Acupoint stimulation monitoring device and monitoring method based on multi-frequency thermoacoustic imaging technology

Abstract

The application claims a kind of acupoint stimulation monitoring device and monitoring method based on multi-frequency thermoacoustic imaging technology, it is related to the field of microwave thermoacoustic imaging.It includes microwave excitation module, acupoint stimulation module, data acquisition module and stimulation visualization module.Microwave excitation module is used to stimulate the monitoring target to generate thermoacoustic signal, acupoint stimulation module is used to stimulate one or more acupoints of monitoring target, data acquisition module is used to detect thermoacoustic signal and store, stimulation visualization module includes real-time monitoring submodule and data post-processing submodule, respectively used for qualitative image real-time reconstruction and quantitative significance and correlation calculation of collected data.The application proposes a kind of acupoint stimulation monitoring device and monitoring method based on multi-frequency thermoacoustic imaging technology, which is expected to provide a new way of thinking for acupuncture mechanism research from the perspective of dielectric properties.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of microwave thermoacoustic imaging and the field of traditional Chinese medicine research, and particularly relates to a multi-frequency microwave thermoacoustic imaging acupoint monitoring device and a monitoring method. BACKGROUND

[0002] Acupoint stimulation, as an important method in traditional Chinese medicine treatment, was first recorded in Huangdi Neijing and has a history of more than 2000 years. Acupoint stimulation mainly refers to stimulating acupoints by means of acupuncture, moxibustion, acupoint injection, acupoint catgut embedding, blood-letting and cupping, etc. to regulate the nervous system and achieve therapeutic effect. It has become one of the most common complementary and alternative therapies in the world, and its efficacy has been affirmed. However, the specific mechanism of acupoint stimulation is still largely unknown. Exploring the mechanism of acupoint stimulation provides a modern scientific explanation and verification for traditional Chinese medicine therapy, and reveals its deep mechanism, which is of great significance for promoting the application and development of traditional Chinese medicine in the global medical field.

[0003] With the development of non-invasive medical imaging technology, people can explore the mechanism of acupoint stimulation more deeply. At present, Positron Emission Computed Tomography (PET), functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG) and Photoacoustic Imaging (PAI) are widely used in the exploration of acupoint stimulation mechanism. Although these examination methods have their own advantages, there are also some shortcomings, for example: PET can reflect the activity of neural cells in a specific brain region by recording the glucose metabolism and blood perfusion parameters in the brain, but it needs to inject radioisotopes as contrast agents, which poses a risk of ionizing radiation to patients; fMRI can monitor the paramagnetic properties of oxygenated hemoglobin and deoxygenated hemoglobin without the help of exogenous contrast agents, and can observe the changes of brain blood flow associated with neural activity in a specific region, and can achieve sub-millimeter spatial resolution, but the imaging speed of fMRI is slow, and it is difficult to achieve rapid real-time monitoring; EEG can directly detect millisecond-level neuronal discharge activity, and is the most direct means of studying neural electrical activity in clinical research, but EEG has the disadvantage of low spatial resolution; PAI is also used to monitor the hemoglobin content and blood oxygen level under acupoint stimulation due to the high absorption of hemoglobin to light in a specific wavelength range. However, the penetration depth of light in tissue limits the use of PAI in brain imaging research mainly to small animal studies. In summary, there is currently a lack of a new biomedical imaging tool that is free of ionizing radiation risk, has high spatial and temporal resolution, and has deep imaging depth for the exploration of acupoint stimulation mechanism.

[0004] As a new non-invasive medical imaging technology, microwave-induced thermoacoustic imaging (MITAI) combines the high contrast and deep penetration of microwave imaging (MWI) with the high resolution of ultrasound imaging (US), and can reflect the structural information of the tissue while reflecting the microwave dielectric function absorption. In MITAI, the biological tissue produces thermal expansion and radiates ultrasonic waves outward after absorbing the microwave short pulse energy. In recent years, MITAI has made outstanding progress in the application fields of breast imaging, joint imaging, liver imaging and brain imaging, among which the research in the field of brain imaging mainly focuses on brain structure imaging and brain hemorrhage detection, and has not involved the research on brain activity monitoring when the body is stimulated by external stimulation. After the acupoint is stimulated by external stimulation, the neural activity in the brain functional area will change, thereby causing the change of the dielectric properties of the tissue. Based on this, the microwave-induced thermoacoustic imaging technology is expected to become a new non-invasive biomedical imaging tool for acupoint stimulation monitoring. SUMMARY

[0005] The present application aims to solve the problems of the prior art. An acupoint stimulation monitoring device and method based on multi-frequency thermoacoustic imaging technology are proposed. The technical solution of the present application is as follows:

[0006] An acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology comprises:

[0007] A microwave excitation module, an acupoint stimulation module, a data acquisition module and a stimulation visualization module, wherein

