Method for evaluating three-dimensional tissue containing epithelial cells, evaluation device, and program

Abstract

A method for evaluating a three-dimensional tissue containing epithelial cells includes evaluating a formation process of an epithelial lumen formed in the three-dimensional tissue by using refractive index distribution data at a plurality of points in time of the three-dimensional tissue containing epithelial cells.

Description

Method, device and program for evaluating three-dimensional tissue containing epithelial cells

[0001] The present disclosure relates to a method, an evaluation device, and a program for evaluating three-dimensional tissue containing epithelial cells.

[0002] Epithelial tissues contain hollow structures called epithelial lumens. The epithelial lumens are tubular structures surrounded by the apical surfaces of epithelial cells, and are known to exist in, for example, the intestinal tract, pulmonary alveoli, and renal tubules. In living organisms, the epithelial lumens play roles such as absorbing, excreting, and transporting substances necessary for vital activities (Non-Patent Document 1).

[0003] In epithelial tissue, epithelial lumens are formed through a variety of formation processes. Two typical formation processes for epithelial lumens are known: hollowing and cavitation. In the hollowing process, vesicles within cells that form epithelial tissue are transported out of the cells, creating spaces between the cells, thereby forming a lumen. In the cavitation process, selective cell death occurs in some of the cells that form epithelial tissue, and a lumen is formed in the space where the dead cells were located (Non-Patent Documents 1 and 2).

[0004] Incidentally, the present inventors have proposed a methodology for evaluating an observation object containing cells using refractive index distribution data, as described in Patent Documents 1 to 4.

[0005] International Publication No. WO 2023 / 095378 International Publication No. WO 2024 / 024147 International Publication No. WO 2024 / 029124 International Publication No. WO 2024 / 029125 International Publication No. WO 2022 / 054305 International Publication No. WO 2023 / 095441 International Publication No. WO 2023 / 095440

[0006] Shinji Matsumoto, "Molecular Mechanisms of Epithelial Lumen Morphogenesis and Their Abnormalities in Tumorigenesis," Biochemistry, Vol. 93, No. 5, pp. 733-748 (2021). Deborah J. Andrew and Andrew J. Ewald, "Morphogenesis of Epithelial Tubes: Insights into Tube Formation, Elongation, and Elaboration," Developmental Biology 341, 34-55 (2010). Wei Yu et al., "Formation of Cysts by Alveolar Type II Cells in Three-Dimensional Culture Reveals a Novel Mechanism for Epithelial Morphogenesis," Molecular Biology of the Cell 18, 1693-1700 (2007). Alejo E. Rodriguez-Fraticelli and Fernando Martin-Belmonte, "Methods for Analysis of Apical Lumen Trafficking Using Micropatterned 3D Systems," Methods in Cell Biology 118:105-23 (2013). Yasuhiko O, Takeuchi K. In-silico clearing approach for deep refractive index tomography by partial reconstruction and wave-backpropagation. Light Sci Appl. 12:101 (2023).

[0007] In vivo, epithelial lumen formation occurs in three-dimensionally organized epithelial tissues. Therefore, it is important to evaluate the process of epithelial lumen formation in spatially organized cell tissues (three-dimensional tissues) such as spheroids and organoids, rather than in flat-cultured epithelial cells. Therefore, visualization techniques that only provide two-dimensional information, such as phase contrast microscopy and total internal reflection microscopy, cannot observe the spatial structure of epithelial lumen in three-dimensional tissues, and therefore may not be able to fully evaluate the process of epithelial lumen formation.

[0008] Given this background, evaluation of the process of epithelial lumen formation is typically performed by forming epithelial tissue using cells with fluorescently labeled proteins and evaluating the process of epithelial lumen formation in that epithelial tissue based on fluorescent images acquired using a fluorescence microscope, such as a confocal microscope, that can acquire spatial (three-dimensional) fluorescence distribution (e.g., Non-Patent Document 3). However, because fluorescence observation can only observe labeled proteins, it is impossible to observe structures formed within the lumen of an epithelial lumen that are not related to the protein, for example. Furthermore, because cells must be labeled with fluorescent proteins and the labeled cells must be intermittently irradiated with excitation light to evaluate the formation process over time, there is a concern that the irradiation of the excitation light may damage the cells.

[0009] In view of the above, the present disclosure aims to provide a method, an evaluation device, and a program for evaluation of three-dimensional tissue containing epithelial cells, which can evaluate the process of epithelial lumen formation in three-dimensional tissue.

[0010] One aspect of the present disclosure is “[1] a method for evaluating a three-dimensional tissue containing epithelial cells, comprising evaluating a process of epithelial lumen formation in the three-dimensional tissue using refractive index distribution data of the three-dimensional tissue containing epithelial cells at multiple time points.” According to this aspect, the process of epithelial lumen formation in the three-dimensional tissue containing epithelial cells can be evaluated based on changes in refractive index distribution data over time.

[0011] There are many unknowns regarding the process of epithelial lumen formation in epithelial tissue, and it is not always easy to identify the process by which the epithelial lumen is formed from the epithelial lumen that is finally formed. Furthermore, it is believed that epithelial lumens in cancer tissues are formed through a process different from that in normal epithelial tissues, making it even more difficult to identify and evaluate abnormal formation processes caused by such diseases from the epithelial lumen that is finally formed. In contrast, in this embodiment, the process of epithelial lumen formation is evaluated using refractive index distribution data at multiple time points, and therefore, the time-dependent changes in the structure of the epithelial lumen during the formation process can be evaluated from the time-dependent changes in the refractive index distribution data.

[0012] One aspect of the present disclosure is "the method according to [1], which includes [2] identifying a region in the three-dimensional tissue that exists in the extracellular region and has a lower refractive index than the epithelial cells as the epithelial lumen region." The inventors have found that, in refractive index distribution data of epithelial tissue, the epithelial lumen region exists in the extracellular region and has a lower refractive index than the epithelial cells. Therefore, according to this aspect, a region that exists in the extracellular region and has a lower refractive index than the epithelial cells can be identified as the epithelial lumen region. This allows the structure of the epithelial lumen to be suitably evaluated at a certain time point, and further allows the process of epithelial lumen formation to be suitably evaluated by evaluating the structure at multiple time points.

[0013] One aspect of the present disclosure is "[3] the method according to [1] or [2], wherein the maximum diameter of the epithelial lumen is 10 μm or more." According to this aspect, since epithelial lumens with a maximum diameter of 10 μm or more are evaluated, the formation process of the epithelial lumen can be suitably evaluated while distinguishing them from lumens with small inner diameters, such as bile canaliculi, and vesicles present in the cytoplasm.

[0014] One aspect of the present disclosure is "the method according to any one of [1] to [3], wherein the evaluation of the epithelial lumen formation process includes identifying the process as a hollowing type, identifying the process as a cavitation type, or identifying the process as a type other than the hollowing type and the cavitation type." The method of this aspect includes identifying whether the epithelial lumen formation process belongs to a typical type, and therefore can suitably evaluate the epithelial lumen formation process.

[0015] One aspect of the present disclosure is "[5] the method according to any one of [1] to [4], wherein at least two of the time points included in the plurality of time points are separated by at least one day." According to the method of this aspect, the process of epithelial lumen formation can be suitably evaluated by evaluating the structure of the epithelial lumen over a period of at least one day.

[0016] One aspect of the present disclosure is “[6] a method according to any one of [1] to [5], wherein the refractive index distribution data is refractive index tomographic data in a predetermined direction.” According to the method of this aspect, three-dimensional tissue can be suitably evaluated by using refractive index tomographic data in a predetermined direction as refractive index distribution data.

[0017] One aspect of the present disclosure is "[7] a method according to any one of [1] to [6], which includes identifying a region of cells that have undergone programmed cell death in the three-dimensional tissue based on the spatial change in refractive index." In addition to evaluating the process of epithelial lumen formation, the method of this aspect also identifies a region of cells that have undergone programmed cell death according to the method described in Patent Document 3, making it possible to suitably evaluate three-dimensional tissue.

[0018] One aspect of the present disclosure is "a method according to any one of [1] to [7], which comprises identifying a region of necrotic cells in a region of cells having cell nuclei in the three-dimensional tissue based on the average or median refractive index of the entire cells and / or the variation in the refractive index of the cell nuclei." In this aspect, in addition to evaluating the process of epithelial lumen formation, the method also identifies a region of necrotic cells according to the method described in Patent Document 4, thereby enabling suitable evaluation of three-dimensional tissue.

[0019] One aspect of the present disclosure is "[9] the method according to any one of [1] to [8], further comprising identifying, in the three-dimensional tissue, a region present in the cytoplasm and having a lower refractive index than the cytoplasm of the epithelial cells, as a vesicle region." The inventors discovered that, in refractive index distribution data of epithelial tissue, a vesicle region is present in the cytoplasm and has a lower refractive index than the cytoplasm of the epithelial cells. Therefore, the method of this aspect not only evaluates the process of epithelial lumen formation but also identifies the vesicle region, thereby enabling suitable evaluation of three-dimensional tissue. Furthermore, since the method of this aspect also identifies the vesicle region, it can also be used to evaluate, for example, the hollowing-type formation process, in which intracellular vesicles are transported outside the cell to form an epithelial lumen, from the perspective of evaluating the process of epithelial lumen formation.

[0020] One aspect of the present disclosure is "a drug screening method, comprising: (10) exposing a three-dimensional tissue containing epithelial cells or cells before the formation of such a tissue to a drug; and evaluating the three-dimensional tissue according to the method described in any one of (1) to (9)."

[0021] According to the screening method of this embodiment, for example, the process of epithelial lumen formation by cells or three-dimensional tissues exposed to a drug can be evaluated. Abnormalities in epithelial lumen formation are thought to be more likely to occur under certain pathological conditions (e.g., Non-Patent Document 4). Therefore, for example, by exposing cancer tissue organoids to a drug and then evaluating the process and quality of epithelial lumen formation in the cancer tissue, cancer therapeutic drugs that can suppress epithelial lumen abnormalities in cancer tissue can be screened (selected). Furthermore, for example, by exposing normal tissue organoids to a drug and then evaluating the process and quality of epithelial lumen formation in the normal tissue, drugs that may cause diseases accompanied by epithelial lumen abnormalities as a side effect can be negatively screened (excluded).

[0022] Furthermore, according to the screening method of this embodiment, for example, the process of epithelial lumen formation in a three-dimensional tissue can be evaluated, and then the three-dimensional tissue can be exposed to a drug to evaluate the effects of the drug on the three-dimensional tissue and epithelial lumen according to the process of epithelial lumen formation. In this way, drugs that do not induce cell death in three-dimensional tissues with epithelial lumens formed by typical formation processes, such as hollowing or cavitation, but induce cell death in three-dimensional tissues with epithelial lumens formed by abnormal formation processes, can be screened (selected) as drugs selective for three-dimensional tissues with abnormal epithelial lumen formation. Drugs selected in this way are expected to have minimal side effects.

