Stem cell detection device, stem cell detection system, stem cell detection method, and stem cell detection program

Abstract

To noninvasively detect stem cells in simple and precise manner.SOLUTION: A stem cell detection device is provided that includes an image data acquisition unit that acquires three-dimensional image data of an object including a cell, and a stem cell detection unit that detects a stem cell included in the object, by using the three-dimensional image data and predetermined stem cell morphological features.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present disclosure relates to stem cell detection techniques. [Background technology]

[0002] In the analysis of stem cells, a method of taking a biopsy and performing a staining process before analysis is generally used. Stem cells are also contained in the human epidermis, and homeostasis is maintained in the human epidermis by turnover, in which cells are periodically regenerated by the proliferation and differentiation of epidermal stem cells. It is known that the number of epidermal stem cells decreases due to the effects of aging and photoaging caused by ultraviolet rays. A decrease in epidermal stem cells causes thinning of the epidermis, delayed turnover, and homeostasis abnormalities, inducing aging symptoms such as wrinkles and dullness. Conventionally, a method of taking a biopsy and analyzing it has been proposed as a method of detecting and analyzing epidermal stem cells (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. WO2018 / 074606

[0004] However, taking a biopsy involves problems such as high invasiveness at the sampling site, and staining a biopsy with antibodies is time-consuming and unstable. Summary of the Invention [Problem to be solved by the invention]

[0005] Therefore, there is a demand for a method for detecting stem cells non-invasively and easily with high accuracy. [Means for solving the problem]

[0006] In order to solve at least part of the above problems, the present disclosure employs the following various aspects.

[0007] A first aspect provides a stem cell detection device, comprising: an image data acquisition unit that acquires three-dimensional image data of a target object containing cells; and a stem cell detection unit that detects stem cells contained in the target object using the three-dimensional image data and predetermined morphological features of stem cells.

[0008] According to the detection device of the first aspect, stem cells contained in an object are detected using three-dimensional image data of the object and predetermined morphological features of the stem cells, thereby making it possible to detect stem cells non-invasively and easily with high accuracy.

[0009] In the detection device according to the first aspect, the morphological feature may be at least one of the ratio of the length and width of the cell and the area of ​​the cell, and the stem cell detection unit may specify at least one of the ratio of the length and width of the cell and the area of ​​the cell contained in the three-dimensional image data, and detect stem cells using the corresponding morphological feature. In this case, the detection of stem cells can be easily performed and the detection accuracy can be improved.

[0010] In the detection device according to the first aspect, the object may be skin, and the image data acquisition unit may acquire a plurality of continuous tomographic image data in a depth direction of the skin as the three-dimensional image data. In this case, the morphology of cells contained in the skin can be efficiently compared with the morphological features of stem cells.

[0011] In the detection device according to the first aspect, the stem cell detection unit may identify the morphology of cells included in the multiple tomographic image data, and use the identified morphology of cells to determine at least one of the ratio of the vertical dimension to the horizontal dimension (vertical dimension / horizontal dimension) and the area of ​​the cells included in the three-dimensional image data, and detect stem cells using the morphological feature amount corresponding to at least one of the determined ratio of the vertical dimension to the horizontal dimension and the area. In this case, the detection accuracy of stem cells can be further improved.

[0012] In the detection device according to the first aspect, the stem cell detection unit may identify a plurality of points corresponding to cell membranes in each of the plurality of tomographic image data, and may identify the morphology of the cells in contact with the basement membrane of the skin using the identified plurality of points. In addition, in the detection device according to the first aspect, in the identified morphology of the cells, a direction perpendicular to the basement membrane may be set as a first axis, the length of the first axis may be acquired as the vertical dimension, and the length of a second axis perpendicular to the first axis may be acquired as the horizontal dimension. In this case, the morphology of the cells can be easily identified.

