Microfluidic field condition determination method and apparatus

Abstract

The application provides a micro flow field condition determination method and device, three-dimensional OCTA data corresponding to three-dimensional tissue is collected according to a preset scanning mode; a complex cross-correlation difference value corresponding to the three-dimensional OCTA data is calculated based on the three-dimensional OCTA data; a previously established relationship curve is acquired, the three-dimensional tissue corresponding to the complex cross-correlation difference value is evaluated according to the relationship curve, and an evaluation result is obtained; the relationship curve is a relationship curve of the corresponding relationship between the complex cross-correlation difference value and the micro flow field flow velocity; and the micro flow field condition satisfying the comprehensive index is determined from the micro flow field flow velocity included in the evaluation result according to a pre-stored comprehensive index and a preset perfusion mode. The application can not only obtain the structure data of the three-dimensional tissue when the three-dimensional tissue is dynamically cultured, but also obtain the corresponding micro flow field distribution data, so that the micro flow control chip technology can be used for three-dimensional tissue culture, and the required micro flow field condition for culture can be obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of microfluidic chip, and in particular to a microflow field condition determination method and device. BACKGROUND

[0002] Microfluidic chip technology has a wide application in live cell and tissue analysis, can simulate the key function of the organ of the human body, has the advantages of miniaturization, integration and low power consumption, and can accurately and systematically control the parameters of the microfluidic chip operation, such as chemical concentration gradient, fluid shear stress, tissue-tissue interface, etc. The microfluidic technology can adjust the flow rate and shear force, and the geometric structure of the microfluidic chip affects the fluid dynamics environment of the three-dimensional tissue, which helps to realize the robust and replicable three-dimensional tissue culture, and is used as an advanced in vitro model to study the physiological and pathological mechanism of the tissue.

[0003] However, the microfluidic chip technology is still in its infancy, and there are still a large number of technical problems to be solved, such as the small size of the microchannel and the chamber of the microfluidic chip, which cannot obtain the structure data of the three-dimensional tissue with a larger size and the corresponding microflow field distribution in three-dimensional visual monitoring. If the corresponding microflow field distribution of the three-dimensional tissue cannot be obtained, the microflow field condition parameters of the microfluidic chip technology for culturing the three-dimensional tissue cannot be obtained. Therefore, the current microfluidic chip technology is not suitable for large-size three-dimensional tissue culture. In summary, how to dynamically culture three-dimensional tissue in the microfluidic chip and obtain the structure data of the three-dimensional tissue and the corresponding microflow field distribution is a major technical difficulty. SUMMARY

[0004] Therefore, the present application aims to provide a microflow field condition determination method and device, which can obtain the structure data of the three-dimensional tissue corresponding to the three-dimensional visual monitoring and the microflow field distribution data, and further obtain the microflow field condition for culturing the three-dimensional tissue.

[0005] In a first aspect, the present application provides a microflow field condition determination method, which comprises: collecting three-dimensional OCTA data corresponding to a three-dimensional tissue according to a preset scanning mode; calculating a complex cross-correlation difference value corresponding to the three-dimensional OCTA data based on the three-dimensional OCTA data; obtaining a previously established relationship curve, evaluating the three-dimensional tissue corresponding to the complex cross-correlation difference value according to the relationship curve, and obtaining an evaluation result; wherein the relationship curve is a relationship curve of the corresponding relationship between the complex cross-correlation difference value and the microflow field flow rate, and the evaluation result includes the microflow field flow rate corresponding to the three-dimensional tissue; determining the microflow field condition satisfying the comprehensive index from the microflow field flow rate included in the evaluation result according to the pre-stored comprehensive index and the preset perfusion mode.

[0006] With reference to the first aspect, in a first possible implementation of the first aspect, the method further includes: obtaining original microflow field information corresponding to the three-dimensional tissue according to the acquired three-dimensional OCTA data, and original three-dimensional structure data corresponding to the original microflow field information; performing calculation on the original three-dimensional structure data and the original microflow field information to obtain target microflow field information and target three-dimensional tissue structure data corresponding to the target microflow field information; wherein the target microflow field information includes microflow field information when the microflow field flow rate is 0 and microflow field information when the microflow field flow rate is not 0; and determining, as the complex cross-correlation difference value corresponding to the three-dimensional OCTA data, a difference value between the microflow field information when the microflow field flow rate is not 0 and the microflow field information when the microflow field flow rate is 0.

[0007] With reference to the first aspect, in a second possible implementation of the first aspect, the method further includes: performing filtering and binarization operations on the original three-dimensional structure data to obtain a structure mask; performing point multiplication processing on the structure mask and the original three-dimensional structure data to obtain denoised microflow field information; generating a binarization mask corresponding to the denoised microflow field information based on the denoised microflow field information; performing point multiplication processing on the binarization mask and the denoised microflow field information to obtain the target microflow field information; inverting the binarization mask and performing point multiplication on the inverted binarization mask and the original three-dimensional structure data to obtain the target three-dimensional tissue structure data corresponding to the target microflow field information.

[0008] With reference to the first aspect, in a third possible implementation of the first aspect, the microflow field flow rate includes an initial speed and a target speed, and the target speed is determined by gradually increasing the initial speed by a preset flow rate interval; the method further includes: acquiring a complex signal corresponding to the three-dimensional tissue in each microflow field flow rate based on a plurality of preset microflow field flow rates and a preset scanning mode; wherein the complex signal includes adjacent signals; calculating a complex cross-correlation value corresponding to the adjacent signals of the complex signal based on the preset scanning mode; determining a complex cross-correlation difference value corresponding to the complex signal based on the complex cross-correlation value; and performing polynomial fitting on the complex cross-correlation difference value of each microflow field flow rate and the current microflow field flow rate to obtain a relationship curve.

[0009] With reference to the first aspect, the embodiments of the present application provide a fourth possible implementation manner of the first aspect, wherein the complex cross-correlation values include complex cross-correlation values when the microfluidic flow rate is 0 and complex cross-correlation values when the microfluidic flow rate is not 0; and the step of determining the complex cross-correlation difference value corresponding to the complex signal based on the complex cross-correlation values includes: determining a difference value between the complex cross-correlation value of the current complex signal and the complex cross-correlation value when the microfluidic flow rate is 0 based on the microfluidic flow rate corresponding to the complex signal, to obtain the complex cross-correlation difference value corresponding to the complex signal.

[0010] With reference to the first aspect, the embodiments of the present application provide a fifth possible implementation manner of the first aspect, wherein the preset scanning mode includes a BM scanning mode and an MB scanning mode; the three-dimensional tissue corresponds to a microfluidic flow rate; and the method further includes: when the microfluidic flow rate corresponding to the three-dimensional tissue is greater than a preset flow rate threshold, using the MB scanning mode to collect data of the three-dimensional tissue; and when the microfluidic flow rate corresponding to the three-dimensional tissue is less than the preset flow rate threshold, using the BM scanning mode to collect data of the three-dimensional tissue.

[0011] With reference to the first aspect, the embodiments of the present application provide a sixth possible implementation manner of the first aspect, wherein the method further includes: determining the multiple data collection results corresponding to each microfluidic flow rate based on the preset scanning mode.