[0023] One aspect of the present disclosure is “

[11] an evaluation device for three-dimensional tissue containing epithelial cells, comprising: a data acquisition unit that acquires refractive index distribution data of three-dimensional tissue containing epithelial cells; and an evaluation unit that evaluates the process of epithelial lumen formation in the three-dimensional tissue using the refractive index distribution data at multiple time points.” According to this aspect, the process of epithelial lumen formation in three-dimensional tissue containing epithelial cells can be evaluated based on changes in refractive index distribution data over time.

[0024] One aspect of the present disclosure is “

[12] a program for causing a computer to execute a data acquisition step of acquiring refractive index distribution data of a three-dimensional tissue containing epithelial cells, and an evaluation step of evaluating the process of epithelial lumen formation in the three-dimensional tissue using the refractive index distribution data at multiple time points.” According to this aspect, the process of epithelial lumen formation in a three-dimensional tissue containing epithelial cells can be evaluated based on changes in the refractive index distribution data over time.

[0025] According to the present disclosure, there are provided a method, an apparatus, and a program for evaluating three-dimensional tissue containing epithelial cells, which are capable of evaluating the process of epithelial lumen formation in the three-dimensional tissue. The evaluation method of the present disclosure is simple because it does not require cell labeling.

[0026] 6 is a diagram showing an example of a three-dimensional tissue to be evaluated and its refractive index tomographic data. FIG. 7 is a diagram showing an example of refractive index tomographic data of a three-dimensional tissue to be evaluated using the positions of the epithelial lumen region, the dead cell region, and the vesicle region as indicators. FIG. 8 is a diagram showing an example of negative screening of a drug when a drug exposure step is performed simultaneously with the preparation step and in the first half of the preparation step. FIG. 9 is a schematic diagram showing an example of recovery of contents from the epithelial lumen. FIG. 10 is a diagram showing an example of the configuration of an evaluation device used in an evaluation method of an embodiment. FIG. 11 is a diagram showing representative refractive index tomographic data extracted from refractive index distribution data of a three-dimensional tissue cultured for 4, 7, or 14 days in Example 1. FIG. 12 is a diagram showing, enclosed by a solid line, a region of interest (ROI) in the refractive index tomographic data of a three-dimensional tissue cultured for 7 or 14 days shown in FIG. 6 in Example 1, which was used to evaluate a renal tubule region. FIG. 13 is a diagram showing, enclosed by a solid line, a region of interest (ROI) in the refractive index tomographic data of a three-dimensional tissue cultured for 7 or 14 days shown in FIG. 6 in Example 1, which was used to evaluate a dead cell region. 1 is a diagram showing, enclosed by a solid line, a region of interest (ROI) in the evaluation of vesicle regions in the refractive index tomographic data of three-dimensional tissue cultured for four days shown in FIG. 6 in Example 1. FIG. 2 is a diagram showing the configuration of an observation device 1A. FIG. 3 is a diagram showing a schematic diagram of incidence of first light and second light on an observation object S, and incidence of the first light and second light on an imaging unit 50 after passing through the observation object S. FIG. 4 is a diagram showing the configuration of a processing unit 60 of the observation device. FIG. 5 is a flowchart of an observation method. FIG. 6 is a diagram showing representative refractive index tomographic data extracted from refractive index distribution data of three-dimensional tissue acquired on the first, second, and seventh days after the start of culture in Example 2. FIG. 7 is a diagram showing representative refractive index tomographic data extracted from refractive index distribution data of a sample before and after the addition of staurosporine in Example 3.

[0027] One embodiment of the present disclosure will be described below, but the present disclosure should not be construed as being limited to the following embodiment.

[0028] One embodiment of the present disclosure relates to a method for evaluating three-dimensional tissue containing epithelial cells, which includes evaluating the formation process of epithelial lumens formed in the three-dimensional tissue using refractive index distribution data of the three-dimensional tissue containing epithelial cells at multiple time points.

[0029] <Epithelial Cells> In the present disclosure, epithelial cells refer to cells that form epithelial tissue. Epithelial cells may be, for example, cells that form the inner wall and / or mucosa of a hollow organ. Epithelial cells may be, for example, at least one type selected from the group consisting of squamous epithelial cells, cuboidal epithelial cells, and columnar epithelial cells. Epithelial cells may be, for example, epithelial cells that form at least one type of epithelium selected from the group consisting of simple epithelium, stratified epithelium, and pseudostratified epithelium. Epithelial cells may be, for example, epithelial cells that form at least one type of epithelium selected from the group consisting of simple squamous epithelium, simple cuboidal epithelium, simple columnar epithelium, stratified squamous epithelium, stratified cuboidal epithelium, pseudostratified columnar epithelium, and transitional epithelium. Epithelial cells may be, for example, intestinal epithelial cells, alveolar epithelial cells, renal tubular epithelial cells, salivary gland epithelial cells, mammary gland epithelial cells, prostate epithelial cells, pancreatic duct epithelial cells, bile duct epithelial cells, gastric gland epithelial cells, or endometrial epithelial cells. Epithelial cells are located on the surface of the body and inside the walls of organs, and have an apical surface that faces the outside of the body or the inside of the lumen, and a basal surface that adheres to connective tissue.

[0030] <Three-dimensional tissue> In the present disclosure, a three-dimensional tissue is a three-dimensional object containing a plurality of cells and having optical transparency. The plurality of cells contained in such a three-dimensional tissue includes cells that form part of the tissue through cell-to-cell adhesion or adhesion to an extracellular matrix, not through adhesion to a culture substrate. A three-dimensional tissue is not limited to an aggregate of cells. In addition to cells, a cell sample may further contain components that may be contained in a cell sample, such as extracellular matrix and / or neutral fat. A three-dimensional tissue is, for example, a three-dimensional tissue artificially produced using cells. A three-dimensional tissue may at least partially contain epithelial tissue, and in a preferred embodiment, may be epithelial tissue. A three-dimensional tissue is, for example, a spheroid or organoid. A three-dimensional tissue may contain one or more types of cells, including epithelial cells and cells other than epithelial cells. The cells contained in the three-dimensional tissue may be, for example, human-derived cells. The cells contained in the three-dimensional tissue may be live cells, dead cells, and / or a mixture thereof, and preferably contain live cells, for example, 50% or more of the cells contained therein are live cells. The three-dimensional tissue may have a thickness of, for example, 1 μm or more, 5 μm or more, 10 μm or more, or 50 μm or more, or 1000 μm or less, 500 μm or less, 250 μm or less, or 100 μm or less, and these may be freely combined. The three-dimensional tissue evaluation method according to one embodiment uses refractive index distribution data as an index and can be used when the tissue is thick or when evaluating a deep part of the tissue, similar to fluorescence imaging, etc.

[0031] <Epithelial lumen> In the present disclosure, an epithelial lumen is a lumen surrounded by the apical surface of epithelial cells. In epithelial tissue, the epithelial lumen plays roles such as absorption, excretion, and transport of substances necessary for vital activities. The epithelial lumen may be, for example, the intestinal tract, pulmonary alveoli, renal tubules, salivary glands, mammary glands, prostate glands, pancreatic ducts, bile ducts, gastric glands, or endometrial lumen. On the other hand, epithelial lumens are clearly distinguished from lumens surrounded by parenchymal cells that do not belong to epithelial cells. Therefore, for example, bile canaliculi, which are lumens surrounded by hepatic parenchymal cells, are not epithelial lumen.

[0032] The epithelial lumen according to one embodiment may have a maximum diameter of 10 μm or more. According to this embodiment, since an epithelial lumen having a maximum diameter of 10 μm or more is evaluated, the formation process of the epithelial lumen can be suitably evaluated while distinguishing it from lumens with small inner diameters, such as bile canaliculi, and vesicles present in the cytoplasm.

[0033] In epithelial tissue, epithelial lumens are formed through a variety of formation processes. Two typical epithelial lumen formation processes are known: hollowing and cavitation. In the hollowing process, vesicles within cells that form epithelial tissue are transported out of the cells, creating spaces between the cells, thereby forming a lumen. In the cavitation process, selective cell death occurs in some of the cells that form the epithelial tissue, and a lumen is formed in the space where the apoptotic cells were located. On the other hand, it is also believed that epithelial lumens are formed in diseased epithelial tissue, such as cancer tissue, through a process different from that in normal epithelial tissue. In diseased epithelial tissue, epithelial lumens may be formed that have abnormal morphologies, such as a larger number of epithelial lumens than normal epithelial tissue or a lower circularity of the flow channel cross-section, or abnormal formation of epithelial lumens, such as the presence of dead cells remaining in the epithelial lumens.

[0034] <Refractive index distribution data> The refractive index distribution data is data indicating a three-dimensional distribution of the refractive index for each voxel in a space including three-dimensional tissue, or data indicating a two-dimensional distribution of the refractive index for each pixel in a tomographic plane in a predetermined direction in the space including the three-dimensional tissue. Furthermore, the refractive index tomographic data is data, among the refractive index distribution data, indicating a two-dimensional distribution of the refractive index for each pixel in a tomographic plane in a predetermined direction in the space including the three-dimensional tissue. The refractive index distribution data according to one aspect may be refractive index tomographic data.

[0035] The method for acquiring refractive index distribution data according to one embodiment may be any method capable of acquiring the three-dimensional refractive index distribution of three-dimensional tissue. A preferred method for acquiring refractive index distribution data according to one embodiment may be optical diffraction tomography (ODT). ODT is an advanced version of quantitative phase imaging (QPI) that enables three-dimensional imaging, enabling three-dimensional refractive index tomography of three-dimensional tissue. ODT can measure the three-dimensional refractive index distribution of three-dimensional tissue non-staining and non-invasively. Detailed ODT techniques and devices for use therewith include those described in, for example, Patent Document 1, Patent Document 5, Patent Document 6, Patent Document 7, or Non-Patent Document 5, and the like, and the following devices can also be used.

[0036] 10 is a diagram showing the configuration of an observation device 1A. This observation device 1A includes a light source 10, an irradiation unit 31, an imaging unit 50, and a processing unit 60. The light source 10 outputs spatially coherent light. The light output from the light source 10 may or may not be temporally coherent.

[0037] The light source 10 may be a laser light source, or may be a light source such as a super luminescent diode (SLD), a super continuum (SC) light source, or an optical frequency comb light source. Furthermore, the light source 10 may be configured to enhance spatial coherence by passing spatially incoherent light output from a light emitting diode (LED), a mercury lamp, or the like through a pinhole or the like.

[0038] The lens 21 is optically connected to the light source 10, and focuses the light output from the light source 10 onto a light input end 22 of an optical fiber 23, causing the light to be incident on the light input end 22. The optical fiber 23 guides the light that has been input to the light input end 22 to a light output end 24. The light guided by the optical fiber 23 is output as divergent light from the light output end 24. The lens 25 is optically connected to the light output end 24, and inputs and collimates the light that has been output as divergent light from the light output end 24, and outputs the collimated light to the irradiation unit 31.

