorting device, and program

Abstract

To inhibit an analysis result with insufficient accuracy from being output due to the nature of a specimen.SOLUTION: A cell classification method for classifying cells contained in a specimen, comprises: processing a specimen under a first preparation condition to prepare a first measurement sample; obtaining a first signal from the prepared first measurement sample; classifying cells included in the first measurement sample, using the first signal; processing the specimen under a second preparation condition different from the first preparation condition, to prepare a second measurement sample; obtaining a second signal from the prepared second measurement sample; classifying cells included in the second measurement sample, using the second signal; and comparing a cell classification result using the first signal and a cell classification result using the second signal, to output an analysis result including the number of cells based on the comparison result.SELECTED DRAWING: Figure 9

Description

[Technical field]

[0001] The present invention relates to a cell sorting method, a sorting device, and a program. [Background technology]

[0002] The system uses information obtained by irradiating a hemolyzed blood sample with light to identify white blood cells in the blood. For example, Patent Document 1 discloses a method for classifying a mixture of cellulose and cellulose according to a predetermined preparation condition. Identifying, classifying, and / or quantifying leukocytes and leukocyte subpopulations in a test sample prepared using the method described above. A system for analyzing a sample of whole blood is disclosed. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2016-514267 Summary of the Invention [Problem to be solved by the invention]

[0004] According to the system described in Patent Document 1, when classifying white blood cells in blood into multiple types, Analysis is performed on measurement samples prepared according to specific preparation conditions. However, it may not be possible to accurately classify white blood cells. For example, depending on the specimen, In some cases, erythrocytes and monocytes have similar sizes and membrane permeability to the staining solution, and this In such cases, it is not possible to accurately classify neutrophils and monocytes. The system described in Patent Document 1 analyzes a measurement sample prepared according to a predetermined preparation condition. Therefore, depending on the properties of the sample, the analytical results may be insufficiently accurate.

[0005] Therefore, the present invention is directed to preventing the output of analytical results with insufficient accuracy due to the nature of the sample. The purpose of this Act is to prevent the following: [Means for solving the problem]

[0006] The cell classification method according to one embodiment of the present invention is carried out by an analysis device (1), A cell sorting method for sorting cells, comprising: treating a specimen under a first preparation condition to obtain a first measurement sample. obtaining a first signal from the first measurement sample; classifying cells contained in the first measurement sample using a first signal; preparing a second measurement sample by treating the sample under second preparation conditions different from the first preparation conditions; obtaining a second signal from the prepared second measurement sample; and classifying cells contained in the second measurement sample using the first signal; The classification result of the first signal is compared with the classification result of the second signal, and based on the comparison result, and outputting an analysis result including the number of cells based on the result of the analysis. This makes it possible to prevent analysis results with insufficient accuracy from being output.

[0007] A cell sorting method according to another aspect of the present invention is carried out by an analysis device (1), A cell sorting method for sorting cells, comprising: treating a specimen under a first preparation condition to obtain a first measurement sample; preparing a sample, acquiring a first signal from the prepared first measurement sample, classifying cells contained in the first measurement sample using the first signal; Evaluating the classification ability of cell classification using the signal, and determining whether the evaluation result of the classification ability satisfies a predetermined condition. If the first condition is satisfied, the sample is treated under second preparation conditions different from the first preparation conditions to obtain a second preparing a second measurement sample; and acquiring a second signal from the prepared second measurement sample. classifying cells contained in the second measurement sample using the second signal; and and outputting the number of cells based on the second signal. This makes it possible to prevent analysis results with insufficient accuracy from being output.

[0008] A cell sorting method according to another aspect of the present invention is carried out by an analysis device (1), A cell sorting method for sorting cells, comprising: treating a specimen under a first preparation condition to obtain a first measurement sample; preparing a sample, acquiring a first signal from the prepared first measurement sample, classifying cells contained in the first measurement sample using the first signal; and preparing a second measurement sample by treating the sample under second preparation conditions different from the first preparation conditions. and acquiring a second signal from the prepared second measurement sample. classifying cells contained in the second measurement sample using the first signal; and evaluating the classification ability in cell classification. and outputting an analysis result including the number of cells based on the signal or an analysis result including the number of cells based on the second signal. This prevents the output of analytical results with insufficient accuracy due to the nature of the sample. This makes it possible to prevent the above from happening.

[0009] The analytical device (1) according to another aspect of the present invention is an analytical device ( 1), a sample preparation section (25) for preparing a measurement sample by preparing a specimen with a reagent; The apparatus includes a detection unit (26) that acquires a signal from a material, and a control unit (500), 00) in the sample preparation section (25), a sample is treated under first preparation conditions to prepare a first measurement sample. preparing a sample and treating the sample under second preparation conditions different from the first preparation conditions. and preparing a second measurement sample by using the above-mentioned second measurement sample, and causing the detection unit (26) to detect the prepared first measurement sample. Obtaining a first signal from the first measurement sample; and obtaining a second signal from the prepared second measurement sample. and acquiring a second signal from said first signal, and detecting the presence of a cell in said sample using said first signal. classifying cells in the specimen using the second signal; and classifying cells in the specimen using the second signal. a classification result of the cells using the first signal, and a classification result of the cells using the second signal. , and outputting an analysis result based on the comparison result. It is possible to prevent insufficient analytical results from being output due to the nature of the sample. It becomes Noh.

[0010] The analytical device (1) according to another aspect of the present invention is an analytical device ( 1), a sample preparation section (25) for preparing a measurement sample by preparing a specimen with a reagent; The apparatus includes a detection unit (26) that acquires a signal from a material, and a control unit (500), 00) in the sample preparation section (25), a sample is treated under first preparation conditions to prepare a first measurement sample. preparing a sample and treating the sample under second preparation conditions different from the first preparation conditions. and causing the detection unit (26) to perform the steps of: preparing a second measurement sample by using the acquiring a first signal from the first measurement sample prepared in the first measurement sample; classifying cells contained in the specimen using the first signal; and and evaluating the classification ability of the cell classification. The sample is subjected to second preparation conditions different from the first preparation conditions in the sample preparation section (25). and processing the sample to prepare a second measurement sample. acquiring a second signal from the prepared second measurement sample; classifying cells contained in the second measurement sample using a second signal; This allows for accurate measurement of the number of cells based on the characteristics of the sample. This makes it possible to prevent insufficient analysis results from being output.

[0011] The analytical device (1) according to another aspect of the present invention is an analytical device ( 1), a sample preparation section (25) for preparing a measurement sample by preparing a specimen with a reagent; The apparatus includes a detection unit (26) that acquires a signal from a material, and a control unit (500), 00) in the sample preparation section (25), a sample is treated under first preparation conditions to prepare a first measurement sample. preparing a sample and treating the sample under second preparation conditions different from the first preparation conditions. and preparing a second measurement sample by using the above-mentioned second measurement sample, and causing the detection unit (26) to detect the prepared first measurement sample. Obtaining a first signal from the first measurement sample; and obtaining a second signal from the prepared second measurement sample. and acquiring a second signal from said first signal, and detecting the presence of a cell in said sample using said first signal. classifying cells in the specimen using the second signal; and classifying cells in the specimen using the second signal. evaluating a classification ability in cell classification using the first signal; and evaluating the classification ability. Based on the results, an analysis result including a cell count based on the first signal or a cell count based on the second signal is obtained. The analysis results, including the number of cells, are output. This makes it possible to prevent analysis results with insufficient accuracy from being output.

[0012] A program according to another aspect of the present invention causes a computer to A sample preparation section (25) prepares a sample by treating the specimen under first preparation conditions to prepare a first measurement sample. and treating the sample under second preparation conditions different from the first preparation conditions. and obtaining a signal from the measurement sample. A detection unit (26) acquires a first signal from the prepared first measurement sample; acquiring a second signal from the second measurement sample; and classifying cells contained in the specimen using the first signal; and classifying the cells contained in the specimen using the second signal. classifying cells contained in the sample; and determining a result of the classification of the cells using the first signal and The cell classification result using the second signal is compared with the above, and an analysis result is output based on the comparison result. This prevents inaccurate analytical results due to the nature of the sample. It is possible to prevent the information from being output.

[0013] A program according to another aspect of the present invention includes a program for causing a computer to execute a measurement A sample preparation section (25) prepares a sample by treating the specimen under first preparation conditions to prepare a first measurement sample. and treating the sample under second preparation conditions different from the first preparation conditions. and obtaining a signal from the measurement sample. A detection unit (26) acquires a first signal from the prepared first measurement sample. evaluating a classification ability of cell classification using the first signal; and When the evaluation result satisfies a predetermined condition, the sample is added to the sample preparation section (25). and preparing a second measurement sample by treating the sample under second preparation conditions different from the first preparation conditions. and detecting a second signal from the prepared second measurement sample in the detection unit (26). and acquiring a second signal from the second measurement sample. classifying the cells detected by the second signal; and outputting a cell count based on the second signal. This prevents insufficient analytical results from being output depending on the characteristics of the sample. It becomes possible to suppress.