[0012] With reference to the first aspect, the embodiments of the present application provide a seventh possible implementation manner of the first aspect, wherein the perfusion mode includes a limited perfusion mode and a continuous perfusion mode; the limited perfusion mode includes perfusing the three-dimensional tissue according to a preset perfusion time interval; the continuous perfusion mode includes perfusing the three-dimensional tissue according to a preset perfusion cycle; the microfluidic condition includes the microfluidic flow rate and the perfusion mode; and the step of determining the microfluidic condition satisfying the comprehensive index from the microfluidic flow rates included in the evaluation result according to the pre-stored comprehensive index and the preset perfusion mode includes: determining a structural morphology of the three-dimensional tissue corresponding to each microfluidic flow rate in the evaluation result when the microfluidic flow rate is combined with the perfusion mode; judging whether the structural morphology of the three-dimensional tissue satisfies the comprehensive index; and if yes, determining the microfluidic condition corresponding to the microfluidic flow rate and the perfusion mode as the microfluidic condition satisfying the comprehensive index.

[0013] With reference to the first aspect, the embodiments of the present application provide an eighth possible implementation manner of the first aspect, wherein the pre-stored comprehensive index is determined through imaging analysis and biological analysis of the three-dimensional tissue.

[0014] In a second aspect, the embodiment of the present application further provides a micro flow field condition determination device, which comprises: a data acquisition module configured to acquire three-dimensional OCTA data corresponding to a three-dimensional tissue according to a preset scanning mode; a difference calculation module configured to calculate a complex cross-correlation difference value corresponding to the three-dimensional OCTA data based on the three-dimensional OCTA data; a condition determination module configured to obtain a previously established relationship curve, evaluate the three-dimensional tissue corresponding to the complex cross-correlation difference value according to the relationship curve, and obtain an evaluation result; wherein the relationship curve is a relationship curve of the corresponding relationship between the complex cross-correlation difference value and the micro flow field flow rate, and the evaluation result comprises a micro flow field flow rate corresponding to the three-dimensional tissue; and a screening module configured to determine a micro flow field condition satisfying a comprehensive index from the micro flow field flow rates included in the evaluation result according to the preset comprehensive index and a preset perfusion mode.

[0015] The embodiment of the present application has the following beneficial effects: The micro flow field condition determination method and device provided by the present application first acquires OCTA data of a three-dimensional tissue, determines a complex cross-correlation difference value corresponding to the three-dimensional tissue according to the data, then determines an evaluation result corresponding to the complex cross-correlation difference value from a previously established relationship curve, and the relationship curve is a curve between the micro flow field flow rate and the complex cross-correlation difference value, so that when the three-dimensional tissue is dynamically cultured, not only the structure data of the three-dimensional tissue can be obtained, but also the micro flow field distribution data corresponding to the structure data of the three-dimensional tissue can be obtained, so that the micro fluidic chip technology can be used for three-dimensional tissue culture. Then, whether the three-dimensional tissue meets the requirements is determined in combination with the comprehensive index, and the required micro flow field condition can be obtained.

[0016] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application will be realized and achieved by the structures particularly pointed out in the description, claims and drawings.

[0017] In order to make the above-mentioned objects, characteristics and advantages of the present application more obvious and easy to understand, the following preferred embodiments are specifically described below, and the accompanying drawings are described in detail as follows. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0019] Figure 1 A flow chart of a micro flow field condition determination method provided by the embodiment of the present application;

[0020] Figure 2 A flow chart of another micro flow field condition determination method provided for an embodiment of the present application is shown in FIG. 6;

[0021] Figure 3 A flow chart of another micro flow field condition determination method provided for an embodiment of the present application is shown in FIG. 6;

[0022] Figure 4 A structural schematic diagram of a micro flow field condition determination device provided for an embodiment of the present application is shown in FIG. 7;

[0023] Figure 5 A structural schematic diagram of an electronic device provided for an embodiment of the present application is shown in FIG. 8;

[0024] Figure 6 A partial structural schematic diagram of a micro fluidic system provided for an embodiment of the present application is shown in FIG. 9;

[0025] Figure 7 A relational curve schematic diagram corresponding to a BM scanning mode provided for an embodiment of the present application is shown in FIG. 10;

[0026] Figure 8 A relational curve schematic diagram corresponding to a MB scanning mode provided for an embodiment of the present application is shown in FIG. 11;

[0027] Figure 9 A complex signal result schematic diagram of a three-dimensional tissue under different micro flow field flow rates corresponding to a BM scanning mode provided for an embodiment of the present application is shown in FIG. 12;

[0028] Figure 10 A complex signal result schematic diagram of a three-dimensional tissue under different micro flow field flow rates corresponding to a MB scanning mode provided for an embodiment of the present application is shown in FIG. 13;

[0029] Figure 11 A top view structural schematic diagram of a support provided for an embodiment of the present application is shown in FIG. 14;

[0030] Figure 12 A mean value projection diagram of a three-dimensional tissue in a depth direction corresponding to different micro flow field flow rates provided for an embodiment of the present application is shown in FIG. 15;

[0031] Figure 13 A 3D distribution diagram of a three-dimensional tissue corresponding to different micro flow field flow rates provided for an embodiment of the present application is shown in FIG. 16. DETAILED DESCRIPTION

[0032] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the present application will be described below in detail with reference to the accompanying drawings. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of the present application.

[0033] Microfluidic chip technology has a wide range of applications in live cell and tissue analysis, and can simulate the key functions of the organ-bionic system. Not only does it have the advantages of miniaturization, integration and low power consumption, but it can also accurately and systematically control the parameters of the microfluidic chip operation, such as chemical concentration gradient, fluid shear stress, tissue-tissue interface, etc. Microfluidic technology can adjust the flow rate and shear force, and the geometry of the microfluidic chip affects the fluid dynamics environment of the three-dimensional tissue, which helps to achieve robust and reproducible three-dimensional tissue culture, and serves as an advanced in vitro model for studying the physiological and pathological mechanisms of the tissue.

[0034] However, the microfluidic chip technology is still in its early stages, and there are still a lot of technical problems to be solved. For example, the microchannel size and chamber of the microfluidic chip are small, and it is difficult to obtain the structural data of the three-dimensional tissue and the corresponding microfluid field distribution when three-dimensional visualization monitoring is performed. If the corresponding microfluid field distribution of the three-dimensional tissue cannot be obtained, the microfluid field condition parameters for culturing the three-dimensional tissue using the microfluidic chip technology cannot be obtained. Therefore, the current microfluidic chip technology is not suitable for culturing large-sized three-dimensional tissues.

[0035] Among them, three-dimensional cell tissues such as three-dimensional multicellular spheroids, organoids, and cell-laden scaffolds are more similar to in vivo tissues, including physiological gradient environments of oxygen, nutrients, growth factors, and metabolites. The growth of tissue cells is closely related to the flow rate of the fluid around the cells. Too low flow rate is not conducive to the entry and exit of nutrients, metabolites and oxygen into the cells in the scaffold, and cannot promote the good growth of cells. Too high flow rate will cause a large number of cell deaths in the scaffold. In summary, how to dynamically culture three-dimensional tissues in a microfluidic chip and obtain the structural data of the three-dimensional tissues and the corresponding microfluid field distribution is a major technical difficulty.

[0036] Based on this, the microfluid field condition determination method and device provided by the embodiments of the present application can obtain the structural data of the three-dimensional tissue corresponding to the three-dimensional visualization monitoring, and the microfluid field distribution, and further obtain the microfluid field condition for culturing the three-dimensional tissue.

