Calculation method of trabecular bone morphometric parameters for polymer-embedded sectional specimens

Abstract

The present invention provides a calculation method for the morphological metrology parameters of trabecular bone in polymer-embedded sectional specimens, which relates to the field of biomedical engineering technology. The aim is to solve the problems in the existing trabecular bone morphology measurement, such as the inability to quickly reflect the true situation in vivo and the repeated sampling, which increases the labor intensity. The adopted technical solution is that at the macro-micro level, the precise morphological metrology parameters of trabecular bone at multiple positions are intelligently identified in a large range, which is of great significance for understanding the biomechanical information of the trabecular bone gradient change in situ bone and further developing biomaterials with better biocompatibility; in programming software, the division of the region of interest of bone sections is realized, and the operator can repeatedly extract the trabecular bone information of the region of interest in a large range and at multiple sites according to his own situation, without the need for manual cutting and grinding of bone tissue, reducing the human error and simplifying the work process.

Description

Technical Field

[0001] The present invention relates to the technical field of biomedical engineering, and particularly to a method for calculating the morphometric parameters of trabecular bone in polymer-embedded tomographic specimens. Background Art

[0002] Through the mutual connection between various ligaments and muscle tissues, bones form an organic whole, which plays a role in supporting and protecting organisms. Therefore, through long-term evolution, bones have formed unique structures and mechanical properties. At the microscopic level, bone can be divided into cortical bone and cancellous bone. Cortical bone is hard and has a compact structure, while cancellous bone is mostly spongy-like and is composed of intertwined trabecular bone arranged. The mechanical properties of bones are relatively complex, and the stress-strain curve of bones is related to the porosity and internal microstructure in the bones. Usually, the content of minerals in bone mass and the distribution of trabecular bone both show non-uniform characteristics. Therefore, fully understanding the architectural characteristics and distribution of trabecular bone in bone is of great significance for accurately understanding the mechanical properties of the affected bone.

[0003] Based on this, in order to better see the distribution of trabecular bone and define its mechanical properties, a lot of work has been done. For example, the application of micro-computed tomography (Micro-CT) technology, nuclear magnetic resonance (MRI) technology, and hard tissue grinding slice technology. However, although nuclear magnetic resonance (MRI) technology can see the boundary of soft tissue, there are still limitations in grasping the fine structure of trabecular bone. Micro-computed tomography (Micro-CT) technology can obtain the fine structure of trabecular bone but cannot guarantee the boundary of soft tissue. And in the histological technology of trabecular bone structure, such as hard tissue grinding slice technology, the area is sliced and stained for observation, and the observation results of this area can also be analyzed by pictures to obtain some bone morphology parameters. However, this method is too microscopic, making it impossible for observers to observe the local structure from a global perspective, resulting in certain limitations in the information obtained. In addition, both micro-computed tomography technology and nuclear magnetic resonance technology are imaging technologies. Limited by the imaging characteristics of imaging technologies, it may not be possible to judge the true characteristics of the structure.

[0004] With the increasing depth of research work, when obtaining the characteristic trabecular bone structure in the region of interest, while observing the distribution characteristics of trabecular bone structure in the region of interest (such as the direction of trabecular bone, the distribution range, etc.), it is becoming increasingly necessary to obtain the relationship between these trabecular bone structures and the surrounding structures (such as the change trend of the trabecular bone gradient compared with the trabecular bone in other parts of the affected bone, and how this gradient change is related to the mechanical effect of the surrounding soft tissue, etc.). These requirements directly raise the requirements for research means.

[0005] Chinese Patent CN 201810719290.3 discloses a porous structure design method based on the trabecular bone structure morphology and mechanical properties. The technical solution adopted includes the following steps: (1) establishing a three-dimensional model of trabecular bone; (2) solving the morphological parameters of trabecular bone; (3) exporting the trabecular bone volume mesh model; (4) calculating the mechanical properties of trabecular bone; (5) optimizing and solving the porous model; (6) restoring the solid structure. The above solution has the following problems: Micro-CT scans and projects the target structure layer by layer with X-rays. The X-rays passing through the layer are received by the detector, converted into visible light, then converted into electrical signals by the photoelectric converter, and then converted into digital signals by the analog-to-digital converter and input into the computer for imaging. This process involves the conversion of optical signals - electrical signals - digital signals. Therefore, limited by the imaging characteristics of imaging technology, it may not be possible to judge the true characteristics of the structure, that is, the structural information obtained is not in-situ. Micro-CT has requirements for the physical size of the sample and cannot obtain the trabecular bone information in overly large bones. If precise measurement is required, the target structure needs to be artificially cut to obtain the information, which has a certain degree of subjectivity. If information on different parts within the same structure needs to be obtained, it is necessary to cut and measure repeatedly. The process is cumbersome, and the inaccuracy caused by manual cutting cannot be ignored, that is, it is impossible to intelligently identify the precise morphological measurement parameters of trabecular bone in multiple positions on a large scale. Micro-CT has great limitations in determining the levels and boundaries of soft tissues. The growth of trabecular bone is closely related to the force on the affected area. For organisms, bones form an organic whole through the mutual connection between various ligaments and muscle tissues. Therefore, when studying the content of trabecular bone morphological measurement, combining the boundaries and levels of soft tissues is of great significance for comprehensively analyzing the biomechanical information of the target area, that is, it is impossible to obtain the relationship between the trabecular bone structure and the surrounding structures, and the measured values cannot reflect the true situation in the organism. With the intervention of different scientific problems, it is necessary to repeatedly obtain samples according to requirements, increasing the workload.

