JPWO2016104308A1 - Cell image analysis method and cell image analysis apparatus - Google Patents

Abstract

[Problem] In a cell image analyzer for detecting target cells from a cell image of a sample containing multiple cell types in which target cells such as rare cells and non-target cells such as non-rare cells coexist, the cytoplasm is localized A cell image analyzing method and a cell image analyzing apparatus capable of detecting a target cell even when stained. [Solution] A first cell image acquisition step for acquiring a cell image specifically stained for a target cell, a second cell image acquisition step for acquiring a cell image specifically stained for a non-target cell, a target cell, A third cell image acquisition step for acquiring a cell image in which all non-target cells and residual cells are stained, a first cell image acquired in the first cell image acquisition step, and a second cell acquired in the second cell image acquisition step A target cell detection step of detecting a target cell based on the image and the third cell image acquired in the third cell image acquisition step;

Description

  The present invention relates to a cell image analyzer that automatically analyzes a cell image obtained by imaging a sample including a plurality of cell types and extracts a target cell, and particularly detects a rare cell mixed in a non-rare cell group. The present invention relates to a cell image analysis method and a cell image analysis apparatus.

  Circulating tumor cells (CTC) are found in the blood of patients with breast cancer, lung cancer, prostate cancer, pancreatic cancer, etc., and the number reflects the metastatic nature of cancer. It is attracting attention as it becomes important information above.

  However, the density of CTC in blood is extremely low (in the case of low, about 1 to 10 per 10 mL of whole blood), and its detection and counting are not easy.

  Conventionally, in order to distinguish such rare cells from a sample mixed with multiple cell types, a bright field image obtained by imaging a sample containing multiple cell types in a state in which specific rare cells are stained Image processing, such as increasing the contrast of specific cell types in cell images such as fluorescent images and fluorescent images, detects rare cells that have undergone specific staining.

  Even when specific staining is performed on rare cells in this way, nonspecific staining may be performed on non-rare cells at a certain rate. In order to improve the quality, a plurality of dyeings may be applied.

  In this case, for example, specific staining is performed on the target cell type and specific staining is performed on any of the other cell types, and the target cell type is estimated by combining two fluorescent images. ing. As a result, unintended cell types can be reliably excluded, and the reliability of the detection results of rare cells is enhanced.

  Thus, in the method of detecting a target cell type by image analysis using a cell image, when the cell density in the cell image is low, particularly when there is only one cell in the region of interest, a single cell type is detected. Since it is clearly a signal from a cell, the intensity of transmitted light, reflected light, scattered light, and fluorescence (hereinafter referred to as “detection light”) (hereinafter referred to as “detection light intensity”) is simply used. By measuring, the cell type can be estimated.

  On the other hand, if the cell density in the cell image is high, especially when the cells are close, dense, or aggregated, there is an overlap with adjacent cells, and even if the detected light intensity is measured, Therefore, it is difficult to determine the cell type, and it is difficult to count the number of target cells in the cell image.

  For this reason, in Patent Document 1, with respect to a cell image of a sample containing a plurality of cell types that are specifically stained for the target cell type, the morphology of the cell nucleus region and the cytoplasm region, that is, the contour of the cell nucleus and the cytoplasm The contour is detected, the cell from which the detection light is derived is determined from the overlap between the cell nucleus and the cytoplasm, and the target cell type is detected from the cell image.

JP 2011-27542 A

  However, a staining means that specifically stains the target cell type does not necessarily stain the entire cytoplasm, and may not detect the contour of the cytoplasm. The method described in Patent Document 1 Some cell types may not be detected.

  In addition, when cells are stained locally, the cell nucleus and the cytoplasmic staining region may not overlap, and even in such a case, the target cell type cannot be detected by the method described in Patent Document 1. Sometimes.

  Furthermore, when the target cell is specifically stained, the non-target cell is non-specifically stained and mistakenly detected as the target cell, or the target cell is locally stained and the cell nucleus and cytoplasm region overlap. The problem of not becoming.

  Further, when cells overlap, it is difficult to determine whether the target cell is stained or a non-target cell is stained.

  In the present invention, in view of such a current situation, a cell image for detecting a target cell from a cell image of a sample including a plurality of cell types in which target cells such as rare cells and non-target cells such as non-rare cells are mixed. An object of the present invention is to provide a cell image analysis method and a cell image analysis apparatus capable of detecting a target cell even when the cytoplasm is locally stained in the analysis apparatus.

