JP2023131197A - Accuracy management method, accuracy management device and program - Google Patents

Abstract

To provide an accuracy management method, an accuracy management device, and a program that can appropriately perform accuracy management of samples according to processing conditions for smear and staining adopted by each facility.SOLUTION: An accuracy management method for samples prepared from specimens, includes: setting at least one index used for accuracy management of a sample from management index information (MII) in which multiple indices related to the samples are associated with management values corresponding to each of the multiple indices (S1); obtaining a feature value related to at least one index from image data of the sample (S3); and outputting accuracy management information of the sample based on the feature value and the management value associated with at least one index (S5).SELECTED DRAWING: Figure 1

Description

The present invention relates to a quality control method, a quality control device, and a program.

A method is known in which quality control of a specimen preparation device is performed based on the staining state of a specimen. For example, Patent Document 1 discloses that using a specific color component of a nuclear region in a blood cell image of a smear sample as an index, the brightness value of the specific color component is compared with a predetermined lower limit reference value and a predetermined upper limit reference value, A system is described that notifies the occurrence of staining abnormality when the luminance value is less than or equal to a predetermined lower limit reference value or greater than or equal to a predetermined upper limit reference value.

Japanese Patent Application Publication No. 2010-169484

The smearing/staining processing conditions for a smear specimen include the reagents, equipment, and conditions of each step (e.g., smear conditions, pH of the staining solution, temperature of the staining solution, and staining time) used to prepare the smear specimen. , which can affect the staining status of the smear. However, smearing and staining processing conditions for smear specimens may vary depending on the testing facility, region or country, or depending on the reagents and equipment used. Among these smearing/staining processing conditions for a plurality of smear specimens, there are smearing/staining processing conditions for which the quality control of the specimen cannot be appropriately performed using the index described in Patent Document 1.

An object of the present invention is to provide a quality control method, a quality control device, and a program that can appropriately control the quality of specimens according to the smear/staining processing conditions adopted by each facility.

As shown in FIGS. 2 and 6, the quality control method of the present invention is a quality control method for specimens prepared from specimens, and includes a plurality of indicators regarding the specimen and control values corresponding to each of the plurality of indicators. At least one index used for quality control of the specimen is set from the management index information (MII) associated with the sample (S1), and a feature value regarding at least one index is acquired from the image data of the specimen (S3). , the quality control information of the sample is output based on the feature value and the control value associated with at least one index (S5).

According to the quality control method of the present invention, at least one index used for quality control of the specimen is set from the management index information (MII), a feature value regarding the at least one index is acquired from the image data of the specimen, Quality control information of the sample is output based on the feature value and the control value associated with at least one index. Therefore, with the quality control method of the present invention, it is possible to appropriately control the quality of specimens based on the smear and staining processing conditions adopted by each facility.

As shown in FIGS. 1, 2, and 6, the quality control device (1) of the present invention is a quality control system that performs quality control of specimens prepared from specimens, and includes a control unit (50), The control unit (50) selects at least one index used for quality control of the specimen from management index information (MII) in which a plurality of indices regarding the specimen are associated with management values corresponding to each of the plurality of indices. set, obtain a feature value related to at least one index from image data of the specimen, and output accuracy control information of the specimen based on the feature value and a control value associated with the at least one index. Features.

According to the quality control device (1) of the present invention, the control unit (50) sets at least one index used for quality control of the specimen from the management index information (MII), and sets at least one index from the image data of the specimen. Obtain feature values regarding one index. The control unit (50) outputs quality control information of the sample based on the feature value and the control value associated with at least one index. Therefore, with the quality control system of the present invention, it is possible to appropriately manage the quality of specimens based on the smear and staining processing conditions adopted by each facility.

As shown in FIGS. 1, 2, and 6, the program of the present invention provides a quality control device (1) that performs quality control of a specimen prepared from a specimen with a plurality of indicators related to the specimen and each of the plurality of indicators. At least one index used for quality control of the specimen is set (S1) from management index information (MII) associated with a management value corresponding to the A program for executing the following steps: acquiring a feature value (S3), and outputting quality control information of a specimen (S5) based on the feature value and a control value associated with at least one index. .

According to the program of the present invention, at least one index used for quality control of a specimen is set from management index information (MII), a feature value regarding at least one index is acquired from image data of the specimen, and a feature value and a control value associated with at least one index, the quality control information of the sample is output. Therefore, with the program of the present invention, it is possible to appropriately control the quality of specimens based on the smearing and staining processing conditions adopted by each facility.

According to the present invention, it is possible to appropriately control the quality of specimens based on the smearing and staining processing conditions adopted by each facility.

FIG. 1 is a schematic diagram showing an overview of the quality control system. FIG. 2 is a block diagram showing an example of the configuration of the quality control device. FIG. 3(A) is a diagram showing an overview of management index information. FIG. 3(B) is a diagram showing an overview of setting index information. FIG. 4 is a diagram showing an overview of feature value acquisition processing. FIG. 5 is a diagram showing an outline of the quality control information output screen. FIG. 6 is a flowchart illustrating an example of output control processing of sample quality control information. FIG. 7 is a flowchart showing a first example of index setting processing. FIG. 8 is a diagram showing an example of a setting screen selected by the user in the first example of the index setting process. FIG. 9 is a diagram illustrating an example of a setting screen for file selection in the first example of index setting processing. FIG. 10 is a flowchart showing a second example of index setting processing. FIG. 11 is a diagram illustrating an example of processing using Region ID in the second example of index setting processing. FIG. 12 is a diagram illustrating an example of processing using Guideline ID in the second example of index setting processing. FIG. 13 is a diagram illustrating another example of the process in the second example of the index setting process. FIG. 14 is a diagram illustrating an example of a setting screen in the second example of the index setting process. FIG. 15 is a diagram illustrating an example of a process using a Vender Recommend ID in a second example of the index setting process. FIG. 16 is a diagram illustrating an example of a process using the manufacturing condition ID in the second example of the index setting process. FIG. 17 is a diagram illustrating an example of a setting screen for condition selection in the second example of the index setting process. FIG. 18 is a flowchart showing a third example of index setting processing. FIG. 19 is a diagram illustrating an example of information processing of the management center and the inspection system in the third example of the index setting process. FIG. 20 is a flowchart showing the process of acquiring feature values that reflect the staining state of the smear specimen to be managed. FIG. 21 is a flowchart illustrating an example of feature value acquisition processing. FIG. 22 is a diagram illustrating an example of feature value acquisition processing. FIG. 23 is a diagram illustrating an example of feature values that reflect the stainability of red blood cells. FIG. 24 is an example of a process for obtaining an average value of brightness values of red components of red blood cells. FIG. 25 is a diagram illustrating an example of characteristic values that reflect the stainability of white blood cells. FIG. 26 is a diagram illustrating an example of feature values that reflect the morphology of blood cells. FIG. 27 is a flowchart illustrating an example of a granule index acquisition process. FIG. 28 is a diagram illustrating an example of a granule index acquisition process. FIG. 29 is a diagram showing an example of an extraction process for primary granules and secondary granules. FIG. 30 is a diagram showing an example of an output screen of feature values and quality control information that reflect the staining state of the smear specimen to be managed. FIG. 31 is a diagram showing an example of an output screen of feature values and quality control information that reflect the staining state of the smear specimen to be managed. FIG. 32 is a diagram showing an example of an output screen of feature values and quality control information that reflect the staining state of the smear specimen to be managed. FIG. 33 is a diagram illustrating an example of a screen displaying a plurality of image data acquired from a smear sample. FIG. 34 is a diagram illustrating an example of a screen that displays specific image data and a plurality of feature values associated with the specific image data in association with each other. FIG. 35 is a diagram showing an example of a screen from which feature values to be acquired can be selected. FIG. 36 is a diagram showing an example of a screen on which a normal range can be set for any characteristic value.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. Note that the same elements are given the same reference numerals and redundant explanations will be omitted. In addition, the positional relationships such as top, bottom, left, and right are based on the positional relationships shown in the drawings unless otherwise specified. Furthermore, the dimensional ratios in the drawings are not limited to the illustrated ratios. Further, the following embodiments are illustrative for explaining the present invention, and the present invention is not limited to these embodiments.

