A data calibration method for a sample analysis system and a sample analysis system
By acquiring sample measured values and theoretical values, responding to automatic calibration commands, selecting calibration points and making corrections, the problem of inconsistent measurement results from different sample analysis instruments is solved, and highly consistent measurement results are output.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHEMCLIN DIAGNOSTICS (SUZHOU) CO LTD
- Filing Date
- 2024-12-31
- Publication Date
- 2026-06-30
Smart Images
Figure CN122307131A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of sample data processing technology, and in particular to a data calibration method and a sample analysis system for a sample analysis system. Background Technology
[0002] Sample analyzers are high-precision measuring instruments, typically with measurement accuracy at the microgram / mL level. Chemiluminescence analyzers can even achieve nanogram / mL accuracy, with some instruments reaching picogram / mL. This high-precision requirement makes the measurement quality of sample analyzers highly susceptible to variation, such as component misalignment due to daily operation. Therefore, sample analyzer calibration plays a crucial role in laboratory testing quality management. Traditional calibration methods involve calibrating the sample analyzer itself relative to calibrators. In traditional methods, a sample analyzer uses multiple calibrators of known concentrations to establish a numerical relationship between the instrument's test signal intensity and the sample concentration. This relationship can be represented by a fitted calibration curve. After constructing the calibration curve, a sample of unknown concentration is placed in the measurement program, and the measured signal value is applied to the calibration curve to interpolate its concentration, thus estimating the sample concentration. By using calibrators provided by the sample analyzer manufacturer or third-party calibrators, it is possible to ensure that the measurement results of the testing instrument and system are consistent with standard values, improving the accuracy and comparability of the measurement results and ensuring that the sample analyzer's testing performance meets laboratory standards.
[0003] During the construction of calibration curves, the test signal strength of a sample analyzer depends on the instrument's own detection sensitivity and the detection method. Even using the same calibrators, deviations will exist between the test signals of different sample analyzers, resulting in different fitting parameters in the calibration curves established by different analyzers. Even sample analyzers from the same manufacturer may exhibit slight differences in measurement performance. Due to the different fitting parameters of the calibration curves, the measurement results of different sample analyzers for the same sample often differ. Measurement differences between different instruments lead to poor consistency in the measurement results of the same sample at different analyzers. The same sample may be measured as a low concentration of the analyte at instrument A, but as a medium concentration at instrument B. This makes it difficult for laboratories to assess the detection consistency of various sample analyzers during quality control.
[0004] In theory, this inconsistency in measurement values between instruments can be eliminated by adjusting the calibration curve fitting parameters of each instrument. However, fitting parameters from different manufacturers are difficult to obtain, so a new method is needed to eliminate measurement inconsistency. Summary of the Invention
[0005] This application provides a data calibration method and a sample analysis system for a sample analysis system, in order to solve or partially solve the problem of reducing the inconsistency of measurement results of different instruments for the same test sample without adjusting the calibration curve fitting parameters.
[0006] The first aspect of this application provides a data calibration method for a sample analysis system, comprising: Obtain the sample measurements of multiple test samples and the corresponding theoretical values of the sample measurements; In response to an automatic calibration command, determine the automatic calibration parameters corresponding to the automatic calibration command; At least one calibration point is selected according to the preset calibration configuration rules, and the sample measurement value corresponding to the calibration point is corrected using the automatic calibration parameters to obtain the sample correction value. The sample measurements are calibrated based on the sample correction value and the theoretical value, and the calibrated sample measurements are output.
[0007] In one example, the preset calibration configuration rules include calibration point selection intervals and calibration point selection locations, and selecting at least one calibration point according to the preset calibration configuration rules includes: Obtain the theoretical value range of the tested sample; The theoretical values within the theoretical value range are sorted and numbered in ascending order to obtain a list of theoretical values, with each theoretical value corresponding to a theoretical value point. At least one calibration point is selected from multiple theoretical value points according to the calibration point selection interval and the calibration point selection position.
[0008] In one example, the automatic calibration parameters include a computational quantity of K, and the step of correcting the sample measurement value corresponding to the calibration point using the automatic calibration parameters to obtain a sample correction value includes: Using the calibration point as a reference point, calculate the mean deviation of the measured values of the K samples before and after the calibration point; The average deviation is used as the deviation value of the calibration point; The sample measurements are corrected using the deviation and theoretical values of the calibration points to obtain the corrected sample values.
[0009] In one instance, the automatic calibration parameters further include a preset threshold, and the calculation of the mean deviation of the K sample measurements before and after includes: Calculate the percentage deviation of the K sample measurements before and after the calibration point; The sample measurements whose percentage deviation exceeds the preset threshold are identified as outliers; After removing the outliers, the mean of the percentage deviations of the remaining sample measurements is calculated to obtain the mean deviation.
[0010] In one instance, calibrating the sample measurement based on the sample correction value and the theoretical value, and outputting the calibrated sample measurement, includes: The sample correction values and theoretical values of the calibration points are fitted together to obtain a function model; The sample measurements are input into the function model, and the calibrated sample measurements are output.
[0011] In one instance, the automatic calibration command is a command triggered by a preset method, used to initialize the automatic calibration parameters.
[0012] In one instance, the method further includes: In response to an image display instruction, determine image display parameters corresponding to the image display instruction, wherein the image display parameters include at least image coordinates, consistency limits, and data display type; A calibration statistical image is generated using the image coordinates, the consistency limit, and the data display type. The calibration statistical image is used to display the image before and after consistency.
[0013] A second aspect of this application provides a sample analysis system, including a sample detection module and a controller; The sample detection module is used to acquire sample measurement values of multiple test samples and send the sample measurement values to the controller; The controller is configured to acquire the theoretical value corresponding to the sample measurement; in response to an automatic calibration command, determine the automatic calibration parameters corresponding to the automatic calibration command; select at least one calibration point according to a preset calibration configuration rule, and use the automatic calibration parameters to correct the sample measurement corresponding to the calibration point to obtain a sample correction value; calibrate the sample measurement based on the sample correction value and the theoretical value, and output the calibrated sample measurement.