[0037] In order to facilitate the understanding of the present embodiment, first of all, a microfluid field condition determination method disclosed by the present embodiment will be described in detail, Figure 1 a flow chart of a microfluid field condition determination method is shown, specifically, as shown in Figure 1 a flow chart of a microfluid field condition determination method, comprising the following steps:

[0038] Step S102, according to the preset scanning mode, three-dimensional OCTA data corresponding to the three-dimensional tissue is collected.

[0039] Specifically, the three-dimensional tissue is located in the microfluidic chip chamber, and the microfluidic chip chamber also corresponds to a microfluid field flow rate, that is, the three-dimensional OCTA data of the collected three-dimensional tissue is collected in the pre-set microfluid field flow rate. Under the current microfluid field flow rate, the structure of the three-dimensional tissue will present different states, and therefore the three-dimensional tissue can be collected according to the pre-set scanning mode.

[0040] In a specific implementation, the microfluidic chip has a relatively narrow flow channel, a slightly larger chamber, and a three-dimensional tissue with a small internal pore. The above characteristics are usually in micrometer units, and the overall perfusion flow rate is usually in millimeter / second units. Therefore, the microfluid field measurement technology requires high sensitivity and a wide dynamic flow rate measurement range. Therefore, based on the monitoring needs of the three-dimensional structure-microfluid field of the three-dimensional tissue dynamically cultured in the microfluidic chip, the application uses the OCTA technology of analyzing dynamic scattering signals to process the data of the three-dimensional tissue based on OCT. OCT imaging has the advantages of no labeling, non-contact, non-invasive, real-time, high sensitivity, and high resolution, which promotes the development of OCT imaging technology and OCT functional imaging technology. The OCT system mainly obtains the refractive index information of the sample by detecting the change of the backscattering light signal caused by the optical inhomogeneity of the biological sample, and then reconstructs the optical structure image of the sample. Based on the OCT technology and the dynamic scattering analysis technology, the OCTA technology can extract the microfluid field information from the static tissue and can monitor the microfluid field change in real time and non-invasively. Therefore, the three-dimensional OCTA data corresponding to the three-dimensional tissue is collected to determine the growth state of the three-dimensional tissue.

[0041] In step S104, the complex cross-correlation difference value corresponding to the three-dimensional OCTA data is calculated based on the three-dimensional OCTA data.

[0042] In a specific implementation, in order to obtain high-sensitivity data, in this embodiment, the complex cross-correlation algorithm with high sensitivity and not easy to be disturbed by phase noise is selected. That is, the three-dimensional OCTA data collected is calculated to obtain the complex cross-correlation difference value corresponding to the three-dimensional OCTA data.

[0043] In step S106, a pre-established relationship curve is obtained, and the three-dimensional tissue corresponding to the complex cross-correlation difference value is evaluated according to the relationship curve to obtain an evaluation result.

[0044] Since it is difficult to monitor the structure of the three-dimensional tissue and the distribution of the micro flow field in the microfluidic chip during dynamic culture, the embodiment of the present application pre-establishes a relationship curve of the complex cross-correlation difference and the corresponding micro flow field flow rate, the evaluation result includes the micro flow field flow rate in the relationship curve, and the relationship curve is obtained in the pre-simulated micro flow field environment, different complex cross-correlation differences and different micro flow field flow rates are calibrated with each other, therefore, the corresponding micro flow field flow rate, i.e., the distribution of the micro flow field, can be obtained according to the relationship curve and the obtained complex cross-correlation difference.

[0045] In step S108, the micro flow field condition satisfying the comprehensive index is determined from the micro flow field flow rate included in the evaluation result according to the pre-stored comprehensive index and the pre-set perfusion mode.

[0046] In order to determine the micro flow field condition suitable for culturing a three-dimensional tissue with a larger size, the pre-set perfusion mode can be combined with the micro flow field flow rate corresponding to the evaluation result, and it is determined according to the pre-stored comprehensive index that the structure of the three-dimensional tissue in the micro flow field condition corresponding to which combination mode satisfies the comprehensive index requirement, and then the target micro flow field condition is obtained.

[0047] The micro flow field condition determination method provided by the embodiment of the present application first acquires the OCTA data of the three-dimensional tissue, and then determines the corresponding complex cross-correlation difference according to the data, and then determines the evaluation result corresponding to the complex cross-correlation difference from the pre-established relationship curve, the relationship curve is the curve between the pre-calibrated micro flow field flow rate and the complex cross-correlation difference, therefore, when the three-dimensional tissue is dynamically cultured, not only the structure data of the three-dimensional tissue can be obtained, but also the micro flow field distribution data corresponding to the three-dimensional tissue can be obtained, so that the micro fluidic chip technology can be used for three-dimensional tissue culture. Then, the three-dimensional tissue is combined with the comprehensive index to determine whether the three-dimensional tissue meets the requirement, and then the required micro flow field condition can be obtained.

[0048] For the convenience of understanding, on the basis of Figure 1 , the embodiment of the present application further provides another micro flow field condition determination method, Figure 2 The flow chart of another micro flow field condition determination method is shown, and the embodiment of the method is to introduce the determination process of the pre-established relationship curve in detail.

[0049] Specifically, as Figure 2 shown in the flow chart of another micro flow field condition determination method, the method includes the following steps:

[0050] In step S202, the complex signal corresponding to the three-dimensional tissue in each micro flow field flow rate is acquired based on the pre-set multiple micro flow field flow rates and the pre-set scanning mode.

[0051] Specifically, in order to determine the structure state of the three-dimensional tissue in different microfluid field flow rates, it is necessary to first collect OCTA data corresponding to the three-dimensional tissue in different microfluid field flow rates. In a specific implementation, the OCTA data corresponding to the three-dimensional tissue in different microfluid field flow rates can be scanned based on a preset scanning mode. In order to monitor the microfluid field flow rate distribution in the microfluid channel of the microfluidic chip, a contrast agent needs to be added to the dynamic perfusion fluid, such as a culture medium, as the source of the OCTA scattering signal in the fluid. The contrast agent needs to have biocompatibility and be a micron-sized particle with a density difference of less than 5% from the dynamic perfusion fluid, such as a polystyrene particle, a polyamide particle, or a melamine resin particle.

[0052] When the size of the microfluidic platform chamber and the internal three-dimensional tissue is greater than the maximum imaging field of view of the imaging device, multi-field data acquisition and large-field splicing are needed. In order to obtain a wide dynamic flow rate measurement range, the adaptive sampling interval strategy of the BM scanning mode and the MB scanning mode is combined for data acquisition, that is, the above-mentioned preset scanning mode can include the BM scanning mode and the MB scanning mode. In the embodiment of the present application, when the microfluid field flow rate corresponding to the three-dimensional tissue is greater than the preset flow rate threshold, the MB scanning mode is used to collect data of the three-dimensional tissue; when the microfluid field flow rate corresponding to the three-dimensional tissue is less than the preset flow rate threshold, the BM scanning mode is used to collect data of the three-dimensional tissue.

[0053] In a specific implementation, the BM scanning mode can be used when the microfluid field flow rate is less than 0.5 mm / s; the MB scanning mode can be used when the microfluid field flow rate is greater than 0.5 mm / s. Specifically, in order to establish a more comprehensive relationship curve, wide range flow rate data needs to be collected. In order to realize imaging of the microfluidic chip channel, chamber and internal three-dimensional tissue, the imaging range needs to be set according to its actual size. When the microfluid field flow rate corresponding to the three-dimensional tissue is within the flow rate data of 0-5 mm / s, the BM scanning mode can be used to collect data of the three-dimensional tissue, and the field of view specific parameters are that the field of view is set to 2.5 (x) x 3.58 (z) mm, and the pixel is set to 100 (x) pixel x 1024 (z) pixel; when the microfluid field flow rate corresponding to the three-dimensional tissue is within the flow rate data of 5-600 mm / s, the MB scanning mode can be used to collect data of the three-dimensional tissue, and the field of view specific parameters are that the field of view is set to 2.5 (x) x 3.58 (z) mm, and the pixel is set to 500 (x) pixel x 1024 (z) pixel.