[Overview of quality control system]
With reference to FIGS. 1 and 2, an overview of a quality control system 100 that outputs quality control information of a blood smear sample collected from a subject will be described. FIG. 1 is a schematic diagram showing an overview of the quality control system 100.

The quality control system 100 includes a plurality of inspection systems 70-1 to 70-4 including a smear preparation device 20, a specimen transport device 30, and a specimen image capturing device 40, a quality control device 1 that outputs quality control information, Equipped with

The inspection systems 70-1 to 70-4 prepare a smear slide 10 using the smear preparation device 20, and transport the prepared smear slide 10 to the specimen image capturing device 40 using the specimen transport device 30. This system images a smear specimen slide 10 using a specimen image capturing device 40, acquires image data of the smear specimen, and transmits the image data to the quality control device 1. The testing systems 70-1 to 70-4 are installed in multiple testing facilities (testing facilities A to D). The plurality of testing facilities (testing facilities A to D) have different smear and staining conditions when preparing smear specimens. The quality control device 1 is installed at the facility of the provider of the specimen image capturing device 40 (for example, the manufacturer of the specimen image capturing device 40), and performs smear sample preparation for the inspection systems 70-1 to 70-4 via a network. It is connected to the apparatus 20, the specimen transport device 30, and the specimen image capturing device 40.

FIG. 2 is a block diagram showing an example of the configuration of the quality control device 1. As shown in FIG. As shown in FIG. 2, quality control device 80 includes a control section 50, a storage section 80, an input section 90, a display section 60, and a communication section 77.

The control unit 50 exemplarily includes a CPU that executes information processing for outputting smear quality control information. Further, the control unit 50 can communicate with the smear preparation device 20, specimen transport device 30, and specimen image capturing device 40 shown in FIG. 1 via the communication unit 77. The storage unit 80 exemplarily includes a memory that stores information for executing information processing by the control unit 50 and information generated by executing the information processing. The input unit 90 is, for example, a keyboard or a mouse, and the display unit 60 is, for example, a liquid crystal display or an organic EL display.

The storage unit 80 stores, for example, management index information MII, reference information CI, setting index information SII, and accuracy management information AMI. “Standard information CI” is information regarding a predetermined standard for setting indicators used in quality control. The predetermined standards include, for example, guidelines regarding specimen quality control that are established according to a predetermined country, region, or organization. The predetermined criteria include criteria for setting an index determined according to the conditions for preparing the smear specimen.

The storage unit 80 includes management index information MII in which a plurality of indicators related to the smear sample are associated with management values corresponding to each of the plurality of indicators, and setting index information SII indicating an index used for quality control of the smear sample. is memorized. The quality control device 1 sets at least one index suitable for quality control as set index information SII from the plurality of indicators of the management index information MII stored in the storage unit 80 for each of the testing facilities A to D. The quality control device 1 receives image data of a smear specimen from the specimen image capturing device 40 via the network. The quality control device 1 acquires feature values related to set indicators from the received image data, and outputs smear quality control information AMI based on the obtained feature values and control values associated with the set indicators. do.

Referring to FIGS. 3(A) and 3(B), management index information MII in which a plurality of indicators related to a smear sample and a control value corresponding to each of the plurality of indicators are associated with each other and is used for quality control of the smear sample. The set index information SII indicating the index will be explained.

FIG. 3(A) is a diagram showing an overview of the management index information MII stored in the storage unit 80 shown in FIG. 2. As shown in FIG. 3(A), the management index information MII includes a plurality of indices related to the smear sample and a management value (for example, a lower limit value, an upper limit value, and a target value) corresponding to each of the plurality of indices. This is a database created by The plurality of indicators related to the smear specimen are management items that reflect the staining state of the smear specimen and the morphology of specific cells in the smear specimen slide 10. The plurality of indicators regarding the smear include, for example, at least one of color information and morphological information of blood cells in blood. In the management index information MII, the indicators are RBC Color R (brightness value of the red component of red blood cells), RBC Color G (brightness value of the green component of red blood cells), RBC Color B (brightness value of the blue component of red blood cells), and RBC Color. H (hue value of red blood cells), RBC Color S (saturation value of red components of red blood cells), RBC Color V (brightness value of red components of red blood cells), RBC Redness Index (redness index of red blood cells), Granule Index (saturation value of red components of red blood cells) granule index), Diameter (cell diameter of blood cells), Nuclear Diameter (nuclear diameter of blood cells), etc. are stored.

FIG. 3(B) is a diagram showing an overview of the setting index information SII stored in the storage unit 80 shown in FIG. 2. As shown in FIG. 3(B), the set index information SII is a database in which indexes used for quality control of smear specimens are stored. In the setting index information SII, indicators corresponding to the indicators in the management index information MII are associated with settings indicating whether or not each index is used for quality control. For example, in the setting index information SII of testing facility A, the index "RBC Redness Index" is set as the index to be used. Furthermore, in the set index information SII of testing facility B, the index "RBC Redness Index," the index "Granule Index," and the index "Diameter" are set as the indexes to be used. Similarly, setting index information SII is stored in the storage unit 80 for the testing facilities C to D.

With reference to FIGS. 4 and 5, a process for acquiring feature values of a smear sample to be managed and a process for outputting quality control information will be described.

FIG. 4 is a diagram illustrating an overview of a process for acquiring feature values of a smear sample to be managed.

As shown in FIG. 4, the quality control device 1 acquires the characteristic value Y of the smear to be managed regarding the index set as the set index information SII shown in FIG. 3(B). For example, image data reflecting the area of blood cells in the blood is acquired from Sample), and a feature value Y reflecting the staining state of the smear to be managed is acquired from the acquired image data. The feature value Y that reflects the staining state of the smear to be managed is obtained, for example, from the image data of at least one smear out of all the smears imaged on that day.

