WO2022059300A1 - Image processing method, image processing device, and image processing program - Google Patents

Image processing method, image processing device, and image processing program Download PDF

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Publication number
WO2022059300A1
WO2022059300A1 PCT/JP2021/025483 JP2021025483W WO2022059300A1 WO 2022059300 A1 WO2022059300 A1 WO 2022059300A1 JP 2021025483 W JP2021025483 W JP 2021025483W WO 2022059300 A1 WO2022059300 A1 WO 2022059300A1
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Prior art keywords
cell
specific
image
biological substance
position information
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PCT/JP2021/025483
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French (fr)
Japanese (ja)
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雄一 尾崎
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コニカミノルタ株式会社
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Publication of WO2022059300A1 publication Critical patent/WO2022059300A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material

Definitions

  • the present invention relates to an image processing method, an image processing device, and an image processing program.
  • tissue section is stained and observed under a microscope, and the diagnosis is made based on morphological information such as the size and shape of the stained cell nucleus, pattern change as a tissue, and staining information.
  • morphological information such as the size and shape of the stained cell nucleus, pattern change as a tissue, and staining information.
  • staining method hematoxylin staining, DAB staining and the like are known.
  • a method for confirming the presence of a biological substance in a cell a method of binding a substance (for example, an antibody) specifically bound to the biological substance labeled with the fluorescent substance to the biological substance and observing the fluorescence is known.
  • images of tissue sections obtained using these methods are processed to quantify biological material and identify specific cell types.
  • Patent Document 1 describes a method for evaluating the expression level of a biological substance in a cell membrane.
  • tissue sections are stained with a fluorophore (a) that stains the cell membrane and a fluorophore (b) that binds to a biological material and has a peak emission wavelength different from that of the fluorophore (a). .. Then, the position of the stained cell membrane is identified, and the number of bright spots and the fluorescence intensity of the fluorescent substance (b) on the identified cell membrane are measured.
  • Patent Document 2 describes a cancer diagnosis method by a multiple staining method.
  • the cell membrane of cancer cells in a pathological specimen is DAB stained so that the cancer cells can be observed with visible light.
  • a fluorescent marker is attached to the chromosome of the cell so that the chromosome can be observed fluorescently, and then the chromosome is stained with new fuchsine so that the chromosome can be observed with visible light.
  • Patent Document 1 can quantify the biological substance and identify the cell expressing the biological substance, it is possible to specify the type of the cell expressing the biological substance. Can not. Further, the method described in Patent Document 2 can distinguish between cancer cells and other cells, but cannot quantify the biological substance expressed in the cancer cells.
  • Patent Document 1 In the method described in 1 and the method described in Patent Document 2, only one or two of these can be performed. Further, when the method described in Patent Document 1 and the method described in Patent Document 2 are combined, a large number of types of dyes are used, which may complicate the process and adversely affect fluorescence observation. be.
  • the present invention has been made in view of the above circumstances, and the quantification of intracellular biological substances, the identification of cells expressing biological substances, and the identification of the types of the cells are performed by using a small number of dyes. It is an object of the present invention to provide an image processing method, an image processing apparatus, and an image processing program that can be performed by using a simple step.
  • An image processing method for solving the above problems is a cell morphology image showing the morphology of the specific cells stained with a dye that stains the specific cells in a tissue section, and the tissue.
  • the image processing apparatus for solving the above-mentioned problems includes a cell morphology image showing the morphology of the specific cells stained with a dye that stains the specific cells in a tissue section.
  • the position information of the specific cell is extracted from the input unit for inputting a fluorescent image showing a specific biological substance with a fluorescent bright spot in the same range as the cell morphology image of the tissue section and the cell morphology image.
  • an image processing program relating to an embodiment of the present invention for solving the above-mentioned problems is a cell morphology indicating to a computer the morphology of the specific cells stained with a dye that stains the specific cells in a tissue section.
  • image processing that can quantify intracellular biological substances, identify cells expressing biological substances, and identify the type of the cells in a simple step using a small number of dyes.
  • FIG. 1 is a flowchart of an image processing method according to the first embodiment.
  • 2A to 2E are diagrams schematically showing images obtained in each step in the image processing method according to the second embodiment.
  • FIG. 3 is a flowchart showing the details of the step of extracting the position information of a specific cell according to the first embodiment.
  • FIG. 4 is a flowchart showing the details of the step of extracting the position information of a specific biological substance according to the first embodiment.
  • FIG. 5 is a block diagram schematically showing a functional configuration of the image processing apparatus according to the first embodiment.
  • FIG. 6 is a block diagram schematically showing a functional configuration of a control unit in the image processing apparatus according to the first embodiment.
  • FIG. 7 is a flowchart of the image processing method according to the second embodiment.
  • FIGS. 8A to 8F are diagrams schematically showing images obtained in each step in the image processing method according to the second embodiment.
  • FIG. 9 is a flowchart showing the details of the step of extracting the position information of the cell nucleus according to the second embodiment.
  • FIG. 10 is a block diagram schematically showing the functional configuration of the image processing apparatus according to the second embodiment.
  • FIG. 11 is a block diagram schematically showing a functional configuration of a control unit of the image processing apparatus according to the second embodiment.
  • FIG. 1 is a flowchart of an image processing method according to the first embodiment.
  • the image processing method includes (1) a step of inputting a cell morphology image and a fluorescent image (step S110), and (2) the cell morphology image.
  • a step of extracting the position information of a specific cell step S120
  • a step of extracting the position information of a specific biological substance from the fluorescent image step S130
  • (4) the specific living body It comprises a step (step S140) of determining whether or not the substance is expressed from the specific cell.
  • the step (2) may be performed at any time after the cell morphology image is input in the step (1).
  • the step (3) may also be performed at any time after the fluorescence image is input in the step (1).
  • the step (3) may be performed before the step (2).
  • the step (4) is performed after the step (2) and the step (3).
  • FIG. 2A to 2E are diagrams schematically showing images obtained in each step in the image processing method according to the present embodiment.
  • FIG. 2A shows a cell morphology image obtained in step S110.
  • FIG. 2B shows an image showing the position information of the specific cells extracted in step S120.
  • FIG. 2C is a fluorescence image obtained in step S110.
  • FIG. 2D shows an image showing the position information of the specific biological substance extracted in step S130.
  • FIG. 2E shows an image in which an image showing the position information of a specific cell and an image showing the position information of a specific biological substance are superimposed in the step S140.
  • Step of inputting cell morphology image and fluorescence image (step S110)
  • a cell morphology image showing the morphology of the specific cell stained with a dye that stains the specific cell in the tissue section and a specific biological substance in the same range as the cell morphology image of the tissue section are obtained.
  • the fluorescent image indicated by the fluorescent bright spot and the fluorescent image are input.
  • a tissue section may be prepared, a specific cell may be stained with a predetermined dye, a specific biological substance may be stained with a fluorescent dye, and a cell morphology image and a fluorescent image may be taken. Further, the cell morphology image and the fluorescence image taken in advance may be input via a storage medium, a communication line, or the like.
  • the cell morphology image is an image obtained by staining a specific cell with a dye in a tissue section and photographing a region showing the specific cell (FIG. 2A).
  • a specific cell it is preferable that at least one of the cytoplasm and the cell membrane is stained.
  • the method for staining a specific cell with a dye is not particularly limited, and is, for example, immunohistochemical staining by an enzyme antibody method.
  • the combination of the enzyme and the substrate in the enzyme antibody method is not particularly limited, and can be appropriately selected from known combinations of the enzyme and the substrate.
  • Examples of combinations of the enzyme that labels the antibody and the chromogenic substrate include a combination of peroxidase and diaminobenzidine (DAB) (DAB staining), a combination of peroxidase and aminoethylcarbazole (AEC) (AEC staining), alkaline phosphatase and Fast. Included are combinations with Red, alkaline phosphatase with Fast blue, alkaline phosphatase with bromochloroindolyl phosphate (BCIP), and the like.
  • DAB diaminobenzidine
  • AEC aminoethylcarbazole
  • alkaline phosphatase and Fast include a combination with Red, alkaline phosphatase with Fast blue, alkaline phosphatase with bromochloroindolyl phosphate (BCIP), and the like.
  • an antibody that binds directly or indirectly to a marker protein expressed in a particular type of cell is labeled with peroxidase, the antibody is bound to the marker protein in a tissue section, and diaminobenzidine is wrapped around the bound antibody.
  • DAB diaminobenzidine
  • the following is an example of the procedure for DAB staining of paraffin sections.
  • the dyeing is performed after performing the deparaffinization treatment and the activation treatment.
  • the paraffin section is immersed in a container containing xylene to remove the paraffin.
  • the temperature is not particularly limited, but it can be carried out at room temperature.
  • the immersion time is preferably 3 minutes or more and 30 minutes or less. If necessary, xylene may be replaced during immersion.
  • the tissue section from which paraffin has been removed is immersed in a container containing ethanol, and xylene is replaced with ethanol.
  • the temperature is not particularly limited, but it can be carried out at room temperature.
  • the immersion time is preferably 3 minutes or more and 30 minutes or less. If necessary, ethanol may be replaced during immersion.
  • the temperature is not particularly limited, but it can be carried out at room temperature.
  • the immersion time is preferably 3 minutes or more and 30 minutes or less. If necessary, the water may be replaced during the immersion.
  • the activation treatment is a treatment for exposing a biological substance (antigen that binds an antibody) in a tissue. Depending on the type of biological material, activation treatment may not be necessary.
  • the activation conditions are not particularly limited and are appropriately selected depending on the type of biological substance (antigen).
  • 0.01 M citrate buffer (pH 6.0) 1 mM, EDTA solution (pH 8.0), 5% urea, 0.1 M Tris-hydrochloric acid buffer and the like can be used as the heating device.
  • an autoclave, a microwave, a pressure cooker, a water bath, or the like can be used as the heating device.
  • the heating temperature can be 50 ° C. or higher and 130 ° C. or lower, and the time can be 5 minutes or longer and 30 minutes or shorter.
  • the tissue section after the activation treatment is immersed in a container containing PBS (phosphate buffered saline) and washed.
  • PBS phosphate buffered saline
  • the temperature is not particularly limited, but it can be carried out at room temperature.
  • the immersion time is preferably 3 minutes or more and 30 minutes or less. If necessary, the PBS may be replaced during the immersion.
  • a known blocking agent such as PBS containing BSA (bovine serum albumin) onto the tissue section.
  • the liquid containing the primary antibody is dropped and allowed to stand for a predetermined time.
  • the primary antibody is an antibody that specifically binds to a marker protein that is specifically expressed in cells to be stained. After this, the tissue section is washed. Next, a liquid containing the secondary antibody is added dropwise to the tissue to which the primary antibody is bound, and the mixture is allowed to stand for a predetermined time.
  • the secondary antibody is an antibody that specifically binds to the primary antibody and is labeled with peroxidase. After this, the tissue section is washed. Next, the DAB staining solution is dropped onto the tissue to which the secondary antibody is bound to stain the tissue.
  • the cell morphology image can be obtained by taking a picture with a known optical microscope equipped with a camera.
  • the visual field of the cell morphology image obtained by photographing is preferably 3 mm 2 or more, more preferably 30 mm 2 or more, and further preferably 300 mm 2 or more.
  • the upper limit of the visual field of the cell morphology image is not particularly limited, but is, for example, the size of a tissue section.
  • Input the captured image by sending it to an image analysis device such as a computer.
  • the fluorescent image is an image obtained by staining (labeling) a specific biological substance with a fluorescent substance in a tissue section and photographing the fluorescent bright spot by the fluorescent substance (FIG. 2C). ..
  • the fluorescent bright spots appearing in the fluorescent image indicate the presence of a particular biological material.
  • the method for staining (labeling) a specific biological substance with a fluorescent substance is not particularly limited, and is, for example, immunohistochemical staining by a fluorescent antibody method.
  • an antibody that directly or indirectly binds to a specific biological substance is labeled with a fluorescent substance, and this antibody is bound to the biological substance in a tissue section and irradiated with excitation light to obtain the specific biological substance.
  • Fluorescence can be emitted only from the existing part.
  • the specific biological substance is not particularly limited and may be appropriately selected depending on the intended purpose, and is, for example, PD-1 or Her2.
  • the type of fluorescent substance is not particularly limited.
  • the fluorescent material is a fluorescent organic dye or quantum dots (semiconductor particles).
  • the antibody may be labeled with fluorescent material-encapsulating nanoparticles containing a plurality of fluorescent organic dyes or a plurality of quantum dots.
  • the fluorescent material preferably emits fluorescence having a wavelength of 400 to 1100 nm when excited by light having a wavelength of 200 to 700 nm.
  • Fluorescent organic dyes include, for example, fluorescein dye molecules, rhodamine dye molecules, AlexaFluor (Invitrogen) dye molecules, BODIPY (Invigen) dye molecules, cascade dye molecules, coumarin dye molecules, and eodin dyes. Molecules, NBD-based dye molecules, pyrene-based dye molecules, TexasRed-based dye molecules, cyanine-based dye molecules, and the like. Specific examples of fluorescent organic dyes include 5-carboxy-fluorescein, 6-carboxy-fluorescein, 5,6-dicarboxy-fluorescein, 6-carboxy-2', 4,4', 5', 7,7.
  • the quantum dot is, for example, a quantum dot containing an II-VI group compound, a quantum dot containing a III-V compound, or a quantum dot containing a group IV element as a component.
  • semiconductors constituting quantum dots include CdSe, CdS, CdTe, ZnSe, ZnS, ZnTe, InP, InN, InAs, InGaP, GaP, GaAs, Si, and Ge. These quantum dots may also be used alone or in combination.
  • a quantum dot having the above quantum dot as a core and a shell provided on the core.
  • the notation of the quantum dot having a shell when the core is CdSe and the shell is ZnS, it is expressed as CdSe / ZnS.
  • the quantum dots having a core-shell structure are, for example, CdSe / ZnS, CdS / ZnS, InP / ZnS, InGaP / ZnS, Si / SiO 2 , Si / ZnS, Ge / GeO 2 , Ge / ZnS, and the like.
  • the quantum dots may be surface-treated with an organic polymer or the like.
  • Such quantum dots are, for example, CdSe / ZnS having a surface carboxy group (manufactured by Invitrogen), CdSe / ZnS having a surface amino group (manufactured by Invitrogen), and the like.
  • the method for binding the fluorescent substance to the antibody is not particularly limited, and can be appropriately selected from known methods.
  • Fluorescent substance-encapsulating nanoparticles are nanoparticles in which a plurality of fluorescent substances are dispersed therein.
  • the fluorescent substance and the nanoparticles themselves may or may not be chemically bonded.
  • the material constituting the nanoparticles is not particularly limited, and examples thereof include silica, polystyrene, polylactic acid, and melamine.
  • Fluorescent substance-encapsulating nanoparticles can be produced by a known method.
  • silica nanoparticles containing a fluorescent organic dye can be synthesized with reference to the synthesis of FITC-encapsulating silica particles described in Langmuir Vol. 8, p. 2921 (1992).
  • FITC fluorescent organic dye
  • various fluorescent organic dye-encapsulating silica nanoparticles can be synthesized.
  • Silica nanoparticles encapsulating quantum dots can be synthesized with reference to the synthesis of CdTe-encapsulating silica nanoparticles described in New Journal of Chemistry Vol. 33, p. 561 (2009).
  • Polystyrene nanoparticles containing a fluorescent organic dye can be obtained by a copolymerization method using an organic dye having a polymerizable functional group described in US Pat. No. 4,326,008 or fluorescent organic to polystyrene nanoparticles described in US Pat. No. 5,326,692. It can be produced by using a dye impregnation method. Polymer nanoparticles containing quantum dots can be produced by using the method of impregnating polystyrene nanoparticles with quantum dots described in Nature Biotechnology, Vol. 19, pp. 631 (2001).
  • the average particle size of the nanoparticles encapsulating the fluorescent substance is not particularly limited, but is, for example, 30 to 800 nm.
  • For the average particle size take an electron micrograph using a scanning electron microscope (SEM), measure the cross-sectional area of a sufficient number of particles, and use the diameter of the circle as the area of each measured value. It is a value obtained as a diameter.
  • the arithmetic mean of the particle sizes of 1000 particles is taken as the average particle size.
  • the coefficient of variation is also a value calculated from the particle size distribution of 1000 particles.
  • the method for binding the nanoparticles containing the fluorescent substance to the antibody is not particularly limited, and can be appropriately selected from known methods.
  • fluorescent immunostaining is performed after deparaffinization treatment and activation treatment.
  • Deparaffin treatment and activation treatment The same operation as the deparaffinization treatment and activation treatment described in the section of cell morphology image is performed.
  • a known blocking agent such as BSA (bovine serum albumin) -containing PBS is preferably added dropwise to the tissue section.
  • the liquid containing the primary antibody is dropped and allowed to stand for a predetermined time.
  • the primary antibody is an antibody that specifically binds to the biological substance to be stained. After this, the tissue section is washed. Next, a liquid containing the secondary antibody is added dropwise to the tissue to which the primary antibody is bound, and the mixture is allowed to stand for a predetermined time.
  • the secondary antibody is an antibody that specifically binds to the primary antibody, and is labeled with the fluorescent substance or the nanoparticles encapsulating the fluorescent substance. After this, the tissue section is washed.
  • the tissue section is enclosed.
  • a commercially available encapsulant may be dropped onto the stained tissue section and a cover glass may be placed on the stained tissue section.
  • the fluorescence image can be obtained by taking a picture with a known fluorescence microscope equipped with a camera. When photographing, an excitation light source and an optical filter corresponding to the absorption maximum wavelength and the fluorescence wavelength of the fluorescent substance used are used.
  • the field of view of the fluorescent image is the same range as the field of view of the cell morphology image.
  • Step S120 Step of extracting position information of a specific cell
  • the position information of a specific cell is extracted from the cell morphology image input in step S110 by using image processing software or the like.
  • FIG. 2B is a diagram schematically showing an image showing the position information of the extracted specific cells.
  • FIG. 3 is a flowchart showing an example of this process.
  • this step includes a step of converting an image to grayscale (step S121), a step of binarizing an image (step S122), a step of performing noise processing (step S124), and labeling. It has a step of processing (step S125). In addition, this step may further include a step (step S123) for performing a morphology treatment.
  • step S121 the cell morphology image is converted to grayscale. This is because the brightness of the color image (RGB) varies from section to section.