The present invention was invented in order to solve the problems in the prior art as described above, and in order to achieve at least one of the objects described above, a cell image analysis reflecting one aspect of the present invention. The method is
A cell image analysis method for detecting a target cell using a cell image of a sample containing a plurality of types of cells,
A first cell image acquisition step of acquiring a cell image obtained by specifically staining a target cell;
A second cell image acquisition step of acquiring a cell image that specifically stains non-target cells;
A third cell image acquisition step of acquiring a cell image obtained by staining the target cell and the non-target cell;
Based on the first cell image acquired in the first cell image acquisition step, the second cell image acquired in the second cell image acquisition step, and the third cell image acquired in the third cell image acquisition step. And a target cell detection step of detecting the target cell.

A cell image analyzer reflecting one aspect of the present invention,
Cell image acquisition means for acquiring a first cell image that specifically stains target cells, a second cell image that specifically stains non-target cells, and a third cell image that stains target cells and non-target cells When,
A target cell detection means for detecting the target cell based on the first cell image, the second cell image, and the third cell image;
Is provided.

  According to the present invention, a plurality of cell images subjected to different staining can be used, and the staining area of the target cell can be reliably identified by image analysis due to the difference in the staining area of each cell image. The target cell can be reliably detected.

FIG. 1 is a block diagram illustrating a schematic configuration of a cell image analysis apparatus according to an aspect of the present invention. FIG. 2 is a process diagram for explaining the image analysis process. FIG. 3 is a schematic diagram for explaining a method for determining whether or not the stained region of the intermediate image and the stained region of the first cell image are close to each other in the target cell detection step. FIG. 4 is a schematic diagram for explaining another method for determining whether or not the stained region of the intermediate image and the stained region of the first cell image are close to each other in the target cell detection step. FIG. 5 is a process diagram of an image analysis process in another embodiment.

  Hereinafter, embodiments (examples) of the present invention will be described in more detail based on the drawings.

  FIG. 1 is a block diagram illustrating a schematic configuration of a cell image analysis apparatus according to an aspect of the present invention.

  As shown in FIG. 1, the cell image analysis apparatus 10 of the present embodiment includes a cell image acquisition unit 12 that acquires a cell image of a sample including a plurality of types of cells (hereinafter referred to as “test sample”), An intermediate image generating unit 16 that generates an intermediate image as described later from a plurality of cell images acquired by the cell image acquiring unit 12, and a target cell that detects a target cell that is a detection target as described later from the cell image and the intermediate image. And detecting means 18.

  The cell image analysis apparatus 10 can be configured by a computer or the like, and the cell image acquisition unit 12, the intermediate image generation unit 16, and the target cell detection unit 18 may be software executed by a computer.

  In addition, the cell image acquisition means 12 includes a first cell image that is a cell image that specifically stains the target cell, a second cell image that is a cell image that specifically stains the non-target cell, A third cell image that is a cell image in which all the target cells and the remaining cells are stained is obtained.

  In the present specification, the “target cell” is an arbitrary cell detected by the cell image analysis apparatus 10 and may be a rare cell such as a blood circulating cancer cell (CTC).

  The “non-target cell” is a cell other than the “target cell” among the cells contained in the test sample, and may be a non-rare cell having a relatively high content in the test sample. it can. The “non-target cell” may include a plurality of types of cells.

  Further, “residual cells” mean cells that are neither “target cells” nor “non-target cells” contained in a test sample. That is, normally, cells that are not stained by antibodies that specifically stain target cells or antibodies that specifically stain non-target cells. In addition, although a present Example demonstrates by the case where a residual cell exists, a residual cell may not exist.

  Samples containing such target cells, non-target cells, and residual cells are not particularly limited, but are collected from humans or other animals such as blood, urine, lymph, tissue fluid, and body cavity fluid. Specimens.

  Note that the cell image acquisition means 12 can be configured only by software for taking a cell image that has been captured and converted into data into the cell image analysis apparatus 10, or, as shown in FIG. An image photographing device 14 such as a digital camera for photographing the image can also be included.

  The intermediate image generation means 16 generates an intermediate image from the second cell image and the third cell image. Normally, only non-target cells are imaged in the second cell image, and all of target cells, non-target cells, and residual cells are imaged in the third cell image.