FIG. 5 is a diagram showing an outline of the quality control information output screen. The accuracy management information AMI outputs the indicators set in the set index information SII, but does not output the indicators not set in the set index information SII. The example shown in FIG. 5 is based on the control value associated with the index I set in the set index information SII of one laboratory (test facility A) and the characteristic value Y regarding the index I. This is an example of outputting quality control information AMI. For example, the accuracy management information AMI is a diagram (for example, a chart or a graph) that comparably shows the management value associated with the index I and the feature value Y, or notification information (for example, an alert). In the example shown in FIG. 5, the control value associated with the index I set as the set index information SII of one laboratory (test facility A) and the staining state of the smear specimen to be managed regarding the index I are reflected. This is a chart that outputs the characteristic value Y. The control value associated with the index I is generated, for example, every day from the image data of all the smears imaged on that day.

As shown in Fig. 5, the control value associated with the index I set as the set index information SII of one testing facility (testing facility A) and the staining state of the smear specimen to be managed regarding the index I are reflected. A plurality of plots P corresponding to the feature value Y are output. As the management values, for example, a target value ACI corresponding to the index I and a management width MW corresponding to the index I are output. By visually understanding the relationship between the target value ACI and the control width MW, which are control values, and the output plot P, the user can easily perform accuracy control on the smear specimen to be managed. For example, for the target value ACI and the control width MW, which are the control values associated with the index I set as the set index information SII of one laboratory (laboratory facility A), the smear sample to be managed regarding the index I By outputting the plot P corresponding to the feature value Y of , the laboratory technician at the laboratory A can perform accuracy control on the smear specimen to be managed. Here, the horizontal axis ("Sample") in the output chart shows the smear that is the subject of management. For example, the smear of Sample 2 and the smear of Sample 4 are different. shows. The vertical axis indicates the characteristic value that reflects the staining state of the smear specimen to be managed.

The management value stored in the management index information MII is a median value or average value set corresponding to each of a plurality of indices. Further, the control value includes at least one of an upper limit value and a lower limit value that are, for example, ±2SD (Standard Deviation) or ±3SD with respect to the median value or the average value. As the management value, in addition to a median value or an average value, for example, a value based on a moving average may be used. Moreover, the control value may be only a median value or an average value.

The process of generating the management values stored in the management index information MII involves acquiring image data that reflects each area of blood cells in the blood from each of a plurality of smears, and generating a smear from each of the plurality of image data. By acquiring feature values that reflect the staining state of the specimen, a control value is generated using a control range based on, for example, a target value, an upper limit value, and a lower limit value. The target value is calculated from the average value of the plurality of acquired characteristic values, and the upper and lower limit values of the control range are calculated from ±2SD (Standard Deviation) with respect to the target value.

The feature value is numerical information that reflects the staining state of the smear in image data that reflects the area of blood cells in blood. In addition, the feature value includes, for example, color information of red blood cells, and the color index of the intracellular region is acquired for each cell from each of the multiple image data, and the staining state in each smear of the multiple image data is quantitatively determined. It is quantified into .

The quality management information AMI is, for example, information in which an index related to a smear specimen, a management value corresponding to the index, and a characteristic value related to the index acquired from image data are associated.

By outputting the quality control information AMI, it is possible to compare the control value and the characteristic value for the set index and understand, for example, whether there is a problem with the staining state of the smear specimen to be managed. I can do it. In such a case, it is possible to ensure the quality of the smear specimen to be managed based on the quality control information AMI.

The timing for outputting the quality control information AMI is arbitrary, and may be, for example, every day, every few days, every week, every month, or every few hours.

The subject is primarily a human, but may also be a non-human animal. The quality control system 100 performs, for example, analysis of specimens collected from patients for clinical testing or medical research. The specimen is a specimen derived from a living body. Specimens derived from living organisms include, for example, liquids such as blood (whole blood, serum, or plasma), urine, or other body fluids collected from a subject, or samples obtained by subjecting the collected body fluids or blood to specified pretreatments. liquid obtained by Further, the specimen may be, for example, a part of the subject's tissue or cells other than liquid.

The smear preparation device 20 is a device that performs a smear process of smearing a specimen onto a slide, and performs a specimen staining process on the smear specimen slide 10 on which the specimen has been smeared. The smear preparation device 20 aspirates a sample as a specimen, drops it onto a slide, smears it, and stains it to prepare a smear slide 10.

The specimen transport device 30 receives the smear slide 10 produced by the smear specimen preparation device 20 and transports it to the specimen image capturing device 40 . Further, the specimen transport device 30 receives the smear specimen slide 10 imaged by the specimen image imaging device 40 and stores it.

The specimen image capturing device 40 captures an image of the smear specimen slide 10 transported by the specimen transporting device 30.

Note that the inspection systems 70-1 to 70-4 may include other devices. For example, the testing systems 70-1 to 70-4 include an analyzer that analyzes a specimen (for example, a blood cell counting tester that classifies and counts blood cells in a specimen), and a transport system that transports a container containing a specimen. It may also include a device.

Note that the inspection system 70 including the smear preparation device 20, the specimen transport device 30, and the specimen image capturing device 40 is described in, for example, US Patent Application Publication No. 2019/0049474. US Patent Application Publication No. 2019/0049474 is herein incorporated by reference.

FIG. 6 is a flowchart illustrating an example of output control processing of smear quality control information. As shown in FIG. 6, the control unit 50 of the quality control device 1 shown in FIG. Step S1). The control unit 50 acquires a feature value regarding at least one index from the image data of the smear sample (step S3). The control unit 50 outputs the quality control information AMI of the smear specimen to the display unit 60 based on the feature value and the management value associated with at least one index (step S5). A specific example of step S1 related to the index setting process will be described below.

<First example of index setting process>
In the first example of the index setting process, the control unit 50 of the quality management device 1 sets the index based on the user's input via the input unit 90. FIG. 7 is a flowchart showing a first example of index setting processing. The control unit 50 acquires management index information MII from the storage unit 80 shown in FIG. 2 (step S11). The control unit 50 receives user input via the input unit 90 (step S13). The control unit 50 sets at least one index used for quality control of the smear sample based on user input via the input unit 90 (step S15). In the first example of the index setting process, the index and management value used for quality control are, for example, input by the user via the input section 90 from a plurality of indexes included in the management index information MII stored in the storage section 80. Set by selection. An example of a setting screen in the first example of the index setting process will be described with reference to FIGS. 8 and 9.