[0008] The microwave excitation module comprises a computer, a frequency-adjustable microwave source, a T-shaped waveguide and a wideband antenna connected in sequence. The computer controls the frequency-adjustable microwave source to generate pulsed microwaves with rapidly switchable frequencies. The pulsed microwaves are divided into two paths via the T-shaped waveguide and are radiated to the monitoring target including brain tissue and visceral tissue by a pair of identical wideband antennas. The tissue absorbs microwave energy to generate ultrasonic waves, i.e. thermoacoustic signals;

[0009] The acupoint stimulation module comprises a monitoring target and an acupoint stimulation module;

[0010] The data acquisition module comprises an array ultrasonic transducer, a multi-channel amplifier and a multi-channel data acquisition card. The array ultrasonic transducer is used to quickly detect the thermoacoustic signals and convert them into electrical signals. The multi-channel amplifier amplifies the electrical signals output by the array ultrasonic transducer in phase and outputs them to the multi-channel data acquisition card. The multi-channel data acquisition card collects and stores the electrical signals amplified by the multi-channel amplifier into the computer;

[0011] The stimulation visualization module comprises a computer, a real-time monitoring submodule and a data post-processing submodule, in the computer, the electrical signals collected by a multi-channel data acquisition card are subjected to image reconstruction and analysis, that is, the data are subjected to qualitative and quantitative expression through the real-time monitoring submodule and the data post-processing submodule; the real-time monitoring submodule comprises an image reconstruction algorithm module, an image registration algorithm module and an image difference algorithm module, wherein the image reconstruction algorithm module is used for real-time display of brain function thermosonic images and organ thermosonic images, the image registration algorithm module is used for extraction of brain function area and organ tissue boundaries, and the image difference algorithm module is used for qualitative description of intensity changes of the brain function thermosonic images and the organ thermosonic images; the data post-processing submodule comprises a saliency algorithm module and a correlation algorithm module, wherein the saliency algorithm module is used for measurement of changes of brain function area and organ thermosonic signals with time, and the correlation algorithm module is used for quantitative calculation of correlations between thermosonic signals of different brain function areas, between brain function area and organ thermosonic signals, and between thermosonic signals of the same brain function area and organ under microwave excitation of different frequencies when the acupoint is stimulated.

[0012] Further, the frequency adjustable in the frequency adjustable microwave source means that the microwave center frequency is rapidly switched within 0.4 GHz-10 GHz, and it is required to ensure that other parameters of the microwave source including pulse width, pulse power and pulse repetition frequency remain unchanged during the monitoring experiment; the wideband antenna is a wideband antenna sufficient to cover the frequency range of 0.4 GHz-10 GHz.

[0013] Further, the array ultrasonic transducer is a concave array ultrasonic transducer or a linear array ultrasonic transducer; the array ultrasonic transducer completes detection of the thermosonic signals in cooperation with an ultrasonic coupling medium, and the ultrasonic coupling medium is used for excluding air between the array ultrasonic transducer and the monitoring target, so that the thermosonic signals can be detected by the array ultrasonic transducer with minimum attenuation.

[0014] Further, the ultrasonic coupling medium refers to a medium capable of reducing attenuation of the thermosonic signals at the tissue surface, including a medical ultrasonic coupling agent, paraffin oil and a low-conductivity ultrasonic coupling pad.

[0015] Further, the real-time monitoring submodule is used for reflecting changes of the brain function area and the organ thermosonic signals during the acupoint stimulation in real time; specifically, the thermosonic signals are subjected to image reconstruction, image registration and image difference in sequence in combination with the image reconstruction algorithm module, the image registration algorithm module and the image difference algorithm module, the monitoring target is determined, whether the brain function area and the organ thermosonic signals change is determined, and the strength of the change is qualitatively determined; wherein,

[0016] The image reconstruction algorithm module is used for thermosonic image reconstruction of the brain function area and the organ according to the relationship between the time domain information and the spatial position of the thermosonic signals by using a delay and superposition algorithm.

[0017] The image registration algorithm module automatically reads the coordinate information of different brain function areas in the brain function localization atlas and the boundary coordinates of organs in the anatomical atlas, and scales according to the appropriate scale to register the brain tissue thermosound image and the organ thermosound image reconstructed by the image reconstruction module, and sets the thermosound signal outside the brain function area or the organ area in the registered image to 0.

[0018] The image difference algorithm module is obtained by subtracting the registered brain function image and organ image obtained at the initial monitoring time from the registered brain function image and organ image obtained at the monitoring time, that is:

[0019] ΔP = P x -P0

[0020] (x = 0min, 3min, 6min, …, 60min)

[0021] Wherein, P0 represents the image matrix of the brain function area or the organ after registration at the initial time, P x represents the image matrix of the brain function area or the organ after registration at x time, and ΔP represents the difference image matrix obtained at x time.

[0022] Further, the image reconstruction algorithm module is to reconstruct the thermosound image of the brain function area and the organ according to the relationship between the time domain information and the spatial position of the thermosound signal by using the delay and superposition algorithm, which specifically includes:

[0023] The delay and superposition algorithm takes the position of each crystal of the array ultrasonic transducer as the center, reversely projects the thermosound signal detected by each crystal to the imaging area for image reconstruction, and the signal amplitude of any point in the reconstructed image is the superposition of the thermosound signal amplitude detected by each crystal.

