An ultrasonic cavitation control system for nephritis therapy

Abstract

The present invention belongs to the field of ultrasonic technology, and is particularly an ultrasonic cavitation control system for nephritis physical therapy, including: using a three-dimensional imaging probe to generate an ultrasonic image of the kidney area and collect echo information; extracting ultrasonic cavitation features to monitor the cavitation degree in real time, combining the ultrasonic image and echo information to obtain the sound field and biological information, and performing multi-angle cavitation index calculation and normalization processing; processing the ultrasonic image to obtain kidney position information, configuring delay parameters for the physical therapy array, integrating the normalized cavitation index to establish an evaluation equation, and adjusting the index weight according to the cavitation monitoring information, guiding the selection of ultrasonic amplitude-frequency parameters, and ensuring that the cavitation degree of the focus area is within an ideal range; encoding the delay and amplitude-frequency parameter information into a physical therapy array configuration excitation signal, and emitting ultrasonic waves. The system of the present invention can coordinate the monitoring of cavitation effects and physical therapy of nephritis, improve the drug penetration ability through controllable cavitation effects, and improve the physical therapy effect of nephritis.

Description

Technical Field

[0001] The invention relates to the field of ultrasonic technology, in particular to an ultrasonic cavitation control system for nephritis therapy. Background Art

[0002] With the development of ultrasound technology, local drug absorption efficiency can be significantly improved by focusing on lesions and combining them with drug therapy. Compared with systemic medication, ultrasound-assisted drug transport can concentrate on the lesion site at a lower dose, reduce systemic side effects and shorten intervention time, showing good application prospects. However, the existing ultrasound focusing accuracy and the safety and stability of cavitation control still have certain shortcomings.

[0003] At present, ultrasound focusing technology only uses fixed focal length or limited focusing scales, which cannot effectively respond to the biological tissue characteristics of different patients, resulting in deviations in drug delivery positions and poor targeting effects, limiting the widespread application of ultrasound drug delivery technology in clinical practice. With the development of acoustic field and biological model simulation technology, the use of finite element simulation software to establish a multi-physics field model tailored to patient characteristics can achieve customized and personalized ultrasound focusing for different patients, making up for the lack of focusing accuracy of existing technologies.

[0004] In ultrasound-assisted drug delivery, the transport and absorption efficiency of drugs mainly depends on the ultrasonic cavitation effect, but the intensity of the cavitation effect needs to be precisely controlled, otherwise it may lead to uncertainty in drug delivery. At present, most physical therapy systems for ultrasound nephritis drug delivery lack strict cavitation monitoring and control systems, cannot intuitively reflect the severity of the cavitation effect, and fail to fully consider the large differences in the sensitivity of patient tissues to the cavitation effect, which poses a safety hazard. Therefore, we proposed a physical therapy system that combines personalized focused cavitation monitoring and dynamic control to solve the above problems. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the problem that the focal area and cavitation degree are difficult to accurately control in the existing ultrasound-assisted drug delivery process, the present invention uses ultrasound imaging, echo processing, finite element analysis, index calculation and fusion, and weight adjustment system to construct a drug transport auxiliary system that combines personalized focused cavitation monitoring and dynamic control. The proposed multi-physics field model, index fusion, and weight optimization algorithm can accurately focus on the lesion area and dynamically adjust the ultrasound amplitude and frequency parameters in real time to achieve dynamic control of the cavitation degree, solving the problems raised in the above background technology.

[0007] (II) Technical solution

[0008] In order to achieve the above-mentioned purpose, the present invention specifically adopts the following technical solutions:

[0009] An ultrasonic cavitation control system for nephritis physical therapy includes the following steps:

[0010] S1: Generate ultrasound images of the kidney area and collect echo information using a three-dimensional imaging probe;

[0011] S2: Extract ultrasonic cavitation features to monitor the cavitation degree in real time and generate cavitation monitoring information. Combine ultrasonic images and echo information to obtain sound field and biological information, and calculate and normalize multi-angle cavitation indicators.