FIG. 8 is a diagram showing an example of a setting screen selected by the user in the first example of the index setting process. As shown in FIG. 8, the user arbitrarily selects an index (for example, "RBC Color G") from among the plurality of indexes included in the management index information MII, and the selected index is set. For example, when a user selects an index for management values including a lower limit value, an upper limit value, and a target value, each value corresponding to the selected index is automatically extracted from the management index information MII. Note that each extracted management value may be set to be changeable by the user. When the setting button B1 is selected by the user, an index used for quality control and a management value corresponding to the index are recorded as setting index information SII shown in FIG. 2.

FIG. 9 is a diagram illustrating an example of a setting screen for file selection in the first example of index setting processing. First, created index file data (for example, a CSV file) is displayed in a selectable manner on the screen. The index file data includes information in which at least one index used in quality control is associated with a management value corresponding to the index based on the management index information MII. As shown in FIG. 9, when the user selects a specific index file (for example, "File 02") and presses the setting button B3, the selected index file data is imported and the information contained in the index file data is Based on this, setting index information SII is set.

<Second example of index setting process>
In the second example of the index setting process, the control unit 50 of the quality management device 1 sets the index based on the reference information CI. FIG. 10 is a flowchart showing a second example of index setting processing. The control unit 50 acquires management index information MII from the storage unit 80 shown in FIG. 2 (step S21). The control unit 50 acquires reference information CI regarding quality control of the smear sample from the storage unit 80 based on the user's input via the input unit 90 (step S23). The control unit 50 sets at least one index used for quality control of the smear sample based on user input via the input unit 90 (step S25).

With reference to FIGS. 11 to 14, set indicators to be used for quality control from the management index information MII based on guidelines for quality control of smear specimens established according to a given country, region, or organization. Explain the method. In this method, each index and management value included in the management index information MII is applied according to area type information such as the country or region where the testing facility is located or the organization to which it belongs, as well as the location and affiliation of the testing facility. is associated with at least one of the guideline type information.

FIG. 11 is a diagram illustrating an example of processing using Region ID in the second example of index setting processing. Region ID is an example of region type information such as the country or region where the testing facility is located, or the organization to which it belongs. As shown in FIG. 11, in the control unit 50 of the quality control device 1, the region ID "CN" indicating China is specified by the user via the input unit 90 shown in FIG. 2, for example. Then, the control unit 50 extracts one or more indicators associated with the Region ID “CN” and the management value associated with the indicator from the management index information MII stored in the storage unit 80. and set as the setting index information SII. Note that each area type information and the indicators included in the management indicator information MII are associated based on guideline information defined by each country, region, or organization.

FIG. 12 is a diagram illustrating an example of processing using Guideline ID in the second example of index setting processing. The Guideline ID is an example of guideline type information that is applied depending on the location and affiliation of the testing facility. As shown in FIG. 12, in the control unit 50 of the quality control device 1, the user specifies, for example, a Guideline ID “G02” indicating a Chinese guideline via the input unit 90. Then, the control unit 50 extracts one or more indicators associated with the Guideline ID “G02” and the management value associated with the indicator from the management indicator information MII stored in the storage unit 80. and set as the setting index information SII. Note that each guideline type information and the indicators included in the management index information MII are associated based on guideline information defined by each country, region, or organization.

Note that in the examples of FIGS. 11 and 12, different management values may be set depending on the area type information or the guideline type information even for the same type of index. For example, the index "RBC Color R" in FIGS. 11 and 12 corresponds to "RBC Color R 01," "RBC Color R 02," "RBC Color R 03," etc., depending on the area type information or guideline type information. The assigned upper limit value, lower limit value, and target value may be set to different values.

Further, FIG. 13 shows an example of setting the index and management value corresponding to the Region ID "CN" indicating China. As shown in FIG. 13, different types of indicators may be set as indicators used for quality control depending on area type information or guideline type information. FIG. 13 is an example in which different types of indicators are set depending on area type information. For example, the type of index associated with Japan's Region ID "JP" (RBC Color S, RBC Redness Index, NEUT Granule Index, NEUT Cell Diameter), and the type of index associated with China's Region ID "CN" (RBC Color S, RBC Redness Index, NEUT Granule Index, NEUT Cell Diameter). RBC RGB, RBC Redness Index, NEUT Nucler Color G, NEUT N/C). Then, when the Region ID "CN" indicating China is specified, the index associated with "CN" and the management value associated with the index are extracted and set as the set index information SII.

FIG. 14 is a diagram illustrating an example of a setting screen in the second example of the index setting process. First, on the screen, a plurality of Region IDs, such as "JP", "US", or "CN", are displayed in a pull-down format so that they can be selected. As shown in FIG. 14, when the user selects a Region ID (for example, "CN") and presses the setting button B5, one or more indicators associated with the Region ID "CN" are selected from the management index information MII. , and the management value associated with the index are extracted and set as set index information SII. Information on the set indicators and management values is displayed in the settings list.

Next, with reference to FIG. 15, a method of setting an index used in quality control from the management index information MII will be described based on a predetermined standard determined according to the smear preparation conditions. The predetermined standards according to the specimen preparation conditions are information that defines the indicators used for quality control and their control values according to the type of reagent and/or type of specimen preparation device used for specimen preparation. be. Such information can be provided to the user as information on recommended quality control conditions, for example, from a provider of reagents and devices used for specimen preparation, or a provider of analysis and quality control software. In this method, each index and control value included in the management index information MII is combined with information regarding the type of reagent used for specimen preparation and/or the type of specimen preparation device (Vender Recommend ID), and the reagent for specimen preparation. and/or associated with at least one of information regarding the type of manufacturing condition (manufacturing condition ID) assigned depending on the device.

Here, the "type of reagent" (for example, "reagent A") is information regarding, for example, a staining solution, a buffer solution, or a combination thereof. The staining state of a smear specimen is an important parameter, especially since it is affected by pH. “Type of smear preparation device” is, for example, information regarding the type of smear preparation device or setting information. The staining condition of a specimen is particularly influenced by staining conditions and staining time, and the cell diameter is particularly influenced by drying conditions (for example, forced drying or natural drying).

FIG. 15 is a diagram illustrating an example of a process using information (Vender Recommend ID) regarding the type of reagent and/or type of specimen preparation device used for preparing a smear sample in the second example of the index setting process. As shown in FIG. 15, in the control unit 50 of the quality control device 1, a plurality of Vender Recommend IDs, such as “Reagent A/SP-10” and “Reagent B/SP-10” are input by the user via the input unit 90. A specific Vender Recommend ID “Reagent B/SP-10” is specified from “Reagent A/SP-50” and the like. Then, the control unit 50 associates one or more indicators associated with the Vender Recommend ID ID “Reagent B/SP-10” with the indicator from the management indicator information MII stored in the storage unit 80. The managed value is extracted and set as the setting index information SII. Note that the Vender Recommend ID and the index included in the management index information MII are associated based on a predetermined standard determined according to the preparation conditions of the specimen.

Next, with reference to FIG. 16, a method of setting an index used in quality control from management index information based on a predetermined standard determined according to smear preparation conditions will be described.