[0014] A third aspect of this application provides a computer-readable storage medium having executable code stored thereon, which, when executed by a controller of an electronic device, causes the controller to perform the method described above.
[0015] A fourth aspect of this application provides a sample analyzer including the computer-readable storage medium described above.
[0016] The technical solution provided in this application may include the following beneficial effects: In this embodiment, sample measurements of multiple test samples and their corresponding theoretical values are obtained; in response to an automatic calibration command, automatic calibration parameters corresponding to the automatic calibration command are determined; at least one calibration point is selected according to a preset calibration configuration rule, and the sample measurements corresponding to the calibration point are corrected using the automatic calibration parameters to obtain a sample correction value; the sample measurements are calibrated according to the sample correction value and the theoretical value, and the calibrated sample measurements are output.
[0017] Compared with related technologies, the technical solution provided in this application, after triggering the automatic calibration command, first automatically determines the automatic calibration parameters corresponding to the automatic calibration command, and quickly selects at least one calibration point according to the pre-set calibration configuration rules. Then, for each selected calibration point, the sample measurement value is effectively corrected using the automatic calibration parameters to obtain a sample correction value that is closer to the theoretical value. This allows for accurate calibration of the sample measurement value by combining the sample correction value with a smaller error and the theoretical value, resulting in sample measurement values with a high degree of consistency. It can be seen that when it is necessary to evaluate the measurement results of different instruments on the same test sample, this application can provide a unified calibration process to calibrate the measurement results of each instrument. This effectively reduces the measurement deviation caused by each instrument without adjusting the calibration fitting parameters of each instrument, and significantly improves the consistency of the measurement results.
[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0019] The above and other objects, features and advantages of this application will become more apparent from the following description of exemplary embodiments of this application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of this application.
[0020] Figure 1 This is a schematic flowchart illustrating a data calibration method for a sample analysis system, as shown in an embodiment of this application. Figure 2 This is another schematic flowchart illustrating a data calibration method for a sample analysis system, as shown in an embodiment of this application. Figure 3 This is a schematic diagram of the functional interface of the sample analysis system shown in the embodiments of this application; Figure 4 This is a schematic diagram illustrating calibration point information in an embodiment of this application; Figure 5 This is a schematic diagram of the first data conversion shown in an embodiment of this application; Figure 6 This is a schematic diagram of the second data conversion shown in an embodiment of this application; Figures 7A-7BThis is a BA diagram without outlier removal shown in the embodiments of this application; Figures 8A-8B This is a BA diagram illustrating the removal of outliers, as shown in the embodiments of this application; Figure 9 This is a schematic diagram of the structure of a sample analysis system shown in an embodiment of this application; Figure 10 This is a schematic diagram of the sample analyzer shown in the embodiments of this application. Detailed Implementation
[0021] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While embodiments of this application are shown in the drawings, it should be understood that this application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to make this application more thorough and complete, and to fully convey the scope of this application to those skilled in the art.
[0022] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.
[0023] It should be understood that although the terms "first," "second," "third," etc., may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.
[0024] In existing calibration processes, calibration points can provide known standard values, such as the sample concentration of a specific sample corresponding to each calibration point or other data.
[0025] When an unknown sample is placed in the measurement program, the instrument first measures the signal value of the sample, then applies the measured signal value to the calibration curve, and estimates the sample concentration or other data of the unknown sample through interpolation. Finally, the estimated sample concentration or other data is compared with known standard values to evaluate the measurement deviation of the instrument.
[0026] However, due to differences in the fitting parameters of the calibration curves, different sample analyzers often produce different measurement results for the same sample. These measurement differences between instruments lead to poor consistency in the measurement results of the same sample across different analyzers. The same sample might be measured as a low concentration of the analyte at instrument A, but as a medium concentration at instrument B. This makes it difficult for laboratories to assess the consistency of detection across different sample analyzers when performing quality control.
[0027] To address the aforementioned issues, this application provides a data calibration method for a sample analysis system, which can improve the inconsistency of measurement results for the same test sample from different instruments without adjusting calibration curve fitting parameters.
[0028] The technical solutions of the embodiments of this application are described in detail below with reference to the accompanying drawings.
[0029] Figure 1 This is a schematic flowchart illustrating a data calibration method for a sample analysis system, as shown in an embodiment of this application. See also... Figure 1 The method includes at least the following steps.
[0030] Step 101: Obtain the sample measurements of multiple test samples and the corresponding theoretical values.
[0031] In this embodiment, the data calibration method is applied to a sample analysis system. The sample analysis system possesses functions of precise measurement, data analysis, and result calibration. It is primarily used to ensure consistency of measurement results from different laboratories and instruments. For example, suppose laboratory A and laboratory B use instruments from different brands to measure the same sample. Due to differences in instrument performance, environmental conditions, and other factors, the measurement results obtained by the two instruments may have some deviation. In this case, the sample analysis system of this application can be used to automatically calibrate the measurement results of the two instruments, improving the consistency of the measurement results.
[0032] In this application, the sample analysis system can receive and display the measured values of multiple test samples and the corresponding theoretical values.
[0033] The test sample refers to a sample where the concentration of the analyte is unknown and requires quantitative or qualitative analysis. It can be a freshly collected blood sample.
[0034] Sample measurements refer to the data obtained after measuring a sample using an instrument, and are used to reflect the characteristics of the sample. Sample measurements can be all acquired sample measurements, sample measurements excluding those corresponding to calibration points, or a subset of all sample measurements.