[0039] The illumination unit 31 receives light output from the light source 10 and transmitted through the lens 21, the optical fiber 23, and the lens 25, and generates first light and second light from the received light. The illumination unit 31 also superimposes the first light and second light on each other and illuminates the observation object S. The illumination unit 31 illuminates the observation object S with the first light along a fixed light illumination direction, and illuminates the observation object S with the second light along each of a plurality of light illumination directions.

[0040] The irradiation unit 31 includes a beam splitter 311 , a phase-modulating spatial light modulator 313 , a polarizer 314 , a half-wave plate 315 , a polarizer 316 , a lens 318 and an objective lens 319 .

[0041] The beam splitter 311 reflects light that has reached it via a polarizer 314 and a half-wave plate 315, which are provided between the beam splitter 311 and the lens 25, to the spatial light modulator 313. The beam splitter 311 also receives light that has reached it from the spatial light modulator 313, and outputs this light to a polarizer 316.

[0042] The spatial light modulator 313 selectively phase-modulates the linearly polarized light in the second direction, without phase-modulating the linearly polarized light in the first direction, among the linearly polarized light in the first and second directions that are orthogonal to each other and that is incident on the modulation surface of the spatial light modulator 313. The polarizer 314 and the half-wave plate 315 set the polarization state of the light so that the light that is incident on the modulation surface of the spatial light modulator 313 from the beam splitter 311 contains linearly polarized components in the first and second directions to the same extent.

[0043] The polarizer 316 inputs the light that has arrived from the spatial light modulator 313 via the beam splitter 311 and enables interference between the linearly polarized light in the first and second directions contained in the light. The polarizer 316 has an optical axis whose orientation is 45 degrees different from the polarization orientation of the light (linearly polarized light in the first and second directions) that has arrived from the spatial light modulator 313 via the beam splitter 311, and selectively transmits the polarized component of the input light in the orientation of the optical axis. The lens 318 and the objective lens 319 irradiate the first light and the second light output from the polarizer 316 onto the observation object S as plane waves.

[0044] The irradiation unit 31 having such a configuration can treat linearly polarized light in a first direction that has not been phase-modulated by the spatial light modulator 313 as first light, and can irradiate this first light along a fixed light irradiation direction onto the observation object S. The irradiation unit 31 can treat linearly polarized light in a second direction that has been phase-modulated by the spatial light modulator 313 as second light, and can irradiate this second light along each of a plurality of light irradiation directions onto the observation object S.

[0045] The direction of irradiation of the second light onto the observation object S can be set by the orientation and spacing of the phase modulation pattern on the modulation surface of the spatial light modulator 313. Furthermore, the phase difference between the first light and the second light can be set by shifting the phase modulation pattern on the modulation surface of the spatial light modulator 313.

[0046] The objective lens 41 receives light (first light and second light) that has been irradiated onto the observation object S by the irradiation unit 31 and passed through the observation object S, and outputs the light to the mirror 42. The lens 43 receives light that has been output from the objective lens 41 and reflected by the mirror 42, and causes the light to be incident on the imaging surface of the imaging unit 50.

[0047] The imaging unit 50 receives both the first light and the second light that have reached the imaging surface from the lens 43, and captures an interference intensity image resulting from interference between the first light and the second light. The imaging unit 50 captures interference intensity images when the phase difference between the first light and the second light is set to each of a plurality of phase differences for each of a plurality of light irradiation directions of the second light.

[0048] The processing unit 60 is electrically connected to the imaging unit 50, and performs required processing based on the interference intensity image captured by the imaging unit 50 to generate a complex amplitude image, etc. The processing content of the processing unit 60 will be described later.

[0049] Next, an observation method using the observation device 1A (FIG. 10) will be described.

[0050] 11 is a diagram schematically illustrating the incidence of the first light and the second light on the observation object S, and the incidence of the first light and the second light on the imaging unit 50 after passing through the observation object S. The wavefront of the first light incident on the observation object S is denoted by u. ０,in The wavefront of the second light incident on the observation object S along the n-th light irradiation direction (n=1 to N) among the plurality of (N) light irradiation directions of the second light is represented as u ｎ,in (r) is expressed as exp(iφ).

[0051] r is a variable representing a position. φ is a phase difference between the first light and the second light. i is an imaginary unit. The wavefront of the first light on the imaging plane or focal plane (a plane optically conjugate to the imaging plane) of the imaging unit 50 is defined as u. ０ (r), and the wavefront of the second light is represented as u ｎ (r) is expressed as exp(iφ).

[0052] An interference intensity image I obtained by imaging using the imaging unit 50 ｎ (r, φ) is expressed by the following equation (1): Interference intensity image I ｎ (r, φ) is an interference intensity image acquired by imaging with the imaging unit 50 when the first light is incident on the observation object S along a certain light irradiation direction and the second light is incident on the observation object along the nth light irradiation direction, with φ being the phase difference between the first light and the second light. The focal plane (a plane optically conjugate to the imaging plane) may be on the observation object S, may be on the imaging unit 50 side of the observation object S, or may be on the irradiation unit 31 side of the observation object S.

[0053] 12 is a diagram showing the configuration of a processing unit 60 of the observation device. The processing unit 60 includes an interference term calculation unit 61, a first complex amplitude image generation unit 62, a second complex amplitude image generation unit 63, a complex differential interference image generation unit 64, a differential phase image generation unit 65, and a refractive index distribution image generation unit 66. The processing unit 60 may be, for example, a computer.

[0054] 13 is a flowchart of the observation method. In an irradiation step S1, the irradiation unit 31 irradiates the observation object S with first light and second light in an overlapping manner. At this time, the light irradiation direction of the first light with respect to the observation object S is fixed, the light irradiation direction of the second light with respect to the observation object S is set to each of a plurality of light irradiation directions, and the phase difference φ between the first light and the second light is set to each value.

[0055] In the imaging step S2, the imaging unit 50 captures an interference intensity image (Equation (1)) when the phase difference φ between the first light and the second light is set to each of the multiple phase differences for each of the multiple light irradiation directions of the second light.

[0056] The processing steps performed by the processing unit 60 include steps S3 to S8. In the interference term calculation step S3, the interference term calculation unit 61 of the processing unit 60 calculates the interference term by the phase shift method based on the interference intensity images (Equation (1)) acquired by the imaging unit 50 when each of the plurality of phase differences φ is set for each of the plurality of light irradiation directions of the second light.

[0057] For example, when the three-point phase shift method is used, the interference term calculation unit 61 calculates the interference term C by the following equation (2): ｎ (r) = u ０ ＊ (r) u ｎ (r) is found. Interference term u ０ (r) u ｎ ＊ (r) may be calculated. A phase shift method of four or more points may be used. ｎ (r) is found for each of the plurality of light irradiation directions of the second light (that is, for each n (=1 to N)).

[0058] In the first complex amplitude image generating step S4, the first complex amplitude image generating unit 62 of the processing unit 60 generates the interference term C ｎ (r) to generate a complex amplitude image of the first light. ０ The phase of (r) can be estimated as follows.

[0059] After correcting the phase gradient (difference in the light incident direction) between the first light and the second light, the coherent sum C of the interference terms after the correction is sum (r) is calculated by the following formula (3): Here, the light incident direction of the first light is set parallel to the z axis, and the wave vector representing the n-th light incident direction of the second light is set as k ｎ Let's say.

[0060] The first factor (u ０ ＊ The phase of the first light component (u (r)) is incident on the observation object S along a fixed light irradiation direction, and is significantly affected by scattering because it does not have an optical sectioning effect. ｎ (r)exp(ik ｎ The phase of the signal (sum of signals (r) and (r)) is the sum of signals for multiple incident directions of light, and has a relatively flat distribution because information near the focal plane is selectively extracted by the optical sectioning effect of the coherent sum.

[0061] From this, the complex amplitude u of the first light ０ Phase φ of (r) ０ (r) is the coherent sum C of the interference term after phase gradient correction, as expressed by the following equation (4): sum It can be approximately expressed by the phase of (r).

[0062] The complex amplitude u of the first light ０ The amplitude of (r) is the amplitude of the intensity image |u ０ (r) | ２ It can be found from

[0063] For example, in the observation device 1A (FIG. 10), by adjusting the orientation of the optical axis of each of the polarizer 314 and the half-wave plate 315 in the irradiation unit 31, only the first light can be irradiated onto the observation object S.

[0064] Furthermore, the complex amplitude u of the first light ０ The amplitude of (r) is the interference term C ｎ It can also be estimated based on (r) as follows: ｎ (r) Intensity sum I sum (r) is calculated using the following formula (5).

[0065] The first factor (|u ０ (r) | ２ ) is a component of the first light incident on the observation object S along a fixed light irradiation direction, and is significantly affected by scattering because it does not have an optical sectioning effect. On the other hand, the second factor (|u ｎ (r) | ２ The sum of the scattered light rays (sum of the scattered light rays) is the sum of the scattered light rays for multiple incident directions of light, and the optical sectioning effect of the coherent sum averages the scattered light to a relatively uniform distribution.

[0066] From this, the complex amplitude u of the first light ０ Amplitude A of (r) ０ (r) is the interference term C as shown in the following equation (6). ｎ (r) Intensity sum I sum It can be approximately expressed as the square root of (r).

[0067] In the first complex amplitude image generating step S4, the first complex amplitude image generating unit 62 generates the complex amplitude u of the first light obtained as described above. ０ Phase φ of (r) ０ (r) and amplitude A ０ Based on (r), the complex amplitude image u of the first light is calculated by the following equation (7): ０ (r) can be generated.

[0068] The optical sectioning effect is the ability to selectively capture an image at the focal plane of an objective lens in, for example, a confocal microscope or a differential interference microscope. In these microscopes, the optical sectioning effect can be achieved by increasing the numerical aperture on both the entrance and detection sides, thereby achieving selective illumination and detection.

[0069] In the second complex amplitude image generating step S5, the second complex amplitude image generating unit 63 of the processing unit 60 generates a complex amplitude image u of the first light. ０ (r) and the interference term C ｎ Based on (r), the complex amplitude image u of the second light in each of the plurality of light irradiation directions is calculated by the following equation (8): ｎ However, in this equation (8), when the denominator on the right side is 0, u ｎ Since (r) is indefinite, the complex amplitude image u of the second light in each of the plurality of light irradiation directions can be calculated by the following equation (9) instead of the equation (8). ｎ It is preferable to generate (r), where ε is a small positive value. When ε=0, equation (9) is equal to equation (8).