[0014] A program according to another aspect of the present invention includes a program for causing a computer to execute a measurement A sample preparation section (25) prepares a sample by treating the specimen under first preparation conditions to prepare a first measurement sample. and treating the sample under second preparation conditions different from the first preparation conditions. and a detection unit ( 26) obtaining a first signal from the prepared first measurement sample; and acquiring a second signal from a second measurement sample, and using the first signal to classifying cells contained in the sample; and detecting the presence of the cells contained in the sample using the second signal. Sorting the cells and evaluating the sorting ability of the cells using the first signal. and an analysis result including the number of cells based on the first signal based on the evaluation result of the classification ability. and outputting an analysis result including the number of cells based on the second signal. This prevents insufficient analytical results from being output due to the nature of the sample. This makes it possible. Effect of the Invention

[0015] According to the present invention, it is possible to prevent an analysis result with insufficient accuracy from being output depending on the properties of the sample. can be suppressed. [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 is a perspective view showing the appearance of an analysis device according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram illustrating a configuration example of a measurement unit. [Diagram 3] FIG. 2 is a diagram illustrating a configuration example of an optical detector. [Figure 4] FIG. 2 is a diagram illustrating an example of the configuration of an information processing unit. [Diagram 5] FIG. 2 is a diagram illustrating an example of a functional configuration of an information processing unit. [Figure 6] FIG. 13 is a diagram showing an example of a scattergram. [Figure 7] FIG. 13 is a diagram showing an example of blood cell distribution in a scattergram. [Figure 8] 13 is a flowchart showing an example of a process for assigning each blood cell to one of the clusters. [Figure 9] 13 is a flowchart illustrating an example of a processing procedure performed by the analysis device. [Figure 10] FIG. 13 is a diagram showing an example of classification results based on preparation conditions A and preparation conditions B. [Figure 11] FIG. 13 is a diagram showing an example of classification results based on preparation conditions A and preparation conditions B. [Figure 12] FIG. 13 is a diagram showing an example of classification results based on preparation conditions A and preparation conditions B. [Figure 13] 13 is a diagram for explaining an example of calculation of the degree to which the boundaries of two clusters are in contact with each other; FIG. [Figure 14] FIG. 13 is a diagram showing an example of classification results based on preparation conditions A and preparation conditions B. [Figure 15]FIG. 13 is a diagram showing an example of classification results based on preparation conditions A and preparation conditions B. [Figure 16] FIG. 13 is a diagram showing an example of classification results based on preparation conditions A and preparation conditions B. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] An embodiment of the present invention will be described with reference to the accompanying drawings. Those marked with the same symbol have the same or similar configuration.

[0018] <Configuration of the sample measurement system> FIG. 1 is a perspective view showing the appearance of an analysis device 1 according to the present embodiment. The analyzer 1 is a multi-item blood cell analyzer that counts the number of white blood cells contained in a sample. A measuring unit 2, a transport unit 3 arranged in front of the measuring unit 2, and an information processing unit The peripheral blood sample taken from the patient is placed in a sample container (a blood collection tube). A plurality of sample containers T are supported on a sample rack L. L is transported by the transport unit 3, and the blood sample is supplied to the measurement unit 2.

[0019] The information processing unit 4 includes a display unit 41 and an input unit 42. The sending unit 3 is connected to a host computer 5 (see FIG. 2) so as to be able to communicate with the host computer 5. The information processing unit 4 controls the operations of the measurement unit 2 and the transport unit 3. The analysis is performed based on the measurement results obtained by the test set 2, and the analysis results are transmitted to the host computer 5 (Fig. Refer to 2.

[0020] FIG. 2 is a diagram illustrating a schematic configuration example of the measurement unit 2. As shown in FIG.

[0021] The measurement unit 2 includes a hand unit 21, a sample container setting unit 22, and a barcode unit 2. 3, a specimen aspirating section 24, a sample preparation section 25, and a detection section 26. The sample preparation unit 25 includes a piercer 24a and is configured to aspirate a sample from a sample container T. It is equipped with a mixing chamber MC and a heater H, and is used for measurement by mixing the sample with a reagent. The detection unit 26 is equipped with an optical detector D, and detects blood from the measurement sample. The measurement unit 2 detects the ball. Each part of the measurement unit 2 is controlled by the information processing unit 4.

[0022] The sample container T positioned at the position P1 by the transport unit 3 is grasped by the hand unit 21. The sample is then pulled out upward from the sample rack L. Then, the hand unit 21 is swung. By this, the sample in the sample container T is mixed. After mixing, the sample container T is The sample container is set in the sample container setting section 22 located at position P1 by the sample container setting section 21. Thereafter, the sample container T is transported by the sample container setting section 22 to position P2.

[0023] When the sample container T is positioned at position P2, the barcode reader installed near position P2 reads the sample. The unit 23 reads the sample number from the barcode label attached to the sample container T. Thereafter, the sample container T is transported to position P3 by the sample container setting unit 22. When the sample container T is positioned at position P3, the sample aspirator 24 aspirates the sample through the piercer 24a. A predetermined amount of sample is aspirated from the sample container T. When the aspirating of the sample is completed, the sample container T The sample container is transported forward by the specimen container setting section 22 and the original sample wrapper is then inserted by the hand section 21. The sample aspirated through the piercer 24a is returned to the support position of the piercer 24a. After being transported to the position of the mixing chamber MC, a predetermined amount of the sample is introduced into the mixing chamber MC by the sample suction unit 24. Only the liquid is discharged.

[0024] The sample preparation unit 25 performs measurement by mixing the blood sample and the reagent according to predetermined preparation conditions. Prepare a sample. The reagents include a hemolytic agent (first reagent) and a fluorescent substance (second reagent). The hemolytic agent dissolves red blood cells and platelets in the blood, and the fluorescent substance stains white blood cells. To be colored.

[0025] The measurement sample prepared in the sample preparation section 25 is supplied to the optical detector D of the detection section .

[0026] FIG. 3 is a diagram showing a schematic configuration example of the optical detector D. The optical detector D includes a flow cell D1, sheath flow system D2, beam spot forming system D3, forward scattered light receiving system D4, It has a scattered light receiving system D5 and a fluorescent light receiving system D6.

[0027] The sheath flow system D2 sends the measurement sample into the flow cell D1, The beam spot forming system D3 is configured to generate a liquid flow. The light emitted from 31 passes through a collimator lens D32 and a condenser lens D33. The light is irradiated onto the flow cell D1. The blood cells contained in the liquid flow passing through the blood vessel are irradiated with the laser light. , and a beam stopper D34.

[0028] The forward scattered light receiving system D4 collects the forward scattered light (forward scattered light) through a forward condenser lens D41. The light passing through the pinhole D42 is received by the photodiode D43. The photodiode D43 detects the forward scattered light based on the peak value of the received forward scattered light. The side scattered light receiving system D5 detects the side scattered light (side scattered light The diffuse light is focused by the side focusing lens D51, and part of the light is focused by the dichroic mirror. The light is reflected by photodiode D52 and received by photodiode D53. The D53 generates a side scatter signal (SSC) based on the peak value of the received side scatter. Output.

[0029] Light scattering occurs when particles such as blood cells obstruct the path of light. This phenomenon occurs when the direction of the scattered light changes. By using this method, information on the size and material of the particles can be obtained. In particular, from forward scattered light, Information about the size of particles (blood cells) can be obtained. Also, from the side scattered light, When a blood cell particle is irradiated with a laser beam, the side scattered light intensity is depends on the internal complexity of the cell (shape, size, density of the nucleus and amount of granules).

[0030] The fluorescence receiving system D6 receives the light (fluorescence) that is transmitted through the dichroic mirror D52 from the side scattered light. ) is further passed through a spectral filter D61 and received by an avalanche photodiode D62. The avalanche photodiode D62 detects the peak value of the received fluorescent light. Based on this, a side fluorescence signal (SFL) is output.

[0031] When light is shone on blood cells stained with a fluorescent substance, fluorescence with a longer wavelength than the wavelength of the irradiated light is emitted. The intensity of the fluorescence is strong if the stain is strong, and the intensity of the fluorescence can be measured. This provides information regarding the degree of staining of blood cells.

[0032] The forward scattered light signal (FSC) and side scattered light signal (SSC) obtained for each blood cell by the optical detector D. The signal (SSC) and the side fluorescence signal (SFL) are sent to an information processing unit 4.

[0033] FIG. 4 is a diagram showing an example of the configuration of the information processing unit 4. As shown in FIG.

[0034] The information processing unit 4 is a personal computer, and includes a main body 40, a display unit 41, and The main body 40 is composed of a CPU 401, a ROM 402, and an RA. M403, a hard disk 404, a reading device 405, and an image output interface 4 06, an input / output interface 407, and a communication interface 408.

[0035] The CPU 401 executes a computer program stored in the ROM 402 and a RAM 403. The RAM 403 executes a computer program loaded into the ROM 403. 2 and hard disk 404 for reading out computer programs recorded therein. In addition, when these computer programs are executed, the RAM 403 stores the following: It is also used as a working area for the CPU 401.

[0036] The hard disk 404 stores an operating system, The computer program for the purpose of the operation and the data used to execute the computer program are recorded. The hard disk 404 also stores the information for executing the processing of the information processing unit 4. The reading device 405 is a CD drive or A non-transitory computer-readable recording medium that is made up of a DVD drive or similar Computers recorded on non-transitory computer readable medium 405a The program and data can be read out. If it is recorded on the medium 405a, it is read from the recording medium 405a by the reading device 405. The read program 404 a is stored in the hard disk 404 .