  • RGB color image
  • the cell morphology image converted to gray scale is binarized. Specifically, the value of each pixel is binarized by performing the threshold value processing on the image converted to gray scale with a predetermined threshold value.
  • the image to be binarized may be a likelihood image created from a cell morphology image using a machine learning technique such as deep learning.
  • step S124 objects other than the target object are identified as noise and removed. That is, it is a step of removing a portion other than a specific cell. Specifically, the number of pixels of each object is measured, and the object having the number of pixels equal to or less than the specified value is converted into the same color as the background color as noise.
  • each cell is numbered and labeled in order to identify the object in the image.
  • step S122 When cells whose cell membrane is shredded are present in the image, it is preferable to perform a morphology treatment after the step of binarizing the image (step S122).
  • step S123 the cells whose cell membranes have been cut are filled with holes to connect the cell membranes.
  • Step S130 Step of extracting position information of a specific biological substance
  • the position information of a specific biological substance is extracted from the fluorescent image input in step S110 by using image processing software or the like.
  • FIG. 2D is a diagram schematically showing an image showing the position information of the extracted specific biological substance.
  • FIG. 4 is a flowchart showing an example of this step according to the first embodiment.
  • this step includes a step of extracting a color component corresponding to the wavelength of the fluorescent bright spot (step S131) and a step of binarizing the color component (step S132).
  • step S131 In the step of extracting the color component corresponding to the wavelength of the fluorescent bright spot (step S131), for example, when the emission wavelength of the fluorescent substance in the fluorescent image is 550 nm, only the fluorescent bright spot having that wavelength component is used as an image. Be extracted.
  • step S132 the fluorescent image after color component extraction is thresholded to create a binary image. Specifically, the integrated value of the fluorescence intensity of each fluorescence bright spot is calculated, and based on the normalized fluorescence intensity, the fluorescence bright spot having a fluorescence intensity equal to or lower than an arbitrarily set threshold value is removed, and a binary image is obtained. To make.
  • noise reduction processing such as autofluorescence of cells and other unnecessary signal components may be performed.
  • Step of determining a biological substance In this step, whether or not the specific biological substance is expressed from the specific cell is determined from the position information of the specific cell and the position information of the specific biological substance extracted in the steps S120 and S130, respectively. judge.
  • FIG. 2E is a diagram schematically showing an image in which an image in which the position information of a specific cell is extracted and an image in which the position information of a specific biological substance is extracted are superimposed.
  • the fluorescent bright spot indicating the expression of the specific biological substance is located within the region indicating the specific cell. It can be judged by.
  • the fluorescent bright spot may be located at the edge of a region indicating a specific cell, or may be located within the region. At this time, it is more preferable that the stained region in the cell morphology image is ROI (Region of Interest).
  • ROI Region of Interest
  • the number of specific biological substances determined to be expressed in a specific cell in this step may be calculated, and the specific cell may be calculated.
  • the number of specific biological substances determined not to be expressed in a specific cell may be calculated.
  • tissue sections are subjected to the above-mentioned deparaffinization treatment and activation treatment.
  • a primary reaction with an anti-PD-1 antibody (primary antibody) and a secondary reaction with a secondary antibody labeled with a fluorescent substance are performed, and PD-1 is labeled with the fluorescent substance.
  • a primary reaction with an anti-CD8 antibody (primary antibody) that specifically binds to the protein CD8 expressed on killer T cells and a secondary reaction with a secondary antibody labeled with peroxidase were performed, and diaminobenzidine (DAB) was further added. Donate and color to stain killer T cells. After completing these stainings, tissue sections are encapsulated.
  • the obtained cell morphology image is converted to gray scale, and binarization treatment, noise treatment, and labeling treatment are performed to extract the position information of the killer T cells (obtain the extracted image of the killer T cells).
  • the color component corresponding to the wavelength of the fluorescent bright spot is extracted, binarized, and the position information of PD-1 is extracted.
  • the stained region (killer T cell) of the tissue section is designated as ROI, the cell morphology image and the fluorescent image are superimposed, and the fluorescent bright spot existing in the stained region is determined to be PD-1 expressed in the killer T cell.
  • the number of PD-1 determined above is measured using image processing software.
  • PD-1 can be quantified, cells expressing PD-1 can be specified, and the type of the cells can be specified.
  • tissue sections are subjected to the above-mentioned deparaffinization treatment and activation treatment.
  • a primary reaction with an anti-Her2 antibody (primary antibody) and a secondary reaction with a secondary antibody labeled with a fluorescent substance are performed, and Her2 is labeled with the fluorescent substance.
  • a primary reaction with an anti-cytokeratin antibody (primary antibody) that specifically binds to the protein cytokeratin expressed in the tumor region and a secondary reaction with a secondary antibody labeled with peroxidase were performed, and further, diaminobenzidine (DAB) was performed.
  • DAB diaminobenzidine
  • a fluorescence microscope is used to photograph fluorescence from a fluorescent substance indirectly bound to Her2, and a fluorescence image is acquired.
  • the obtained cell morphology image is converted to gray scale, and binarization treatment, noise treatment, and labeling treatment are performed to extract the position information of the tumor region (obtain the extracted image of the tumor region).
  • the color component corresponding to the wavelength of the fluorescent bright spot is extracted, binarized, and the position information of Her2 is extracted.
  • the stained region (tumor region) of the tissue section is designated as ROI, the cell morphology image and the fluorescent image are superimposed, and the fluorescent bright spot existing in the stained region is determined to be Her2 expressed in the tumor region. Next, the number of Her2 determined above is measured using image processing software.
  • Image processing device The image processing device according to the first embodiment of the present invention, which can be used when the above image processing method is carried out, will be described.
  • the present invention is not limited to the following embodiments.
  • the image processing apparatus is a cell morphology image showing the morphology of the specific cells stained with a dye that stains the specific cells in the tissue section, and the cell morphology image of the tissue section.
  • An input unit for inputting a fluorescent image showing a specific biological substance with a fluorescent bright spot in the same range as the above, a cell extraction unit for extracting position information of the specific cell from the cell morphology image, and the fluorescent image. From the biological substance extraction unit that extracts the positional information of the specific biological substance, the positional information of the specific cell, and the positional information of the specific biological substance, the specific biological substance is the specific cell. It has a biological substance expression determination unit for determining whether or not it is expressed from.
  • FIG. 5 is a block diagram schematically showing the functional configuration of the image processing apparatus 100.
  • the image processing device 100 includes an input unit 10, a control unit 20, an operation unit 30, a display unit 40, and a storage unit 50.
  • the image processing apparatus 100 analyzes a cell morphology image and a fluorescence image transmitted or input from an external device, and determines whether or not a specific biological substance is expressed from a specific cell.
  • the input unit 10 inputs the above-mentioned cell morphology image and fluorescence image.
  • the input unit 10 is, for example, a fluorescence microscope having a camera (which can also function as an optical microscope). Further, the input unit 10 may input image information sent from an external device (for example, the above-mentioned fluorescence microscope) or image information stored in a storage medium.
  • FIG. 6 is a block diagram schematically showing the functional configuration of the control unit 20.
  • the control unit 20 has a CPU (Central Processing Unit), a RAM (Random Access Memory), and the like, executes various processes in cooperation with various programs stored in the storage unit 50, and operates the image processing device 100. Is controlled comprehensively.
  • the control unit 20 includes a cell extraction unit 21, a biological substance extraction unit 22, and a biological substance expression determination unit 23.
  • the control unit 20 functions the cell extraction unit 21, the biological material extraction unit 22, and the biological material expression determination unit 23 in cooperation with the image processing program stored in the storage unit 50 to execute the image analysis processing. ..
  • the cell extraction unit 21 has a function of extracting the position information of a specific cell from the cell morphology image input by the input unit 10.
  • the cell extraction unit 21 converts the cell morphology image into gray scale and performs binarization treatment, noise treatment, and labeling treatment to extract the position information of a specific cell.
  • the cell extraction unit 21 may perform a morphology treatment after binarizing the cell morphology image to extract the position information of a specific cell.
  • the biological substance extraction unit 22 has a function of extracting the position information of a specific biological substance from the fluorescent image input by the input unit 10.
  • the biological substance extraction unit extracts the color component corresponding to the wavelength of the fluorescent bright spot from the fluorescent image, performs binarization processing, and extracts the position information of the biological substance.
  • the biomaterial extraction unit 22 may extract the position information of the biomaterial by performing noise reduction processing such as cell autofluorescence and other unnecessary signal components before the binarization processing.
  • the biological substance expression determination unit 23 identifies a specific biological substance from the position information of the specific cell extracted by the cell extraction unit 21 and the position information of the specific biological substance extracted by the biological substance extraction unit 22. It has a function of determining whether or not it is expressed from the cells of.
  • the control unit 20 may further include a calculation unit 24.
  • the calculation unit 24 is a specific biological substance determined to be expressed from a specific cell by the biological substance expression determination unit 23, or a specific biological substance determined not to be expressed from a specific cell. It has a function to calculate the number.
  • the operation unit 30 has, for example, a keyboard including character input keys, number input keys, various function keys, and a pointing device such as a mouse, and a key pressing signal operated by the keyboard and an operation signal by the pointing device. Is output to the control unit 20 as an input signal.
  • the display unit 40 is configured to include a monitor such as a CRT (Cathode Ray Tube) or an LCD (Liquid Crystal Display), and displays various screens according to instructions of a display signal input from the control unit 20.
  • a monitor such as a CRT (Cathode Ray Tube) or an LCD (Liquid Crystal Display)
  • the image processing device 100 may be provided with a LAN adapter, a router, or the like, and may be configured to be connected to an external device via a communication network such as a LAN.
  • the storage unit 50 is composed of, for example, an HDD (Hard Disk Drive) or a semiconductor non-volatile memory. As described above, various programs, various data, and the like are stored in the storage unit 50.
  • HDD Hard Disk Drive
  • semiconductor non-volatile memory As described above, various programs, various data, and the like are stored in the storage unit 50.
  • Image processing program The image processing program according to the first embodiment of the present invention, which can be used when performing image analysis processing in the image processing apparatus, will be described.
  • the present invention is not limited to the following embodiments.
  • a cell morphology image showing the morphology of the specific cells stained with a dye that stains the specific cells in the tissue section and the tissue section of the tissue section are described in a cell morphology image.
  • the process of determining whether or not it is performed and the process of determining whether or not it is performed are executed.
  • the image processing program cooperates with the control unit 20 of the image processing apparatus to function the cell extraction unit 21, the biological substance extraction unit 22, and the biological substance expression determination unit 23 to execute image processing.
  • the image processing method, the image processing apparatus, and the image processing program according to the first embodiment identify cells expressing a specific biological substance, quantify the expression level of the specific biological substance, and further, the specific biological substance. It is possible to identify the type of cell in which is expressed.
  • Embodiment 2 2-1 Image processing method
  • a step of extracting the position information of the cell nucleus from the cell morphology image and a step of identifying the position information of the cell nucleus in addition to each step of the image processing method according to the first embodiment, a step of extracting the position information of the cell nucleus from the cell morphology image and a step of identifying the position information of the cell nucleus.
  • FIG. 7 is a flowchart of the image processing method according to the second embodiment.
  • the image processing method according to the second embodiment is specified from (1) a step of inputting a cell morphology image and a fluorescent image (step S110) and (2) the cell morphology image.
  • a step of extracting the position information of the cell step S120
  • a step of extracting the position information of the cell nucleus from the cell morphology image step S210
  • (3) a specific biological substance from the fluorescent image step S130
  • Step S130 (4) a step of determining whether or not the specific biological substance is expressed from the specific cell, and (B) the specific biological substance.
  • a step of determining whether or not the cell nucleus is the cell nucleus of the specific cell from the cell position information (step S220), and (C) a step of identifying the cell nucleus to which the specific biological substance belongs (step S230). And have.
  • the image processing method according to the second embodiment is as follows: (A) a step of extracting the position information of the cell nucleus from the cell morphology image (step S210), and (B) the cell nucleus is described above from the position information of the specific cell. It is carried out in that it further has a step of determining whether or not it is a cell nucleus of a specific cell (step S220) and (C) a step of specifying a cell nucleus to which the specific biological substance belongs (step S230). Different from Form 1.
  • the same components as those of the image processing method according to the first embodiment are designated by the same reference numerals, and the description thereof will be omitted.
  • FIG. 8A to 8E are diagrams schematically showing images obtained in each step in the image processing method according to the present embodiment.
  • FIG. 8A shows a cell morphology image obtained in step S110.
  • FIG. 8B shows an image showing the position information of the specific cells extracted in step S120.
  • FIG. 8C shows an image showing the position information of the cell nucleus extracted in step S210.
  • FIG. 8D shows the fluorescence image obtained in step S110.
  • FIG. 8E shows an image showing the position information of the specific biological substance extracted in step S130.
  • FIG. 8F shows an image in which an image showing the position information of a specific cell and an image showing the position information of a specific biological substance are superimposed in the step S140.
  • Step S210 Step of extracting position information of cell nucleus
  • the position information of the cell nucleus is extracted from the cell morphology image input in step S110.
  • FIG. 9 is a flowchart showing the details of this step according to the second embodiment.
  • the cell morphology image further shows the cell nuclei of the dye-stained cells.
  • the dye that stains the cell nucleus is not particularly limited, but is, for example, hematoxylin. Staining with hematoxylin is performed after deparaffinization. For example, the tissue section from which paraffin has been removed is immersed in a staining solution containing hematoxylin, and the tissue section is stained with hematoxylin. Then, the tissue section stained with hematoxylin is immersed in running water to color it.
  • This step includes a step of binarizing the image (step S211), a noise processing step (step S212), and a labeling process (step S213).
  • the cell morphology image may be color-separated according to the color stained with the cell nucleus and then binarized, or a machine learning method such as deep learning may be used. May be used to create a likelihood image of the cell nucleus from the cell morphology image and then binarization processing.
  • Step S Steps S212 to S213 are the same as the steps S124 to S125 in the first embodiment, respectively, and therefore detailed description thereof will be omitted.
  • the position information of the cell nucleus is extracted by the processing of steps S211 to S213.
  • step S210 may be performed between the step of inputting the cell morphology image and the fluorescent image (step S110) and the step of determining the cell nucleus (step S220), and the position information of a specific cell is extracted. It may be performed before or after the step (S120) and the step of extracting the position information of a specific biological substance (step S130).
  • Step S220 Step of determining cell nucleus In this step, it is determined whether or not the cell nucleus is the cell nucleus of the specific cell from the position information of the specific cell extracted in the step S210.
  • the cell nucleus As a method for determining whether or not the cell nucleus is the cell nucleus of a specific cell, it may be determined whether or not the cell nucleus is located in the region indicating the specific cell. Whether or not the cell nucleus is located in the region indicating a specific cell is whether the ratio of the contour length of the cell nucleus in the region indicating a specific cell to the contour length of the cell nucleus is higher than an arbitrarily set threshold value. It may be judged by whether or not. Further, it may be determined whether or not the ratio of the area of the cell nucleus in the region indicating a specific cell to the area of the cell nucleus is higher than an arbitrarily set threshold value. According to this determination method, if the cell nucleus is located in the region indicating a specific cell, the cell nucleus is determined to be the cell nucleus of the specific cell.
  • this step may be performed after the step of extracting the position information of the cell nucleus (step S210) and may be performed before the determination of the biological substance (step S140).
  • Step S230 Step of identifying cell nucleus In this step, among the cell nuclei determined to be the cell nuclei of a specific cell in step S220, the cell nucleus to which the specific biological substance determined to be expressed from the specific cell in step S140 belongs is specified.
  • the method of identifying the cell nucleus to which a specific biological substance belongs may be specified as belonging to the cell nucleus closest to the fluorescent bright spot indicating the specific biological substance. Specifically, in the region indicating a specific cell, the cell nucleus in which the distance between the center of the cell nucleus determined to be the cell nucleus of the specific cell and the center of the fluorescent bright spot indicating the specific biological substance is the shortest is specified. It is identified as the cell nucleus to which the biological material belongs. In addition, it is specified that the fluorescent bright spot indicating a specific biological substance existing outside the region indicating a specific cell belongs to the closest cell nucleus among the cell nuclei not determined to be the cell nucleus of the specific cell.
  • the number of specific biological substances identified as belonging to the cell nucleus determined to be the cell nucleus of the specific cell may be calculated.
  • the number of specific biological substances identified as belonging to the cell nucleus that was not determined to be the cell nucleus of the specific cell may be calculated. ..
  • tissue sections are subjected to the above-mentioned deparaffinization treatment and activation treatment.
  • a primary reaction with an anti-PD-1 antibody (primary antibody) and a secondary reaction with a secondary antibody labeled with a fluorescent substance are carried out, and PD-1 is labeled with the fluorescent substance.
  • a primary reaction with an anti-CD8 antibody (primary antibody) that specifically binds to the protein CD8 expressed on killer T cells and a secondary reaction with a secondary antibody labeled with peroxidase were performed, and diaminobenzidine (DAB) was further added. Donate and color to stain killer T cells.
  • the cell nucleus of each cell is stained with hematoxylin. After completing these stainings, tissue sections are encapsulated.
  • the obtained cell morphology image is converted to gray scale, and binarization treatment, noise treatment, and labeling treatment are performed to extract the position information of the killer T cells (obtain the extracted image of the killer T cells).
  • a likelihood image of the cell nucleus is created using deep learning, and binarization treatment, noise treatment, and labeling treatment are performed to extract the position information of the cell nucleus (cell nucleus). Get the extracted image).
  • the color component corresponding to the wavelength of the fluorescent bright spot is extracted, binarized, and the position information of PD-1 is extracted.
  • the stained region (killer T cell) of the tissue section is designated as ROI, the cell morphology image and the fluorescent image are superimposed, and the fluorescent bright spot existing in the stained region is determined to be PD-1 expressed in the killer T cell. ..
  • the hematoxylin-stained cell nucleus located in the stained area is determined to be the cell nucleus of the killer T cell.
  • the distance between the center of the determined killer T cell nucleus and the center of the fluorescent bright spot indicating PD-1 determined to be expressed in the killer T cell is measured. Then, the cell nucleus located closest to the fluorescent bright spot is identified as the cell nucleus to which PD-1 belongs.