[0013] In the detection device according to the first aspect, the area of ​​the cell is 90 to 180 μm 2 This area range indicates a morphological characteristic amount of stem cells, and the detection accuracy of stem cells can be improved.

[0014] In the detection device according to the first aspect, the stem cells may have an ellipsoidal shape, and the ratio of the length to the width of the cells (length / width) may be 1.4 to 2.4. This range of aspect ratio indicates a morphological characteristic value of the ellipsoidal stem cells, and can improve the detection accuracy of the stem cells.

[0015] The second aspect provides a detection system for detecting stem cells. The detection system according to the second aspect includes the detection device according to the first aspect, an imaging device that captures the three-dimensional image data, and an output device that outputs the detection result of the stem cells detected by the detection device. The detection system according to the second aspect detects stem cells contained in the object using the three-dimensional image data of the object and predetermined morphological features of the stem cells, so that the stem cells can be detected non-invasively and easily with high accuracy.

[0016] A third aspect provides a method for detecting stem cells, comprising: acquiring three-dimensional image data of an object containing cells; and detecting stem cells contained in the object using the three-dimensional image data and predetermined morphological features of stem cells.

[0017] According to the detection method of the third aspect, stem cells contained in an object are detected using three-dimensional image data of the object and predetermined morphological features of stem cells, thereby making it possible to detect stem cells non-invasively and easily with high accuracy.

[0018] A fourth aspect provides a detection program for detecting stem cells. The detection program according to the fourth aspect causes a computer to realize a function for acquiring three-dimensional image data of a target object containing cells, and a function for detecting stem cells contained in the target object using the three-dimensional image data and predetermined morphological features of stem cells.

[0019] According to the detection program of the fourth aspect, stem cells contained in an object are detected using three-dimensional image data of the object and predetermined morphological features of the stem cells, and therefore the detection program of the fourth aspect, which can detect stem cells non-invasively or easily and accurately, may be stored on a computer-readable medium, for example, a CD, a DVD, a Blu-ray disc, or a semiconductor memory. [Brief description of the drawings]

[0020] [Figure 1] FIG. 1 is an explanatory diagram showing an example of a detection device and a detection system according to a first embodiment. [Diagram 2] FIG. 2 is an explanatory diagram illustrating the detection device according to the first embodiment by illustrating a functional portion. [Diagram 3] FIG. 1 is a block diagram showing the functional internal configuration of a detection device according to a first embodiment. [Figure 4] FIG. 1 is an explanatory diagram showing an example of a microscopic cell image obtained using an immunohistochemical staining method. [Diagram 5] FIG. 2 is an explanatory diagram showing various forms of stem cells and non-stem cells used in the first embodiment. [Figure 6] FIG. 2 is an explanatory diagram showing an example of conditions used to specify morphological characteristic amounts of stem cells used in the first embodiment. [Figure 7]FIG. 13 is an explanatory diagram showing an example of a comparison result between a predicted stem cell abundance rate and an actual measured value with respect to area. [Figure 8] FIG. 13 is an explanatory diagram showing an example of a comparison result between a predicted stem cell abundance rate and an actual measured value with respect to aspect ratio. [Figure 9] FIG. 13 is an explanatory diagram showing an example of a comparison result between predicted stem cell abundance rates and actual measured values ​​for a combination of area and aspect ratio. [Figure 10] 4 is a flowchart showing each processing step of a stem cell detection process executed by the detection device according to the first embodiment. [Figure 11] FIG. 2 is an explanatory diagram showing the concept of three-dimensional image data obtained by an imaging device. [Figure 12] FIG. 2 is an explanatory diagram showing a method for identifying cell morphology in the first embodiment. [Figure 13] FIG. 2 is an explanatory diagram showing the distribution of predicted stem cell abundance rates of epidermal stem cells by age group obtained using the detection device according to the first embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] Conventionally, a commonly known method for analyzing stem cells inside tissues is, for example, to collect skin tissue, slice it, and then perform immunohistochemical staining using an antibody against a marker protein specifically expressed in epidermal stem cells to analyze epidermal stem cells inside the skin. However, this method is highly invasive because it requires the collection of a biopsy, the antibody used for staining is expensive, immunohistochemical staining is a complicated method, and furthermore, there are problems such as variation in staining between samples and differences in antibody lots, and the stability of the analysis is not high.