FIG. 16 is a diagram illustrating an example of a process using production condition type information (preparation condition ID) assigned depending on the specimen preparation reagent and/or apparatus in the second example of the index setting process. As shown in FIG. 16, in the control unit 50, the user inputs the production condition ID through the input unit 90, for example, "Production condition ID of reagent A/SP-10: C01", "Production condition ID of reagent B/SP-10". A specific production condition ID "C02" is specified from "condition ID: C02" and "production condition ID of reagent A/SP-50: C10". Then, the control unit 50 extracts one or more indicators associated with the manufacturing condition ID “C02” and the management value associated with the indicator from the management indicator information MII stored in the storage unit 80. and set as the setting index information SII. Note that the manufacturing condition ID and the index included in the management index information MII are associated based on a predetermined standard determined according to the specimen manufacturing condition.

FIG. 17 is a diagram illustrating an example of a setting screen for condition selection in the second example of the index setting process. First, on the screen, multiple Vender Recommend IDs, such as "Reagent A/SP-10," "Reagent B/SP-10," and "Reagent A/SP-50," are displayed in a pull-down format for selection. . As shown in FIG. 17, when the user selects the Vender Recommend ID (for example, "Reagent B/SP-10") and presses the setting button B7, the Vender Recommend ID "Reagent B/SP-10" is selected from the management index information MII. 10'' and the management value associated with the index are extracted and set as set index information SII.

Note that on the settings screen, conditions different from the Vender Recommend ID are displayed for selection, and one or more indicators associated with the selected condition and the management value associated with the indicator are extracted. may be set as the setting index information SII. "Different conditions" include, for example, information regarding the production condition ID, the pH of the staining solution, the buffer, or the staining time. Further, a plurality of selection columns may be displayed on the setting screen so that these plurality of conditions can be selected individually.

Note that even if the indicators used for quality control are of the same type, different management values may be set depending on the Vender Recommend ID or the manufacturing condition ID. For example, the index “RBC Color R” in FIGS. 16 and 17 corresponds to “RBC Color R 01,” “RBC Color R 02,” “RBC Color R 03,” etc., depending on the Vender Recommend ID or production condition ID. The assigned upper limit value, lower limit value, and target value may be set to different values. Furthermore, different types of indicators may be set for each indicator depending on the Vender Recommend ID or the production condition ID. For example, the type of index (RBC Color S, RBC Redness Index, NEUT Granule Index, NEUT Cell Diameter) associated with the Vender Recommend ID "Reagent A/SP-10" and the Vender Reco mmend ID “Reagent B/SP-10 ” is different from the index type (RBC RGB, RBC Redness Index, NEUT Nucler Color G, NEUT N/C) by at least one. Then, when the Region ID "Reagent B/SP-10" is specified, the index associated with "Reagent B/SP-10" and the management value associated with the index are extracted, and the set index is It is set as information SII.

<Third example of index setting process>
In the third example of the index setting process, one or more inspection systems set the index based on index-related information including information on the index and management value used for quality control, which is transmitted from the management center (server). FIG. 18 is a flowchart showing a third example of index setting processing. FIG. 19 is a diagram illustrating an example of information processing of the management center and the inspection system in the third example of the index setting process.

As shown in FIGS. 18 and 19, the control unit 50 of the quality control device 1 requests the management center 110 that manages the management index information MII to transmit information (step S31 in FIG. 18/"(" shown in FIG. 19). 1) Request”). The management center 110 distributes information to the control unit 50. The control unit 50 acquires information from the management center 110 (step S33 in FIG. 18/"(2) Distribution" shown in FIG. 19). The control unit 50 sets or updates at least one index used for quality control of the smear sample based on the information from the management center 110, and records it as set index information SII (step S35 in FIG. 18/shown in FIG. 19). “(3) Record/update”).

In response to a request from the control unit 50 of the quality control device 1, the information transmitted from the control center 110 includes, for example, at least part of the management index information MII including the indices and management values corresponding to the testing facilities A to D. May include. Further, the information transmitted from the management center 110 may include information including predetermined standards regarding specimen preparation conditions. In addition, the management center 110 automatically distributes at least part of the management index information MII including the indicators and management values corresponding to the testing facilities A to D, based on the information of the testing facilities A to D, regardless of whether there is a request or not. You may. For example, information on testing facilities A to D may include predetermined standards regarding smear preparation conditions adopted within each testing facility, or the types of reagents and/or specimen preparation equipment used for smear preparation. Contains information regarding predetermined standards determined depending on the type.

The management center 110 is a facility that includes one or more servers or information processing devices. The management center 110 may be, for example, a facility of a vendor that provides software for analysis and quality control, or may be a central facility of a facility group in which a plurality of testing facilities cooperate. The management center 110 may be a cloud system that can be connected to any of the above facilities via a predetermined communication network.

Note that in the example of FIG. 19, one management center 110 is arranged in the management system 200, but the number of management centers is not limited to this and may be arbitrary. Furthermore, in the management system 200, the number of testing facilities A to D is also arbitrary.

<Feature value acquisition process>

FIG. 20 is a flowchart showing a process for acquiring feature values that reflect the staining state of the smear specimen to be managed.

As shown in FIG. 20, the control unit 50 of the quality control device 1 shown in FIG. 2 acquires a plurality of image data to be managed (step S1). The control unit 50 acquires feature values from a plurality of image data to be managed (step S2). Get the value.

FIG. 21 is a flowchart showing the feature value acquisition process in step S2 of FIG. As shown in FIG. 21, the control unit 50 shown in FIG. 5 recognizes each cell component based on the plurality of acquired image data IDs (step S11). Next, the control unit 50 specifies and extracts each region of each cell including the nucleus and cytoplasm based on the recognition result in step S11 (step S12). The control unit 50 acquires color information (feature value reflecting the staining state of the smear specimen) of blood cells in each extracted region for each of the plurality of image data IDs (step S13).

FIG. 22 is a diagram showing details of the image data acquisition process and feature value acquisition process for the smear sample to be managed. As shown in FIG. 22, the control unit 50 shown in FIG. 2 acquires, for example, hundreds or thousands of image data IDs from each of the plurality of smears. More specifically, the control unit 50 acquires a plurality of image data IDs acquired by imaging by the specimen image capturing devices 40 of the inspection systems 70-1 to 70-4 shown in FIG.

The control unit 50 acquires a feature value that reflects the staining state of the smear sample from each of the plurality of image data IDs. As shown in FIG. 22, the control unit 50 performs feature value acquisition processing to (1) recognize cell components, (2) extract nuclear/cytoplasmic regions, and (3) provide blood cell color information for each image data. Execute the acquisition.

More specifically, as processing (1), the control unit 50 recognizes each cell component based on the plurality of acquired image data IDs. Next, as process (2), the control unit 50 identifies and extracts each region of each cell, including, for example, the nucleus and cytoplasm, based on the recognition result of process (1). As processing (3), the control unit 50 extracts information on cell types (erythrocytes, white blood cells, platelets, etc.) and structural components (nuclei, cytoplasm, granules, etc.) in each extracted region for each of the plurality of image data IDs. The color information of the blood cells (feature value reflecting the staining state of the smear specimen) is obtained by associating the color information with the color information of the blood cells.