[0054] Further, the different micro flow field flow rates in the embodiment of the present application can be realized by the following micro fluidic system, in which the micro fluidic system includes a micro fluidic chip, a hose, a syringe pump, a syringe, a 2 ‰ polystyrene microsphere solution, and a waste liquid recovery bottle. Before perfusion, the micro fluidic system is first assembled. A 5ml syringe is used to suck 5ml of polystyrene solution. The hose is connected to the inlet of the micro fluidic chip, the outlet of the micro fluidic chip, and the waste liquid recovery bottle. After the air in the hose and the flow channel of the micro fluidic chip is pushed out, the syringe is fixed on the syringe pump. Then, the injection rate of the syringe pump is set, and the perfusion is started. Specifically, Figure 6 Part of the structure of the above-mentioned micro fluidic system is shown in the structure diagram, in which the connection structure of the micro fluidic chip, the syringe pump and the waste liquid recovery bottle is shown. The structure in the middle of the diagram is the micro fluidic chip, which is connected to the syringe pump on the left side and the waste liquid recovery bottle on the right side through the hose.

[0055] In a specific implementation, the above-mentioned micro flow field flow rate includes an initial speed and a target speed. Different acquisition data correspond to different micro flow field flow rates. The target speed is determined by gradually increasing the initial speed and a preset flow rate interval. According to the requirement of culturing three-dimensional tissues, in combination with the narrow flow channel size, the flow rate range in the narrow flow channel is usually set to 0-2mm / s by using a micro syringe pump, and the flow rate interval is 0.1mm / s. That is, the initial speed can be 0mm / s, and the preset flow rate interval can be 0.1mm / s. At this time, according to the above-mentioned two-dimensional OCTA data acquisition of each micro flow field flow rate, 21 acquisition data can be obtained. The acquisition field of view of the narrow flow channel data is usually set to 2.5mm (x) x 3.58mm (z), and the corresponding pixel number is 150pixel x 1024pixel.

[0056] When the scanning mode is the BM scanning mode, the data is acquired at a certain time interval, and N times of repeated scanning are performed for each frame of data. For example, each frame of Bscan is repeatedly acquired 10 times. Alternatively, when the scanning mode is the MB scanning mode, the data is acquired at a certain time interval, and M times of repeated scanning are performed for the data corresponding to each line of Ascan. For example, each line is repeatedly acquired 10 times to obtain multiple data corresponding to the current position, which is used to calculate more accurate data results.

[0057] Further, the two-dimensional OCTA data corresponding to the current micro flow field flow rate contains the acquisition information of the entire micro fluidic chip. Therefore, the preset scanning mode also corresponds to multiple adjacent signals. That is, the complex signal obtained by acquisition contains adjacent signals.

[0058] Step S204, based on the preset scanning mode, the complex cross-correlation value corresponding to the adjacent signal of the complex signal is calculated.

[0059] Specifically, different scanning modes can obtain different complex signals, and then different complex cross-correlation values can be calculated, for example, when the BM scanning mode is used to obtain the complex signal, the complex cross-correlation value between each adjacent frame corresponding to the complex signal can be determined; when the MB scanning mode is used to obtain the complex signal, the complex cross-correlation value between each adjacent line corresponding to the complex signal can be determined.

[0060] Specifically, when the perfusion speed of the microfluidic chip is not 0, the complex cross-correlation value is CCflow. The complex cross-correlation value corresponding to the BM scanning mode and the complex cross-correlation value corresponding to the MB scanning mode can be determined by the following calculation expression respectively:

[0061]

[0062]

[0063] Wherein, CC BM (z, x) is the complex cross-correlation value corresponding to the BM scanning mode, CC MB (z, x) is the complex cross-correlation value corresponding to the MB scanning mode; in the formula, p, q are the number of pixels in the z, x direction of the two-dimensional sliding window, is the complex signal of the nth frame of the section when the BM scanning mode is used, A n is the intensity signal of the nth frame of the section when the BM scanning mode is used; is the complex signal of the mth line of the section when the MB scanning mode is used, A m is the intensity signal of the mth line of the section when the MB scanning mode is used; * represents the complex conjugate signal, N is the repetition number of Bscan in the BM scanning mode, and M is the repetition number of Ascan in the MB scanning mode.

[0064] According to the above calculation expression, the complex cross-correlation value of the current microfluidic field flow rate corresponding to the corresponding scanning mode can be obtained.

[0065] Step S206, based on the complex cross-correlation value, determine the complex cross-correlation difference value corresponding to the complex signal.

[0066] Specifically, in order to eliminate the spectral signal noise of the liquid itself, such as the dynamic scattering noise caused by Brownian motion, the data in the unperfusion state needs to be processed to obtain the OCTA complex cross-correlation value in the unperfusion state, which is the complex cross-correlation value CCstatic when the perfusion speed of the microfluidic chip is 0.

[0067] Wherein, when the perfusion state corresponding to the above complex cross-correlation value is obtained, the complex cross-correlation difference value corresponding to the complex signal can be determined according to the complex cross-correlation value. In specific implementation, the difference value between the complex cross-correlation value corresponding to the current microfluidic flow rate and the complex cross-correlation value when the microfluidic flow rate is 0 can be determined, and the difference value is determined as the complex cross-correlation difference value CCd corresponding to the complex signal of the current microfluidic flow rate.

[0068] Step S208, the complex cross-correlation difference value of each microfluidic flow rate is polynomially fitted with the current microfluidic flow rate to obtain a relationship curve.

[0069] Specifically, after obtaining the complex cross-correlation difference value corresponding to each microfluidic flow rate, the current microfluidic flow rate and the complex cross-correlation difference value corresponding to the current microfluidic flow rate can be calibrated, and the complex cross-correlation difference values corresponding to the plurality of microfluidic flow rates using the BM scanning mode are polynomially fitted to obtain a relationship curve corresponding to the BM scanning mode, and the complex cross-correlation difference values corresponding to the plurality of microfluidic flow rates using the MB scanning mode are polynomially fitted to obtain a relationship curve corresponding to the MB scanning mode, so that according to the above relationship curve, the microfluidic flow rate corresponding to the complex cross-correlation difference value of the three-dimensional OCTA data can be obtained.

[0070] Further, in order to facilitate understanding, Figure 7 The relationship curve corresponding to the BM scanning mode is shown, Figure 8 The relationship curve corresponding to the MB scanning mode is shown. Figure 9 The complex signal result schematic diagram of three-dimensional organization under different microfluidic flow rates corresponding to the BM scanning mode is shown, Figure 10 The complex signal result schematic diagram of three-dimensional organization under different microfluidic flow rates corresponding to the MB scanning mode is shown.

