A method and device for drug action analysis based on tumor organoid homogeneity

Abstract

The application discloses a drug action analysis method and device based on tumor organoid homogeneity, and relates to the technical field of tumor organoids. After obtaining original three-dimensional structure data of a tumor organoid, the application first determines the connected domain data corresponding to each organoid in the target organoid cluster, thereby establishing a spherical coordinate system with the centroid of each organoid as the origin, and determining the morphological homogeneity of each organoid according to the polar radius corresponding to the organoid entity of different polar angles and different azimuth angles. The connected domain data and the original three-dimensional structure data points of each organoid are multiplied to obtain the intensity information of each organoid and analyze the intensity homogeneity of each organoid. The morphological homogeneity and the intensity homogeneity of each organoid reflect the tumor heterogeneity, and on this basis, the tumor organoids are classified to construct a growth level model for drug action analysis, thereby improving the classification accuracy of the tumor organoids and realizing more targeted research on the tumor organoids.

Description

Technical Field

[0001] This invention relates to the field of tumor organoid technology, and in particular to a method and apparatus for analyzing drug effects based on the homogeneity of tumor organoids. Background Technology

[0002] Currently, three-dimensional tumor organoids, as miniaturized and simplified organ model systems in vitro, possess the key structural and functional characteristics of organs and tumor tissues, thus holding significant importance in disease modeling, personalized medicine, and drug screening. As physiologically relevant models, tumor organoids hold promise as powerful tools for exploring tumor biology and individual patient drug sensitivity.

[0003] However, current research on tumor organoid heterogeneity largely focuses on the cytogenetics or cellular composition level, while the analysis of tumor morphological diversity is insufficient. This analysis may be limited by the ability to capture three-dimensional spatial structural information of tumor organoids or by the simulation of tumor morphological change models. Commonly used bright-field microscopy has limitations in imaging the three-dimensional structure of tumor organoids and cannot fully demonstrate the complexity of three-dimensional spatial relationships, thus leading to certain limitations in morphological analysis based on two-dimensional images.

[0004] Three-dimensional simulation can acquire information such as cell division to obtain the evolution of organoid three-dimensional models and perform theoretical analysis, but it cannot analyze the morphology of actual tumor organoids. Three-dimensional imaging is a necessary condition for revealing the complex structure and morphological phenotype of tumor organoids and for confirming that organoids can realistically reflect their corresponding organs in vivo.

[0005] In existing technologies, three-dimensional imaging can generally be used to obtain the three-dimensional spatial structure of tumor organoids for classification, allowing for targeted research on the drug effects of different types of tumor organoids. However, during actual tumor growth, after multiple divisions and proliferations, the daughter cells exhibit molecular biological or genetic changes, leading to differences in tumor growth rate, invasiveness, drug sensitivity, and prognosis. This results in the existence of many different genotypes or subtypes of cells within the same tumor. The same tumor can exhibit different treatment effects and prognoses in different individuals, and even tumor cells in the same individual may have different characteristics and differences. Therefore, in addition to surface morphological characteristics, the internal morphology and heterogeneity of tumor organoids are also crucial for drug effect analysis. However, existing studies are mostly based on two-dimensional or three-dimensional surface morphological characteristics of organoids, lacking analysis of internal heterogeneity.

[0006] In summary, the current lack of heterogeneity analysis of tumor organoids based on three-dimensional imaging results in low accuracy of organoid classification, leading to insufficient comprehensiveness and accuracy in drug action analysis based on tumor organoids. Summary of the Invention

[0007] Therefore, it is necessary to provide a method and apparatus for analyzing drug effects based on the homogeneity of tumor organoids to address the aforementioned technical problems.

[0008] The present invention adopts the following technical solution:

[0009] This invention provides a method for drug action analysis based on the homogeneity of tumor organoids. First, original three-dimensional structural data of multiple tumor organoids are acquired. Organoid segmentation and connectivity analysis are performed on the original three-dimensional structural data to determine the connected component data corresponding to each organoid within the target organoid cluster. Then, based on the connected component data corresponding to each organoid, the centroid of each organoid is determined. A spherical coordinate system is established with the centroid of each organoid as the origin. The morphological homogeneity of each organoid is determined based on the polar radii corresponding to organoid entities at different polar angles and azimuth angles. The connected component data of each organoid is then multiplied by the original three-dimensional structural data to obtain the intensity information of each organoid. The intensity homogeneity of each organoid is determined based on the intensity value vectors corresponding to different polar angles and azimuth angles. Finally, based on the morphological and intensity homogeneity of each organoid, various organs within the target organoid cluster are classified, and a growth level model of various organs within the target organoid cluster is constructed for drug action analysis.