[0012] S3: Use ultrasound images to obtain kidney position information to configure delay parameters for the physical therapy array, fuse the normalized multi-angle cavitation indicators to generate an evaluation equation, adjust the indicator weights according to the cavitation monitoring information, and guide the selection of ultrasound amplitude and frequency parameters;

[0013] S4: configuring an excitation signal for the therapy array according to the ultrasonic parameters of the output module, and transmitting ultrasonic waves to induce cavitation effect in the lesion area;

[0014] Furthermore, the S1 uses a PODA RCA row-column addressing ultrasound three-dimensional imaging probe with an array element width of 90 μm, a spacing of 120 μm, and a bandwidth of 80% to generate an ultrasound image of the kidney area.

[0015] Furthermore, based on the three-dimensional imaging probe, a sampling frequency of 4 MHz and a spatial resolution of 0.2 mm to 1 mm were used to collect ultrasonic echo information, and an FIR bandpass filter with a passband of 3.5 MHz to 4.5 MHz, a transition bandwidth of 50 KHz, and a passband attenuation rate of 40 db was used for echo preprocessing to obtain an ideal echo signal.

[0016] Furthermore, the cavitation monitoring information of S2 is specifically as follows: performing time-frequency analysis on the echo signal through short-time Fourier transform to identify the changes in the signal spectrum during the cavitation process, applying wavelet transform to perform multi-resolution analysis on the echo signal to capture the instantaneous characteristic changes of the cavitation phenomenon, extracting quantitative indicators related to the degree of cavitation, and realizing accurate monitoring of the degree of cavitation.

[0017] Furthermore, the acoustic field and biological information of S2 are obtained by combining the ultrasonic image and ultrasonic echo information with the acoustic field model and the finite element difference algorithm to obtain information such as the sound pressure amplitude, the negative value of the sound pressure peak, the cavitation bubble information, the tissue environment pressure and the dynamic viscosity coefficient.

[0018] Furthermore, based on the above information, the mechanical index, cavitation threshold, bubble radius change and ultrasonic energy density are calculated and normalized, wherein the mechanical index is used to measure the cavitation risk, the cavitation threshold is used to evaluate the minimum threshold that causes cavitation, the bubble radius change (Rayleigh-Prasser equation) is used to describe the dynamic changes of bubbles under the action of ultrasonic waves, and the ultrasonic energy density is used to measure the intensity of cavitation.

[0019] The formula for the mechanical index is:

[0020]

[0021] Where P_ is the ultrasonic peak negative pressure, and f is the ultrasonic frequency.

[0022] The formula for the cavitation threshold is:

[0023]

[0024] Where σ is the surface tension of the tissue fluid, R0 is the initial radius of the bubble, and P0 is the ambient static pressure.

[0025] The formula for the bubble radius change (Rayleigh-Prasser equation) is:

[0026]

[0027] Where R is the bubble radius, ρ is the tissue fluid density, P0 is the ambient pressure of the tissue fluid, and P ac (t) is the sound pressure of ultrasound at a certain time t, σ is the surface tension of tissue fluid, and μ is the dynamic viscosity coefficient of tissue fluid.

[0028] The formula for the ultrasonic energy density is:

[0029]

[0030] Where P ac is the ultrasonic sound pressure amplitude, ρ is the medium density, and c is the propagation speed of ultrasound in the medium.

[0031] Furthermore, the mechanical index, cavitation threshold, bubble radius change and ultrasonic energy density are normalized:

[0032]

[0033]

[0034]

[0035]

[0036] Where, MI min , CT min , (ΔR) min 、E Dmin is the minimum value, MI max , CT max , (ΔR) max 、E Dmax is the maximum value of this value.

