JP5258350B2 - Sample analyzer and sample analysis method - Google Patents

Description

  The present invention relates to a sample analyzer and a sample analysis method for analyzing a sample such as blood and urine.

  Conventionally, a particle analyzer that classifies particles in a sample such as blood and urine into a plurality of types of particles is known (see, for example, Patent Documents 1 and 2).

  In Patent Document 1, by changing the detection sensitivity for detecting a predetermined component according to the animal species, if an erroneous analysis result occurs, the detection sensitivity is changed and the predetermined component is again applied to the same sample. A blood analysis device for detecting the above is disclosed.

In Patent Document 2, the first threshold value for distinguishing white blood cells and bacteria in a sample from other particles is used to distinguish bacteria and white blood cells in the sample from other particles. If it is determined that the concentration of bacteria in the sample is high, a second threshold value greater than the first threshold value is used to differentiate only white blood cells in the sample from other particles containing bacteria. Disclosed is a particle analyzer that controls while a measurement sample forms a sample stream. This makes it possible to accurately measure a sample containing a large amount of bacteria.
JP 2000-310642 A Japanese Patent Laid-Open No. 2002-277381

  In Patent Document 1, when the reliability of the analysis result based on the measurement data is low at the set detection sensitivity, it is necessary to suck the sample again and perform measurement again. Therefore, the user has a problem that the operation becomes complicated, such as taking out a sample that needs to be measured again and measuring it. Patent Document 2 describes a technique for accurately measuring a sample containing a large amount of bacteria, but does not disclose or suggest a technique for changing detection conditions.

  The present invention has been made in view of such circumstances, and at the time of measurement on one measurement sample, by detecting a predetermined component based on a plurality of detection conditions, an appropriate detection condition is selected and analyzed with high accuracy. It is an object of the present invention to provide a sample analysis apparatus and a sample analysis method capable of performing the above.

In order to achieve the above object, a sample analyzer according to the first invention comprises a sample preparation unit for preparing a measurement sample including a sample and a reagent, and predetermined components included in the measurement sample prepared by the sample preparation unit. A detection unit for detecting, a detection condition setting unit for setting a plurality of detection conditions when a predetermined component is detected by the detection unit, and a plurality of detection conditions set by the detection condition setting unit , A detection unit control unit that controls the detection unit to detect a predetermined component contained in a measurement sample ; a selection unit that automatically selects one detection result from detection results for each of the plurality of detection conditions; and the selection Analyzing means for analyzing the predetermined component based on one detection result selected by the means .

The sample analyzer according to the second aspect, in the first shot bright, the detection unit includes an amplifier for amplifying a detection signal of said predetermined component, said plurality of detection conditions, the detection signal by the amplifier The condition is related to the amplification factor.

The sample analyzer according to a third aspect of the present invention is the sample analysis apparatus according to the first or second aspect , wherein the detection unit includes a flow cell through which the measurement sample passes, and a light emitting unit that irradiates the measurement sample through the flow cell with light. And a light receiving unit that receives light from the measurement sample irradiated with light from the light emitting unit.

The sample analyzer according to a fourth invention is characterized in that, in the third invention, the plurality of detection conditions are conditions relating to light detection sensitivity by the light receiving section.

The sample analyzer according to a fifth aspect of the present invention is the sample analysis apparatus according to the third or fourth aspect , wherein the plurality of detection conditions are conditions related to light irradiation intensity by the light emitting unit.

The sample analyzer according to a sixth aspect of the present invention is the sample analysis apparatus according to any one of the third to fifth aspects, wherein the detection unit control means sets one detection condition while the measurement sample passes through the flow cell. It is characterized by changing to other detection conditions.

Next, in order to achieve the above object, a sample analysis method according to a seventh aspect of the present invention includes a detection unit that detects a predetermined component contained in the sample, and the sample is based on the predetermined component detected by the detection unit. In a sample analysis method that can be executed by a sample analyzer that analyzes a sample, a measurement sample including a sample and a reagent is prepared, a plurality of detection conditions are set, and a predetermined measurement included in the prepared single measurement sample is prepared. the components were detected for each set of the plurality of detection conditions, the plurality of each detected condition detection result from one detection result automatically selected, predetermined in accordance with one of the detection result of the selected It is characterized by analyzing components.