  However, some of the remaining cells and foreign substances that are not cells are stained when the non-target cells are specifically stained, and may be captured in the second cell image.

  For this reason, by removing a portion where the second cell image is superimposed from the third cell image, an intermediate image in which only the target cell and the residual cell (some of the residual cell in some cases) are captured can be generated. it can.

  Moreover, the target cell detection means 18 detects a target cell from the intermediate image and the first cell image. In the first cell image, normally, only the target cell is imaged, but a part of the non-target cell or a foreign substance that is not a cell is stained when the target cell is specifically stained, The first cell image may be captured.

  Therefore, a first cell image in which a target cell, a part of a non-target cell, and a foreign substance that is not a cell are imaged, and an intermediate image in which a target cell and a residual cell (a part of the residual cell in some cases) are imaged. And, for example, a region where both stained regions overlap or are close to each other is determined as a target cell.

  Hereinafter, a flow of detecting a target cell from a test sample using the cell image analysis apparatus 10 configured as described above will be described in more detail.

1. Staining process First, the target cells and non-target cells are stained specifically for the test sample, and all the target cells, non-target cells, and residual cells, ie, all cells are stained. Apply.

  In addition, as a method of specifically staining the target cell, it can be performed by contacting a test sample with a solution containing a labeled antibody that binds to an antigen of a cell to be detected.

  The antibody that shows a specific reaction with the antigen of the cell to be detected is not particularly limited, and examples thereof include an anti-CD45 antibody, an anti-β-actin antibody, an anti-α-tubulin antibody, and an anti-β- Tubulin antibodies, anti-vimentin antibodies and the like can be used.

  In addition, a method for specifically staining non-target cells can be performed by bringing a solution containing a labeled antibody that stains the entire cell membrane into contact with a test sample.

  The antibody that stains the entire cell membrane is not particularly limited. For example, anti-CK antibody, anti-CD2 antibody, anti-CD13 antibody, anti-CD14 antibody, anti-CD15 antibody, anti-CD19 antibody, anti-CD203c antibody, etc. Can be used.

  In addition, when specifically staining non-target cells, it is preferable to stain the whole non-target cells so that the outline of the non-target cells can be identified in the cell image by staining with a plurality of stains. .

  As such a labeled antibody, an antibody labeled with a known fluorescent dye, an antibody labeled with an antibody labeled with a dye, or the like can be used. When using fluorescent dyes, different excitation wavelengths and fluorescent wavelengths are used so that the fluorescent dye of the labeled antibody that stains the target cell and the fluorescent dye of the labeled antibody that stains the non-target cell can be measured separately. A fluorescent dye having the following may be used.

  As a method for staining all cells, staining can be performed by staining the cell nucleus. For example, DAPI (4 ′, 6-diamidino-2-phenylindole), Hoechst dye (Hoechst 33342, Hoechst 33258) Etc.), Acridine Orange, DAMO, Ethidium Bromide (Ethidium bromide), Ethidium Homodimer, Propidium Iodide and the like.

  Since staining is performed in this manner, when all cells are stained, each cell is locally stained.

In addition, as a method for specifically staining non-target cells and a method for staining all cells, it is preferable to satisfy any of the following conditions.
(1) The stained region of non-target cells when stained by a method of specifically staining non-target cells is included in the stained region of non-target cells when stained by a method of staining all cells. (2) When stained by the method of specifically staining with non-target cells, the entire cell membrane or cytoplasm of the non-target cells is stained, and the non-target cell staining region depicts the outline of the non-target cells, The stained area of non-target cells when all cells are stained by the staining method is a part of the cells and does not match the contour of the non-target cells.

  By performing staining in this manner, the stained area of non-target cells in the third cell image 26 becomes smaller than the stained area of non-target cells in the second cell image 24, so that the intermediate image generating means 16 will be described later. Thus, when the second cell image 24 is removed from the third cell image 26, an intermediate image in which the non-target cell staining region in the third cell image 26 is reliably removed can be generated.

  In addition, by performing staining so that the second cell image 24 and the third cell image 26 are superimposed in this manner, the second cell image 24 and the third cell image 26 are partially overlapped. It can be determined that the cells are not non-target cells, and even when the cells overlap each other, the target cells and the non-target cells can be distinguished.