[0024] Further, the data post-processing sub-module is used for quantitative determination of the influence of acupoint stimulation on brain function area and organ; the quantitative determination rule of the strength and correlation of the change of the monitoring target including the thermosound signal of the internal organ and the brain function area caused by acupoint stimulation is: using the significance algorithm module to calculate the significance of the thermosound signal of the brain function area and the organ with the same frequency microwave excitation changing with time, using the correlation algorithm module to calculate the change correlation between the thermosound signals of different brain function areas under the same frequency microwave excitation, between the thermosound signals of the brain function area and the organ under the same frequency microwave excitation, and between the thermosound signals of the same brain function area under different frequency microwave excitations, and between the thermosound signals of the organ under different frequency microwave excitations.

[0025] Further, the significance algorithm module extracts the pixels of different brain function areas or organs in each difference image to represent the intensity of thermoacoustic signals, and calculates the significance of the thermoacoustic signals of brain function areas and organs over time through variance analysis.

[0026] The correlation algorithm module calculates the mean of pixels of different brain function areas or organs in each difference image to represent the intensity of thermoacoustic signals, and calculates the Pearson correlation coefficient or Spearman correlation coefficient between the thermoacoustic signals of different brain function areas under the same frequency microwave excitation, between the thermoacoustic signals of brain function areas and organs under the same frequency microwave excitation, and between the thermoacoustic signals of the same brain function area under different frequency microwave excitations and between the thermoacoustic signals of organs under different frequency microwave excitations.

[0027] An acupoint monitoring method based on any of the systems, comprising the following steps:

[0028] S1, turn on the device, determine the order of each excitation frequency point of the microwave source, and other system working parameters, determine the total number of monitoring and each monitoring time point, and the monitoring time interval is greater than the time required for a complete multi-frequency microwave excitation;

[0029] S2, fix the imaging site, and the array ultrasonic transducer is fully coupled with the imaging site through the ultrasonic coupling medium;

[0030] S3, timing, the computer triggers a single-frequency microwave pulse to excite the monitoring target, and the thermoacoustic signals are detected, collected and stored, and the computer displays the brain function thermoacoustic image and the organ thermoacoustic image and the corresponding difference thermoacoustic image under the single-frequency microwave excitation pulse in real time;

[0031] S4, judge whether the multi-frequency point microwave excitation is completed, if not, quickly switch to the next microwave excitation point, repeat S3-S4, if yes, proceed to S5;

[0032] S5, judge whether the total number of monitoring is met, if not, execute S6, if yes, execute S8;

[0033] S6, initialize the excitation frequency point of the microwave source, and maintain other experimental conditions unchanged, judge whether to start or continue acupoint stimulation, if not, proceed to S3-S4 at the monitoring time point, if yes, proceed to S7;

[0034] S7, start acupoint stimulation or continue acupoint stimulation at the nearest monitoring time point, and proceed to S3-S4 at each monitoring time point;

[0035] S8, stop monitoring, and perform data post-processing on the data obtained during the monitoring, i.e., perform significance and correlation analysis;

[0036] S9, output the monitoring results.

[0037] The advantages and beneficial effects of the present application are as follows:

[0038] 1. Compared with the existing medical imaging technology for acupoint stimulation monitoring, the microwave thermoacoustic imaging technology in the present application has the advantages of non-invasive, real-time imaging, deep penetration, high resolution, and the ability to reflect the internal structure characteristics and dielectric function characteristics of the measured tissue. The acupoint stimulation module links acupoints and monitoring targets including brain functional areas and organs. According to the specific implementation steps, the continuous and immediate monitoring of the thermoacoustic signal changes of brain functional areas and organs can be realized, and the mechanism of acupoint stimulation can be analyzed from the perspective of dielectric properties.

[0039] 2. From the qualitative perspective, the method and the improvement of the microwave thermoacoustic imaging system can monitor the changes of the thermoacoustic signal of the monitoring target including brain functional areas and organs over time under acupoint stimulation in real time through the real-time monitoring sub-module integrated with the image reconstruction algorithm module, the image registration algorithm module and the image difference algorithm module, realizing the visualization of the whole monitoring process, and thus evaluating the influence of acupoint stimulation in real time. From the quantitative perspective, through the data post-processing sub-module integrated with the saliency algorithm module and the correlation algorithm module, the thermoacoustic data can be post-processed, and the effect of acupoint stimulation on the monitoring target can be quantitatively analyzed from the perspective of dielectric properties.

