CN115056488A - Construction method of anisotropic structure bionic tissue based on bioprinting - Google Patents
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
- B29C64/30—Auxiliary operations or equipment
- B29C64/386—Data acquisition or data processing for additive manufacturing
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
- B29C64/30—Auxiliary operations or equipment
- B29C64/386—Data acquisition or data processing for additive manufacturing
- B29C64/393—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y50/00—Data acquisition or data processing for additive manufacturing
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- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y50/00—Data acquisition or data processing for additive manufacturing
- B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
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Abstract
The invention discloses a method for constructing an anisotropic structure bionic tissue based on bioprinting, which comprises the following steps: slicing the three-dimensional structure of the bionic tissue to generate different cross sections; generating a grid pattern within each cross-sectional morphology: generating an anisotropic grid pattern by adopting a self-adaptive grid generation algorithm based on triangulation algorithm optimization; and converting the grid pattern into an ordered printing path data set which can be introduced into a G code command language system of the biological printer by utilizing a triangular unit greedy search algorithm so as to construct the anisotropic structure bionic tissue. The bionic anisotropic structure is designed based on natural tissue characteristics and the step-by-step algorithm for ordered printing is used for assisting biological printing, so that a new strategy can be provided for the customized construction of the bionic tissue microstructure.
Description
Technical Field
The invention belongs to the technical field of biological tissue construction, and particularly relates to a construction method of an anisotropic structure bionic tissue based on biological printing.
Background
The natural anisotropic structures present in human tissues and organs play a critical role in their normal operation. For example, cancellous bone is a porous anisotropic network consisting of trabeculae of bone about 200 μm thick; this microstructure is closely related to local mechanical properties and mediates local biological reactions. The morphology and distribution of the vascular network in the tissue directly determines the nutrition, oxygen supply and waste discharge. Therefore, the importance of constructing an anisotropic structure in a biomimetic tissue has been gradually emphasized in research in the fields of regenerative medicine, disease pathogenesis, and the like. In recent decades, with the realization of controllable arrangement of multiple types of bio-ink, the application potential of extrusion bio-printing in tissue and organ construction has been increasingly highlighted. Through regulating and controlling the chemical components of the biological ink and the loaded growth factors, the biological printing structural body which provides a growth microenvironment required by specific tissue regeneration can be successfully constructed. During printing, by applying external stimuli (e.g., forces and magnetic fields), the manner in which cells are arranged in the printed structure can be manipulated. However, due to the limitations of the prior art, the construction of the anisotropic structure of the biomimetic tissue is still difficult to achieve. Therefore, the development of upgraded bioprinting techniques for customizable anisotropic structures has become the focus of current functional tissue-organ building research.
In the G code driving mode, the extrusion type biological printing system deposits biological ink layer by layer along the planned printing path by controlling the printing nozzle to construct a three-dimensional structure. The single path planning method adopted by the common biological printing system is a main reason for being incapable of realizing anisotropic structure design and printing. Although the advantages of building specific G-code print path data are increasingly prominent in custom structure building, the strategy is limited to small-batch path data processing of a rule structure. Therefore, mathematical algorithm-assisted strategies are beginning to be tried for the print construction of specific structures based on their characteristics for systematic design of structure data. Grigoryan et al applied a space-filling mathematical topological algorithm to stereolithography bioprinting, successfully designed and printed a biomimetic vascular network based on the structural features of natural vascular networks. The introduction of the algorithm design enables the shape-adjustable interactive blood vessel network and the branched blood vessel network surrounding the airway to be successfully constructed. However, due to the difference of the structure forming mechanism, the existing topological structure design algorithm-assisted strategy matching with the stereolithography bioprinting technology cannot be used for extrusion type bioprinting.
Disclosure of Invention
In order to solve the problems, the invention provides a bionic tissue construction method of an anisotropic structure based on biological printing; the stable bionic anisotropic structure is designed based on natural tissue characteristics, and the step-by-step algorithm for orderly printing is used for assisting biological printing, so that the precision and the efficiency of constructing the bionic tissue can be improved.