  In addition, it is preferable to perform an appropriate pretreatment before staining the test sample in this way. Hereinafter, a pretreatment method when blood, which is a representative sample, is used as a test sample will be described.

-Anticoagulation treatment Blood (whole blood) collected and taken out of the body will coagulate over time if exposed to air as it is, and the cells contained therein cannot be recovered and observed. Therefore, it is preferable that the collected blood is immediately subjected to anticoagulation treatment.

  Various anticoagulants for whole blood are known and can be used in accordance with conditions such as general concentration and treatment time. For example, anticoagulant of the type that inhibits coagulation by binding to calcium ion by chelating action and removing it from the reaction system, represented by ethylenediaminetetraacetic acid (EDTA) and citric acid (including salts such as sodium salt) And anticoagulant of the type that inhibits coagulation by forming a complex with antithrombin III in plasma, represented by heparin, and suppressing the production of thrombin. A blood collection tube in which such an anticoagulant is previously stored may be used.

-Density gradient centrifugation The density gradient centrifugation can fractionate the components in the blood containing cells according to the specific gravity. In particular, it removes erythrocytes contained in a large amount in the blood and removes target cells such as CTC. Only white blood cells can be used for cell observation.

  The separation liquid used for the density gradient centrifugation may be any material that has a specific gravity suitable for the fractionation of cells in blood and can be welded so as to have an osmotic pressure and pH that do not destroy the cells. For example, commercially available sucrose solutions such as Ficoll (registered trademark) and Percoll (registered trademark) can be used.

  When density gradient centrifugation is performed after adjusting the specific gravity of this separated liquid to be smaller than the specific gravity of red blood cells and larger than the specific gravity of white blood cells, the blood sample is divided into `` a fraction rich in red blood cells '' and `` other than red blood cells '' Can be separated into at least two layers.

For example, when the specific gravity of the separation liquid is preferably 1.113 or less, more preferably 1.085 or less, the mixing rate of erythrocytes in the “fraction containing many cells other than erythrocytes” is 2 to 6% or less. Can be suppressed. Cell observation using “a fraction containing a large amount of cells other than erythrocytes” is preferable because the risk of failure to detect target cells such as CTC due to erythrocytes is reduced and the accuracy of diagnosis can be increased. .

  In addition, immobilization treatment, permeabilization treatment, blocking treatment, and other pretreatments can be performed on the cells contained in the test sample as necessary. These pretreatments can be performed at any time and in any order as long as the desired effect is exhibited.

  For example, after obtaining the cell fraction by density gradient centrifugation, immobilize cells before immobilizing on the observation substrate, immobilize on the observation substrate, and then permeabilize and block. May be performed simultaneously (ie, the cells are treated with a solution containing both a penetrant and a blocking agent).

  When cells are immobilized before immobilization on the observation substrate, the cells do not lose their ability to adsorb to the observation substrate even after immobilization. (Physical (intermolecular) interaction) between the substrate and the substrate.

  When cells are immobilized after being immobilized on the observation substrate, if the cells have already been adsorbed on the observation substrate, the immobilization by adsorption can be maintained even after immobilization.

  Further, in some cases, pretreatment for cells is performed before separating a cell fraction from a sample such as blood (for example, immediately after collecting a blood sample, cell anti-coagulation treatment and cell immobilization treatment are performed, Thereafter, density gradient centrifugation is performed to obtain a cell fraction).

-Immobilization treatment Immobilization treatment is a treatment performed to delay cell autolysis and spoilage and maintain its morphology and antigenicity. In the present invention, the detection of target cells such as CTC is enhanced. In addition, it is possible to suppress damage to cells or antigens by a dissociating agent such as an acid used in the antigen-antibody dissociation step.

  In particular, when an experiment is performed by repeating the binding and dissociation multiple times, the effect of the dissociation agent on the cells is greatly increased, so cell deterioration may increase and the experiment may not continue normally. .

  However, the immobilization treatment as in this step increases the retention of cells in form and antigenicity, and the effect of making immunostaining less likely to deteriorate even when the experiment is repeated multiple times. Bring.

  Various fixing agents are known, and examples thereof include aldehydes such as formaldehyde, glutaraldehyde and glyoxal; ketones such as acetone and methyl ethyl ketone; and alcohols such as ethanol and methanol. Among these, aldehydes such as formaldehyde and ketones such as acetone are immobilizing agents that act as a cross-linking agent by reacting an aldehyde group and a ketone group with a specific amino acid residue to form a covalent bond. It is a preferred immobilizing agent in the present invention because it can gel the cell protoplasm and suppress enzyme activity.