In the first invention and the seventh invention, a measurement sample including a sample and a reagent is prepared, a plurality of detection conditions are set, and a predetermined component included in the prepared one measurement sample is set to a plurality of set detections. Detect for each condition . One detection result is automatically selected from detection results for each of a plurality of detection conditions, and a predetermined component is analyzed based on the selected one detection result . Thereby, the detection result with respect to several detection conditions can be obtained in one measurement process with respect to one measurement sample. Therefore, even when re-analysis with a changed detection condition is required, it is not necessary to perform measurement on the same sample again, and the optimal detection condition is not required by the user to perform complicated operations. Therefore, the analysis accuracy can be improved. In addition, by acquiring detection results for a plurality of detection conditions, there is no need to perform measurement on the same sample again, even when re-analysis with changed detection conditions is required. Since it is not necessary to supply the measurement sample to the detection unit a plurality of times, the measurement can be completed in a short time. Further, by supplying one measurement sample to the detection unit a plurality of times, it is possible to prevent the measurement sample from being deteriorated and the analysis accuracy from being lowered. Furthermore, one detection result is automatically selected from the detection results for each of a plurality of detection conditions, and a predetermined component is analyzed based on the selected one detection result, so that the user of the apparatus can detect a plurality of detection results. It is not necessary to select an optimal detection result from the detection results for each condition, and the operation burden on the user can be further reduced.

In the second invention, it is possible to use an amplification factor larger than usual under one detection condition by using, as a plurality of detection conditions, a condition relating to the amplification factor of the detection signal by an amplifier that amplifies the detection signal of a predetermined component. Even a component with a small detection signal that cannot be detected with a normal amplification factor can be detected.

In the third invention, the detection unit receives light from the flow cell through which the measurement sample passes, the light emitting unit that irradiates light to the measurement sample that passes through the flow cell, and the measurement sample irradiated with light from the light emitting unit. By including the light receiving unit, it is possible to detect optical characteristic information of a predetermined component included in the sample.

In the fourth aspect of the invention, by using the conditions relating to the light detection sensitivity by the light receiving unit as a plurality of detection conditions, it becomes possible to improve the detection sensitivity more than usual under one detection condition, the emitted signal is small, Even components that cannot be detected with detection sensitivity can be detected.

In the fifth invention, by using the conditions regarding the light irradiation intensity by the light emitting part as a plurality of detection conditions, it becomes possible to increase the irradiation intensity than usual under one detection condition, and the emitted signal is small, Even components that cannot be detected by the irradiation intensity can be detected.

In the sixth invention, by changing one detection condition to another detection condition while the measurement sample passes through the flow cell, detection results under various detection conditions can be obtained even in a short time measurement. Can do. Therefore, even when re-analysis is necessary, it is not necessary to perform measurement on the same sample again, and analysis can be performed based on the detection result under the optimal detection conditions. It becomes possible to improve and speed up the measurement.

According to the above configuration, it is possible to detect a predetermined component included in one measurement sample for each of a plurality of detection conditions. Therefore, even when re-analysis with a changed detection condition is required, it is not necessary to perform measurement on the same sample again, and the optimal detection condition is not required by the user to perform complicated operations. Therefore, the analysis accuracy can be improved. In addition, by acquiring detection results for a plurality of detection conditions, there is no need to perform measurement on the same sample again, even when re-analysis with changed detection conditions is required. Since it is not necessary to supply the measurement sample to the detection unit a plurality of times, the measurement can be completed in a short time. Further, by supplying one measurement sample to the detection unit a plurality of times, it is possible to prevent the measurement sample from being deteriorated and the analysis accuracy from being lowered. Furthermore, by automatically selecting one detection result from the detection results for each of a plurality of detection conditions and analyzing a predetermined component based on the selected one detection result, the user of the apparatus himself can detect a plurality of detection results. It is not necessary to select an optimal detection result from the detection results for each condition, and the operation burden on the user can be further reduced.

  Hereinafter, in the present embodiment, a blood analyzer that analyzes blood as an example of a sample analyzer will be described as an example, and will be specifically described based on the drawings. Therefore, the analysis process is a blood cell classification process, and the analysis data is generated as classification data.

  FIG. 1 is a perspective view schematically showing a configuration of a sample analyzer according to an embodiment of the present invention. As shown in FIG. 1, the sample analyzer according to the present embodiment includes a measurement device 1 and a calculation display device 2 connected so as to be able to perform data communication with the measurement device 1.

  The measuring device 1 and the calculation display device 2 are connected via a communication line (not shown), and control the operation of the measuring device 1 by data communication with each other, and the measurement data output from the measuring device 1 is transmitted. Process to get analysis results. The measuring device 1 and the calculation display device 2 may be connected via a network, or may be integrated as one device to exchange data by interprocess communication or the like.

  The measuring device 1 detects characteristic information such as white blood cells, reticulocytes, and platelets in the blood using a flow cytometry method, and transmits the detection result to the calculation display device 2 as measurement data. Here, the flow cytometry method is a method of forming a sample flow including a measurement sample and irradiating the sample flow with a laser beam to forward scattered light and side scattered light emitted from particles (blood cells) in the measurement sample. This is a particle (blood cell) measurement method for detecting light such as side fluorescence and thereby detecting particles (blood cells) in a sample.

  FIG. 2 is a block diagram showing the configuration of the measurement apparatus 1 of the sample analyzer according to the embodiment of the present invention. The measuring apparatus 1 includes an apparatus mechanism unit 4, a detection unit 5 that performs measurement of a measurement sample, an analog processing unit 6 for the output of the detection unit 5, a display / operation unit 7, and the operations of the above-described hardware units. And a control board unit 9 to be controlled.