[0040] 3. The acupoint monitoring method of the multi-frequency microwave thermoacoustic imaging device proposed in the present application can quickly switch different frequencies of microwaves through the microwave excitation module, so as to quickly obtain multiple sets of single-frequency thermoacoustic difference images. The correlation analysis of the thermoacoustic signals between brain functional areas and between brain functional areas and organ tissues can be performed through the data post-processing sub-module on each set of single-frequency thermoacoustic difference images. The correlation analysis of the thermoacoustic signals under different frequency microwave excitation can also be performed on brain functional areas or organ tissues. Thus, the frequency spectrum dependence of the dielectric properties of biological tissues is fully utilized.

[0041] 4. Compared with the existing photoacoustic imaging technology, the same ultrasonic transducer can be used to receive thermoacoustic signals and photoacoustic signals in the present application, and the obtained thermoacoustic images and photoacoustic images are naturally registered. Therefore, an independent laser source and an optical fiber can be added to form a dual-mode acupoint stimulation monitoring device based on the present application. The dielectric function characteristics of microwave thermoacoustic imaging and the hemodynamic parameters of photoacoustic imaging are complementary to each other, realizing more accurate monitoring visualization effect and mechanism analysis. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 is a structural schematic diagram of the multi-frequency microwave thermoacoustic imaging technology acupoint stimulation monitoring device provided by the present application;

[0043] Figure 2This is a flowchart illustrating the visualization of acupoint stimulation according to an embodiment of the present invention;

[0044] Figure 3 This is a flowchart illustrating an embodiment of the present invention applicable to a multi-frequency microwave thermoacoustic imaging method for monitoring and visualizing acupoint stimulation. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and thoroughly described below with reference to the accompanying drawings. The described embodiments are merely some embodiments of the present invention.

[0046] The technical solution of the present invention to solve the above-mentioned technical problems is:

[0047] like Figure 1 As shown, this embodiment provides an acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology, including: a microwave excitation module, an acupoint stimulation module, a data acquisition module, and a stimulation visualization module. The microwave excitation module includes a computer, a frequency-adjustable microwave source, a T-shaped waveguide, and a pair of broadband antennas connected in sequence, used to radiate the generated multi-frequency pulsed microwaves to the monitoring target, including brain tissue and organ tissue. The acupoint stimulation module includes the monitoring target and acupoint stimulation. The monitoring target includes brain tissue and organ tissue, absorbing microwave energy to generate thermoacoustic signals, and the acupoints are stimulated by methods including but not limited to acupuncture, moxibustion, acupoint injection, acupoint embedding, bloodletting, and cupping. The data acquisition module includes an array ultrasonic transducer, a multi-channel amplifier, and a multi-channel data acquisition card connected in sequence, used to detect and store the thermoacoustic signals generated by the monitoring target brain tissue and corresponding organ tissue. The stimulation visualization module includes a computer, a real-time monitoring submodule, and a data post-processing submodule. It is used to reconstruct brain function thermoacoustic images, organ thermoacoustic images, and corresponding thermoacoustic differential images in real time during acupoint monitoring, and to perform significance and correlation analysis on the obtained thermoacoustic data after the acupoint monitoring ends.

[0048] Specifically, the real-time monitoring submodule includes an image reconstruction algorithm for real-time display of brain functional thermoacoustic images and organ thermoacoustic images, an image registration algorithm for extracting the boundaries of brain functional areas and organ tissues, and an image differencing algorithm for qualitatively describing the intensity changes of brain functional thermoacoustic images and organ thermoacoustic images. The data post-processing submodule includes an algorithm module for quantifying the significance of changes in brain functional area and organ thermoacoustic signals over time, and an algorithm module for quantitatively calculating the correlation between thermoacoustic signals of different brain functional areas, between brain functional areas and organ thermoacoustic signals under microwave excitation of the same frequency during acupoint stimulation, and between thermoacoustic signals of the same brain functional area and organ under microwave excitation of different frequencies.

[0049] On the basis of the above embodiment, the frequency adjustable in the frequency adjustable microwave source means that the microwave center frequency can be quickly switched within 0.4GHz-10GHz, and the other parameters of the microwave source including pulse width, pulse power and pulse repetition frequency need to be kept unchanged during the monitoring experiment. The wideband antenna is a wideband antenna sufficient to cover the frequency range of 0.4GHz-10GHz. Among them, the frequency adjustable microwave source combined with the T-shaped waveguide output two-way microwave can also be replaced by two frequency adjustable microwave sources with the same parameters.

[0050] Further, based on the law that the theoretical microwave absorption coefficient between biological tissues changes with the microwave frequency, different brain function areas or organ tissues respond differently to microwaves of different frequencies; therefore, the frequency adjustable microwave source generates pulsed microwaves of multiple frequencies, and for different brain function areas or organ tissues, multiple microwave frequencies are set in advance for excitation, and the monitoring target is excited in turn through the wideband antenna during the experiment, and the generated thermoacoustic signals are collected by the data acquisition module in turn.

[0051] On the basis of the above embodiment, the array ultrasonic transducer is a concave array ultrasonic transducer or a linear array ultrasonic transducer. The array ultrasonic transducer completes the detection of the thermoacoustic signal in cooperation with the ultrasonic coupling medium, which can eliminate the air between the array ultrasonic transducer and the monitoring target, so that the thermoacoustic signal can be effectively detected by the array ultrasonic transducer and converted into an electric signal with the maximum coupling degree.