  In addition, although it does not act directly as a fixing agent, a donor that liberates the fixing agent upon hydrolysis or the like, such as a formaldehyde donor, can also be used as one form of the fixing agent. An aqueous solution obtained by dissolving these immobilizing agents in an appropriate solvent such as PBS (or diluting a commercially available solution such as formalin from the beginning) can be used as an immobilization treatment solution.

  The immobilization treatment can be performed by bringing the immobilization treatment solution having an appropriate concentration into contact with the cells for an appropriate time. The concentration of the immobilizing agent in the immobilizing treatment liquid can be adjusted as appropriate. For example, in the case of aldehydes, it is about 0.1 to 10 w / w%, and in the case of alcohols, it is about 70 to 100 v / v%. . The contact time between the immobilization treatment solution and the cells (immobilization treatment time) can be adjusted as appropriate, and is, for example, about 10 minutes to 1 hour at room temperature.

  The immobilization treatment may be performed before or during the staining step, and may be performed before or during the first staining step, or after the Nth dissociation step and (N + 1) th. It may be repeated before or during the dyeing process.

-Permeabilization treatment The permeabilization treatment is a treatment for improving the permeability of the cell membrane to facilitate the penetration of substances from the outside of the cell into the inside of the cell. In the present invention, the antigen in the cell (protoplasm) The effect of improving the immunostaining by facilitating the binding of a fluorescent-labeled antibody to the antibody.

  Various penetrants are known. For example, Triton X-100 (polyoxyethylene alkylphenyl ether), Tween 20 (polyoxyethylene sorbitan monolaurate), saponin, digitonin, Leukoperm, NP-40, etc. Surfactants (commercial products). An aqueous solution in which these permeabilizing agents are dissolved in an appropriate solvent such as PBS can be used as the permeation treatment liquid.

  The permeabilization treatment can be performed by bringing the permeabilization treatment solution having an appropriate concentration into contact with the cells for an appropriate time. The concentration of the permeabilizing agent in the permeabilizing liquid can be adjusted as appropriate. For example, in the case of the surfactant as described above, it is about 0.01 to 1.0 v / v%. The contact time between the permeabilization solution and the cells (permeabilization time) can be adjusted as appropriate, and is, for example, about 10 minutes to 1 hour at room temperature.

-Blocking treatment The blocking agent is used to prevent non-specific staining of the cells other than the target antigen. The cell blocking treatment may be performed before or during the staining step, and may be performed either or both.

  In the case of immobilizing a cell containing a blocking agent, it is necessary to form a microchamber or the like on the observation substrate as described above (using a structural method relating to the method of immobilizing a cell described later).

  In addition, by covering the part that is likely to cause adsorption (interaction) with the observation substrate on the cell surface, it is possible to prevent the cells from adsorbing to parts other than the part related to the solid phase of the cell such as a micro chamber. It is also used for accommodating cells in a predetermined site.

  Various blocking agents are known, and examples include hydrophilic polymers such as casein, skim milk, bovine serum albumin (BSA), and polyethylene glycol, and low molecular compounds such as phospholipid, ethylenediamine, and acetonitrile. An aqueous solution obtained by diluting these blocking agents with an appropriate solvent such as PBS can be used as a blocking treatment solution.

  The blocking treatment can be performed by bringing a blocking treatment solution having an appropriate concentration into contact with cells or an observation substrate for an appropriate time. Although the density | concentration of the blocking agent in a blocking process liquid can be adjusted suitably, it is about 0.01-20 w / v%, for example. The contact time between the blocking treatment solution and the cells (blocking treatment time) can be adjusted as appropriate, and is, for example, about 5 to 120 minutes at room temperature.

2. Imaging Step In the above-described staining step, a cell image is captured using the image capturing device 14 for the test sample subjected to the three types of staining.

  When labeling with a fluorescent dye, excitation that excites the fluorescent dye of the labeled antibody that stains the target cells, the fluorescent dye of the labeled antibody that stains non-target cells, and the fluorescent dye that labels all cells. What is necessary is just to image | photograph the cell image based on the fluorescence which light is irradiated sequentially and light-emitted from each fluorescent dye.