  The control board unit 9 includes a control unit 91 having a control processor and a memory for operating the control processor, and a 12-bit A / D conversion unit 92 that converts a signal output from the analog processing unit 6 into a digital signal. And an arithmetic unit 93 that stores the digital signal output from the A / D conversion unit 92 and executes a process of selecting data to be output to the control unit 91. The control unit 91 is connected to the display / operation unit 7 via the bus 94a and the interface 95b, and is connected to the arithmetic display device 2 via the bus 94b and the interface 95c. The calculation unit 93 outputs the calculation result to the control unit 91 via the interface 95d and the bus 94a. Further, the control unit 91 transmits the calculation result (measurement data) to the calculation display device 2.

  The device mechanism unit 4 is provided with a sample preparation unit 41 for preparing a measurement sample from the reagent and blood. The sample preparation unit 41 prepares a white blood cell measurement sample, a reticulocyte measurement sample, and a platelet measurement sample.

  FIG. 3 is a block diagram schematically illustrating the configuration of the sample preparation unit 41 according to the embodiment of the present invention. The sample preparation unit 41 includes a blood collection tube 41a filled with a predetermined amount of blood, a sampling valve 41b for sucking blood, and a reaction chamber 41c.

  The sampling valve 41b is configured to be able to quantify blood in the blood collection tube 41a sucked by a suction pipette (not shown). The reaction chamber 41c is connected to the sampling valve 41b, and is configured so that a predetermined reagent and a staining solution can be further mixed with blood quantified by the sampling valve 41b. The reaction chamber 41c is connected to the detection unit 5, and is configured to flow into the detection unit 5 a measurement sample in which a predetermined reagent and a staining solution are mixed in the reaction chamber 41c.

  Thereby, the sample preparation unit 41 can prepare a measurement sample in which white blood cells are stained and red blood cells are hemolyzed as a white blood cell measurement sample. In addition, a measurement sample in which reticulocytes are stained can be prepared as a sample for reticulocyte measurement, and a measurement sample in which platelets are stained can be prepared as a sample for platelet measurement. The prepared measurement sample is supplied to a sheath flow cell of the detection unit 5 described later together with the sheath liquid.

  FIG. 4 is a block diagram schematically illustrating the configuration of the detection unit 5 and the analog processing unit 6 according to the embodiment of the present invention. As shown in FIG. 4, the detection unit 5 includes a light emitting unit 501 that emits laser light, an irradiation lens unit 502, a sheath flow cell 503 that is irradiated with laser light, and a laser beam that is emitted from the light emitting unit 501. A condensing lens 504, a pinhole 505, and a PD (photodiode) 506 disposed on an extension line in the direction (a beam stopper (not shown) is disposed between the sheath flow cell 503 and the condensing lens 504). , A condensing lens 507, a dichroic mirror 508, an optical filter 509, a pin hole 510, an APD (avalanche photodiode) 511, and a dichroic mirror, which are arranged in a direction crossing the direction in which the laser light emitted from the light emitting unit 501 travels. PD (photodiode) 512 arranged on the side of 508 Eteiru.

  The light emitting unit 501 is provided to emit light to a sample flow including a measurement sample that passes through the inside of the sheath flow cell 503. The irradiation lens unit 502 is provided to make light emitted from the light emitting unit 501 into parallel light. The PD 506 is provided to receive forward scattered light emitted from the sheath flow cell 503. Information regarding the size of particles (blood cells) in the measurement sample can be obtained from the forward scattered light emitted from the sheath flow cell 503.

  The dichroic mirror 508 is provided to separate the side scattered light and the side fluorescence emitted from the sheath flow cell 503. Specifically, the dichroic mirror 508 is provided to cause the side scattered light emitted from the sheath flow cell 503 to enter the PD 512 and to cause the side fluorescence emitted from the sheath flow cell 503 to enter the APD 511. The PD 512 is provided to receive side scattered light. With the side scattered light emitted from the sheath flow cell 503, it is possible to obtain internal information such as the size of the nuclei of particles (blood cells) in the measurement sample.

  The APD 511 is provided for receiving side fluorescence. When a fluorescent material such as a stained blood cell is irradiated with light, light having a wavelength longer than the wavelength of the irradiated light is emitted. The fluorescence intensity increases as the degree of staining increases. Therefore, characteristic information regarding the degree of staining of blood cells can be obtained by measuring the side fluorescence intensity emitted from the sheath flow cell 503. Therefore, the classification of white blood cells and other measurements can be performed based on the difference in lateral fluorescence intensity. The PDs 506 and 512 and the APD 511 convert the received optical signals into electric signals, amplify them by the amplifiers 61, 62 and 63, and transmit them to the control board unit 9.