[0052] Specifically, the ultrasonic coupling medium refers to a medium capable of reducing the attenuation of the thermoacoustic signal at the tissue surface, including medical ultrasonic coupling agent, paraffin oil and low-conductivity ultrasonic coupling pad. During the monitoring experiment, the array ultrasonic transducer can be immersed in a polyethylene film filled with paraffin oil, and a small amount of medical ultrasonic coupling agent can be uniformly applied on the surface of the tissue; or a low-conductivity ultrasonic coupling pad can be embedded between the array ultrasonic transducer and the monitoring target instead.

[0053] On the basis of the above embodiment, the real-time monitoring sub-module can reflect the changes of the thermoacoustic signals of the brain function areas and the organs during the acupoint stimulation process in real time. That is, the thermoacoustic signals are sequentially subjected to image reconstruction, image registration and image difference by combining the image reconstruction algorithm, the image registration algorithm and the image difference algorithm, to determine whether the thermoacoustic signals of the monitoring target, including the brain function areas and the organs, have changed, and to qualitatively judge the strength of the change.

[0054] Specifically, the image reconstruction algorithm can reconstruct the thermoacoustic images of the brain function areas and the organs according to the relationship between the time domain information and the spatial position of the thermoacoustic signals by using the delay-and-sum algorithm.

[0055] Specifically, the image registration algorithm automatically reads the coordinate information of different brain function areas in the brain function localization atlas and the boundary coordinates of organs in the anatomical atlas, and scales according to the appropriate scale, to register the brain tissue thermoacoustic image and the organ thermoacoustic image reconstructed by the image reconstruction algorithm, and set the thermoacoustic signals outside the brain function area or organ region in the registered image to 0.

[0056] Specifically, the image difference algorithm is obtained by subtracting the registered brain function image or organ image obtained at the initial monitoring time from the registered brain function image and organ image obtained at the monitoring time, that is, it can be expressed as:

[0057] ΔP = P x -P0

[0058] (x = 0 min, 3 min, 6 min, …, 60 min)

[0059] Wherein, P0 represents the image matrix of the brain function area or organ after registration at the initial time, P x represents the image matrix of the brain function area or organ after registration at the monitoring time point x, and ΔP represents the difference image matrix obtained at x.

[0060] On the basis of the above embodiment, the data post-processing sub-module can quantitatively determine the influence of acupoint stimulation on brain function areas and organs; the quantitative determination rule of the strength and correlation of the change of the monitoring target including the in-vivo organ and brain function area thermoacoustic signal caused by acupoint stimulation is: using the significance algorithm module to calculate the significance of the brain function area and organ thermoacoustic signal change with time under the same frequency microwave excitation, using the correlation algorithm module to calculate the change correlation between different brain function area thermoacoustic signals under the same frequency microwave excitation, between brain function area and organ thermoacoustic signals under the same frequency microwave excitation, and between the same brain function area under different frequency microwave excitation, and between the organ under different frequency microwave excitation.

[0061] Specifically, the saliency algorithm module can extract the pixels of different brain functional areas or organs in each difference image to represent the intensity of the thermoacoustic signal, and calculate the significance of the thermoacoustic signal of the brain functional area or organ over time by variance analysis. More specifically, according to the extracted pixels, it is proposed that the intensity of the thermoacoustic signal at different time points does not have significant differences (original hypothesis H0) and the pixels at different monitoring time points have significant differences (mutually exclusive hypothesis H1); then the sum of squares of the pixels at all monitoring time points (between-group sum of squares) and the sum of squares of the pixels at each monitoring time point (within-group sum of squares) are calculated; on this basis, the mean square deviation of the pixels at all monitoring times (between-group mean square deviation) and the mean square deviation of the pixels at a single monitoring time (within-group mean square deviation) are calculated; finally, the F statistic is calculated according to the between-group mean square deviation and the within-group mean square deviation, and whether to reject the original hypothesis H0 is compared according to the calculation result and the critical value. If the original hypothesis H0 is rejected, it is considered that the intensity of the thermoacoustic signal at different monitoring time points has significant differences; otherwise, it is considered that the intensity of the thermoacoustic signal at different monitoring time points does not have significant differences. The formula is as follows:

[0062]

[0063] Where SSB represents the between-group sum of squares, k represents the total number of monitoring time points n j represents the number of pixels at the jth monitoring time point, represents the mean value of the pixels at the jth monitoring time point, represents the overall pixel mean value, SSW represents the within-group sum of squares, X ij represents the ith pixel at the jth monitoring time point, MSB represents the between-group mean square deviation, n represents the number of pixels at all monitoring time points, and MSW represents the within-group mean square deviation.