[0022] In order to solve these problems, the inventors of the present application have intensively studied methods for analyzing stem cells, and as a result, by analyzing stem cells using immunohistochemical staining, they have found that epidermal stem cells in tissues retain their unique cell morphology (cell size, aspect ratio), and have identified morphological parameters specific to stem cells. They have discovered that it is possible to quantify the morphology of cells present in the epidermal basal layer using three-dimensional image data obtained by capturing continuous tomographic images in the depth direction of the epidermis and the identified morphological parameters. Below, the detection device, detection system, detection method, and detection program according to the present disclosure will be described based on embodiments with reference to the drawings.

[0023] First embodiment: FIG. 1 shows an example of a detection device and a detection system for stem cells according to the first embodiment. The detection system 100 includes at least detection devices 10 and 40 and an imaging device 20. The detection device 10 may be realized as a computer 10P, such as a desktop computer shown in the figure or a notebook computer not shown in the figure, or may be realized as a tablet terminal 10T. The computer 10P may be connected to a display device 31 as an output device by wire or wirelessly. The tablet terminal 10T includes a display unit 32. The detection device 40 may be realized as a server computer 40. When the detection device 40 is realized as a server computer 40, the imaging data obtained by the imaging device 20 is transmitted to the server computer 40 via a network NT, and the detection result of the stem cells detected by the server computer 40 is transmitted to the computer 10P or the tablet terminal 10T via the network NT, and the detection result is displayed on the display device 31 or the display unit 32. The network NT is the Internet or an intranet, and the computer 10P, the tablet terminal 10T, and the imaging device 20 are connected to the network NT by wire or wirelessly. The computer 10P and the tablet terminal 10T may be connected to the imaging device 20 in a wired or wireless manner. A wireless connection may be realized by wireless communication conforming to a short-range wireless communication standard such as WIFI (registered trademark) or BLUETOOTH (registered trademark).

[0024] The imaging device 20 is an imaging device that enables non-invasive analysis of cells present in the basal layer of the epidermis, and can non-invasively capture three-dimensional image data of the internal structure of the skin. The imaging device 20 is an imaging device that can continuously capture and output tomographic images in the depth direction of the epidermis, that is, slice images corresponding to a plurality of different depths in the depth direction. In this embodiment, the three-dimensional image data is tomographic image data in the depth direction of the epidermis, and slice image data that are continuous in the depth direction. A confocal laser microscope is used as the imaging device 20 in this embodiment. In addition to this, the imaging device 20 may also be a magnetic resonance imaging (MRI) device, an optical coherence tomography (FF-OCT, LC-OCT, SS-OCT, SD-OCT) device, a multiphoton microscope, a second harmonic generation optical microscope, a photoacoustic microscope, a photoacoustic microscope, a confocal Raman microscope, an optical coherence microscope (OCM), a focused ion beam scanning electron microscope, or the like.

[0025] The detection results are displayed on the display device 31 and the display unit 32. The detection results may include, for example, a display of the number of stem cells as a numerical value or a graph, a display of the percentage of the number of stem cells of the subject relative to the average number of stem cells according to the age of the subject, and a display of the distribution of stem cells in tissue.