  The image capturing device 14 that captures such cell images is not particularly limited, but is preferably a device that captures cell images as image data that can be handled by software executed on a computer. For example, a digital camera using a CCD image sensor or a CMOS image sensor can be used.

  The image data of the cell image photographed by the image photographing device 14 is read into the cell image analyzing device 10 by the cell image obtaining means 12, and the image analysis of the cell image is performed.

3. Image analysis step In the intermediate image generation means 16 and the target cell detection means 18, as shown in the process diagram of FIG. 2, the first cell, which is a cell image specifically stained for the target cells taken in by the cell image acquisition means 12. Based on the image 22, the second cell image 24 that is a cell image that specifically stains non-target cells, and the third cell image 26 that is a cell image in which all target cells, non-target cells, and residual cells are stained. Detecting target cells in the test sample.

(Intermediate image generation process)
The intermediate image generating unit 16 generates the intermediate image 28 by removing the overlapping portion of the second cell image 24 from the third cell image 26.

  Specifically, first, after binarizing the third cell image 26 and the second cell image 24 by image processing calculation, the second cell image 24 may be subtracted from the third cell image 26.

  In this specification, “subtraction processing” means subtraction in image processing, and subtracting the value of the pixel at the same position in the other cell image from the value of the pixel in one cell image is performed for the pixels at all positions. It can be determined by doing. In general, the pixel value is preferably set to 0 when the minimum value is 0, and when the pixel value becomes negative as a result of the subtraction process.

  In the binarization process in the present embodiment, an arbitrary threshold value can be set and processed. In addition to the binarization process (1-bit imaging), 8-bit imaging or 16-bit imaging (grayscale) may be used. The acquired cell image may be used as it is.

  As shown in Table 1, in the third cell image 26, target cells, non-target cells, and residual cells are stained and imaged. On the other hand, in the second cell image 24, non-target cells are usually used. However, in some cases, some of the remaining cells and some of the foreign substances that are not cells may be stained and imaged. For this reason, in the intermediate image 28, the target cell and the residual cell are normally imaged, and in some cases, only the target cell and a part of the residual cell may be imaged.

In Table 1, “◯” means that the image is captured, and “x” means that the image is not captured. Note that ◯ or × may or may not be captured in the image.

(Target cell detection process)
Next, the target cell detection means 18 detects the target cell by comparing the intermediate image 28 and the first cell image 22.

  As shown in Table 2, in the first cell image 22, normally, only target cells should be stained and imaged. However, in some cases, non-target cells and some foreign substances that are not cells are stained. May be captured.

In Table 2, “◯” means that the image is captured, and “x” means that the image is not captured. Note that ◯ or × may or may not be captured in the image.

  Specifically, as described below, the stained region 29 of the intermediate image 28 (region where the target cells and a part of the remaining cells are stained) and the stained region 23 of the first cell image 22 (target cells, non-target) And a region where both stained regions are superimposed or close to each other are detected as target cells.

  Note that it is possible to determine whether or not both staining regions are close to each other, for example, as follows.

  In a state where the intermediate image 28 and the first cell image 22 are overlaid, as shown in FIG. 3, the minimum value t of the distance between the pixels of both staining regions is calculated, and this minimum value t is calculated from the intermediate image 28. The shortest distance between the stained region 29 and the stained region 23 of the first cell image 22 is set. If the shortest distance is equal to or smaller than a predetermined proximity determination value j, it can be determined that the shortest distance is close.

  Note that the proximity determination value j can be an arbitrary value depending on the cell to be detected. For example, when the average size of the target cell is considered to be equal to that of the white blood cell, the radius of the white blood cell is When it is assumed that it is about 7 μm, it is desirable that the proximity determination value is 7 μm. In addition, when it is assumed that the radius of white blood cells is about 15 μm, it is desirable that the proximity determination value be 15 μm. This is because if the cells are located within a radius range such as leukocytes, it can be determined that the cells are one cell unless the cells overlap in the vertical direction.

  In addition, with the intermediate image 28 and the first cell image 22 superimposed, as shown in FIG. 4, both stained regions are treated with known image processing algorithms (for example, nearest neighbor method, bilinear interpolation method, bicubic interpolation method). , Lanczos interpolation method or the like), and it is possible to determine that they are close to each other when the inflated dyeing regions 29a and 23a are superposed.