[0035] The theoretical value can be the average of the sample measurements collected by multiple sample analyzers for the same sample. The theoretical value can also be the measurement value of the same sample using a different, higher-standard testing device with a different methodology than the sample analyzer. For example, the sample analyzer might be a chemiluminescence immunoassay analyzer, while the testing device providing the theoretical value might be a molecular diagnostic device.
[0036] As an example, suppose the sample to be tested is sample ①, and multiple sample analyzers, including sample analyzer 1, sample analyzer 2, and sample analyzer 3, are used to test sample ①, obtain multiple sample concentrations of sample ①, and then the average value of the multiple sample concentrations is used as the theoretical value.
[0037] Step 102: In response to the automatic calibration command, determine the automatic calibration parameters corresponding to the automatic calibration command.
[0038] In this embodiment of the application, the sample analysis system can respond to an automatic calibration command and dynamically determine the automatic calibration parameters corresponding to the automatic calibration command.
[0039] The automatic calibration command is the command that initiates the automatic calibration process and can specify the algorithm to be used for this data calibration. For example, it can specify whether to use the percentage deviation method or the ratio method as the calibration algorithm.
[0040] Automatic calibration parameters are generated based on automatic calibration instructions and participate in operations such as data correction, deviation calculation, and model fitting during the actual calibration process. For example, automatic calibration parameters may include calculation quantities, thresholds, and other parameters associated with the percentage deviation method or ratio method.
[0041] Step 103: Select at least one calibration point according to the preset calibration configuration rules, and use automatic calibration parameters to correct the sample measurement value corresponding to the calibration point to obtain the sample correction value.
[0042] In this embodiment of the application, after the sample analysis system obtains the sample measured value and theoretical value, it needs to select at least one calibration point according to the preset calibration configuration rules. At each calibration point, the sample measured value is corrected using the automatic calibration parameters determined in step 102 to obtain the sample corrected value.
[0043] Among them, the preset calibration configuration rules refer to a set of predefined rules and logic followed by the sample analysis system during the data calibration process. The calibration configuration rules are usually flexibly changed according to calibration requirements, so as to quickly select calibration points and ensure the standardization and consistency of the calibration process.
[0044] Calibration points refer to a set of reference points with known theoretical values selected during the calibration process of this application, in order to effectively evaluate and correct the measurement deviation of the sample analyzer. Calibration points are usually distributed within the operating range of the sample analyzer.
[0045] The sample correction value refers to the correction result obtained by the deviation calculation method of the calibration point. It is used to adjust the sample measurement value of the sample analyzer to make it closer to the theoretical value, and it directly affects the accuracy of the final calibration.
[0046] As an example, the sample analysis system selects five calibration points according to the preset calibration configuration rules, namely the first calibration point, the second calibration point, the third calibration point, the fourth calibration point, and the fifth calibration point. Using the automatic calibration parameters and the theoretical values corresponding to the above calibration points, the measurement deviation of the sample analyzer is calculated, and the sample measurement value at each calibration point is corrected using the measurement deviation, thereby obtaining the sample correction value at each calibration point.
[0047] Step 104: Calibrate the sample measurements based on the sample correction value and the theoretical value, and output the calibrated sample measurements.
[0048] In this embodiment of the application, after obtaining the sample correction value, the sample analysis system calibrates all sample measurements based on the sample correction value and the theoretical value, and outputs the calibrated sample measurements.
[0049] In this embodiment, sample measurements of multiple test samples and their corresponding theoretical values are obtained; in response to an automatic calibration command, automatic calibration parameters corresponding to the automatic calibration command are determined; at least one calibration point is selected according to a preset calibration configuration rule, and the sample measurements corresponding to the calibration point are corrected using the automatic calibration parameters to obtain a sample correction value; the sample measurements are calibrated according to the sample correction value and the theoretical value, and the calibrated sample measurements are output.
[0050] Compared with related technologies, the technical solution provided in this application, after triggering the automatic calibration command, first automatically determines the automatic calibration parameters corresponding to the automatic calibration command, and quickly selects at least one calibration point according to the pre-set calibration configuration rules. Then, for each selected calibration point, the sample measurement value is effectively corrected using the automatic calibration parameters to obtain a sample correction value that is closer to the theoretical value. This allows for accurate calibration of the sample measurement value by combining the sample correction value with a smaller error and the theoretical value, resulting in sample measurement values with a high degree of consistency. It can be seen that when it is necessary to evaluate the measurement results of different instruments on the same test sample, this application can provide a unified calibration process to calibrate the measurement results of each instrument. This effectively reduces the measurement deviation caused by each instrument without adjusting the calibration fitting parameters of each instrument, and significantly improves the consistency of the measurement results.
[0051] Figure 2 This is another schematic flowchart illustrating a data calibration method for a sample analysis system, as shown in an embodiment of this application. Figure 2 relatively Figure 1The technical solution of the embodiments of this application is described in more detail. The method may include the following steps: Step 201: Obtain the sample measurements of multiple test samples and the corresponding theoretical values of the sample measurements.
[0052] In actual laboratory testing quality control processes, different instruments (sample analyzers) may produce different measurement results even when testing the same sample. These differences are usually manifested as systematic errors between instruments, random errors, or measurement deviations caused by environmental changes.
[0053] These instrument errors make it difficult to directly compare test results obtained from different instruments, thereby affecting the effectiveness of laboratory quality control and the consistency of data.
[0054] To address this issue, this application designs a software tool to achieve consistency in sample measurements, namely the sample analysis system of this application. This tool has different functional modules that work together to provide a unified calibration procedure, thereby reducing errors caused by inconsistencies in calibration procedures, making measurement results comparable between different laboratories and different equipment, and improving the reliability of the data.
[0055] Furthermore, the sample analysis system may need to process a large number of test samples to meet the needs of rapid detection. Therefore, the sample analysis system of this application is equipped with at least two sample analyzers and a computer to perform data calibration methods, thereby improving detection efficiency.