[0026] FIG. 2 is an explanatory diagram showing the detection system 100 according to the first embodiment by its functional units. The detection device 10 includes an image data acquisition unit F1 and a stem cell detection unit F2. The image data acquisition unit F1 is connected by wire or wirelessly to an imaging device 20 capable of capturing three-dimensional image data, and acquires the three-dimensional image data from the imaging device 20. The stem cell detection unit F2 determines the morphology of cells including stem cells using the three-dimensional image data acquired by the image data acquisition unit F1, and detects stem cells contained in the object using predetermined morphological features of the stem cells. The detection result of the stem cells detected by the stem cell detection unit F2 is output to the display device 31 or the display unit 32, which is an output device.

[0027] FIG. 3 is a block diagram showing the functional internal configuration of the detection device 10 according to the first embodiment. The detection device 10 includes a central processing unit (CPU) 101, a memory 102, an input / output interface 103, and a clock generator (not shown). The CPU 101, the memory 102, the input / output interface 103, and the clock generator are connected via an internal bus 104 so as to be able to communicate in both directions. The memory 102 includes a memory, such as a ROM, that stores a stem cell detection program Pr1 in a non-volatile and read-only manner for determining the morphology of cells using three-dimensional image data and detecting stem cells contained in a target object using predetermined morphological features of stem cells, and a memory, such as a RAM, that can be read and written by the CPU 101. The non-volatile and readable / writable area of ​​the memory 102 includes a morphological feature storage area 102a for storing morphological features of various stem cells to be detected. The CPU 101, i.e., the detection device 10, functions as an image data acquisition unit F1 and a stem cell detection unit F2 by expanding the stem cell detection program Pr1 stored in the memory 102 into a readable / writable memory and executing it. The CPU 101 may be a single CPU, or may be multiple CPUs that execute each program, or may be a multitask or multithread type CPU that can execute multiple programs simultaneously. The image data acquisition unit F1 and the stem cell detection unit F2 may be realized in hardware as logic circuits.

[0028] The input / output interface 103 is a physical and logical wireless or wired interface used to connect the detection device 10 to various other devices, and can be realized as a known terminal such as a USB terminal, a LAN terminal, or a serial bus terminal, or a wireless receiving unit conforming to each wireless protocol. In the first embodiment, the input / output interface 103 is connected to a display unit 32 having, for example, a liquid crystal panel, a display device 31, and an imaging device 20, each via a signal line or wirelessly. Note that instead of the display device 31, or together with the display device 31, a printing device that outputs, i.e., prints, an estimated impression on a print medium, for example, paper, may be provided.

[0029] Identifying morphological features of stem cells: Skin stem cells, more specifically, skin tissue (KAC) commercially available for the analysis of epidermal stem cells, were fixed with 4% PFA, paraffin blocks were prepared, and tissue sections were prepared using a microtome. The prepared sections were deparaffinized and then immunohistochemically stained using a primary antibody (Origene) against CD271, a marker gene for epidermal stem cells, and a fluorescently labeled secondary antibody. The stained images of the tissue sections were captured using a Leica fluorescence microscope to obtain stained images, and the morphological features of CD271-positive epidermal stem cells and CD271-negative epidermal keratinocytes present in the basal layer of the epidermis were identified using Metamorph's image analysis software. More specifically, the vertical dimension a and horizontal dimension b of each cell were measured. Figure 4 shows a schematic diagram of the identification of cell morphology using epidermal stem cells SC as an example, where the vertical dimension a was determined as the maximum length of the vertical straight line of the cell stretched perpendicular to the basement membrane BL, and the horizontal dimension b was determined as the maximum length of the horizontal straight line perpendicular to the vertical straight line. Figure 4 is a schematic diagram showing a fusion image of a stained image and a bright field image showing a cross section of a tissue section cut along a plane parallel to the depth direction of the skin. The morphological features of epidermal stem cells SC and non-epidermal stem cells OC were calculated as the average values ​​of the morphological features of multiple stem cells and cells contained in the tissue section. The measurement results are shown in Figure 5. As shown in Figure 5, when comparing epidermal stem cells SC and non-epidermal stem cells OC, it was found that the average area and average aspect ratio exist as morphological features specific to epidermal stem cells SC. In other words, the average area of ​​epidermal stem cells SC is 109.5 μm 2 whereas the average area of ​​non-epidermal stem cell OCs was 89.0 μm 2 and 20 μm 2There is a difference in the degree of the average area, and the average area has technical significance as a feature that characterizes the morphology of epidermal stem cells SC. The average area was calculated using a known image analysis program. The average aspect ratio (a / b) of epidermal stem cells SC is 1.64, while the average aspect ratio (a / b) of non-epidermal stem cells OC is 1.08, so there is a difference of about 0.6, and the average aspect ratio (a / b) has technical significance as a feature that characterizes the morphology of epidermal stem cells SC. As shown by the average aspect ratio (a / b) of epidermal stem cells SC, epidermal stem cells SC are cells with an ellipsoidal shape, and it is possible to determine whether a cell is an epidermal stem cell SC or not using the geometric characteristic of an ellipsoidal shape without relying on immunohistochemical staining. In this respect, the morphological feature of the aspect ratio of a cell is a feature that reflects the morphology of epidermal stem cells SC.