  The expansion value d can be an arbitrary value depending on the cell to be detected, and can be a value slightly larger than half of the proximity determination value j. For example, when the size of the target cell is assumed to be the same as that of the white blood cell, it is assumed that the diameter of the white blood cell is about 15 μm because there is a possibility that the objects to be stained exist within the range of the white blood cell diameter. In this case, the expansion value can be 8 μm.

  Further, if the objects to be stained are within the radius range of leukocytes, it can be determined that the possibility of the same is higher than the above, and if the radius of leukocytes is assumed to be about 7 μm, the expansion value d Can be 4 μm.

  Further, by performing a combination of the above-described proximity determinations, it is possible to determine more accurately whether or not both staining regions are close to each other.

  Further, when the distance between the center (centroid) position of one staining region and the center (centroid) position of the other staining region is smaller than a predetermined proximity determination value, it is determined that both staining regions are close to each other. You may make it do.

  When the target cell is detected in this manner, for example, a discrimination image 30 indicating the position of the target cell is displayed on a display unit such as a display.

  In the above-described embodiment, the intermediate image is generated from the third cell image and the second cell image. However, the intermediate image is not necessarily generated, and the first cell image 22 and the second cell are not necessarily generated. The target cell can be detected by appropriately combining the image 24 and the third cell image 26.

  For example, the target cell can be detected by multiplying the inverted second cell image obtained by inverting the luminance value of the second cell image 24, the first cell image, and the third cell image.

  In this specification, “multiplication processing” means multiplication in image processing, and the product of the pixel value of one cell image and the pixel value at the same position of the other cell image is the color depth of the image ( For example, in the case of an 8-bit image, it can be obtained by performing multiplication by 256 or 255) on pixels at all positions.

  FIG. 5 is a process diagram of an image analysis process in another embodiment. In this embodiment, a bright field image 32 is taken by the image taking device 14 separately from the first cell image 22, the second cell image 24, and the third cell image 26, and the cell image obtaining device 12 takes the cell image analyzing device. 10 is taken in.

  Also in this embodiment, the intermediate image generation process can be performed in the same manner as described above, and thus the description thereof is omitted.

(Target cell detection process)
The target cell detection means 18 first extracts the contour of a cell or the like from the bright field image 32 based on a known image processing algorithm (for example, Sobel filter, Roberts filter, Prewitt filter, etc.), and generates a contour image 34. .

  Note that the outline image 34 displays all the outlines of target cells, non-target cells, residual cells, and foreign substances that are not cells.

  Then, by superimposing the intermediate image 28, the first cell image 22 and the contour image 34, the stained region of the intermediate image 28 and the stained region of the first cell image 22 are within the same contour in the contour image 34, that is, When it exists in the outline of the same cell, it discriminate | determines that the said area | region is a target cell.

  The preferred embodiment of the present invention has been described above. However, the present invention is not limited to this, and in the above embodiment, a rare cell such as CTC is detected as the target cell. The cells are not limited to rare cells, and various modifications can be made without departing from the object of the present invention, such as use for detecting any cell.

  In addition, a program for causing the above-described cell image analysis method to be executed by a computer and the program recorded therein, for example, a magnetic tape (digital data storage (DSS), etc.), a magnetic disk (hard disk drive (HDD), a flexible disk (FD) )), Optical disc (compact disc (CD), digital versatile disc (DVD), Blu-ray disc (BD), etc.), magneto-optical disc (MO), flash memory (SSD (Solid State Drive), memory card, USB memory, etc.) And the like are also included as one embodiment of the present invention.

DESCRIPTION OF SYMBOLS 10 Cell image analyzer 12 Cell image acquisition means 14 Image capturing device 16 Intermediate image generation means 18 Target cell detection means 22 First cell image 23 Stained region 23a Stained region 24 after expansion Second cell image 26 Third cell image 28 Intermediate Image 29 Stained area 29a Stained area 30 after expansion Discriminated image 32 Bright field image 34 Contour image

Claims (22)