In order to achieve the purpose, the invention adopts the technical scheme that: a construction method of an anisotropic structure bionic tissue based on biological printing comprises the following steps:
s10, slicing the three-dimensional structure of the tissue to generate different cross sections;
s20, generating a grid pattern within each cross-sectional shape: generating an anisotropic grid pattern by adopting a self-adaptive grid generation algorithm based on triangulation algorithm optimization;
s30, converting the anisotropic grid pattern into an ordered print path: converting the grid pattern into a printing path by adopting a triangular unit greedy search algorithm;
and S40, depositing bio-ink by the 3D bio-printing system according to the planned printing path to construct the anisotropic structure bionic tissue.
Further, the three-dimensional structure is obtained by scanning and collecting tissues according to image detection equipment, is processed through image processing software, and is sliced to generate different cross sections.
Further, an adaptive mesh generation algorithm based on triangulation algorithm optimization is adopted to generate anisotropic mesh patterns:
based on the physical similarity of a network structure and a truss structure, the self-adaptive grid generation algorithm simulates connection points in the pattern to truss structure nodes and network lines among the points to a truss on the basis of the pattern generation design of a Matlab software triangulation algorithm, and the pattern is further optimized by a free energy minimization mechanism by adding a force-displacement function condition;
the characteristics of the generated pattern comprise the shape, the size and the distribution of an internal grid structure, and the regulation and control are carried out by adding a set parameter equation or positioning seed points; and when all the parameters are determined and run, the network topology pattern is quickly generated based on the minimum free energy.
Further, converting the network pattern into printing paths, and sequencing all the printing paths; and converting the pattern data into an ordered printing path data set introduced into a G code command language system of the biological printer by using a triangular unit greedy search algorithm to serve as a printing path, so that the printer nozzle starts from an initial nozzle position, sequentially passes through the planning path and deposits biological ink.
Further, the logic for operating the method for planning a print path dataset for a line of multiple points using a triangle unit greedy search algorithm comprises the steps of:
firstly, moving the spray head to a vertex which is closest to the current spray head and has at least one unprinted triangle edge;
if there are multiple unprinted edges, one of them will be selected randomly;
after printing of one edge is finished, searching an edge with the smallest included angle with the previous printing edge as the next printing edge;
the nozzle continues to seek and print edges until it reaches a vertex where all edges have been printed, ending the printing of a multi-point, one-line path.
Then, the spray head stops depositing the biological ink and moves to the nearest vertex to start printing a new path;
when all edges have been printed, the entire printing process stops.
The beneficial effects of the technical scheme are as follows:
the method adopts a self-adaptive mesh generation algorithm based on triangulation algorithm optimization to generate an anisotropic mesh pattern; converting the anisotropic grid pattern into an ordered printing path data set which can be placed into a printer language to form a G code instruction by utilizing a triangular unit greedy search algorithm; the stepwise algorithm-assisted bioprinting method can design a stable bionic anisotropic structure based on natural tissue characteristics and perform ordered printing.
The self-adaptive mesh generation algorithm based on triangulation algorithm optimization introduces force-displacement function condition design on the basis of Matlab triangulation algorithm, and high-quality anisotropic mesh patterns which have the minimum free energy and optimized mechanical characteristics are efficiently designed and generated in a specific space. The size and distribution of the anisotropic grid in the planar model can be controllably adjusted by adjusting and controlling parameters in the algorithm.
The invention can conveniently convert the generated pattern into ordered printing path data by using the greedy search algorithm of the triangular unit, effectively avoids structural deformation caused by multiple accumulation of materials and reduces the printing time. By utilizing the randomness function in the grid pattern generation algorithm, a multilayer structure pattern with anisotropic interconnected pores can be designed and bioprinted.
The method has high-efficiency structural design and path planning capability, universal applicability to biological materials and biological printers, and the stepwise algorithm assisted biological printing technology has the potential of customizing bionic tissues containing anisotropic structures.