  • the fluorescent bright spot indicating PD-1 existing outside the stained region identifies that the center-to-center distance between the cell nucleus of the killer T cell and the cell nucleus not determined to belong to the closest cell nucleus.
  • the number of PD-1 per cell nucleus of the killer T cell is calculated by dividing the measured number of PD-1 expressed in the killer T cell by the number of the determined cell nuclei of the killer T cell.
  • FIG. 10 is a block diagram schematically showing a functional configuration of the image processing device 200 according to the second embodiment
  • FIG. 11 is a control unit of the image processing device according to the second embodiment. It is a block diagram which roughly showed the functional structure of 20.
  • the image processing apparatus 200 according to the second embodiment is different from the image processing apparatus 100 according to the first embodiment in that the control unit 20 further includes the cell nucleus extraction unit 25, the cell nucleus determination unit 26, and the cell nucleus identification unit 27.
  • the same components as those of the image processing apparatus 100 according to the first embodiment are designated by the same reference numerals, and the description thereof will be omitted.
  • the cell nucleus extraction unit 25 has a function of extracting the position information of the cell nucleus from the cell morphology image input by the input unit 10.
  • the cell nucleus extraction unit 25 performs binarization treatment, noise treatment, and labeling treatment on the cell morphology image to extract the position information of the cell nucleus.
  • the cell morphology image may be color-separated according to the color of the cell nucleus stained, and then the binarization treatment may be performed, or the cell nucleus may be subjected to the binarization treatment using a machine learning method such as deep learning. After creating the likelihood image of, the binarization process may be performed.
  • the cell nucleus determination unit 26 has a function of determining whether the cell nucleus extracted by the cell nucleus extraction unit 25 is the cell nucleus of a specific cell from the position information of the specific cell extracted by the cell extraction unit 21.
  • the cell nucleus specifying unit 27 contains the position information of the cell nucleus determined to be the cell nucleus of the specific cell by the cell nucleus determination unit 26 and the position information of the specific biological substance determined to be expressed from the specific cell by the biological substance expression determination unit 23. Therefore, it has a function of specifying the cell nucleus to which a specific biological substance belongs.
  • the cell nucleus is specified from the step of extracting the position information of the cell nucleus from the cell morphology image, the position information of the cell nucleus, and the position information of the specific cell. From the step of determining whether or not the cell nucleus is a cell nucleus, the position information of the cell nucleus determined to be the cell nucleus of the specific cell, and the position information of the biological substance determined to be expressed from the specific cell. It differs from the first embodiment in that the step of specifying the cell nucleus to which the specific biological substance belongs is further executed.
  • the same components as those of the image processing program according to the first embodiment are designated by the same reference numerals, and the description thereof will be omitted.
  • the image processing program cooperates with the control unit 20 of the image processing apparatus to perform a cell extraction unit 21, a biological material extraction unit 22, a biological material expression determination unit 23, a cell nucleus extraction unit 25, a cell nucleus determination unit 26, and a cell nucleus.
  • the specific unit 27 is made to function and image processing is executed.
  • the quantification of an intracellular biological substance, the identification of a cell expressing a biological substance, and the identification of the type of the cell can be performed by a simple step using a small number of dyes.
  • An image processing method can be provided.
  • the present invention is useful for pathological diagnosis and the like.

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Abstract

This invention relates to the image processing method that makes it possible to quantify an intracellular biological substance, to specify a cell in which the biological substance is expressed, and to specify the type of the cell using a small number of pigment types and a simple process. In this method, input are a cell form image showing, in a tissue section, the form of a specific cell stained by a pigment that stains the specific cell and a fluorescence image showing a specific biological substance as a fluorescent bright spot within the same range of the tissue section as the cell form image. Position information for the specific cell is extracted from the cell form image. Whether the specific biological substance is expressed in the specific cell is determined from a step of extracting position information for the specific biological substance from the fluorescence image, the position information for the specific cell, and the position information for the specific biological substance.

Description

画像処理方法、画像処理装置、および画像処理プログラムImage processing method, image processing device, and image processing program
　本発明は、画像処理方法、画像処理装置、および画像処理プログラムに関する。 The present invention relates to an image processing method, an image processing device, and an image processing program.
　近年、抗体医薬を中心とした分子標的薬を用いた治療の拡大に伴い、分子標的薬をより効果的に使用するための正確な診断法の必要性が高まっている。具体的には、組織切片における生体物質の定量や、生体物質が発現している細胞の特定および当該細胞の種類の特定が求められている。 In recent years, with the expansion of treatments using molecular-targeted drugs centered on antibody drugs, the need for accurate diagnostic methods for more effective use of molecular-targeted drugs has increased. Specifically, it is required to quantify biological substances in tissue sections, identify cells expressing biological substances, and identify the types of the cells.
　一般的に、病理診断では、組織切片を染色して顕微鏡観察を行い、染色された細胞核の大きさや形状、組織としてのパターン変化等の形態学的な情報、染色情報をもとに診断を行っている。染色方法としては、ヘマトキシリン染色やＤＡＢ染色などが知られている。また、細胞内の生体物質の存在を確認する方法として、蛍光物質で標識された、生体物質に特異的に結合する物質（例えば抗体）を生体物質に結合させて、蛍光観察する方法が知られている。これらの方法を用いて得られた組織切片の画像を処理し、生体物質の定量化や、特定の細胞の種類の特定を行う。 Generally, in pathological diagnosis, a tissue section is stained and observed under a microscope, and the diagnosis is made based on morphological information such as the size and shape of the stained cell nucleus, pattern change as a tissue, and staining information. ing. As a staining method, hematoxylin staining, DAB staining and the like are known. Further, as a method for confirming the presence of a biological substance in a cell, a method of binding a substance (for example, an antibody) specifically bound to the biological substance labeled with the fluorescent substance to the biological substance and observing the fluorescence is known. ing. Images of tissue sections obtained using these methods are processed to quantify biological material and identify specific cell types.
　例えば、特許文献１には、細胞膜における生体物質の発現レベルの評価方法が記載されている。この方法では、組織切片を、細胞膜を染色する蛍光体（ａ）と、生体物質に結合する、蛍光体（ａ）とは異なる発光波長のピークを持つ蛍光体（ｂ）とで染色している。そして、染色された細胞膜の位置を同定し、同定された細胞膜上の蛍光体（ｂ）の輝点数および蛍光強度を計測している。 For example, Patent Document 1 describes a method for evaluating the expression level of a biological substance in a cell membrane. In this method, tissue sections are stained with a fluorophore (a) that stains the cell membrane and a fluorophore (b) that binds to a biological material and has a peak emission wavelength different from that of the fluorophore (a). .. Then, the position of the stained cell membrane is identified, and the number of bright spots and the fluorescence intensity of the fluorescent substance (b) on the identified cell membrane are measured.
　また、特許文献２には、多重染色法によるガン診断方法が記載されている。この方法では、病理標本中のガン細胞の細胞膜をＤＡＢ染色して、ガン細胞を可視光観察できるようにする。また、細胞の染色体に蛍光マーカーを付与して染色体を蛍光観察できるようにし、その後にニューフクシン染色をして染色体を可視光観察できるようにしている。 Further, Patent Document 2 describes a cancer diagnosis method by a multiple staining method. In this method, the cell membrane of cancer cells in a pathological specimen is DAB stained so that the cancer cells can be observed with visible light. In addition, a fluorescent marker is attached to the chromosome of the cell so that the chromosome can be observed fluorescently, and then the chromosome is stained with new fuchsine so that the chromosome can be observed with visible light.
特開２０１３－５７６３１号公報Japanese Unexamined Patent Publication No. 2013-57631 特開２００４－１５７０５３号公報Japanese Unexamined Patent Publication No. 2004-157053
　しかしながら、特許文献１に記載の方法では、生体物質の定量化、および生体物質が発現している細胞の特定をすることができるものの、生体物質が発現している細胞の種類を特定することができない。また、特許文献２に記載の方法では、ガン細胞とそれ以外の細胞とを区別することができるが、ガン細胞に発現する生体物質を定量化することができない。 However, although the method described in Patent Document 1 can quantify the biological substance and identify the cell expressing the biological substance, it is possible to specify the type of the cell expressing the biological substance. Can not. Further, the method described in Patent Document 2 can distinguish between cancer cells and other cells, but cannot quantify the biological substance expressed in the cancer cells.
　特定の細胞に発現する生体物質の定量化を行うために、生体物質の定量化、生体物質が発現している細胞の特定、および当該細胞の種類の特定を行う必要があるが、特許文献１に記載の方法および特許文献２に記載の方法では、これらのうちのいずれか１つまたは２つしか行うことができない。また、特許文献１に記載の方法と特許文献２に記載の方法とを組み合わせた場合、多種類の色素を用いることになるため、工程が複雑になるとともに、蛍光観察に悪影響が及ぶ可能性がある。 In order to quantify the biological substance expressed in a specific cell, it is necessary to quantify the biological substance, identify the cell expressing the biological substance, and specify the type of the cell. Patent Document 1 In the method described in 1 and the method described in Patent Document 2, only one or two of these can be performed. Further, when the method described in Patent Document 1 and the method described in Patent Document 2 are combined, a large number of types of dyes are used, which may complicate the process and adversely affect fluorescence observation. be.
　本発明は、上記の事情に鑑みてなされたものであり、細胞内の生体物質の定量化、生体物質が発現している細胞の特定、および当該細胞の種類の特定を、少ない種類の色素を用いて簡単な工程で行うことができる画像処理方法、画像処理装置、および画像処理プログラムを提供することを目的とする。 The present invention has been made in view of the above circumstances, and the quantification of intracellular biological substances, the identification of cells expressing biological substances, and the identification of the types of the cells are performed by using a small number of dyes. It is an object of the present invention to provide an image processing method, an image processing apparatus, and an image processing program that can be performed by using a simple step.
　上記課題を解決するための本発明の一実施の形態に関する画像処理方法は、組織切片における、特定の細胞を染色する色素により染色された前記特定の細胞の形態を示す細胞形態画像と、前記組織切片の前記細胞形態画像と同一範囲における、特定の生体物質を蛍光輝点で示す蛍光画像と、を入力する工程と、前記細胞形態画像から、前記特定の細胞の位置情報を抽出する工程と、前記蛍光画像から、前記特定の生体物質の位置情報を抽出する工程と、前記特定の細胞の位置情報と、前記特定の生体物質の位置情報とから、前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する工程と、を有する。 An image processing method according to an embodiment of the present invention for solving the above problems is a cell morphology image showing the morphology of the specific cells stained with a dye that stains the specific cells in a tissue section, and the tissue. A step of inputting a fluorescent image showing a specific biological substance with a fluorescent bright spot in the same range as the cell morphology image of a section, and a step of extracting position information of the specific cell from the cell morphology image. From the step of extracting the position information of the specific biological substance from the fluorescent image, the position information of the specific cell, and the position information of the specific biological substance, the specific biological substance is the specific cell. It has a step of determining whether or not it is expressed from.
　また、上記課題を解決するための本発明の一実施の形態に関する画像処理装置は、組織切片における、特定の細胞を染色する色素により染色された前記特定の細胞の形態を示す細胞形態画像と、前記組織切片の前記細胞形態画像と同一範囲における、特定の生体物質を蛍光輝点で示す蛍光画像と、を入力する入力部と、前記細胞形態画像から、前記特定の細胞の位置情報を抽出する細胞抽出部と、前記蛍光画像から、前記特定の生体物質の位置情報を抽出する生体物質抽出部と、前記特定の細胞の位置情報と、前記特定の生体物質の位置情報とから、前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する生体物質発現判定部と、を有する。 Further, the image processing apparatus according to the embodiment of the present invention for solving the above-mentioned problems includes a cell morphology image showing the morphology of the specific cells stained with a dye that stains the specific cells in a tissue section. The position information of the specific cell is extracted from the input unit for inputting a fluorescent image showing a specific biological substance with a fluorescent bright spot in the same range as the cell morphology image of the tissue section and the cell morphology image. The specific cell extraction unit, the biological material extraction unit that extracts the position information of the specific biological substance from the fluorescent image, the position information of the specific cell, and the position information of the specific biological substance. It has a biological substance expression determination unit for determining whether or not the biological substance is expressed from the specific cell.
　また、上記課題を解決するための本発明の一実施の形態に関する画像処理プログラムは、コンピュータに、組織切片における、特定の細胞を染色する色素により染色された前記特定の細胞の形態を示す細胞形態画像と、前記組織切片の前記細胞形態画像と同一範囲における、特定の生体物質を蛍光輝点で示す蛍光画像と、を入力する工程と、前記細胞形態画像から、前記特定の細胞の位置情報を抽出する工程と、前記蛍光画像から、前記特定の生体物質の位置情報を抽出する工程と、前記特定の細胞の位置情報と、前記特定の生体物質の位置情報とから、前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する工程と、を実行させる。 Further, an image processing program relating to an embodiment of the present invention for solving the above-mentioned problems is a cell morphology indicating to a computer the morphology of the specific cells stained with a dye that stains the specific cells in a tissue section. A step of inputting an image and a fluorescent image showing a specific biological substance with a fluorescent bright spot in the same range as the cell morphology image of the tissue section, and the position information of the specific cell from the cell morphology image. From the step of extracting, the step of extracting the position information of the specific biological substance from the fluorescent image, the position information of the specific cell, and the position information of the specific biological substance, the specific biological substance is obtained. , And the step of determining whether or not it is expressed from the specific cell.
　本発明により、細胞内の生体物質の定量化、生体物質が発現している細胞の特定、および当該細胞の種類の特定を、少ない種類の色素を用いて簡単な工程で行うことができる画像処理方法、画像処理装置、および画像処理プログラムが提供される。 According to the present invention, image processing that can quantify intracellular biological substances, identify cells expressing biological substances, and identify the type of the cells in a simple step using a small number of dyes. Methods, image processing devices, and image processing programs are provided.
図１は、実施の形態１に係る画像処理方法のフローチャートである。FIG. 1 is a flowchart of an image processing method according to the first embodiment. 図２Ａ～Ｅは、実施の形態２に係る画像処理方法において、各工程で得られる画像を模式的に示した図である。2A to 2E are diagrams schematically showing images obtained in each step in the image processing method according to the second embodiment. 図３は、実施の形態１に係る、特定の細胞の位置情報を抽出する工程の詳細を示す、フローチャートである。FIG. 3 is a flowchart showing the details of the step of extracting the position information of a specific cell according to the first embodiment. 図４は、実施の形態１に係る、特定の生体物質の位置情報を抽出する工程の詳細を示す、フローチャートである。FIG. 4 is a flowchart showing the details of the step of extracting the position information of a specific biological substance according to the first embodiment. 図５は、実施の形態１に係る画像処理装置の機能的構成を概略的に示したブロック図である。FIG. 5 is a block diagram schematically showing a functional configuration of the image processing apparatus according to the first embodiment. 図６は、実施の形態１に係る画像処理装置における制御部の機能的構成を概略的に示したブロック図である。FIG. 6 is a block diagram schematically showing a functional configuration of a control unit in the image processing apparatus according to the first embodiment. 図７は、実施の形態２に係る画像処理方法のフローチャートである。FIG. 7 is a flowchart of the image processing method according to the second embodiment. 図８Ａ～Ｆは、実施の形態２に係る画像処理方法において、各工程で得られる画像を模式的に示した図である。8A to 8F are diagrams schematically showing images obtained in each step in the image processing method according to the second embodiment. 図９は、実施の形態２に係る、細胞核の位置情報を抽出する工程の詳細を示したフローチャートである。FIG. 9 is a flowchart showing the details of the step of extracting the position information of the cell nucleus according to the second embodiment. 図１０は、実施の形態２に係る、画像処理装置の機能的構成を概略的に示したブロック図である。FIG. 10 is a block diagram schematically showing the functional configuration of the image processing apparatus according to the second embodiment. 図１１は、実施の形態２に係る画像処理装置の制御部の機能的構成を概略的に示したブロック図である。FIG. 11 is a block diagram schematically showing a functional configuration of a control unit of the image processing apparatus according to the second embodiment.
　以下、本発明の実施の形態について詳細に説明する。なお、本発明は、以下の形態に限定されるものではない。 Hereinafter, embodiments of the present invention will be described in detail. The present invention is not limited to the following forms.
　１．実施の形態１
　１－１．画像処理方法
　図１は、実施の形態１に係る画像処理方法のフローチャートである。 1. 1. Embodiment 1
1-1. Image processing method FIG. 1 is a flowchart of an image processing method according to the first embodiment.
　図１に示すように、本発明の一実施の形態に係る画像処理方法は、（１）細胞形態画像と、蛍光画像と、を入力する工程（工程Ｓ１１０）と、（２）前記細胞形態画像から、特定の細胞の位置情報を抽出する工程（工程Ｓ１２０）と、（３）前記蛍光画像から、特定の生体物質の位置情報を抽出する工程（工程Ｓ１３０）と、（４）前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する工程（工程Ｓ１４０）と、を有する。（２）の工程は、（１）の工程で細胞形態画像を入力した後であれば、いつ行われてもよい。（３）の工程も、（１）の工程で蛍光画像を入力した後であれば、いつ行われてもよい。たとえば、（３）の工程は、（２）の工程の前に行われてもよい。（４）の工程は、（２）の工程および（３）の工程の後に行われる。 As shown in FIG. 1, the image processing method according to the embodiment of the present invention includes (1) a step of inputting a cell morphology image and a fluorescent image (step S110), and (2) the cell morphology image. From the above, a step of extracting the position information of a specific cell (step S120), (3) a step of extracting the position information of a specific biological substance from the fluorescent image (step S130), and (4) the specific living body. It comprises a step (step S140) of determining whether or not the substance is expressed from the specific cell. The step (2) may be performed at any time after the cell morphology image is input in the step (1). The step (3) may also be performed at any time after the fluorescence image is input in the step (1). For example, the step (3) may be performed before the step (2). The step (4) is performed after the step (2) and the step (3).
