JPH0926389A - Analysis data correcting method, calculator used therefor, and particle analyzer using the method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To correct the irregularity among apparatuses by measuring the same specimen with a reference particle analyzer and an object particle analyzer, calculating correlation parameter from the reference and object distribution data, and correcting the distribution data obtained by measuring the arbitrary specimen by the object particle analyzer by the correlation parameter. SOLUTION: The reference particle analyzer 1 and the object particle analyzer 2 have the same specifications. A sample is measured by the distribution data forming means 9 of the analyzer 1, reference distribution data f(x) is formed, and stored in memory means 4. The same specimen is measured by the means 9 of the analyzer 2, object distribution data g(x) is formed, and stored in memory means 5. Then, the means 9 obtains the correlation parameter of the data f(x), g(x), i.e., an offset (d) and a scale S, which are output from output means 7, and stored in the memory means 8 of the analyzers 2. The analyzer 2 measures arbitrary specimen by the means 9 to form analysis data h(x), the offset (d) and the scale S are corrected by correcting means 10, which analyzes the particles by the corrected data.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for correcting analytical data, an arithmetic unit used therefor, and a particle analyzer using the correcting method, and more particularly to correcting variations in analytical data among a plurality of particle analyzers having the same specifications. Technology.

[0002]

2. Description of the Related Art Conventionally, in a particle analyzer such as a flow cytometer, an optical system for optically detecting a parameter characterizing a particle and a distribution data (distribution It is equipped with a signal processing system to create the figure) and analyze the morphology and number of blood cells contained in the sample.

[0003]

However, when the same sample is analyzed by a plurality of particle analyzers manufactured with the same specifications, particles produced due to variations in characteristics between those optical systems and signal processing systems. There is a problem that the same analysis results cannot be obtained because the distribution data are different from each other.

The present invention has been made in consideration of such circumstances, and an analysis data correction method capable of correcting variations in analysis results among a plurality of particle analysis apparatuses, an arithmetic unit used therefor, and a correction method thereof. The present invention provides a particle analyzer using the.

[0005]

SUMMARY OF THE INVENTION The present invention is directed to measuring a sample by a reference particle analyzer to create reference distribution data, and measuring the same sample as the sample by the target particle analyzer to obtain an object. Create distribution data, calculate the correlation parameter that represents the difference between the reference distribution data and the target distribution data, measure any sample with the target particle analyzer to create distribution data, and create the analysis data using the correlation The present invention provides an analytical data correction method for a particle analyzer, which is characterized in that it is corrected by parameters. The above-mentioned “same sample as the sample” does not mean a sample in the same container in a strict sense, but the containers may be different. That is, it means a sample from which the same distribution data can be obtained.

The particles to be analyzed in the present invention are various cells and blood cells mainly contained in body fluids collected from humans or mammals, but may be fine particles such as inorganic powder.

The particle analyzer according to the present invention is used to measure the parameters characterizing the particles by an arbitrary method, for example, an electrical and / or optical method to create particle distribution data, and based on the distribution data. This is a device for analyzing particles.

Regarding the reference distribution data and the object distribution data, when analyzing the same sample with a plurality of particle analyzers having the same specifications, the distribution data obtained from one selected specific particle analyzer is used as a reference. The distribution data is used as the target distribution data.

The distribution data is data generally created by a conventional particle analyzer, for example, distribution map (scattergram or histogram) data represented by one or more parameters and their frequencies. .

The correlation parameter representing the difference between the reference distribution data and the target distribution data is a parameter for matching both distribution data obtained for the same sample. When represented in the figure, it can be represented by a scale (scale ratio of coordinate axes) and an offset (deviation in the coordinate axis direction) between each distribution chart.

In this case, the target distribution data can be matched with the reference distribution data by adjusting the scale and offset in the target distribution data.

That is, when analyzing an arbitrary sample with a target particle analyzer, if the distribution data is corrected with a correlation parameter (scale and offset), the same distribution data as the reference particle analyzer can be obtained. You can The scale and offset can be calculated from the statistically expected value and variance of the basic distribution data and the target distribution data.

