Tumor organoid homogeneity-based drug action analysis method and device

Abstract

The invention discloses a drug action analysis method and device based on homogeneity of tumor organoids, and relates to the technical field of tumor organoids. According to the method, after the original three-dimensional structure data of the tumor type organ is obtained, the connected domain data corresponding to each type organ in the target type organ cluster is determined, so that the spherical coordinate system is established by taking the centroid of each type organ as an original point, and according to the polar radiuses corresponding to the type organ entities with different polar angles and different azimuth angles, the three-dimensional structure data of the tumor type organ is obtained. And determining the morphological homogeneity of each organ, carrying out point multiplication on the connected domain data of each organ and the original three-dimensional structure data to obtain the intensity information of each organ, and analyzing the intensity homogeneity of each organ. Therefore, the tumor heterogeneity is reflected by the form homogeneity and the strength homogeneity of each organoid, and on the basis, the tumor organoid is classified to construct the growth level model of the tumor organoid for drug action analysis, so that the classification accuracy of the tumor organoid is improved, and more targeted research on the tumor organoid is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of tumor organoids, and particularly to a method and device for analyzing the effect of drugs based on the homogeneity of tumor organoids. Background Art

[0002] At present, three-dimensional tumor organoids, as an in vitro miniaturized and simplified organ model system, possess the key structural and functional characteristics of organs and tumor tissues, and thus have great significance in the fields of disease modeling, personalized medicine, and drug screening. As a physiologically relevant model, tumor organoids are expected to become a powerful tool for exploring tumor biology and the drug sensitivity of individual patients.

[0003] However, current research on the heterogeneity of tumor organoids mostly focuses on the cytogenetics or cell composition level, and the analysis of tumor morphological diversity is insufficient. This analysis may be limited by the ability to capture the three-dimensional spatial structure information of tumor organoids or the limitation of the simulation of tumor morphological change models. Conventional bright-field microscopes are insufficient in imaging the three-dimensional structure of tumor organoids and cannot fully display the complexity of three-dimensional spatial relationships, resulting in certain limitations in the morphological analysis based on two-dimensional images.

[0004] Three-dimensional simulation can obtain the evolution of the three-dimensional model of organoids based on information such as cell division and conduct theoretical analysis, but it cannot analyze the actual morphology of tumor organoids. Three-dimensional imaging is a necessary condition for revealing the complex structure and morphological phenotypes of tumor organoids and confirms that organoids can truly reflect their corresponding organs in vivo.

[0005] In the prior art, generally, the three-dimensional spatial structure of tumor organoids can be obtained through three-dimensional imaging to classify tumor organoids, and then the effects of drugs on various types of tumor organoids can be studied respectively. However, during the actual growth process of tumors, after multiple divisions and proliferations, their daughter cells show changes in molecular biology or genes, resulting in differences in various aspects such as the growth rate, invasion ability, drug sensitivity, and prognosis of tumors. As a result, there can be many different genotypes or subtypes of cells in the same tumor. The same type of tumor can show different treatment effects and prognoses in different individuals, and even the tumor cells in the same individual also have different characteristics and differences. Therefore, in addition to surface morphological characteristics, the internal morphology and heterogeneity of tumor organoids also play an important role in drug effect analysis. However, existing research is mostly based on the two-dimensional morphology or three-dimensional surface morphological characteristics of organoids, lacking internal heterogeneity analysis.

[0006] In summary, there is currently a lack of heterogeneity analysis of tumor organoids based on three-dimensional imaging, and the accuracy of organoid classification is relatively low, resulting in insufficient comprehensiveness and accuracy of drug effect analysis based on tumor organoids. Summary of the Invention

[0007] Based on this, in view of the above technical problems, it is necessary to provide a method and device for analyzing the effect of drugs based on the homogeneity of tumor organoids.