[0070] In the complex differential interference image generating step S6, the complex differential interference image generating unit 64 of the processing unit 60 generates a complex amplitude image u of the second light in each of the plurality of light irradiation directions. ｎ Based on (r), a complex differential interference image W(r) can be generated using the following equation (10). δr represents shear. At least one of the x-component δx and y-component δy of δr is non-zero. If δx ≠ 0 and δy = 0, a complex differential interference image with the x-direction as the shear direction is obtained. If δx = 0 and δy ≠ 0, a complex differential interference image with the y-direction as the shear direction is obtained. If δx ≠ 0 and δy ≠ 0, a complex differential interference image with the direction according to the ratio of δx to δy as the shear direction is obtained.

[0071] In the phase differential image generating step S7, the phase differential image generating unit 65 of the processing unit 60 can generate a phase differential image represented by the phase of the complex differential interference image W(r). Furthermore, in the refractive index distribution image generating step S8, the refractive index distribution image generating unit 66 of the processing unit 60 can obtain a phase differential image (i.e., a three-dimensional phase differential image) at each position in the z-axis direction using the equation for free propagation of a wavefront, and can generate a refractive index distribution image of the observation object S by deconvolution based on the phase differential image.

[0072] <Method for Evaluating Three-Dimensional Tissue> The evaluation method of this embodiment includes the steps of preparing a three-dimensional tissue containing epithelial cells (preparation step), acquiring refractive index distribution data of the three-dimensional tissue at multiple time points (refractive index distribution data acquisition step), evaluating the formation process and quality of an epithelial lumen formed in the three-dimensional tissue using the acquired refractive index distribution data at multiple time points (epithelial lumen evaluation step), identifying a region of cells that have undergone programmed cell death and / or a region of cells that have undergone necrosis (dead cell region identification step), identifying a region of vesicles (vesicle region identification step), and evaluating the three-dimensional tissue based on the results identified and evaluated in the epithelial lumen evaluation step, the dead cell region identification step, and / or the vesicle region identification step (three-dimensional tissue evaluation step).

[0073] <Preparation Step> In the preparation step, a three-dimensional tissue containing epithelial cells is prepared. The preparation method in the preparation step may be any method that can prepare a three-dimensional tissue containing epithelial cells and can acquire refractive index distribution data of the prepared three-dimensional tissue at multiple points in time. For example, the preparation method includes seeding cells containing epithelial cells into a culture vessel that is optically transparent and therefore applicable to the acquisition of refractive index distribution data, and that can prepare a three-dimensional tissue by seeding cells, and culturing the cells under general cell culture conditions (e.g., 37°C, 5% CO ２For example, the production method may be a method including seeding cells including epithelial cells into a culture vessel configured to allow recovery of a three-dimensional tissue and capable of producing a three-dimensional tissue when the cells are seeded therein, and culturing the cells under general cell culture conditions, recovering the three-dimensional tissue immediately before performing the refractive index distribution data acquisition step, and seeding the three-dimensional tissue used after performing the refractive index distribution data acquisition step back into the culture vessel and culturing it again.

[0074] Examples of culture vessels capable of producing three-dimensional tissues by seeding cells include those with a concave bottom that allow cells to be cultured three-dimensionally when seeded, and such culture vessels can be suitably used for producing three-dimensional tissues such as spheroids. Examples of culture vessels capable of producing three-dimensional tissues by seeding cells include those configured to produce three-dimensional tissues having multiple substructures, such as multiple epithelial tissues or epithelial tissue and parenchymal tissue, by seeding and culturing different types of cells from separate channels, and such culture vessels can be suitably used for producing three-dimensional tissues such as organoids.

[0075] A culture vessel configured to allow the recovery of three-dimensional tissue is a culture vessel that can recover three-dimensional tissue without causing dissociation of intercellular adhesions between the cells of the three-dimensional tissue. A culture vessel configured to allow the recovery of three-dimensional tissue may be, for example, a culture vessel whose surface is coated with a dissolvable coating agent (e.g., Matrigel), and such a culture vessel allows the recovery of three-dimensional tissue by dissolving the coating agent. Furthermore, a culture vessel configured to allow the recovery of three-dimensional tissue may be, for example, a culture vessel whose surface is coated with a light-transmitting sheet that can be peeled off together with the formed three-dimensional tissue.

[0076] In the production process, the culture period of cells for producing three-dimensional tissue may be any period that results in the production of three-dimensional tissue, and may be, for example, 3 days or more, 7 days or more, 14 days or more, 21 days or more, or 28 days or more, or 180 days or less, 150 days or less, 120 days or less, 90 days or less, 60 days or less, or 45 days or less, and these upper and lower limits can be freely combined.

[0077] <Refractive Index Distribution Data Acquisition Step> In the refractive index distribution data acquisition step, refractive index distribution data of the three-dimensional tissue created in the fabrication step is acquired. In the evaluation method of this embodiment, the process of epithelial lumen formation is evaluated using refractive index distribution data at multiple time points. Therefore, the evaluation method of this embodiment includes multiple refractive index distribution data acquisition steps. That is, in the evaluation method of this embodiment, the refractive index distribution data acquisition step is performed multiple times. An evaluation method of one aspect of this embodiment may include, for example, three or more or five or more refractive index distribution data acquisition steps, and may also include, for example, one, two, three, four, five, six, seven, eight, nine, ten, or more refractive index distribution data acquisition steps. All of the multiple refractive index distribution data acquisition steps may be performed simultaneously with the fabrication step, or one refractive index distribution data acquisition step may be performed immediately after the fabrication step, and the remaining refractive index distribution steps may be performed simultaneously with the fabrication step. This allows the process of epithelial lumen formation in the fabrication step to be evaluated over time, making it easier to evaluate the process of epithelial lumen formation. The method for acquiring refractive index distribution data in the refractive index distribution data acquisition step is as described above, for example, ODT.

[0078] The evaluation method of this embodiment includes a step of acquiring multiple refractive index distribution data, thereby acquiring refractive index distribution data at multiple time points, where at least two of the multiple time points are separated by at least one day. That is, the two most distant time points are separated by at least one day. In one aspect, at least two of the multiple time points may be separated by at least one day, two or more days, three or more days, four or more days, five or more days, seven or more days, ten or more days, fifteen or more days, twenty or more days, twenty-five or more days, or thirty or more days, or may be separated by at most 50 days, 40 or less days, 32 or less days, 27 or less days, 21 or less days, 16 or less days, 12 or less days, or nine or less days, and these upper and lower limits can be freely combined. In another aspect, at least two of the multiple time points may be separated by at least one day and at most 50 days, at least three days and at most 27 days, or at least five days and at most 16 days. When at least two of the multiple time points are separated by a period of time equal to or greater than the lower limit, the structure of the epithelial lumen at different stages of the formation process can be evaluated over time, thereby enabling the formation process of the epithelial lumen to be evaluated favorably.

[0079] <Epithelial lumen evaluation step> In the epithelial lumen evaluation step, refractive index distribution data at multiple time points is used to evaluate the formation process and quality of an epithelial lumen formed in three-dimensional tissue. The refractive index distribution data at multiple time points used in this embodiment is acquired in the refractive index distribution data acquisition step. In the epithelial lumen evaluation step, first, the region of the epithelial lumen in the refractive index distribution data is identified, and then the formation process and quality of the identified epithelial lumen are evaluated.

[0080] In one aspect, the epithelial lumen evaluation step identifies an epithelial lumen region in each of refractive index distribution data at multiple time points. In one aspect, the epithelial lumen evaluation step may identify the region as an epithelial lumen region if the refractive index, circularity, maximum diameter, and / or area in the refractive index distribution data satisfy at least one, at least two, at least three, or more of the following specific requirements:

[0081] In one embodiment, the region of the epithelial lumen is identified by identifying a region that exists in the extracellular region and has a lower refractive index than epithelial cells. The identified region with a lower refractive index may be, for example, a region with a lower refractive index than the entire epithelial cell, or may be, for example, a region with a lower refractive index than the cytoplasm of the epithelial cell. Specifically, for example, a region may be identified as a region of the epithelial lumen if the average or median refractive index of the region is lower than the average or median refractive index of the cytoplasm or the entire epithelial cell. More specifically, a region may be identified as a region of the epithelial lumen if the difference between the average or median refractive indexes is 0.001 or more, 0.002 or more, 0.003 or more, 0.004 or more, or 0.005 or more.

[0082] In one aspect, the epithelial lumen region is identified by a region in which the circularity of the cross section of the refractive index distribution data is equal to or greater than a predetermined lower limit. For example, the epithelial lumen region may be identified by a region in which the circularity of the cross section of the refractive index distribution data is 0.50 or greater, 0.70 or greater, 0.75 or greater, 0.80 or greater, 0.85 or greater, 0.90 or greater, or 0.95 or greater. In another aspect, the epithelial lumen region may be identified by a region in which the circularity of the cross section of the refractive index distribution data monotonically increases over time. The circularity may be the circularity of the flow path cross section of the tube in the tubular region included in the refractive index distribution data.

[0083] In one aspect, the epithelial lumen region may be identified as a region having a maximum diameter (the length of the longest line segment that can be drawn within the region) of 10 μm or more, 15 μm or more, 20 μm or more, 25 μm or more, 30 μm or more, or 50 μm or more in a cross section of the refractive index distribution data. ２ Above, 20μm ２ Above, 30 μm ２ Above, 60 μm ２ More than 100μm ２ More than 200μm ２ More than 300μm ２ More than 500μm ２ or more or 1000 μm２ The above-mentioned regions may be identified as the epithelial lumen region. Furthermore, in one aspect, the region of the epithelial lumen may be identified as the epithelial lumen region by a region in which the area of ​​the cross section of the refractive index distribution data monotonically increases over time. These maximum diameters or areas may be, for example, the maximum diameters or areas of the cross sections of the flow channels of the tubes in the tubular region included in the refractive index distribution data.

[0084] In one embodiment, the formation process of an epithelial lumen is evaluated based on the shape of the epithelial lumen region determined from refractive index distribution data at multiple time points, and the formation process is evaluated based on changes in the structure of the epithelial lumen over time. For example, if a dead cell region (described below) is not observed within the epithelial lumen region, while the size and / or number of a vesicle region (described below) in the epithelial cells decreases over time, or the vesicle region accumulates toward the epithelial lumen region over time, the epithelial lumen can be identified as having been formed by a hollowing-type formation process. Furthermore, if a dead cell region (described below) is observed within the epithelial lumen region, and the size of the dead cell region decreases over time while the size of the epithelial lumen region increases over time, the epithelial lumen can be identified as having been formed by a cavitation-type formation process. Furthermore, if an epithelial lumen is formed through a process that does not correspond to either the hollowing-type or cavitation-type processes, the epithelial lumen can be identified as a type other than the hollowing-type or cavitation-type. Thus, in one aspect, the epithelial lumen evaluation step may include identifying the epithelial lumen formation process as a hollowing type, a cavitation type, or a type other than the hollowing type and the cavitation type.Furthermore, in one aspect, the epithelial lumen evaluation step may include identifying the epithelial lumen formation process as a hollowing type or a cavitation type.