[0037] Furthermore, the delay parameter configuration and the amplitude-frequency parameter selection in s3 are specifically a process of delay calculation, evaluation equation establishment and adjustment, amplitude-frequency parameter selection and ultrasonic parameter integration output, which is specifically manifested as follows:

[0038] The delay calculation module uses finite element software to establish a multi-physics field model to simulate the kidney area and obtain the phased ultrasound delay parameters that can reach the kidney position; it uses an intelligent optimization algorithm to dynamically adjust the delay parameters to obtain ultrasound delay parameters that can make the ultrasound beam accurately focus on the lesion and have a stronger main lobe energy and a more convergent focal area.

[0039] The evaluation equation module integrates the multi-angle cavitation indicators including the normalized mechanical index, cavitation threshold, bubble radius change and ultrasonic energy density to obtain the cavitation evaluation equation, and adjusts the indicator weights in combination with the cavitation monitoring information to guide the parameter selection module to select the amplitude-frequency parameters. The evaluation equation of the normalized multi-indicator fusion is:

[0040] AC=k1(MI norm )+k2(1 / CT norm )+k3(E Dnorm )+k4(ΔR norm )

[0041] In the formula, AC represents the degree of cavitation effect, the initial values ​​of k1, k2, k3, and k4 are set to 0.4, 0.3, 0.2, and 0.1, and MI norm is the normalized mechanical index, CT norm is the normalized cavitation threshold, E Dnorm is the normalized ultrasound energy density, ΔR norm is the normalized bubble radius change (Rayleigh-Prasser equation).

[0042] The weight adjustment is performed based on the cavitation monitoring unit information so that the evaluation equation can guide the selection of ultrasonic parameters under the premise of ensuring cavitation safety. The weight optimization criterion is:

[0043]

[0044] Where O is the weight rationality index, STC is the lowest critical point of stable cavitation, UTSC is the highest critical point of stable cavitation, and IC is the lowest critical point of inertial cavitation.

[0045] The amplitude-frequency parameter selection module establishes an ultrasonic amplitude-frequency parameter library based on the cavitation degree requirements for nephritis drug transport assistance and selects ultrasonic amplitude-frequency parameters in real time and dynamically through the instructions of the evaluation module.

[0046] The output module integrates the delay parameters and amplitude-frequency parameters and outputs them to the physical therapy unit.

[0047] Furthermore, the amplitude-frequency parameter selection module uses finite element software to establish a cavitation model and simulate it, obtains the corresponding ultrasound amplitude and frequency range according to the degree of cavitation required for nephritis drug transport assistance, and uses the ascending gradient method to sort the amplitude-frequency parameter information to obtain an amplitude-frequency parameter library.

[0048] Furthermore, the S4 therapy array uses 63 aluminum nitride transducers with a center frequency of 1.37 MHz and a diameter of 5 mm, and is composed of a 3-layer center-blank elliptical ring therapy array that is more in line with the shape of the kidney according to the rules of array element spacing and layer spacing of 1.25 mm.

[0049] Furthermore, the excitation signal of S4 uses an FPGA development board with a crystal oscillator frequency of 50MHz as a controller, uses a frequency multiplier to increase the frequency to 200MHz, and cooperates with a phase-locked loop to obtain a PWM signal with a maximum error of no more than 5ns to write delay parameters, and uses a downconverter to obtain a 100MHz stable signal output to a DDS signal generator, and generates a sinusoidal wave excitation signal in combination with the amplitude-frequency parameters.

[0050] (III) Beneficial effects

[0051] Compared with the prior art, the present invention provides an ultrasonic cavitation control system for nephritis physical therapy, which has the following beneficial effects:

[0052] The present invention processes echo information to obtain real-time information on the degree of cavitation of the lesion as a cavitation evaluation index. When faced with the problem that different patients have large differences in cavitation sensitivity, the present invention can intuitively display the degree of cavitation in the focal area, guide personalized treatment, improve the stability of drug transport, and reduce the risk of mechanical damage and excessive cavitation.