[0071] As described above Figure 7 and Figure 8 As shown in the above

[0072] Another microfluidic field condition determination method provided by the embodiment of the present application acquires complex signals corresponding to different microfluidic field flow rates through a preset scanning mode, and acquires signals of repeated frames or repeated lines, and after calculation, more accurate complex cross-correlation value data can be obtained. Then, in order to eliminate the spectral signal noise of the liquid itself, the complex cross-correlation difference value corresponding to the complex cross-correlation value is determined, the complex cross-correlation difference value is calibrated with the corresponding microfluidic field flow rate, and a corresponding relationship curve corresponding to the scanning mode is fitted. Based on the relationship curve, the microfluidic field flow rate is quantitatively processed, so that when the three-dimensional structure data is dynamically cultured, the corresponding microfluidic field distribution can be determined from the relationship curve according to the calculated complex cross-correlation difference value, the three-dimensional tissue is evaluated, and the microfluidic field condition meeting the comprehensive index is obtained.

[0073] For the convenience of understanding, in Figure 1 and Figure 2 , the embodiment of the present application further provides another microfluidic field condition determination method, Figure 3 a flow chart of another microfluidic field condition determination method is shown, and the embodiment of the method is to introduce the specific steps of calculating the complex cross-correlation difference value corresponding to the three-dimensional OCTA data based on the three-dimensional OCTA data (specifically realized by steps S304-S308), and the specific steps of determining the microfluidic field condition meeting the comprehensive index from the microfluidic field flow rate included in the evaluation result according to the pre-stored comprehensive index and the preset perfusion mode (specifically realized by steps S312-316).

[0074] Specifically, as Figure 3 a flow chart of another microfluidic field condition determination method is shown, and the method comprises the following steps:

[0075] Step S302: acquiring three-dimensional OCTA data corresponding to the three-dimensional tissue according to a preset scanning mode.

[0076] In the embodiment of the present application, the step of acquiring three-dimensional tissue data is the same as the step of step S202, and the data acquisition is also performed by using the BM scanning mode or the MB scanning mode, and the three-dimensional tissue under the current microfluidic field flow rate is also collected multiple times to obtain multiple data acquisition results corresponding to the current microfluidic field flow rate.

[0077] Specifically, to obtain the low flow rate information distribution, the embodiment of the present application can use the BM scanning strategy, and each frame is repeatedly collected N times, such as 10 times or other collection times; to obtain the high flow rate information distribution, the MB scanning strategy is used, and each line is repeatedly collected M times, such as 10 times or other collection times; to simultaneously obtain the low flow rate and the high flow rate in the field of view, the BM scanning strategy is combined with the MB scanning strategy, and after each frame is repeatedly collected N times, each line is repeatedly collected M times.

[0078] In a specific implementation, the inlet flow rate of the microfluidic chip can be set to 0.3 mm / s, 0.6 mm / s or 0.9 mm / s, and since the set flow rate is not more than 5 mm / s, the BM scanning mode is used to collect three-dimensional data of the microfluidic chip chamber in the flow and static state in the embodiment of the application. Generally, the collection parameters of three-dimensional OCTA data are also determined according to the size of the microfluidic chip chamber, and the collection parameters of three-dimensional OCTA data are slightly larger than the size of the chamber, for example, when the size of the microfluidic chip chamber is 5*5 mm, the collection field of view of three-dimensional OCTA data can be set to 5 mm (x) * 5 mm (y) * 3.58 mm (z), and the pixel number is 100 pixel * 300 pixel * 1024 pixel.

[0079] In step S304, the original microflow field information corresponding to the three-dimensional tissue and the original three-dimensional structure data corresponding to the original microflow field information are obtained according to the collected three-dimensional OCTA data.

[0080] In a specific implementation, when the three-dimensional OCTA data is collected, the original data corresponding to the three-dimensional OCTA data can be directly obtained, and specifically, since the three-dimensional OCTA data is obtained in the microfluidic chip chamber, the original data can include the original microflow field information CCori and the original three-dimensional structure data Iori corresponding to the current original microflow field information.

[0081] In step S306, the original three-dimensional structure data and the original microflow field information are calculated to obtain target microflow field information and target three-dimensional tissue structure data corresponding to the target microflow field information.

[0082] In a specific implementation, considering that the three-dimensional OCTA data contains information of the three-dimensional tissue and the fluid region, the three-dimensional tissue structure Istructure and the fluid region microflow field Cflow are extracted to obtain the target microflow field information and the target three-dimensional tissue structure data corresponding to the target microflow field information.

[0083] In the embodiment of the application, the original data directly obtained when the three-dimensional OCTA data is collected is calculated to extract the target microflow field information and the target three-dimensional tissue structure data corresponding to the target microflow field information. The target microflow field information can be the fluid region microflow field information Cflow of the microfluidic chip, wherein Cflow represents a complex signal obtained by calculation when the microflow field flow rate is not 0, that is, a complex cross-correlation value; and the target three-dimensional tissue structure data can be the three-dimensional tissue structure Istructure obtained after preprocessing the collected data, that is, three-dimensional tissue structure image data.

[0084] In a specific implementation, the target micro flow field information and the target three-dimensional tissue structure data corresponding to the target micro flow field information can be determined through the following steps 11-15:

[0085] Step 11, filtering and binarization operation is performed on the original three-dimensional structure data to obtain a structure mask.

[0086] Step 12, the structure mask is multiplied with the original three-dimensional structure data to obtain the denoised micro flow field information.

[0087] In a specific implementation, filtering and binarization operation can be performed on the three-dimensional structure data Iori to obtain a structure mask Imask, and the original micro flow field information CCori and the structure mask Imask are multiplied to obtain the denoised micro flow field information CCrei. At this time, the denoised micro flow field information CCrei contains the fluid domain information corresponding to the micro flow field and the structure information of the three-dimensional tissue.

[0088] Step 13, based on the denoised micro flow field information, a denoised micro flow field information corresponding binary mask is generated.

[0089] Step 14, the binary mask is multiplied with the denoised micro flow field information to obtain the target micro flow field information.

[0090] Specifically, after obtaining the denoised micro flow field information, the denoised micro flow field information CCrei can be used to generate a binary mask Cmask, and then the CCrei is multiplied with the binary mask Cmask to obtain the target micro flow field information Cflow, that is, the fluid domain micro flow field information Cflow.

[0091] Step 15, the binary mask is inverted and multiplied with the original three-dimensional structure data to obtain the target three-dimensional tissue structure data corresponding to the target micro flow field information.

[0092] After obtaining the binary mask Cmask, the binary mask Cmask is inverted and multiplied with the original three-dimensional structure data Iori to obtain the target three-dimensional tissue structure information Istructure corresponding to the target micro flow field information.

[0093] Specifically, the target micro flow field information determined by the above steps 11-15 and the target three-dimensional tissue structure data corresponding to the target micro flow field information are preprocessed data, which can filter various external influencing factors in the original data, and thus the required information data is closer to the actual data. Among them, the required three-dimensional tissue structure information can represent the growth state of the three-dimensional tissue.

[0094] Step S308, the difference between the microfluid field information when the microfluid field flow rate is not 0 and the microfluid field information when the microfluid field flow rate is 0 is determined as the complex cross-correlation difference value corresponding to the three-dimensional OCTA data.

[0095] Specifically, the target microfluid field information includes the microfluid field information when the flow rate is 0 and the microfluid field information when the flow rate is not 0. After obtaining the target microfluid field information and the target three-dimensional tissue structure data corresponding to the target microfluid field information, in order to improve the linear relationship between the target microfluid field information CCflow result and the flow rate and reduce the influence of liquid Brownian motion on the complex cross-correlation value, the result of the microfluid field information CCflow when the flow rate is not 0 is subtracted from the result of the microfluid field information CCstatic when the flow rate is 0, and at this time, the signal difference CCd can be obtained, which is the complex cross-correlation difference value corresponding to the current microfluid field information.