[0008] The present invention adopts the following technical solutions: The present invention provides a method for analyzing the effect of drugs based on the homogeneity of tumor organoids. First, obtain the original three-dimensional structure data of multiple tumor organoids, perform organoid segmentation and connectivity analysis on the original three-dimensional structure data to determine the connectivity domain data corresponding to each organoid in the target organoid cluster among the multiple tumor organoids. Then, based on the connectivity domain 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 according to the polar radii corresponding to the organoid entities at different polar angles and different azimuth angles. Thus, multiply the connectivity domain data of each organoid by the original three-dimensional structure data points to obtain the intensity information of each organoid; determine the intensity homogeneity of each organoid according to the intensity value vectors corresponding to different polar angles and different azimuth angles; finally, classify each organoid in the target organoid cluster according to the morphological homogeneity and intensity homogeneity of each organoid, and construct a growth level model of each type of organoid in the target organoid cluster for drug effect analysis.

[0009] The present invention provides a device for analyzing the effect of drugs based on the homogeneity of tumor organoids, including: An acquisition module, configured to acquire the original three-dimensional structure data of multiple tumor organoids, perform organoid segmentation and connectivity analysis on the original three-dimensional structure data, and determine the connectivity domain data corresponding to each organoid in the target organoid cluster among the multiple tumor organoids; A morphological homogeneity analysis module, configured to determine the centroid of each organoid according to the connectivity 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 radii corresponding to the organoid entities at different polar angles and different azimuth angles; An intensity homogeneity analysis module, configured to multiply the connectivity domain data of each organoid by the original three-dimensional structure data points to obtain the intensity information of each organoid; determine the intensity homogeneity of each organoid according to the intensity value vectors corresponding to different polar angles and different azimuth angles; A drug effect analysis module, configured to classify each organoid in the target organoid cluster according to the morphological homogeneity and intensity homogeneity of each organoid, and construct a growth level model of each type of organoid in the target organoid cluster for drug effect analysis.

[0010] The present invention provides a computer-readable storage medium, where the storage medium stores a computer program, and when the computer program is executed by a processor, the above method for analyzing the effect of drugs based on the homogeneity of tumor organoids is implemented.

[0011] 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, the above-mentioned drug effect analysis method based on the homogeneity of tumor organoids is realized.

[0012] The above at least one technical solution adopted by the present invention can achieve the following beneficial effects: After obtaining the original three-dimensional structure data of tumor organoids, the present invention 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 radii corresponding to the organoid entities at different polar angles and different azimuth angles. Then, the connected domain data of each organoid is dot-multiplied with the original three-dimensional structure data points to obtain the intensity information of each organoid. According to the intensity value vectors corresponding to different polar angles and different azimuth angles, the intensity homogeneity of each organoid is determined. Thus, the tumor heterogeneity is reflected by the morphological homogeneity and intensity homogeneity of each organoid. On this basis, classification is performed according to the morphological homogeneity and intensity homogeneity of each organoid in the target organoid cluster, and a growth level model of various organoids in the target organoid cluster is constructed for drug effect analysis, improving the classification accuracy of tumor organoids to achieve more targeted research on tumor organoids. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention, and do not constitute an improper limitation to the present invention. In the drawings:

[0014] Figure 1 is a schematic flow chart of a drug effect analysis method based on the homogeneity of tumor organoids provided by the present invention; Figure 2 is a schematic three-dimensional image of an organoid provided by the present invention; Figure 3 is a schematic diagram of selecting an organoid provided by the present invention; Figure 4 is a schematic three-dimensional image of an organoid provided by the present invention Figure 1 ; Figure 5 is a schematic three-dimensional image of an organoid provided by the present invention Figure 2 ; Figure 6 is a schematic three-dimensional image of an organoid provided by the present invention Figure 3 ; Figure 7 is a schematic diagram of a drug effect analysis device based on the homogeneity of tumor organoids provided by the present invention. Detailed implementation manners

[0015] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0016] The technical solutions provided by each embodiment of the present invention will be described in detail below in conjunction with the drawings.

[0017] Figure 1 It is a schematic flowchart of a method for analyzing the effect of a drug based on the homogeneity of tumor organoids in the present invention, which specifically includes the following steps: S101: Obtain the original three-dimensional structure data of multiple tumor organoids, perform organoid segmentation and connectivity analysis on the original three-dimensional structure data, and determine the connectivity domain data corresponding to each organoid in the target organoid cluster among the multiple tumor organoids.

[0018] S102: Determine the centroid of each organoid according to the connectivity 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 radii corresponding to the organoid entities at different polar angles and different azimuth angles.