[0064] Specifically, the correlation algorithm module can calculate the mean value of the pixels in each difference image in different brain functional areas or organs to represent the average intensity of the thermoacoustic signal, and calculate the Pearson correlation coefficient or Spearman correlation coefficient between the thermoacoustic signals of different brain functional areas under the same frequency microwave excitation, between the thermoacoustic signals of brain functional areas and organs under the same frequency microwave excitation, and between the thermoacoustic signals of the same brain functional area under different frequency microwave excitations and between the thermoacoustic signals of the organs under different frequency microwave excitations. Taking the correlation calculation between the thermoacoustic signals of the primary motor cortex brain functional area and the caudate nucleus brain functional area as an example, the Pearson correlation coefficient calculation formula is as follows:

[0065]

[0066] Where p represents the Pearson correlation coefficient, X i and Y iR(x) and R(y) represent the average rank of x and y.

[0067] The formula for calculating the Spearman correlation coefficient is as follows:

[0068]

[0069] Where, p s represents the Spearman correlation coefficient, x i and y i represent the pixel mean of the corresponding region of the calculated primary motor cortex brain function area and caudate nucleus brain function area at the i-th monitoring time point. i R(x) and R(y) represent the average rank of x and y. i i i

[0070] Further, for a plurality of experimental animals subjected to the same experimental method and the same implementation steps, the significance algorithm module and the correlation algorithm module can also be used for significance analysis and correlation analysis to more accurately quantify and analyze the effect of acupoint stimulation on the monitoring target from the perspective of dielectric properties. The specific steps are generally consistent with the above-mentioned significance and correlation analysis steps. The difference lies in that for a plurality of experimental animals under the same experimental conditions, the significance algorithm module calculates the pixel mean of different brain function areas or organs of each experimental animal at any monitoring time point to represent the intensity of the thermoacoustic signal; the correlation algorithm module calculates the pixel mean of all monitoring target brain function areas or organs, and takes the average of the calculated pixel mean to represent the average thermoacoustic signal intensity.

[0071] On the basis of the above embodiment, for single-frequency thermoacoustic data i (i = 1, 2, ···, n), the data visualization processing flowchart is as shown in Figure 2

[0072] Specifically, the single-frequency thermoacoustic data i contains structural information and dielectric function information of brain tissue and organ tissue, and the image reconstruction algorithm is used to reconstruct brain tissue thermoacoustic images and organ tissue thermoacoustic images.

[0073] Further, the brain function atlas and the anatomical atlas cooperate with the image registration algorithm to register the reconstructed brain tissue thermoacoustic images and organ tissue thermoacoustic images, and extract the corresponding brain function area thermoacoustic images and organ thermoacoustic images.

[0074] ​​​​Further, the brain function thermoacoustic image and the organ thermoacoustic image at the monitoring time point are respectively differentiated with the brain function thermoacoustic image and the organ thermoacoustic image at the start of monitoring via an image difference algorithm to obtain a brain function thermoacoustic difference image and an organ thermoacoustic difference image at the corresponding monitoring time point.

[0075] Further, the brain function thermoacoustic difference image is subjected to a saliency algorithm module

[0076] The saliency of the thermoacoustic signals of different brain function regions at the same microwave excitation frequency is calculated as the monitoring time changes; the saliency of the organ difference image is calculated by a saliency algorithm module.

[0077] Further, the Pearson correlation coefficient or the Spearman correlation coefficient of the thermoacoustic signals between different brain function regions and between the brain function region and the organ at the same microwave excitation frequency is calculated by a correlation algorithm module.

[0078] Further, the Pearson correlation coefficient or the Spearman correlation coefficient between the thermoacoustic signals generated by the same brain function region at n microwave excitation frequencies and between the thermoacoustic signals generated by the organ at n microwave excitation frequencies is calculated by a correlation algorithm module.

[0079] As shown in Figure 3 The application provides an acupoint stimulation monitoring visualization method of a multi-frequency microwave thermoacoustic imaging technology, which comprises the following steps:

[0080] S1, turn on the equipment, determine the order of each excitation frequency of the microwave source and other system working parameters, determine the total number of monitoring and each monitoring time point, and the monitoring time interval is greater than the time required for one complete multi-frequency microwave excitation;

[0081] S2, fix the imaging part, and fully couple the array ultrasonic transducer and the imaging part through an ultrasonic coupling medium;

[0082] S3, time counting, a computer triggers a single-frequency microwave pulse to excite the monitoring target, and thermoacoustic signal detection, acquisition and storage are performed, and the computer displays the brain function thermoacoustic image and the organ thermoacoustic image and the corresponding difference thermoacoustic image under the single-frequency microwave excitation pulse in real time;

[0083] S4, judge whether the multi-frequency point microwave excitation is completed, if not, quickly switch to the next microwave excitation point, and repeat S3-S4, if yes, perform S5;

[0084] S5, judge whether the total number of monitoring is met, if not, perform S6, if yes, perform S8;

[0085] S6, the microwave source excitation frequency point is initialized, and other experimental conditions remain unchanged, whether to start or continue the acupoint stimulation is judged, if not, S3-S4 is performed at the monitoring time point, if yes, S7 is performed;

[0086] S7, the acupoint stimulation is started or continued at the nearest monitoring time point, and S3-S4 is performed at each monitoring time point;

[0087] S8, the monitoring is stopped, and data post-processing is performed on the data obtained in the monitoring process, that is, significance and correlation analysis are performed;

[0088] S9, the monitoring result is output.