[0096] Specifically, after the data is processed by using the above-mentioned complex cross-correlation algorithm, the data obtained includes the structural information of the stent and the microfluid field flow rate information of the fluid region of the microfluidic chip. The corresponding acquisition information image schematic diagram can be obtained by using the MATLAB (Matrix Laboratory) software and the Amira software, which includes the mean projection graph in the depth direction of the stent and the flow rate 3D distribution graph. In order to facilitate understanding, Figure 11 The top view structural schematic diagram of the above-mentioned stent is shown, which is arranged above the microfluidic chip, and the above-mentioned complex cross-correlation algorithm is based on the Figure 11 It is illustrated that, Figure 11 The direction of the middle finger pointing to the lower side is the z direction, and the direction of the middle finger pointing to the right side is the x direction. Further, Figure 12 And Figure 13 Both show the image data corresponding to three kinds of microfluid field flow rates of 0.3 mm / s, 0.6 mm / s and 0.9 mm / s respectively, wherein, Figure 12 The mean projection graph in the depth direction of different microfluid field flow rates corresponding to the three-dimensional tissue is shown, Figure 13 The 3D distribution graph of different microfluid field flow rates corresponding to the three-dimensional tissue is shown; wherein, Figure 12 And Figure 13 Both include three image schematic diagrams, from left to right are the images corresponding to 0.3 mm / s, 0.6 mm / s and 0.9 mm / s respectively, and the left side of each image is the inlet position of the chamber of the microfluidic chip, and the right side of the image is the outlet position of the chamber. It can be known from Figure 12 And Figure 13 It can be known that the flow rate at the inlet and outlet of the chamber of the microfluidic chip and the gap between the stent and the chamber is large, and the flow rate between the holes of the stent shows small difference and the flow rate distribution is relatively uniform.

[0097] Step S310, the pre-established relationship curve is obtained, and the three-dimensional organization corresponding to the complex cross-correlation difference value is evaluated according to the relationship curve to obtain an evaluation result.

[0098] After obtaining the complex cross-correlation difference value, the three-dimensional organization corresponding to the current three-dimensional OCTA data can be evaluated based on the pre-established relationship curve to obtain a corresponding evaluation result. At this time, since the preset scanning mode is determined, the corresponding relationship curve can be determined according to the corresponding scanning mode, and the microfluid field flow rate data corresponding to the current complex cross-correlation difference value can be determined from the corresponding relationship curve. At this time, not only the three-dimensional organization can be three-dimensionally visualized and monitored, but also the corresponding microfluid field distribution can be obtained, and then the microfluid field condition suitable for the three-dimensional organization culture can be determined.

[0099] Step S312, determining the structure and morphology of the three-dimensional organization corresponding to each microfluid field flow rate in the evaluation result when used in combination with the perfusion mode.

[0100] Further, in addition to the microfluid field flow rate for culturing the three-dimensional organization, the embodiments of the present application also relate to different perfusion modes, which are used in combination with different microfluid field flow rates, and then the best microfluid field condition for dynamically culturing the three-dimensional organization in the microfluidic chip is determined. At this time, it is necessary to establish the correlation between different perfusion modes and microfluid field flow rates and the growth index of the three-dimensional organization. Specifically, the above-mentioned perfusion mode corresponds to a perfusion period, and the three-dimensional organization is cultured in the microfluid field condition determined by the combination of different perfusion periods or perfusion modes and different microfluid field flow rates, and different three-dimensional organization morphologies can be obtained.

[0101] In a specific implementation, the dynamic culture period of the three-dimensional organization is 7-14 days, and the above-mentioned perfusion mode includes a limited perfusion mode and a continuous perfusion mode. The limited perfusion mode includes perfusing the three-dimensional organization according to a preset perfusion time interval, wherein perfusion can be performed once every 1 hour, 2 hours, 4 hours, 8 hours, or 16 hours. The continuous perfusion mode includes perfusing the three-dimensional organization according to a preset perfusion period, such as a 24h perfusion period.

[0102] Step S314, determining whether the structure and morphology of the three-dimensional organization meet the comprehensive index.

[0103] According to different microfluid field conditions, different structure and morphologies of the three-dimensional organization can be obtained, and at this time, the structure and morphology of the three-dimensional organization corresponding to the current evaluation result in combination with the perfusion mode can be determined whether it meets the comprehensive index by combining the structure and morphology of the current three-dimensional organization and the obtained evaluation result.

[0104] Specifically, the above-mentioned comprehensive index is a pre-stored index determined by imaging analysis and biological analysis of the three-dimensional organization.

[0105] In a specific implementation, the imaging analysis includes morphological analysis and cell volume analysis. The morphological analysis is performed on the three-dimensional tissue after obtaining the target three-dimensional tissue structure information Istructure. If the three-dimensional tissue is a multicellular spheroid, the spheroidicity of the spheroid can be analyzed. If the three-dimensional tissue is a cell-laden scaffold, the porosity, scaffold volume, and scaffold surface area of the cell-laden scaffold can be analyzed based on the target three-dimensional tissue structure information Istructure. If the three-dimensional tissue is an organoid, the Matrigel morphology containing the organoid can be analyzed. The cell volume analysis is an analysis method for further analyzing the cell information in the tissue. Further analysis of the three-dimensional tissue structure information, such as cell volume, is required. The processing steps include removing the interface noise of the microfluidic chip device, the hydrogel signal in the cell-laden scaffold, and the Matrigel signal in the organoid, and then obtaining the three-dimensional structure information containing only the cells. This structure information allows long-term monitoring and analysis of the cell volume Volume during the dynamic culture process. The cell volume is related to the number of cells.

[0106] The biological analysis includes microscopic observation analysis, analysis of cell metabolic activity, and detection of cell activity. In the microscopic observation analysis, the proliferation of cells in the scaffold can be observed using a bright field microscope on the 1st, 3rd, 5th, and 7th days of perfusion culture. In the analysis of cell metabolic activity, the culture medium flowing through the scaffold can be collected and stored every day. The glucose consumption and lactic acid production in the waste medium can be detected using a glucose kit and a lactic acid kit to analyze the metabolic activity of the cells. In addition, Calcein-AM and propidium iodide can be used to detect cell activity.

[0107] In step S316, if yes, the microfluidic field condition corresponding to the microfluidic field flow rate and the perfusion mode is determined as the microfluidic field condition that satisfies the comprehensive index.

[0108] When the morphology of the three-dimensional tissue satisfies the comprehensive index, the combination of the microfluidic field flow rate corresponding to the current morphology and the corresponding perfusion mode is determined as the microfluidic field condition suitable for culturing the three-dimensional tissue. That is, culturing the three-dimensional tissue according to the microfluidic field condition can make the three-dimensional tissue satisfy the pre-stored comprehensive index.

[0109] Another microfluidic flow rate determination method provided by the embodiment of the present application is to collect three-dimensional OCTA data when three-dimensional tissue is dynamically cultured, and to obtain corresponding complex signals through a complex cross-correlation algorithm. Then, the complex cross-correlation difference value of the current complex signal is determined according to the complex signal in the un-perfused state. The obtained complex signal is obtained by preprocessing the collected original data. Compared with the original data, the preprocessed data is clearer, that is, the complex cross-correlation difference value data used for evaluating the microfluidic flow rate can be obtained more accurately. After the corresponding microfluidic flow rate is obtained according to the relationship curve, the embodiment of the present application further determines whether the three-dimensional tissue in the current microfluidic field condition meets the comprehensive index in combination with different perfusion cycles or perfusion modes. The combination form of the perfusion mode and the microfluidic flow rate is various. Therefore, the best perfusion mode and microfluidic flow rate can be accurately obtained to guide the microfluidic chip design of the microfluidic field condition conducive to the growth of three-dimensional tissue.