　図２Ａ～Ｅは、本実施の形態に係る画像処理方法において、各工程で得られる画像を模式的に示した図である。図２Ａは、工程Ｓ１１０で得られる細胞形態画像を示す。図２Ｂは、工程Ｓ１２０で抽出された特定の細胞の位置情報を示した画像を示す。図２Ｃは、工程Ｓ１１０で得られる蛍光画像である。図２Ｄは、工程Ｓ１３０で抽出された特定の生体物質の位置情報を示した画像を示す。図２Ｅは、工程Ｓ１４０において、特定の細胞の位置情報を示す画像と、特定の生体物質の位置情報を示す画像と、を重ね合わせた画像を示す。以下各工程について説明する。 2A to 2E are diagrams schematically showing images obtained in each step in the image processing method according to the present embodiment. FIG. 2A shows a cell morphology image obtained in step S110. FIG. 2B shows an image showing the position information of the specific cells extracted in step S120. FIG. 2C is a fluorescence image obtained in step S110. FIG. 2D shows an image showing the position information of the specific biological substance extracted in step S130. FIG. 2E shows an image in which an image showing the position information of a specific cell and an image showing the position information of a specific biological substance are superimposed in the step S140. Each process will be described below.
　１－１－１．細胞形態画像と蛍光画像とを入力する工程（工程Ｓ１１０）
　本工程では、組織切片における、特定の細胞を染色する色素により染色された前記特定の細胞の形態を示す細胞形態画像と、前記組織切片の前記細胞形態画像と同一範囲における、特定の生体物質を蛍光輝点で示す蛍光画像と、を入力する。たとえば、組織切片を作製し、特定の細胞を所定の色素で染色し、特定の生体物質を蛍光色素で染色し、細胞形態画像と蛍光画像を撮影してもよい。また、予め撮影された細胞形態画像および蛍光画像を、記憶媒体や通信回線などを介して入力してもよい。 1-1-1. Step of inputting cell morphology image and fluorescence image (step S110)
In this step, a cell morphology image showing the morphology of the specific cell stained with a dye that stains the specific cell in the tissue section and a specific biological substance in the same range as the cell morphology image of the tissue section are obtained. The fluorescent image indicated by the fluorescent bright spot and the fluorescent image are input. For example, a tissue section may be prepared, a specific cell may be stained with a predetermined dye, a specific biological substance may be stained with a fluorescent dye, and a cell morphology image and a fluorescent image may be taken. Further, the cell morphology image and the fluorescence image taken in advance may be input via a storage medium, a communication line, or the like.
　（１）細胞形態画像
　本実施の形態において、細胞形態画像は、組織切片において、特定の細胞を色素によって染色し、上記特定の細胞を示す領域を撮影した画像である（図２Ａ）。特定の細胞は、細胞質および細胞膜の少なくとも一方が染色されることが好ましい。特定の細胞を色素によって染色する方法は、特に限定されないが、例えば酵素抗体法による免疫組織化学染色である。酵素抗体法における酵素と基質の組み合わせは、特に限定されず、公知の酵素と基質の組み合わせから適宜選択されうる。抗体を標識する酵素と発色基質の組み合わせの例には、ペルオキシダーゼとジアミノベンジジン（ＤＡＢ）との組み合わせ（ＤＡＢ染色）、ペルオキシダーゼとアミノエチルカルバゾール（ＡＥＣ）との組み合わせ（ＡＥＣ染色）、アルカリフォスファターゼとＦａｓｔ　Ｒｅｄとの組み合わせ、アルカリフォスファターゼとＦａｓｔ　ｂｌｕｅとの組み合わせ、アルカリフォスファターゼとブロモクロロインドリルリン酸（ＢＣＩＰ）との組み合わせなどが含まれる。たとえば、特定の種類の細胞に発現するマーカータンパク質に直接または間接的に結合する抗体をペルオキシダーゼで標識しておき、この抗体を組織切片中のマーカータンパク質に結合させ、結合した抗体の周囲にジアミノベンジジン（ＤＡＢ）を提供することで、特定の種類の細胞のみを茶色に染色することができる。染色したい細胞の種類に応じて抗体を変えることで、染色対象の細胞の種類を変えることが可能である。 (1) Cell morphology image In the present embodiment, the cell morphology image is an image obtained by staining a specific cell with a dye in a tissue section and photographing a region showing the specific cell (FIG. 2A). For specific cells, it is preferable that at least one of the cytoplasm and the cell membrane is stained. The method for staining a specific cell with a dye is not particularly limited, and is, for example, immunohistochemical staining by an enzyme antibody method. The combination of the enzyme and the substrate in the enzyme antibody method is not particularly limited, and can be appropriately selected from known combinations of the enzyme and the substrate. Examples of combinations of the enzyme that labels the antibody and the chromogenic substrate include a combination of peroxidase and diaminobenzidine (DAB) (DAB staining), a combination of peroxidase and aminoethylcarbazole (AEC) (AEC staining), alkaline phosphatase and Fast. Included are combinations with Red, alkaline phosphatase with Fast blue, alkaline phosphatase with bromochloroindolyl phosphate (BCIP), and the like. For example, an antibody that binds directly or indirectly to a marker protein expressed in a particular type of cell is labeled with peroxidase, the antibody is bound to the marker protein in a tissue section, and diaminobenzidine is wrapped around the bound antibody. By providing (DAB), only certain types of cells can be stained brown. By changing the antibody according to the type of cells to be stained, it is possible to change the type of cells to be stained.
　以下に、パラフィン切片をＤＡＢ染色する場合の手順の一例を示す。ここでは、脱パラフィン処理と賦活化処理とを行った後に染色を行うこととする。 The following is an example of the procedure for DAB staining of paraffin sections. Here, the dyeing is performed after performing the deparaffinization treatment and the activation treatment.
　（脱パラフィン処理）
　キシレンを入れた容器にパラフィン切片を浸漬させ、パラフィンを除去する。温度は特に限定されないが、室温で行うことができる。浸漬時間は、３分以上３０分以下であることが好ましい。必要により浸漬途中でキシレンを交換してもよい。 (Deparaffin treatment)
The paraffin section is immersed in a container containing xylene to remove the paraffin. The temperature is not particularly limited, but it can be carried out at room temperature. The immersion time is preferably 3 minutes or more and 30 minutes or less. If necessary, xylene may be replaced during immersion.
　次いで、エタノールを入れた容器にパラフィンを除去した組織切片を浸漬させ、キシレンをエタノールに置換する。温度は特に限定されないが、室温で行うことができる。浸漬時間は、３分以上３０分以下であることが好ましい。必要により浸漬途中でエタノールを交換してもよい。 Next, the tissue section from which paraffin has been removed is immersed in a container containing ethanol, and xylene is replaced with ethanol. The temperature is not particularly limited, but it can be carried out at room temperature. The immersion time is preferably 3 minutes or more and 30 minutes or less. If necessary, ethanol may be replaced during immersion.
　次いで、水を入れた容器に組織切片を浸漬させ、エタノールを水に置換する。温度は特に限定されないが、室温で行うことができる。浸漬時間は、３分以上３０分以下であることが好ましい。必要により浸漬途中で水を交換してもよい。 Next, immerse the tissue section in a container containing water and replace ethanol with water. The temperature is not particularly limited, but it can be carried out at room temperature. The immersion time is preferably 3 minutes or more and 30 minutes or less. If necessary, the water may be replaced during the immersion.
　（賦活化処理）
　賦活化処理は、組織中の生体物質（抗体を結合させる抗原）を露出させる処理である。生体物質の種類によっては、賦活化処理は不要である。賦活化条件は、特に限定されず、生体物質（抗原）の種類に応じて適宜選択される。たとえば、賦活液としては、０．０１Ｍクエン酸緩衝液（ｐＨ６．０）１ｍＭ、ＥＤＴＡ溶液（ｐＨ８．０）、５％尿素、０．１Ｍトリス塩酸緩衝液などを用いることができる。加熱機器は、オートクレーブ、マイクロウェーブ、圧力鍋、ウォーターバスなどを用いることができる。加熱温度は５０℃以上１３０℃以下、時間は５分以上３０分以下で行うことができる。 (Activation process)
The activation treatment is a treatment for exposing a biological substance (antigen that binds an antibody) in a tissue. Depending on the type of biological material, activation treatment may not be necessary. The activation conditions are not particularly limited and are appropriately selected depending on the type of biological substance (antigen). For example, as the activating solution, 0.01 M citrate buffer (pH 6.0) 1 mM, EDTA solution (pH 8.0), 5% urea, 0.1 M Tris-hydrochloric acid buffer and the like can be used. As the heating device, an autoclave, a microwave, a pressure cooker, a water bath, or the like can be used. The heating temperature can be 50 ° C. or higher and 130 ° C. or lower, and the time can be 5 minutes or longer and 30 minutes or shorter.
　次いで、ＰＢＳ（リン酸緩衝生理食塩水）を入れた容器に、賦活化処理後の組織切片を浸漬させ、洗浄を行う。温度は特に限定されないが、室温で行うことができる。浸漬時間は、３分以上３０分以下であることが好ましい。必要により浸漬途中でＰＢＳを交換してもよい。 Next, the tissue section after the activation treatment is immersed in a container containing PBS (phosphate buffered saline) and washed. The temperature is not particularly limited, but it can be carried out at room temperature. The immersion time is preferably 3 minutes or more and 30 minutes or less. If necessary, the PBS may be replaced during the immersion.
　染色する前に、ＢＳＡ（ウシ血清アルブミン）含有ＰＢＳなどの公知のブロッキング剤を、組織切片に滴下することが好ましい。 Before staining, it is preferable to drop a known blocking agent such as PBS containing BSA (bovine serum albumin) onto the tissue section.
　（染色）
　一次抗体を含む液体を滴下し、所定の時間静置する。一次抗体は、染色対象の細胞に特異的に発現するマーカータンパク質に特異的に結合する抗体である。この後、組織切片を洗浄する。次いで、一次抗体を結合させた組織に、二次抗体を含む液体を滴下し、所定の時間静置する。二次抗体は、一次抗体に特異的に結合する抗体であり、ペルオキシダーゼで標識されている。この後、組織切片を洗浄する。次いで、二次抗体を結合させた組織に、ＤＡＢ染色液を滴下して染色する。 (staining)
The liquid containing the primary antibody is dropped and allowed to stand for a predetermined time. The primary antibody is an antibody that specifically binds to a marker protein that is specifically expressed in cells to be stained. After this, the tissue section is washed. Next, a liquid containing the secondary antibody is added dropwise to the tissue to which the primary antibody is bound, and the mixture is allowed to stand for a predetermined time. The secondary antibody is an antibody that specifically binds to the primary antibody and is labeled with peroxidase. After this, the tissue section is washed. Next, the DAB staining solution is dropped onto the tissue to which the secondary antibody is bound to stain the tissue.
　（細胞形態画像の取得）
　細胞形態画像は、公知のカメラ付き光学顕微鏡で撮影するなどして取得することができる。撮影して得られる細胞形態画像の視野は、３ｍｍ２以上であることが好ましく、３０ｍｍ２以上であることがより好ましく、３００ｍｍ２以上であることがさらに好ましい。細胞形態画像の視野の上限値は特に限定されないが、例えば、組織切片の大きさである。撮影された画像を、コンピュータなどの画像解析機器に送信するなどして、入力する。 (Acquisition of cell morphology image)
The cell morphology image can be obtained by taking a picture with a known optical microscope equipped with a camera. The visual field of the cell morphology image obtained by photographing is preferably 3 mm 2 or more, more preferably 30 mm 2 or more, and further preferably 300 mm 2 or more. The upper limit of the visual field of the cell morphology image is not particularly limited, but is, for example, the size of a tissue section. Input the captured image by sending it to an image analysis device such as a computer.
　（２）蛍光画像
　本実施の形態において、蛍光画像は、組織切片において、特定の生体物質を蛍光物質によって染色（標識）し、この蛍光物質による蛍光輝点を撮影した画像である（図２Ｃ）。蛍光画像に現れる蛍光輝点は、特定の生体物質の存在を示している。特定の生体物質を蛍光物質によって染色（標識）する方法は、特に限定されないが、例えば蛍光抗体法による免疫組織化学染色である。たとえば、特定の生体物質に直接または間接的に結合する抗体を蛍光物質で標識しておき、この抗体を組織切片中の生体物質に結合させ、励起光を照射することで、特定の生体物質の存在する部分のみから蛍光を放出させることができる。蛍光染色（標識）したい生体物質の種類に応じて抗体を変えることで、染色対象の生体物質の種類を変えることが可能である。特定の生体物質は、特に限定されず、目的に応じて適宜選択すればよいが、例えば、ＰＤ－１やＨｅｒ２などである。 (2) Fluorescent image In the present embodiment, the fluorescent image is an image obtained by staining (labeling) a specific biological substance with a fluorescent substance in a tissue section and photographing the fluorescent bright spot by the fluorescent substance (FIG. 2C). .. The fluorescent bright spots appearing in the fluorescent image indicate the presence of a particular biological material. The method for staining (labeling) a specific biological substance with a fluorescent substance is not particularly limited, and is, for example, immunohistochemical staining by a fluorescent antibody method. For example, an antibody that directly or indirectly binds to a specific biological substance is labeled with a fluorescent substance, and this antibody is bound to the biological substance in a tissue section and irradiated with excitation light to obtain the specific biological substance. Fluorescence can be emitted only from the existing part. By changing the antibody according to the type of biological substance to be fluorescently stained (labeled), it is possible to change the type of biological substance to be stained. The specific biological substance is not particularly limited and may be appropriately selected depending on the intended purpose, and is, for example, PD-1 or Her2.
　（蛍光物質）
　蛍光物質の種類は、特に限定されない。たとえば、蛍光物質は、蛍光有機色素または量子ドット（半導体粒子）である。抗体は、複数の蛍光有機色素または複数の量子ドットを含む蛍光物質内包ナノ粒子で標識されていてもよい。蛍光物質は、２００～７００ｎｍの波長の光により励起されたときに、４００～１１００ｎｍの波長の蛍光を放出することが好ましい。 (Fluorescent substance)
The type of fluorescent substance is not particularly limited. For example, the fluorescent material is a fluorescent organic dye or quantum dots (semiconductor particles). The antibody may be labeled with fluorescent material-encapsulating nanoparticles containing a plurality of fluorescent organic dyes or a plurality of quantum dots. The fluorescent material preferably emits fluorescence having a wavelength of 400 to 1100 nm when excited by light having a wavelength of 200 to 700 nm.
　蛍光有機色素は、例えば、フルオレセイン系色素分子、ローダミン系色素分子、ＡｌｅｘａＦｌｕｏｒ（インビトロジェン社製）系色素分子、ＢＯＤＩＰＹ（インビトロジェン社製）系色素分子、カスケード系色素分子、クマリン系色素分子、エオジン系色素分子、ＮＢＤ系色素分子、ピレン系色素分子、ＴｅｘａｓＲｅｄ系色素分子、シアニン系色素分子などである。蛍光有機色素の具体的な例には、５－カルボキシ－フルオレセイン、６－カルボキシ－フルオレセイン、５，６－ジカルボキシ－フルオレセイン、６－カルボキシ－２’，４，４’，５’，７，７’－ヘキサクロロフルオレセイン、６－カルボキシ－２’，４，７，７’－テトラクロロフルオレセイン、６－カルボキシ－４’，５’－ジクロロ－２’，７’－ジメトキシフルオレセイン、ナフトフルオレセイン、５－カルボキシ－ローダミン、６－カルボキシ－ローダミン、５，６－ジカルボキシ－ローダミン、ローダミン６Ｇ、テトラメチルローダミン、Ｘ－ローダミン、ＡｌｅｘａＦｌｕｏｒ３５０、ＡｌｅｘａＦｌｕｏｒ４０５、ＡｌｅｘａＦｌｕｏｒ４３０、ＡｌｅｘａＦｌｕｏｒ４８８、ＡｌｅｘａＦｌｕｏｒ５００、ＡｌｅｘａＦｌｕｏｒ５１４、ＡｌｅｘａＦｌｕｏｒ５３２、ＡｌｅｘａＦｌｕｏｒ５４６、ＡｌｅｘａＦｌｕｏｒ５５５、ＡｌｅｘａＦｌｕｏｒ５６８、ＡｌｅｘａＦｌｕｏｒ５９４、ＡｌｅｘａＦｌｕｏｒ６１０、ＡｌｅｘａＦｌｕｏｒ６３３、ＡｌｅｘａＦｌｕｏｒ６３５、ＡｌｅｘａＦｌｕｏｒ６４７、ＡｌｅｘａＦｌｕｏｒ６６０、ＡｌｅｘａＦｌｕｏｒ６８０、ＡｌｅｘａＦｌｕｏｒ７００、ＡｌｅｘａＦｌｕｏｒ７５０、ＢＯＤＩＰＹＦＬ、ＢＯＤＩＰＹＴＭＲ、ＢＯＤＩＰＹ４９３／５０３、ＢＯＤＩＰＹ５３０／５５０、ＢＯＤＩＰＹ５５８／５６８、ＢＯＤＩＰＹ５６４／５７０、ＢＯＤＩＰＹ５７６／５８９、ＢＯＤＩＰＹ５８１／５９１、ＢＯＤＩＰＹ６３０／６５０、ＢＯＤＩＰＹ６５０／６６５、メトキシクマリン、エオジン、ＮＢＤ、ピレン、Ｃｙ５、Ｃｙ５．５、Ｃｙ７などが含まれる。これらの蛍光有機色素は、単独で使用されてもよいし、混合して使用されてもよい。 Fluorescent organic dyes include, for example, fluorescein dye molecules, rhodamine dye molecules, AlexaFluor (Invitrogen) dye molecules, BODIPY (Invigen) dye molecules, cascade dye molecules, coumarin dye molecules, and eodin dyes. Molecules, NBD-based dye molecules, pyrene-based dye molecules, TexasRed-based dye molecules, cyanine-based dye molecules, and the like. Specific examples of fluorescent organic dyes include 5-carboxy-fluorescein, 6-carboxy-fluorescein, 5,6-dicarboxy-fluorescein, 6-carboxy-2', 4,4', 5', 7,7. '-Hexachlorofluorescein, 6-carboxy-2', 4,7,7'-tetrachlorofluorescein, 6-carboxy-4', 5'-dichloro-2', 7'-dimethoxyfluorescein, naphthofluorescein, 5-carboxy -Rhodamine, 6-carboxy-Rhodamine, 5,6-dicarboxy-Rhodamine, Rhodamine 6G, Tetramethyl Rhodamine, X-Rhodamine, Fluorescein350, Fluorescein405, Fluorescein430, AlexaFluor488, AlexaFluor500, AlexaFluor514, AlexaFluor5 , AlexaFluor610, AlexaFluor633, AlexaFluor635, AlexaFluor647, AlexaFluor660, AlexaFluor680, AlexaFluor700, AlexaFluor750, BODIPYFL, BODIPYTMR, BODIPY493 / 503, BODIPY530 / 550, BODIPY558 / 568, BODIPY564 / 570, BODIPY576 / 589, BODIPY581 / 591, BODIPY630 / 650, BODIPY650 / 665, methoxycoumarin, eodin, NBD, pyrene, Cy5, Cy5.5, Cy7 and the like are included. These fluorescent organic dyes may be used alone or in combination.