  In the present embodiment, the light emitting unit 501 emits light with an output of 3.4 mW during white blood cell classification measurement (hereinafter referred to as DIFF measurement). Further, at the time of reticulocyte measurement (hereinafter referred to as RET measurement), light is emitted with an output of 6 mW. Furthermore, at the time of platelet measurement (PLT measurement), light is emitted with an output of 10 mW.

  FIG. 5 is a block diagram showing a configuration of the calculation display device 2 of the sample analyzer according to the embodiment of the present invention. As shown in FIG. 5, the arithmetic display device 2 connects a CPU (central processing unit) 21, a RAM 22, a storage device 23, an input device 24, a display device 25, an output device 26, a communication interface 27, and the hardware described above. An internal bus 28 is used. The CPU 21 is connected to each hardware unit as described above of the arithmetic display device 2 via the internal bus 28, controls the operation of each hardware unit described above, and stores the computer program 231 stored in the storage device 23. Various software functions are executed according to the above. The RAM 22 is composed of a volatile memory such as SRAM or SDRAM, and a load module is expanded when the computer program 231 is executed, and stores temporary data generated when the computer program 231 is executed.

  The storage device 23 is configured by a built-in fixed storage device (hard disk) or the like. The storage device 23 also includes a patient information storage unit 232 in which information about a patient including age information of a patient (subject) associated with identification information that can be acquired by reading a barcode label is stored. Yes. FIG. 6 is an exemplary diagram of a data configuration of the patient information storage unit 232. As shown in FIG. 6, in association with a sample ID that is identification information acquired by reading a barcode label, a subject ID that is identification information for identifying the subject, gender information of the subject, The age information of the examiner, the disease information regarding the contents of the disease, and the clinical department information for identifying the clinical department are stored. The patient information storage unit 232 is not limited to being provided in the storage device 23, but may be configured to store the information in an external computer and make an inquiry via the communication interface 27.

  The communication interface 27 is connected to the internal bus 28, and can transmit and receive data by being connected to the measuring apparatus 1 via a communication line. That is, instruction information indicating the start of measurement is transmitted to the measurement apparatus 1 and measurement data is received.

  The input device 24 is a data input medium such as a keyboard and a mouse. The display device 25 is a display device such as a CRT monitor or LCD, and displays the analysis result graphically. The output device 26 is a printing device such as a laser printer or an inkjet printer.

  In the measurement apparatus 1 and the calculation display apparatus 2 of the sample analyzer having the above-described configuration, blood of an adult is measured, and leukocytes contained in the blood are converted into lymphocytes, monocytes, neutrophils, basophils, and When classified into eosinophils, a scattergram as shown in FIG. 7 is created and displayed on the display device 25. FIG. 7 is an exemplary diagram of a scattergram at the time of white blood cell classification measurement (DIFF measurement). In FIG. 7, the vertical axis represents the side fluorescence intensity, and the horizontal axis represents the side scattered light intensity. The white blood cell classification method used in the sample analyzer according to the present embodiment will be described below.

  In the sample analyzer according to the embodiment, as shown in FIG. 7, it is assumed that the lymphocyte distribution region 101 and monocytes are distributed based on the past statistical values of adult blood. Monocyte distribution region 102, eosinophil distribution region 103 in which eosinophils are assumed to be distributed, neutrophil distribution region 104 in which neutrophils are assumed to be distributed, basophils in which basophils are assumed to be distributed The distribution area 105 is predetermined. Then, after sampling integer string information based on the measurement data on the same coordinate axis, the lymphocyte distribution region 101, the monocyte distribution region 102, the eosinophil distribution region 103, the neutrophil distribution region 104, the basophil distribution region The blood cell belonging degree to each of the distribution areas 105 is calculated, and each blood cell is classified into a specific type of blood cell according to the calculated belonging degree. Then, by counting the classified blood cells, the number of lymphocytes, monocytes and the like can be obtained. The above-described white blood cell classification method is described in detail in US Pat. No. 5,555,196. Note that a computer program for executing the above-described white blood cell classification method and data used for the execution of the computer program are stored in the storage device 23 in advance.

  It has been recognized by the present inventors that blood cells contained in pediatric blood are less stained with a staining solution than blood cells contained in adult blood. For this reason, in the measurement data obtained by measuring pediatric blood, it has been found that the sampling values are distributed slightly below each region to be originally distributed as shown in FIG. FIG. 8 is an exemplary diagram showing the relationship between the lymphocyte distribution region 101 of the scattergram created during the DIFF measurement and the sampling value.

  As shown in FIG. 8, when the measurement data is adult blood, sampling values should be collected around the lymphocyte distribution region 101. However, when the measurement data is not pediatric blood but pediatric blood, since the degree of staining with dye is lower in pediatric blood than in the case of adult blood, both fluorescence intensity and scattered light intensity are measured lower. Therefore, the sampling values are collected in the vicinity of the region 111 that is below the lymphocyte distribution region 101.