[0089] The system, device, module or unit illustrated in the above embodiments can be specifically implemented by a computer chip or entity, or by a product with certain functions.

[0090] It should also be noted that the terms “comprising”, “including”, or any other variant thereof are intended to cover non-exclusive inclusion, so that processes, methods, articles or devices including a series of elements not only include those elements, but also include other elements not explicitly listed, or further include elements inherent in such processes, methods, articles or devices. Without more limitations, the element defined by the statement “comprising a” does not exclude the presence of additional identical elements in the process, method, article or device including the element.

[0091] The above embodiments should be understood as only for illustrating the present application and not for limiting the protection scope of the present application. After reading the content of the present application, the skilled in the art can make various changes or modifications to the present application, and these equivalent changes and modifications also fall within the scope defined by the claims of the present application.

Claims

1. An acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology, characterized in that, include: The system includes a microwave excitation module, an acupoint stimulation module, a data acquisition module, and a stimulation visualization module. The microwave excitation module includes a computer, a frequency-tunable microwave source, a T-shaped waveguide, and a broadband antenna connected in sequence. The computer controls the frequency-tunable microwave source to generate pulse microwaves with rapidly switchable frequencies. The pulse microwaves are split into two paths through the T-shaped waveguide and radiated to the monitoring targets, including brain tissue and organ tissue, by a pair of identical broadband antennas. The tissues absorb microwave energy to generate ultrasonic waves, i.e., thermoacoustic signals. The acupoint stimulation module includes a monitoring target and an acupoint stimulation module; The data acquisition module includes an array ultrasonic transducer, a multi-channel amplifier, and a multi-channel data acquisition card. The array ultrasonic transducer is used to quickly detect thermoacoustic signals and convert them into electrical signals. The multi-channel amplifier amplifies the electrical signals output by the array ultrasonic transducer in phase and outputs them to the multi-channel data acquisition card. The multi-channel data acquisition card acquires the amplified electrical signals from the multi-channel amplifier and stores them in a computer. The stimulation visualization module includes a computer, a real-time monitoring submodule, and a data post-processing submodule. The computer performs image reconstruction and analysis on the electrical signals acquired by the multi-channel data acquisition card; that is, the real-time monitoring submodule and the data post-processing submodule express the data qualitatively and quantitatively. The real-time monitoring submodule includes an image reconstruction algorithm module, an image registration algorithm module, and an image difference algorithm module. The image reconstruction algorithm module is used for real-time display of brain functional thermoacoustic images and organ thermoacoustic images; the image registration algorithm module is used to extract the boundaries of brain functional areas and organ tissues; and the image difference algorithm module is used to qualitatively describe the intensity changes of brain functional thermoacoustic images and organ thermoacoustic images. The data post-processing submodule includes a saliency algorithm module and a correlation algorithm module. The saliency algorithm module is used to measure the changes of brain functional area and organ thermoacoustic signals over time; and the correlation algorithm module is used to quantitatively calculate the correlation between thermoacoustic signals of different brain functional areas, between brain functional areas and organ thermoacoustic signals under the same frequency microwave excitation during acupoint stimulation, and between thermoacoustic signals of the same brain functional area and organ under different frequency microwave excitations.

2. The acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology according to claim 1, characterized in that, The frequency-tunable microwave source refers to the rapid switching of the microwave center frequency within the range of 0.4 GHz to 10 GHz, and it is necessary to ensure that other parameters of the microwave source, including pulse width, pulse power, and pulse repetition frequency, remain unchanged during the monitoring experiment; the broadband antenna is a wideband antenna that is sufficient to cover the frequency range of 0.4 GHz to 10 GHz.

3. The acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology according to claim 1, characterized in that, The array ultrasonic transducer is a concave array ultrasonic transducer or a linear array ultrasonic transducer; the array ultrasonic transducer, in conjunction with an ultrasonic coupling medium, completes the detection of thermoacoustic signals. The ultrasonic coupling medium is used to remove air between the array ultrasonic transducer and the monitoring target, so that the thermoacoustic signals can be detected by the array ultrasonic transducer with minimal attenuation.

4. The acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology according to claim 3, characterized in that, The ultrasonic coupling medium refers to a medium that can reduce the attenuation of thermoacoustic signals at the tissue surface, including medical ultrasonic coupling agents, paraffin oil, and ultrasonic coupling pads with low conductivity.