[0037] The image output interface 406 outputs a video signal corresponding to the image data to the display unit 41. The display unit 41 displays an image based on the video signal output from the image output interface 406. The user inputs an instruction via the input unit 42, and the input / output interface 4 07 receives a signal input via the input unit 42. is connected to a measurement unit 2, a transport unit 3, and a host computer 5, The PU 401 transmits and receives instruction signals between these devices via a communication interface 408. and transmits and receives data.

[0038] FIG. 5 is a diagram showing an example of the functional configuration of the information processing unit 4. The control unit 500 includes a CPU 4 01 reads and executes the computer program. This is realized using the RAM 403 or the hard disk 404 .

[0039] The control unit 500 controls the operation of the measurement unit 2 and the transport unit 3 to measure the sample. The measurement control unit 501 performs the measurement, and the forward scattered light signal (F Classification of leukocytes based on side scatter signal (SSC), side fluorescence signal (SFL) and side scatter signal (SSC). and an analysis processing unit 502 that performs counting of the number of blood cells, etc., and the number of blood cells by type of the measured white blood cells. A display control unit 50 that performs processing to display the image data, a scattergram (distribution diagram), etc. on the display unit 41. 3, and an input processing unit 504 that receives input from the user via the input unit 42.

[0040] The storage unit 505 stores the level of the forward scattered light signal (FSC) received from the measurement unit 2, Measurement information showing the level of side scatter light signal (SSC) and the level of side fluorescence signal (SFL) The measurement information is stored for each blood cell. The measurement information includes the level of forward scatter signal (FSC), side scatter The level of the side scatter signal (SSC) and the level of the side fluorescence signal (SFL) are This information is expressed as quantized values ​​called "channels." Channels will be explained later.

[0041] The analysis processing unit 502 detects the presence of the marker in the blood sample based on the measurement information stored in the memory unit 505. The white blood cells present are lymphocytes (LYMPH), monocytes (MONO), and neutrophils (NEUT). The blood cells are classified into basophils (BASO) and eosinophils (EO), and the number of each type is counted. .

[0042] The analysis processing unit 502 creates a scattergram (distribution diagram) based on the measurement information. to classify the white blood cells present in a blood sample.

[0043] Here, the scattergram is a forward scattered light signal output from the photodiode D43. (FSC), side scattered light signal (SSC) output from photodiode D53, Two types of side fluorescence signals (SFL) are output from the FT-IR photodiode D62. This is a two-dimensional distribution diagram with signals on the vertical and horizontal axes.

[0044] Forward scatter signal (FSC), side scatter signal (SSC) and side fluorescence signal (SFL) The types of white blood cells that can be classified vary depending on which two types of signals are used. In an embodiment, side fluorescence signals (SFL) and side scatter signals (SSC) are used to identify neutrophils, It classifies four types of white blood cells: lymphocytes, monocytes, and eosinophils. It also measures the forward scatter signal (FS C) and side fluorescence signal (SFL) were used to identify basophils and non-basophil leukocytes (neutrophils). The types of lymphocytes that can be classified into three types: lymphocytes, monocytes, and eosinophils.

[0045] The scattergram shown in Figure 6 has the side scattered light signal (SSC) on the horizontal axis and the side fluorescence on the vertical axis. When points corresponding to individual blood cells are plotted on a two-dimensional distribution diagram that serves as the signal (SFL), This is an example of a forward scatter signal (FSC) and a side fluorescence signal (SFL) as two axes. When classifying white blood cells other than leukocytes and basophils, the same method should be used to classify blood cells. This can be done.

[0046] The analysis processing unit 502 classifies the points on the scattergram into four subclasses of white blood cells. The four corresponding clusters (lymphocyte cluster A11, monocyte cluster A12, neutrophil cluster A13, The eosinophil cluster A13 and the eosinophil cluster A14 are classified as follows: For example, the points corresponding to each blood cell plotted on the scattergram and the points corresponding to the predetermined The degree of belonging of each blood cell to each cluster is obtained from the distance to the center of gravity of each cluster. Then, each blood cell is assigned to each cluster according to the degree of membership.

[0047] Here, an example of a procedure for allocating each blood cell to each cluster will be described in more detail. The two types of signals used to create the signalgram are amplified by an amplifier and then converted into digital form by an A / D converter. The signal is converted into a digital signal, i.e., quantized. For example, a signal is classified into one of 256 channels, numbered from 0 to 255.

[0048] Based on these digital signals, the information processing unit 4 performs the i-channel A scattergram is obtained with the jth channel on the X-axis and the jth channel on the Y-axis. The X-axis and Y-axis each have 256 channels, so there are a total of 256 x 256 blood cells. Each basic element is recorded with the number of blood cells that correspond to that basic element. For example, if the X axis is channel 1 and the Y axis is channel 2, the basic element value is 6. If there is one, the signal for the size of the cytoplasm of the blood cell is 1, and the signal for the density and size of the nucleus and granules is 2. This indicates that there are six blood cells with a signal magnitude of 2.

[0049] FIG. 8 is a flowchart showing an example of a process for assigning each blood cell to one of the clusters. First, the information processing unit 4 performs an initial division (S2). In this initial division, The distribution of the basic elements is shown in the scattergram in Fig. 1, ignoring the number of blood cells in each basic element. If it is a lymphocyte, it is a fixed area that is expected to be distributed there, and if it is a monocyte, it is a fixed area that is expected to be distributed there. The fixed area where neutrophils are expected to be distributed. The expected fixation area, the expected fixation area where eosinophils are clearly distributed, If the ghosts consist of platelets or red blood cells, they would obviously be distributed in the fixed regions. Each fixed area is set in advance. The blood cells present in each fixed area are assigned a degree of belonging. Let's say it's 1.

[0050] Next, the information processing unit 4 calculates the number of lymphocyte clusters using the following equations 1 and 2. The initial center of gravity is calculated (S4).

number

number

[0051] Next, the information processing unit 4 calculates the cluster number for each blood cell that does not belong to any immobilization region. The degree of belonging to the raster is calculated (S6). Calculate the degree of belonging to each cluster based on the distance from the location to the centroid of each cluster. Here, the distance of each blood cell to the center of gravity of each cluster is calculated by dividing the distance between the position of each blood cell and each cluster. The distance between the blood cells (Euclidean distance) is not used, but the minor axis length of a given ellipse is used to determine the position of each blood cell. The distance between each cluster is the distance between the clusters. Note that the specified ellipse is a ellipse with the center of gravity of the cluster as its center. , which has a specific slope determined in advance according to the cluster, and the blood cell of interest is located on the arc. The ellipse is located at the center of the sphere, and its minor axis is a, with its major axis being a k (k is a proportionality constant).

[0052] The distance L of each blood cell to each cluster x Once (x=1~N (N is the number of clusters)) is found, The degree of belonging of the blood cells to each cluster is calculated by the following formula 3. Of course, these degrees of belonging are Both values ​​are smaller than 1.

number

[0053] Next, for each cluster, the weights are calculated based on the degree of belonging of each blood cell to each cluster. The center of gravity is calculated (S8). This weighted center of gravity can be calculated, for example, by using Equations 4 and 5. .

number

number

[0054] After the weighted center of gravity of each cluster is calculated in this manner, the weighted center of gravity of each cluster is calculated in step S4. The change is compared with the corresponding initial center of gravity position of the data, and the change is a predetermined amount, for example, 0. If the amount is not the predetermined amount, the weighted center of gravity of each cluster calculated this time is determined as , and the processing steps S6, S8 and S10 are repeated by replacing the initial center of gravity of each cluster. That is, the distance of each blood cell to the weighted center of gravity of each cluster is calculated, and the weighted center of gravity is calculated based on this distance. Based on this, the degree of belonging of each blood cell to each cluster is calculated, and the weight of each cluster is newly calculated based on these degrees of belonging. The weighted center of gravity of each new cluster is calculated, and the weighted center of gravity of each new cluster is compared with that of each previous cluster. It is judged whether the amount of change from the weighted center of gravity position is a predetermined amount, and if it is not the predetermined amount, the current calculation is The weighted center of gravity of each cluster is used as the initial center of gravity and the processes in steps S6, S8, and S10 are performed. Repeat the procedure.

[0055] However, even if steps S6, S8, and S10 are repeated a predetermined number of times, the predetermined amount is not reached. Therefore, if the determination in step S10 is NO, the information processing unit Step 4 judges whether steps S6, S8, and S10 have been executed a predetermined number of times (S12). If so, the display unit 41 displays "analysis impossible" (S14), and the process ends.

[0056] When the change in the center of gravity of each cluster reaches a predetermined amount, the information processing unit 4 The final assignment of blood cells to each cluster is determined to determine the number of blood cells in each cluster ( Step S16).

[0057] The final assignment of each blood cell was determined by assigning it to the cluster with the maximum value of the final assignment degree. For example, if a basic element has 10 blood cells, the list of these blood cells may be The degree of membership for the lymphocyte cluster was 0.95, and the degree of membership for the monocyte cluster was 0.03. , the degree of belonging to the neutrophil cluster was 0.03, the degree of belonging to the eosinophil cluster was 0.02, When the ghost cluster membership is 0, these 10 blood cells are Thus, the cluster of lymphocytes showing the greatest degree of attribution will belong to the lymphocyte cluster.