[0085] In one embodiment, the quality of an epithelial lumen is evaluated based on parameters of the epithelial lumen region identified from refractive index distribution data at multiple time points. For example, an epithelial lumen in a region that satisfies at least two, at least three, at least four, at least five, at least six, at least seven, or more of the above-mentioned specific requirements for the epithelial lumen region may be evaluated as a highly mature and high-quality epithelial lumen. For example, since a highly mature epithelial lumen has fewer remnants such as dead cells within the lumen, in one embodiment, an epithelial lumen with a low refractive index may be evaluated as a highly mature and high-quality epithelial lumen. Also, in one embodiment, an epithelial lumen with a small area of ​​the dead cell region (described below) within the epithelial lumen region may be evaluated as a highly mature and high-quality epithelial lumen.

[0086] <Dead Cell Region Identification Step> In the dead cell region identification step, the region of cells undergoing programmed cell death and / or the region of cells undergoing necrosis is identified using refractive index distribution data. In the present disclosure, the region of cells undergoing programmed cell death and the region of cells undergoing necrosis are collectively referred to as dead cell region.

[0087] Programmed cell death is a broad concept that refers to cell death that falls into the latter category when cell death is broadly divided into two groups: (I) accidental cell death (ACD) and (II) programmed cell death (PCD) or regulated cell death (RCD). Known examples of programmed cell death include apoptosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entosis, nephrosis, and autophagic cell death. The programmed cell death that can be identified in this embodiment may be at least one selected from the group consisting of apoptosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entosis, netosis, and autophagic cell death, or may be at least one selected from the group consisting of apoptosis, ferroptosis, pyroptosis, parthanatos, entosis, netosis, and autophagic cell death, or may be apoptosis.

[0088] In one embodiment of the dead cell region identification process, the region of cells undergoing programmed cell death is identified based on the spatial variation in refractive index. The spatial variation is a parameter related to the degree of spatial variation in refractive index determined for each pixel or voxel, and can be obtained, for example, by a differential calculus, a difference calculus (one-dimensional differential calculus), a blob detection method, or the like. When calculating the spatial variation in refractive index using a differential calculus, for example, a convolution is performed on a refractive index distribution image using the fourth-order derivative of a Gaussian function as the kernel, and the absolute value of the convoluted image is then taken, followed by threshold processing for each pixel or voxel to extract areas where the degree of spatial variation in refractive index is large. When calculating the spatial variation in refractive index using a difference calculus, the difference between pixel values ​​of adjacent pixels or voxels in each direction is calculated, and the sum of squares of the difference components in each direction is then taken, followed by threshold processing for each pixel or voxel to extract areas where the degree of spatial variation in refractive index is large. When calculating the spatial change in refractive index using the blob detection method, a difference of Gaussians process, which is often used in blob detection, is performed, and then threshold processing is performed on the absolute value of the processed image for each pixel or voxel to extract areas where the degree of change in refractive index relative to space is large.

[0089] The identification of the region of cells undergoing programmed cell death, for example, is performed based on the magnitude relationship between the spatial change in refractive index at pixels or voxels contained in the refractive index distribution data and a threshold value. That is, a region where the spatial change in refractive index is greater than a threshold value is determined to be a region of cells undergoing programmed cell death. The threshold value can be determined based on the type and state of the three-dimensional tissue and the type and content of cells contained in the three-dimensional tissue. For example, the threshold value can be determined using known information, or can be determined so that a region of cells that can be determined to have undergone programmed cell death based on cell morphology is determined to be a region of cells undergoing programmed cell death. Alternatively, the threshold value can be calculated using unsupervised machine learning such as clustering. Furthermore, the threshold value can be determined so that a region of cells that can be determined to have undergone programmed cell death is determined to be a region of cells that can be determined to have undergone programmed cell death based on the refractive index distribution data of a three-dimensional tissue (reference) other than the three-dimensional tissue (sample) in which the region of cells undergoing programmed cell death is determined.

[0090] The region of cells undergoing programmed cell death is identified, for example, by inputting the refractive index distribution data of the three-dimensional tissue into a learning model trained using training data including data on the region of programmed cell death of a reference three-dimensional tissue and refractive index distribution data of the reference three-dimensional tissue corresponding to the region of programmed cell death, and the feature used by the learning model includes the spatial variation of the refractive index at the pixel or voxel included in the refractive index distribution data. The reference three-dimensional tissue is an object composed primarily of cells, prepared or obtained by a method similar to that of the three-dimensional tissue.

[0091] For a more detailed method and device for identifying the region of cells that have undergone programmed cell death, the method and device described in Patent Document 3 can be used. The contents of Patent Document 3 are incorporated herein by reference.

[0092] Necrosis is a type of cell death that occurs when cells are exposed to external factors, such as hypoxia, high temperature, toxins, nutrient deficiency, and cell membrane damage. Necrotic cells are characterized by morphological changes, such as swelling and cell membrane disruption, but do not exhibit the pronounced nuclear fragmentation seen in apoptosis, and the nuclear characteristics are maintained. Necrotic cells first undergo cell membrane disruption, followed by leakage of cell contents and subsequent cell disruption, including the nucleus, leading to cell death through a sequential process. Therefore, cells undergoing necrosis are thought to undergo morphological changes similar to those of necrotic cells.

[0093] When cell death is broadly divided into two groups, namely, (I) accidental cell death (ACD) and (II) programmed cell death (PCD) or regulated cell death (RCD), necrosis is generally classified as the former. On the other hand, necroptosis, which is a type of programmed cell death, is known to exhibit morphological changes similar to those observed in necrosis, such as cell swelling, cell membrane breakdown, and maintenance of nuclear characteristics. Therefore, in one embodiment of the dead cell region identification step, the region of cells undergoing necroptosis may be determined in addition to the region of cells undergoing necrosis.

[0094] In one embodiment of the dead cell region specifying step, the region of cells that have undergone necrosis is determined based on the fact that the region of each cell included in the refractive index distribution data has characteristics of necrotic cells.

[0095] The characteristics of necrotic cells include at least the characteristic of having a region corresponding to the nucleus. The nucleus (cell nucleus, Nucleus) is one of the organelles of eukaryotic cells. In particular, in mammalian cells, it exists in a spherical shape with a radius of approximately 1 to 10 μm outside of the mitotic phase. Typically, one cell has one nucleus. The nucleus is separated from the cytoplasm by a nuclear membrane and contains structures such as nucleoli and chromatin (a thread-like structure consisting of intranuclear DNA). Therefore, the region corresponding to the nucleus is, for example, an approximately circular or approximately spherical region present within the region of each cell included in the refractive index distribution data, and is a region whose statistical value of the refractive index is greater than the statistical value of the refractive index of the entire cell. The statistical value may be, for example, the mean value, median value, maximum value, or minimum value, and may be the mean value or median value. The approximately circular region refers to a region whose circularity is equal to or greater than a threshold value, and the approximately spherical region refers to a region whose sphericity is equal to or greater than a threshold value. The threshold value can be determined based on the type and state of the three-dimensional tissue, the type and content of cells contained in the three-dimensional tissue, etc. It can also be determined so that a region recognized as a nucleus based on other structural features in the refractive index distribution data of a three-dimensional tissue (reference) other than the three-dimensional tissue (sample) used to determine the region of necrotic cells is determined to be the region corresponding to the nucleus. The threshold value can be, for example, 60%, 65%, 70%, 75%, or 80%. The region corresponding to the nucleus is, for example, a substantially circular or spherical region present within the region of each cell included in the refractive index distribution data and surrounded by a membrane structure with a high refractive index corresponding to the nuclear membrane. The region corresponding to the nucleus is, for example, a substantially circular or spherical region present within the region of each cell included in the refractive index distribution data and surrounded by a membrane structure with a high refractive index corresponding to the nuclear membrane, and containing a nucleolus structure with a high refractive index and a filamentous chromatin structure with a lower refractive index than the nucleolus.

[0096] In one aspect, the characteristics of necrotic cells further include one or more characteristics selected from the group consisting of a statistical value of the refractive index of the whole cell being below a threshold and a statistical variation of the refractive index of the nucleus being above a threshold. The statistical value may be, for example, a mean value, a median value, a maximum value, or a minimum value, and may be the mean value or the median value. In necrotic cells, the refractive index of the whole cell is lower than that of live cells because the cellular contents leak due to cell rupture. Furthermore, focusing on the nucleus, the nucleoli within the nucleus have a relatively high refractive index even in necrotic cells, resulting in a large statistical variation in the refractive index of the nucleus. Therefore, the region of a necrotic cell can be determined based on whether the region of each cell included in the refractive index distribution data has one or more characteristics selected from the group consisting of these characteristics.

[0097] The statistical value threshold and statistical variation threshold can be determined depending on the type and state of the three-dimensional tissue and the type and content of cells contained in the three-dimensional tissue, and may be determined using known information, for example, or may be determined so that a region of cells that can be determined to be necrotic based on cell morphology is determined to be a region of necrotic cells, or may be calculated by unsupervised machine learning such as clustering. Furthermore, they can also be determined so that a region of cells that can be determined to be necrotic based on refractive index distribution data of a three-dimensional tissue (reference) different from the three-dimensional tissue (sample) used to determine the region of necrotic cells is determined to be a region of necrotic cells.

[0098] In one aspect, the determination of the region of necrotic cells is performed by inputting the refractive index distribution data of the three-dimensional tissue into a learning model trained using training data including necrotic region data of a reference three-dimensional tissue and refractive index distribution data of the reference three-dimensional tissue corresponding to the necrotic region data. In one embodiment, the features used by the learning model include features corresponding to features having a region corresponding to the nucleus. The reference three-dimensional tissue is an object composed primarily of cells, prepared or obtained by a method similar to that of the three-dimensional tissue.

[0099] For a more detailed method and device for identifying the region of cells that have undergone necrosis, the method and device described in Patent Document 4 can be used. The contents of Patent Document 4 are incorporated herein by reference.

[0100] <Follicle Region Identification Step> In the vesicle region identification step, a vesicle region is identified. Identifying the vesicle region allows for suitable evaluation of, for example, the hollowing-type formation process, which is the process in which intracellular vesicles are transported to the outside of the cell to form an epithelial lumen. In one aspect, in the vesicle region identification step, a region may be identified as a vesicle region if the refractive index, circularity, sphericity, and / or area in the refractive index distribution data satisfy at least one, at least two, at least three, or more of the following specific requirements:

[0101] In one embodiment, a region in the cytoplasm that has a lower refractive index than epithelial cells is identified as a vesicle region. The identified region with a lower refractive index may be, for example, a region with a lower refractive index than the entire epithelial cell, or may be, for example, a region with a lower refractive index than the cytoplasm of an epithelial cell. Specifically, for example, a region may be identified as a vesicle region if the average or median refractive index of the region is lower than the average or median refractive index of the cytoplasm or the entire epithelial cell. More specifically, a region may be identified as a vesicle region if the difference between the average or median refractive indexes is 0.001 or more, 0.002 or more, 0.003 or more, 0.004 or more, or 0.005 or more.