[0006] Currently, the tissue sectioning technology made by embedding with polymer materials has gradually come into people's view. For example, the P45 bio-plasticization technology, which is a technology between microscopic anatomy and gross anatomy. It can observe the fine structures of large specimens in-situ in a transparent state, clearly showing the levels and boundaries of soft tissues while clearly presenting the trabecular bone architecture characteristics. It bridges the gap between gross anatomy and histology. Therefore, based on the superiority of the tissue sectioning technology made by embedding with polymer materials, the present invention proposes a calculation method for the morphological measurement parameters of trabecular bone in polymer material embedded section specimens at the macro-micro level. Summary of the Invention

[0007] In view of the problems existing in the prior art, the present invention discloses a calculation method for the morphological measurement parameters of trabecular bone in polymer-embedded tomographic specimens. The technical solution adopted is as follows:

[0008] Step 1: Select a healthy object to be processed. After processing, a target section is prepared.

[0009] Step 2: Use a collection device to take an overall picture and record the target section in Step 1.

[0010] Step 3: In programming software, through program writing, calculate the Hessian matrix for the image in Step 2, identify different regional structures through the eigenvalues of the Hessian matrix, select the target regional structure for filtering and enhancement, and suppress other background regional structures.

[0011] Step 4: During the process of filtering and enhancing the target regional structure, calculate the eigenvectors of the Hessian matrix, obtain the direction information of the trabecular bone, mask the trabecular bone in non-interested directions, and then use threshold segmentation to convert the target regional structure into a binary image.

[0012] Step 5: Use mouse interaction to create a polygon object and specify the shape and position of the region of interest within the binary image generated in Step 4.

[0013] Step 7: Convert the content within the region of interest into a binary image and calculate the porosity of the trabecular bone within this region.

[0014] Step 8: Adopt the mean intercept length algorithm to calculate the anisotropy degree of the trabecular bone within the region of interest through the ratio of the minimum unit intercept to the large unit intercept.

[0015] Step 9: Generate N randomly oriented and sized line segments within the region of interest, count the number of intersections with trabecular bone and non-trabecular bone during the line segment traversal, calculate the average number of intersections per unit length of the line segment between the trabecular bone and non-trabecular bone regions, and convert it to the physical size.

[0016] As a preferred technical solution of the present invention, the processing process in Step 1 includes embedding, freezing, dehydration, degreasing, and polymer infiltration treatment. Since the specimen has undergone dehydration and degreasing treatment, the layers and boundaries of the soft tissue are clearly visible. Therefore, after obtaining the trabecular bone information of the region of interest, the biomechanical information of this region can be comprehensively analyzed by combining the distribution of the soft tissue, and the information obtained is closer to the real situation inside the organism.

[0017] As a preferred technical solution of the present invention, in step 1, the target section is prepared by P45 bioplasticization technology. Since it is a tomographic image of the specimen, the information obtained is in situ and can reflect the true situation of the trabecular bone of the object in situ.

[0018] As a preferred technical solution of the present invention, the acquisition device in step 2 uses a digital camera, and the division of the region of interest of the bone section is realized in programming software. The operator can, according to his own situation, repeatedly extract the trabecular bone information of the region of interest in a large range and multiple parts, and no longer needs to manually cut and polish the bone tissue, reducing human error and simplifying the work process.

[0019] As a preferred technical solution of the present invention, the programming software in step 3 can use Matlab. At the macro and micro levels, it can intelligently identify the precise parameters of the trabecular bone morphology in multiple positions in a large range, which is of great significance for understanding the biomechanical information of the in situ trabecular bone gradient change and further developing biomaterials with better biocompatibility.