[0110] Corresponding to the above method embodiment, the embodiment of the present application also provides a microfluidic flow rate determination device. FIG. 4 shows a structural schematic diagram of a microfluidic flow rate determination device. As shown in FIG. 4, the device includes:

[0111] The data acquisition module 401 is configured to collect three-dimensional OCTA data corresponding to the three-dimensional tissue according to a preset scanning mode.

[0112] The difference calculation module 402 is configured to calculate the complex cross-correlation difference value corresponding to the three-dimensional OCTA data based on the three-dimensional OCTA data.

[0113] The condition determination module 403 is configured to obtain a pre-established relationship curve, evaluate the three-dimensional tissue corresponding to the complex cross-correlation difference value according to the relationship curve, and obtain an evaluation result. The relationship curve is a relationship curve of the pre-calibrated corresponding relationship between the complex cross-correlation difference value and the microfluidic flow rate. The evaluation result includes the microfluidic flow rate corresponding to the three-dimensional tissue.

[0114] The screening module 404 is configured to determine the microfluidic field condition meeting the comprehensive index from the microfluidic flow rate included in the evaluation result according to the pre-stored comprehensive index and the preset perfusion mode.

[0115] Further, the difference calculation module 402 is further configured to obtain original microflow field information corresponding to the three-dimensional tissue and original three-dimensional structure data corresponding to the original microflow field information according to the collected three-dimensional OCTA data; calculate the original three-dimensional structure data and the original microflow field information to obtain target microflow field information and target three-dimensional tissue structure data corresponding to the target microflow field information; wherein the target microflow field information includes microflow field information when the microflow field flow rate is 0 and microflow field information when the microflow field flow rate is not 0; and determine a difference between the microflow field information when the microflow field flow rate is not 0 and the microflow field information when the microflow field flow rate is 0 as a complex cross-correlation difference value corresponding to the three-dimensional OCTA data.

[0116] The difference calculation module 402 is further configured to perform filtering and binarization operations on the original three-dimensional structure data to obtain a structure mask; perform point multiplication processing on the structure mask and the original three-dimensional structure data to obtain denoised microflow field information; generate a binarization mask corresponding to the denoised microflow field information based on the denoised microflow field information; perform point multiplication processing on the binarization mask and the denoised microflow field information to obtain the target microflow field information; take the binarization mask as a complement and perform point multiplication on the original three-dimensional structure data to obtain the target three-dimensional tissue structure data corresponding to the target microflow field information.

[0117] Further, the device further includes a curve determination module configured to collect a complex signal corresponding to a three-dimensional tissue in each microflow field flow rate based on a plurality of preset microflow field flow rates and a preset scanning mode; wherein the complex signal includes adjacent signals; calculate a complex cross-correlation value corresponding to the adjacent signals of the complex signal based on the preset scanning mode; determine a complex cross-correlation difference value corresponding to the complex signal based on the complex cross-correlation value; and perform polynomial fitting on the complex cross-correlation difference value of each microflow field flow rate and the current microflow field flow rate to obtain a relationship curve.

[0118] The curve determination module is further configured to determine a difference between the complex cross-correlation value of the current complex signal and a complex cross-correlation value when the microflow field flow rate is 0 based on the microflow field flow rate corresponding to the complex signal to obtain the complex cross-correlation difference value corresponding to the complex signal.

[0119] Further, the device further includes an acquisition module configured to perform data acquisition on a three-dimensional tissue by using an MB scanning mode when a microflow field flow rate corresponding to the three-dimensional tissue is greater than a preset flow rate threshold; and perform data acquisition on the three-dimensional tissue by using a BM scanning mode when the microflow field flow rate corresponding to the three-dimensional tissue is less than the preset flow rate threshold. The acquisition module is further configured to determine a plurality of data acquisition results corresponding to each microflow field flow rate based on the preset scanning mode.

[0120] The aforementioned screening module 404 is also used to determine the structural morphology of the three-dimensional tissue corresponding to each microfluidic velocity and irrigation method in the evaluation results; to determine whether the structural morphology of the three-dimensional tissue meets the comprehensive index; if so, to determine the microfluidic field conditions corresponding to the microfluidic velocity and irrigation method as microfluidic field conditions that meet the comprehensive index, wherein the pre-stored comprehensive index is determined through imaging analysis and biological analysis of the three-dimensional tissue.

[0121] The micro-flow field velocity determination device provided in this embodiment of the invention has the same technical features as the micro-flow field velocity determination method provided in the above embodiments, so it can also solve the same technical problems and achieve the same technical effects.

[0122] This invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described... Figures 1 to 3 The steps of any of the methods shown. Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the above-described steps. Figures 1 to 3 The steps of any of the methods shown.

[0123] This invention also provides a schematic diagram of the structure of an electronic device, such as... Figure 5 The diagram shows the structure of the electronic device, which includes a processor 51 and a memory 50. The memory 50 stores computer-executable instructions that can be executed by the processor 51. The processor 51 executes the computer-executable instructions to implement the above-mentioned... Figures 1 to 3 Any of the methods shown. In Figure 5 In the illustrated embodiment, the electronic device further includes a bus 52 and a communication interface 53, wherein the processor 51, the communication interface 53, and the memory 50 are connected via the bus 52.

[0124] The memory 50 can include a high-speed random access memory (RAM) and can also include a non-volatile memory such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 53 (which can be wired or wireless), and the Internet, a wide area network, a local area network, a metropolitan area network, etc. can be used. The bus 52 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc., and can also be an AMBA (Advanced Microcontroller Bus Architecture) bus, in which AMBA defines three types of buses, including an APB (Advanced Peripheral Bus) bus, an AHB (Advanced High-performance Bus) bus, and an AXI (Advanced eXtensible Interface) bus. The bus 52 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one bidirectional arrow is used to represent the bus in the figure, but it does not mean that there is only one bus or only one type of bus.

[0125] The processor 51 can be an integrated circuit chip with processing capability. In the implementation process, each step of the above method can be completed by the integrated logic circuit of hardware in the processor 51 or the instruction in the form of software. The processor 51 described above can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register, etc. The storage medium in the storage is read by the processor 51, and the hardware thereof is combined to complete the foregoing Figures 1 to 3 any of the methods described.

[0126] The computer program product of the micro flow field flow rate determination method and device provided by the embodiment of the present application includes a computer readable storage medium storing program codes, the instructions included in the program codes can be used to execute the method described in the foregoing method embodiment, and the specific implementation can be referred to the method embodiment, which will not be described here. Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the foregoing method embodiment, which will not be described here.

[0127] In addition, in the description of the embodiment of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connecting" should be understood in a broad sense, for example, can be fixedly connected, can also be detachably connected, or integrally connected; can be mechanically connected, can also be electrically connected; can be directly connected, can also be indirectly connected through an intermediate medium, can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0128] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of software products. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0129] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", "third" are only for the purpose of description, and cannot be understood as indicating or implying relative importance.