[0010] This invention provides a drug action analysis device based on the homogeneity of tumor organoids, comprising:

[0011] The acquisition module is used to acquire the original three-dimensional structural data of multiple tumor organoids, perform organoid segmentation and connectivity analysis on the original three-dimensional structural data, and determine the connected component data corresponding to each organoid in the target organoid cluster among multiple tumor organoids.

[0012] The morphological homogeneity analysis module is used to determine the centroid of each organoid based on the connected component data corresponding to each organoid, establish a spherical coordinate system with the centroid of each organoid as the origin, and determine the morphological homogeneity of each organoid based on the polar radius corresponding to organoid entities with different polar angles and different azimuth angles.

[0013] The intensity homogeneity analysis module is used to multiply the connected component data of each organoid with the original three-dimensional structural data to obtain the intensity information of each organoid; and to determine the intensity homogeneity of each organoid based on the intensity value vectors corresponding to different polar angles and different azimuth angles.

[0014] The drug action analysis module is used to classify various organs within the target organoid cluster based on the morphological homogeneity and intensity homogeneity of each organoid, and to construct growth level models of various organoids within the target organoid cluster for drug action analysis.

[0015] The present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for drug action analysis based on the homogeneity of tumor organoids.

[0016] The present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-described method for drug action analysis based on the homogeneity of tumor organoids.

[0017] The above-mentioned at least one technical solution adopted in this invention can achieve the following beneficial effects:

[0018] This invention, after obtaining the original three-dimensional structural data of tumor organoids, first determines the connected component data corresponding to each organoid within the target organoid cluster. A spherical coordinate system is then established with the centroid of each organoid as the origin. Based on the polar radii corresponding to organoid entities at different polar angles and azimuth angles, the morphological homogeneity of each organoid is determined. The connected component data of each organoid is then multiplied by the original three-dimensional structural data to obtain the intensity information of each organoid. The intensity homogeneity of each organoid is determined based on the intensity value vectors corresponding to different polar angles and azimuth angles. Thus, the morphological and intensity homogeneity of each organoid reflects tumor heterogeneity. Based on this, classification is performed according to the morphological and intensity homogeneity of each organoid within the target organoid cluster. A growth level model of each type of organoid within the target organoid cluster is constructed for drug action analysis, improving the accuracy of tumor organoid classification and enabling more targeted research on tumor organoids. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0020] Figure 1 A schematic flowchart of a drug action analysis method based on the homogeneity of tumor organoids provided by the present invention;

[0021] Figure 2 A schematic diagram of a three-dimensional image of an organoid provided by the present invention;

[0022] Figure 3 A schematic diagram illustrating the selection of organoids provided by the present invention;

[0023] Figure 4 A schematic diagram of a three-dimensional image of an organoid provided by the present invention. Figure 1 ;

[0024] Figure 5A schematic diagram of a three-dimensional image of an organoid provided by the present invention. Figure 2 ;

[0025] Figure 6 A schematic diagram of a three-dimensional image of an organoid provided by the present invention. Figure 3 ;

[0026] Figure 7 This is a schematic diagram of a drug action analysis device based on the homogeneity of tumor organoids provided by the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0028] The technical solutions provided by the various embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0029] Figure 1 This is a schematic diagram of a drug action analysis method based on the homogeneity of tumor organoids in this invention, which specifically includes the following steps:

[0030] S101: Obtain the original three-dimensional structural data of multiple tumor organoids, perform organoid segmentation and connectivity analysis on the original three-dimensional structural data, and determine the connected component data corresponding to each organoid in the target organoid cluster among multiple tumor organoids.

[0031] S102: Based on the connected component data corresponding to each organoid, determine the centroid of each organoid, establish a spherical coordinate system with the centroid of each organoid as the origin, and determine the morphological homogeneity of each organoid based on the polar radius corresponding to organoid entities with different polar angles and different azimuth angles.

[0032] S103: Multiply the connected component data of each organoid by the original three-dimensional structural data to obtain the intensity information of each organoid; determine the intensity homogeneity of each organoid based on the intensity value vectors corresponding to different polar angles and different azimuth angles.