[0020] As a preferred technical solution of the present invention, the target region structure includes a tubular structure and a spherical structure.

[0021] As a preferred technical solution of the present invention, in step 4, the ratio of the number of trabecular bone pixels in a specific direction to the number of pixels in the entire trabecular bone region is statistically calculated using a histogram to calculate the proportion of trabecular bone in different directions.

[0022] As a preferred technical solution of the present invention, in step 6, the area of the region of interest is calculated using the vertex coordinate positions of the polygon region of interest. After studying a scientific problem once, the bone section is stored conventionally. When another scientific problem is involved, only the region of interest needs to be obtained again in the programmable software according to the situation, and there is no need to take materials again and re-make the bone tomographic section.

[0023] As a preferred technical solution of the present invention, in step 7, zero pixels represent pores and one pixel represents the trabecular bone structure. By calculating the ratio of zero pixels to the total number of pixels in the region of interest, the porosity of the trabecular bone in this region is calculated.

[0024] As a preferred technical solution of the present invention, in step 8, the mean intercept algorithm includes randomly generating N groups of parallel lines in different directions in the region of interest, counting the intersections of the parallel lines in the same group direction with the trabecular bone, calculating the average unit intercept of the intersections of the parallel lines in the same group direction with the trabecular bone, and finally calculating the average unit intercept of N groups in different directions.

[0025] Advantages of the present invention: At the macro and micro levels, the present invention can accurately identify the morphological measurement parameters of bone trabeculae at multiple positions in a large range in an intelligent manner, which is of great significance for understanding the biomechanical information of the in-situ bone trabecular gradient change and further developing biomaterials with better biocompatibility.

[0026] Furthermore, since the information of the specimen's tomographic image is obtained in-situ, it can reflect the true situation of the object's bone trabeculae in-situ; the division of the region of interest of the bone section is realized in programming software, and the operator can repeatedly extract the bone trabecular information of the region of interest in a large range and at multiple sites according to their own situation, without the need to artificially cut and polish the bone tissue, reducing human error and simplifying the work process; since the specimen has been dehydrated and defatted, the layers and boundaries of the soft tissue are clearly shown. Therefore, after obtaining the bone trabecular information of the region of interest, the biomechanical information of this region can be comprehensively analyzed by combining the distribution of the soft tissue, and the information obtained is closer to the true situation inside the organism; after studying a scientific problem once, the bone section is stored conventionally. When another scientific problem is involved, only the region of interest needs to be obtained again in the programmable software according to the situation, without the need to take samples again and make bone tomographic sections again.

[0027] Furthermore, the bone tomographic section embedded with polymer materials can observe the fine structures of the specimen in a large range in-situ in a transparent state, clearly show the layers and boundaries of the soft tissue in high definition while presenting the bone trabecular architecture characteristics in high definition, which ensures that the obtained bone trabecular information is all in-situ and the obtained information is not limited; the information acquisition on the tomographic section is realized through programming means, and this process is intelligent and supports the extraction of information from different parts on the same section, greatly reducing the participation of human labor. Description of the Drawings

[0028] Figure 1 It is the program flow chart of the present invention. Detailed Embodiments Embodiment 1

[0029] As Figure 1 shown, the present invention discloses a calculation method for the morphological measurement parameters of bone trabeculae of a polymer material-embedded tomographic specimen. The technical solution adopted includes the following steps:

[0030] Step 1, select a healthy object to be processed, and after processing, obtain a target section;

[0031] Step 2, use a collection device to take an overall picture and record the target section in Step 1;

[0032] Step 3: In programming software, calculate the Hessian matrix for the image in Step 2 through programming. Identify different regional structures based on the eigenvalues of the Hessian matrix, select the target regional structure for filtering and enhancement, and suppress other background regional structures.

[0033] Step 4: During the process of filtering and enhancing the target regional structure, calculate the eigenvectors of the Hessian matrix to obtain the direction information of the trabecular bone, mask the trabecular bone in non - interesting directions, and then use threshold segmentation to convert the target regional structure into a binary image.

[0034] Step 5: Use mouse interaction to create a polygon object and specify the shape and position of the region of interest within the binary image generated in Step 4.

[0035] Step 6: Calculate the area of the region of interest.

[0036] Step 7: Convert the content within the region of interest into a binary image and calculate the porosity of the trabecular bone in this region.

[0037] Step 8: Adopt the mean intercept length algorithm to calculate the anisotropy degree of the trabecular bone in the region of interest by calculating the ratio of the minimum unit intercept to the large unit intercept.