[0030] Comparison of epidermal stem cell abundance predicted using morphological characteristics of cells and actual measurements: The analysis of the distribution of epidermal stem cells was verified using the average aspect ratio (a / b) and average area, which are the morphological features of the identified epidermal stem cells. First, immunohistochemical staining was performed on tissue sections using skin tissue (KAC) using primary and secondary antibodies against CD271. Stained images and bright-field images of the stained epidermal stem cells were taken, and fusion images were created. The number of CD271-positive epidermal stem cells relative to the total number of cells present in the basal layer of the epidermis in these images was visually counted, and the presence rate of stem cells present in the basal layer (number of epidermal stem cells present in the basal layer / total number of cells present in the basal layer) was analyzed, resulting in an presence rate of 20%. Next, the cell morphology of the basal layer of the bright-field image (also acceptable for hematoxylin-eosin (HE) staining) was quantified, and the predicted presence rate of epidermal stem cells was calculated by applying each of the conditions 1 to 21 shown in Figure 6 to the quantitative value as conditions for identifying epidermal stem cells using morphological features. It should be noted that conditions 1 to 21 shown in FIG. 6 are merely examples, and other conditions may be used.

[0031] The accuracy of identifying epidermal stem cells under each of conditions 1 to 21 was verified by comparing the predicted presence rate of epidermal stem cells obtained using morphological features with the actual measured value (20%). The verification results are shown in Figs. 7 to 9, and the accuracy table in each figure is as follows: Accuracy rating A: difference from the actual measured value of ±2% or less; Accuracy rating B: difference from the actual measured value of greater than ±2% and less than ±5%; Accuracy rating C: difference from the actual measured value of greater than ±5% and less than 10%; Accuracy rating D: difference from the actual measured value of greater than 10%, with the accuracy ratings being A (highest)>B>C>D (lowest). Fig. 7 shows the verification results when conditions 1 to 7, which use area as a condition, were applied. As shown in Fig. 7, when area is used as a condition, the area is 90 to 180 μm 2 It is preferable that the aspect ratio is 1.4 to 2.4, and epidermal stem cells can be identified under conditions 2 to 6 with accuracy evaluation C or higher, and preferably under conditions 3 to 5 with accuracy evaluation B or higher, and most preferably under condition 4 with accuracy evaluation A. As shown in FIG. 8, when the aspect ratio is used as a condition, the aspect ratio is preferably 1.4 to 2.4, and epidermal stem cells can be identified under conditions 9 to 13 with accuracy evaluation C or higher, and preferably under conditions 10 to 12 with accuracy evaluation B or higher, and most preferably under condition 11 with accuracy evaluation A. Furthermore, as shown in FIG. 9, by combining both conditions of area and aspect ratio, it was verified that five conditions, 16 to 20, correspond to conditions with accuracy evaluation B or higher, and three conditions, 17 to 19, correspond to conditions with accuracy evaluation A, demonstrating that more accurate detection of epidermal stem cells is possible.