　量子ドットは、例えばＩＩ－ＶＩ族化合物を含有する量子ドット、ＩＩＩ－Ｖ化合物を含有する量子ドット、またはＩＶ族元素を成分として含有する量子ドットである。量子ドットを構成する半導体の例には、ＣｄＳｅ、ＣｄＳ、ＣｄＴｅ、ＺｎＳｅ、ＺｎＳ、ＺｎＴｅ、ＩｎＰ、ＩｎＮ、ＩｎＡｓ、ＩｎＧａＰ、ＧａＰ、ＧａＡｓ、Ｓｉ、Ｇｅが含まれる。これらの量子ドットも、単独で使用されてもよいし、混合して使用されてもよい。 The quantum dot is, for example, a quantum dot containing an II-VI group compound, a quantum dot containing a III-V compound, or a quantum dot containing a group IV element as a component. Examples of semiconductors constituting quantum dots include CdSe, CdS, CdTe, ZnSe, ZnS, ZnTe, InP, InN, InAs, InGaP, GaP, GaAs, Si, and Ge. These quantum dots may also be used alone or in combination.
　上記量子ドットをコアとし、その上にシェルを設けた量子ドットを用いることもできる。下記では、シェルを有する量子ドットの表記法として、コアがＣｄＳｅ、シェルがＺｎＳの場合、ＣｄＳｅ／ＺｎＳと表記する。コアシェル構造の量子ドットは、例えば、ＣｄＳｅ／ＺｎＳ、ＣｄＳ／ＺｎＳ、ＩｎＰ／ＺｎＳ、ＩｎＧａＰ／ＺｎＳ、Ｓｉ／ＳｉＯ２、Ｓｉ／ＺｎＳ、Ｇｅ／ＧｅＯ２、Ｇｅ／ＺｎＳなどである。 It is also possible to use a quantum dot having the above quantum dot as a core and a shell provided on the core. In the following, as the notation of the quantum dot having a shell, when the core is CdSe and the shell is ZnS, it is expressed as CdSe / ZnS. The quantum dots having a core-shell structure are, for example, CdSe / ZnS, CdS / ZnS, InP / ZnS, InGaP / ZnS, Si / SiO 2 , Si / ZnS, Ge / GeO 2 , Ge / ZnS, and the like.
　量子ドットは、有機ポリマーなどにより表面処理が施されていてもよい。そのような量子ドットは、例えば、表面カルボキシ基を有するＣｄＳｅ／ＺｎＳ（インビトロジェン社製）、表面アミノ基を有するＣｄＳｅ／ＺｎＳ（インビトロジェン社製）などである。 The quantum dots may be surface-treated with an organic polymer or the like. Such quantum dots are, for example, CdSe / ZnS having a surface carboxy group (manufactured by Invitrogen), CdSe / ZnS having a surface amino group (manufactured by Invitrogen), and the like.
　抗体に蛍光物質を結合させる方法は、特に限定されず、公知の方法から適宜選択されうる。 The method for binding the fluorescent substance to the antibody is not particularly limited, and can be appropriately selected from known methods.
　（蛍光物質内包ナノ粒子）
　蛍光物質内包ナノ粒子は、その内部に複数の蛍光物質が分散しているナノ粒子である。蛍光物質とナノ粒子自体とが化学的に結合していてもよいし、結合していなくてもよい。ナノ粒子を構成する素材は、特に限定されるものではなく、シリカ、ポリスチレン、ポリ乳酸、メラミンなどを挙げることができる。 (Fluorescent substance-encapsulating nanoparticles)
Fluorescent substance-encapsulating nanoparticles are nanoparticles in which a plurality of fluorescent substances are dispersed therein. The fluorescent substance and the nanoparticles themselves may or may not be chemically bonded. The material constituting the nanoparticles is not particularly limited, and examples thereof include silica, polystyrene, polylactic acid, and melamine.
　蛍光物質内包ナノ粒子は、公知の方法により作製することが可能である。たとえば、蛍光有機色素を内包したシリカナノ粒子は、ラングミュア８巻２９２１ページ（１９９２）に記載されているＦＩＴＣ内包シリカ粒子の合成を参考に合成することができる。ＦＩＴＣの代わりに所望の蛍光有機色素を用いることで、種々の蛍光有機色素内包シリカナノ粒子を合成することができる。量子ドットを内包したシリカナノ粒子は、ニュー・ジャーナル・オブ・ケミストリー３３巻５６１ページ（２００９年）に記載されているＣｄＴｅ内包シリカナノ粒子の合成を参考に合成することができる。蛍光有機色素を内包したポリスチレンナノ粒子は、米国特許４３２６００８に記載されている重合性官能基をもつ有機色素を用いた共重合法や、米国特許５３２６６９２に記載されているポリスチレンナノ粒子への蛍光有機色素の含浸法を用いて作製することができる。量子ドットを内包したポリマーナノ粒子は、ネイチャー・バイオテクノロジー１９巻６３１ページ（２００１年）に記載されているポリスチレンナノ粒子への量子ドットの含浸法を用いて作製することができる。 Fluorescent substance-encapsulating nanoparticles can be produced by a known method. For example, silica nanoparticles containing a fluorescent organic dye can be synthesized with reference to the synthesis of FITC-encapsulating silica particles described in Langmuir Vol. 8, p. 2921 (1992). By using a desired fluorescent organic dye instead of FITC, various fluorescent organic dye-encapsulating silica nanoparticles can be synthesized. Silica nanoparticles encapsulating quantum dots can be synthesized with reference to the synthesis of CdTe-encapsulating silica nanoparticles described in New Journal of Chemistry Vol. 33, p. 561 (2009). Polystyrene nanoparticles containing a fluorescent organic dye can be obtained by a copolymerization method using an organic dye having a polymerizable functional group described in US Pat. No. 4,326,008 or fluorescent organic to polystyrene nanoparticles described in US Pat. No. 5,326,692. It can be produced by using a dye impregnation method. Polymer nanoparticles containing quantum dots can be produced by using the method of impregnating polystyrene nanoparticles with quantum dots described in Nature Biotechnology, Vol. 19, pp. 631 (2001).
　蛍光物質内包ナノ粒子の平均粒径は、特に限定されないが、例えば３０～８００ｎｍである。また、粒径のばらつきを示す変動係数（＝（標準偏差／平均値）×１００％）は、特に限定されないが、２０％以下であることが好ましい。平均粒径は、走査型電子顕微鏡（ＳＥＭ）を用いて電子顕微鏡写真を撮影して十分な数の粒子について断面積を計測し、各計測値を円の面積としたときの円の直径を粒径として求めた値である。本実施の形態では、１０００個の粒子の粒径の算術平均を平均粒径とする。変動係数も、１０００個の粒子の粒径分布から算出した値とする。 The average particle size of the nanoparticles encapsulating the fluorescent substance is not particularly limited, but is, for example, 30 to 800 nm. The coefficient of variation (= (standard deviation / average value) × 100%) indicating the variation in particle size is not particularly limited, but is preferably 20% or less. For the average particle size, take an electron micrograph using a scanning electron microscope (SEM), measure the cross-sectional area of a sufficient number of particles, and use the diameter of the circle as the area of each measured value. It is a value obtained as a diameter. In this embodiment, the arithmetic mean of the particle sizes of 1000 particles is taken as the average particle size. The coefficient of variation is also a value calculated from the particle size distribution of 1000 particles.
　抗体に蛍光物質内包ナノ粒子を結合させる方法は、特に限定されず、公知の方法から適宜選択されうる。 The method for binding the nanoparticles containing the fluorescent substance to the antibody is not particularly limited, and can be appropriately selected from known methods.
　以下に、パラフィン切片を蛍光免疫染色する場合の手順の一例を示す。ここでは、脱パラフィン処理と賦活化処理とを行った後に蛍光免疫染色を行うこととする。 The following is an example of the procedure for fluorescent immunostaining of paraffin sections. Here, fluorescent immunostaining is performed after deparaffinization treatment and activation treatment.
　（脱パラフィン処理および賦活化処理）
　細胞形態画像の項で説明した脱パラフィン処理および賦活化処理と同様の操作を行う。染色する前に、ＢＳＡ（ウシ血清アルブミン）含有ＰＢＳなどの公知のブロッキング剤を、組織切片に滴下することが好ましい。 (Deparaffin treatment and activation treatment)
The same operation as the deparaffinization treatment and activation treatment described in the section of cell morphology image is performed. Prior to staining, a known blocking agent such as BSA (bovine serum albumin) -containing PBS is preferably added dropwise to the tissue section.
　（染色）
　一次抗体を含む液体を滴下し、所定の時間静置する。一次抗体は、染色対象の生体物質に特異的に結合する抗体である。この後、組織切片を洗浄する。次いで、一次抗体を結合させた組織に、二次抗体を含む液体を滴下し、所定の時間静置する。二次抗体は、一次抗体に特異的に結合する抗体であり、上記蛍光物質または蛍光物質内包ナノ粒子で標識されている。この後、組織切片を洗浄する。 (staining)
The liquid containing the primary antibody is dropped and allowed to stand for a predetermined time. The primary antibody is an antibody that specifically binds to the biological substance to be stained. After this, the tissue section is washed. Next, a liquid containing the secondary antibody is added dropwise to the tissue to which the primary antibody is bound, and the mixture is allowed to stand for a predetermined time. The secondary antibody is an antibody that specifically binds to the primary antibody, and is labeled with the fluorescent substance or the nanoparticles encapsulating the fluorescent substance. After this, the tissue section is washed.
　上記の細胞形態画像用の染色と、蛍光画像用の染色とを終えた後、組織切片を封入する。たとえば、染色された組織切片に市販の封入剤を滴下し、カバーガラスを載せればよい。 After completing the above-mentioned staining for the cell morphology image and the staining for the fluorescence image, the tissue section is enclosed. For example, a commercially available encapsulant may be dropped onto the stained tissue section and a cover glass may be placed on the stained tissue section.
　（蛍光画像の取得）
　蛍光画像は、公知のカメラ付き蛍光顕微鏡で撮影するなどして取得することができる。撮影するときは、使用した蛍光物質の吸収極大波長および蛍光波長に対応した励起光源および光学フィルターを用いる。蛍光画像の視野は、上記細胞形態画像の視野と同一範囲である。 (Acquisition of fluorescent image)
The fluorescence image can be obtained by taking a picture with a known fluorescence microscope equipped with a camera. When photographing, an excitation light source and an optical filter corresponding to the absorption maximum wavelength and the fluorescence wavelength of the fluorescent substance used are used. The field of view of the fluorescent image is the same range as the field of view of the cell morphology image.
　１－１－２．特定の細胞の位置情報を抽出する工程（工程Ｓ１２０）
　本工程では、工程Ｓ１１０で入力された細胞形態画像から、画像処理ソフト等を用いて、特定の細胞の位置情報を抽出する。図２Ｂは、抽出された特定の細胞の位置情報を示した画像を模式的に示す図である。図３は、本工程の一例を示すフローチャートである。 1-1-2. Step of extracting position information of a specific cell (step S120)
In this step, the position information of a specific cell is extracted from the cell morphology image input in step S110 by using image processing software or the like. FIG. 2B is a diagram schematically showing an image showing the position information of the extracted specific cells. FIG. 3 is a flowchart showing an example of this process.
　図３に示すように、本工程は、画像をグレースケールに変換する工程（工程Ｓ１２１）と、画像を２値化処理する工程（工程Ｓ１２２）と、ノイズ処理する工程（工程Ｓ１２４）と、ラベリング処理する工程（工程Ｓ１２５）と、を有する。なお、本工程は、Ｍｏｒｐｈｏｌｏｇｙ処理する工程（工程Ｓ１２３）をさらに有していてもよい。 As shown in FIG. 3, this step includes a step of converting an image to grayscale (step S121), a step of binarizing an image (step S122), a step of performing noise processing (step S124), and labeling. It has a step of processing (step S125). In addition, this step may further include a step (step S123) for performing a morphology treatment.
　画像をグレースケールに変換する工程（工程Ｓ１２１）では細胞形態画像をグレースケールに変換する。カラー画像（ＲＧＢ）は切片ごとに輝度にバラツキがあるためである。グレースケール変換の条件は、公知のものを適宜使用することができる。 In the step of converting the image to grayscale (step S121), the cell morphology image is converted to grayscale. This is because the brightness of the color image (RGB) varies from section to section. As the conditions for grayscale conversion, known ones can be appropriately used.
　画像を２値化処理する工程（工程Ｓ１２２）では、グレースケールに変換された細胞形態画像を２値化する。具体的には、グレースケールに変換された画像に対して、あらかじめ定められた閾値で閾値処理することで、各画素の値を２値化する。なお、２値化処理する画像は、ディープラーニング等の機械学習手法を用いて細胞形態画像から作成した、尤度画像であってもよい。 In the step of binarizing the image (step S122), the cell morphology image converted to gray scale is binarized. Specifically, the value of each pixel is binarized by performing the threshold value processing on the image converted to gray scale with a predetermined threshold value. The image to be binarized may be a likelihood image created from a cell morphology image using a machine learning technique such as deep learning.
　ノイズ処理する工程（工程Ｓ１２４）では、対象オブジェクト以外のオブジェクトをノイズと識別して除去する。すなわち、特定の細胞以外の部分を除去する工程である。具体的には、各オブジェクトの画素数を測定し、規定値以下の画素数を有するオブジェクトをノイズとして、背景色と同色に変換する。 In the noise processing step (step S124), objects other than the target object are identified as noise and removed. That is, it is a step of removing a portion other than a specific cell. Specifically, the number of pixels of each object is measured, and the object having the number of pixels equal to or less than the specified value is converted into the same color as the background color as noise.
　ラベリング処理する工程（工程Ｓ１２５）では、画像内のオブジェクトを識別するために、各細胞に番号を付してラベリングする。 In the labeling process (step S125), each cell is numbered and labeled in order to identify the object in the image.
　画像内に、細胞膜が寸断された細胞が存在する場合、画像を２値化処理する工程（工程Ｓ１２２）の後に、Ｍｏｒｐｈｏｌｏｇｙ処理をすることが好ましい。Ｍｏｒｐｈｏｌｏｇｙ処理をする工程（工程Ｓ１２３）では、細胞膜が寸断された細胞を、穴埋め処理し、細胞膜をひとつながりにする。 When cells whose cell membrane is shredded are present in the image, it is preferable to perform a morphology treatment after the step of binarizing the image (step S122). In the step of performing the morphology treatment (step S123), the cells whose cell membranes have been cut are filled with holes to connect the cell membranes.
　１－１－３．特定の生体物質の位置情報を抽出する工程（工程Ｓ１３０）
　本工程では、工程Ｓ１１０で入力された蛍光画像から、画像処理ソフト等を用いて、特定の生体物質の位置情報を抽出する。図２Ｄは、抽出された特定の生体物質の位置情報を示した画像を模式的に示す図である。図４は、実施の形態１に係る、本工程の一例を示すフローチャートである。 1-1-3. Step of extracting position information of a specific biological substance (step S130)
In this step, the position information of a specific biological substance is extracted from the fluorescent image input in step S110 by using image processing software or the like. FIG. 2D is a diagram schematically showing an image showing the position information of the extracted specific biological substance. FIG. 4 is a flowchart showing an example of this step according to the first embodiment.
　図４に示すように、本工程は、蛍光輝点の波長に応じた色成分を抽出する工程（工程Ｓ１３１）と、２値化処理する工程（工程Ｓ１３２）と、を有する。 As shown in FIG. 4, this step includes a step of extracting a color component corresponding to the wavelength of the fluorescent bright spot (step S131) and a step of binarizing the color component (step S132).
　蛍光輝点の波長に応じた色成分を抽出する工程（工程Ｓ１３１）では、例えば、蛍光画像における蛍光物質の発光波長が５５０ｎｍである場合には、その波長成分を有する蛍光輝点のみが画像として抽出される。 In the step of extracting the color component corresponding to the wavelength of the fluorescent bright spot (step S131), for example, when the emission wavelength of the fluorescent substance in the fluorescent image is 550 nm, only the fluorescent bright spot having that wavelength component is used as an image. Be extracted.
　２値化処理する工程（工程Ｓ１３２）では、色成分抽出後の蛍光画像に閾値処理をして２値画像を作製する。具体的には、各蛍光輝点の蛍光強度の積算値を算出し、正規化した蛍光強度をもとに、任意に設定した閾値以下の蛍光強度を有する蛍光輝点を除去し、２値画像を作製する。 In the step of binarizing (step S132), the fluorescent image after color component extraction is thresholded to create a binary image. Specifically, the integrated value of the fluorescence intensity of each fluorescence bright spot is calculated, and based on the normalized fluorescence intensity, the fluorescence bright spot having a fluorescence intensity equal to or lower than an arbitrarily set threshold value is removed, and a binary image is obtained. To make.
　なお、工程Ｓ１３２の閾値処理の前に、細胞の自家蛍光や他の不要な信号成分などのノイズ除去処理が施されてもよい。 Before the threshold value processing in step S132, noise reduction processing such as autofluorescence of cells and other unnecessary signal components may be performed.
　１－１－４．生体物質を判定する工程（Ｓ１４０）
　本工程では、工程Ｓ１２０および工程Ｓ１３０でそれぞれ抽出された、特定の細胞の位置情報および特定の生体物質の位置情報から、上記特定の生体物質が、上記特定の細胞から発現しているか否かを判定する。 1-1-4. Step of determining a biological substance (S140)
In this step, whether or not the specific biological substance is expressed from the specific cell is determined from the position information of the specific cell and the position information of the specific biological substance extracted in the steps S120 and S130, respectively. judge.