[0038] Step 9: Generate N randomly - directed and - lengthed line segments within the region of interest, count the number of intersections with trabecular bone and non - trabecular bone during the line segment traversal, calculate the average number of intersections between trabecular bone and non - trabecular bone regions per unit length of the line segment, and convert it to physical dimensions.

[0039] As a preferred technical solution of the present invention, the processing process in Step 1 includes embedding, freezing, dehydration, degreasing, and polymer infiltration treatment.

[0040] As a preferred technical solution of the present invention, the target section is obtained by P45 bioplastics technology in Step 1.

[0041] As a preferred technical solution of the present invention, the acquisition device in Step 2 uses a digital camera.

[0042] As a preferred technical solution of the present invention, the programming software in Step 3 can use Matlab. Through programming, calculate the Hessian matrix for the section image, identify different regional structures based on the eigenvalues of the Hessian matrix, selectively enhance the tubular structure region and the spherical structure therein, and suppress the low - contrast background region, so as to achieve the purpose of enhancing the trabecular bone structure.

[0043] As a preferred technical solution of the present invention, the target regional structure includes a tubular structure and a spherical structure.

[0044] As a preferred technical solution of the present invention, in step 4, the ratio of the number of trabecular pixels in a specific direction to the number of pixels in the entire trabecular region is statistically calculated by using a histogram to calculate the proportion of trabeculae in different directions. The bone tomographic section made by embedding with a polymer material can in-situ observe the fine structures of a large range of specimens in a transparent state, clearly show the soft tissue layers and boundaries in high definition while presenting the trabecular architecture characteristics in high definition, which ensures that the obtained trabecular information is all in-situ and the obtained information is not limited.

[0045] As a preferred technical solution of the present invention, in step 6, the area of the region of interest is calculated by using the vertex coordinate positions of the polygon region of interest.

[0046] As a preferred technical solution of the present invention, in step 7, zero pixels represent pores and one pixel represents the trabecular structure. By calculating the ratio of zero pixels in the region of interest to the total number of pixels, the porosity of the trabeculae in this region is calculated. The information acquisition on the tomographic section is realized by programming means. This process is intelligent and supports the extraction of information from different parts of the same section, greatly reducing the participation of human labor.

[0047] As a preferred technical solution of the present invention, in step 8, the mean intercept length algorithm includes randomly generating N groups of parallel lines in different directions in the region of interest, counting the intersections of the parallel lines in the same group direction and the trabeculae, calculating the average unit intercept of the intersections of the parallel lines in the same group direction and the trabeculae, and finally calculating the average unit intercepts of the N groups of different directions.

[0048] Working principle of the present invention: During use, bone tomographic slices made by embedding with polymer materials are imported into programmable software in the form of images. Then, by calculating the Hessian matrix for the slice images, different structures are identified through the eigenvalues of the Hessian matrix, and the tubular structures and spherical structures among them are selectively enhanced, while the background regions with low contrast are suppressed, so as to achieve the purpose of enhancing the trabecular bone structure; during the trabecular bone filtering and enhancement process, the direction information of the trabecular bone can be obtained by calculating the eigenvectors of the Hessian matrix; in the programmable software, according to requirements, the trabecular bone in non-interested directions is masked to make it the same as the background value, so as to achieve the purpose of only displaying the trabecular bone structure within the specified direction range; then, the ratio of the number of pixels of the trabecular bone in a specific direction to the number of pixels in the entire trabecular bone area is statistically calculated using a histogram to calculate the proportion of the trabecular bone in different directions; subsequently, threshold segmentation is used to convert the filtered and enhanced slice image into a binary image; then, a polygon object is interactively created using the mouse to specify the shape and position of the region of interest; the area of the region of interest is calculated using the vertex coordinate positions of the polygon region of interest; further, the content within the region of interest is converted into a binary image, where zero pixels represent pores and one pixel represents the trabecular bone structure, and the ratio of the number of zero pixels to the total number of pixels within the region of interest is the porosity of the trabecular bone in this region; then, using the mean intercept length algorithm, N groups of parallel lines in different directions are randomly generated within the region of interest, the intersections of the parallel lines in the same group direction with the trabecular bone are counted, the average unit intercept of the intersections of the parallel lines in the same group direction with the trabecular bone is calculated, and finally the average unit intercepts of the N groups in different directions are calculated, and the minimum unit intercept / maximum unit intercept represents the anisotropy degree of the trabecular bone within the region of interest; similarly, N line segments with random directions and lengths are generated within the region of interest, the number of intersections with the trabecular bone and non-trabecular bone during the line segment's travel is counted, the average number of intersections of the trabecular bone and non-trabecular bone regions per unit length of the line segment is calculated, and it is converted to the physical size.