[0058] By carrying out the above process, each blood cell in the scattergram is classified into one of the classes. The data is assigned to the

[0059] <Analytical device operation> The analytical device 1 first uses a measurement sample prepared according to predetermined preparation conditions. The processing includes classification of white blood cells, counting the number of blood cells, and outputting the analysis results. In this embodiment, this is referred to as the "normal mode." In addition, in the normal mode, the analysis device 1 If it is determined that the white blood cells may not be classified sufficiently, change the preparation conditions and perform the measurement. A fixed sample is prepared, and the white blood cell count and classification are carried out again, and the analysis results are output. This process is referred to as the "extended mode" in this embodiment.

[0060] FIG. 9 is a flowchart showing an example of a processing procedure performed by the analysis device 1.

[0061] In step S100, the sample preparation section 25 of the measurement unit 2 prepares a blood sample and a reagent in a predetermined The measurement sample is prepared by mixing according to the preparation conditions. This is referred to as production condition A.

[0062] Preparation condition A (also referred to as preparation condition B described below) is the time for reacting the reagent with the blood sample. Preparation condition A (also preparation condition B described below) is a condition related to the length of blood samples. The temperature conditions for reacting the reagent with the body and the mixing ratio of the blood sample and the reagent In addition, the blood sample may be subjected to a reaction with a reagent. The reaction time is determined based on the heating time when the blood sample and the reagent are mixed and heated with a heater. The condition may be related to the length of time for heating.

[0063] The reaction time, temperature and mixture ratio under preparation condition A are as follows: for a healthy blood sample, white blood cells to a value that can be used to classify lymphocytes, monocytes, neutrophils, basophils, and eosinophils. It is predetermined.

[0064] Next, the detection section 26 of the measurement unit 2 irradiates the prepared measurement sample with light (laser light). Then, the control unit 500 of the information processing unit 4 acquires the optical signal. Based on this, the white blood cells in the blood sample are classified and the number of each type of white blood cell is counted. Post a comment.

[0065] In step S101, the control unit 500 of the information processing unit 4 receives the result of classifying white blood cells and Then, a scattergram and / or blood cell count for each white blood cell is output.

[0066] In step S102, the control unit 500 controls the white blood cell count for the measurement sample prepared under preparation condition A. By evaluating the classification ability of white blood cells (cell classification), it is possible to determine whether each white blood cell is sufficiently separated. The classification ability is the degree to which multiple types of cells can be classified correctly. More specifically, the blood sample is analyzed to determine the amount of white blood cells in the blood. Correct classification by type (lymphocytes, monocytes, neutrophils, basophils, and eosinophils) For example, the control unit 500 may classify white blood cells into lymphocytes, monocytic cells, and At least two types of leukocytes among leukocytes, neutrophils, basophils, and eosinophils, are sufficiently differentiated. If they are not separated, it is determined that the individual white blood cells have not been sufficiently classified.

[0067] When the control unit 500 judges that each white blood cell has been sufficiently classified ("classification ability is not within a predetermined range"), If the condition is not met, the process ends without switching to the extended mode. On the other hand, if it is determined that there is a possibility that each white blood cell may not be sufficiently classified ("the classification ability is not as specified" When the condition is satisfied, the control unit 500 performs the following to transition to the extended mode: The process proceeds to step S103. If there is a possibility that each white blood cell has not been sufficiently classified, For example, blood samples taken from subjects with certain diseases may be taken from unhealthy subjects. This is thought to occur when a sample is analyzed, etc.

[0068] In step S103, the sample preparation section 25 of the measurement unit 2 mixes the blood sample and the reagent again. The measurement sample is prepared by mixing according to preparation condition A. Next, the measurement unit 2 The output unit 26 obtains an optical signal by irradiating the prepared measurement sample with light. The control unit 500 of the information processing unit 4 classifies white blood cells contained in the blood sample using the optical signal. At the same time, the number of each type of white blood cell is counted.

[0069] In step S104, the sample preparation section 25 of the measurement unit 2 prepares the blood sample and the reagent. The measurement sample is prepared by mixing according to preparation condition B, which is different from condition A. The detection unit 26 of the measurement unit 2 irradiates the prepared measurement sample with light to obtain an optical signal. Next, the control unit 500 of the information processing unit 4 uses the optical signal to detect the amount of the ionizing radiation contained in the blood sample. The white blood cells detected are classified and the number of each type of white blood cell is counted.

[0070] In step S105, the control unit 500 performs a white blood cell analysis using the optical signal obtained under the preparation condition A. The classification results of spheres are compared with the classification results of white blood cells using optical signals obtained under preparation condition B. The comparison result of the classification results under preparation condition A and the classification results under preparation condition B is within a specified range. If the above is true, it is determined that the white blood cells have been sufficiently classified under preparation condition A, and step S On the other hand, if the comparison result is outside the predetermined range, the processing proceeds to step 106. It was determined that the classification results under preparation condition A were more appropriate than those under preparation condition B, and the steps were Proceed to the processing procedure of S107.

[0071] In step S106, the control unit 500 performs the following operation based on the comparison result in step S105: The control unit 500 outputs the analysis result including the blood cell count for each type of white blood cell. The count number and / or scatter of each white blood cell based on the optical signal obtained under preparation condition A Output grams.

[0072] In step S107, the control unit 500 performs the following operation based on the comparison result in step S105: For example, the control unit 500 outputs the analysis result including the white blood cell count obtained under the preparation condition A. The count number and / or scattergram of each white blood cell based on the optical signal and the count of each white blood cell are The information on the reliability of the number of cases is output to the display unit 41. For example, the number of white blood cells counted and / or the scattergram may be unreliable. It may be a flag or a character string indicating

[0073] The above-described processing procedures of steps S100, S103, and S104 In each of the above, the control unit 500 detects the side fluorescence emitted from the measurement sample A (or the measurement sample B). White blood cells are classified using two optical signals: side-scattered light (SFL) and side-scattered light (SSC). In order to classify white blood cells, two types of scattered light with different angles (i.e., forward scattered light signal (FS C), side scatter signal (SSC) and side fluorescence signal (SFL) An optical signal may also be used.

[0074] The control unit 500 also detects two light signals, a side fluorescent light signal (SFL) and a side scattered light signal (SSC). The distribution of leukocytes was determined based on the scattergram obtained by plotting the signals on different axes. Get similar results.

[0075] The control unit 500 also uses the side fluorescent light signal (SFL) and the side scattered light signal (SSC) By doing so, the blood samples were classified into four types: lymphocytes, monocytes, neutrophils, and eosinophils. Get it.

[0076] The control unit 500 receives a forward scattered light signal (FSC), a side scattered light signal (SSC), and a side scattered light signal (SSC). By using all the single fluorescence signals (SFL), blood samples were analyzed to determine lymphocytes, monocytes, neutrophils, and leukocytes. A classification result in which the leukocytes are classified into five types, including basophils, eosinophils, and eosinophils, may be acquired.

[0077] The preparation condition A, the measurement sample, and the optical signal in the processing procedure of step S103 described above are These are called the first preparation condition, the first measurement sample, and the first optical signal, respectively. The preparation condition B, the measurement sample, and the optical signal in the process step 104 are respectively set to the second preparation condition These are called the second measurement sample and the second optical signal. The preparation condition A, the measurement sample, and the optical signal are respectively set to the third preparation condition, the third measurement sample, and the third is called the optical signal.

[0078] As another example, the preparation condition A, the measurement sample, and the light in the processing procedure of step S100 The signals are referred to as the first preparation condition, the first measurement sample, and the first optical signal, respectively. The preparation condition B, the measurement sample, and the optical signal in the processing procedure of step S104 are respectively set to the second The preparation conditions, the second measurement sample, and the second optical signal are referred to as the preparation conditions, the second measurement sample, and the second optical signal.

[0079] In the above embodiment, the preparation of the sample under preparation condition A, the measurement of the optical signal, and the classification are carried out as follows: This is executed in steps S100 and S103. A long time has elapsed between the preparation of the sample in step S100 and the preparation of the sample in step S103. Even if the sample is prepared under the preparation condition B in step S104, the sample is similar to the sample prepared under the preparation condition B. Using a fresh sample, the sample is prepared under preparation condition A. Therefore, in step S1 This can improve the accuracy of the analysis results output in step S106 or step S107.

[0080] (Modification 1 regarding the operation of the analyzer) In the processing procedure of step S107, the control unit 500 The count number and / or scattergram of each white blood cell based on the signal is output.

[0081] (Modification 2 regarding the operation of the analyzer) The control unit 500 performs steps S103 and S105 of the process shown in FIG. The above processing procedure may be omitted. That is, the control unit 500 performs the following processing under the preparation condition A. When the evaluation result of the white blood cell classification ability using the obtained optical signal satisfies a predetermined condition, The process of step S103 is not executed, and the process of step S104 is executed. In addition, the control unit 500 controls the temperature sensor 100 to detect the temperature obtained under the preparation condition B obtained in the processing procedure of step S104. The optical signal generated by the blood sample is used to classify the white blood cells contained in the blood sample and to count the number of each type of blood cell. The count number and / or scattergram of each white blood cell are output to the display unit 41.

[0082] In the second modification, the preparation condition A, the measurement sample, and the optical signal in the processing procedure of step S100 are The signals are referred to as the first preparation condition, the first measurement sample, and the first optical signal, respectively. The preparation condition A, the measurement sample, and the optical signal in the process step S104 are respectively set to the second preparation condition A, the measurement sample, and the optical signal. These are called the preparation conditions, the second measurement sample, and the second optical signal.