[0102] In one embodiment, a region where the sphericity in the refractive index distribution data and / or the circularity in the cross section of the refractive index distribution data is equal to or greater than a predetermined lower limit is identified as a vesicle region. For example, a region where the sphericity or circularity is 0.50 or more, 0.70 or more, 0.75 or more, 0.80 or more, 0.85 or more, 0.90 or more, or 0.95 or more may be identified as a vesicle region.

[0103] In one embodiment, the area of ​​the vesicle is determined by the cross section of the refractive index distribution data. ２ Below, 30μm ２ Below, 20 μm ２Below, 15μm ２ Below, 10μm ２ Below, 7 μm ２ Less than or equal to 5 μm ２ The following regions may be identified as vesicle regions: In one embodiment, vesicle regions are identified as regions with a volume of 250 μm in the refractive index distribution data. ３ Below, 200 μm ３ Below, 150μm ３ Below, 100 μm ３ Below, 70μm ３ Below, 50 μm ３ Less than or equal to 40 μm ３ The following regions may be identified as vesicle regions: In one aspect, regions in which the maximum diameter in the refractive index distribution data or refractive index tomography data is 8 μm or less, 6 μm or less, 5 μm or less, 4 μm or less, or 3 μm or less may be identified as vesicle regions.

[0104] <Three-dimensional tissue evaluation step> In the three-dimensional tissue evaluation step, the three-dimensional tissue is evaluated based on the results of the identification and evaluation in the epithelial lumen evaluation step, the dead cell region identification step, and / or the vesicle region identification step. In one aspect, a three-dimensional tissue having an epithelial lumen but a small number of epithelial lumens may be evaluated as being highly mature and of high quality. For example, a three-dimensional tissue having one to five or one to two epithelial lumens may be evaluated as being highly mature and of high quality, and a three-dimensional tissue having one epithelial lumen may be evaluated as being more mature and of high quality. In one aspect, a three-dimensional tissue having a highly mature and high-quality epithelial lumen may be evaluated as being highly mature and of high quality. In one aspect, a three-dimensional tissue having a small dead cell region may be evaluated as being highly mature and of high quality. In one aspect, a three-dimensional tissue having a small vesicle size and / or number may be evaluated as being highly mature and of high quality. Note that as epithelial tissue matures, the frequency of endocytosis decreases. Therefore, a three-dimensional tissue having a small number of vesicles may be evaluated as being highly mature and of high quality.

[0105] FIG. 1 shows an example of a three-dimensional tissue to be evaluated and its refractive index tomographic data. Epithelial culture A has no epithelial lumens and many follicles. Epithelial culture B has many epithelial lumens with small areas, and dead cell regions are present within these lumens. In contrast, epithelial culture C has only one large epithelial lumen, and no follicles or dead cell regions are observed. Based on these results, epithelial culture C may be evaluated as being highly mature and of high quality.

[0106] Furthermore, in the three-dimensional tissue evaluation step, the three-dimensional tissue may be evaluated using the positions of the epithelial lumen region, dead cell region, and / or vesicle region identified in the epithelial lumen evaluation step, dead cell region identification step, and / or vesicle region identification step as indicators. For example, three-dimensional tissue in which the epithelial lumen region, dead cell region, and / or vesicle region are located closer to the center of the three-dimensional tissue is considered to be more similar to a living organism, and therefore may be evaluated as being more mature and of higher quality.

[0107] 2 is a diagram showing an example of refractive index tomographic data of a three-dimensional tissue to be evaluated using the positions of the epithelial lumen region, dead cell region, and vesicle region as indicators. Epithelial culture D has an epithelial lumen region, dead cell region, and vesicle region near the surface of the three-dimensional tissue, while epithelial culture E has an epithelial lumen region, dead cell region, and vesicle region near the center of the three-dimensional tissue. For example, based on these results, epithelial culture E may be evaluated as being more mature and of higher quality. In this case, the positions of the epithelial lumen region, dead cell region, and vesicle region can be determined, for example, by the maximum diameter L in the refractive index tomographic data. ｍａｘ After specifying the point, its midpoint O may be identified and the distance from O may be used as an index (FIG. 2).

[0108] Furthermore, in the evaluation in the three-dimensional tissue evaluation step, the maturity and quality of the three-dimensional tissue may be comprehensively evaluated by weighting the criteria for high-maturity, high-quality three-dimensional tissue as described above. In such a comprehensive evaluation, for example, the parameters for each criterion may be scored, and the evaluation may be performed using the sum of the scores as an index. In this case, for example, since the method of this embodiment includes evaluating the process of epithelial lumen formation and its quality, a heavy score may be assigned to the process of epithelial lumen formation and its quality.

[0109] <Effects> The evaluation method of this embodiment includes evaluating the process of epithelial lumen formation in three-dimensional tissue containing epithelial cells using refractive index distribution data at multiple time points. This allows the process of epithelial lumen formation in three-dimensional tissue containing epithelial cells to be evaluated based on changes in refractive index distribution data over time. Much of the process of epithelial lumen formation in epithelial tissue remains unknown, and it is not always easy to identify the process by which the epithelial lumen is formed from the epithelial lumen that is finally formed. Furthermore, it is believed that epithelial lumen formation in cancerous tissue occurs through a process different from that in normal epithelial tissue. Therefore, it is even more difficult to identify and evaluate abnormal formation processes caused by such diseases from the epithelial lumen that is finally formed. In contrast, this embodiment evaluates the process of epithelial lumen formation using refractive index distribution data at multiple time points, allowing the time-dependent changes in the structure of the epithelial lumen during the formation process to be evaluated from the changes in refractive index distribution data over time.

[0110] The evaluation method of this embodiment includes not only evaluating the process of epithelial lumen formation in three-dimensional tissue, but also identifying dead cell regions and / or vesicle regions. Because cell death is involved in the cavitation-type formation process and vesicles are involved in the hollowing-type formation process, the process of epithelial lumen formation can be appropriately evaluated. Furthermore, three-dimensional tissue can be evaluated from multiple perspectives based on parameters of the dead cell regions and / or vesicle regions, as well as the process and quality of epithelial lumen formation.

[0111] In the above-described example, the three-dimensional tissue was prepared from cells in the preparation step, but in another embodiment, the three-dimensional tissue may be prepared from developing epithelial tissue collected from a human or non-human animal. By culturing the developing epithelial tissue in a culture vessel (explant culture), it is possible to prepare a three-dimensional tissue that preferably reproduces the epithelial tissue of the human or non-human animal from which it was collected.

[0112] In the above-described example, the refractive index distribution data at multiple time points was obtained in the refractive index distribution data acquisition process, but in another aspect, the epithelial lumen evaluation process, the dead cell region identification process, and / or the vesicle region identification process may be performed using refractive index distribution data that may have been obtained in advance and stored in a database.

[0113] <Application Example 1: Evaluation of Fabrication Method> According to the above-described method for evaluating three-dimensional tissues, for example, by evaluating each of a plurality of three-dimensional tissues fabricated under different fabrication conditions, it is possible to indirectly evaluate the fabrication conditions (fabrication method) of the three-dimensional tissue based on the maturity and quality of the three-dimensional tissue.

[0114] <Application Example 2: Drug Evaluation and Drug Screening> According to the above-described method for evaluating a three-dimensional tissue, for example, by evaluating a three-dimensional tissue exposed to a drug, it is possible to indirectly evaluate or screen for a drug based on the maturity and quality of the three-dimensional tissue. Thus, in one aspect, this embodiment can be a drug screening method that includes exposing a three-dimensional tissue containing epithelial cells or cells before the formation of the three-dimensional tissue to a drug (drug exposure step), and evaluating the three-dimensional tissue according to the evaluation method of the above-described embodiment.

[0115] In the drug exposure step, a three-dimensional tissue containing epithelial cells or cells before the formation of such a tissue is exposed to a drug. The drug to be exposed is the drug to be screened, i.e., a candidate drug. The form of the drug is not particularly limited, and may be, for example, a synthetic small molecule, peptide, protein, nucleic acid, or a complex thereof. The drug may have known or unknown efficacy. If the drug has known efficacy, the known efficacy may be related or unrelated to the epithelial lumen. Exposure of the three-dimensional tissue or cells before the formation of such a tissue to a drug can be achieved by adding the drug or its encapsulated form (e.g., liposomes or viral capsids) to the culture supernatant in which the three-dimensional tissue or cells are cultured. The drug concentration and exposure time when exposing the three-dimensional tissue or cells before the formation of such a tissue to a drug may be appropriately determined by those skilled in the art and may be optimized over multiple screening trials.

[0116] The drug exposure step is carried out at least before the final refractive index distribution data acquisition step, and the detailed timing thereof may be appropriately determined by a person skilled in the art depending on the mechanism of action or purpose of the drug to be evaluated or screened. The drug exposure step may be carried out before the fabrication step, simultaneously with the fabrication step, after the fabrication step and before the final refractive index distribution data acquisition step, or across multiple of these periods.

[0117] In one embodiment, when the drug exposure step is performed before the preparation step or simultaneously with the preparation step, for example, in the first half of the preparation step, the screening method of this embodiment can evaluate the process of epithelial lumen formation in three-dimensional tissue exposed to the drug. Abnormal formation of epithelial lumens is thought to be more likely to occur under certain pathological conditions (e.g., Non-Patent Document 4). Therefore, for example, by exposing organoids of cancer tissue to a drug and then evaluating the process and quality of epithelial lumen formation in the cancer tissue, cancer therapeutic drugs that can suppress epithelial lumen abnormal formation in cancer tissue can be screened (selected). Furthermore, for example, by exposing organoids of normal tissue to a drug and then evaluating the process and quality of epithelial lumen formation in the normal tissue, drugs that may cause diseases accompanied by epithelial lumen abnormal formation as a side effect can be negatively screened (excluded).

[0118] Figure 3 shows an example of negative screening of drugs when the drug exposure process is performed simultaneously with the preparation process, during the first half of the process. In the example shown in Figure 3, a mature epithelial lumen is formed in the control three-dimensional tissue to which no drug was added. In contrast, in the three-dimensional tissue to which drug A was added, areas of cell death were observed in the epithelial lumen and the area of ​​the epithelial lumen was small, indicating that while epithelial lumens are being formed during the cavitation-type formation process, the epithelial lumen is likely to be immature. Furthermore, in the three-dimensional tissue to which drug B was added, numerous vesicles were observed, but no clearly detectable epithelial lumen like in the control was observed, indicating that there is likely an abnormality in the formation process of the epithelial lumen in the three-dimensional tissue. Therefore, based on these results, drug A and drug B can be negatively screened (excluded) as drugs that cause abnormal formation of epithelial lumens.