[0019] S103: Multiply the connectivity domain data of each organoid by the original three-dimensional structure data points to obtain the intensity information of each organoid; determine the intensity homogeneity of each organoid according to the intensity value vectors corresponding to different polar angles and different azimuth angles.

[0020] S104: Classify the organoids in the target organoid cluster according to the morphological homogeneity and intensity homogeneity of each organoid, and construct a growth level model of each type of organoid in the target organoid cluster for drug effect analysis.

[0021] For the convenience of description, only the server will be used as the execution subject for description below. The server mentioned in the present invention may be a server set up on a service platform, or a device such as a desktop computer or a laptop computer that can execute the solution of the present invention.

[0022] Generally, when analyzing the effect of a drug based on tumor organoids, the server can first obtain the three-dimensional interference spectrum data of multiple tumor organoids under normal culture conditions based on three-dimensional optical imaging technology .

[0023] For the three-dimensional interference spectrum data Perform spectral frequency domain analysis to obtain the original three-dimensional structure data of multiple tumor organoids . Figure 2 This is a schematic diagram of the three-dimensional image of an organoid in the present invention Figure 2 On the left side is the schematic diagram of the three-dimensional image of the organoid with gray-scale information, and on the right side is the schematic diagram of the three-dimensional image of the organoid without gray-scale information

[0024] Perform organoid segmentation on the original three-dimensional structure data to obtain the binary data containing the target organoid cluster among multiple tumor organoids .

[0025] Perform connectivity analysis on the binary data containing the target organoid cluster to obtain the total number of organoids within the target organoid cluster based on a 3×3×3 neighborhood and the connectivity domain data corresponding to each organoid N . Figure 3 This is a schematic diagram of selecting an organoid in the present invention. The upper side is a certain organoid cluster, the middle is a certain organoid in the cluster, and the lower side is the binary result of the organoid

[0026] After that, the connectivity domain data of each organoid can be used to perform morphological homogeneity analysis. Specifically, the server can first establish a spherical coordinate system with the centroid of each organoid as the origin, convert the connectivity domain data corresponding to each organoid into the spherical coordinate system, and determine multiple sampling directions according to the preset sampling intervals of the polar angle and the azimuth angle

[0027] Then, for each organoid, traverse each sampling direction, count and accumulate the pixel points of the corresponding entity in the spherical coordinate representation of the organoid in each sampling direction according to the preset radius interval, and obtain the polar radii corresponding to the organoid entities with different polar angles and different azimuth angles

[0028] Based on this, the mean value of the polar radii corresponding to the organoid entities with different polar angles and different azimuth angles can be determined to represent the average radius of the organoid; and the minimum polar radius, the maximum polar radius, and the variance of the polar radii among the organoid entities with different polar angles and different azimuth angles can be statistically calculated

[0029] Determine the absolute value of the difference between the polar radii corresponding to the organoid entities with different polar angles and different azimuth angles and the average radius of the organoid to represent the morphological homogeneity distribution of the organoid; and represent the overall morphological homogeneity of the organoid through the mean value of the absolute values of the differences

[0030] For example, the server can use the connectivity domain information of each organoid (such as the i-th organoid , ) to calculate the centroid of the organoid ​For each organoid, based on all the connected component data corresponding to the organoid non-zero voxel coordinates ( = ), the centroid of each organoid is determined by the following formula: ; ; .

[0031] Among them, is the coordinate of the i th non-zero voxel in the t th organoid, is the total number of non-zero voxels in the target area corresponding to the i th organoid, is the centroid of the i th organoid.

[0032] Then, with the centroid as the origin, a spherical coordinate system is established, that is, with the polar angle , azimuth angle and polar radius r as parameters, the polar angle ranges from 0 to 180 degrees, the azimuth angle ranges from 0 to 360 degrees, and at the same time, the connected component data of the organoid in the xyz space is converted to the spherical coordinate system and expressed as . In spherical coordinates, represents the distance from the point to the origin, ; in the plane, the angle of deflection from the positive half-axis of the z axis to is , ; the angle from the x axis to the projection of the polar radius r in the xy plane is , ,

[0033] Taking e, m, n as the change interval of the polar radius r , polar angle and azimuth angle (which can be adjusted accordingly according to different situations), the polar radius dimensions in directions are obtained; in a traversal form, when the polar angle increases from 0 to 180 degrees at an interval of m and the azimuth angle increases from 0 to 360 degrees at an interval of n, the polar radius value in the th direction is calculated respectively.