  Thus, when the distribution trend is shifted downward from the region assumed as a whole from the scattergram, it can be determined that the measurement data is data for pediatric blood, and the accuracy of the classification process It can be seen that the area 111 where sampling values are aggregated needs to be shifted in the direction of the arrow 112 in order to improve.

  FIG. 9 is a flowchart showing a processing procedure of the control unit 91 of the control board unit 9 and the CPU 21 of the calculation display device 2 of the measurement apparatus 1 according to the embodiment of the present invention. When the control unit 91 of the control board unit 9 of the measuring apparatus 1 detects that the measuring apparatus 1 has been activated, the control unit 91 performs initialization (step S915) and checks the operation of each part of the measuring apparatus 1. In addition, when the CPU 21 of the calculation display device 2 detects that the calculation display device 2 is activated, the CPU 21 executes initialization (initialization of the program) (step S901) and displays a menu screen on the display device 25 (step S901). Step S902). On the menu screen, it is possible to accept selection of DIFF measurement, RET measurement, and CBC measurement, accept a measurement start instruction, and a shutdown instruction. In the present embodiment, the case where DIFF measurement is selected on the menu screen will be described below.

  The CPU 21 of the calculation display device 2 determines whether or not a measurement start instruction has been received (step S903). If the CPU 21 determines that a measurement start instruction has not been received (step S903: NO), the CPU 21 performs step S904. Thru | or step S912 is skipped. When the CPU 21 determines that the measurement start instruction has been received (step S903: YES), the CPU 21 transmits instruction information indicating the measurement start to the measurement apparatus 1 (step S904). The control unit 91 of the control board unit 9 of the measuring apparatus 1 determines whether or not the instruction information indicating the measurement start is received (step S916), and determines that the control unit 91 has received the instruction information indicating the measurement start. If it has been performed (step S916: YES), the controller 91 causes a barcode reader (not shown) to read a barcode label (not shown) affixed to the container containing the blood to identify the blood. Information (sample ID) is acquired (step S917). When the control unit 91 determines that the instruction information indicating the start of measurement has not been received (step S916: NO), the control unit 91 skips steps S917 to S921.

  The control unit 91 transmits the acquired identification information (sample ID) to the calculation display device 2 (step S918), and the CPU 21 of the calculation display device 2 determines whether the identification information (sample ID) has been received (step S918). Step S905). When the CPU 21 has not received the identification information (sample ID) (step S905: NO), the CPU 21 enters a reception waiting state. When the CPU 21 receives the identification information (sample ID) (step S905: YES), the CPU 21 refers to the patient information storage unit 232 of the storage device 23 to acquire patient information (step S906), and measures the patient information. It transmits to the apparatus 1 (step S907).

  Next, the control unit 91 of the control board unit 9 of the measuring apparatus 1 determines whether or not patient information has been received (step S919), and when the control unit 91 determines that it has not been received (step S919: NO), the control unit 91 enters a reception waiting state. When the control unit 91 determines that it has been received (step S919: YES), the control unit 91 controls the sample preparation unit 41 to prepare the measurement sample, and then starts the measurement sample measurement process (step S920). . Specifically, DIFF measurement is performed, and electrical signals corresponding to the received light intensity of side scattered light and side fluorescence are output to the control board unit 9 via the detection unit 5 and the analog processing unit 6. The A / D conversion unit 92 of the control board unit 9 converts the acquired analog signal into a 12-bit digital signal, and the calculation unit 93 performs predetermined processing on the digital signal output from the A / D conversion unit 92. To the control unit 91. The control unit 91 transmits the received 12-bit integer string information as measurement data to the calculation display device 2 (step S921).

  FIG. 10 is a flowchart showing a measurement processing procedure executed in step S920 of FIG. 9 by the control unit 91 of the control board unit 9 of the measurement apparatus 1 according to the embodiment of the present invention. In FIG. 10, the control unit 91 of the control board unit 9 of the measuring apparatus 1 prepares a measurement sample (step S1001), sets the counter n to an initial value 1 (step S1002), and detects the detection unit 5 of the measuring apparatus 1. As the detection condition, the detection sensitivity is set to the nth sensitivity (step S1003). As the detection sensitivity, first to nth detection sensitivities are set in advance. The set detection sensitivity means the detection sensitivity of the PDs 506 and 512 and the APD 511 which are light receiving units that receive light emitted from the light emitting unit 501 shown in FIG.

  The controller 91 starts supplying the measurement sample to be measured to the sheath flow cell 503 (step S1004), and starts storing feature information detected at the nth detection sensitivity in the built-in memory (step S1005). ). The control unit 91 determines whether or not 10 seconds have elapsed since the start of storing feature information at the nth detection sensitivity (step S1006), and the control unit 91 determines that 10 seconds have not elapsed. When it does (step S1006: NO), the control part 91 will be in a progress waiting state.