　特定の生体物質が、特定の細胞から発現しているか否かを判定する際は、特定の細胞の位置情報が抽出された画像と、特定の生体物質の位置情報が抽出された画像と、を重ね合わせることが好ましい。図２Ｅは、特定の細胞の位置情報が抽出された画像と、特定の生体物質の位置情報が抽出された画像と、を重ね合わせた画像を模式的に示す図である。 When determining whether or not a specific biological substance is expressed from a specific cell, an image in which the position information of the specific cell is extracted and an image in which the position information of the specific biological substance is extracted are displayed. Overlapping is preferred. FIG. 2E is a diagram schematically showing an image in which an image in which the position information of a specific cell is extracted and an image in which the position information of a specific biological substance is extracted are superimposed.
　特定の生体物質が特定の細胞から発現しているか否かを判定する際には、例えば、特定の生体物質の発現を示す蛍光輝点が、特定の細胞を示す領域内に位置するか否かで判定すればよい。上記蛍光輝点が、特定の細胞を示す領域の縁に位置していても、上記領域内に位置するとしてもよい。このとき、細胞形態画像における染色領域をＲＯＩ（Region of Interest）とすることがより好ましい。この判定方法では、上記蛍光輝点が、上記領域内に位置していれば、特定の生体物質が特定の細胞に発現していると判定され、上記蛍光輝点が上記領域内に位置していなければ、特定生体物質が特定の細胞に発現していないと判定される。 When determining whether or not a specific biological substance is expressed from a specific cell, for example, whether or not the fluorescent bright spot indicating the expression of the specific biological substance is located within the region indicating the specific cell. It can be judged by. The fluorescent bright spot may be located at the edge of a region indicating a specific cell, or may be located within the region. At this time, it is more preferable that the stained region in the cell morphology image is ROI (Region of Interest). In this determination method, if the fluorescent bright spot is located in the region, it is determined that a specific biological substance is expressed in a specific cell, and the fluorescent bright spot is located in the region. If not, it is determined that the specific biological substance is not expressed in the specific cell.
　特定の細胞に発現している特定の生体物質の数を定量するときは、本工程で特定の細胞に発現していると判定された特定の生体物質の数を算出すればよく、特定の細胞に発現していない特定の生体物質の数を定量するときは、特定の細胞に発現していないと判定された特定の生体物質の数を算出すればよい。 When quantifying the number of specific biological substances expressed in a specific cell, the number of specific biological substances determined to be expressed in a specific cell in this step may be calculated, and the specific cell may be calculated. When quantifying the number of specific biological substances that are not expressed in a specific cell, the number of specific biological substances determined not to be expressed in a specific cell may be calculated.
　１－１－５．適用例
　（キラーＴ細胞に発現するタンパク質ＰＤ－１の定量）
　上述した画像処理方法を用いて、キラーＴ細胞に発現するタンパク質ＰＤ－１の発現量を定量する例について説明する。 1-1-5. Application example (quantification of protein PD-1 expressed in killer T cells)
An example of quantifying the expression level of the protein PD-1 expressed in killer T cells by using the above-mentioned image processing method will be described.
　まず、組織切片に対して、上述した、脱パラフィン処理と賦活化処理とを行う。次いで、抗ＰＤ－１抗体（一次抗体）による一次反応と、蛍光物質で標識された二次抗体による二次反応を行い、ＰＤ－１を蛍光物質で標識する。また、キラーＴ細胞に発現するタンパク質ＣＤ８に特異的に結合する抗ＣＤ８抗体（一次抗体）による一次反応と、ペルオキシダーゼで標識された二次抗体による二次反応を行い、さらにジアミノベンジジン（ＤＡＢ）を提供して発色させて、キラーＴ細胞を染色する。これらの染色を終えた後、組織切片を封入する。 First, the tissue sections are subjected to the above-mentioned deparaffinization treatment and activation treatment. Next, a primary reaction with an anti-PD-1 antibody (primary antibody) and a secondary reaction with a secondary antibody labeled with a fluorescent substance are performed, and PD-1 is labeled with the fluorescent substance. In addition, a primary reaction with an anti-CD8 antibody (primary antibody) that specifically binds to the protein CD8 expressed on killer T cells and a secondary reaction with a secondary antibody labeled with peroxidase were performed, and diaminobenzidine (DAB) was further added. Donate and color to stain killer T cells. After completing these stainings, tissue sections are encapsulated.
　光学顕微鏡を用いて茶色に染色されたキラーＴ細胞を撮影し、細胞形態画像を取得する。また、蛍光顕微鏡を用いてＰＤ－１に間接的に結合している蛍光物質からの蛍光を撮影し、蛍光画像を取得する。 Using an optical microscope, photograph the brown-stained killer T cells and acquire a cell morphology image. In addition, fluorescence from a fluorescent substance indirectly bound to PD-1 is photographed using a fluorescence microscope, and a fluorescence image is acquired.
　得られた細胞形態画像をグレースケールに変換し、二値化処理、ノイズ処理、およびラベリング処理を施して、キラーＴ細胞の位置情報を抽出する（キラーＴ細胞の抽出画像を得る）。 The obtained cell morphology image is converted to gray scale, and binarization treatment, noise treatment, and labeling treatment are performed to extract the position information of the killer T cells (obtain the extracted image of the killer T cells).
　得られた蛍光画像において、蛍光輝点の波長に応じた色成分を抽出し、２値化処理して、ＰＤ－１の位置情報を抽出する。 In the obtained fluorescent image, the color component corresponding to the wavelength of the fluorescent bright spot is extracted, binarized, and the position information of PD-1 is extracted.
　組織切片の染色領域（キラーＴ細胞）をＲＯＩとし、上記細胞形態画像と上記蛍光画像を重ね合わせ、染色領域内に存在する蛍光輝点をキラーＴ細胞に発現するＰＤ－１と判定する。次いで、画像処理ソフトを用いて、上記判定されたＰＤ－１の数を測定する。 The stained region (killer T cell) of the tissue section is designated as ROI, the cell morphology image and the fluorescent image are superimposed, and the fluorescent bright spot existing in the stained region is determined to be PD-1 expressed in the killer T cell. Next, the number of PD-1 determined above is measured using image processing software.
　以上の手順により、ＰＤ－１の定量、ＰＤ－１が発現している細胞の特定、および当該細胞の種類の特定をすることができる。 By the above procedure, PD-1 can be quantified, cells expressing PD-1 can be specified, and the type of the cells can be specified.
　（腫瘍領域に発現するタンパク質Ｈｅｒ２の定量）
　上述した画像処理方法を用いて、腫瘍領域に発現するタンパク質Ｈｅｒ２の発現量を定量する例について説明する。 (Quantification of protein Her2 expressed in tumor region)
An example of quantifying the expression level of the protein Her2 expressed in the tumor region by using the above-mentioned image processing method will be described.
　まず、組織切片に対して、上述した、脱パラフィン処理と賦活化処理とを行う。次いで、抗Ｈｅｒ２抗体（一次抗体）による一次反応と、蛍光物質で標識された二次抗体による二次反応を行い、Ｈｅｒ２を蛍光物質で標識する。また、腫瘍領域に発現するタンパク質サイトケラチンに特異的に結合する抗サイトケラチン抗体（一次抗体）による一次反応と、ペルオキシダーゼで標識された二次抗体による二次反応を行い、さらにジアミノベンジジン（ＤＡＢ）を提供して発色させて、キラーＴ細胞を染色する。これらの染色を終えた後、組織切片を封入する。 First, the tissue sections are subjected to the above-mentioned deparaffinization treatment and activation treatment. Next, a primary reaction with an anti-Her2 antibody (primary antibody) and a secondary reaction with a secondary antibody labeled with a fluorescent substance are performed, and Her2 is labeled with the fluorescent substance. In addition, a primary reaction with an anti-cytokeratin antibody (primary antibody) that specifically binds to the protein cytokeratin expressed in the tumor region and a secondary reaction with a secondary antibody labeled with peroxidase were performed, and further, diaminobenzidine (DAB) was performed. To stain killer T cells by providing color. After completing these stainings, tissue sections are encapsulated.
　光学顕微鏡を用いて茶色に染色された腫瘍領域を撮影し、細胞形態画像を取得する。また、蛍光顕微鏡を用いてＨｅｒ２に間接的に結合している蛍光物質からの蛍光を撮影し、蛍光画像を取得する。 Using an optical microscope, photograph the tumor area stained brown and acquire a cell morphology image. In addition, a fluorescence microscope is used to photograph fluorescence from a fluorescent substance indirectly bound to Her2, and a fluorescence image is acquired.
　得られた細胞形態画像をグレースケールに変換し、二値化処理、ノイズ処理、およびラベリング処理を施して、腫瘍領域の位置情報を抽出する（腫瘍領域の抽出画像を得る）。 The obtained cell morphology image is converted to gray scale, and binarization treatment, noise treatment, and labeling treatment are performed to extract the position information of the tumor region (obtain the extracted image of the tumor region).
　得られた蛍光画像において、蛍光輝点の波長に応じた色成分を抽出し、２値化処理して、Ｈｅｒ２の位置情報を抽出する。 In the obtained fluorescent image, the color component corresponding to the wavelength of the fluorescent bright spot is extracted, binarized, and the position information of Her2 is extracted.
　組織切片の染色領域（腫瘍領域）をＲＯＩとし、上記細胞形態画像と上記蛍光画像を重ね合わせ、染色領域内に存在する蛍光輝点を腫瘍領域に発現するＨｅｒ２と判定する。次いで、画像処理ソフトを用いて、上記判定されたＨｅｒ２の数を測定する。 The stained region (tumor region) of the tissue section is designated as ROI, the cell morphology image and the fluorescent image are superimposed, and the fluorescent bright spot existing in the stained region is determined to be Her2 expressed in the tumor region. Next, the number of Her2 determined above is measured using image processing software.
　以上の手順により、Ｈｅｒ２の定量、Ｈｅｒ２が発現している細胞の特定、および当該細胞の種類の特定をすることができる。 By the above procedure, it is possible to quantify Her2, identify the cell expressing Her2, and identify the type of the cell.
　１－２．画像処理装置
　上記画像処理方法を実施するときに用いることができる、本発明の実施の形態１に係る画像処理装置について説明する。なお、本発明は、以下の実施の形態に限定されるものではない。 1-2. Image processing device The image processing device according to the first embodiment of the present invention, which can be used when the above image processing method is carried out, will be described. The present invention is not limited to the following embodiments.
　本発明の実施の形態１に係る画像処理装置は、組織切片における、特定の細胞を染色する色素により染色された前記特定の細胞の形態を示す細胞形態画像と、前記組織切片の前記細胞形態画像と同一範囲における、特定の生体物質を蛍光輝点で示す蛍光画像と、を入力する入力部と、前記細胞形態画像から、前記特定の細胞の位置情報を抽出する細胞抽出部と、前記蛍光画像から、前記特定の生体物質の位置情報を抽出する生体物質抽出部と、前記特定の細胞の位置情報と、前記特定の生体物質の位置情報とから、前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する生体物質発現判定部と、を有する。 The image processing apparatus according to the first embodiment of the present invention is a cell morphology image showing the morphology of the specific cells stained with a dye that stains the specific cells in the tissue section, and the cell morphology image of the tissue section. An input unit for inputting a fluorescent image showing a specific biological substance with a fluorescent bright spot in the same range as the above, a cell extraction unit for extracting position information of the specific cell from the cell morphology image, and the fluorescent image. From the biological substance extraction unit that extracts the positional information of the specific biological substance, the positional information of the specific cell, and the positional information of the specific biological substance, the specific biological substance is the specific cell. It has a biological substance expression determination unit for determining whether or not it is expressed from.
　図５は画像処理装置１００の機能的構成を概略的に示したブロック図である。画像処理装置１００は、入力部１０、制御部２０、操作部３０、表示部４０、記憶部５０を有する。画像処理装置１００は、外部の機器から送信または入力された、細胞形態画像および蛍光画像を解析し、特定の生体物質が、特定の細胞から発現しているか否かを判定する。 FIG. 5 is a block diagram schematically showing the functional configuration of the image processing apparatus 100. The image processing device 100 includes an input unit 10, a control unit 20, an operation unit 30, a display unit 40, and a storage unit 50. The image processing apparatus 100 analyzes a cell morphology image and a fluorescence image transmitted or input from an external device, and determines whether or not a specific biological substance is expressed from a specific cell.
　入力部１０は、前述の細胞形態画像および蛍光画像を入力する。入力部１０は、例えば、カメラを有する蛍光顕微鏡（光学顕微鏡としても機能できる）である。また、入力部１０は、外部装置（例えば前述の蛍光顕微鏡）から送られてきた画像情報、または記憶媒体に格納された画像情報を入力してもよい。 The input unit 10 inputs the above-mentioned cell morphology image and fluorescence image. The input unit 10 is, for example, a fluorescence microscope having a camera (which can also function as an optical microscope). Further, the input unit 10 may input image information sent from an external device (for example, the above-mentioned fluorescence microscope) or image information stored in a storage medium.
　図６は制御部２０の機能的構成を概略的に示したブロック図である。制御部２０は、ＣＰＵ（Central Processing Unit）、ＲＡＭ（Random Access Memory）などを有し、記憶部５０に記憶されている各種プログラムとの協働により各種処理を実行し、画像処理装置１００の動作を統括的に制御する。また、図５に示されるように、制御部２０は、細胞抽出部２１、生体物質抽出部２２、および生体物質発現判定部２３を有する。制御部２０は、記憶部５０に記憶されている画像処理プログラムとの協働により、細胞抽出部２１、生体物質抽出部２２、および生体物質発現判定部２３を機能させ、画像解析処理を実行する。 FIG. 6 is a block diagram schematically showing the functional configuration of the control unit 20. The control unit 20 has a CPU (Central Processing Unit), a RAM (Random Access Memory), and the like, executes various processes in cooperation with various programs stored in the storage unit 50, and operates the image processing device 100. Is controlled comprehensively. Further, as shown in FIG. 5, the control unit 20 includes a cell extraction unit 21, a biological substance extraction unit 22, and a biological substance expression determination unit 23. The control unit 20 functions the cell extraction unit 21, the biological material extraction unit 22, and the biological material expression determination unit 23 in cooperation with the image processing program stored in the storage unit 50 to execute the image analysis processing. ..
　細胞抽出部２１は、入力部１０で入力された細胞形態画像から、特定の細胞の位置情報を抽出する機能を有する。細胞抽出部２１は、細胞形態画像をグレースケールに変換し、２値化処理、ノイズ処理およびラベリング処理して、特定の細胞の位置情報を抽出する。なお、細胞抽出部２１は、細胞形態画像を２値化処理した後に、Ｍｏｒｐｈｏｌｏｇｙ処理して、特定の細胞の位置情報を抽出してもよい。 The cell extraction unit 21 has a function of extracting the position information of a specific cell from the cell morphology image input by the input unit 10. The cell extraction unit 21 converts the cell morphology image into gray scale and performs binarization treatment, noise treatment, and labeling treatment to extract the position information of a specific cell. The cell extraction unit 21 may perform a morphology treatment after binarizing the cell morphology image to extract the position information of a specific cell.
　生体物質抽出部２２は、入力部１０で入力された蛍光画像から、特定の生体物質の位置情報を抽出する機能を有する。生体物質抽出部では、蛍光画像から、蛍光輝点の波長に応じた色成分を抽出し、２値化処理して、生体物質の位置情報を抽出する。なお、生体物質抽出部２２は、２値化処理する前に、細胞自家蛍光や他の不要信号成分などのノイズ除去処理をして、生体物質の位置情報を抽出してもよい。 The biological substance extraction unit 22 has a function of extracting the position information of a specific biological substance from the fluorescent image input by the input unit 10. The biological substance extraction unit extracts the color component corresponding to the wavelength of the fluorescent bright spot from the fluorescent image, performs binarization processing, and extracts the position information of the biological substance. The biomaterial extraction unit 22 may extract the position information of the biomaterial by performing noise reduction processing such as cell autofluorescence and other unnecessary signal components before the binarization processing.
　生体物質発現判定部２３は、細胞抽出部２１で抽出された特定の細胞の位置情報と、生体物質抽出部２２で抽出された特定の生体物質の位置情報とから、特定の生体物質が、特定の細胞から発現しているか否かを判定する機能を有する。 The biological substance expression determination unit 23 identifies a specific biological substance from the position information of the specific cell extracted by the cell extraction unit 21 and the position information of the specific biological substance extracted by the biological substance extraction unit 22. It has a function of determining whether or not it is expressed from the cells of.
　制御部２０は、算出部２４をさらに有してもよい。算出部２４は、生体物質発現判定部２３で、特定の細胞から発現していると判定された、特定の生体物質、または、特定の細胞から発現していないと判定された特定の生体物質の数を算出する機能を有する。 The control unit 20 may further include a calculation unit 24. The calculation unit 24 is a specific biological substance determined to be expressed from a specific cell by the biological substance expression determination unit 23, or a specific biological substance determined not to be expressed from a specific cell. It has a function to calculate the number.
　操作部３０は、例えば、文字入力キー、数字入力キー、各種機能キーなどを含むキーボードと、マウスなどのポインティングデバイスとを有し、キーボードで押下操作されたキーの押下信号とポインティングデバイスによる操作信号とを、入力信号として制御部２０に出力する。 The operation unit 30 has, for example, a keyboard including character input keys, number input keys, various function keys, and a pointing device such as a mouse, and a key pressing signal operated by the keyboard and an operation signal by the pointing device. Is output to the control unit 20 as an input signal.
　表示部４０は、たとえばＣＲＴ（Cathode Ray Tube）やＬＣＤ（Liquid Crystal Display）などのモニタを備えて構成されており、制御部２０から入力される表示信号の指示に従って、各種画面を表示する。 The display unit 40 is configured to include a monitor such as a CRT (Cathode Ray Tube) or an LCD (Liquid Crystal Display), and displays various screens according to instructions of a display signal input from the control unit 20.
　なお、画像処理装置１００は、ＬＡＮアダプターやルーターなどを備え、ＬＡＮなどの通信ネットワークを介して外部機器と接続される構成としてもよい。 The image processing device 100 may be provided with a LAN adapter, a router, or the like, and may be configured to be connected to an external device via a communication network such as a LAN.
　記憶部５０は、たとえばＨＤＤ（Hard Disk Drive）や半導体の不揮発性メモリーなどで構成されている。記憶部５０には、前述のように各種プログラムや各種データなどが記憶されている。 The storage unit 50 is composed of, for example, an HDD (Hard Disk Drive) or a semiconductor non-volatile memory. As described above, various programs, various data, and the like are stored in the storage unit 50.