[0053] The present invention obtains information such as focal area and sound pressure peak through echo intensity calculation combined with finite element simulation to obtain more accurate sound field distribution information, and uses a dynamic feedback mechanism and a balanced optimization algorithm to iteratively optimize the ultrasound delay, thereby obtaining a more convergent focal area and accurately focusing the sound beam on the lesion area, thereby improving the personalization and accuracy of ultrasound therapy.

[0054] The present invention adopts a multi-angle index fusion method to quantify the degree of cavitation of the lesion, so that ultrasound can collaboratively complete monitoring and physical therapy functions, with strong robustness and accuracy, and lower cavitation control cost. At the same time, the weight of the cavitation index is adjusted in combination with cavitation information through a dynamic weight allocation method, so that the evaluation equation has higher universality, which is more conducive to the promotion of the system and related equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a schematic diagram of the flow of an ultrasonic cavitation control system for nephritis treatment according to an embodiment of the present invention;

[0056] Figure 2 This is a schematic diagram of the distribution of phased array imaging units and physical therapy units according to an embodiment of the present invention;

[0057] Figure 3 This is a diagram of delayed ultrasonic focusing and sound pressure distribution according to an embodiment of the present invention;

[0058] Figure 4 This is a flow chart of adjusting the weight of an evaluation equation indicator according to an embodiment of the present invention;

[0059] Figure 5 Schematic diagram of ultrasonic cavitation effect promoting drug transport according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] Example

[0062] like Figure 1 As shown, an ultrasonic cavitation control system for nephritis treatment, the specific steps are as follows:

[0063] S1: Generate ultrasound images of the kidney area and collect echo information using a three-dimensional imaging probe.

[0064] In this embodiment, Figure 2 As shown, the imaging unit is composed of a PODA RCA row-column addressed ultrasound three-dimensional imaging probe with an array element width of 90 μm, a spacing of 120 μm, and a bandwidth of 80%, and cooperates with a PODA host and a high-performance workstation to generate kidney area ultrasound images and collect echo information.

[0065] S2: Extract ultrasonic cavitation features to monitor the cavitation degree in real time and generate cavitation monitoring information. Combine ultrasonic images and echo information to obtain sound field and biological information, and calculate and normalize multi-angle cavitation indicators.

[0066] The specific steps are:

[0067] A1: First, use a sampling frequency of 4MHz and a spatial resolution of 0.2mm to 1mm to collect ultrasonic echo information, and use a FIR bandpass filter with a passband of 3.5MHz to 4.5MHz, a transition bandwidth of 50KHz, and a passband attenuation rate of 40db to perform echo preprocessing to obtain an ideal echo signal.

[0068] A2: Use short-time Fourier transform to perform time-frequency analysis on the echo signal to identify the changes in the signal spectrum during the cavitation process. Apply wavelet transform to perform multi-resolution analysis on the echo signal to capture the instantaneous characteristic changes of the cavitation phenomenon, extract quantitative indicators related to the degree of cavitation, and accurately evaluate the cavitation phenomenon.

[0069] A3: Process the echo signal to obtain sound field and biological information such as sound pressure amplitude, sound pressure peak negative value, cavitation bubble information, tissue environmental pressure and dynamic viscosity coefficient.

[0070] A4: Calculate the mechanical index, cavitation threshold, bubble radius change and ultrasonic energy density based on the sound field and biological information of A3.

[0071] Mechanical Index formula:

[0072]

[0073] Where P_ is the ultrasonic peak negative pressure, and f is the ultrasonic frequency.

[0074] Cavitation threshold formula:

[0075]

[0076] Where σ is the surface tension of the tissue fluid, R0 is the initial radius of the bubble, and P0 is the ambient static pressure.