[0049] In "Tim, Jerman, Franjo, et al. Enhancement of Vascular Structures in 3Dand 2D Angiographic Images[J]. IEEE Transactions on Medical Imaging, 2016.P3-6", it is stated that "the Hessian matrix is used in imaging technology", indicating that the application of the Hessian matrix in imaging technology is prior art.

[0050] The components not described in detail in this article are prior art.

[0051] Although the specific embodiments of the present invention have been described in detail above, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those of ordinary skill in the art, various changes can be made without departing from the gist of the present invention, and modifications or variations that do not involve creative labor are still within the protection scope of the present invention.

Claims

1. A method for calculating the morphometric parameters of trabecular bone in polymer-embedded sectional specimens, characterized in that, It includes the following steps: Step 1: Select a healthy object to be processed. After processing, obtain the target section. Step 2: Use a collection device to take an overall picture of the target section in Step 1 and record it. Step 3: In programming software, through programming, calculate the Hessian matrix for the image in Step 2. Identify different regional structures through the eigenvalues of the Hessian matrix. Select the target regional structure for filtering and enhancement, and suppress other background regional structures. Step 4: During the process of filtering and enhancing the target regional structure, calculate the eigenvectors of the Hessian matrix to obtain the direction information of the trabeculae. Mask the trabeculae in non - interesting directions, and then use threshold segmentation to convert the target regional structure into a binary image. Step 5: Use mouse interaction to create a polygon object and specify the shape and position of the region of interest within the binary image generated in Step 4. Step 6: Calculate the area of the region of interest. Step 7: Convert the content within the region of interest into a binary image and calculate the porosity of the trabeculae in this region. Step 8: Adopt the mean intercept length algorithm to calculate the anisotropy degree of the trabeculae in the region of interest by calculating the ratio of the minimum unit intercept to the large unit intercept. Step 9: Generate N line segments with random directions and lengths within the region of interest. Count the number of intersections with trabeculae and non - trabeculae during the traversal of the line segments. Calculate the average number of intersections per unit length of the line segments between the trabeculae and non - trabeculae regions and convert it to physical dimensions.

2. The method for calculating the trabecular bone morphometric parameters of the polymer-embedded sectional specimen according to claim 1, wherein: The processing process in Step 1 includes embedding, freezing, dehydration, degreasing, and polymer infiltration treatment.

3. The method for calculating the trabecular bone morphometric parameters of the polymer-embedded sectional specimen according to claim 1, wherein: The target section in Step 1 is obtained by P45 bioplasticization technology.

4. The calculation method of the trabecular bone morphometric parameters of the polymer-embedded sectional specimen according to claim 1, characterized in that: The collection device in Step 2 uses a digital camera.

5. The method for calculating the trabecular bone morphometric parameters of the polymer-embedded sectional specimen according to claim 1, wherein: The programming software in Step 3 can use Matlab.

6. The calculation method of the trabecular bone morphometric parameters of the polymer-embedded sectional specimen according to claim 1, wherein: The target regional structure includes tubular structures and spherical structures.

7. The calculation method of the trabecular bone morphometric parameters of the polymer-embedded sectional specimen according to claim 1, characterized in that: In Step 4, use histogram statistics to calculate the ratio of the number of trabecular pixels in a specific direction to the number of pixels in the entire trabecular region, and calculate the proportion of trabeculae in different directions.

8. The calculation method of the trabecular bone morphometric parameters of the polymer-embedded sectional specimen according to claim 1, wherein: The area of the region of interest in Step 6 is calculated using the vertex coordinate positions of the polygon region of interest.

9. The calculation method of the trabecular bone morphometric parameters of the polymer-embedded sectional specimen according to claim 1, wherein: In Step 7, zero pixels represent pores and one pixel represents trabecular structure. Calculate the porosity of the trabeculae in this region by calculating the ratio of zero pixels to the total number of pixels within the region of interest.

10. The calculation method of the trabecular bone morphometric parameters of the polymer-embedded sectional specimen according to claim 1, characterized in that: In Step 8, the mean intercept algorithm includes randomly generating N groups of parallel lines with different directions within the region of interest, counting the intersections of the parallel lines in the same group direction with the trabeculae, calculating the average unit intercept of the intersections of the parallel lines in the same group direction with the trabeculae, and finally calculating the average unit intercept of the N groups of different directions.

Images