  When the control unit 91 determines that 10 seconds have elapsed (step S1006: YES), the control unit 91 stops storing the feature information detected with the nth detection sensitivity in the built-in memory (step S1007). Then, it is determined whether or not the counter n has exceeded a predetermined number (step S1008). When the control unit 91 determines that n does not exceed the predetermined number (step S1008: NO), the control unit 91 increments the counter n by 1 (step S1009), returns the processing to step S1003, and performs the processing described above. repeat. When the control unit 91 determines that n exceeds the predetermined number (step S1008: YES), the control unit 91 returns the process to step S921 in FIG. A plurality of feature information stored in the built-in memory of the control unit 91 is measurement data. The supply time of the measurement sample to the sheath flow cell 503 is set in advance so that the supply is stopped after the control unit 91 determines that n exceeds a predetermined number. Thereby, the detection sensitivity is continuously changed while one measurement sample is supplied to the sheath flow cell.

  Returning to FIG. 9, the CPU 21 of the calculation display device 2 determines whether or not measurement data has been received (step S908), and if the CPU 21 determines that the measurement data has been received (step S908: YES), the CPU 21 Performs analysis processing based on the received measurement data (step S909). When the CPU 21 determines that the measurement data has not been received (step S908: NO), the CPU 21 enters a reception waiting state.

  FIG. 11 is a flowchart showing the analysis processing procedure executed in step S909 of FIG. 9 by the CPU 21 of the calculation display device 2 according to the embodiment of the present invention. In FIG. 11, the CPU 21 of the calculation display device 2 sets the counter n to an initial value 1 (step S1101), and the measurement data (12-bit integer string information) acquired from the measurement apparatus 1 is converted to 8-bit integer string information. The nth classification data based on the feature information detected with the nth detection sensitivity is generated and stored by reduction (step S1102).

  The CPU 21 determines whether n is larger than a predetermined number (step S1103), and when the CPU 21 determines that n is equal to or smaller than the predetermined number (step S1103: NO), the CPU 21 increments n by 1 ( In step S1104), the processing is returned to step S1002 with the same reduction ratio, and the above-described processing is repeated. When the CPU 21 determines that n is larger than the predetermined number (step S1103: YES), the CPU 21 executes the classification process using the first to nth classification data (step S1105), and the classification results are respectively obtained. It memorize | stores in the memory | storage device 23 (step S1106).

  Specifically, when the CPU 21 generates the classification data, the 12-bit integer string information acquired from the measurement apparatus 1 is reduced at a predetermined reduction rate. For example, the information may be reduced to 8-bit integer string information, may be reduced to 10-bit integer string information, or an arbitrary reduction ratio may be selected.

  The CPU 21 selects one classification data from the plurality of classification data stored in the storage device 23 (step S1107), reads the selected classification data from the storage device 23, and obtains lymphocytes and monocytes. The number of blood cells such as eosinophils, neutrophils, and basophils is counted (step S1108), and the count result is stored in the storage device 23 (step S1109). The CPU 21 also creates a scattergram as shown in FIG. 7, displays the counting result and the scattergram as shown in FIG. 13 described later on the display device 25 as the white blood cell classification result (step S1110), and performs processing. Returning to step S910 of FIG. The user can visually confirm the scattergram displayed on the display device 25. Then, the user can input an execution instruction for executing the reclassification process according to the distribution state of the sampling values in the scattergram.

  Next, a processing procedure for the classification data selection processing shown in step S1107 of FIG. 11 will be described. FIG. 12 is a flowchart illustrating the classification data selection processing procedure of the CPU 21 of the calculation display device 2 according to the embodiment of the present invention. In the sample analyzer according to the present embodiment, it is assumed that the predetermined number shown in FIGS. 10 and 11 is set to 3.

  The CPU 21 of the arithmetic processing device 2 determines whether or not the subject is a child based on the age information included in the patient information received from the measuring device 1 (step S1201). Here, “child” may mean a newborn, an infant, or an infant. Whether or not the patient is a “child” can be arbitrarily set by the user of the sample analyzer according to the second embodiment, and is not only a subject under a predetermined age but also, for example, going to pediatrics and gynecology. The subject who is doing this may be “children”, and the child before entering elementary school may be “children”. In addition, the manufacturer who manufactures the sample analyzer may set the range of “children”. When the CPU 21 determines that the subject is a child (step S1201: YES), the CPU 21 selects the second classification data based on the feature information obtained with the second detection sensitivity (step S1202). The process returns to step S1108.

  When the CPU 21 determines that the subject is not a child (step S1201: NO), the CPU 21 determines lymphocytes, monocytes, eosinophils, neutrophils, neutrophils, and the like for each of the first to third classification data. Particles included in a region where sampling region collection regions such as base spheres overlap, for example, region L in FIG. 7 (hereinafter, abbreviated as “overlapping region”) are counted and stored in RAM 22 (step S1203). When the number of particles in the overlapping region is small, it is considered that the blood cell classification process is being performed well. Therefore, the CPU 21 selects the classification data having the smallest number of particles in the overlapping region. That is, the CPU 21 first determines whether or not the number of particles (N1) in the overlapping region in the first classification data is equal to or less than the number of particles (N2) in the overlapping region in the second classification data (step S1204). ).