[0056] As an example, a laboratory has a sample analysis system consisting of three sample analyzers and a computer for performing data calibration. These three analyzers are designated Instrument A, Instrument B, and Instrument C. Each instrument measures the same blood sample to detect the concentration of different components in the blood. The measurement results from Instrument A are slightly higher than those from Instrument B, and the measurement results from Instrument B are significantly higher than those from Instrument C. The computer can be used to calibrate the measurement results of each instrument individually, thereby obtaining consistent data.
[0057] Reference Figure 3 , Figure 3 This is a schematic diagram of the functional interface of the sample analysis system shown in an embodiment of this application. The sample analysis system includes a data display module, a data conversion module, a model setting module, and a graphic display module. The sample analysis system provides a functional interface for each module: interface A corresponds to the data display module, interface B to the data conversion module, interface C to the model setting module, and interface D to the graphic display module. Users can intuitively understand the actual content of each module through different functional interfaces.
[0058] In this application, the standardized sample measurements and their corresponding theoretical values can be manually entered into the data display module by the user, or the system can automatically receive and input them into the data display module from the sample analyzer.
[0059] It is worth noting that if this application adopts the method of automatic system reception and input of data, then when the data volume is large, the data can be filled in batches, thereby improving the efficiency of data input.
[0060] As an example, the functional interface A corresponding to the data display module is the data input and output interface. In the data input and output interface, there are measured value column, theoretical value column, measured value correction column and calculated value column. The sample analysis system automatically fills the measured value column with the sample measured value one by one, fills the theoretical value column with the corresponding theoretical value one by one, and after obtaining the sample correction value, it also automatically fills the measured value correction column with the sample correction value. After obtaining the final calibrated sample measured value, the calibrated sample measured value is filled into the calculated value column.
[0061] Step 202: In response to the automatic calibration command, determine the automatic calibration parameters corresponding to the automatic calibration command.
[0062] In this application, the automatic calibration command is actually a command triggered by a preset method to initialize the automatic calibration parameters. The preset methods include user selection, system default, and system automatic selection.
[0063] As an example, the automatic calibration command is associated with the data conversion module and the model setting module. The functional interface B corresponding to the data conversion module is the data conversion interface, which includes controls for converting between theoretical values (y) and uniformized results (x), namely "x→y control" and "y→x control". The functional interface C corresponding to the model setting module is the data selection interface, which includes "algorithm control".
[0064] The following explanations of the three preset methods are based on the examples above: The user selection method allows users to actively trigger automatic calibration commands through the interface, buttons, or other interactive methods. For example, the user can manually touch one of the "x→y control" or "y→x control" to trigger the automatic calibration command, or the user can manually touch the "algorithm control" to trigger the automatic calibration command. Alternatively, an additional "Start Calibration Button" can be set up in the sample analysis system, which the user can manually touch to trigger the automatic calibration command. This application does not restrict the type of control touched by the user selection method. The user selection method is suitable for special situations where manual confirmation of calibration is required.
[0065] The system's default mode can automatically trigger calibration commands according to predetermined times or conditions. For example, the "Algorithm Control" in the model settings module defaults to the percentage deviation method. After the system has been running for a certain period of time since startup, it will automatically calibrate based on the percentage deviation method. The system's default mode is suitable for highly automated scenarios, reducing manual intervention.
[0066] The system can automatically select a calibration algorithm for the test sample based on factors such as the type of algorithm used in the past, the type of sample being tested, and the complexity of the data, thereby triggering an automatic calibration command. For example, if the user's last touch of the "algorithm control" was the percentage deviation method, the system can automatically select the percentage deviation method and perform automatic calibration based on it. The system's default mode is suitable for scenarios where the system has complex algorithms and can adjust the algorithms in real time.
[0067] When the automatic calibration command is triggered, the sample analysis system enters the automatic calibration workflow. The core of this process is to select and apply a pre-trained automatic calibration algorithm (such as the percentage deviation method, ratio method, etc.) to effectively correct the sample measurements and eliminate inconsistencies caused by the instrument itself.
[0068] During the calibration process, the sample analysis system uses the algorithm to determine relevant automatic calibration parameters (such as the number of calculations, preset thresholds, etc.) to ensure the accuracy and reliability of the calibration process.
[0069] The number of calculations can be K, the number of preceding and following samples considered when calculating the deviation of sample measurements, where K is a positive integer. For example, if K is 20, it means that the correction process needs to consider 20 preceding and following sample measurements. Setting a reasonable number of calculations can help the sample analysis system better understand data variability and perform more accurate calibration.
[0070] The preset threshold can be a pre-defined range or value used to determine whether the data is abnormal. For example, a preset threshold of 1.5 times the interquartile range (1.5×IQR) can ensure that the calibration process is not affected by data with excessive errors.
[0071] Step 203: Select at least one calibration point according to the preset calibration configuration rules.
[0072] In this application, the preset calibration configuration rules include a pre-set calibration point selection interval and calibration point selection position. First, the theoretical value range of the test sample is obtained. Then, the theoretical values within the theoretical value range are sorted and numbered in ascending order to obtain a theoretical value list. Each theoretical value corresponds to a theoretical value point. At least one calibration point is selected from multiple theoretical value points according to the calibration point selection interval and calibration point selection position.
[0073] The theoretical value list can be a set of values arranged in ascending order of theoretical values. Each value in the theoretical value list corresponds to a theoretical value point. The theoretical value list mainly serves as a reference benchmark and is the basis for selecting calibration points. The sample analysis system can select several calibration points by combining the calibration point selection interval and the calibration point selection location.
[0074] The calibration point selection interval can be the distance between two adjacent calibration points within the theoretical value range. This interval determines the distribution density of calibration points, affecting the accuracy and stability of the calibration process. For example, intervals of 10 points, 50 points, or 100 points.