　１－３．画像処理プログラム
　上記画像処理装置において、画像解析処理を行うときに用いることができる、本発明の実施の形態１に係る画像処理プログラムについて説明する。なお、本発明は、以下の実施の形態に限定されるものではない。 1-3. Image processing program The image processing program according to the first embodiment of the present invention, which can be used when performing image analysis processing in the image processing apparatus, will be described. The present invention is not limited to the following embodiments.
　本発明の実施の形態１に係る画像処理プログラムは、コンピュータに、組織切片における、特定の細胞を染色する色素により染色された前記特定の細胞の形態を示す細胞形態画像と、前記組織切片の前記細胞形態画像と同一範囲における、特定の生体物質を蛍光輝点で示す蛍光画像と、を入力する工程と、前記細胞形態画像から、前記特定の細胞の位置情報を抽出する工程と、前記蛍光画像から、前記特定の生体物質の位置情報を抽出する工程と、前記特定の細胞の位置情報と、前記特定の生体物質の位置情報とから、前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する工程と、を実行させる。 In the image processing program according to the first embodiment of the present invention, a cell morphology image showing the morphology of the specific cells stained with a dye that stains the specific cells in the tissue section and the tissue section of the tissue section are described in a cell morphology image. A step of inputting a fluorescent image showing a specific biological substance with a fluorescent bright spot in the same range as the cell morphology image, a step of extracting position information of the specific cell from the cell morphology image, and the fluorescent image. From the step of extracting the position information of the specific biological substance, the position information of the specific cell, and the position information of the specific biological substance, the specific biological substance is expressed from the specific cell. The process of determining whether or not it is performed and the process of determining whether or not it is performed are executed.
　上記画像処理プログラムは、上記画像処理装置の制御部２０と協働して、細胞抽出部２１、生体物質抽出部２２、および生体物質発現判定部２３を機能させ、画像処理を実行する。 The image processing program cooperates with the control unit 20 of the image processing apparatus to function the cell extraction unit 21, the biological substance extraction unit 22, and the biological substance expression determination unit 23 to execute image processing.
　（効果）
　実施の形態１に係る画像処理方法、画像処理装置、および画像処理プログラムは、特定の生体物質が発現する細胞を特定し、上記特定の生体物質の発現量を定量化し、さらに上記特定の生体物質が発現する細胞の種類を特定することができる。 (effect)
The image processing method, the image processing apparatus, and the image processing program according to the first embodiment identify cells expressing a specific biological substance, quantify the expression level of the specific biological substance, and further, the specific biological substance. It is possible to identify the type of cell in which is expressed.
　２．実施の形態２
　２－１．画像処理方法
　実施の形態２に係る画像処理方法は、実施の形態１に係る画像処理方法の各工程に加えて、細胞形態画像から細胞核の位置情報を抽出する工程と、細胞核の位置情報と特定の細胞の位置情報から細胞核が特定の細胞の細胞核であるか否かを判定する工程と、特定の細胞の細胞核と判定された細胞核の位置情報と、特定の細胞から発現していると判定された生体物質の位置情報とから、特定の生体物質が帰属する細胞核を特定する工程と、をさらに有する。 2. 2. Embodiment 2
2-1. Image processing method In the image processing method according to the second embodiment, in addition to each step of the image processing method according to the first embodiment, a step of extracting the position information of the cell nucleus from the cell morphology image and a step of identifying the position information of the cell nucleus. The step of determining whether or not the cell nucleus is the cell nucleus of a specific cell from the cell position information of the cell, the position information of the cell nucleus determined to be the cell nucleus of the specific cell, and the determination that the cell nucleus is expressed from the specific cell. It further includes a step of identifying the cell nucleus to which the specific biological substance belongs from the position information of the biological substance.
　図７は、実施の形態２に係る画像処理方法のフローチャートである。 FIG. 7 is a flowchart of the image processing method according to the second embodiment.
　図７に示すように、実施の形態２に係る画像処理方法は、（１）細胞形態画像と、蛍光画像と、を入力する工程（工程Ｓ１１０）と、（２）前記細胞形態画像から、特定の細胞の位置情報を抽出する工程（工程Ｓ１２０）と、（Ａ）前記細胞形態画像から、細胞核の位置情報を抽出する工程（工程Ｓ２１０）と、（３）前記蛍光画像から、特定の生体物質の位置情報を抽出する工程（工程Ｓ１３０）と、（４）前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する工程（工程Ｓ１４０）と、（Ｂ）前記特定の細胞の位置情報から、前記細胞核が上記特定の細胞の細胞核であるか否かを判定する工程と（工程Ｓ２２０）、（Ｃ）前記特定の生体物質が帰属する細胞核を特定する工程（工程Ｓ２３０）と、を有する。 As shown in FIG. 7, the image processing method according to the second embodiment is specified from (1) a step of inputting a cell morphology image and a fluorescent image (step S110) and (2) the cell morphology image. A step of extracting the position information of the cell (step S120), (A) a step of extracting the position information of the cell nucleus from the cell morphology image (step S210), and (3) a specific biological substance from the fluorescent image. (Step S130), (4) a step of determining whether or not the specific biological substance is expressed from the specific cell, and (B) the specific biological substance. A step of determining whether or not the cell nucleus is the cell nucleus of the specific cell from the cell position information (step S220), and (C) a step of identifying the cell nucleus to which the specific biological substance belongs (step S230). And have.
　実施の形態２に係る画像処理方法は、（Ａ）前記細胞形態画像から、細胞核の位置情報を抽出する工程（工程Ｓ２１０）と、（Ｂ）前記特定の細胞の位置情報から、前記細胞核が上記特定の細胞の細胞核であるか否かを判定する工程と（工程Ｓ２２０）、（Ｃ）前記特定の生体物質が帰属する細胞核を特定する工程（工程Ｓ２３０）と、をさらに有する点で、実施の形態１と異なる。実施の形態１に係る画像処理方法と同じ構成要素については、同じ符号を付して説明を省略する。 The image processing method according to the second embodiment is as follows: (A) a step of extracting the position information of the cell nucleus from the cell morphology image (step S210), and (B) the cell nucleus is described above from the position information of the specific cell. It is carried out in that it further has a step of determining whether or not it is a cell nucleus of a specific cell (step S220) and (C) a step of specifying a cell nucleus to which the specific biological substance belongs (step S230). Different from Form 1. The same components as those of the image processing method according to the first embodiment are designated by the same reference numerals, and the description thereof will be omitted.
　図８Ａ～Ｅは、本実施の形態に係る画像処理方法において、各工程で得られる画像を模式的に示した図である。図８Ａは、工程Ｓ１１０で得られる細胞形態画像を示す。図８Ｂは、工程Ｓ１２０で抽出された特定の細胞の位置情報を示した画像を示す。図８Ｃは、工程Ｓ２１０で抽出された細胞核の位置情報を示した画像を示す。図８Ｄは、工程Ｓ１１０で得られる蛍光画像を示す。図８Ｅは、工程Ｓ１３０で抽出された特定の生体物質の位置情報を示した画像を示す。図８Ｆは、工程Ｓ１４０において、特定の細胞の位置情報を示す画像と、特定の生体物質の位置情報を示す画像と、を重ね合わせた画像を示す。以下各工程について説明する。 8A to 8E are diagrams schematically showing images obtained in each step in the image processing method according to the present embodiment. FIG. 8A shows a cell morphology image obtained in step S110. FIG. 8B shows an image showing the position information of the specific cells extracted in step S120. FIG. 8C shows an image showing the position information of the cell nucleus extracted in step S210. FIG. 8D shows the fluorescence image obtained in step S110. FIG. 8E shows an image showing the position information of the specific biological substance extracted in step S130. FIG. 8F shows an image in which an image showing the position information of a specific cell and an image showing the position information of a specific biological substance are superimposed in the step S140. Each process will be described below.
　２－１－１．細胞核の位置情報を抽出する工程（工程Ｓ２１０）
　本工程では、工程Ｓ１１０で入力された細胞形態画像から、細胞核の位置情報を抽出する。図９は、実施の形態２に係る、本工程の詳細を示したフローチャートである。 2-1-1. Step of extracting position information of cell nucleus (step S210)
In this step, the position information of the cell nucleus is extracted from the cell morphology image input in step S110. FIG. 9 is a flowchart showing the details of this step according to the second embodiment.
　実施の形態２において、細胞形態画像は、色素で染色された細胞の細胞核をさらに示す。細胞の細胞核を染色する色素は、特に限定されないが、例えば、ヘマトキシリンである。ヘマトキシリンによる染色は、脱パラフィン処理を行った後に行われる。たとえば、ヘマトキシリンを含む染色液にパラフィンを除去した組織切片を浸漬させて、組織切片をヘマトキシリンで染色する。次いで、ヘマトキシリンで染色した組織切片を流水に浸漬させて、色出しをする。 In Embodiment 2, the cell morphology image further shows the cell nuclei of the dye-stained cells. The dye that stains the cell nucleus is not particularly limited, but is, for example, hematoxylin. Staining with hematoxylin is performed after deparaffinization. For example, the tissue section from which paraffin has been removed is immersed in a staining solution containing hematoxylin, and the tissue section is stained with hematoxylin. Then, the tissue section stained with hematoxylin is immersed in running water to color it.
　本工程は、画像を２値化処理する工程（工程Ｓ２１１）と、ノイズ処理する工程（工程Ｓ２１２）と、ラベリング処理する工程（工程Ｓ２１３）と、を有する。 This step includes a step of binarizing the image (step S211), a noise processing step (step S212), and a labeling process (step S213).
　画像を２値化処理する工程（工程Ｓ２１１）では、細胞形態画像を、細胞核を染色した色に応じて、色分離してから２値化処理してもよいし、ディープラーニング等の機械学習手法を用いて細胞形態画像から細胞核の尤度画像を作成してから２値化処理してもよい。 In the step of binarizing the image (step S211), the cell morphology image may be color-separated according to the color stained with the cell nucleus and then binarized, or a machine learning method such as deep learning may be used. May be used to create a likelihood image of the cell nucleus from the cell morphology image and then binarization processing.
　工程Ｓ工程Ｓ２１２～Ｓ２１３は、それぞれ、実施の形態１における、工程Ｓ１２４～Ｓ１２５と同様であるため、詳しい説明は省略する。工程Ｓ２１１～Ｓ２１３の処理により細胞核の位置情報が抽出される。 Step S Steps S212 to S213 are the same as the steps S124 to S125 in the first embodiment, respectively, and therefore detailed description thereof will be omitted. The position information of the cell nucleus is extracted by the processing of steps S211 to S213.
　なお、本工程（工程Ｓ２１０）は、細胞形態画像および蛍光画像を入力する工程（工程Ｓ１１０）と細胞核を判定する工程（工程Ｓ２２０）の間に行われればよく、特定の細胞の位置情報を抽出する工程（Ｓ１２０）および特定の生体物質の位置情報を抽出する工程（工程Ｓ１３０）の前に行ってもよく、後に行ってもよい。 The present step (step S210) may be performed between the step of inputting the cell morphology image and the fluorescent image (step S110) and the step of determining the cell nucleus (step S220), and the position information of a specific cell is extracted. It may be performed before or after the step (S120) and the step of extracting the position information of a specific biological substance (step S130).
　２－１－２．細胞核を判定する工程（工程Ｓ２２０）
　本工程では、工程Ｓ２１０で抽出された特定の細胞の位置情報から、細胞核が特定の細胞の細胞核であるか否かを判定する。 2-1-2. Step of determining cell nucleus (step S220)
In this step, it is determined whether or not the cell nucleus is the cell nucleus of the specific cell from the position information of the specific cell extracted in the step S210.
　細胞核が特定の細胞の細胞核であるか否かを判定する方法は、細胞核が特定の細胞を示す領域内に位置するか否かを判定すればよい。細胞核が特定の細胞を示す領域内に位置するか否かは、細胞核の輪郭長に対する、特定の細胞を示す領域内にある細胞核の輪郭長の割合が、任意に設定される閾値よりも高いか否かで判定してもよい。また、細胞核の面積に対する、特定の細胞を示す領域内にある上記細胞核の面積の割合が、任意に設定される閾値よりも高いか否かで判定してもよい。この判定方法により、細胞核が特定の細胞を示す領域内に位置していれば、細胞核は特定の細胞の細胞核であると判定される。 As a method for determining whether or not the cell nucleus is the cell nucleus of a specific cell, it may be determined whether or not the cell nucleus is located in the region indicating the specific cell. Whether or not the cell nucleus is located in the region indicating a specific cell is whether the ratio of the contour length of the cell nucleus in the region indicating a specific cell to the contour length of the cell nucleus is higher than an arbitrarily set threshold value. It may be judged by whether or not. Further, it may be determined whether or not the ratio of the area of the cell nucleus in the region indicating a specific cell to the area of the cell nucleus is higher than an arbitrarily set threshold value. According to this determination method, if the cell nucleus is located in the region indicating a specific cell, the cell nucleus is determined to be the cell nucleus of the specific cell.
　なお、本工程は、細胞核の位置情報を抽出する工程（工程Ｓ２１０）の後であればよく、生体物質の判定（工程Ｓ１４０）の前に行ってもよい。 Note that this step may be performed after the step of extracting the position information of the cell nucleus (step S210) and may be performed before the determination of the biological substance (step S140).
　２－１－３．細胞核を特定する工程（工程Ｓ２３０）
　本工程では、工程Ｓ２２０で特定の細胞の細胞核と判定された細胞核の内、工程Ｓ１４０で特定の細胞から発現していると判定された、特定の生体物質が帰属する細胞核を特定する。 2-1-3. Step of identifying cell nucleus (step S230)
In this step, among the cell nuclei determined to be the cell nuclei of a specific cell in step S220, the cell nucleus to which the specific biological substance determined to be expressed from the specific cell in step S140 belongs is specified.
　特定の生体物質が帰属する細胞核を特定する方法は、特定の生体物質を示す蛍光輝点に最も近い細胞核に、帰属すると特定すればよい。具体的には、特定の細胞を示す領域内において、特定の細胞の細胞核と判定された細胞核の中心と、特定の生体物質を示す蛍光輝点の中心との距離が、最も近い細胞核が、特定の生体物質が帰属する細胞核であると特定する。なお、特定の細胞を示す領域外に存在する、特定の生体物質を示す蛍光輝点は、特定の細胞の細胞核と判定されなかった細胞核のうち、最も近い細胞核に帰属すると特定する。 The method of identifying the cell nucleus to which a specific biological substance belongs may be specified as belonging to the cell nucleus closest to the fluorescent bright spot indicating the specific biological substance. Specifically, in the region indicating a specific cell, the cell nucleus in which the distance between the center of the cell nucleus determined to be the cell nucleus of the specific cell and the center of the fluorescent bright spot indicating the specific biological substance is the shortest is specified. It is identified as the cell nucleus to which the biological material belongs. In addition, it is specified that the fluorescent bright spot indicating a specific biological substance existing outside the region indicating a specific cell belongs to the closest cell nucleus among the cell nuclei not determined to be the cell nucleus of the specific cell.
　特定の細胞の細胞核に発現している特定の生体物質の数を定量するときは、特定の細胞の細胞核と判定された細胞核に帰属すると特定された特定の生体物質の数を算出すればよい。特定の細胞の細胞核に発現していない特定の生体物質の数を定量するときは、特定の細胞の細胞核と判定されなかった細胞核に帰属すると特定された特定の生体物質の数を算出すればよい。 When quantifying the number of specific biological substances expressed in the cell nucleus of a specific cell, the number of specific biological substances identified as belonging to the cell nucleus determined to be the cell nucleus of the specific cell may be calculated. When quantifying the number of specific biological substances that are not expressed in the cell nucleus of a specific cell, the number of specific biological substances identified as belonging to the cell nucleus that was not determined to be the cell nucleus of the specific cell may be calculated. ..
　２－１－４．適用例
　（キラーＴ細胞に発現するタンパク質ＰＤ－１の発現元の特定）
　上述した画像処理方法を用いて、キラーＴ細胞に発現するタンパク質ＰＤ－１の発現量を定量する例について説明する。 2-1-4. Application example (identification of the expression source of protein PD-1 expressed in killer T cells)
An example of quantifying the expression level of the protein PD-1 expressed in killer T cells by using the above-mentioned image processing method will be described.
　まず、組織切片に対して、上述した、脱パラフィン処理と賦活化処理とを行う。次いで、抗ＰＤ－１抗体（一次抗体）による一次反応と、蛍光物質で標識された二次抗体による二次反応を行い、ＰＤ－１を蛍光物質で標識する。また、キラーＴ細胞に発現するタンパク質ＣＤ８に特異的に結合する抗ＣＤ８抗体（一次抗体）による一次反応と、ペルオキシダーゼで標識された二次抗体による二次反応を行い、さらにジアミノベンジジン（ＤＡＢ）を提供して発色させて、キラーＴ細胞を染色する。また、ヘマトキシリンで各細胞の細胞核を染色する。これらの染色を終えた後、組織切片を封入する。 First, the tissue sections are subjected to the above-mentioned deparaffinization treatment and activation treatment. Next, a primary reaction with an anti-PD-1 antibody (primary antibody) and a secondary reaction with a secondary antibody labeled with a fluorescent substance are carried out, and PD-1 is labeled with the fluorescent substance. In addition, a primary reaction with an anti-CD8 antibody (primary antibody) that specifically binds to the protein CD8 expressed on killer T cells and a secondary reaction with a secondary antibody labeled with peroxidase were performed, and diaminobenzidine (DAB) was further added. Donate and color to stain killer T cells. In addition, the cell nucleus of each cell is stained with hematoxylin. After completing these stainings, tissue sections are encapsulated.
　光学顕微鏡を用いて、茶色に染色されたキラーＴ細胞と、青紫色に染色された細胞核を撮影し、細胞形態画像を取得する。また、蛍光顕微鏡を用いてＰＤ－１に間接的に結合している蛍光物質からの蛍光を撮影し、蛍光画像を取得する。 Using an optical microscope, photograph the killer T cells stained in brown and the cell nuclei stained in bluish purple, and acquire a cell morphology image. In addition, fluorescence from a fluorescent substance indirectly bound to PD-1 is photographed using a fluorescence microscope, and a fluorescence image is acquired.