[0083] (Modification 3 regarding the operation of the analyzer) The control unit 500 controls the input unit 42 to measure the blood sample in the extended mode instead of the standard mode. In this case, the control unit 500 receives a measurement instruction from the user to set the measurement. When the above-mentioned signal is received, the process of steps S100 to S102 in the process procedure shown in FIG. Skip a step (i.e., skip standard mode).

[0084] (Modification 4 regarding the operation of the analyzer) The control unit 500 performs the process of combining the above-described modified example 1 and modified example 3. That is, the control unit 500 issues a measurement instruction to measure the blood sample in the extended mode rather than the standard mode. When the instruction is received from the user, steps S100 to S104 are performed in the process shown in FIG. The processing procedure of step S102 is omitted (that is, the standard mode is omitted). In the processing procedure of 107, the counting of each white blood cell based on the optical signal obtained under preparation condition B is performed. The number of samples and / or the scattergram are output.

[0085] <Examples of Preparation Condition A and Preparation Condition B> Preparation condition B is a condition in which the time for reacting the reagent with the blood sample is extended compared to preparation condition A. In addition, preparation condition B is set at a temperature higher than preparation condition A when reacting the reagent with the blood sample. The mixing ratio of the blood sample and the reagent may be set to a higher value. Alternatively, the proportion of the reagent may be higher than that in Preparation Condition A.

[0086] <Specific example of process for determining or analyzing white blood cell classification results> In the process of determining whether to switch from normal mode to extended mode, each white blood cell is sufficiently In the extended mode, the process of determining whether the preparation conditions are correct or not (S102) The results of white blood cell classification under A and B were compared and analyzed. The process of outputting the results (S105 to S107) will now be described in detail.

[0087] (Pattern A) Pattern A is one of the clusters in the scattergram. This is a method for determining or comparing the classification results of each white blood cell by using the number of cells belonging to the same cluster.

[0088] [Process to determine whether to switch from normal mode to extended mode] The control unit 500 classifies the white blood cells, and then detects the white blood cells belonging to one of the clusters. If the count is a certain value (e.g. 0) or less than a certain value (e.g. 5 or 10), It is judged that each white blood cell may not be classified sufficiently (i.e., the classification ability does not meet the specified conditions). On the other hand, if the counts of all white blood cells are not a predetermined value (for example, 0), If the value is equal to or greater than a predetermined value, it is determined that each white blood cell has been sufficiently classified (i.e., (It is determined that the similar ability does not meet the specified conditions.)

[0089] As an example, a side fluorescence signal (SFL) and a side scatter signal (SSC) are used as optical signals. The results showed that white blood cells were classified into four types: neutrophils, lymphocytes, monocytes, and eosinophils. When the eosinophil count is a certain value (e.g., 0), each white blood cell is sufficiently classified. It is determined that there is no

[0090] [Process for comparing the classification results of preparation conditions A and B] The control unit 500 detects a plurality of classes included in the scattergram obtained under the preparation condition A. The number of cells belonging to any one of the clusters in the data and the number of cells belonging to the scan obtained under preparation condition B were The number of cells belonging to any one of the multiple clusters contained in the datagram Based on the comparison results, the analysis results including the white blood cell count are output.

[0091] More specifically, the control unit 500 detects the following in the scattergram obtained under preparation condition A: The number of leukocytes belonging to any one of the multiple clusters and the number of leukocytes belonging to the preparation condition B were The scattergram obtained was then used to find the clusters that matched the clusters. If the difference between the number of white blood cells belonging to each group is within a specified range, each white blood cell is sufficiently If the difference is greater than the predetermined value, the process proceeds to step S106. If the range is exceeded, the classification results under preparation condition B are more appropriate for each leukocyte than those under preparation condition A. Then, the process proceeds to step S107.

[0092] FIG. 10 is a diagram showing an example of a classification result under preparation condition A and a classification result under preparation condition B. In the example of FIG. 10, the classification result for preparation condition A does not include the eosinophil cluster (the eosinophil cluster The classification results for preparation condition B showed eosinophil clusters (eosinophil count was 0), whereas the classification results for preparation condition B showed eosinophil clusters (eosinophil count was 100 or more). Therefore, the control unit 500 determines that the classification result under the preparation condition B is higher than that under the preparation condition B. It is judged that the white blood cells are classified more appropriately than A.

[0093] (Pattern B) Pattern B is the classification result of each white blood cell using the number of clusters present in the scattergram. This is a method for determining or comparing the above.

[0094] [Process to determine whether to switch from normal mode to extended mode] The control unit 500 classifies the white blood cells, and determines the number of clusters present in the scattergram. If the value is below a certain level, it is determined that there is a possibility that each white blood cell is not being sufficiently classified (i.e. On the other hand, if the number of clusters is a predetermined value, , each white blood cell is judged to be sufficiently classified (i.e., the classification ability does not meet the specified conditions) The predetermined value is determined in advance depending on the type of scattergram. For example, a scanning sig- nal with side fluorescence (SFL) as the Y-axis and side scatter (SSC) as the X-axis is used. For the gram, there are four predefined values: neutrophils, lymphocytes, monocytes, and eosinophils.

[0095] [Process for comparing the classification results of leukocytes under preparation conditions A and B] The control unit 500 determines the number of clusters present in the scattergram obtained under the preparation condition A. Based on the comparison with the number of clusters present in the scattergram obtained under preparation condition B, The analysis results, including the white blood cell count, are output.

[0096] More specifically, the control unit 500 detects the presence of the scattergram obtained under the preparation condition A. The number of clusters in the scattergram obtained under preparation condition B was compared with the number of clusters in the scattergram obtained under preparation condition B. If the difference is within a predetermined range (e.g., the difference is 0), each of the white blood cells is sufficiently treated under preparation condition A. If it is determined that the classification has been completed, the process proceeds to step S106. If the difference is greater than the range (e.g., the difference is 1 or more), the classification result under preparation condition B is higher than that under preparation condition A. It is determined that each white blood cell has been appropriately classified, and the process proceeds to step S107.

[0097] In the example of Figure 10, the classification result for preparation condition A has only three clusters, but There are four clusters in the classification result of the preparation condition B. It is determined that the classification results under preparation condition B are more appropriate for classifying white blood cells than those under preparation condition A.

[0098] (Pattern C) Pattern C is a method for classifying each white blood cell by using the distance between two clusters in the scattergram. This is a method for determining or comparing the classification results of the balls.

[0099] [Process to determine whether to switch from normal mode to extended mode] The control unit 500 classifies the white blood cells and detects two clusters in the scattergram. If the distance between the white blood cells is less than a certain value, there is a possibility that the white blood cells are not being classified sufficiently. On the other hand, the difference between the two clusters is If the distance exceeds a predetermined value, it is determined that each white blood cell is sufficiently classified (i.e., classification (determining that the function does not meet the specified conditions).

[0100] As an example, the control unit 500 may determine that the distance between the neutrophil cluster and the monocyte cluster is a predetermined value. If the value is below a certain level, it is determined that each white blood cell has not been sufficiently classified.

[0101] [Process for comparing the classification results of leukocytes under preparation conditions A and B] The control unit 500 detects two classes included in the scattergram obtained under the preparation condition A. The distance between the clusters in the scattergram obtained under preparation condition B was Based on the comparison result with the distance, the analysis result including the white blood cell count is output.

[0102] More specifically, the control unit 500 detects the following in the scattergram obtained under preparation condition A: The distance between two given clusters and the distance between the two given clusters in the scattergram obtained under preparation condition B. The difference between the distance between the two clusters is within a certain range (for example, within 10 channels). etc.), it is determined that each leukocyte has been sufficiently classified under preparation condition A, and the step On the other hand, if the difference is greater than a predetermined range (for example, 10 chamfers), the process proceeds to step S106. (When the number of leukocytes exceeds the number of cells, etc.), the classification results under preparation condition B are better than those under preparation condition A. If it is determined that the classification has been performed appropriately, the process proceeds to step S107.

[0103] In the example of Figure 11, the classification result for preparation condition A shows a gap between the neutrophil cluster and the eosinophil cluster. The distance between the neutrophil cluster and the eosinophil cluster is 25 channels. The distance between clusters is 50 channels. In this case, the difference in the distance between clusters is 25 channels. The channel is outside the predetermined range (10 channels). Therefore, the control unit 500 It was determined that the classification results under preparation condition B were more appropriate than those under preparation condition A. Determine.

[0104] The distance between clusters was calculated by comparing the average value of the X-axis of each blood cell position belonging to each cluster. Here, the average value of the X-axis of each blood cell position belonging to the cluster is the X-axis of each blood cell. It can be calculated by dividing the total axis value (channel value) by the number of blood cells. For example, as shown in FIG. 7, if there is a cluster surrounded by the region of X=0 to 2 and Y=0 to 3, If we assume that the average value on the X-axis is ((3+6)×1+(1+10+8)×2)÷(3 +6+1+10+8) ≒ 1.68. Alternatively, the distance may be obtained by comparing the average Y-axis values ​​of the positions of each blood cell belonging to a cluster.