[0075] The selection of calibration points can be based on choosing specific locations from a sorted list of theoretical values, affecting the accuracy and applicability of the calibration. Examples include the starting point, ending point, or a specific location within the theoretical value list.
[0076] As an example, taking 90 quality control data points detected by a certain device as an example, the sample analysis system first obtains the theoretical lower limit and theoretical upper limit values manually input by the user or automatically identified by the system. The lower limit measured value is 0, the theoretical value is 0, the upper limit measured value is the upper limit of the device, and the theoretical value is the upper limit of the measured value × (1 + 15%). The theoretical values are arranged in ascending order and numbered. For the arranged data, one point is selected every 10 as a calibration point. At the same time, all selected calibration points must include the first theoretical value point and the last theoretical value point. The final selected calibration point numbers are: No. 2, No. 11, No. 21, ..., No. 91.
[0077] Step 204: Correct the sample measurements corresponding to the calibration points using automatic calibration parameters to obtain the sample correction values.
[0078] Due to incomplete calibration of the sample measurement equipment itself or differences between different equipment, the measured values of samples measured by different sample measurement equipment may deviate significantly from the theoretical values, and the data distribution is relatively wide, which increases the complexity of data analysis.
[0079] Therefore, in the process of data standardization, this application corrects the sample measurements at each calibration point in order to reduce the differences between different measuring devices, obtain more accurate and consistent measurement results, and improve the reliability and accuracy of the measurement results.
[0080] In this application, the process of correcting sample measurements mainly includes two parts: removing outliers and determining the deviation of calibration points.
[0081] The process of removing outliers can be as follows: using the calibration point as a reference point, calculate the percentage deviation of the K sample measurements before and after the calibration point, identify the sample measurements with percentage deviations exceeding a preset threshold as outliers, remove outliers, and then calculate the mean of the percentage deviations of the remaining sample measurements to obtain the mean deviation.
[0082] As an example, assuming the number of calculations K is 20, then using the calibration point as the reference point, the percentage deviation calculation formula is first applied: Calculate the percentage deviation of the measurements for the 20 samples before and after the test, and then calculate the lower quartiles of the percentage deviation data. and the upper quartile That is, interquartile range .
[0083] Will Below or Higher than The values are considered outliers and are removed, leaving only the sample measurements after outlier removal.
[0084] The process of determining the deviation of the calibration point can be as follows: obtain the mean deviation of the K sample measurements before and after (the average of the percentage deviations is taken), use the mean deviation as the deviation value of the calibration point, and use the deviation value of the calibration point and the theoretical value to correct the sample measurements to obtain the sample correction value.
[0085] As an example, the deviation of a calibration point is equal to the average of the percentage deviations (excluding outliers) of the 20 measurements before and after that point. That is, the deviation of the first calibration point (number 2) is the average of the percentage deviations from 2 to 11 after removing outliers; the deviation of the second calibration point (number 11) is the average of the percentage deviations from 2 to 21 after removing outliers; the deviation of the third calibration point (number 21) is the average of the percentage deviations from 12 to 31 after removing outliers; and so on, until the deviation of the tenth calibration point (number 91) is the average of the percentage deviations from 82 to 91 after removing outliers.
[0086] After obtaining the mean deviation, each mean deviation is used as the deviation value of each calibration point. The correction formula is used: Corrected measured value = theoretical value × (1 + calibration point deviation). The sample measured values corresponding to each calibration point are corrected one by one to obtain the sample correction value.
[0087] Reference Figure 4 , Figure 4 This is a schematic diagram of calibration point information shown in the embodiments of this application. In conjunction with Table 1 below, the sample correction values and theoretical values corresponding to the first to tenth calibration points can be obtained.
[0088] Table 1
[0089] Taking the sample measurement and sample correction value of the first calibration point as an example, the sample measurement value of the first calibration point is 22.48, and the sample correction value is 24.47. Compared with the theoretical value of 25.18, the sample correction value is closer to the theoretical value.
[0090] It can be seen that the uncorrected sample measurements deviate significantly from the theoretical values, and the distribution is quite discrete, making it difficult to meet the accuracy requirements. The corrected sample measurements deviate less from the theoretical values, are close to the theoretical range, and the distribution is more concentrated, exhibiting less fluctuation and effectively reducing the influence of instrument errors, systematic biases, and external environmental factors.
[0091] Step 205: Calibrate the sample measurements based on the sample correction value and the theoretical value, and output the calibrated sample measurements.
[0092] In this application, the method of calibrating the sample measurements using sample correction values and theoretical values is mainly a data fitting method. This method involves fitting the sample correction values and theoretical values of all calibration points to obtain a function model, then inputting the sample measurements into the function model, and outputting the calibrated sample measurements.
[0093] It's worth noting that data fitting primarily involves constructing a mathematical model to minimize the error between observed data and model predictions. For calibrating sample measurements, the goal of data fitting is to find a function model that best maps the relationship between theoretical values and corrected sample values.
[0094] As an example, suppose the sample analysis system, after going through steps 201 to 204, obtains a set of calibration point data, where each calibration point includes a theoretical value and a corrected sample measurement value (sample correction value): First calibration point: theoretical value is 50, sample correction value is 52; Second calibration point: theoretical value is 100, sample correction value is 106; Third calibration point: theoretical value is 150, sample correction value is 155; And so on... Nth calibration point: theoretical value is Y, sample correction value is X.
[0095] The sample analysis system can determine the functional relationship between the sample correction value and the theoretical value based on data fitting methods such as linear fitting, polynomial fitting, and exponential fitting, and construct the corresponding functional model.
[0096] Finally, the sample measurements are input into the function model to output the calibrated sample measurements, thus achieving data consistency.