[0033] S104: Classify the various organs within the target organoid cluster according to the morphological homogeneity and intensity homogeneity of each organoid, and construct growth level models of various organoids within the target organoid cluster for drug action analysis.

[0034] For ease of explanation, the following description focuses solely on the server as the executing entity. The server mentioned in this invention can be a server set up on a business platform, or a device such as a desktop computer or laptop computer capable of executing the solution of this invention.

[0035] Generally, when performing drug action analysis based on tumor organoids, the server can first acquire three-dimensional interference spectral data of multiple tumor organoids under normal culture conditions using three-dimensional optical imaging technology. .

[0036] Three-dimensional interferometric spectral data Spectral frequency domain analysis was performed to obtain raw three-dimensional structural data of multiple tumor organoids. . Figure 2 This is a schematic diagram of a three-dimensional image of an organoid according to the present invention. Figure 2 The left side shows a schematic diagram of a 3D image of an organoid with grayscale information, while the right side shows a schematic diagram of a 3D image of an organoid without grayscale information.

[0037] For the original three-dimensional structural data Perform organoid segmentation to obtain binary data of the target organoid cluster contained in multiple tumor organoids. .

[0038] Binarized data containing target organoid clusters Connectivity analysis was performed to obtain the total number of organoids within the target organoid cluster based on a 3×3×3 neighborhood. N and the connected component data corresponding to each organoid. . Figure 3 This is a schematic diagram of organ selection in this invention. The top side shows a cluster of a certain type of organ, the middle side shows a certain type of organ in the cluster, and the bottom side shows the binarization result of that type of organ.

[0039] Then, the connected domain data of each organoid can be utilized. Morphological homogeneity analysis is performed. Specifically, the server can first establish a spherical coordinate system with the centroid of each organoid as the origin, transform the connected component data corresponding to each organoid into the spherical coordinate system, and determine multiple sampling directions based on the preset sampling intervals of polar angle and azimuth angle.

[0040] Then, for each organoid, the sampling directions are traversed, and the pixel points of the corresponding entity in the spherical coordinate system representation of the organoid in each sampling direction are counted and accumulated according to the preset radius interval to obtain the polar radius corresponding to the organoid entity with different polar angles and different azimuth angles.

[0041] Based on this, the mean value of the polar radius corresponding to organoid entities with different polar angles and different azimuth angles can be determined, which represents the average radius of the organoid entity; and the minimum polar radius, maximum polar radius, and polar radius variance among the polar radii corresponding to organoid entities with different polar angles and different azimuth angles can be calculated.

[0042] The absolute value of the difference between the polar radius of organoid entities at different polar angles and azimuth angles and the average radius of the organoid is determined to characterize the morphological homogeneity distribution of the organoid; and the mean of the absolute values ​​of the differences is used to characterize the overall morphological homogeneity of the organoid.

[0043] For example, the server can utilize the connected component information of each organoid (such as the i-th organoid). , ), calculate the centroid of organoids Here, for each organoid, all connected component data corresponding to that organoid can be processed. Non-zero voxel coordinates ( = The centroid of each organoid is determined by the following formula: ; ; .

[0044] in, For the first i The first of the organoids t The coordinates of a non-zero voxel. It is the first i The total number of non-zero voxels corresponding to each organoid region. For the first i The centroid of an organoid.

[0045] Then, establish a spherical coordinate system with the centroid as the origin, that is, with the polar angle as the origin. Azimuth and polar radius r As parameters, the polar angle ranges from 0 to 180 degrees, and the azimuth angle ranges from 0 to 360 degrees, while also including organoid connected component data in the xyz space. Transform to spherical coordinates, represented as In spherical coordinates, using This represents the distance from the point to the origin. ;exist On a plane, from z Axial positive half axis The angle of deflection is , ;from x Axis deflection to polar radius r exist xy The angle of the plane projection is , ,

[0046] by e,m,n As the polar radius r Polar angle and azimuth The interval of change (which can be adjusted according to different situations) is used to obtain... Polar radius dimensions in each direction Array; in traversal form, when polar angle With intervals m From 0 to 180 degrees, azimuth angle Calculate the number of degrees as the interval n increases from 0 to 360 degrees. Polar radius values ​​in each direction .