[0105] In pattern C, the two clusters for which distances are compared are different depending on the type of scattergram. For example, the side fluorescence signal (SFL) may be set as the Y-axis, and the side scattering In the case of a scattergram with the optical signal (SSC) on the x-axis, lymphocyte clusters and monocyte clusters are Alternatively, the distance between the monocyte cluster and the neutrophil cluster may be compared. Alternatively, the distance between the neutrophil cluster and the eosinophil cluster may be compared. The distance between the target and the target may be compared.

[0106] (Pattern D) Pattern D is the degree to which the boundaries of two clusters in the scattergram are in contact. This is a method for determining or comparing the classification results of each white blood cell using the above method.

[0107] [Process to determine whether to switch from normal mode to extended mode] The control unit 500 classifies the white blood cells and detects two clusters in the scattergram. If the degree of contact between the boundaries is below a certain value, each white blood cell is not classified sufficiently. On the other hand, it is judged that there is a possibility that the classification ability satisfies a predetermined condition. If the borders of two clusters touch each other to a certain degree, each leukocyte is classified sufficiently. It is determined that the classification ability satisfies the predetermined condition (i.e., it is determined that the classification ability does not satisfy the predetermined condition).

[0108] [Process for comparing the classification results of preparation conditions A and B] The control unit 500 detects two clusters included in the scattergram obtained under the preparation condition A. The degree of contact between the boundaries of the two samples and the 2 The analysis results, including the white blood cell count, are based on the comparison of the degree to which the boundaries of the clusters are in contact with each other. Output.

[0109] More specifically, the control unit 500 detects the following in the scattergram obtained under preparation condition A: The degree of contact between the boundaries of the two clusters and the scattergram obtained under preparation condition B If the difference between the degree of contact between the boundaries of two clusters in the cluster is within a certain range, It is determined that the white blood cells are sufficiently classified under preparation condition A, and the process of step S106 is performed. On the other hand, if the difference is beyond the predetermined range, the classification result under preparation condition B is It is determined that the white blood cells are classified more appropriately under the preparation condition A than under the preparation condition B, and the process of step S107 is performed. Proceed to the procedure.

[0110] FIG. 12 is a diagram showing an example of a classification result under preparation condition A and a classification result under preparation condition B. In the example of Figure 12, the classification result for preparation condition A shows that the neutrophil cluster and the eosinophil cluster are in contact with each other. However, the classification results for preparation condition B showed that the neutrophil clusters and eosinophil clusters were not in contact with each other. Therefore, the control unit 500 determines that the classification result under preparation condition B is smaller than that under preparation condition A. It is judged that the ball has been properly classified.

[0111] FIG. 13 is a diagram for explaining an example of calculating the degree of contact between the boundaries of two clusters. Figure 13 shows the area where the neutrophil cluster and the eosinophil cluster are in contact in the scattergram. The vertical axis is the axis of side fluorescence (SFL) (Y axis), and the horizontal axis is the axis of side fluorescence (SFL) (Y axis). is the side scatter signal (SSC) axis (X-axis).

[0112] The degree to which the boundaries of two clusters are in contact is expressed as the degree to which either of the two clusters is in contact. Among the coordinates around each coordinate on the boundary of the cluster, there are blood cells that belong to the other cluster. For example, in the case of FIG. 13(a), the number of coordinates around the A4 coordinates is counted. Of the eight coordinates, the only one where a neutrophil exists is the one at the top left of A4. Among the eight coordinates around the coordinate of A8, the coordinates where neutrophils exist are the left and right coordinates of A8. The three coordinates are the top and bottom. When counted in this way, in the case of Figure 13(a), neutrophils The degree of contact between the cluster and the eosinophil cluster is "9". In this case, the degree to which the boundaries of the neutrophil cluster and the eosinophil cluster touch is "1."

[0113] In the example of Figure 13, the coordinates around the eosinophil cluster where neutrophils are present are clustered. The number of coordinates is counted based on the neutrophil cluster. Count the number of coordinates that contain eosinophils among the coordinates around the boundary of the data. do.

[0114] In pattern D, the degree of contact between two clusters is compared using scatter tags. For example, the side fluorescence signal (SFL) may be plotted on the Y axis. In the case of a scattergram with the side scatter signal (SSC) on the X-axis, the lymphocyte class is The degree of contact between the monocyte cluster and the neutrophil cluster may be compared. It is also possible to compare the degree of contact between neutrophil clusters and eosinophil clusters, or the degree of contact between neutrophil clusters and eosinophil clusters. You can compare the degree to which

[0115] (Pattern E) Pattern E is a cluster distribution pattern of blood cells in a scattergram. This is a method for determining or comparing the classification results of each white blood cell.

[0116] [Process to determine whether to switch from normal mode to extended mode] The control unit 500 detects at least one of the white blood cells present in the scattergram as a result of classifying the white blood cells. If the distribution shape of blood cells on the X-axis or Y-axis of the cluster of each white blood cell meets the specified conditions, It is determined that the ball may not be sufficiently classified (i.e., the classification ability does not meet the specified criteria). On the other hand, if at least one cluster in the scattergram has a If the distribution shape of blood cells on the Y axis does not match the specified conditions, each white blood cell cannot be classified sufficiently. It is determined that the classification ability does not satisfy a predetermined condition (i.e., it is determined that the classification ability does not satisfy a predetermined condition).

[0117] The given condition is that the number of blood cells present in each channel on the X-axis is represented as a histogram. There may be two or more peaks in each channel in the X-axis. A method for calculating the number of blood cells will be described with reference to FIG. 7. For example, in the region of X=0 to 2 and Y=0 to 3, In this case, we assume that there exists a cluster surrounded by a region. The blood counts in the two cases are 0, 9, and 19, respectively.

[0118] [Process for comparing the classification results of preparation conditions A and B] The control unit 500 detects a predetermined class present in the scattergram obtained under the preparation condition A. The distribution shape of blood cells on the X-axis or Y-axis of the data and the scattergram obtained under preparation condition B The distribution shape of blood cells on the X-axis or Y-axis of the specified cluster in the system is compared with the distribution shape of blood cells on the X-axis or Y-axis of the specified cluster in the system. Based on this, the analysis results including the white blood cell count are output.

[0119] More specifically, the control unit 500 detects the presence of the scattergram obtained under the preparation condition A. The number of peaks in the distribution shape of blood cells on the X-axis or Y-axis of a given cluster, and the preparation conditions The blood concentration on the X or Y axis of a given cluster in the scattergram obtained by B The number of peaks in the distribution of the spheres is the same, or the number of peaks in the distribution of the spheres is greater under preparation condition B than under preparation condition A. If the number of peaks is greater, it is determined that the white blood cells are sufficiently classified under preparation condition A. Proceed to step S106. On the other hand, if the number of peaks has decreased and the number of clusters has increased, In this case, the classification results under preparation condition B are more appropriate for classifying each leukocyte than those under preparation condition A. It is determined that the EEPROM 100 is in the ON state, and the process proceeds to step S107.

[0120] The predetermined clusters used to determine the number of peaks are lymphocyte cluster, monocyte cluster, neutrophil cluster, and The cluster may be any one of the clusters, the eosinophil cluster, and the basophil cluster. Any one of the clusters (eg, the neutrophil cluster) may be predetermined.

[0121] FIG. 14 is a diagram showing an example of a classification result under preparation condition A and a classification result under preparation condition B. In the example of FIG. 14(a), under preparation condition A, there are two peaks in the neutrophil cluster. However, in the case of preparation condition B, there is only one peak in the neutrophil cluster. The number of the control units 500 is three under preparation condition A, but four under preparation condition B. The classification results under preparation condition B were more appropriate than those under preparation condition A. Make a judgment.

[0122] (Pattern F) Pattern F uses the number of clusters in the scattergram and the number of boundary particles to determine each This is a method for determining or comparing the results of white blood cell classification.

[0123] [Process for comparing the classification results of preparation conditions A and B] The control unit 500 determines the number of clusters present in the scattergram obtained under the preparation condition A. , the number of boundary particles in a given cluster and the scattergram obtained under preparation condition B Based on the result of comparing the number of clusters present with the number of boundary particles in the given cluster, , and output analysis results including white blood cell count.

[0124] More specifically, the control unit 500 detects the presence of the scattergram obtained under the preparation condition A. The number of clusters present in the scattergram obtained under preparation condition B is If the number of boundary particles in a given cluster under preparation condition B is different, If the number of boundary particles in a given cluster under condition A is greater than or equal to that under condition A, the preparation It is determined that each white blood cell has been sufficiently classified under condition A, and the processing procedure of step S106 is performed. Proceed to.

[0125] On the other hand, the control unit 500 detects the class present in the scattergram obtained under the preparation condition A. The number of clusters in the scattergram obtained under preparation condition B is the same as the number of clusters in the scattergram obtained under preparation condition B. and the number of boundary particles in a given cluster under preparation condition B is greater than that under preparation condition A. If the number of boundary particles in a given cluster is smaller than the number of boundary particles in the given cluster, the classification result under preparation condition B is It is determined that the white blood cells are classified more appropriately under the preparation condition A than under the preparation condition B, and the process of step S107 is continued. Proceed to procedure.