[0097] Reference Figure 5 and Figure 6 , Figure 5 This is a schematic diagram of the first data conversion shown in an embodiment of this application. Figure 6 This is a schematic diagram of the second data conversion shown in an embodiment of this application. The first data is converted into a theoretical value calculated from the sample measurement (X→Y), and the second data is converted into a sample measurement calculated from the theoretical value (Y→X). After obtaining the function model for the detection sample, the sample measurement is converted into a theoretical value of the detection sample by performing the first data conversion, or the theoretical value is converted into a sample measurement by performing the second data conversion.
[0098] Step 206: In response to the image display instruction, generate a calibration statistical image associated with the calibrated sample measurements.
[0099] The sample analysis system also provides an image display module, which can respond to image display instructions and determine the image display parameters corresponding to the instructions. The image display parameters include at least image coordinates, consistency limits, and data display type. Based on the image coordinates, consistency limits, and data display type, a calibration statistical image associated with the calibrated sample measurements is generated.
[0100] Calibration statistical images primarily reflect the calibration effect of sample measurements through graphics and data points, displaying images before and after standardization. Assuming the calibration statistical image is a BA (Bland-Altman) plot, the horizontal axis in the BA plot may represent the theoretical value, while the vertical axis represents the deviation between the calibrated sample measurements and the theoretical value.
[0101] In this application, an image display instruction refers to a command triggered by a user through interface buttons, menu options, or other interactive methods (such as voice, shortcut keys, etc.). Image display parameters are display data corresponding to user operations or system defaults. In this application, image display parameters include at least image coordinates, consistency limits, and data display type.
[0102] Image coordinates include x-coordinates and y-coordinates, which define the position of data points in the image. For calibration statistical images, the x-coordinate can be one of the following: rank, theoretical value, or mean, while the y-coordinate can be the algorithm type.
[0103] Consistency limits define the display range of calibrated sample measurements. For calibration statistical graphs, consistency limits are typically represented by lines or regions to distinguish whether data falls within the expected range. For example, they are used when calculating the mean of percentage deviation or ratio data. The consistency bound is equal to the standard deviation (SD). .
[0104] Data display type refers to the data type that can be displayed on a calibration statistical image, such as selecting to display outliers or remove outliers. In practical applications, users can choose different data display types according to their needs to obtain a visualization method that meets their requirements. For example, a calibration statistical image is a BA image. A BA image without outlier removal is suitable for data diagnosis and anomaly analysis, helping to comprehensively understand the data distribution. A BA image with outlier removal is suitable for data analysis with high consistency requirements, helping to eliminate the interference of outliers on the overall analysis results.
[0105] It should be understood that the data display types provided in this application can meet different application needs and data conditions, and flexibly choose the way to display or remove outliers in order to obtain the most suitable visualization effect and analysis results.
[0106] Reference Figures 7A-7B , Figures 7A-7B This is a BA diagram without outlier removal, as shown in an embodiment of this application. From... Figure 7A and Figure 7B As can be seen, the BA plot without outliers reflects all the measurement data, including normal measurements and outliers. Outliers usually deviate from the central tendency of the overall data and form obvious "dot-like" areas outside the upper and lower control limits marked by dashed lines.
[0107] Reference Figures 8A-8B , refer to Figures 8A-8B This is a BA diagram illustrating outlier removal as shown in an embodiment of this application. From... Figure 8A and Figure 8B As can be seen, the BA plot after removing outliers reflects part of the measurement data. Outliers that deviate too far from other data points were removed by a certain method (such as the interquartile range method), and the remaining data points are more concentrated and evenly distributed within the upper and lower control limits marked by dashed lines.
[0108] As an example, the image display command is associated with the model settings module and the image display module. In the data selection interface corresponding to the model settings module, the vertical axis defaults to percentage deviation. Other selectable image display parameters include: algorithm type (percentage deviation method, ratio method), horizontal axis type (rank, theoretical value, mean), and data display type (BA plot to remove outliers).
[0109] Generate a BA diagram that matches the image display parameters and display it on the corresponding functional interface D of the image display module. Functional interface D is the graphic display interface.
[0110] To enable those skilled in the art to better understand the technical solutions of the embodiments of this application, the embodiments of this application are further illustrated below with an example.
[0111] 1) Obtain 90 quality control data points provided by the sample analyzer, use these 90 quality control data points as sample measurements, and at the same time obtain the theoretical values corresponding to the sample measurements.
[0112] 2) In response to the automatic calibration command, determine the automatic calibration algorithm and use the automatic calibration algorithm to automatically calibrate 90 quality control data.
[0113] 21) Calibration Point Configuration Rules: Sort and number the theoretical values in ascending order to obtain a list of theoretical values, with each theoretical value corresponding to a theoretical value point. For the sorted theoretical value points, select one point out of every 10 as a calibration point. All selected calibration points must include both the first and last theoretical value points. Automatically input the lower and upper limits of the theoretical values, where the lower limit is 0 (the theoretical value is 0), and the upper limit is the upper limit of the sample analyzer's measurement range. The final selected calibration points are numbered as follows: 2, 11, 21, ..., 91.
[0114] 22) Outlier removal: Calculate the lower quartiles for the percentage deviation data. and the upper quartile Then the interquartile range It will be lower than or higher The measured values of the sample are considered outliers.
[0115] The formula for calculating the percentage deviation is as follows: .
[0116] 23) Determine the deviation value of the calibration point: The deviation value of the calibration point is equal to the average of the percentage deviations (excluding outliers) of the 20 measured data points before and after that point. That is, the deviation value of the first calibration point (serial number 2) is the average of the percentage deviations of 2-11 after removing outliers; the deviation value of the second calibration point (serial number 11) is the average of the percentage deviations of 2-21 after removing outliers; the deviation value of the third calibration point (serial number 21) is the average of the percentage deviations of 12-31 after removing outliers; ..., the deviation value of the tenth calibration point (serial number 91) is the average of the percentage deviations of 82-91 after removing outliers.
[0117] 24) Correct the sample measurements at each calibration point: Correct the sample measurements based on the deviation values at the calibration points. The corrected measurement value equals the theoretical value. (1 + calibration point deviation).