Drawings
FIG. 1 is a schematic diagram of the principle of a bio-printing-based anisotropic bionic tissue construction method of the invention;
FIG. 2 is a logic flow diagram of a triangle cell greedy search algorithm to formulate a generated pattern as print path data in an embodiment of the present invention;
FIG. 3 is a print path design drawing and corresponding print head movement distance data for different algorithm strategy plans in an embodiment of the present invention;
FIG. 4 is a drawing of a single layer anisotropic pattern design and a physical printing using calcium phosphate based, polycaprolactone, and hydrogel bio-inks, respectively, in accordance with an embodiment of the present invention;
FIG. 5 is a schematic representation of a layout of a multilayer structure with locally controlled anisotropy and a bioprinted entity in an embodiment of the present invention;
FIG. 6 is a diagram of different custom structure designs and printed entities in an embodiment of the invention.
FIG. 7 is a digital photograph, a Micro-CT three-dimensional reconstruction image and a scanning electron microscope photograph of anisotropic bionic bone printed by calcium phosphate-based bio-ink in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described with reference to the accompanying drawings.
In this embodiment, referring to fig. 1, the present invention provides a method for constructing an anisotropic bionic tissue based on bioprinting, including the steps of:
s10, slicing the three-dimensional structure of the tissue to generate different cross sections;
s20, generating a grid pattern within each cross-sectional morphology: generating an anisotropic grid pattern by adopting a self-adaptive grid generation algorithm based on triangulation algorithm optimization;
s30, converting the anisotropic grid pattern into an ordered print path: converting the grid pattern into a printing path by adopting a triangular unit greedy search algorithm;
and S40, depositing bio-ink by the 3D bio-printing system according to the planned printing path to construct the anisotropic structure bionic tissue.
As an optimization scheme of the above embodiment, the three-dimensional structure scans and collects tissues through an image monitoring device, and is processed and sliced by image processing software to generate different cross sections.
As an optimization scheme of the above embodiment, an adaptive mesh generation algorithm based on triangulation algorithm optimization is adopted to generate an anisotropic mesh pattern:
based on the physical similarity of a network structure and a truss structure, the self-adaptive grid generation algorithm simulates connection points in the pattern to truss structure nodes and network lines among the points to a truss on the basis of the pattern generation design of a Matlab software triangulation algorithm, and the pattern is further optimized by a free energy minimization mechanism by adding a force-displacement function condition;
the characteristics of the generated pattern comprise the shape, the size and the distribution of an internal grid structure, and the regulation and control are carried out by adding a set parameter equation or positioning seed points; and when all the parameters are determined and run, the network topology pattern is quickly generated based on the minimum free energy.
The method has great advantages for bionic construction of natural tissue structures with irregular shapes, and the self-adaptive characteristic that the pattern generation algorithm automatically adjusts the density degree of the grids according to the shapes. The method proposed by the invention relates the change of the geometry to the local stress change, and the position with larger change of the geometry needs to generate a denser grid, and vice versa. Therefore, in the pattern design algorithm strategy of the present invention: based on the self-adaptive characteristic, a denser grid is formed in a region with larger change of the geometric form, and the constructed bionic tissue has more stable mechanical characteristics.
As an optimization scheme of the above embodiment, the network pattern is converted into the printing paths, and the printing paths are sequenced; and converting the pattern data into an ordered printing path data set introduced into a G code command language system of the biological printer by using a triangular unit greedy search algorithm to serve as a printing path, so that the printer nozzle starts from an initial nozzle position, sequentially passes through the planning path and deposits biological ink.
As shown in fig. 2, the logic for planning a print path data set of a multi-point-one-line by using a trigonometric greedy search algorithm includes the following steps:
firstly, moving the spray head to a vertex which is closest to the current spray head and has at least one unprinted triangle edge;
if there are multiple unprinted edges, one of them will be selected randomly;
after printing of one edge is finished, searching an edge with the smallest included angle with the previous printing edge as the next printing edge;
the nozzle continues to seek and print edges until it reaches a vertex where all edges have been printed, ending the printing of a multi-dot, one-line print path.