Further, the present invention is an arithmetic unit for use in the above method, comprising first storage means for storing first distribution data, second storage means for storing second distribution data, and first storage means.
And a calculation means for calculating a correlation parameter representing the difference between the second distribution data and an output means for outputting the calculated correlation parameter.

Here, the first and second storage means and the calculation means can be integrally configured by using a microcomputer including a CPU, a ROM and a RAM, and the output means converts, for example, a correlation parameter into an electric signal. It may be a means for outputting in real time, or a device for temporarily storing the correlation parameter in a recording medium such as a floppy disk and outputting it.

Further, according to the present invention, storage means for storing the correlation parameter output from the above apparatus, distribution data creating means for measuring a sample to create distribution data, and the created distribution data based on the correlation parameter The present invention provides a particle analysis device provided with a correction means for performing correction and a analysis means for performing particle analysis based on the corrected distribution data.

Here, as the distribution data creating means and the analyzing means, it is possible to use an optical system and an analyzing system constituting a conventionally known particle analyzer. The storage unit and the correction unit can be integrally configured by using a microcomputer.

[0017]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below in detail with reference to the embodiments shown in the drawings. This does not limit the present invention. FIG. 1 is a block diagram showing an embodiment of the arithmetic unit of the present invention, and FIG. 2 is a block diagram showing an embodiment of the particle analyzer of the present invention.

In FIG. 1, 1 and 2 are particle analyzers manufactured with the same specifications. In both cases, a sample is measured to create distribution data, and particles of the sample are analyzed based on the distribution data. Has become. Here, 1 is a reference particle analyzer and 2 is a target particle analyzer.

FIG. 2 is a block diagram showing the configuration of the particle analyzers 1 and 2 shown in FIG. 1. Reference numeral 8 is a storage means for storing correlation parameters for correcting distribution data, and 9 is a sample, and distribution data is created. A distribution data creating means, 10 is a correcting means for correcting the distribution data created by the distribution data creating means 9 based on the correlation parameter stored in the storage means 8, and 11 is a particle analysis based on the corrected distribution data. It is an analytical tool.

In the arithmetic unit 3 of FIG. 1, 4 is a first storage means for storing the reference distribution data created by the distribution data creating means 9 of the reference particle analyzer 1, and 5 is a distribution data creating means of the target particle analyzer 2. Second storage means 9 stores the created target distribution data, 6 is a calculating means for calculating a correlation parameter representing the difference between the first and second distribution data, and 7 is an output means for outputting the calculated correlation parameter.

Here, for simplification of explanation, it is assumed that the reference distribution data and the object distribution data are functions f (x) and g (x) representing a one-dimensional histogram, respectively.
The difference between the distribution data f (x) and g (x) is considered to be caused by the following two factors, for example.

(1) Due to a slight difference in optical system between particle analyzers. As shown in FIGS. 4A and 4B, g
(X) has the same waveform as f (x), but if it is offset by an offset d in the X-axis direction,

[0023]

[Equation 1] Is represented by

(2) Due to a slight difference in signal processing system between particle analyzers. As shown in (a) and (b) of FIG. 5, g (x)
Is a scale S expanded in the X-axis direction with respect to f (x)

[0025]

[Equation 2] Is represented by

Usually, g (x) is the above (1),
Since both factors (2) cause a difference from f (x), in general,

[0027]

(Equation 3) Is represented by

Therefore, if g (x) is inversely transformed by the scale S and the offset d, f (x) can be calculated. That is, g (x) can be corrected with the scale S and the offset d to be f (x).

The operation of the embodiment shown in FIGS. 1 and 2 will be described below with reference to the flow chart shown in FIG. First, the sample is measured by the distribution data creating unit 9 of the reference particle analyzer 1, the basic distribution data f (x) is created and stored in the first storage unit 4 (step S1), and then the target particle analyzer. The same sample as the sample is measured by the second distribution data creating means 9, and the target distribution data g (x) is created and stored in the second storage means 5 (step S2).