  When the CPU 21 determines that the number of particles in the overlapping region (N1) in the first classification data is equal to or less than the number of particles (N2) in the overlapping region in the second classification data (step S1204: YES), the CPU 21 Determines whether or not the number of particles (N1) in the overlapping region in the first classification data is equal to or less than the number of particles (N3) in the overlapping region in the third classification data (step S1205).

  When the CPU 21 determines that the number of particles in the overlapping region (N1) in the first classification data is equal to or less than the number of particles (N3) in the overlapping region in the third classification data (step S1205: YES), the CPU 21 Selects the first classification data (step S1206), and returns the process to step S1108.

  When the CPU 21 determines that the number of particles (N1) in the overlapping region in the first classification data is larger than the number of particles (N2) in the overlapping region in the second classification data (step S1204: NO), or When it is determined that the number of particles (N1) in the overlapping region in the classification data of 1 is larger than the number of particles (N3) in the overlapping region in the third classification data (step S1205: NO), the CPU 21 It is determined whether or not the number of particles in the overlapping region (N2) in the classification data is equal to or less than the number of particles in the overlapping region (N3) in the third classification data (step S1207).

  When the CPU 21 determines that the number of particles in the overlapping area (N2) in the second classification data is equal to or less than the number of particles (N3) in the overlapping area in the third classification data (step S1207: YES), the CPU 21 Selects the second classification data (step S1202), and returns the process to step S1108. When the CPU 21 determines that the number of particles in the overlapping region (N2) in the second classification data is larger than the number of particles (N3) in the overlapping region in the third classification data (step S1207: NO), the CPU 21 The third classification data is selected (step S1208), and the process returns to step S1108.

  Note that the method for selecting the classification data is not particularly limited, but for example, the overlapping state and appearance of sampling regions of lymphocytes, monocytes, eosinophils, neutrophils, basophils, etc. The CPU 21 selects based on the position and the like. Specifically, (1) the distance between the representative value of the collective region and the representative value of each region assumed in advance is selected based on the number of particles included in the region where the collective region overlaps (3) Select according to the relative position of the aggregate area and each area assumed in advance, (4) The area of the aggregate area and the area of each area assumed in advance Select by combining methods such as selecting by size.

  Returning to FIG. 9, the CPU 21 of the calculation display device 2 determines whether or not a reclassification instruction that is an instruction to execute the reclassification process is received from the user (step S <b> 910), and the CPU 21 accepts the reclassification instruction. If it is determined that it is not present (step S910: NO), the CPU 21 skips steps S911 and S912. If the CPU 21 determines that a reclassification instruction has been accepted (step S910: YES), the CPU 21 accepts selection of other classification data (step S911), and executes a counting process based on the classification data for which the selection has been accepted. (Step S912).

  FIG. 13 is a view showing an example of a screen for displaying the classification result of the display device 25 of the calculation display device 2 according to the embodiment of the present invention. In FIG. 13, when n in FIG. 10 and FIG. 11 is 3, that is, when three types of classification data are generated based on three types of measurement data having different detection sensitivities, Based on the classification result. The classification results when the classification data selected by the CPU 21 is used are displayed in the main result display area 211, and the classification results when other classification data are used are displayed in the sub result display areas 212 and 213.

  The reclassification instruction is performed by the user selecting one of the secondary result display areas 212 and 213 displaying the classification result based on the classification data desired to be reclassified by the user. For example, when the sub result display area 212 is selected, the display contents of the sub result display area 212 and the main result display area 211 are switched, and the counting process is executed.

  Returning to FIG. 9, the CPU 21 of the calculation display device 2 determines whether or not a shutdown instruction has been received (step S <b> 913), and when the CPU 21 determines that a shutdown instruction has not been received (step S <b> 913: NO), the CPU 21. Returns the processing to step S903 and repeats the above-described processing. When the CPU 21 determines that a shutdown instruction has been received (step S913: YES), the CPU 21 transmits shutdown instruction information to the measurement apparatus 1 (step S914).

  The control unit 91 of the control board unit 9 of the measuring apparatus 1 determines whether or not the shutdown instruction information has been received (step S922). If the control unit 91 has not received the shutdown instruction information (step S922). : NO), the control unit 91 returns the process to step S916 and repeats the above-described process. When the control unit 91 determines that the shutdown instruction information has been received (step S922: YES), the control unit 91 executes the shutdown (step S923) and ends the process.

  As described above, according to the present embodiment, a plurality of classification data having different detection conditions are generated in advance, and the optimal classification data is selected according to the sample, so that the animal species are different. Even when there are differences such as different ages and different genders, the counting process can be executed using the optimum classification data, and the sample analysis accuracy can be improved.