[0032] The epidermal stem cell detection process using cell morphology and morphological features of epidermal stem cells, which is executed by the detection device 10 according to the first embodiment, will be described below. Fig. 10 is a flow chart showing each processing step of the stem cell detection process executed by the detection device 10 according to the first embodiment. More specifically, the process is realized by the CPU 101 executing the stem cell detection program Pr1.

[0033] The imaging unit of the imaging device 20 is brought close to the detection target, i.e., the skin area of ​​the subject. More specifically, the objective lens of the confocal laser microscope, which is the imaging device 20, is brought close to the skin area to be detected, a skin area of ​​1.2 mm x 0.5 mm square is imaged, and three-dimensional image data of the inside of the skin at a depth of about 0.3 mm is imaged. The CPU 101 acquires the captured three-dimensional image data from the imaging device 20 (step S100). In this embodiment, the three-dimensional image data in the depth direction of the skin is composed of data corresponding to 20 tomographic images from the tomographic image LG1 on the most dermis side to the tomographic image LG20 on the most epidermis side, as shown in FIG. 11. A tomographic image including a cell, for example, a point cloud or point sequence CD corresponding to the outer periphery of the cell, i.e., the cell membrane, is obtained as shown in the tomographic images LG6, LG11, and LG14. Therefore, by using the point sequence CD included in all the tomographic images, the morphology of the cell can be three-dimensionally identified as described below. Although the orientation of each cell inside the skin is not uniform, by identifying the cell morphology three-dimensionally, it is possible to determine the morphological features of the cells with little variation. Note that at least epidermal stem cells have a morphology with a long axis extending in the depth direction of the skin, starting from the basement membrane BL.

[0034] CPU101 uses the three-dimensional image data to identify the morphology of the cell in contact with the basement membrane BL, that is, the morphology of the cell body (step S102). Specifically, using a point sequence CD corresponding to the cell membrane included in a plurality of tomographic images, a direction perpendicular to the basement membrane BL is determined as the first axis, and a cell body is identified in which the root mean square of the distance to the surface of the cell body with the direction of the first axis fixed is minimized for all point sequences corresponding to the cell membrane of one cell, and other axes other than the first axis passing through the center position are obtained. The length of the first axis and the length of each of the other axes are derived, and the second longest axis is determined as the second axis, thereby identifying the morphology of the cell. A cell has a morphology such as a sphere, an ellipsoid, or an approximate sphere, and by determining at least the first longest axis and the second longest axis, the morphology of the cell is determined as shown in FIG. 12. More specifically, a cross-sectional shape cut by a plane passing through the first axis and the second axis is determined, and the length of the first axis, that is, the vertical dimension, and the length of the second axis, that is, the horizontal dimension, can be obtained. As described above, epidermal stem cells have an ellipsoid shape and an elliptical cross section. CPU 101 acquires the length of the first axis as the vertical dimension a of the cell, and the length of the second axis as the horizontal dimension b (step S104). CPU 101 uses the acquired vertical dimension a and horizontal dimension b to calculate the aspect ratio a / b of the cell and the area of ​​the cell (π×(a / 2)×(b / 2)).

[0035] CPU 101 detects epidermal stem cells using at least one of the calculated aspect ratio a / b and area (step S106). Specifically, CPU 101 detects cells that satisfy the above-mentioned conditions 2 to 6, 9 to 13, and 16 to 20, which can be determined according to the required accuracy, using at least one of the aspect ratio a / b and area that indicate the morphological characteristic amount of epidermal stem cells that have a predetermined ellipsoidal shape and an elliptical cross section, and at least one of the aspect ratio a / b and area that correspond to the cells whose morphology has been specified, as epidermal stem cells. CPU 101 outputs the detection result (step S108) and ends this processing routine. The detection result may be displayed on the display device 31 or the display unit 32, or may be printed on a medium via a printing device. The displayed or printed verification results may be, for example, the number of detected epidermal stem cells, a predicted stem cell abundance rate, which is the ratio of epidermal stem cells among skin cells, or a percentage or ratio of increase or decrease relative to a standard value for the subject's age or age group. The displayed or printed form may be numerical or graphical.