The feature value reflecting the staining state of the smear sample includes the above-mentioned color information acquired from each area of blood cells in the image data. "Feature values that reflect the staining state of a smear sample" include, for example, the brightness value, hue, saturation, and , a brightness (Value) value, and a value that is a combination of these values (eg, HSV value, RGB).

"Blood cells" include, for example, at least one of red blood cells, white blood cells, and platelets. White blood cells include, for example, at least one of basophils, eosinophils, neutrophils, monocytes, and lymphocytes.

Red blood cells account for about 90% of the blood cells contained in blood, and they occupy a large proportion (area) in a smear. Therefore, red blood cell color information can be information that reflects the staining state of the entire smear, and is therefore more preferable as a feature value that reflects the staining state of the smear. Red blood cell color information tends to reflect changes in staining status due to differences in staining conditions such as pH more easily than white blood cell color information. On the other hand, color information of white blood cells may be employed as the feature value reflecting the staining state of the smear sample. In this case, accuracy control may be performed using multiple types of characteristic values that reflect the staining state of the smear specimen, such as red blood cells and white blood cells. For example, by using at least one color information of red blood cells and at least one color information of white blood cells, the quality of the staining state of the entire smear specimen can be controlled, while the components of white blood cells that are important targets for analysis (for example, nuclei) can be controlled. or granules) can also be controlled.

FIG. 23 is a diagram illustrating an example of feature values that reflect the stainability of red blood cells. As shown in FIG. 23, the characteristic values reflecting the stainability of red blood cells include, for example, the average brightness value of each color component of red blood cells, the average value of hue values of red blood cells, the average value of chroma values of red blood cells, and the average value of red blood cell saturation values. It includes the average brightness value and the HSV value of red blood cells. Here, with reference to FIG. 24, an example of a process for acquiring an average value of brightness values of red components of red blood cells, which is an example of a feature value, will be described.

As shown in FIG. 24, the control unit 50 shown in FIG. 2 acquires a plurality of image data IDs generated by imaging one smear (sample). Next, the control unit 50 obtains the average value (redcell_r_mean) of red (R) in the red blood cell region for each of the plurality of obtained image data IDs. Then, the control unit 50 controls the average value (RBC Color R).

The feature values obtained from the image data include feature values corresponding to color information obtained from the structural components of white blood cells, such as the nucleus, cytoplasm, and granules. These reflect the stainability of structural components of leukocytes. A specific example of feature values obtained from white blood cells will be described with reference to FIG. 25.

FIG. 25 is a diagram illustrating an example of characteristic values that reflect the stainability of white blood cells. As shown in FIG. 25, the characteristic values reflecting the stainability of white blood cells include, for example, the average value of the brightness values of each color component in the cytoplasmic region of white blood cells, the average value of the hue values of the cytoplasmic region of white blood cells, and the average value of the hue values of the cytoplasmic region of white blood cells. It includes the average value of the saturation value and the average value of the brightness value of the cytoplasmic region of white blood cells. Feature values that reflect the stainability of white blood cells include, for example, the average value of the brightness values of each color component in the nuclear region of white blood cells, the average value of the hue values of the nuclear region of white blood cells, the average value of the saturation values of the nuclear region of white blood cells, It also includes the average brightness value of the nuclear region of white blood cells. Further, the characteristic values reflecting the stainability of white blood cells may include the standard deviation values regarding the brightness value, hue value, saturation value, and lightness value in the cytoplasmic region and nuclear region of the white blood cell. The characteristic value reflecting the stainability of leukocytes includes, for example, the average value of the granule index of leukocytes. Note that the feature values include feature values that reflect the morphology of blood cells.

Feature values obtained from blood cells in smear image data include feature values that reflect morphological information of blood cells, in addition to the above-mentioned "feature values that reflect the staining state of the smear sample."

FIG. 26 is a diagram illustrating an example of feature values that reflect the morphology of blood cells. As shown in FIG. 26, characteristic values that reflect the morphology of blood cells obtained from blood cells include, for example, the average value of the cell diameter of blood cells, the average value of the nuclear diameter of blood cells, the average value of the N/C ratio of blood cells, and the average value of the N/C ratio of blood cells. This includes the average value of the area of the cytoplasm, the average value of the circularity (roundness) of blood cells, and the average value of the circularity of the nucleus.

Here, an example of a process for acquiring a granule index (Granule_Index) regarding, for example, neutrophils among white blood cells, as an example of a feature value, will be described with reference to FIGS. 27 and 28.

FIG. 27 is a flowchart showing the feature value acquisition process in step S2 of FIG. 20, and is a flowchart showing an example of the granule index acquisition process. As shown in FIG. 27, the control unit 50 shown in FIG. 2 acquires image data that corresponds to the smear and includes, for example, white blood cells (step S21). The control unit 50 performs, for example, local binarization processing on the acquired image data to extract a cytoplasmic region (step S22). The control unit 50 extracts granules (step S23). Specifically, the control unit 50 identifies granules (for example, granules of several pixels or more) from the extracted cytoplasmic region based on a predetermined number of pixels. The control unit 50 acquires the granule size (area) and average brightness for each identified granule. The control unit 50 classifies the identified granules into primary granules and secondary granules by setting predetermined thresholds for each of the granule size and the difference between the average granule brightness and the average cytoplasm brightness.

Next, the control unit 50 calculates the area related to the granules (step S24). Specifically, the control unit 50 calculates the total number of primary granules and secondary granules in the granule region recognized as granules. The control unit 50 may calculate the total area of regions recognized as granules (total granule area) or the total granule area ratio of regions recognized as granules. The control unit 50 acquires at least one value of the calculated total number of granules in the granule region, total granule area, and total granule area ratio as a granule index (step S25).

Here, an example of a process for acquiring a granule index (Granule_Index) regarding, for example, neutrophils among white blood cells, as an example of a feature value, will be described with reference to FIG. 28. As shown in FIG. 28, (1) the control unit 50 shown in FIG. 2 acquires image data containing white blood cells that corresponds to the smear sample. (2) The control unit 50 performs, for example, local binarization processing on the acquired image data to extract a cytoplasmic region. Here, the "granule index" is a characteristic value that reflects the number of granules contained in white blood cells, and can be obtained based on the number or area of granule regions identified in the cytoplasmic region of white blood cells. The "granule region" can be identified as distinct from the cytoplasmic portion based on the binarized image data. By obtaining the granule index, it is possible to objectively and quantitatively show changes in granules in blood cells, so it is possible to objectively and quantitatively show changes in granules in blood cells. It may be useful for diagnosing and evaluating diseases that involve an increase or decrease in granules.