[0077] Bubble radius change (Rayleigh-Prasser equation) formula:

[0078]

[0079] Where R is the bubble radius, ρ is the tissue fluid density, P0 is the ambient pressure of the tissue fluid, and P ac (t) is the sound pressure of ultrasound at a certain time t, σ is the surface tension of tissue fluid, and μ is the dynamic viscosity coefficient of tissue fluid.

[0080] Ultrasonic energy density formula:

[0081]

[0082] Where P ac is the ultrasonic sound pressure amplitude, ρ is the medium density, and c is the propagation speed of ultrasound in the medium.

[0083] A5: Normalization of mechanical index, cavitation threshold, bubble radius change and ultrasonic energy density:

[0084]

[0085]

[0086]

[0087]

[0088] Where, MI min , CT min , (ΔR) min 、E Dmin is the minimum value, MI max , CT max , (ΔR) max 、E Dmax is the maximum value of this value.

[0089] In this example, the finite element acoustic field model will simulate and save the ultrasonic parameter information in the Intel(R) Core(TMi7-10700K processor + NVIDIAGeForce RTX 2080Ti + COMSOL Multiphysics 6.2 environment, and construct the excitation signal based on the simulated and optimized ultrasonic parameters.

[0090] S3: Use ultrasound images to obtain kidney position information to configure delay parameters for the physical therapy array, fuse the normalized multi-angle cavitation indicators to generate an evaluation equation, and adjust the indicator weights according to the cavitation monitoring information to guide the selection of ultrasound amplitude and frequency parameters.

[0091] A1: Use the Canny algorithm to perform edge detection to identify tissue boundaries in ultrasound images, separate the tissue boundaries of each biological layer from the lumbar cortex to the renal medulla for biological layer division, and use the adaptive thickness measurement method to measure the vertical distance between each pixel using the outer and inner boundaries of the renal cortical area in the segmentation results to obtain the biological layer thickness.

[0092] A2: Based on the biological layer thickness information, a three-dimensional biological model was established using COMSOL Multiphysics finite element simulation software. Since the speed of ultrasound in different biological layers is different, after obtaining the kidney position to determine the lesion area, this example simulates each array element one by one to obtain the time it takes for each array element to reach the focus, thereby obtaining the initial delay parameter. COMSOL LiveLink for MATLAB was used to write an improved balanced optimization code in MATLAB that has the ability to call simulation data sets to connect and drive COMSOL Multiphysics to iteratively optimize the delay parameters, and the following is obtained: Figure 3 The main lobe energy shown is stronger, the focal area is more convergent, and the sound field is focused and the sound pressure distribution is distributed. The optimization process is as follows:

[0093] (1) Optimizing the generation probability: The fixed generation probability is modified to a mode that gradually decays from 1 to 0 with the number of iterations, so that the degree to which the generation probability participates in the optimization process gradually decreases, reducing its exploration ability and increasing the convergence efficiency of the algorithm.

[0094] (2) Jump out of local optimum: Use random perturbations with gradually decreasing strength of 0.01*(1-current number of iterations / maximum number of iterations)*upper and lower bounds*rand(dimension) to improve the algorithm's ability to jump out of local optimum. When the algorithm converges in the later stage of iteration, weaken the perturbation intensity to prevent the algorithm from performing invalid iterations.

[0095] (3) Calling the data set: Using COMSOL LiveLink for MATLAB, the data set is automatically exported to MATLAB for evaluation after each COMSOL Multiphysics simulation.

[0096] (4) Iterative optimization: Set the objective function, based on the number of data points and the kidney position of the imaging information, set the simulation focus position and set the main lobe range within 3 mm of the focus position. The energy of the remaining positions is classified as side lobes. Use Cauchy initialization to set 100 particles, perform 75 iterative optimizations, and export the optimization results to the output module for integration.

[0097] A3: Use finite element software to build a cavitation model and simulate it. According to the degree of cavitation required for nephritis drug transport assistance, the corresponding ultrasound amplitude and frequency range are obtained. The amplitude-frequency parameter information is sorted using the ascending gradient method to obtain the amplitude-frequency parameter library.