[0047] In the In each direction, the polar radius value The initial value is 0, and the polar radius starts from 0. e As the intervals gradually increase, the polar radius corresponding to this length is determined. Check if the pixel value is 1 (linear interpolation is required for non-integer values). If it is 1, then the polar radius value... Increase by 1; if it is 0, then the polar radius value Keep it unchanged; and take the last polar radius value that no longer changes as the polar radius value in that direction. Based on this, different polar angles can be obtained through Boolean operations. and azimuth The corresponding polar radius value And integrate them to obtain a two-dimensional matrix. .

[0048] Furthermore, Individual radius values Construct a two-dimensional matrix The three-dimensional spatial radius roughness characterization is transformed into a two-dimensional spatial matrix roughness analysis using spherical coordinates:

[0049] First, calculate the two-dimensional matrix. The mean value is used as the average polar radius value. , representing the average radius of this type of organ. Then, the two-dimensional matrix is ​​statistically analyzed. The minimum value, maximum value, and standard deviation are respectively used as the minimum polar radius value. Maximum polar radius value and the standard deviation of the polar radius value .

[0050] Finally, calculate the two-dimensional matrix. Roughness distribution This characterizes the homogeneity of morphological distribution. And utilizes... The average value is used as the average roughness. Characterizes the overall morphological homogeneity of organoids.

[0051] Furthermore, the server can also connect each organoid to a domain. Compared with the original three-dimensional structural data Perform dot product to obtain single organoid data containing intensity information. , respectively using Intensity homogeneity analysis was performed on each organoid.

[0052] Specifically, the server can traverse the polar radius based on the maximum polar radius among the polar radii corresponding to organoid entities with different polar angles and different azimuth angles. For each polar radius, the server performs correlation analysis on the intensity value vectors corresponding to different polar angles and different azimuth angles for each organoid at that polar radius length under preset polar angle and azimuth angle windows to obtain the intensity homogeneity distribution within the polar radius length range of each organoid. The server also determines the mean of the intensity homogeneity distribution within the polar radius length range of each organoid to characterize the overall intensity homogeneity of each organoid within the polar radius length range.

[0053] For example, the server can first determine the maximum value of the two-dimensional array of polar radius values ​​from the previous step. Build 3D matrix Used for storage Intensity vectors in different directions .

[0054] Then utilize the intensity value distribution information of each organoid (e.g., the i-th organoid) Similarly, a spherical coordinate system is established with the centroid as the origin, using the polar angle, azimuth angle, and polar radius r as parameters. The polar angle ranges from 0 to 180 degrees, and the azimuth angle ranges from 0 to 360 degrees. The organoid coordinates in the xyz space are also defined. Transform to spherical coordinates, represented as .

[0055] Based on this, in the first jk In each direction, the initial value of the polar radius is 0, starting from 0, and... e As intervals, record the downward direction sequentially. The intensity value (which requires linear interpolation for non-integer cases) is used as the intensity value vector in that direction. Center front The value for the nth value arrive Each value is padded with zeros.

[0056] Iterate through the different directions corresponding to different polar angles and different azimuth angles, and obtain and store the different polar angles. azimuth Three-dimensional matrix of the lower intensity value sequence Therefore, based on the three-dimensional matrix Conduct intensity homogeneity analysis.

[0057] First, the correlation between the intensity value vectors of spheres with different radii centered at the origin is used to characterize the homogeneity of the intensity distribution of this type of organ within that radius.

[0058] Specifically, when the radius is taken (in, p Traverse from 1 to ), only considering The first vector Several intensity values, and for different polar angles and azimuth The front of the corresponding intensity vector p A vector composed of intensity values Conduct correlation analysis, in , Choose an appropriate window size for the analysis, such as for (… j , k Nine intensity vectors within a 3×3 window at location ( , , , , , , , , ) respectively taken from ( j-1,k-1 ), ( j-1,k ), ( j-1,k+1 ), ( j,k-1 ), ( j, k ), ( j,k+1 ), ( j+1,k-1 ), ( j+1,k ), ( j+1,k+1 Perform pairwise correlation analysis to... , For example, first calculate the covariance of the two. :

[0059] .

[0060] In the formula, , express j,k The cases for different values, Describing covariance, Express the expectation. Further calculations. , Calculation of correlation coefficient :

[0061] .