Then, the spray head stops depositing the biological ink and moves to the nearest vertex to start printing a new printing path;
when all edges have been printed, the entire printing process stops.
After printing one edge, the triangular unit greedy search algorithm selects the next edge with the minimum included angle with the previous edge to print.
One way of doing this is to select the next edge with an angle closest to 180 degrees each time to print. The minimum angle approach is selected based on the following three reasons. First, it allows the printer to print in focus on a local area. The batch-by-batch local printing enables each position structure to have stable and appropriate curing time, so that more thorough stable forming is realized and uniform material characteristics are obtained. If a contrast method is used, the nozzle path performs structural printing on small branches of the entire design pattern, often returning to the printed vertices and causing new printing paths to pass over existing printed structures causing material stacking and structural distortion; the strategy proposed by the present invention can effectively overcome this problem. Secondly, the strategy provided by the invention can effectively avoid generating an extremely short path which wastes time and is easy to cause structural deformation. Finally, the path planning strategy of the invention enables the total moving distance of the spray head to be smaller, so that the whole printing process can be completed more quickly. FIG. 3 shows the result of a digitized comparison of two methods of programming a path.
In order to verify the feasibility of the method provided by the invention in the auxiliary 3D bio-printing anisotropic structure design, a simple circular model is established.
As shown in fig. 4, a single-layer mesh pattern having a uniform anisotropic morphology can be designed and generated within a circular plane by a pattern generation algorithm. Through data processing of a path planning algorithm, various types of bio-ink (including calcium phosphate base, polycaprolactone and hydrogel) can be orderly printed to construct a design structure entity. Furthermore, the pattern generation algorithm proposed by the present invention allows for the generation of topological patterns of different mesh densities based on geometric curvature design, which is an ideal property for the construction of highly anisotropic structures. For example, in some cancellous bones (e.g., the femoral head, etc.), there are significant differences in local anisotropic structures. Similarly, through curvature regulation and control in a pattern design algorithm and conversion processing of a printing path algorithm, the invention successfully constructs an anisotropic structure entity which has the same appearance but can efficiently regulate and control a local microstructure.
Typically, the thickness of one printed layer is only 200-400 μm. This means that multiple layers of stack are required to form a suitable biomimetic structure during the bioprinting of biomimetic tissue such as cancellous bone, and furthermore, the geometric differences between successive layers are small. In the design of structures, if the same design pattern is used for successive printing layers, the printing ink is continuously stacked to form non-connected thick walls, thereby hindering the transportation of nutrients and wastes in the structure and the like. To avoid this, the pattern generation algorithm of the present invention can be used for design. In particular, different seed points are arranged for generating the pattern, i.e. at different longitudinal positions. As shown in fig. 5, the multilayer structures printed with this design exhibit interconnected customizable pores whose distribution is designed to approximate the heterogeneity of the native microstructure in the femoral head.