[0098] A4: Integrate multi-angle cavitation indicators including normalized mechanical index, cavitation threshold, bubble radius change and ultrasonic energy density, adjust indicator weights based on cavitation monitoring information, derive cavitation evaluation equation, and guide parameter selection module to select amplitude-frequency parameters.

[0099] Cavitation evaluation equation:

[0100] AC=k1(MI norm )+k2(1 / CT norm )+k3(E Dnorm )+k4(ΔR norm )

[0101] In the formula, AC represents the degree of cavitation effect, the initial values ​​of k1, k2, k3, and k4 are set to 0.4, 0.3, 0.2, and 0.1, and MI norm is the normalized mechanical index, CT norm is the normalized cavitation threshold, E Dnorm is the normalized ultrasound energy density, ΔR norm is the normalized bubble radius change (Rayleigh-Prasser equation);

[0102] A5: Figure 4 As shown, the weight optimization criterion is set to guide the optimization of the weight.

[0103] Weight optimization criteria:

[0104]

[0105] Where O is the weight rationality index, STC is the lowest critical point of stable cavitation, UTSC is the highest critical point of stable cavitation, and IC is the lowest critical point of inertial cavitation.

[0106] Based on the cavitation monitoring unit information, stable cavitation and inertial cavitation are divided and critical information is obtained as the judgment condition for weight adjustment, such as Figure 4 As shown, the judgment process is as follows:

[0107] (1) AC≤STC:

[0108] First, determine whether the degree of cavitation has reached the minimum critical point of stable cavitation. If, under the guidance of the evaluation equation after adjusting the weight, the degree of cavitation is always lower than the minimum critical point of stable cavitation, it indicates that the parameters of the amplitude-frequency parameter library cannot cause stable cavitation effect in the kidney when facing this patient, and the drug transport auxiliary capacity is low. The parameter library parameters should be improved. After reconstructing the parameter library, the weight adjustment of the evaluation equation and the amplitude-frequency parameter guidance should be carried out.

[0109] (2) STC<AC <UTSC:

[0110] If, under the guidance of an initial or weighted evaluation equation, the degree of cavitation is higher than the lowest critical point of stable cavitation and lower than the highest critical point of stable cavitation, it indicates that the amplitude-frequency parameters selected for cavitation under the evaluation equation can keep the cavitation in a stable cavitation state, with bubbles expanding and shrinking regularly. At this time, there is no need to adjust the indicator weight.

[0111] (3) AC ≥ IC:

[0112] If the degree of cavitation is always higher than the lowest critical point of inertial cavitation under the guidance of the evaluation equation after adjusting the weight, it indicates that the patient is highly sensitive to cavitation, the degree of cavitation in the lesion is too large, and the parameters in the amplitude-frequency parameter library do not meet the patient's needs. The parameters in the parameter library should be lowered, and the weight of the evaluation equation and the amplitude-frequency parameter guidance should be adjusted after the parameter library is reconstructed.

[0113] (4)UTSC≤AC<IC:

[0114] If, under the guidance of the evaluation equation of the initial weight, the cavitation degree is higher than the highest critical point of stable cavitation but lower than the inertial cavitation threshold, the weight is adjusted to increase the weight of the mechanical index and ultrasonic energy density, so as to improve the sensitivity of the evaluation equation to the cavitation degree and reduce the cavitation degree to within the stable cavitation range.

[0115] A4: Integrate the delay parameters and the amplitude-frequency parameters and output them to the physical therapy unit to form an excitation signal.

[0116] S4: According to the ultrasonic parameters of the output module, an excitation signal is configured for the physical therapy array, and ultrasonic waves are emitted to induce cavitation effect in the lesion area.