[0062] in, , This represents the standard deviation of two intensity value vectors. And obtain ( j , k The correlation coefficients between each pair of the nine intensity value vectors within a 3×3 window at a given location are used, with the mean value as the ( j , k Location intensity vector correlation This indicates that the location is p Homogeneity of strength within the radius.

[0063] Therefore, the radius is obtained. p intensity vector correlation matrix Characterizing this type of organ in p The intensity is homogeneously distributed within the radius. Finally, the correlation matrix of this intensity vector is calculated. Mean_ Characterizing this type of organ p Overall strength homogeneity within the radius.

[0064] Secondly, when the radius p for That is, considering the entire length The correlation between the intensity value vectors can be used to obtain the intensity vector correlation matrix. Characterizes the overall intensity homogeneity distribution of this type of organ, and the mean value can be obtained. Mean_ This characterizes the overall strength homogeneity of this type of organ. The calculation process for the radius range of p is still performed as described above, but the result obtained this time is no longer... The correlation coefficient matrix, but... The correlation coefficient matrix, which is the matrix of all equations Replace with Based on the aforementioned process, a normalized correlation coefficient matrix is ​​obtained. And then The mean is obtained Mean_ It characterizes the overall strength homogeneity of this type of organ.

[0065] Figure 4 , Figure 5 , Figure 6 These are schematic diagrams of three-dimensional images of three different morphological organoids in this invention. Calculations can yield their corresponding... Mean_ , and , Figure 4 medium organoids , and ; Figure 5 medium organoids , and ; Figure 6 medium organoids , and .

[0066] After completing the analysis of organoid homogeneity, the server can classify various organs within the target organoid cluster based on the morphological homogeneity and intensity homogeneity of each organoid. Of course, in one or more embodiments of the present invention, the server can also perform morphological analysis on the connected component data corresponding to each organoid within the target organoid cluster to obtain morphological parameters including at least one of organoid entity volume, organoid filling volume, organoid surface area, longest axis, shortest axis, sphericity, ratio of major to minor axis, and specific surface area. Thus, based on the morphological homogeneity and intensity homogeneity of each organoid within the target organoid cluster combined with multi-dimensional morphological parameters, classification is performed using K-means clustering.

[0067] Finally, principal component analysis is performed on the morphological homogeneity, intensity homogeneity, and multi-dimensional morphological parameters of each organoid in the target organoid cluster. The eigenvectors corresponding to the eigenvalues ​​that reach the preset cumulative contribution rate are identified as principal components, and the scores of each organoid type on each principal component are determined. The scores are then weighted and summed based on the contribution rate of each principal component to determine the growth level of each organoid type. Finally, drug effect analysis of tumor organoids can be performed based on the growth levels under different drugs or drug concentrations to determine whether the drugs promote or inhibit tumor organoid growth. There are already relatively mature techniques for drug effect analysis of tumor organoids based on growth levels, which will not be elaborated upon in this invention.

[0068] based on Figure 1 The proposed method for drug action analysis based on the homogeneity of tumor organoids involves first determining the connected component data for each organoid within the target organoid cluster after obtaining the original three-dimensional structural data of the tumor organoids. A spherical coordinate system is then established with the centroid of each organoid as the origin. The morphological homogeneity of each organoid is determined based on its polar radius at different polar angles and azimuth angles. The connected component data and the original three-dimensional structural data of each organoid are then multiplied to obtain its intensity information. The intensity homogeneity of each organoid is determined based on its intensity value vectors at different polar angles and azimuth angles. Thus, the morphological and intensity homogeneity of each organoid reflects tumor heterogeneity. Based on this, classification is performed according to the morphological and intensity homogeneity of each organoid within the target organoid cluster. A growth level model of each organoid within the target organoid cluster is constructed for drug action analysis, improving the accuracy of tumor organoid classification and enabling more targeted research on tumor organoids.

[0069] When applying the drug action analysis method based on the homogeneity of tumor organoids provided by this invention, it is not necessary to consider... Figure 1 The steps shown are executed in sequence. The specific execution order of each step can be determined as needed, and this invention does not impose any restrictions on it.

[0070] The above describes a method for analyzing drug effects based on the homogeneity of tumor organoids, provided by one or more embodiments of the present invention. Based on the same idea, the present invention also provides a corresponding device for analyzing drug effects based on the homogeneity of tumor organoids, such as... Figure 7 As shown.