(3) The control unit 50 identifies granules (for example, granules of several pixels or more) from the extracted cytoplasmic region based on a predetermined number of pixels. The control unit 50 acquires the granule size (area) and average brightness for each identified granule. The control unit 50 sets predetermined threshold values for each of the granule size and the difference between the granule average brightness and the cytoplasm average brightness (for example, the difference between the average brightness of the cytoplasm excluding the granule part and the average brightness of the granules). The identified granules are classified into primary granules and secondary granules. Here, when the difference between the granule average brightness and the cytoplasm average brightness is 0 (zero), it indicates that the brightness is the same as that of the background part of the image data. Further, when the difference between the granule average brightness and the cytoplasm average brightness is large in the negative direction, it indicates that the granule portion is darker (darker) than the other portions. The granule classification process will be described in more detail with reference to FIG. 29.

FIG. 29 is a diagram showing an example of an extraction process for primary granules and secondary granules. For example, if the threshold value for the granule size of secondary granules is set to "10" pixels and the threshold value for the difference between the average granule brightness and the average cytoplasm brightness is set to "0", the control unit 50 controls the identified granules to The granules are classified into primary granules G1 contained in a region R1 surrounded by a broken line in the graph in FIG. 29, and secondary granules G2 contained in a region R2 different from region R1 in the graph in FIG. Note that each of the above threshold values can be arbitrarily set, for example, based on the resolution of the image data, and can be changed as appropriate. Further, the size of one pixel may be set as appropriate, and is, for example, approximately 0.01 μm ² .

Returning to FIG. 28, (4) the control unit 50 calculates the total number of primary granules and secondary granules in the granule area recognized as granules. The control unit 50 may calculate the total area of regions recognized as granules (total granule area) or the total granule area ratio of regions recognized as granules. Here, since there is a predetermined correlation between the total number of granules in the granule region, the total granule area, and the total granule area ratio, the feature value may be used in addition to or instead of the total number of granules in the granule region. Therefore, the total granule area and the total granule area ratio can be used. The total granule area ratio refers to, for example, the ratio of the granule area to the cytoplasm area. (5) The control unit 50 obtains at least one value of the calculated total number of granules in the granule region, total granule area, and total granule area ratio as a granule index.

<Example of output screen regarding quality control information>
FIG. 30 is a diagram showing an example of an output screen of feature values and quality control information that reflect the staining state of the smear specimen to be managed. FIG. 30 shows an output screen of feature values and quality control information that reflect the staining state of the smear specimen to be managed, and shows an example of the output screen as internal quality control. The quality control device 1 shown in FIG. 1 acquires a plurality of feature values from each of a plurality of smears prepared in one testing facility, and outputs quality control information determined based on the feature values. As shown in FIG. 30, for each feature value index I (for example, RBC Redness Index, RBC Color S, Granule Index), the quality control device 1 plots a plurality of feature value plots P regarding red blood cell color information and a white blood cell plot P. A plot P of a plurality of feature values related to color information is output together with the management width MW. According to this configuration, it is possible to grasp the staining state of the entire smear sample based on the color information of the red blood cells, while also controlling the accuracy of the staining properties and morphology of the white blood cells, which are important targets for analysis.

The RBC Redness Index, which is the feature value index I, is calculated from the average value of each value after performing principal component analysis on the red blood cell hue value, red blood cell saturation value, and red blood cell brightness value. is the value to be used. RBC Color S, which is the feature value index I, is the saturation value of red blood cells. Granule Index, which is the feature value index I, is a granule index of white blood cells.

Note that the quality control device 1 may output only a plot P of a plurality of feature values related to color information of red blood cells to the output screen, or output only a plot P of a plurality of feature values related to color information of white blood cells to the output screen. You may.

Quality control information as internal quality control is information indicating variations in the staining state of smear specimens within one predetermined testing facility. The quality control information can serve as a standard for quality control according to the staining conditions of one predetermined testing facility. Therefore, it becomes possible to manage the quality of smears prepared daily in the one testing facility based on standards suitable for the testing facility.

In addition, quality control information as internal quality control can also be used in the following situations. For example, quality control information as internal quality control is used to confirm whether there is any problem in the staining state of a smear sample obtained after maintenance of an inspection device, after replacing a reagent, or when changing a reagent lot. Furthermore, according to quality control information as internal quality control, abnormalities in reagents or testing devices can be grasped in advance by checking the trend of increase or decrease in characteristic values over time. Furthermore, since environmental conditions such as temperature and humidity affect the stainability of smear specimens, quality control information for internal quality control is also useful when optimizing staining processing conditions in response to changes in environmental conditions. can be used.

FIG. 31 is a diagram showing an example of an output screen of feature values and quality control information that reflect the staining state of the smear specimen to be managed. When outputting feature values and quality control information that reflect the staining status of the smear specimen to be managed, it is checked whether the characteristic values reflecting the staining status of the smear specimen to be managed are included within a predetermined range. Output in an identifiable manner. In the screen example shown in FIG. 31, for example, since the plot P1 corresponding to a specific feature value is outside the management width MW, the plot P1 corresponding to this specific feature value is different from other plots on the output screen. output in the form For example, plot P1 is output more emphasized than other plots. More specifically, the plot P1 is output in a different color, a different size, or a different shape (for example, the plot P1 is round and the other plots are square). According to this configuration, it is possible to easily distinguish a plot corresponding to a specific feature value that is not included within the predetermined range from other plots that are included within the predetermined range.

FIG. 32 shows an example of an output screen that includes a predetermined alert display regarding a plot corresponding to a specific feature value that deviates from the management width MW. As shown in FIG. 32, when the user's first designation operation is performed on plot P3 that corresponds to a specific feature value that is outside the management width MW, detailed information on the specific feature value that corresponds to plot P3 is An alert display AI containing the information is output. The user's first designation operation is arbitrary, but includes, for example, stopping the cursor C1, which corresponds to the movement of the mouse operated by the user, on the plot P3 for a certain period of time.

According to this configuration, it is possible to appropriately present detailed information regarding a specific feature value outside the management range to the user. Therefore, by touching the detailed information, the user can easily identify the cause of the characteristic value falling outside the management range. Note that when performing a one-click operation with the mouse when the cursor C1 is stopped on the plot P3, a screen displaying multiple image data associated with the feature values of the plot P3, as shown in FIG. 33, which will be described later, is displayed. May be displayed.

FIG. 33 is a diagram showing an example of a screen displaying a plurality of image data acquired from one smear. In particular, FIG. 33 is a screen that is output when the user performs a predetermined operation on the screen shown in FIG. 32, for example. For example, on the output screen shown in FIG. 32, when the user performs the second designation operation on plot P5 corresponding to a specific feature value, when acquiring the specific feature value corresponding to plot P5, A screen shown in FIG. 33 is output that displays the plurality of image data IDs used.