[0117] In this embodiment, Figure 2 As shown, 63 aluminum nitride transducers with a center frequency of 1.37 MHz and a diameter of 5 mm are used to form a 3-layer elliptical ring therapy unit that is more in line with the shape of the kidney according to the rules of array element spacing and layer spacing of 1.25 mm, so as to perform focused therapy on the kidney and induce cavitation effect.

[0118] In this embodiment, an FPGA development board with a crystal oscillator frequency of 50 MHz produced by ALTERA's CycloneIV E series is used as a controller. A frequency multiplier is used to increase the frequency to 200 MHz, and a PWM signal with a maximum error of no more than 5 ns is obtained in conjunction with a phase-locked loop to write delay parameters. A frequency reducer is used to obtain a stable signal of 100 MHz, which is output to a DDS signal generator to generate a sinusoidal wave excitation signal in conjunction with the amplitude-frequency parameters, thereby stimulating the array transducer to emit an ultrasonic beam to induce cavitation effect in the lesion area.

[0119] like Figure 5 As shown, it is a schematic diagram of the stable cavitation drug transport assistance after parameter optimization based on the cavitation monitoring unit and the evaluation equation of the present invention. Under ultrasonic irradiation, the cavitation bubbles expand and shrink periodically according to the ultrasonic stimulation to improve the flow capacity of the surrounding drug particles, and the permeability of the tissue membrane is increased under the stimulation of ultrasonic waves, which is more conducive to the transportation and absorption of drugs.

[0120] In view of the problem that the cavitation effect is difficult to accurately control during the existing ultrasound-assisted drug delivery process, the present invention uses ultrasound imaging, echo processing, finite element analysis, and index fusion and adjustment systems to construct a drug delivery system that combines personalized focusing with cavitation monitoring and dynamic control. The proposed multi-physics field model, index fusion, and optimization algorithm can accurately focus on the lesion area and realize the dynamic control of cavitation intensity in real time and accurately, solving the problems of low efficacy of direct ultrasound beam irradiation therapy and poor safety and control of existing ultrasound cavitation. Therefore, the system proposed in this article can be used as an effective and feasible way to achieve efficient treatment of nephritis through precise control of cavitation degree.

[0121] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An ultrasonic cavitation control system for nephritis treatment, characterized by: It includes an ultrasonic three-dimensional imaging probe, a cavitation monitoring unit, a time delay calculation module, an evaluation equation module, an amplitude-frequency parameter selection module and an output module; The imaging unit composed of ultrasonic three-dimensional imaging probe cooperates with PODA host and high-performance workstation to generate ultrasonic images of kidney area and collect echo information; The cavitation monitoring unit obtains the sound pressure amplitude, the sound pressure peak negative value, the cavitation bubble information, the tissue environment pressure and the dynamic viscosity coefficient acoustic field and biological information by processing the echo signal; The specific steps are: S1: Generate a renal ultrasound image and collect echo information using an ultrasound three-dimensional imaging probe; S2: Extract the features in the cavitation monitoring unit to monitor the cavitation degree in real time and generate cavitation monitoring information, combine the ultrasonic image and echo information to obtain the sound field and biological information, and calculate and normalize the cavitation indicators from multiple angles; S3: Use ultrasound images to obtain kidney position information to configure delay parameters for the physical therapy array, fuse the normalized multi-angle cavitation indicators to generate an evaluation equation, adjust the indicator weights according to the cavitation monitoring information, and guide the selection of ultrasound amplitude and frequency parameters; The configuration of the delay parameters and the selection of the amplitude-frequency parameters in S3 are specifically a process of delay calculation, establishment and adjustment of evaluation equations, selection of amplitude-frequency parameters and integrated output of ultrasonic parameters; The integrated output process is specifically manifested as follows: The delay calculation module uses finite element software to establish a multi-physics field model to simulate the kidney area and obtain the phased ultrasound delay parameters that can reach the kidney position; the intelligent optimization algorithm is used to dynamically adjust the delay parameters to obtain the ultrasound delay parameters that can accurately focus the ultrasound beam on the lesion and make the main lobe energy stronger and the focal area more convergent; The evaluation equation module integrates the normalized mechanical index, cavitation threshold, ultrasonic energy density and bubble radius change indicators, uses the hierarchical analysis method to assign weights to each indicator, forms an evaluation equation, and dynamically adjusts the weights in real time based on the cavitation monitoring information to obtain a personalized evaluation equation that meets the patient's needs; The amplitude-frequency parameter selection module, based on the cavitation degree required for nephritis drug transport assistance, establishes an ultrasound amplitude-frequency parameter library and selects ultrasound amplitude-frequency parameters in real time and dynamically through the instructions of the evaluation module; The output module integrates the delay parameters and the amplitude-frequency parameters and outputs them to the physical therapy unit; S4: According to the ultrasonic parameters of the output module, an excitation signal is configured for the physical therapy array, and ultrasonic waves are emitted to induce cavitation effect in the lesion area.