The method provided by the invention is used for verifying the capability of constructing the bionic tissue by combining the customizable anisotropic structure of the auxiliary 3D biological printing design and the designed biological ink. In terms of structural design, an allogeneic cancellous bone implant is first taken to analyze the true microstructure of the bone. It has been found that the network structure (including pore shape, size, distribution) in cancellous bone exhibits heterogeneity; the pore diameter is mainly distributed between 200 and 2000 mu m. On the basis of researching the natural bone structure, the invention provides an algorithm strategy for designing tissue-specific seed points so as to print and construct bionic cancellous bones with different pore sizes and distributions. After extracting the external shape data of the femoral model, the feasibility of the biomimetic structure design and the path generation strategy was first evaluated using polycaprolactone bio-ink. As shown in fig. 6, a single layer anisotropic structure with small, medium, large and gradient grid pore sizes is designed and printed and constructed by algorithm parameter setting. All printed solid structures are consistent with the design pattern. As previously mentioned, one key aspect of the design of biomimetic cancellous bone structures is to maintain pore connectivity within the structure after a multi-layered stack of bio-ink. In the algorithm printing design scheme, the bionic pore structure is gradually formed in the process of layer-by-layer superposition like the traditional printing technology. The scheme design of different pore connectivity characteristic organizational structures can be realized through the algorithm provided by the invention. As shown in fig. 7, the bionic bone with anisotropic structure was successfully constructed by combining the printing path designed by this strategy with calcium phosphate-based bio-ink.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (5)
1. A construction method of anisotropic structure bionic tissue based on biological printing is characterized by comprising the following steps:
s10, slicing the three-dimensional structure of the tissue to generate different cross sections;
s20, generating a grid pattern within each cross-sectional shape: generating an anisotropic grid pattern by adopting a self-adaptive grid generation algorithm based on triangulation algorithm optimization;
s30, converting the anisotropic grid pattern into an ordered print path: converting the grid pattern into a printing path by adopting a triangular unit greedy search algorithm;
and S40, depositing bio-ink by the 3D bio-printing system according to the planned printing path to construct the anisotropic structure bionic tissue.
2. The method for constructing the bionic tissue with the anisotropic structure based on the bioprinting as claimed in claim 1, wherein the three-dimensional structure is obtained by scanning and collecting the tissue according to a detection device, processing the tissue by image processing software, and slicing the tissue to generate different cross sections.
3. The method for constructing the bionic tissue with the anisotropic structure based on the biological printing as claimed in claim 1, characterized in that the adaptive mesh generation algorithm based on the triangulation algorithm optimization is adopted to generate the anisotropic mesh pattern:
based on the physical similarity of a network structure and a truss structure, the self-adaptive grid generation algorithm simulates connection points in the pattern to truss structure nodes and network lines among the points to a truss on the basis of the pattern generation design of a Matlab software triangulation algorithm, and the pattern is further optimized by a free energy minimization mechanism by adding a force-displacement function condition;
the characteristics of the generated pattern comprise the shape, the size and the distribution of an internal grid structure, and the regulation and control are carried out by adding a set parameter equation or positioning seed points; and when all the parameters are determined and run, the network topology pattern is quickly generated based on the minimum free energy.
4. The method for constructing the bionic tissue with the anisotropic structure based on the bioprinting as claimed in claim 1, characterized in that the network pattern is converted into printing paths, and the printing paths are sequenced; and converting the pattern data into an ordered printing path data set introduced into a G code command language system of the biological printer as a printing path by using a triangular unit greedy search algorithm, so that the printer nozzle starts from the initial nozzle position, sequentially passes through the planned path and deposits biological ink.
5. The method for constructing the bionic tissue with the anisotropic structure based on the bioprinting as claimed in claim 4, wherein the logic for operating the method for planning the data set of one printing path of one line of multiple points by using the greedy search algorithm of the trigonometric unit comprises the following steps:
firstly, moving the spray head to a vertex which is closest to the current spray head and has at least one unprinted triangle edge;
if there are multiple unprinted edges, one of them will be selected randomly;
after printing of one edge is finished, searching an edge with the smallest included angle with the previous printing edge as the next printing edge;
the nozzle continues to seek and print edges until it reaches a vertex where all edges have been printed, ending the printing of a multi-point, one-line path.
Then, the spray head stops depositing the biological ink and moves to the nearest vertex to start printing a new path;
when all edges have been printed, the entire printing process stops.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2018126535A3 (en) * | 2018-07-18 | 2020-01-20 | ||
| CN111168990A (en) * | 2019-12-30 | 2020-05-19 | 浙江大学 | Biological 3D printing device and method capable of realizing online detection and real-time correction |
| CN111789614A (en) * | 2020-08-10 | 2020-10-20 | 上海联影医疗科技有限公司 | Imaging system and method |
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