[0130] Finally, it should be noted that: the above embodiments are only specific embodiments of the present application, which are used to illustrate the technical solutions of the present application, and are not limited thereto, the protection scope of the present application is not limited thereto, although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art within the technical range disclosed by the present application can modify or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications, changes or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for determining microfluidic field conditions, characterized by, The method comprises: According to a preset scanning mode, three-dimensional OCTA data corresponding to a three-dimensional tissue is collected; Based on the three-dimensional OCTA data, a complex cross-correlation difference value corresponding to the three-dimensional OCTA data is calculated; A pre-established relationship curve is obtained, and the three-dimensional tissue corresponding to the complex cross-correlation difference value is evaluated according to the relationship curve to obtain an evaluation result; wherein the relationship curve is a relationship curve of the corresponding relationship between the pre-calibrated complex cross-correlation difference value and the microflow field flow rate, and the evaluation result includes the microflow field flow rate corresponding to the three-dimensional tissue; According to a pre-stored comprehensive index and a preset perfusion mode, a microflow field condition satisfying the comprehensive index is determined from the microflow field flow rate included in the evaluation result; The perfusion mode includes a limited perfusion mode and a continuous perfusion mode; the limited perfusion mode includes perfusing the three-dimensional tissue according to a preset perfusion time interval; and the continuous perfusion mode includes perfusing the three-dimensional tissue according to a preset perfusion cycle; The microflow field condition includes a microflow field flow rate and a perfusion mode; The step of determining, according to a pre-stored comprehensive index and a preset perfusion mode, a microflow field condition satisfying the comprehensive index from the microflow field flow rate included in the evaluation result, comprises: Determine the structure morphology of the three-dimensional tissue corresponding to the combination of the microflow field flow rate in the evaluation result and the perfusion mode; Determine whether the structure morphology of the three-dimensional tissue satisfies the comprehensive index; If yes, the microflow field condition corresponding to the microflow field flow rate and the perfusion mode that satisfies the comprehensive index is determined as the microflow field condition satisfying the comprehensive index.

2. The method of claim 1, wherein, The step of calculating, based on the three-dimensional OCTA data, a complex cross-correlation difference value corresponding to the three-dimensional OCTA data, comprises: According to the collected three-dimensional OCTA data, obtain the original microflow field information corresponding to the three-dimensional tissue and the original three-dimensional structure data corresponding to the original microflow field information; Calculate the original three-dimensional structure data and the original microflow field information to obtain target microflow field information and target three-dimensional tissue structure data corresponding to the target microflow field information; wherein the target microflow field information includes microflow field information when the microflow field flow rate is 0 and microflow field information when the microflow field flow rate is not 0; The difference between the complex cross-correlation value corresponding to the microflow field information when the microflow field flow rate is not 0 and the complex cross-correlation value corresponding to the microflow field information when the microflow field flow rate is 0 is determined as the complex cross-correlation difference value corresponding to the three-dimensional OCTA data.

3. The method of claim 2, wherein, The step of calculating the original three-dimensional structure data and the original microflow field information to obtain target microflow field information and target three-dimensional tissue structure data corresponding to the target microflow field information, comprises: Filtering and binarization operation is performed on the original three-dimensional structure data to obtain a structure mask; Point multiplication processing is performed on the structure mask and the original microflow field information to obtain denoised microflow field information; the denoised microflow field information includes fluid domain information corresponding to the microflow field and structure information of the three-dimensional tissue; generating a binary mask corresponding to the denoised micro flow field information based on the denoised micro flow field information; performing point multiplication processing on the binary mask and the denoised micro flow field information to obtain target micro flow field information; performing point multiplication processing on the binary mask and the denoised micro flow field information to obtain target micro flow field information; 4. The method of claim 1, wherein, The method further comprises: Based on the preset multiple micro flow field flow rates and the preset scanning mode, the complex signal corresponding to the three-dimensional tissue in each micro flow field flow rate is collected; wherein the complex signal contains adjacent signals; the preset multiple micro flow field flow rates include an initial speed and multiple target speeds, and each target speed is determined by gradually increasing the initial speed and a preset flow rate interval; Based on the preset scanning mode, the complex cross-correlation value corresponding to the adjacent signals of the complex signal is calculated; Based on the complex cross-correlation value, the complex cross-correlation difference value corresponding to the complex signal is determined; The complex cross-correlation difference value of each micro flow field flow rate is fitted with the current micro flow field flow rate to obtain the relationship curve.

5. The method of claim 4, wherein, The complex cross-correlation value includes a complex cross-correlation value when the micro flow field flow rate is 0 and a complex cross-correlation value when the micro flow field flow rate is not 0; The step of determining the complex cross-correlation difference value corresponding to the complex signal based on the complex cross-correlation value comprises: Based on the micro flow field flow rate corresponding to the complex signal, the difference between the complex cross-correlation value of the current complex signal and the complex cross-correlation value when the micro flow field flow rate is 0 is determined to obtain the complex cross-correlation difference value corresponding to the complex signal.

6. The method according to claim 1 or 4, characterized in that, The preset scanning mode includes a BM scanning mode and an MB scanning mode; the three-dimensional tissue corresponds to a micro flow field flow rate; the method further comprises: When the micro flow field flow rate corresponding to the three-dimensional tissue is greater than a preset flow rate threshold, the MB scanning mode is used to collect data of the three-dimensional tissue; When the micro flow field flow rate corresponding to the three-dimensional tissue is less than a preset flow rate threshold, the BM scanning mode is used to collect data of the three-dimensional tissue.

7. The method of claim 6, wherein, The method further comprises: Based on the preset scanning mode, the multiple data collection results corresponding to each micro flow field flow rate are determined.

8. The method of claim 1, wherein, The pre-stored comprehensive index is determined through imaging analysis and biological analysis of the three-dimensional tissue.

9. A microfluidic field condition determining apparatus, characterized by, The device comprises: A data collection module for collecting three-dimensional OCTA data corresponding to a three-dimensional tissue according to a preset scanning mode; A difference calculation module for calculating a complex cross-correlation difference value corresponding to the three-dimensional OCTA data based on the three-dimensional OCTA data; A condition determination module for obtaining a relationship curve, evaluating the three-dimensional tissue corresponding to the complex cross-correlation difference value according to the relationship curve, and obtaining an evaluation result; wherein the relationship curve is a relationship curve of the pre-calibrated corresponding relationship between the complex cross-correlation difference value and the micro flow field flow rate, and the evaluation result includes the micro flow field flow rate corresponding to the three-dimensional tissue. The screening module is configured to determine a microfluidic field condition satisfying the comprehensive index from the microfluidic field flow rate included in the evaluation result according to a pre-stored comprehensive index and a pre-set perfusion mode. The perfusion mode includes a finite perfusion mode and a continuous perfusion mode; the finite perfusion mode includes perfusing the three-dimensional tissue according to a pre-set perfusion time interval; and the continuous perfusion mode includes perfusing the three-dimensional tissue according to a pre-set perfusion cycle. The microfluidic field condition includes a microfluidic field flow rate and a perfusion mode. The screening module is further configured to determine a structure morphology of the three-dimensional tissue corresponding to the microfluidic field flow rate and the perfusion mode in the evaluation result, to judge whether the structure morphology of the three-dimensional tissue satisfies the comprehensive index, and to determine the microfluidic field condition corresponding to the microfluidic field flow rate and the perfusion mode as the microfluidic field condition satisfying the comprehensive index if the structure morphology of the three-dimensional tissue satisfies the comprehensive index.

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