[0118] 25) Calculation of uniformity results: The sample corrected measurement value (X) of the calibration point is fitted with its corresponding theoretical value (Y) to obtain the functional relationship. Based on the functional relationship, a function model is constructed. Finally, the sample measurement value is substituted into the function model to output the calibrated sample measurement value, which is the uniform measurement result.
[0119] 3) After automatic calibration is completed, draw the BA diagram.
[0120] 31) Select the vertical axis: percentage deviation or ratio The formula for calculating percentage deviation is: ; The formula for calculating the ratio is: .
[0121] 32) Select the x-axis: rank, theoretical value, or mean. Rank: Plot a BA graph with the rank of the theoretical value as the x-axis; Theoretical values: Plot a BA chart with theoretical values as the x-axis; Mean: A BA chart is plotted with the average of the measured and theoretical values as the x-axis. ).
[0122] 33) Selecting outliers: Based on the interquartile range of the percentage deviation data. To identify outliers, the value will be lower than or higher The value is removed.
[0123] 34) Set consistency limits: Calculate the mean of the percentage deviation (ratio) data. The consistency bound is equal to the standard deviation (SD). .
[0124] 35) Generate a BA chart based on parameters such as the vertical axis, horizontal axis, whether outliers are removed, and consistency limits.
[0125] This application provides a unified data calibration method, which on the one hand improves the comparability of measurement results between different laboratories and different equipment, reduces errors caused by inconsistent calibration procedures, and thus improves data reliability. On the other hand, it reduces human error and time in the process of automated calibration and standardization, and improves the efficiency of standardization. At the same time, the BA diagram visually displays the differences before and after calibration and their distribution, which helps to evaluate the effect of data standardization.
[0126] It should be noted that the embodiments of this application include, but are not limited to, the examples described above. It is understood that, under the guidance of the ideas in the embodiments of this application, those skilled in the art can make settings according to the actual situation, and this application does not impose any restrictions on them.
[0127] In this embodiment, sample measurements of multiple test samples and their corresponding theoretical values are obtained; in response to an automatic calibration command, automatic calibration parameters corresponding to the automatic calibration command are determined; at least one calibration point is selected according to a preset calibration configuration rule, and the sample measurements corresponding to the calibration point are corrected using the automatic calibration parameters to obtain a sample correction value; the sample measurements are calibrated according to the sample correction value and the theoretical value, and the calibrated sample measurements are output.
[0128] Compared with related technologies, the technical solution provided in this application, after triggering the automatic calibration command, first automatically determines the automatic calibration parameters corresponding to the automatic calibration command, and quickly selects at least one calibration point according to the pre-set calibration configuration rules. Then, for each selected calibration point, the sample measurement value is effectively corrected using the automatic calibration parameters to obtain a sample correction value that is closer to the theoretical value. This allows for accurate calibration of the sample measurement value by combining the sample correction value with a smaller error and the theoretical value, resulting in sample measurement values with a high degree of consistency. It can be seen that when it is necessary to evaluate the measurement results of different instruments on the same test sample, this application can provide a unified calibration process to calibrate the measurement results of each instrument. This effectively reduces the measurement deviation caused by each instrument without adjusting the calibration fitting parameters of each instrument, and significantly improves the consistency of the measurement results.
[0129] Corresponding to the aforementioned application function implementation method embodiments, this application also provides a sample analysis system, a sample analyzer, and corresponding embodiments.
[0130] Figure 9 This is a schematic diagram illustrating the structure of a sample analysis system according to an embodiment of this application. See also... Figure 9 The system includes a sample detection module 901 and a controller 902; The sample detection module 901 is used to acquire the sample measurement values of multiple test samples and send the sample measurement values to the controller; The controller 902 is used to acquire the theoretical value corresponding to the sample measurement; in response to the automatic calibration command, determine the automatic calibration parameters corresponding to the automatic calibration command; select at least one calibration point according to the preset calibration configuration rules, and use the automatic calibration parameters to correct the sample measurement corresponding to the calibration point to obtain the sample correction value; calibrate the sample measurement based on the sample correction value and the theoretical value, and output the calibrated sample measurement value.
[0131] As an optional example of this application, the preset calibration configuration rules include calibration point selection interval and calibration point selection location, and the controller 902 is used for: Obtain the theoretical value range for the test sample; The theoretical values within the theoretical value range are sorted and numbered in ascending order to obtain a list of theoretical values, with each theoretical value corresponding to a theoretical value point. At least one calibration point is selected from multiple theoretical value points according to the calibration point selection interval and calibration point selection location.
[0132] As an optional example of this application, the automatic calibration parameters include the number of calculations, where the number of calculations is K, and the controller 902 is used for: Using the calibration point as the reference point, calculate the mean deviation of the measured values of the K samples before and after the calibration point; The mean deviation is used as the deviation value at the calibration point; The sample measurements are corrected using the deviation values of the calibration points and the theoretical values to obtain the corrected sample values.
[0133] As an optional example of this application, the automatic calibration parameters also include a preset threshold, and the controller 902 is used for: Calculate the percentage deviation of the K sample measurements before and after the calibration point; Sample measurements with a percentage deviation exceeding a preset threshold are identified as outliers; After removing outliers, the mean of the percentage deviations of the remaining sample measurements is calculated to obtain the mean deviation.
[0134] As an optional example of this application, controller 902 is used for: The sample correction values and theoretical values of the calibration points are fitted together to obtain the function model; Input the sample measurements into the function model, and output the calibrated sample measurements.
[0135] As an optional example of this application, the automatic calibration command is a command triggered by a preset method to initialize the automatic calibration parameters.
[0136] As an optional example of this application, controller 902 is used for: In response to an image display instruction, determine the image display parameters corresponding to the image display instruction. The image display parameters include at least image coordinates, consistency limits, and data display type. A calibration statistical image is generated by using image coordinates, consistency limits, and data display type. The calibration statistical image is used to display the image before and after consistency.