[0126] In addition, the "number of boundary particles in a given cluster" in pattern F is the number of boundary particles in a given cluster. It means the number of blood cells of a type different from a given cluster that exist in the boundary part of the data. In general, a scattergram using side fluorescence (SFL) and side scatter (SSC) signals is used. In this study, for example, the blood cells in the right border of the neutrophil cluster had forward scattering. There are cases where blood cells can be classified as eosinophils by considering the optical signal (FSC). In such a case, the number of blood cells that can be classified as eosinophils is counted as "the number of blood cells in a given cluster." This corresponds to the "number of boundary particles in the

[0127] In pattern F, the classification results under preparation condition B despite the reduction in the number of boundary particles The reason why we judge that the counts obtained under preparation condition A are more appropriate is that there is an error in the counts obtained under preparation condition A. (For example, a neutrophil was counted as an eosinophil.) This is why.

[0128] (Pattern G) Pattern G uses the width and number of clusters present in the scattergram. This is a method for determining or comparing the classification results of each white blood cell.

[0129] [Process for comparing the classification results of preparation conditions A and B] The control unit 500 detects a predetermined class present in the scattergram obtained under the preparation condition A. The width and number of clusters of the data and the predetermined number of clusters present in the scattergram obtained under preparation condition B Based on the results of comparing the width of the clusters and the number of clusters, the analysis results including the white blood cell count are output. do.

[0130] More specifically, the control unit 500 detects the presence of the scattergram obtained under the preparation condition B. The width of a given cluster is a given width present in a scattergram obtained under preparation condition A. The width of the cluster is longer than or equal to the width of the cluster, or the number of clusters under preparation condition B is , if the number of clusters is smaller than or equal to that in preparation condition A, It is determined that each white blood cell has been sufficiently classified, and the process proceeds to step S106.

[0131] The control unit 500 detects a predetermined class present in the scattergram obtained under the preparation condition B. The width of the cluster is smaller than the width of a given cluster present in the scattergram obtained under preparation condition A. The number of clusters in preparation condition B is shorter than that in preparation condition A. When the number of cells is greater than the number of cells in the sample, the classification results under preparation condition B are better than those under preparation condition A. If it is determined that the classification has been performed appropriately, the process proceeds to step S107.

[0132] FIG. 16 is a diagram showing an example of a classification result under preparation condition A and a classification result under preparation condition B. In the example of FIG. 16, the width of the neutrophil cluster under preparation condition A is 50 channels. The width of the neutrophil cluster in preparation condition B is 40 channels. The number of clusters in the control condition is three, whereas the number of clusters in the control condition B is four. The control unit 500 classifies white blood cells more appropriately under preparation condition B than under preparation condition A. It is judged that it is possible.

[0133] The width of the cluster may be the width on the X axis or the width on the Y axis. The width of the cluster is determined by the number of blood cells in each channel on the X-axis (or Y-axis). It may be the width of the channel that is equal to or greater than a certain number.

[0134] The scattergram under preparation condition A and the scattergram under preparation condition B described above are The grams are referred to as the first distribution map and the second distribution map, respectively.

[0135] In addition, in the processing procedure of step S105, the optical signal obtained under preparation condition A is used. The classification results of the white blood cells were as follows: "The number of white blood cells belonging to any one of the clusters in the data," "The number of scatter in preparation condition A," The number of clusters in the scattergram under preparation condition A, "The distance between the two clusters in the scattergram under preparation condition A" "The degree to which the boundaries of two clusters are in contact" and "The degree to which the boundaries of two clusters are in contact" At least one of the "width of a specific cluster among multiple clusters included in the cluster" It may be expressed as being.

[0136] In addition, in the processing procedure of step S105, the optical signal obtained under preparation condition B is used. The classification results of the white blood cells were as follows: "The number of white blood cells belonging to any one of the clusters in the data," "The number of scatter in preparation condition B," "Number of multiple clusters in the scattergram under preparation condition B" "The distance between the two clusters in the scattergram under preparation condition B" "The degree to which the boundaries of two clusters are in contact" and "The degree to which the boundaries of two clusters are in contact" At least one of the "width of a specific cluster among multiple clusters included in the cluster" It may be expressed as being.

[0137] In addition, in the processing procedure of step S105, the classification result under preparation condition A and the classification result under preparation condition B The comparison of the classification results with the classification results by The number of leukocytes belonging to any one of the clusters and the number of leukocytes belonging to the clusters under preparation condition B were White blood cells that belong to one of the multiple clusters included in the cattergram "Comparison of the number of clusters in the scattergram under preparation condition A" and " The number of clusters in the scattergram under preparation condition B was compared with that under preparation condition C. "The distance between the two clusters in the scattergram under preparation condition A and the "Comparison results with the distance between two clusters contained in the scattergram under manufacturing condition B," The degree to which the boundaries of two clusters in the scattergram under preparation condition A are in contact The boundaries of the two clusters in the scattergram for preparation condition B are in contact with each other. "Comparison of the degree of the chromatogram with that of the scattergram under preparation condition A" and "Comparison of the degree of the chromatogram with that under preparation condition B" The width of a given cluster among multiple clusters and the width of the clusters included in the scattergram under preparation condition B "Comparison result with the width of a predetermined cluster among a plurality of clusters" It may also be expressed as:

[0138] <Summary> According to the embodiment described above, in the standard mode, the sample prepared under the preparation condition A is When measuring a blood sample, it is possible that white blood cells are not being classified sufficiently in normal mode. If it is determined that the blood sample is 100%, the system switches to the extended mode, and the blood sample prepared under preparation condition A and the blood sample prepared under preparation condition B are The white blood cell count was then classified for both blood samples prepared under condition B. In addition, the two classification results are compared and the analysis results including the comparison results are output. This prevents insufficient analytical results from being output due to the nature of the sample. becomes possible.

[0139] The above-described embodiment shows an example of classifying neutrophils and eosinophils under two types of preparation conditions. However, the present invention is not limited thereto, and examples thereof include side fluorescence signals (SFL) and side scatter signals. (SSC) may be used to classify neutrophils and monocytes. In this case, FIG. From the reaction time between the sample and the reagent under the preparation conditions of step S103 shown in FIG. It is advisable to shorten the reaction time between the sample and the reagent in the preparation condition of 104. The reaction temperature in the preparation conditions in step S104 is calculated from the reaction temperature in the preparation conditions in step S103. The concentration may be lowered, or the mixing ratio of the reagents in the preparation conditions in step S103 may be adjusted to be higher than the mixing ratio in step S104. The mixing ratio of the reagents in the preparation conditions of step S104 may be lowered.

[0140] In addition, the types of optical signals used for classifying blood cells are not limited, and may be any combination other than those described above. Two types may be combined, three or more types of optical signals may be combined, or one type An optical signal may also be used.

[0141] In addition, the types of cells classified by the two preparation conditions are not limited to white blood cells, but also include red blood cells. The blood cells may be corpuscles, platelets, or other blood cells.

[0142] The embodiment described above is not limited to the analysis of blood samples, and can be used to analyze various body fluids other than blood, such as urine. In this case, the term "white blood cells" in the above description can be changed to " For example, the analysis device 1 for analyzing urine may be Classify the red blood cells, white blood cells, epithelial cells, squamous epithelial cells, casts, and bacteria contained in urine, The number of such items may be counted.

[0143] The embodiment described above irradiates a first measurement sample and a second measurement sample with light, and generates an optical signal For example, the first measurement sample and the second measurement sample may be The electrical signal generated when the applied pore is added is acquired, and the acquired electrical signal is used to detect the cells. The present invention may be applied to a cell analysis device that classifies cells. The "first optical signal" is referred to as the "first signal," the "second optical signal" is referred to as the "second signal," and the "second The "third optical signal" may also be referred to as the "third signal."

[0144] The above-described embodiment is intended to facilitate understanding of the present invention and does not limit the present invention. The flowcharts, sequences, and implementations described in the embodiments are not intended to be interpreted as being related to the present invention. The elements of the embodiment, as well as their arrangement, materials, conditions, shapes, sizes, etc. are merely examples. The present invention is not limited to the above and may be modified as appropriate. The components may be partially substituted or combined. [Explanation of symbols]

[0145] 1...analysis device, 2...measurement unit, 3...transport unit, 4...information processing unit, 5... test computer, 21...hand part, 22...sample container setting part, 23...barcode unit 24... sample suction unit, 24a... piercer, 25... sample preparation unit, 26... detection unit, 40... main body , 41...display unit, 42...input unit, 401...CPU, 404...hard disk, 404a... Program, 405...reading device, 405a...recording medium, 406...image output interface 407: input / output interface, 408: communication interface, 500: control unit 501: measurement control section; 502: analysis processing section; 503: display control section; 504: input processing section , 505… memory unit

Claims

1. A cell sorting method for sorting cells contained in a sample, the method being performed by an analysis device, comprising: preparing a first measurement sample by treating the specimen under first preparation conditions; Obtaining a first signal from the prepared first measurement sample; classifying a predetermined type of cell contained in the first measurement sample using the first signal; preparing a second measurement sample by treating the specimen under second preparation conditions different from the first preparation conditions; Obtaining a second signal from the prepared second measurement sample; classifying the predetermined type of cells contained in the second measurement sample using the second signal; comparing a result of classifying the cells using the first signal with a result of classifying the cells using the second signal, and outputting an analysis result including a cell count based on the comparison result; Including, the first and second preparation conditions are different from each other in at least one of a condition regarding a length of time for reacting the specimen with a reagent, a condition regarding a temperature when reacting the specimen with a reagent, and a condition regarding a mixing ratio of the specimen and the reagent; The second preparation conditions are conditions in which the same reagent as that in the first preparation conditions is used. Cell classification method.