[0071] Figure 7 A schematic diagram of a drug action analysis device based on the homogeneity of tumor organoids provided by the present invention includes:

[0072] The acquisition module 201 is used to acquire the original three-dimensional structural data of multiple tumor organoids, perform organoid segmentation and connectivity analysis on the original three-dimensional structural data, and determine the connected component data corresponding to each organoid in the target organoid cluster among multiple tumor organoids.

[0073] The morphological homogeneity analysis module 202 is used to determine the centroid of each organoid based on the connected component data corresponding to each organoid, establish a spherical coordinate system with the centroid of each organoid as the origin, and determine the morphological homogeneity of each organoid based on the polar radius corresponding to organoid entities with different polar angles and different azimuth angles.

[0074] The intensity homogeneity analysis module 203 is used to multiply the connected component data of each organoid with the original three-dimensional structural data to obtain the intensity information of each organoid; and to determine the intensity homogeneity of each organoid based on the intensity value vectors corresponding to different polar angles and different azimuth angles.

[0075] The drug action analysis module 204 is used to classify various organs within the target organoid cluster based on the morphological homogeneity and intensity homogeneity of each organoid, and to construct growth level models of various organoids within the target organoid cluster for drug action analysis.

[0076] Specific limitations regarding the drug action analysis device based on the homogeneity of tumor organoids can be found in the limitations of the drug action analysis method based on the homogeneity of tumor organoids mentioned above, and will not be repeated here. Each module in the aforementioned drug action analysis device based on the homogeneity of tumor organoids can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0077] The present invention also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 The provided method is a drug action analysis method based on the homogeneity of tumor organoids.

[0078] This invention also provides a computer device. At the hardware level, the computer device includes a processor, an internal bus, a network interface, memory, and non-volatile memory, and may also include other hardware required for various operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then executes it to achieve the above-mentioned functions. Figure 1 The provided method is a drug action analysis method based on the homogeneity of tumor organoids.

[0079] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0080] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this invention.

Claims

1. A method for drug effect analysis based on homogeneity of tumor organoids, characterized by, The method comprises the following steps: Obtain the original three-dimensional structure data of a plurality of tumor organoids, perform organoid segmentation and connectivity analysis on the original three-dimensional structure data, and determine the connected domain data corresponding to each organoid in a target organoid cluster in the plurality of tumor organoids; Determine the centroid of each organoid according to the connected domain data corresponding to each organoid, establish a spherical coordinate system with the centroid of each organoid as the origin, and determine the morphological homogeneity of each organoid according to the polar radius corresponding to the organoid entity at different polar angles and different azimuth angles; Multiply the connected domain data and the original three-dimensional structure data of each organoid to obtain the intensity information of each organoid; and determine the intensity homogeneity of each organoid according to the intensity value vector corresponding to different polar angles and different azimuth angles. Classify each organoid in the target organoid cluster according to the morphological homogeneity and the intensity homogeneity of each organoid, and construct a growth level model of each organoid in the target organoid cluster to analyze the effect of drugs.

2. The method for drug effect analysis based on homogeneity of tumor organoids according to claim 1, wherein, The spherical coordinate system is established with the centroid of each organoid as the origin, and the morphological homogeneity of each organoid is determined according to the polar radius corresponding to the organoid entity at different polar angles and different azimuth angles, specifically comprising: A spherical coordinate system is established with the centroid of each organoid as the origin, and the connected domain data corresponding to each organoid is converted into the spherical coordinate system; a plurality of sampling directions are determined according to the preset sampling interval of the polar angle and the azimuth angle; For each organoid, traverse each sampling direction, and according to the preset radius interval, count the pixel points of the corresponding entity in the spherical coordinate system representation of the organoid in each sampling direction and accumulate, to obtain the polar radius corresponding to the organoid entity at different polar angles and different azimuth angles; Determine the mean value of the polar radius corresponding to the organoid entity at different polar angles and different azimuth angles, which represents the average radius of the organoid; Determine the absolute value of the difference between the polar radius corresponding to the organoid entity at different polar angles and different azimuth angles and the average radius of the organoid, and the minimum polar radius, the maximum polar radius, the polar radius variance, and the absolute value of the difference in the polar radius corresponding to the organoid entity at different polar angles and different azimuth angles represent the morphological homogeneity distribution of the organoid; and the mean value of the absolute value of the difference represents the overall morphological homogeneity of the organoid.