　得られた細胞形態画像をグレースケールに変換し、二値化処理、ノイズ処理、およびラベリング処理を施して、キラーＴ細胞の位置情報を抽出する（キラーＴ細胞の抽出画像を得る）。 The obtained cell morphology image is converted to gray scale, and binarization treatment, noise treatment, and labeling treatment are performed to extract the position information of the killer T cells (obtain the extracted image of the killer T cells).
　また、得られた細胞形態画像から、ディープラーニングを用いて、細胞核の尤度画像を作成し、二値化処理、ノイズ処理、およびラベリング処理を施して、細胞核の位置情報を抽出する（細胞核の抽出画像を得る）。 In addition, from the obtained cell morphology image, a likelihood image of the cell nucleus is created using deep learning, and binarization treatment, noise treatment, and labeling treatment are performed to extract the position information of the cell nucleus (cell nucleus). Get the extracted image).
　得られた蛍光画像において、蛍光輝点の波長に応じた色成分を抽出し、２値化処理して、ＰＤ－１の位置情報を抽出する。 In the obtained fluorescent image, the color component corresponding to the wavelength of the fluorescent bright spot is extracted, binarized, and the position information of PD-1 is extracted.
　組織切片の染色領域（キラーＴ細胞）をＲＯＩとし、上記細胞形態画像と上記蛍光画像を重ね合わせ、染色領域内に存在する、蛍光輝点を、キラーＴ細胞に発現するＰＤ－１と判定する。 The stained region (killer T cell) of the tissue section is designated as ROI, the cell morphology image and the fluorescent image are superimposed, and the fluorescent bright spot existing in the stained region is determined to be PD-1 expressed in the killer T cell. ..
　上記染色領域（キラーＴ細胞）内に位置する、ヘマトキシリンに染色された細胞核を、キラーＴ細胞の細胞核と判定する。 The hematoxylin-stained cell nucleus located in the stained area (killer T cell) is determined to be the cell nucleus of the killer T cell.
　上記染色領域（キラーＴ細胞）内において、判定されたキラーＴ細胞の細胞核との中心と、キラーＴ細胞に発現すると判定されたＰＤ－１を示す蛍光輝点の中心との距離を、それぞれ測定し、蛍光輝点から最も近くに位置する細胞核が、ＰＤ－１が帰属する細胞核であると特定する。上記染色領域（キラーＴ細胞）外に存在する、ＰＤ－１を示す蛍光輝点は、キラーＴ細胞の細胞核と判定されなかった細胞核との中心間距離が、最も近い細胞核に帰属すると特定する。 Within the staining region (killer T cell), the distance between the center of the determined killer T cell nucleus and the center of the fluorescent bright spot indicating PD-1 determined to be expressed in the killer T cell is measured. Then, the cell nucleus located closest to the fluorescent bright spot is identified as the cell nucleus to which PD-1 belongs. The fluorescent bright spot indicating PD-1 existing outside the stained region (killer T cell) identifies that the center-to-center distance between the cell nucleus of the killer T cell and the cell nucleus not determined to belong to the closest cell nucleus.
　画像処理ソフトを用いて、キラーＴ細胞に発現すると判定されたＰＤ－１の数、および判定されたキラーＴ細胞の細胞核の数を、それぞれ測定する。測定したキラーＴ細胞に発現するＰＤ－１の数を、判定されたキラーＴ細胞の細胞核の数で割ることで、キラーＴ細胞の細胞核１個あたりのＰＤ－１の数を算出する。 Using image processing software, measure the number of PD-1 determined to be expressed in killer T cells and the number of cell nuclei of the determined killer T cells, respectively. The number of PD-1 per cell nucleus of the killer T cell is calculated by dividing the measured number of PD-1 expressed in the killer T cell by the number of the determined cell nuclei of the killer T cell.
　以上の手順により、ＰＤ－１の定量、ＰＤ－１が発現している細胞および細胞核の特定、および当該細胞の種類の特定をすることができる。 By the above procedure, it is possible to quantify PD-1, identify cells expressing PD-1 and cell nuclei, and identify the type of the cells.
　２－２．画像処理装置
　図１０は、実施の形態２に係る、画像処理装置２００の機能的構成を概略的に示したブロック図であり、図１１は、実施の形態２に係る、画像処理装置の制御部２０の機能的構成を概略的に示したブロック図である。実施の形態２に係る画像処理装置２００は、制御部２０が細胞核抽出部２５、細胞核判定部２６、および細胞核特定部２７をさらに有する点で実施の形態１に係る画像処理装置１００と異なる。実施の形態１に係る画像処理装置１００と同じ構成要素については、同じ符号を付して説明を省略する。 2-2. Image processing device FIG. 10 is a block diagram schematically showing a functional configuration of the image processing device 200 according to the second embodiment, and FIG. 11 is a control unit of the image processing device according to the second embodiment. It is a block diagram which roughly showed the functional structure of 20. The image processing apparatus 200 according to the second embodiment is different from the image processing apparatus 100 according to the first embodiment in that the control unit 20 further includes the cell nucleus extraction unit 25, the cell nucleus determination unit 26, and the cell nucleus identification unit 27. The same components as those of the image processing apparatus 100 according to the first embodiment are designated by the same reference numerals, and the description thereof will be omitted.
　細胞核抽出部２５は、入力部１０で入力された細胞形態画像から細胞核の位置情報を抽出する機能を有する。細胞核抽出部２５では、細胞形態画像を２値化処理、ノイズ処理およびラベリング処理して、細胞核の位置情報を抽出する。２値化処理は、細胞形態画像を、細胞核を染色した色に応じて、色分離してから２値化処理してもよいし、ディープラーニング等の機械学習手法を用いて細胞形態画像から細胞核の尤度画像を作成してから２値化処理してもよい。 The cell nucleus extraction unit 25 has a function of extracting the position information of the cell nucleus from the cell morphology image input by the input unit 10. The cell nucleus extraction unit 25 performs binarization treatment, noise treatment, and labeling treatment on the cell morphology image to extract the position information of the cell nucleus. In the binarization treatment, the cell morphology image may be color-separated according to the color of the cell nucleus stained, and then the binarization treatment may be performed, or the cell nucleus may be subjected to the binarization treatment using a machine learning method such as deep learning. After creating the likelihood image of, the binarization process may be performed.
　細胞核判定部２６は、細胞抽出部２１で抽出された特定の細胞の位置情報から、細胞核抽出部２５で抽出された細胞核が、特定の細胞の細胞核であるかを判定する機能を有する。 The cell nucleus determination unit 26 has a function of determining whether the cell nucleus extracted by the cell nucleus extraction unit 25 is the cell nucleus of a specific cell from the position information of the specific cell extracted by the cell extraction unit 21.
　細胞核特定部２７は、細胞核判定部２６で特定の細胞の細胞核と判定された細胞核の位置情報と、生体物質発現判定部２３で、特定の細胞から発現すると判定された特定の生体物質の位置情報とから、特定の生体物質が帰属する細胞核を特定する機能を有する。 The cell nucleus specifying unit 27 contains the position information of the cell nucleus determined to be the cell nucleus of the specific cell by the cell nucleus determination unit 26 and the position information of the specific biological substance determined to be expressed from the specific cell by the biological substance expression determination unit 23. Therefore, it has a function of specifying the cell nucleus to which a specific biological substance belongs.
　２－３．画像処理プログラム
　実施の形態２に係る画像処理プログラムは、細胞形態画像から、細胞核の位置情報を抽出する工程と、上記細胞核の位置情報と、上記特定の細胞の位置情報から、上記細胞核が上記特定の細胞核であるか否かを判定する工程と、上記特定の細胞の細胞核と判定された細胞核の位置情報と、上記特定の細胞から発現していると判定された生体物質の位置情報とから、上記特定の生体物質が帰属する細胞核を特定する工程と、をさらに実行させる点で、実施の形態１と異なる。実施の形態１に係る画像処理プログラムと同じ構成要素については、同じ符号を付して説明を省略する。 2-3. Image processing program In the image processing program according to the second embodiment, the cell nucleus is specified from the step of extracting the position information of the cell nucleus from the cell morphology image, the position information of the cell nucleus, and the position information of the specific cell. From the step of determining whether or not the cell nucleus is a cell nucleus, the position information of the cell nucleus determined to be the cell nucleus of the specific cell, and the position information of the biological substance determined to be expressed from the specific cell. It differs from the first embodiment in that the step of specifying the cell nucleus to which the specific biological substance belongs is further executed. The same components as those of the image processing program according to the first embodiment are designated by the same reference numerals, and the description thereof will be omitted.
　上記画像処理プログラムは、上記画像処理装置の制御部２０と協働して、細胞抽出部２１、生体物質抽出部２２、生体物質発現判定部２３、細胞核抽出部２５、細胞核判定部２６、および細胞核特定部２７を機能させ、画像処理を実行する。 The image processing program cooperates with the control unit 20 of the image processing apparatus to perform a cell extraction unit 21, a biological material extraction unit 22, a biological material expression determination unit 23, a cell nucleus extraction unit 25, a cell nucleus determination unit 26, and a cell nucleus. The specific unit 27 is made to function and image processing is executed.
　（効果）
　実施の形態２に係る画像処理方法、画像処理装置、および画像処理プログラムは、実施の形態１に係る画像処理方法、画像処理装置、および画像処理プログラムの効果に加え、特定の生体物質が発現する細胞核を特定することができる。 (effect)
In the image processing method, the image processing apparatus, and the image processing program according to the second embodiment, in addition to the effects of the image processing method, the image processing apparatus, and the image processing program according to the first embodiment, a specific biological substance is expressed. The cell nucleus can be identified.
　本出願は、２０２０年９月１５日出願の特願２０２０－１５４８１７に基づく優先権を主張する。当該出願明細書および図面に記載された内容は、全て本願明細書に援用される。 This application claims priority based on Japanese Patent Application No. 2020-154817 filed on September 15, 2020. All the contents described in the application specification and drawings are incorporated herein by reference.
　本発明によれば、細胞内の生体物質の定量化、生体物質が発現している細胞の特定、および当該細胞の種類の特定を、少ない種類の色素を用いて簡単な工程で行うことができる画像処理方法を提供できる。たとえば、本発明は、病理診断などに有用である。 According to the present invention, the quantification of an intracellular biological substance, the identification of a cell expressing a biological substance, and the identification of the type of the cell can be performed by a simple step using a small number of dyes. An image processing method can be provided. For example, the present invention is useful for pathological diagnosis and the like.
　１　特定の細胞を示す領域
　２　細胞核
　３　特定の細胞以外の細胞
　４　特定の生体物質を示す蛍光輝点
　５　ノイズ　
　１０　入力部
　２０　制御部
　２１　細胞抽出部
　２２　生体物質抽出部
　２３　生体物質発現判定部
　２４　算出部
　２５　細胞核抽出部
　２６　細胞核判定部
　２７　細胞核特定部
　３０　操作部
　４０　表示部
　５０　記憶部
　Ｓ１１０　細胞形態画像および蛍光画像を入力する工程
　Ｓ１２０　特定の細胞の位置情報を抽出する工程
　Ｓ１３０　特定の生体物質を抽出する工程
　Ｓ１４０　生体物質を判定する工程
　Ｓ２１０　細胞核の位置情報を抽出する工程
　Ｓ２２０　細胞核を判定する工程
　Ｓ２３０　細胞核を特定する工程 1 Region indicating a specific cell 2 Cell nucleus 3 Cell other than a specific cell 4 Fluorescent bright spot indicating a specific biological substance 5 Noise
10 Input unit 20 Control unit 21 Cell extraction unit 22 Biomaterial extraction unit 23 Biomaterial expression determination unit 24 Calculation unit 25 Cell nucleus extraction unit 26 Cell nucleus determination unit 27 Cell nucleus identification unit 30 Operation unit 40 Display unit 50 Storage unit S110 Cell morphology image and Step to input fluorescent image S120 Step to extract position information of specific cell S130 Step to extract specific biological substance S140 Step to judge biological substance S210 Step to extract position information of cell nucleus S220 Step to judge cell nucleus S230 Cell nucleus Process to identify

Claims (8)

  1. 　組織切片における、特定の細胞を染色する色素により染色された前記特定の細胞の形態を示す細胞形態画像と、前記組織切片の前記細胞形態画像と同一範囲における、特定の生体物質を蛍光輝点で示す蛍光画像と、を入力する工程と、
    　前記細胞形態画像から、前記特定の細胞の位置情報を抽出する工程と、
    　前記蛍光画像から、前記特定の生体物質の位置情報を抽出する工程と、
    　前記特定の細胞の位置情報と、前記特定の生体物質の位置情報とから、前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する工程と、
    　を有する、画像処理方法。     A cell morphology image showing the morphology of the specific cell stained with a dye that stains the specific cell in the tissue section, and a specific biological substance in the same range as the cell morphology image of the tissue section at a fluorescent bright spot. The process of inputting the fluorescent image to be shown, and
    A step of extracting the position information of the specific cell from the cell morphology image and
    A step of extracting the position information of the specific biological substance from the fluorescent image, and
    A step of determining whether or not the specific biological substance is expressed from the specific cell from the position information of the specific cell and the position information of the specific biological substance.
    An image processing method.
  2. 　前記細胞形態画像は、細胞の細胞核をさらに示し、
    　前記画像処理方法は、
    　前記細胞形態画像から、前記細胞核の位置情報を抽出する工程と、
    　前記細胞核の位置情報と、前記特定の細胞の位置情報から、前記細胞核が前記特定の細胞の細胞核であるか否かを判定する工程と、
    　前記特定の細胞の細胞核と判定された細胞核の位置情報と、前記特定の細胞から発現していると判定された生体物質の位置情報とから、前記特定の生体物質が帰属する細胞核を特定する工程と、をさらに有する、
    　請求項１に記載の画像処理方法。     The cell morphology image further shows the cell nucleus of the cell.
    The image processing method is
    A step of extracting the position information of the cell nucleus from the cell morphology image and
    A step of determining whether or not the cell nucleus is the cell nucleus of the specific cell from the position information of the cell nucleus and the position information of the specific cell.
    A step of identifying the cell nucleus to which the specific biological substance belongs from the position information of the cell nucleus determined to be the cell nucleus of the specific cell and the position information of the biological substance determined to be expressed from the specific cell. And have more,
    The image processing method according to claim 1.
  3. 　前記色素は、前記特定の細胞の細胞質および細胞膜の少なくとも一方を染色する、請求項１または２に記載の画像処理方法。 The image processing method according to claim 1 or 2, wherein the dye stains at least one of the cytoplasm and the cell membrane of the specific cell.
  4. 　前記特定の生体物質が前記特定の細胞から発現しているか否かを判定する工程では、前記蛍光輝点が前記特定の細胞を示す領域内に位置するか否かを判定する、請求項１～３のいずれか一項に記載の画像処理方法。 Claims 1 to 1, wherein in the step of determining whether or not the specific biological substance is expressed from the specific cell, it is determined whether or not the fluorescent bright spot is located in the region indicating the specific cell. The image processing method according to any one of 3.
  5. 　前記細胞核が前記特定の細胞の細胞核であるか否かを判定する工程では、前記細胞核が前記特定の細胞を示す領域内に位置するか否かを判定する、請求項２に記載の画像処理方法。 The image processing method according to claim 2, wherein in the step of determining whether or not the cell nucleus is the cell nucleus of the specific cell, it is determined whether or not the cell nucleus is located in the region indicating the specific cell. ..
  6. 　前記特定の生体物質が帰属する細胞核を特定する工程では、前記特定の細胞の細胞核と判定された細胞核のうち、前記特定の生体物質を示す蛍光輝点に最も近い細胞核に、前記特定の生体物質が帰属すると判定する、請求項２に記載の画像処理方法。 In the step of identifying the cell nucleus to which the specific biological substance belongs, among the cell nuclei determined to be the cell nuclei of the specific cell, the cell nucleus closest to the fluorescent bright spot indicating the specific biological substance is the specific biological substance. The image processing method according to claim 2, wherein the image processing method is determined to belong to.
  7. 　組織切片における、特定の細胞を染色する色素により染色された前記特定の細胞の形態を示す細胞形態画像と、前記組織切片の前記細胞形態画像と同一範囲における、特定の生体物質を蛍光輝点で示す蛍光画像と、を入力する入力部と、
    　前記細胞形態画像から、前記特定の細胞の位置情報を抽出する細胞抽出部と、
    　前記蛍光画像から、前記特定の生体物質の位置情報を抽出する生体物質抽出部と、
    　前記特定の細胞の位置情報と、前記特定の生体物質の位置情報とから、前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する生体物質発現判定部と、
    　を有する、画像処理装置。     A cell morphology image showing the morphology of the specific cell stained with a dye that stains the specific cell in the tissue section, and a specific biological substance in the same range as the cell morphology image of the tissue section at a fluorescent bright spot. The fluorescent image shown, the input unit for inputting, and
    A cell extraction unit that extracts the position information of the specific cell from the cell morphology image,
    A biological substance extraction unit that extracts the position information of the specific biological substance from the fluorescent image,
    A biological substance expression determination unit that determines whether or not the specific biological substance is expressed from the specific cell from the position information of the specific cell and the position information of the specific biological substance.
    An image processing device.
  8. 　コンピュータに、
    　組織切片における、特定の細胞を染色する色素により染色された前記特定の細胞の形態を示す細胞形態画像と、前記組織切片の前記細胞形態画像と同一範囲における、特定の生体物質を蛍光輝点で示す蛍光画像と、を入力する工程と、
    　前記細胞形態画像から、前記特定の細胞の位置情報を抽出する工程と、
    　前記蛍光画像から、前記特定の生体物質の位置情報を抽出する工程と、
    　前記特定の細胞の位置情報と、前記特定の生体物質の位置情報とから、前記特定の生体物質が、前記特定の細胞から発現しているか否かを判定する工程と、
    　を実行させる、
    　画像処理プログラム。     On the computer
    A cell morphology image showing the morphology of the specific cell stained with a dye that stains the specific cell in the tissue section, and a specific biological substance in the same range as the cell morphology image of the tissue section at a fluorescent bright spot. The process of inputting the fluorescent image to be shown, and
    A step of extracting the position information of the specific cell from the cell morphology image and
    A step of extracting the position information of the specific biological substance from the fluorescent image, and
    A step of determining whether or not the specific biological substance is expressed from the specific cell from the position information of the specific cell and the position information of the specific biological substance.
    To execute,
    Image processing program.
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