[0034] In the th direction, the initial value of the polar radius is 0. The polar radius starts from 0 and gradually increases at an interval of . It is judged whether the corresponding e pixel value is 1 when the polar radius is this length (linear interpolation is required in the case of non-integers). If it is 1, the polar radius value is incremented by 1; if it is 0, the polar radius value remains unchanged; and the finally unchanged polar radius value is used as the polar radius value in this direction . Based on this, through Boolean operations, the polar radius values corresponding to different polar angles and azimuth angles can be obtained, and a two-dimensional matrix is integrated. .

[0035] Furthermore, polar radius values constitute a two-dimensional matrix . Using the spherical coordinate system, the polar radius roughness characterization in three-dimensional space is converted into roughness analysis of a two-dimensional space matrix: First, calculate the mean value of this two-dimensional matrix as the average polar radius value , representing the average radius of this type of organoid. Then, count the minimum value, maximum value, and standard deviation of this two-dimensional matrix as the minimum polar radius value , the maximum polar radius value , and the standard deviation of the polar radius value .

[0036] Finally, calculate the roughness distribution of this two-dimensional matrix to characterize the morphological homogeneity distribution. And use the average value as the average roughness to characterize the overall morphological homogeneity of the organoid.

[0037] Furthermore, the server can also perform a dot product of each organoid connected domain with the original three-dimensional structure data to obtain single-organoid data containing intensity information , and perform intensity homogeneity analysis on each organoid using respectively.

[0038] Specifically, the server can perform polar radius traversal based on the maximum polar radius among the polar radii corresponding to different polar angles and different azimuth angles of the organoid entities. For each polar radius length, perform correlation analysis on the intensity value vectors corresponding to different polar angles and different azimuth angles of each organoid within a preset polar angle and azimuth angle window to obtain the intensity homogeneity distribution of each organoid within the range of this polar radius length; and determine the mean value of the intensity homogeneity distribution of each organoid at this polar radius length to characterize the overall intensity homogeneity of each organoid within the range of this polar radius length.

[0039] For example, the server can first obtain the maximum value of the two-dimensional array of polar radius values in the previous step to construct a three-dimensional matrix for storing intensity value vectors in different directions.

[0040] Then, using the intensity value distribution information of each organoid (such as the i-th organoid ), and its centroid, also taking the centroid as the origin, establish a spherical coordinate system, that is, using the polar angle, azimuth angle, and polar radius r as parameters, the polar angle ranges from 0 to 180 degrees, the azimuth angle ranges from 0 to 360 degrees, and at the same time convert the organoid coordinates in the xyz space to the spherical coordinate system, expressed as

[0041] Based on this, in the jk th direction, the initial value of the polar radius is 0, starting from 0, with e as the interval, successively record the intensity values (linear interpolation is required in the case of non-integers) in this direction as the first values in the intensity value vector , and fill the th to th values with 0.

[0042] Traverse different directions corresponding to different polar angles and different azimuth angles, obtain and store the three-dimensional matrix of the intensity value sequences under different polar angles and azimuth angles . Thus, perform intensity homogeneity analysis based on the three-dimensional matrix .

[0043] First, the correlation between the intensity value vectors of spheres with different radii centered at the origin centroid characterizes the intensity distribution homogeneity of the organoid within the range of this radius.

[0044] Specifically, when the radius takes (where pTraverse from 1 to ), only consider the first strength values in the vector, and for different polar angles and azimuth angles corresponding to the first p strength values in the strength vector perform correlation analysis. Select an appropriate window size for analysis in the , directions. For example, for the 9 strength vectors within a 3×3 window range at ( j , k ), namely ( , , , , , , , , ), which are 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 )) respectively, perform pairwise correlation analysis. Taking , as an example, first calculate the covariance between them: .