[0137] Regarding the sample analysis system in the above embodiments, the specific manner in which the controller performs operations has been described in detail in the embodiments related to the method, and will not be elaborated further here.
[0138] Figure 10 This is a schematic diagram of the sample analyzer shown in the embodiments of this application.
[0139] See Figure 10 The sample analyzer 1000 includes a memory 1010 and a controller 1020.
[0140] The controller 1020 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.
[0141] Memory 1010 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. ROM may store static data or instructions required by controller 1020 or other modules of the computer. Permanent storage devices may be read-write storage devices. Permanent storage devices may be non-volatile storage devices that retain stored instructions and data even when the computer is powered off. In some embodiments, permanent storage devices employ mass storage devices (e.g., magnetic or optical disks, flash memory) as permanent storage devices. In other embodiments, permanent storage devices may be removable storage devices (e.g., floppy disks, optical drives). System memory may be a read-write storage device or a volatile read-write storage device, such as dynamic random access memory. System memory may store some or all of the instructions and data required by the processor during operation. Furthermore, memory 1010 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (e.g., DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, the memory 1010 may include a removable storage device that is readable and / or writable, such as a laser disc (CD), a read-only digital multifunction optical disc (e.g., DVD-ROM, dual-layer DVD-ROM), a read-only Blu-ray disc, an ultra-high density optical disc, a flash memory card (e.g., SD card, mini SD card, Micro-SD card, etc.), a magnetic floppy disk, etc. Computer-readable storage media do not contain carrier waves or transient electronic signals transmitted wirelessly or via wired connections.
[0142] The memory 1010 stores executable code, which, when processed by the processor 1020, can cause the controller 1020 to execute part or all of the methods described above.
[0143] Furthermore, the method according to this application can also be implemented as a computer program or computer program product, which includes computer program code instructions for performing some or all of the steps in the method described above.
[0144] Alternatively, this application may be implemented as a computer-readable storage medium (or a non-transitory machine-readable storage medium or a machine-readable storage medium) storing executable code (or computer program or computer instruction code) thereon, which, when executed by a processor of an electronic device (or server, etc.), causes the processor to perform part or all of the steps of the methods described above according to this application.
[0145] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.
Claims
1. A method of data calibration for a sample analysis system, the method comprising: include: Obtain the sample measurements of multiple test samples and the corresponding theoretical values of the sample measurements; In response to an automatic calibration command, determine the automatic calibration parameters corresponding to the automatic calibration command; At least one calibration point is selected according to the preset calibration configuration rules, and the sample measurement value corresponding to the calibration point is corrected using the automatic calibration parameters to obtain the sample correction value. The sample measurements are calibrated based on the sample correction value and the theoretical value, and the calibrated sample measurements are output.
2. The method of claim 1, wherein, The preset calibration configuration rules include calibration point selection intervals and calibration point selection locations. Selecting at least one calibration point according to the preset calibration configuration rules includes: Obtain the theoretical value range of the tested sample; The theoretical values within the theoretical value range are sorted and numbered in ascending order to obtain a list of theoretical values, with each theoretical value corresponding to a theoretical value point. At least one calibration point is selected from multiple theoretical value points according to the calibration point selection interval and the calibration point selection position.
3. The method of claim 1, wherein, The automatic calibration parameters include a computational quantity of K. The step of correcting the sample measurements corresponding to the calibration point using the automatic calibration parameters to obtain a corrected sample value includes: Using the calibration point as a reference point, calculate the mean deviation of the measured values of the K samples before and after the calibration point; The average deviation is used as the deviation value of the calibration point; The sample measurements are corrected using the deviation and theoretical values of the calibration points to obtain the corrected sample values.
4. The method of claim 3, wherein, The automatic calibration parameters also include a preset threshold, and the mean deviation of the measured values of the K samples before and after calculation includes: Calculate the percentage deviation of the K sample measurements before and after the calibration point; The sample measurements whose percentage deviation exceeds the preset threshold are identified as outliers; After removing the outliers, the mean of the percentage deviations of the remaining sample measurements is calculated to obtain the mean deviation.
5. The method according to any one of claims 2-4, characterized in that, The step of calibrating the sample measurement based on the sample correction value and the theoretical value, and outputting the calibrated sample measurement, includes: The sample correction values and theoretical values of the calibration points are fitted together to obtain a function model; The sample measurements are input into the function model, and the calibrated sample measurements are output.
6. The method according to claim 1, characterized in that, The automatic calibration command is a command triggered in a preset manner and is used to initialize the automatic calibration parameters.
7. The method according to claim 1, characterized in that, The method further includes: In response to an image display instruction, determine image display parameters corresponding to the image display instruction, wherein the image display parameters include at least image coordinates, consistency limits, and data display type; A calibration statistical image is generated using the image coordinates, the consistency limit, and the data display type. The calibration statistical image is used to display the image before and after consistency.
8. A sample analysis system, characterized in that, Includes a sample detection module and a controller; The sample detection module is used to acquire sample measurement values of multiple test samples and send the sample measurement values to the controller; The controller is used to obtain the theoretical value corresponding to the sample measurement value; In response to an automatic calibration command, determine the automatic calibration parameters corresponding to the automatic calibration command; At least one calibration point is selected according to the preset calibration configuration rules, and the sample measurement value corresponding to the calibration point is corrected using the automatic calibration parameters to obtain the sample correction value. The sample measurements are calibrated based on the sample correction value and the theoretical value, and the calibrated sample measurements are output.
9. A computer-readable storage medium having executable code stored thereon, which, when executed by a controller of a sample analysis system, causes the controller to perform the method as described in any one of claims 1-7.
10. A sample analyzer, characterized in that, Includes the computer-readable storage medium as described in claim 9.