[0119] In one embodiment, when the drug exposure step is performed simultaneously with the fabrication step, for example, during the latter half of the fabrication step, or after the fabrication step and before the final refractive index distribution data acquisition step, the screening method of this embodiment involves evaluating the process of epithelial lumen formation in the three-dimensional tissue, and then exposing the three-dimensional tissue to a drug, thereby evaluating the effects of the drug on the three-dimensional tissue and epithelial lumen depending on the process of epithelial lumen formation. In this way, drugs that do not induce cell death in three-dimensional tissues with epithelial lumens formed by typical formation processes, such as hollowing or cavitation, but induce cell death in three-dimensional tissues with epithelial lumens formed by abnormal formation processes, can be screened (selected) as drugs selective for three-dimensional tissues with abnormal epithelial lumen formation. Drugs selected in this manner are expected to have minimal side effects.

[0120] <Application Example 3: Recovery of Epithelial Lumen Contents> In one embodiment of the evaluation method, contents may be recovered from the epithelial lumen whose formation process has been evaluated. FIG. 4 is a schematic diagram showing an example of recovering contents from the epithelial lumen. The contents may be recovered using, for example, a drain. The recovered contents may be evaluated by mass spectrometry or high-performance liquid chromatography, and such evaluations can evaluate, for example, differences in the contents of the epithelial lumen at each formation process. Furthermore, the evaluation method of this embodiment uses refractive index distribution data to non-invasively identify the position of the lumen inside the epithelial culture, allowing the contents to be recovered while suppressing artifacts that occur in the contents compared to conventional methods that require labeling.

[0121] <Evaluation Device and Program> Fig. 5 is a diagram showing an example of the configuration of an evaluation device used in the evaluation method of this embodiment. The evaluation device shown in Fig. 5 includes a data acquisition unit and an evaluation unit.

[0122] The data acquisition unit acquires refractive index distribution data of three-dimensional tissue containing epithelial cells. The epithelial cells, three-dimensional tissue, and refractive index distribution data are the same as those described in the three-dimensional tissue evaluation method. The configuration of the data acquisition unit may be the same as that of the device described in the refractive index distribution data section of the three-dimensional tissue evaluation method, and more specifically, may be the same as that of the device described as being usable in ODT, for example. The data acquisition unit also has a calculation unit that performs various calculations, including executing a data acquisition step to acquire refractive index distribution data of three-dimensional tissue containing epithelial cells.

[0123] The evaluation unit is a unit that evaluates the formation process and quality of an epithelial lumen formed in three-dimensional tissue using refractive index distribution data at multiple time points. That is, the evaluation unit is a unit that performs the epithelial lumen evaluation step described in the three-dimensional tissue evaluation method. In other words, the evaluation unit is a unit that executes an evaluation step that evaluates the formation process of an epithelial lumen formed in three-dimensional tissue using refractive index distribution data at multiple time points. Furthermore, the evaluation unit may be a unit that performs a dead cell region specifying step, a vesicle region specifying step, and / or a three-dimensional tissue evaluation step in addition to the epithelial lumen evaluation step.

[0124] The calculation unit and evaluation unit of the data acquisition unit described above include a processing unit including a CPU that performs various calculation processes, a memory unit including a hard disk drive, RAM, ROM, etc. that stores data and programs, a display unit including a liquid crystal display that displays processing results, etc., and an input unit including a keyboard, mouse, etc. that accepts input of various conditions for acquiring and displaying interference images. The calculation unit and evaluation unit may be configured as a smart device such as a tablet terminal that has a touch panel or the like as an input unit. Furthermore, the processing unit and memory unit of the calculation unit and evaluation unit may be configured as an FPGA (field-programmable gate array) or a microcomputer.

[0125] The present disclosure will be described in more detail below using examples, but the present disclosure should not be construed as being limited to the following examples.

[0126] Example 1: Evaluation of three-dimensional tissue containing epithelial cells [Step 1: Preparation of epithelial tissue] Three-dimensional tissue was prepared using MDCK (Madin-Darby canine kidney) cells, an established epithelial cell line derived from canine renal tubular epithelium. Three-dimensional tissue obtained by 3D embedded culture or 2.5D culture of MDCK cells is known to form cysts (spherical cell clusters) and exhibit various luminal abnormality phenotypes, such as abnormalities in the number and morphology of lumens. Therefore, MDCK cells are one of the cell lines commonly used to evaluate epithelial lumens (e.g., Non-Patent Document 4). In three-dimensional tissue prepared from MDCK cells, renal tubules are formed as epithelial lumens formed by renal tubular epithelial cells.

[0127] The three-dimensional tissue was prepared by the following procedure. First, 5 × 10 MDCK cells were placed on a glass-bottom dish coated with Matrigel (Corning). ４ ~5 x 10 ５ The seeded cells were cultured in MEM medium containing 10% fetal bovine serum (FBS) at a cell concentration of 1000 cells / mL under 5% CO ２ The cells were cultured at 37°C and 100% humidity for 4, 7, or 14 days. After the culture, the dish was exposed to a temperature of 4°C to melt the Matrigel, and the MDCK cell culture (three-dimensional tissue) was collected.

[0128] [Step 2: Acquisition of Refractive Index Distribution Data] Refractive index distribution data was acquired by optical diffraction tomography (ODT) for the three-dimensional tissue prepared in step 1. The refractive index distribution data was acquired using an observation device described in Patent Document 5, which is equipped with a 40x objective lens and a light source with a wavelength of 633 nm.

[0129] Fig. 6 shows representative refractive index tomographic data extracted from refractive index distribution data of three-dimensional tissues cultured for 4, 7, or 14 days. Note that different three-dimensional tissues were used to obtain the refractive index distribution data after 4, 7, or 14 days of culture. In Fig. 6, z indicates the height of the cross section extracted as refractive index tomographic data from the bottom surface of the three-dimensional tissue.

[0130] [Step 3: Evaluation of Three-Dimensional Tissue] The refractive index tomographic data acquired and extracted in step 2 was used to evaluate three-dimensional tissue.

[0131] First, the renal tubule region, which is the epithelial lumen formed in the three-dimensional tissue, was evaluated. Figure 7 shows the region of interest (ROI) in the refractive index tomography data of the three-dimensional tissue cultured for 7 or 14 days shown in Figure 6, enclosed by a solid line. In the refractive index tomography data after 7 days of culture, the evaluation targets were the two lumens, lumen 1 and lumen 2, shown in the figure, and the entire three-dimensional tissue, which is the region enclosed by the outer solid line in the figure. In the refractive index tomography data after 14 days of culture, the evaluation targets were the lumen, which is the region enclosed by the inner solid line in the figure, and the entire three-dimensional tissue, which is the region enclosed by the outer solid line in the figure. The area, perimeter, and circularity of these regions, as well as the mean, standard deviation, and median refractive index, were measured using ImageJ. The results are shown in Table 1. As shown in Table 1, the refractive index of the lumen was smaller than that of the entire cell, and the refractive index was smaller after 14 days of culture than after 7 days of culture. From these results, for example, after 7 days of culture, the regions shown as lumen 1 and lumen 2, which have a refractive index smaller than that of the entire cell and have an average refractive index of 1.345 or less, could be identified as the epithelial lumen region.Furthermore, for example, after 14 days of culture, the region shown as lumen, which has a refractive index smaller than that of the entire cell and have an average refractive index of 1.335 or less, could be identified as the epithelial lumen region.

[0132] Furthermore, in addition to identifying the epithelial lumen area, the maturity and quality of the three-dimensional tissue were also evaluated based on the results in Table 1. For example, using the number of epithelial lumens as an indicator, the three-dimensional tissue after 7 days of culture had two epithelial lumens, whereas the three-dimensional tissue after 14 days of culture had only one epithelial lumen. Based on this, the three-dimensional tissue after 14 days of culture, which had fewer epithelial lumens, could be evaluated as a more mature, high-quality three-dimensional tissue.

[0133] Furthermore, for example, using the lumen area as an index, based on the fact that the lumen area of ​​the three-dimensional tissue after 14 days of culture was larger than that of the lumen after 7 days of culture, the three-dimensional tissue after 14 days of culture with a larger lumen area could be evaluated as a more mature and higher quality three-dimensional tissue. In addition to the evaluation of the three-dimensional tissue, based on the fact that of the two lumens observed in the three-dimensional tissue after 7 days of culture, lumen 1 had a larger area than lumen 2, lumen 1 with a larger area could be evaluated as a more mature and higher quality epithelial lumen.

[0134] Furthermore, for example, using the circularity of the lumen as an index, the three-dimensional tissue after 14 days of culture was found to have a higher circularity than the lumen after 7 days of culture, and based on this, the three-dimensional tissue after 14 days of culture with a higher circularity of the lumen could be evaluated as a more mature and high-quality three-dimensional tissue. In addition to the evaluation of the three-dimensional tissue, in the evaluation of the epithelial lumen, of the two lumens found in the three-dimensional tissue after 7 days of culture, the lumen 1 with a higher circularity could be evaluated as a more mature and high-quality epithelial lumen based on the fact that the lumen 1 had a higher circularity than the lumen 2.

[0135] Furthermore, for example, using the refractive index of the lumen as an index, based on the fact that the refractive index of the lumen observed in the three-dimensional tissue after 14 days of culture was smaller than that observed in the three-dimensional tissue after 7 days of culture, the three-dimensional tissue after 14 days of culture with a smaller refractive index could be evaluated as a more mature and high-quality three-dimensional tissue. Note that, since epithelial lumens are formed by the generation of cavities between cells or in places where cells were previously present, the lower the refractive index of the epithelial lumen, the less cell-derived structures remain in the lumen, and the more mature and high-quality the three-dimensional tissue can be evaluated.

[0136]

[0137] Next, the dead cell regions contained in the three-dimensional tissue were evaluated. Figure 8 shows the regions of interest (ROIs) in the refractive index tomography data of the three-dimensional tissue cultured for 7 or 14 days shown in Figure 6, enclosed by solid lines, that were used to evaluate the dead cell regions. In the refractive index tomography data after 7 days of culture, regions A and B shown in the figure were evaluated. In the refractive index tomography data after 14 days of culture, regions A and B shown in the figure were evaluated. The results of measuring the area, perimeter, and circularity of these regions, as well as the mean, standard deviation, and median refractive index, using ImageJ are shown in Table 2. As shown in Table 2, after 7 days of culture and after 14 days of culture, region A had a larger standard deviation of refractive index than region B. From these results, based on the method described in Patent Document 3, for example, region A could be estimated as the region of apoptotic cells after 7 days of culture and after 14 days of culture.