  In the above-described embodiment, a case has been described in which the detection sensitivity of the PDs 506 and 512 and the APD 511 that receive the light emitted from the light emitting unit 501 is adopted as the detection condition. It is not limited to detection sensitivity. For example, a plurality of amplification factors may be set in the amplifiers 61, 62, and 63 that amplify electric signals obtained by photoelectrically converting received light signals. Further, a plurality of light irradiation intensities at the light emitting unit 501 may be set.

  In the above-described embodiments, blood is used as a sample and a blood cell analyzer that analyzes blood cells contained in blood is described as an example. However, the present invention is not limited to this. The same effect can be expected even when applied to a sample analyzer for analyzing a sample containing biological particles such as urine cells. Furthermore, in the above-described embodiment, the analysis result is displayed on the display device 25 of the calculation display device 2. However, the present invention is not particularly limited, and other computers connected via a network have it. It may be displayed on a display device.

  It should be noted that the present invention is not limited to the above-described embodiments, and it goes without saying that various modifications and substitutions are possible within the scope of the gist of the present invention.

It is a perspective view which shows typically the structure of the sample analyzer which concerns on embodiment of this invention. It is a block diagram which shows the structure of the measuring apparatus of the sample analyzer which concerns on embodiment of this invention. It is a block diagram which illustrates typically the composition of the sample preparation part concerning an embodiment of the invention. It is a block diagram which illustrates typically composition of a detecting part and an analog processing part concerning an embodiment of the invention. It is a block diagram which shows the structure of the calculation display apparatus of the sample analyzer which concerns on embodiment of this invention. It is an illustration figure of the data structure of a patient information storage part. It is an illustration figure of the scattergram at the time of leukocyte classification measurement (DIFF measurement). It is an illustration figure of the relationship between the distribution area of the lymphocyte of a scattergram at the time of DIFF measurement, and a sampling value. It is a flowchart which shows the process procedure of CPU of the control board part of the measuring apparatus which concerns on embodiment of this invention, and a calculation display apparatus. It is a flowchart which shows the measurement process sequence of the control part of the control board part of the measuring device which concerns on embodiment of this invention. It is a flowchart which shows the analysis processing procedure of CPU of the calculation display apparatus which concerns on embodiment of this invention. It is a flowchart which shows the selection processing procedure of the classification data of CPU of the calculation display apparatus which concerns on embodiment of this invention. It is an illustration figure of the screen which displays the classification result of the display apparatus of the calculation display apparatus which concerns on embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Measuring apparatus 2 Computation display apparatus 4 Apparatus mechanism part 5 Detection part 6 Analog processing part 9 Control board part 21 CPU
22 RAM
23 storage device 24 input device 25 display device 26 output device 27 communication interface 28 internal bus 91 control unit 92 A / D conversion unit 93 calculation unit 231 computer program 232 patient information storage unit

Claims (7)

A sample preparation unit for preparing a measurement sample including a sample and a reagent;
A detection unit for detecting a predetermined component contained in the measurement sample prepared by the sample preparation unit;
Detection condition setting means for setting a plurality of detection conditions when the detection unit detects a predetermined component;
Detection unit control means for controlling the detection unit to detect a predetermined component contained in one measurement sample for each of a plurality of detection conditions set by the detection condition setting means ;
Selection means for automatically selecting one detection result from detection results for each of the plurality of detection conditions;
Analyzing means for analyzing the predetermined component based on the one detection result selected by the selecting means . The detection unit includes an amplifier that amplifies the detection signal of the predetermined component,
The sample analysis apparatus according to claim 1 , wherein the plurality of detection conditions are conditions related to an amplification factor of a detection signal by the amplifier . The detector is
A flow cell through which the measurement sample passes;
A light emitting unit for irradiating light to the measurement sample passing through the flow cell;
A light receiving portion for receiving light from the measurement sample irradiated with light from the light emitting portion;
The sample analyzer according to claim 1 or 2, characterized in that it comprises a. The sample analysis apparatus according to claim 3 , wherein the plurality of detection conditions are conditions relating to light detection sensitivity by the light receiving unit . 5. The sample analyzer according to claim 3, wherein the plurality of detection conditions are conditions related to an irradiation intensity of light from the light emitting unit . 6. The detection unit according to claim 3, wherein the detection unit control unit changes one detection condition to another detection condition while the measurement sample passes through the flow cell . Sample analyzer. In a sample analysis method that has a detection unit that detects a predetermined component contained in a sample and can be executed by a sample analyzer that analyzes the sample based on the predetermined component detected by the detection unit,
Prepare a measurement sample containing the sample and reagent,
Set multiple detection conditions,
A predetermined component contained in one prepared measurement sample is detected for each of the set detection conditions,
Automatically selecting one detection result from the detection results for each of the plurality of detection conditions;
A sample analysis method, wherein the predetermined component is analyzed based on one selected detection result .

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