2. Outputting the analysis result includes: outputting a cell count based on the first signal when the comparison result is within a predetermined range; and if the comparison result exceeds a predetermined range, outputting a cell count based on the first signal and information indicating that the reliability of the cell count is low. The method of claim 1 .

3. Outputting the analysis result includes: outputting a cell count based on the first signal when the comparison result is within a predetermined range; and outputting a cell count based on the second signal when the comparison result exceeds a predetermined range. The method of claim 1 .

4. The method further includes receiving a measurement instruction for a sample; When the measurement instruction is received, The method includes preparing the first measurement sample, acquiring the first signal, classifying the predetermined type of cells using the first signal, preparing the second measurement sample, acquiring the second signal, classifying the predetermined type of cells using the second signal, and outputting the analysis result. The cell classification method according to any one of claims 1 to 3.

5. preparing a third measurement sample by treating the specimen under the first preparation conditions; Obtaining a third signal from the prepared third measurement sample; classifying the predetermined type of cells contained in the third measurement sample using the third signal; when it is determined that the cells have not been classified in the evaluation of the cell classification result using the third signal, the method executes the steps of preparing the first measurement specimen, acquiring the first signal, classifying the predetermined type of cells contained in the first measurement specimen, preparing the second measurement specimen, acquiring the second signal, classifying the predetermined type of cells contained in the second measurement specimen, and outputting the analysis result. The cell classification method according to any one of claims 1 to 4.

6. the first signal is a first optical signal; acquiring the first signal includes irradiating the first measurement sample with light to acquire the first optical signal; the second signal is a second optical signal; acquiring the second signal includes irradiating the second measurement sample with light to acquire the second optical signal; The cell classification method according to any one of claims 1 to 5.

7. the first optical signal includes at least two optical signals of the fluorescence emitted from the first measurement sample and two types of scattered light having different angles, the second optical signal includes at least two optical signals of the fluorescence emitted from the second measurement sample and two types of scattered light having different angles, a classification result of the cells using the first optical signal is obtained based on a first distribution map obtained by plotting the at least two optical signals included in the first optical signal on different axes; A result of classifying cells using the second optical signal is obtained based on a second distribution map obtained by plotting the at least two optical signals included in the second optical signal on different axes. The cell classification method according to claim 6.

8. A result of classifying the cells using the first optical signal is The number of cells belonging to any one of a plurality of clusters included in the first distribution map; The number of clusters included in the first distribution map; the distance between two clusters included in the first distribution map; A degree to which the boundaries of two clusters included in the first distribution map are in contact with each other; and a width of a predetermined cluster among a plurality of clusters included in the first distribution map; At least one of A result of classifying the cells using the second optical signal is the number of cells belonging to any one of the plurality of clusters included in the second distribution map; The number of clusters included in the second distribution map; the distance between two clusters included in the second distribution map; A degree to which the boundaries of two clusters included in the second distribution map are in contact with each other; and a width of a predetermined cluster among a plurality of clusters included in the second distribution map; At least one of The comparison result is: a comparison result between the number of cells belonging to any one of a plurality of clusters included in the first distribution map and the number of cells belonging to any one of a plurality of clusters included in the second distribution map; a comparison result between the number of clusters included in the first distribution map and the number of clusters included in the second distribution map; a comparison result between the distance between two clusters included in the first distribution map and the distance between two clusters included in the second distribution map; a comparison result between a degree of contact between the boundaries of two clusters included in the first distribution map and a degree of contact between the boundaries of two clusters included in the second distribution map; and a comparison result between a width of a predetermined cluster among a plurality of clusters included in the first distribution map and a width of a predetermined cluster among a plurality of clusters included in the second distribution map; At least one of The cell classification method according to claim 7.

9. the sample is blood; The cells to be classified include at least lymphocytes, monocytes, neutrophils and eosinophils; The classification method according to any one of claims 1 to 8.

10. Preparing the first measurement sample includes mixing the specimen with a predetermined reagent; Preparing the second measurement sample includes mixing the specimen with the predetermined reagent. The classification method according to any one of claims 1 to 9.

11. A cell sorting method for sorting cells contained in a sample, the method being performed by an analysis device, comprising: preparing a first measurement sample by treating the specimen under first preparation conditions; Obtaining a first signal from the prepared first measurement sample; classifying a predetermined type of cell contained in the first measurement sample using the first signal; preparing a second measurement sample by treating the specimen under second preparation conditions different from the first preparation conditions; Obtaining a second signal from the prepared second measurement sample; classifying the predetermined type of cells contained in the second measurement sample using the second signal; Evaluating a result of classifying the cell using the first signal; and outputting an analysis result including the number of cells based on the first signal or the number of cells based on the second signal depending on whether or not it is determined that the cells have been classified in the evaluation of the classification result; Including, the first and second preparation conditions are different from each other in at least one of a condition regarding a length of time for reacting the specimen with a reagent, a condition regarding a temperature when reacting the specimen with a reagent, and a condition regarding a mixing ratio of the specimen and the reagent; The second preparation conditions are conditions in which the same reagent as that in the first preparation conditions is used. Cell classification method.

12. An analyzer for classifying cells contained in a specimen, comprising: a sample preparation unit that prepares a specimen with a reagent to generate a measurement sample; A detection unit for acquiring a signal from a measurement sample; A control unit, The control unit is causing the sample preparation unit to prepare a first measurement sample by treating a specimen under first preparation conditions, and to prepare a second measurement sample by treating the specimen under second preparation conditions different from the first preparation conditions; causing the detection unit to acquire a first signal from the prepared first measurement sample and acquire a second signal from the prepared second measurement sample; classifying a predetermined type of cell contained in the specimen using the first signal; classifying the predetermined type of cells contained in the specimen using the second signal; comparing a classification result of the cell using the first signal with a classification result of the cell using the second signal, and outputting an analysis result based on the comparison result; the first and second preparation conditions are different from each other in at least one of a condition regarding a length of time for reacting the specimen with a reagent, a condition regarding a temperature when reacting the specimen with a reagent, and a condition regarding a mixing ratio of the specimen and the reagent; The second preparation conditions are conditions in which the same reagent as that in the first preparation conditions is used. Analyzer.

13. An analyzer for classifying cells contained in a specimen, comprising: a sample preparation unit that prepares a specimen with a reagent to generate a measurement sample; A detection unit for acquiring a signal from a measurement sample; A control unit, The control unit is causing the sample preparation unit to prepare a first measurement sample by treating a specimen under first preparation conditions, and to prepare a second measurement sample by treating the specimen under second preparation conditions different from the first preparation conditions; causing the detection unit to acquire a first signal from the prepared first measurement sample and acquire a second signal from the prepared second measurement sample; classifying a predetermined type of cell contained in the specimen using the first signal; classifying the predetermined type of cells contained in the specimen using the second signal; Evaluating a result of classifying the cell using the first signal; and outputting an analysis result including the number of cells based on the first signal or the number of cells based on the second signal depending on whether or not it is determined that the cells have been classified in the evaluation of the classification result; the first and second preparation conditions are different from each other in at least one of a condition regarding a length of time for reacting the specimen with a reagent, a condition regarding a temperature when reacting the specimen with a reagent, and a condition regarding a mixing ratio of the specimen and the reagent; The second preparation conditions are conditions in which the same reagent as that in the first preparation conditions is used. Analyzer.

14. On the computer, causing a sample preparation unit, which prepares a sample with a reagent to generate a measurement sample, to execute the following: treating the sample under first preparation conditions to prepare a first measurement sample; and treating the sample under second preparation conditions different from the first preparation conditions to prepare a second measurement sample; causing a detection unit that acquires a signal from a measurement sample to acquire a first signal from the prepared first measurement sample and acquire a second signal from the prepared second measurement sample; classifying a predetermined type of cell contained in the specimen using the first signal; classifying the predetermined type of cells contained in the specimen using the second signal; comparing a result of classifying the cells using the first signal with a result of classifying the cells using the second signal, and outputting an analysis result based on the comparison result; Run the command, the first and second preparation conditions are different from each other in at least one of a condition regarding a length of time for reacting the specimen with a reagent, a condition regarding a temperature when reacting the specimen with a reagent, and a condition regarding a mixing ratio of the specimen and the reagent; The second preparation conditions are conditions in which the same reagent as that in the first preparation conditions is used. program.

15. On the computer, a sample preparation unit which prepares a sample with a reagent to generate a measurement sample executes the following steps: treating the sample under first preparation conditions to prepare a first measurement sample; and treating the sample under second preparation conditions which are different from the first preparation conditions to prepare a second measurement sample; causing a detection unit that acquires a signal from a measurement sample to acquire a first signal from the prepared first measurement sample and acquire a second signal from the prepared second measurement sample; classifying a predetermined type of cell contained in the specimen using the first signal; classifying the predetermined type of cells contained in the specimen using the second signal; Evaluating a result of classifying the cell using the first signal; and outputting an analysis result including the number of cells based on the first signal or the number of cells based on the second signal depending on whether or not it is determined that the cells have been classified in the evaluation of the classification result; Run the command, the first and second preparation conditions are different from each other in at least one of a condition regarding a length of time for reacting the specimen with a reagent, a condition regarding a temperature when reacting the specimen with a reagent, and a condition regarding a mixing ratio of the specimen and the reagent; The second preparation conditions are conditions in which the same reagent as that in the first preparation conditions is used. program.

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