[0045] In the formula, , represent the situations when j, k takes different values. represents the covariance, and represents the expectation. Further calculate , to calculate the correlation coefficient of

[0046] .

[0047] Among them, , represent the standard deviations of the two strength value vectors. And obtain the correlation coefficients between every two of the 9 strength value vectors within the 3×3 window range at ( j , k ), and take the mean as ( j ,k ) Correlation of intensity value vectors at positions , indicating the intensity homogeneity within p the radius range at this location.

[0048] Furthermore, the intensity vector correlation matrix with a radius of p is obtained, characterizing the intensity homogeneity distribution of this type of organoid within p the radius range. Finally, the mean Mean_ of this intensity vector correlation matrix is calculated, characterizing the overall intensity homogeneity of this type of organoid within p the radius range.

[0049] Secondly, when the radius p is , that is, considering the correlation between intensity value vectors of the entire length , the intensity vector correlation matrix can be obtained, characterizing the intensity homogeneity distribution of the entire organoid of this type, and the mean Mean_ can be obtained, characterizing the overall intensity homogeneity of this type of organoid. At this time, still according to the above operation process within the p-radius range, except that what is obtained at this time is no longer the correlation coefficient matrix, but the correlation coefficient matrix, that is, replacing with in each formula. Based on the foregoing process, the normalized correlation coefficient matrix is obtained, and then the mean of is calculated to obtain Mean_ , which characterizes the overall intensity homogeneity of this type of organoid.

[0050] Figure 4 , Figure 5 , Figure 6 are schematic diagrams of three-dimensional images of organoids with different morphologies in the present invention. After calculation, the corresponding Mean_ , and can be obtained; the Figure 4 of the organoid in , and ; the Figure 5 of the organoid in , and ; the Figure 6 of the organoid in , and .

[0051] After completing the analysis of the homogeneity of the organoids, the server can classify the organoids within the target organoid cluster according to 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 domain data corresponding to each organoid within the target organoid cluster to obtain morphological parameters including at least one of the organoid entity volume, organoid filling volume, organoid surface area, longest axis, shortest axis, sphericity, aspect ratio of the long and short axes, and specific surface area. Thus, according to the morphological homogeneity, intensity homogeneity, and multi-dimensional morphological parameters of each organoid within the target organoid cluster, classification is performed through Kmeans clustering.

[0052] Finally, principal component analysis can be performed on the morphological homogeneity, intensity homogeneity, and multi-dimensional morphological parameters of each type of organoid in the target organoid cluster to determine the eigenvectors corresponding to the eigenvalues that reach the preset cumulative contribution rate as the principal components, and determine the scores of each type of organoid on each principal component. The corresponding scores are weighted and summed through the contribution rates of each principal component to determine the growth levels of each type of organoid. Finally, the drug effect analysis of the tumor organoids can be performed based on the growth levels under different drugs or drug concentrations to determine the promotion or inhibition of the drug on the growth of the tumor organoids, etc. There are already relatively mature techniques for performing drug effect analysis on tumor organoids based on the growth level, and the present invention will not elaborate on this.

[0053] Based on Figure 1 the drug effect analysis method based on the homogeneity of tumor organoids as shown, after obtaining the original three-dimensional structure data of the tumor organoids, the present invention first determines the connected domain data corresponding to each organoid within 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 radii corresponding to the organoid entities at different polar angles and different azimuth angles. The connected domain data of each organoid is dot-multiplied with the original three-dimensional structure data points to obtain the intensity information of each organoid; the intensity homogeneity of each organoid is determined according to the intensity value vectors corresponding to different polar angles and different azimuth angles. Thus, the morphological homogeneity and intensity homogeneity of each organoid are used to reflect tumor heterogeneity. On this basis, classification is performed according to the morphological homogeneity and intensity homogeneity of each organoid within the target organoid cluster, and a growth level model of each type of organoid within the target organoid cluster is constructed for drug effect analysis, improving the classification accuracy of the tumor organoids to achieve more targeted research on the tumor organoids.

[0054] When applying the drug effect analysis method based on the homogeneity of tumor organoids provided by the present invention, it is not necessary to execute according to Figure 1 the order of the steps shown. The specific execution order of each step can be determined as needed, and the present invention does not limit this.