[0036] The detection device 10 according to the first embodiment was used to verify the decrease in epidermal stem cells due to aging. Specifically, 3D image data of the skin was obtained using a confocal laser microscope for eight subjects each in their 20s, 40s, and 60s, and epidermal stem cells were detected by applying condition 18, and a predicted stem cell abundance rate, which is the ratio of epidermal stem cells to skin cells, was calculated. The detection results are shown in FIG. 13, and it was possible to verify that epidermal stem cells gradually decrease with aging.

[0037] As described above, the detection device 10 according to the first embodiment can identify cells in skin tissue using three-dimensional image data of the skin, and detect epidermal stem cells using morphological features of epidermal stem cells. Therefore, epidermal stem cells can be detected non-invasively, simply, and accurately. That is, by applying the characteristic morphology of epidermal stem cells discovered by the inventors of the present application and comparing it with the morphology of skin cells, it has become possible to perform an inexpensive, simple, and highly accurate analysis of epidermal stem cells without being affected by the invasiveness, complexity, and lot-to-lot variation of detection methods using immunohistochemical staining.

[0038] The advantages of detecting skin stem cells with high accuracy are as follows. Human skin has a three-layer structure, broadly divided into the epidermis, dermis, and subcutaneous tissue. Of these three layers, the epidermis, which is the outermost layer of the skin, is the tissue located at the outermost part of the skin and plays an important role in protecting the body from the outside world, i.e., providing a barrier function. The epidermis is composed of multiple layers at different stages of maturity, namely the basal layer, the spinous layer, the granular layer, and the stratum corneum. Most of the epidermis is mainly composed of epidermal keratinocytes, which are supplied by epidermal keratinocytes that originate from epidermal stem cells present in the basal layer, the lowest layer of the epidermis, and mature through self-renewal division and differentiation of stem cells. The homeostasis of the epidermis is maintained by the periodic regeneration of cells through turnover driven by the proliferation and differentiation of epidermal stem cells. It is known that epidermal stem cells are affected by aging and photoaging due to ultraviolet rays, and are reduced in number and depleted, and a decrease in the number of epidermal stem cells is thought to cause epidermal thinning, delayed turnover, and abnormal homeostasis, inducing aging symptoms such as wrinkles and dullness. Therefore, by accurately detecting epidermal stem cells, it is possible to predict epidermal thinning, delayed turnover, and abnormal homeostasis, and it is possible to easily and quickly develop methods, cosmetics, and pharmaceuticals for suppressing or preventing delayed turnover, and to verify the usefulness of the development results.

[0039] Use of the detection device 10 according to the first embodiment can improve the quality and survival rate of cultured epidermis in regenerative medicine, in which epidermal cells are harvested from a patient and an autologous cultured epidermis reconstituted from the cells is transplanted when treating severe skin wounds or burns. That is, while the quality and survival rate of the cultured epidermis depend on the state of stem cells in the harvested tissue, use of the detection device 10 according to the first embodiment can noninvasively detect and analyze stem cells at the site with high accuracy before the tissue is harvested.

[0040] In other embodiments: (1) In the above embodiment, three-dimensional image data obtained by imaging the subject's skin with the imaging device 20 is used as the object for detecting stem cells, but three-dimensional image data obtained by imaging a tissue slice obtained from the subject may also be used. In this case, it is possible to detect stem cells easily and in a short time without performing immunohistochemical staining. In addition, in the above embodiment, skin is used as the object for detecting stem cells, but blood or an excised organ may also be used as the object. In these cases, the morphological features of stem cells are specified in advance by the above-mentioned method, and the cells and morphological features specified using the three-dimensional image data obtained by imaging the object are used to detect stem cells in the same way as epidermal stem cells.