Next, the calculation means 6 calculates the distribution data f (x).
And g (x), the correlation parameter, that is, the offset d when the distribution data is represented by a histogram
(FIG. 4) and scale S (FIG. 5) are calculated (step S
3) The output unit 7 outputs the offset d and the scale S, and the output offset d and the scale S are stored in the storage unit 8 of the target particle analyzer 2.

Next, the target particle analyzer 2 measures an arbitrary sample by the distribution data creating means 9 to calculate the distribution data h.
When (x) is created (step S4), the created distribution data h (x) is corrected by the correction means 10 by the offset d and the scale S (step S5), and the analysis means 10 is corrected by the distribution data. The particles are analyzed by (step S6).

In this way, the same analysis result can be obtained even if the characteristics of the optical system and the signal processing system vary among the plurality of particle analyzers.

Next, in the calculating means 6, f (x) and g
A procedure for calculating the offset d and the scale S from (x) will be described with reference to FIGS. 4 and 5. The expected value E [f] and the variance V [f] of the histogram f (x) are expressed by the following equations.

[0034]

(Equation 4) On the other hand, the expected value E [g] of the histogram g (x) and the variance V
[G] is represented by the following formula.

[0035]

(Equation 5)

[0036]

(Equation 6) From equations (6) and (7),

[0037]

(Equation 7) Becomes

In the above embodiment, the distribution data is a one-dimensional histogram and the distribution data is a function of continuous values. However, even if the distribution data is an n-dimensional histogram, Even if the data is a function of the variance value, the present invention can be similarly applied.

Further, regarding the offset d and the scale s, when two feature points A and B clearly exist in each distribution data,

(Equation 8) Can be easily obtained from Note that the first feature point of Af: f (x), the second feature point of Bf: f (x), the first feature point of Ag: g (x), the second feature point of Bg: g (x).

[0040]

According to the present invention, characteristics between a plurality of particle analyzers can be obtained by calibrating distribution data obtained by another particle analyzer with reference to distribution data obtained by one particle analyzer. The above variation is properly corrected, and the variation in the analysis result is eliminated.

[Brief description of drawings]

FIG. 1 is a block diagram showing one embodiment of the present invention.

FIG. 2 is a detailed block diagram of an essential part of FIG.

FIG. 3 is a flowchart showing the operation of the embodiment.

FIG. 4 is a scattergram for explaining an example of a correlation parameter according to an embodiment.

FIG. 5 is a scattergram for explaining another example of the correlation parameter of the example.

[Explanation of symbols]

 1 Reference Particle Analysis Device 2 Target Particle Analysis Device 3 Calculation Means 4 First Storage Means 5 Second Storage Means 6 Calculation Means 7 Output Means 8 Storage Means 9 Distribution Data Creation Means 10 Correction Means 11 Analysis Means

Claims (5)

[Claims] 1. A standard particle analyzer is used to measure a sample to create standard distribution data, and a target particle analyzer measures the same sample as the sample to create target distribution data. Analytical data characterized by calculating a correlation parameter representing a difference with the distribution data, measuring an arbitrary sample by a target particle analyzer to create distribution data, and correcting the created distribution data by the correlation parameter. Correction method. 2. An arithmetic unit for use in the method according to claim 1, wherein the first storage means stores the first distribution data, the second storage means stores the second distribution data, and the first and second storage means. An arithmetic unit comprising a calculating means for calculating a correlation parameter representing a difference between distribution data and an outputting means for outputting the calculated correlation parameter. 3. A storage unit for storing a correlation parameter output from the device according to claim 2, a distribution data creating unit for measuring a sample to create distribution data, and the created distribution data based on the correlation parameter. A particle analysis device comprising a correction means for correction and an analysis means for performing particle analysis based on the corrected distribution data. 4. The method according to claim 1, wherein the correlation parameter is represented by a value corresponding to the scale ratio of the coordinate axis and the shift in the coordinate axis direction when the distribution data is represented by a distribution chart. 5. The method according to claim 1, wherein the correlation parameter is a value calculated from each expected value and variance of basic distribution data and target distribution data.