[0055] The above is the 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 concept, the present invention also provides a corresponding device for analyzing drug effects based on the homogeneity of tumor organoids, as Figure 7 shown.

[0056] Figure 7 FIG. is a schematic diagram of a device for analyzing drug effects based on the homogeneity of tumor organoids provided by the present invention, including: An acquisition module 201, configured to acquire the original three-dimensional structure data of multiple tumor organoids, perform organoid segmentation and connectivity analysis on the original three-dimensional structure data, and determine the connectivity domain data corresponding to each organoid in the target organoid cluster among the multiple tumor organoids; A morphological homogeneity analysis module 202, configured to determine the centroid of each organoid according to the connectivity 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 radii corresponding to the organoid entities at different polar angles and different azimuth angles; An intensity homogeneity analysis module 203, configured to multiply the connectivity domain data of each organoid by the original three-dimensional structure data points to obtain the intensity information of each organoid; determine the intensity homogeneity of each organoid according to the intensity value vectors corresponding to different polar angles and different azimuth angles; A drug effect analysis module 204, configured to classify each organoid in the target organoid cluster according to the morphological homogeneity and intensity homogeneity of each organoid, and construct a growth level model of each type of organoid in the target organoid cluster for drug effect analysis.

[0057] For the specific limitations of the device for analyzing drug effects based on the homogeneity of tumor organoids, reference can be made to the limitations of the method for analyzing drug effects based on the homogeneity of tumor organoids in the above text, which will not be elaborated here. Each module in the above device for analyzing drug effects based on the homogeneity of tumor organoids can be implemented in whole or in part by software, hardware, and their combinations. The above modules can be embedded in the processor of the computer device in the form of hardware or be independent of it, or can be stored in the memory of the computer device in the form of software, so as to facilitate the processor to call and execute the operations corresponding to the above modules.

[0058] The present invention also provides a computer-readable storage medium, which stores a computer program, and the computer program can be used to execute the above Figure 1 provided method for analyzing drug effects based on the homogeneity of tumor organoids.

[0059] The present invention also provides a computer device. At the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory. Of course, it may also include other hardware required for other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to implement the above Figure 1 drug action analysis method based on the homogeneity of tumor organoids provided.

[0060] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, 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.

[0061] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, 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, it should be considered to be within the scope recorded by the present invention.

Claims

1. A method for analyzing the effect of a drug based on the homogeneity of tumor organoids, characterized in that, Including: Obtaining the original three-dimensional structure data of multiple tumor organoids, performing organoid segmentation and connectivity analysis on the original three-dimensional structure data, and determining the connectivity domain data corresponding to each organoid in the target organoid cluster among the multiple tumor organoids; Determining the centroid of each organoid according to the connectivity domain data corresponding to each organoid, 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 radii corresponding to the organoid entities at different polar angles and different azimuth angles; Multiplying the connectivity domain data of each organoid by the original three-dimensional structure data points to obtain the intensity information of each organoid; determining the intensity homogeneity of each organoid according to the intensity value vectors corresponding to different polar angles and different azimuth angles; Classifying the organoids in the target organoid cluster according to the morphological homogeneity and intensity homogeneity of each organoid, and constructing a growth level model of each type of organoid in the target organoid cluster for drug action analysis.

2. The method for analyzing the effect of a drug based on the homogeneity of tumor organoids according to claim 1, wherein The step of 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 radii corresponding to the organoid entities at different polar angles and different azimuth angles specifically includes: Establishing a spherical coordinate system with the centroid of each organoid as the origin, and converting the connectivity domain data corresponding to each organoid into the spherical coordinate system; determining a plurality of sampling directions according to the preset sampling intervals of the polar angle and the azimuth angle; For each organoid, traversing each sampling direction, statistically accumulating the pixel points of the corresponding entity in the spherical coordinate system representation of the organoid in each sampling direction according to the preset radius interval, and obtaining the polar radii corresponding to the organoid entities at different polar angles and different azimuth angles; Determining the mean value of the polar radii corresponding to the organoid entities at different polar angles and different azimuth angles, which represents the average radius of the organoid; Determining the absolute value of the difference between the polar radii corresponding to the organoid entities at different polar angles and different azimuth angles and the average radius of the organoid, and characterizing the morphological homogeneity distribution of the organoid through the minimum polar radius, the maximum polar radius, the polar radius variance, and the absolute value of the difference among the polar radii corresponding to the organoid entities at different polar angles and different azimuth angles; and characterizing the overall morphological homogeneity of the organoid through the mean value of the absolute value of the difference.