3. The method for drug effect analysis based on homogeneity of tumor organoids according to claim 1, wherein, The intensity homogeneity of each organoid is determined according to the intensity value vector corresponding to different polar angles and different azimuth angles, specifically comprising: According to the maximum polar radius in the polar radius corresponding to the organoid entity at different polar angles and different azimuth angles, the polar radius of each length is traversed, and for each length of polar radius, the correlation analysis is performed on the intensity value vector corresponding to different polar angles and different azimuth angles of each organoid at the preset polar angle and azimuth angle window, to obtain the intensity homogeneity distribution of each organoid within the length range of the polar radius; Determine the mean value of the intensity homogeneity distribution of each organoid at the length of the polar radius, to represent the overall intensity homogeneity of each organoid within the length range of the polar radius.

4. The method for drug effect analysis based on homogeneity of tumor organoids according to claim 1, wherein, The centroid of each organoid is determined according to the connected domain data corresponding to each organoid, specifically comprising: For each organoid, the centroid of each organoid is determined according to the connected domain data corresponding to the organoid by the following formula: ； ； ； wherein, is the centroid of the i th organoid, t is the coordinate of the th non-zero voxel in the i th organoid, is the total number of non-zero voxels in the target region corresponding to the i th organoid.

5. The method for drug effect analysis based on homogeneity of tumor organoids according to claim 1, wherein, The classification according to the morphological homogeneity and intensity homogeneity of each organoid in the target organoid cluster specifically includes: Performing morphological analysis on the connected domain data corresponding to each organoid in the target organoid cluster to obtain morphological parameters including at least one of organoid solid volume, organoid filling volume, organoid surface area, longest axis, shortest axis, sphericity, long-short axis ratio, and specific surface area; Classifying each organoid in the target organoid cluster according to the morphological homogeneity, intensity homogeneity, and multi-dimensional morphological parameters of each organoid in the target organoid cluster through Kmeans clustering.

6. The method for drug effect analysis based on homogeneity of tumor organoids according to claim 1, wherein, The method for obtaining the original three-dimensional structure data of the plurality of tumor organoids, performing organoid segmentation and connectedness analysis on the original three-dimensional structure data, and determining the connected domain data corresponding to each organoid in the target organoid cluster in the plurality of tumor organoids specifically includes: Obtaining three-dimensional interference spectrum data of the plurality of tumor organoids based on three-dimensional optical imaging technology; Performing spectral frequency domain analysis on the three-dimensional interference spectrum data to obtain the original three-dimensional structure data of the plurality of tumor organoids; Performing organoid segmentation on the original three-dimensional structure data to obtain binary data containing the target organoid cluster in the plurality of tumor organoids; Performing connectedness analysis on the binary data containing the target organoid cluster to obtain the connected domain data corresponding to each organoid in the target organoid cluster.

7. A drug action analysis device based on homogeneity of tumor organoids, characterized by, The method specifically includes: An obtaining module is configured to obtain original three-dimensional structure data of a plurality of tumor organoids, perform organoid segmentation and connectedness analysis on the original three-dimensional structure data, and determine connected domain data corresponding to each organoid in a target organoid cluster in the plurality of tumor organoids; A morphological homogeneity analysis module is configured to determine a centroid of each organoid according to the connected domain data corresponding to each organoid, establish a spherical coordinate system with the centroid of each organoid as the origin, and determine the morphological homogeneity of each organoid according to the polar radius corresponding to the organoid entity at different polar angles and different azimuth angles; An intensity homogeneity analysis module is configured to multiply the connected domain data of each organoid by the original three-dimensional structure data to obtain intensity information of each organoid, and determine the intensity homogeneity of each organoid according to the intensity value vector corresponding to different polar angles and different azimuth angles; A drug action analysis module is configured to classify each organoid in the target organoid cluster according to the morphological homogeneity and intensity homogeneity of each organoid, construct a growth level model of each organoid in the target organoid cluster, and perform drug action analysis.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program is executed by the processor to implement the method of any one of claims 1-6.

9. A computer device, comprising: The computer program is stored in the memory and can be run on the processor, and the processor implements the method of any one of claims 1-6 when executing the program. The computer program is stored in the memory and can be run on the processor, and the processor implements the method of any one of claims 1-6 when executing the program.

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