[0138] Furthermore, based on the results in Table 2, in addition to identifying the dead cell region, the maturity and quality of the three-dimensional tissue were also evaluated. For example, using the area of ​​the dead cell region as an indicator, the area of ​​the dead cell region in the three-dimensional tissue after 14 days of culture was smaller than that in the three-dimensional tissue after 7 days of culture. Based on this, the three-dimensional tissue after 14 days of culture, which had a smaller area of ​​the dead cell region, could be evaluated as a more mature and high-quality three-dimensional tissue. In addition to evaluating the three-dimensional tissue, the epithelial lumen was also evaluated. When comparing the lumen 1 in the three-dimensional tissue after 7 days of culture with the lumen in the three-dimensional tissue after 14 days of culture, the area of ​​the dead cell region in the latter was smaller than that in the former. Based on this, the lumen in the three-dimensional tissue after 14 days of culture could be evaluated as a more mature and high-quality epithelial lumen.

[0139] In addition, based on the results of Figures 6-8 and Tables 1 and 2, we investigated the use of refractive index distribution data at multiple time points to evaluate the formation process of epithelial lumens in three-dimensional tissues. Because lumen 2 observed in three-dimensional tissues after 7 days of culture did not contain dead cell regions within its lumen, it was difficult to determine the formation process of the epithelial lumen from the refractive index distribution data at 7 days of culture. In contrast, lumen 1 observed in three-dimensional tissues after 7 days of culture and lumen observed in three-dimensional tissues after 14 days of culture contained dead cell regions within their lumens. Therefore, although a definitive conclusion cannot be drawn because the refractive index distribution data is only from a single time point, it is suggested that these may represent epithelial lumens formed or in the process of forming lumens due to cell death, i.e., cavitation-type formation. As described above, by acquiring such refractive index distribution data at multiple time points and observing, for example, a decrease in the dead cell region within the lumen over time, it is possible to identify the lumen as an epithelial lumen formed during the cavitation-type formation process. It was also suggested that if such refractive index distribution data were obtained at multiple time points and it was observed that, for example, no dead cell areas were formed within the lumen and that the lumen was formed as intracellular vesicles accumulated in the intercellular areas and grew larger over time, the lumen could be identified as an epithelial lumen formed during the hollow-type formation process.

[0140]

[0141] Next, the vesicle regions contained in the three-dimensional tissue were evaluated. Figure 9 shows the regions of interest (ROIs) enclosed by solid lines in the refractive index tomography data of the three-dimensional tissue cultured for four days shown in Figure 6. Regions A, B, and C shown in the figure were evaluated, and the region indicated as a random cell in the figure was set as a comparison region, where cells containing mainly cytoplasm were present on the cross-sectional surface. The entire three-dimensional tissue, the region enclosed by the outer solid line in the figure, was also evaluated. The area, perimeter, and circularity of these regions, as well as the mean, standard deviation, and median refractive index, were measured using ImageJ. The results are shown in Table 3. As shown in Table 3, regions A, B, and C had smaller refractive indices than the random cell region and the entire three-dimensional tissue. First, these results revealed the presence of some kind of cavity in regions A, B, and C.

[0142] Next, it was evaluated whether the cavities in regions A, B, and C corresponded to lumens or vesicles. For example, according to the refractive index tomography data in FIG. 9, region A was located in the extracellular region, while regions B and C were located in the intracellular region. From these results, region A, which is the extracellular cavity, was identified as the region corresponding to the epithelial lumen, and regions B and C, which are intracellular cavities, were identified as the regions corresponding to vesicles. Furthermore, according to Table 3, for example, the area of ​​region A was 244 μm ２ , which was large compared to the cells, while area B and area C were 6.4 μm ２ and 2.9 μm ２ and was small compared to the cells. From these results, it was determined that the large area, region A, corresponds to the epithelial lumen, and the small areas, regions B and C, correspond to vesicles. Furthermore, from the above results, it was determined that region A, which is the large extracellular cavity, corresponds to the epithelial lumen, and regions B and C, which are the small intracellular cavities, correspond to vesicles.

[0143]

[0144] Example 2: Time-lapse observation of three-dimensional tissue containing epithelial cells Step 1: Preparation of epithelial tissue Three-dimensional tissue containing MDCK cells as epithelial cells was prepared by the following procedure. First, 5 × 10 MDCK cells were placed in a glass-bottom dish (MatTek, P35G-0-14-C) whose central bottom was coated with 100 μL of Matrigel (Corning) per well. ３ The seeded cells were cultured in MEM medium (culture medium) containing 10% fetal bovine serum (FBS) under 5% CO ２ The cells were cultured under conditions of 37°C and 100% humidity. Approximately 200 µL of culture medium per well was added to the area covered with Matrigel.

[0145] [Step 2: Obtaining Refractive Index Distribution Data] The three-dimensional tissues prepared in step 1 were observed on days 1, 2, and 7 after the start of culture. To perform time-lapse observations, each observation was performed by adding approximately 3 mL of culture medium to a glass-bottom dish and immersing the objective lens in the medium. Refractive index distribution data was obtained using optical diffraction tomography (ODT). The observation device described in Patent Document 5, equipped with a 60x magnification objective lens and a 633 nm wavelength light source, was used to obtain the refractive index distribution data.

[0146] Fig. 14 shows representative refractive index tomographic data extracted from the refractive index distribution data of the three-dimensional tissue acquired on days 1, 2, and 7 after the start of culture. Note that in Fig. 14, a single three-dimensional tissue was used to acquire the refractive index distribution data on days 1, 2, and 7. In Fig. 14, z indicates the height from the bottom surface of the three-dimensional tissue of the cross section extracted as the refractive index tomographic data.

[0147] [Step 3: Evaluation of Three-Dimensional Tissue] The refractive index tomographic data acquired and extracted in step 2 was used to evaluate the renal tubule region, which is the epithelial lumen formed in the three-dimensional tissue. The area, circumference, and circularity of the renal tubule region in FIG. 14 were measured using ImageJ, and the results are shown in Table 4. As shown in Table 4, the area of ​​the lumen in the three-dimensional tissue increased over time, and its circularity also increased over time. From these results, it was possible to evaluate that the lumen in the three-dimensional tissue matured over time. Furthermore, as shown in Table 4, the magnitude (mean, median) and variance (standard deviation) of the refractive index within the lumen increased over time, suggesting that the lumen in the three-dimensional tissue was formed by apoptosis of cells present at the site of lumen formation. In other words, from these results, it was possible to infer that the lumen formation process in the three-dimensional tissue observed in Example 2 was a cavitation-type formation process.

[0148]

[0149] Example 3: Evaluation of the effect of drugs on three-dimensional tissue with epithelial lumens Three-dimensional tissue on the second day of culture, cultured in the same manner as in Example 2, was used as the pre-addition sample. The post-addition sample was prepared as follows: Approximately 3 mL of culture medium and staurosporine (Fujifilm Wako Pure Chemical Industries, Ltd.) at a final concentration of 5000 nM were added to the glass-bottom dish in which the pre-addition sample was cultured. After the addition, the culture medium was incubated in an atmosphere of 5% CO ２ The three-dimensional tissue was cultured for another day under conditions of 37°C and 100% humidity and used as the post-addition sample. Thus, the post-addition sample is the same three-dimensional tissue as the pre-addition sample. Staurosporine is a drug that induces cell apoptosis. Refractive index distribution data for the pre-addition sample and the post-addition sample was obtained by ODT using the same method as in step 2 of Example 2.

[0150] Figure 15 shows representative refractive index tomographic data extracted from the refractive index distribution data of the sample before and after the addition of staurosporine. Furthermore, the area, perimeter, and circularity, as well as the mean, standard deviation, and median of the refractive index, were measured using ImageJ for the entire three-dimensional tissue and the three lumen regions (lumens 1 to 3) of the sample before the addition of staurosporine, and for the entire three-dimensional tissue of the sample after the addition of staurosporine. The results are shown in Table 5.

[0151] 15, the pre-addition sample showed three lumens with characteristics similar to those observed in Example 2, whereas the post-addition sample showed no regions exhibiting such luminal characteristics. Furthermore, when the refractive index of the entire three-dimensional tissue was compared, the post-addition sample had a larger refractive index (mean, median) and a larger refractive index variance (standard deviation) than the pre-addition sample. This suggests that exposure to the drug induced apoptosis in cells throughout the three-dimensional tissue, thereby inhibiting lumen formation.

[0152]

[0153] 1A...observation device, 10...light source, 21...lens, 22...light input end, 23...optical fiber, 24...light output end, 25...lens, 31...irradiation unit, 41...objective lens, 42...mirror, 43...lens, 50...imaging unit, 60...processing unit, 61...interference term calculation unit, 62...first complex amplitude image generation unit, 63...second complex amplitude image generation unit, 64...complex differential interference image generation unit, 65...phase differential image generation unit, 66...refractive index distribution image generation unit, 311...beam splitter, 313...spatial light modulator, 314...polarizer, 315...half wavelength plate, 316...polarizer, 318...lens, 319...objective lens.

Claims

1. A method for evaluating three-dimensional tissue containing epithelial cells, which comprises evaluating the process of epithelial lumen formation in the three-dimensional tissue using refractive index distribution data of the three-dimensional tissue containing epithelial cells at multiple time points.

2. The method according to claim 1, further comprising identifying a region in the three-dimensional tissue that is present in the extracellular region and has a lower refractive index than the epithelial cells as the epithelial lumen region.

3. The method of claim 1, wherein the maximum diameter of the epithelial lumen is 10 μm or more.

4. The method of claim 1, wherein the evaluation of the process of epithelial lumen formation includes identifying it as a hollowing type, identifying it as a cavitation type, or identifying it as a type other than the hollowing type and the cavitation type.

5. The method of claim 1, wherein at least two of the time points in the plurality of time points are separated from each other by one or more days.

6. The method of claim 1, wherein the refractive index distribution data is refractive index tomographic data in a predetermined direction.

7. The method of claim 1, comprising identifying regions of cells that have undergone programmed cell death in the three-dimensional tissue based on spatial variations in refractive index.

8. The method of claim 1, comprising identifying an area of ​​necrotic cells in a region of cells having cell nuclei in the three-dimensional tissue based on the average or median refractive index of the entire cells and / or the variation in the refractive index of the cell nuclei.

9. The method of claim 1, further comprising identifying regions in the three-dimensional tissue that are present in the cytoplasm and have a lower refractive index than the cytoplasm of the epithelial cells as regions of vesicles.

10. A drug screening method comprising exposing a three-dimensional tissue containing epithelial cells or cells before the formation of the three-dimensional tissue to a drug, and evaluating the three-dimensional tissue according to the method of any one of claims 1 to 9.

11. An evaluation device for three-dimensional tissue containing epithelial cells, comprising: a data acquisition unit that acquires refractive index distribution data of three-dimensional tissue containing epithelial cells; and an evaluation unit that uses the refractive index distribution data at multiple points in time to evaluate the formation process of epithelial lumens formed in the three-dimensional tissue.

12. A program that causes a computer to execute the following steps: a data acquisition step of acquiring refractive index distribution data of a three-dimensional tissue containing epithelial cells; and an evaluation step of evaluating the formation process of an epithelial lumen formed in the three-dimensional tissue using the refractive index distribution data at multiple time points.

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