2. The ultrasonic cavitation control system for nephritis treatment according to claim 1, characterized in that: The delay calculation module in S3 specifically obtains the thickness, density and acoustic reflection coefficient information of the biological layer between the cortex and the renal medulla through ultrasonic images and echo data; uses finite element software to establish a multi-physical field model and configures the biological layer thickness, density and acoustic reflection coefficient for the tissue area, and sets the initial ultrasonic delay parameters in combination with the kidney position information to achieve preliminary focusing; at the same time, a balanced optimization algorithm is used in combination with finite element simulation to dynamically adjust the delay parameters, so as to obtain ultrasonic delay parameters that can accurately focus on the lesion and have stronger main lobe energy and more convergent focal area.

3. The ultrasonic cavitation control system for nephritis treatment according to claim 1, characterized in that: The evaluation equation module in S3 specifically integrates the multi-angle cavitation indexes including the normalized mechanical index, cavitation threshold, bubble radius change and ultrasonic energy density, adjusts the index weights in combination with the cavitation monitoring information, and obtains the cavitation evaluation equation to guide the parameter selection module to select the amplitude-frequency parameters. The evaluation equation of the normalized multi-index fusion is: ； In the formula, AC represents the degree of cavitation effect, , , , The initial values ​​are set to 0.4, 0.3, 0.2, 0.1, is the normalized mechanical index, is the normalized cavitation threshold, is the normalized ultrasound energy density, is the normalized bubble radius change; The index weights are adjusted based on the cavitation monitoring information so that the evaluation equation can guide the selection of ultrasonic amplitude and frequency parameters under the premise of ensuring cavitation safety. The weight optimization criterion is: ； In the formula, O is the weight rationality index, is the lowest critical point of stable cavitation. is the highest critical point of stable cavitation. It is the lowest critical point of inertial cavitation.

4. The ultrasonic cavitation control system for nephritis treatment according to claim 1, characterized in that: The establishment of the ultrasonic amplitude-frequency parameter library in the S3 amplitude-frequency parameter selection module is specifically manifested in that a cavitation model is established and simulated using finite element software, and the corresponding excitation signal amplitude and frequency range are obtained according to the degree of cavitation required for nephritis drug transport assistance, and the parameters are sorted using the ascending gradient method to obtain the ultrasonic amplitude-frequency parameter library.

5. The ultrasonic cavitation control system for nephritis treatment according to claim 1, characterized in that: The S4 specifically uses 63 aluminum nitride transducers with a center frequency of 1.37MHz and a diameter of 5mm, and forms a 3-layer elliptical ring therapy array that is more in line with the shape of the kidney according to the rules of array element spacing and layer spacing of 1.25mm. It uses FPGA as a driving unit to generate a PWM signal with a maximum error of no more than 5ns to write a delay, and integrates the amplitude and frequency parameters to output to the DDS signal generator to generate a sinusoidal wave excitation signal.

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