5. The acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology according to claim 1, characterized in that, The real-time monitoring submodule is used to reflect the changes in thermoacoustic signals of brain functional areas and organs during acupoint stimulation in real time. Specifically, it combines the image reconstruction algorithm module, image registration algorithm module, and image difference algorithm module to sequentially perform image reconstruction, image registration, and image difference on the thermoacoustic signals, determine whether the monitored targets, including brain functional areas and organs, have changed their thermoacoustic signals, and qualitatively determine the strength of the changes. The image reconstruction algorithm module reconstructs thermal images of brain functional areas and organs using a delay superposition algorithm based on the temporal information and spatial location relationship of the thermal signal. The image registration algorithm module automatically reads the coordinate information of different brain functional areas in the brain functional localization map and the boundary coordinates of organs in the anatomical map, and scales them according to an appropriate ratio to register the brain tissue thermoacoustic image and organ thermoacoustic image reconstructed by the image reconstruction module, and sets the thermoacoustic signal outside the brain functional area or organ area in the registered image to 0. The image difference algorithm module is obtained by subtracting the registered brain function image and organ image obtained at the initial monitoring time from the registered brain function image and organ image obtained at the monitoring time, which can be represented as: ΔP=P x -P0 (x=0min,3min,6min,…,60min) Where P0 represents the image matrix of the brain functional areas or organs after registration at the initial moment, P x ΔP represents the image matrix of the registered brain functional area or organ at time x, and ΔP represents the difference image matrix obtained at time x.

6. The acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology according to claim 5, characterized in that, The image reconstruction algorithm module reconstructs thermal images of brain functional areas and organs using a delay-stack algorithm based on the temporal and spatial relationships of the thermal signals. Specifically, it includes: The delay superposition algorithm takes the position of each crystal of the array ultrasonic transducer as the center, and projects the thermoacoustic signal detected by each crystal back onto the imaging area for image reconstruction. The signal amplitude at any point in the reconstructed image is the superposition of the thermoacoustic signal amplitude detected by each crystal.

7. The acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology according to claim 1, characterized in that, The data post-processing submodule is used to quantitatively determine the effects of acupoint stimulation on brain functional areas and organs. The quantitative determination rules for the intensity of changes in thermoacoustic signals of internal organs and brain functional areas caused by acupoint stimulation, as well as the correlation of these changes, are as follows: the significance algorithm module is used to calculate the significance of the changes in thermoacoustic signals of brain functional areas and organs over time under microwave excitation at the same frequency; the correlation algorithm module is used to calculate the correlation of changes between thermoacoustic signals of different brain functional areas under microwave excitation at the same frequency, between thermoacoustic signals of brain functional areas and organs under microwave excitation at the same frequency, between thermoacoustic signals of the same brain functional area under microwave excitation at different frequencies, and between thermoacoustic signals of organs under microwave excitation at different frequencies.

8. The acupoint stimulation monitoring device based on multi-frequency thermoacoustic imaging technology according to claim 7, characterized in that, The saliency algorithm module extracts pixel values ​​of different brain functional areas or organs in each differential image to characterize the intensity of the thermoacoustic signal, and calculates the saliency of the changes in the thermoacoustic signal of brain functional areas and organs over time through variance analysis. The correlation algorithm module calculates the pixel mean of different brain functional areas or organs in each difference image to characterize the intensity of the thermoacoustic signal. It calculates the Pearson correlation coefficient or Spearman correlation coefficient between the thermoacoustic signals of different brain functional areas under the same frequency microwave excitation, between the thermoacoustic signals of brain functional areas and organs under the same frequency microwave excitation, and between the thermoacoustic signals of the same brain functional area under different frequency microwave excitation and between the thermoacoustic signals of organs under different frequency microwave excitation.

9. A method for acupoint monitoring based on the device according to any one of claims 1-8, characterized in that, Includes the following steps: S1. Turn on the equipment, determine the sequence of excitation frequencies of the microwave source, as well as other system operating parameters, determine the total number of monitoring times and each monitoring time point, and the monitoring time interval should be greater than the time required for one complete multi-frequency microwave excitation. S2. Fix the imaging site, and the array ultrasonic transducer is fully coupled to the imaging site through the ultrasonic coupling medium; S3. Timing: The computer triggers a single-frequency microwave pulse to excite the monitored target, perform thermoacoustic signal detection, acquisition and storage, and the computer displays in real time the brain function thermoacoustic image and organ thermoacoustic image and the corresponding differential thermoacoustic image under this single-frequency microwave excitation pulse. S4. Determine whether multi-frequency microwave excitation has been completed. If not, quickly switch to the next microwave excitation point and repeat S3-S4. If yes, proceed to S5. S5. Determine if the total number of monitoring times is met. If not, proceed to S6; if yes, proceed to S8. S6. Initialize the microwave source excitation frequency and keep other experimental conditions unchanged. Determine whether to start or continue acupoint stimulation. If not, proceed to S3-S4 at the monitoring time point. If yes, proceed to S7. S7. Start acupoint stimulation or continue acupoint stimulation at the nearest monitoring time point, and perform S3-S4 at each monitoring time point. S8. Stop monitoring and perform post-processing on the data obtained during the monitoring process, namely, conduct significance and correlation analysis. S9. Monitoring results output.

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