A cell image analysis method for detecting a target cell using a cell image of a sample containing a plurality of types of cells,
A first cell image acquisition step of acquiring a cell image obtained by specifically staining a target cell;
A second cell image acquisition step of acquiring a cell image that specifically stains non-target cells;
A third cell image acquisition step of acquiring a cell image obtained by staining the target cell and the non-target cell;
Based on the first cell image acquired in the first cell image acquisition step, the second cell image acquired in the second cell image acquisition step, and the third cell image acquired in the third cell image acquisition step. A target cell detection step of detecting the target cell;
A cell image analysis method comprising:   The cell image analysis method according to claim 1, wherein the third cell image is an image including stained residual cells.   The target cell detecting step multiplies the inverted second cell image obtained by inverting the luminance value of the second cell image, the first cell image, and the third cell image, thereby processing the target cell. The cell image analysis method according to claim 1, wherein the cell image analysis method is detected. An intermediate image generating step of generating an intermediate image by removing the overlapping portion of the second cell image from the third cell image;
The cell image analysis method according to claim 1 or 2, wherein the target cell detection step detects the target cell by comparing the first cell image and the intermediate image.   5. The target cell detection step compares the stained region in the intermediate image with the stained region in the first cell image, and determines a region where both stained regions overlap or are close to each other as the target cell. Cell image analysis method.   The cell image analysis method according to claim 5, wherein when the distance between the stained region in the intermediate image and the stained region in the first cell image is 15 μm or less, it is determined that both stained regions are close to each other.   The cell image analysis method according to claim 5 or 6, wherein when the shortest distance between the stained area in the intermediate image and the stained area in the first cell image is 7 µm or less, both stained areas are judged to be close to each other. A bright field image acquisition step of acquiring a bright field image for a sample containing the plurality of types of cells,
The target cell detection step compares the stained region in the intermediate image, the stained region in the first cell image, and the bright field image, and compares the stained region in the intermediate image and the stained region in the first cell image. The cell image analysis method according to claim 4, wherein when both are present within an outline of the same cell in the bright field image, the region is determined to be the target cell.   The cell image analysis according to any one of claims 1 to 8, wherein the second cell image is an image in which the non-target cell is specifically stained and an outline of the non-target cell is identifiable. Method.   The cell image analysis method according to claim 1, wherein the third cell image is an image in which each cell is locally stained. A cell image analysis device for detecting a target cell using a cell image of a sample containing a plurality of types of cells,
Cell image acquisition means for acquiring a first cell image that specifically stains target cells, a second cell image that specifically stains non-target cells, and a third cell image that stains target cells and non-target cells When,
A target cell detection means for detecting the target cell based on the first cell image, the second cell image, and the third cell image;
A cell image analysis apparatus comprising:   The cell image analysis apparatus according to claim 11, wherein the third cell image is an image including stained residual cells. The target cell detection means includes
Reversing the luminance value of the second cell image to generate an inverted second cell image;
The cell image analysis device according to claim 11 or 12, wherein the target cell is detected by multiplying the first cell image, the inverted second cell image, and the third cell image. An intermediate image generating means for generating an intermediate image by removing the overlapping portion of the second cell image from the third cell image;
The cell image analysis device according to claim 11 or 12, wherein the target cell detection means detects the target cell by comparing the first cell image and the intermediate image.   The target cell detection means compares the stained region in the intermediate image with the stained region in the first cell image, and determines a region where both stained regions overlap or are close to each other as the target cell. Cell image analysis device.   The cell image analysis apparatus according to claim 15, wherein when the distance between the stained region in the intermediate image and the stained region in the first cell image is 15 μm or less, it is determined that both stained regions are close to each other.   The cell image analyzer according to claim 15 or 16, wherein when the shortest distance between the stained region in the intermediate image and the stained region in the first cell image is 7 µm or less, both stained regions are determined to be close to each other. The cell image acquisition means is configured to further acquire a bright field image of a sample including the plurality of types of cells,
The target cell detection means compares the stained region in the intermediate image, the stained region in the first cell image, and the bright field image, and compares the stained region in the intermediate image and the stained region in the first cell image. The cell image analysis apparatus according to claim 14, wherein when both are present in an outline of the same cell in the bright field image, the region is determined to be the target cell.   The cell image analysis according to any one of claims 14 to 18, wherein the second cell image is an image in which the non-target cell is specifically stained and an outline of the non-target cell is identifiable. apparatus.   The cell image analysis device according to any one of claims 11 to 19, wherein the third cell image is an image in which each cell is locally stained.   A program for causing a computer to execute the cell image analysis method according to any one of claims 1 to 10.   A computer-readable recording medium on which the program according to claim 21 is recorded.