According to this configuration, the user can easily check a list of multiple image data IDs used when acquiring a desired specific feature value. Note that the user's second designation operation is optional, but includes, for example, performing a double-click operation with a mouse when the cursor C3 stops on the plot P5. Further, although it is preferable that the user's first designation operation and second designation operation are different operations, they may be the same operation.

FIG. 34 is a diagram illustrating an example of a screen that displays specific image data and a plurality of feature values associated with the specific image data in association with each other. In particular, FIG. 34 is a screen that is output when the user performs a predetermined operation on the screen shown in FIG. 33, for example. For example, on the output screen shown in FIG. 33, when the user performs the third designation operation on specific image data ID1, detailed information of a plurality of feature values corresponding to the specified specific image data ID1 A screen shown in FIG. 33 is output, including an area R3 surrounded by a broken line, which displays .

According to this configuration, the user can easily check a list of a plurality of feature values corresponding to specific image data desired by the user. Note that the user's third designation operation is optional, but includes, for example, performing a double-click operation with a mouse when the cursor C5 stops on the image data ID1.

Here, the feature value FV (for example, granule_Index) that is outside the preset normal range may be displayed in a different form from other feature values. According to this configuration, a specific feature value FV that is an abnormal value can be easily distinguished from other (normal) feature values. The normal range may be set based on a control value (for example, information on a control range obtained from an upper limit value and a lower limit value) of a set quality control index.

FIG. 35 is a diagram illustrating an example of a screen from which feature values to be acquired can be selected. The characteristic values to be acquired or the characteristic values to be output on the screen as shown in FIGS. 30 to 32 are determined in advance for each testing facility, region, or the like, for example. On the other hand, by operating a feature value selection screen as shown in FIG. 35, the user can select one or more desired feature values. According to this configuration, the feature values desired by the user can be output on the output screen of feature values and quality control information that reflect the staining state of the smear specimen to be managed.

FIG. 36 is a diagram showing an example of a screen on which a normal range (management range) can be set for any characteristic value. On the screen shown in FIG. 36, the user can set the control range for any characteristic value in a region R5 surrounded by a broken line, for example, based on the results of quality control performed at each testing facility. For example, each value (lower, upper) of the item in the fifth row (“LY” in the cell column and “cell_s_mean” in the feature column) indicates the management range of the feature value regarding the staining state of the cytoplasm of lymphocytes. Each value of the item in the sixth row (“MO” in the cell column and “cell_v_mean” in the feature column) indicates the control range of the feature value regarding the staining state of the cytoplasm of the monocyte. In addition, the items in the 7th row (the cell column is "SNE" and the feature column is "segment_num") indicate the management range of the feature value related to the number of neutrophil segmentation. According to this configuration, the user can Since it is possible to arbitrarily set a control range for feature values based on the daily quality control indicators at the testing facility, it is possible to suppress subjective judgment errors between testers.

Regarding image data corresponding to abnormal feature values that are outside the management range set for each feature value shown in FIG. 36, for example, on the screen displaying a plurality of image data shown in FIG. The image data ID may be displayed in a different form from other image data IDs corresponding to normal feature values, such as ID5, ID7, ID9, ID11, and ID13. The method of displaying in a different format is arbitrary, but for example, on the screen, only image data that corresponds to abnormal feature values may be marked with a color frame, or displayed larger than other image data that correspond to normal feature values. including doing.

<Other embodiments>
The above-described embodiments are provided to facilitate understanding of the present invention, and are not to be construed as limiting the present invention. The present invention may be modified/improved (for example, by combining each embodiment or omitting a part of the configuration of each embodiment) without departing from the spirit thereof, and the present invention also includes equivalents thereof. It will be done.

For example, although quality control information for a blood smear sample collected from a subject is output, quality control information for a cell sample collected from a subject may also be output.

For example, although the smear slide 10 is prepared by the smear preparation device 20 included in the quality control system 100, the smear slide 10 may also be prepared manually by a laboratory technician belonging to a testing facility. Further, although the smear slide 10 was imaged by the specimen image capturing device 40, the smear slide 10 may be imaged manually by a laboratory technician belonging to a testing facility.

1: Quality control device, 10: Smear specimen slide, 20: Smear specimen preparation device, 30: Specimen transport device, 40: Specimen image capturing device, 50: Control unit, 60: Display unit, 70-1 to 70-4: Inspection system, 77: Communication department, 80: Storage section, 90: Input section, 100: Quality control system, 110: Management center, 200: Management system

Claims (16)

A method for quality control of a specimen prepared from a specimen, the method comprising:
setting at least one index used for quality control of the specimen from management index information in which a plurality of indices regarding the specimen are associated with management values corresponding to each of the plurality of indices;
obtaining a feature value regarding the at least one index from image data of the specimen;
outputting quality control information of the sample based on the feature value and a control value associated with the at least one index;
A specimen accuracy control method characterized by: 2. The quality control method according to claim 1, wherein the quality control information is a chart or notification information that allows comparison between the characteristic value and the management value. 3. The accuracy control method according to claim 1, wherein the index is set according to a selection from the management index information. The quality control method according to any one of claims 1 to 3, wherein the index is set based on a predetermined standard regarding quality control of a specimen. The quality control method according to any one of claims 1 to 4, wherein the index is set based on a guideline regarding specimen quality control. 6. The quality control method according to claim 5, wherein the index is set based on the guideline determined according to the region where the specimen is prepared. 5. The quality control method according to claim 1, wherein the index is set based on a predetermined standard regarding specimen preparation conditions. 8. The index according to claim 7, wherein the index is set based on the predetermined standard determined according to the type of reagent and/or the type of specimen preparation device used for specimen preparation. Accuracy control method. 9. The quality control method according to claim 1, wherein the index is set based on information transmitted from a server that manages the management index information. 10. The quality control method according to claim 9, wherein the information includes predetermined standards regarding specimen preparation conditions. 11. The quality control method according to claim 1, wherein the specimen is prepared from a specimen containing cells collected from a subject. 12. The quality control method according to claim 11, wherein the specimen is a blood smear prepared from blood collected from a subject. 13. The accuracy control method according to claim 1, wherein the index includes at least color information of cells in image data of the specimen. 14. The quality control method according to claim 13, wherein the cells are blood cells. A quality control device that performs quality control of specimens prepared from specimens,
including a control unit;
The control unit includes:
setting at least one index used for quality control of the specimen from management index information in which a plurality of indices regarding the specimen are associated with management values corresponding to each of the plurality of indices;
obtaining a feature value regarding the at least one index from image data of the specimen;
outputting quality control information of the sample based on the feature value and a control value associated with the at least one index;
A precision control device characterized by: A quality control device that controls the quality of specimens prepared from specimens.
setting at least one index used for quality control of the specimen from management index information in which a plurality of indices regarding the specimen are associated with management values corresponding to each of the plurality of indices;
Obtaining a feature value regarding the at least one index from image data of the specimen;
outputting quality control information of the sample based on the feature value and a control value associated with the at least one index;
A program to run.

Images