[0041] Although the present disclosure has been described above based on various embodiments, the above-described embodiments are intended to facilitate understanding of the present disclosure and are not intended to limit the present disclosure. The present disclosure may be modified or improved without departing from the spirit and scope of the claims, and the present disclosure includes equivalents thereof. [Explanation of symbols]

[0042] 10: detection device, 100: detection system, 101: central processing unit (CPU), 102: memory unit, 20: imaging device, F1: image data acquisition unit, F2: stem cell detection unit.

Claims

1. A device for detecting stem cells, comprising: an image data acquisition unit that acquires a plurality of continuous tomographic image data in a depth direction of skin, which is an object including cells, as three-dimensional image data; a stem cell detection unit that detects stem cells contained in the epidermis of the skin using the three-dimensional image data and predetermined morphological features of epidermal stem cells, and generates a detection result indicating the number of stem cells in the detected epidermis or a predicted stem cell presence rate, which is the ratio of epidermal stem cells among skin cells.

2. 2. The detection device according to claim 1, the morphological feature amount is at least one of a ratio of a vertical dimension to a horizontal dimension of a cell and an area of ​​a cell; The stem cell detection unit identifies the morphology of cells contained in the multiple tomographic image data, and uses the identified morphology of cells to determine at least one of the ratio of the vertical dimension to the horizontal dimension (vertical dimension / horizontal dimension) of the cell contained in the three-dimensional image data and the area of ​​the cell, and detects stem cells using the morphological feature corresponding to at least one of the determined ratio of the vertical dimension to the horizontal dimension and the area.

3. 3. The detection device according to claim 2, The stem cell detection unit identifies a plurality of point groups corresponding to cell membranes in each of the plurality of tomographic image data, and identifies the morphology of the cells in contact with the basement membrane of the skin using the identified plurality of point groups.

4. 4. The detection device according to claim 3, The stem cell detection unit is a detection device that, in the identified cell morphology, defines a direction perpendicular to the basement membrane as a first axis, acquires the length of the first axis as the vertical dimension, and acquires the length of a second axis perpendicular to the first axis as the horizontal dimension.

5. The detection device according to any one of claims 1 to 4, The area of ​​the cells is 90 to 180 μm ２ A detection device.

6. The detection device according to any one of claims 1 to 5, The stem cells have an ellipsoidal shape, A detection device, wherein the ratio of the length to the width of the cell (length / width) is between 1.4 and 2.

4.

7. 1. A detection system for detecting stem cells, comprising: A detection device according to any one of claims 1 to 6, an imaging device that captures the three-dimensional image data; an output device that outputs the detection result of the stem cells detected by the detection device; A detection system comprising:

8. A method for detecting stem cells, comprising: A plurality of continuous tomographic image data in a depth direction of skin, which is an object including cells, is acquired as three-dimensional image data; A detection method comprising: detecting stem cells contained in the epidermis of the skin using the three-dimensional image data and predetermined morphological features of epidermal stem cells; and generating a detection result indicating the number of detected epidermal stem cells or a predicted stem cell presence rate, which is the ratio of epidermal stem cells among skin cells.

9. A detection program for detecting stem cells, comprising: A function for acquiring a plurality of continuous tomographic image data in a depth direction of skin, which is an object including cells, as three-dimensional image data; A detection program that causes a computer to realize a function for detecting stem cells contained in the epidermis of the skin using the three-dimensional image data and predetermined morphological features of epidermal stem cells, and a function for generating a detection result indicating the number of stem cells in the detected epidermis or a predicted stem cell presence rate, which is the ratio of epidermal stem cells among skin cells.

Images