3. The method for analyzing drug effects based on tumor organoid homogeneity according to claim 1, wherein: The step of determining the intensity homogeneity of each organoid according to the intensity value vectors corresponding to different polar angles and different azimuth angles specifically includes: Performing polar radius traversal according to the maximum polar radius among the polar radii corresponding to the organoid entities at different polar angles and different azimuth angles. For each length of the polar radius, performing correlation analysis on the intensity value vectors corresponding to different polar angles and different azimuth angles of each organoid at the length of the polar radius under the preset polar angle and azimuth angle window, and obtaining the intensity homogeneity distribution of each organoid within the range of the length of the polar radius; Determining the mean value of the intensity homogeneity distribution of each organoid at the length of the polar radius to characterize the overall intensity homogeneity of each organoid within the range of the length of the polar radius.

4. The method for analyzing drug effects based on tumor organoid homogeneity according to claim 1, wherein: The step of determining the centroid of each organoid according to the connectivity domain data corresponding to each organoid specifically includes: For each organoid, according to the connectivity domain data corresponding to the organoid, determining the centroid of each organoid through the following formula: ； ； ； Among them, is the coordinate of the i th non-zero voxel in the t th organoid, is the i total number of non-zero voxels in the target area corresponding to the th organoid, and i is the centroid of the th organoid.

5. The method for analyzing the effect of a drug based on the homogeneity of tumor organoids according to claim 1, wherein The classification is based on the morphological homogeneity and intensity homogeneity of each organoid within the target organoid cluster, specifically including: Performing morphological analysis on the connected domain data corresponding to each organoid in the target organoid cluster to obtain at least one morphological parameter selected from the group consisting of organoid solid volume, organoid filling volume, organoid surface area, longest axis, shortest axis, sphericity, ratio of the major axis to the minor axis, and specific surface area; Classification was performed by Kmeans clustering based on the morphological homogeneity, intensity homogeneity, and multidimensional morphological parameters of each organoid within the target organoid cluster.

6. The method for analyzing the effect of a drug based on the homogeneity of tumor organoids according to claim 1, wherein The method of obtaining original three-dimensional structural data of multiple tumor organoids, performing organoid segmentation and connectivity analysis on the original three-dimensional structural data, and determining connected domain data corresponding to each organoid in a target organoid cluster among the multiple tumor organoids specifically includes: Acquire three-dimensional interferometric spectral data of multiple tumor organoids based on three-dimensional optical imaging technology; Perform spectral frequency domain analysis on the three-dimensional interferometric spectroscopy data to obtain the original three-dimensional structural data of multiple tumor organoids; Perform organoid segmentation on the original three-dimensional structure data to obtain binary data containing the target organoid cluster in multiple tumor organoids; Connectivity analysis is performed 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 the homogeneity of tumor organoids, characterized in that, include: an acquisition module for acquiring original three-dimensional structural data of multiple tumor organoids, performing organoid segmentation and connectivity analysis on the original three-dimensional structural data, and determining connected domain data corresponding to each organoid within a target organoid cluster among the multiple tumor organoids; A morphological homogeneity analysis module is used to determine the centroid of each organoid based on 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 based on the polar radius corresponding to the organoid entities at different polar angles and different azimuths; The intensity homogeneity analysis module is used to obtain the intensity information of each organoid by multiplying the connected domain data of each organoid with the original three-dimensional structure data. The intensity homogeneity of each organoid is determined based on the intensity value vectors corresponding to different polar angles and different azimuth angles. The drug effect analysis module is used to classify the various organoids within the target organoid cluster based on the morphological homogeneity and intensity homogeneity of each organoid, and to construct a growth level model of each organoid within the target organoid cluster for drug effect analysis.

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

9. A computer device, characterized in that, The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the program.

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