Precise diagnosis and treatment integrated platform and method based on coupling model

Abstract

According to the precise diagnosis and treatment integrated platform and method based on the coupling model, the cavitation effect is predicted through numerical simulation, negative feedback adjustment is conducted on microbubble mediated ultrasonic treatment, and precise control over the microbubble mediated ultrasonic treatment is achieved. Acoustic parameters are adjusted in real time, it can be ensured that treatment focuses on a lesion area, damage to surrounding healthy tissue is reduced, and therefore the accuracy and safety of treatment are improved. The platform integrates cavitation detection and an acoustic feedback mechanism, the microbubble cavitation effect can be monitored in real time, and treatment parameters can be automatically adjusted. Negative feedback closed-loop control can ensure a stable cavitation state, tissue damage caused by excessive cavitation is effectively avoided, and the stability and reliability of treatment are improved. The platform simplifies the operation process of controlling acoustic parameters. A doctor can complete the whole process from treatment to monitoring on the same operation interface through the integrated platform, and convenience and efficiency of clinical operation are improved. The platform is not only suitable for tumor treatment, ablation and drug delivery, but also can be applied to multiple treatment fields such as vascular diseases and neuromodulation, and has wide clinical application prospects and market potential.

Description

Technical Field

[0001] The present invention relates to the field of ultrasonic therapy technology, and in particular to a precise diagnosis and treatment integrated platform and method based on a coupling model. Background Art

[0002] Microbubble-mediated Ultrasound Therapy combines the physical properties of ultrasound with the biocompatibility of microbubbles. It drives microbubbles through sound waves to achieve multiple therapeutic effects such as targeted drug delivery, tumor ablation, and enhanced blood-brain barrier permeability. As a non-invasive innovative treatment method, it has shown significant effects and application potential in basic research and clinical trials. In recent years, the development of microbubble-mediated ultrasound therapy has been very rapid. Specific ligands are attached to the surface of ultrasound contrast agent microbubbles, which are circulated through the blood to reach the tissue or organ of interest and selectively bind to the corresponding receptors, thereby enhancing the ultrasound signal in the target area. Therefore, in terms of diagnostic applications, ultrasound microbubble contrast agents have been used for the diagnosis of acute focal inflammation, myocardial acoustic contrast, thrombosis, tumors, and the differential diagnosis of some benign and malignant tumors. Scientists have also found that under the action of specific acoustic parameters, the physical behaviors of microbubbles such as resonance, oscillation, and rupture can promote the increase of blood vessel and cell membrane permeability, so that therapeutic molecules such as drugs and genes can be delivered to the target area more accurately and efficiently. This property opens new applications of microbubbles as therapeutic media.

[0003] The cavitation effect is the core mechanism of microbubble-mediated ultrasound therapy. It produces instantaneous pressure changes and microbubble oscillations, leading to increased cell membrane permeability, improved drug delivery efficiency, and tissue destruction, thereby achieving precise therapeutic effects. Cavitation is the dynamic behavior of microbubbles in the sound field, which is mainly divided into inertial cavitation and steady-state cavitation. The regulation of different acoustic parameters has a significant impact on the cavitation effect, and understanding these influencing mechanisms is crucial to optimizing treatment plans.

[0004] In the actual treatment process, due to individual differences, the occurrence of cavitation in different treatment environments is also very different. The use of fixed ultrasonic parameter settings often deviates from the target range of cavitation effect, making it difficult to achieve the ideal treatment effect. In a multi-bubble system, microbubbles will generate secondary radiation sound waves during the oscillation process, and the secondary radiation sound waves will be superimposed and mixed with the incident sound waves. Due to the nonlinear oscillation of bubbles, the sound field in a multi-bubble environment becomes more complex and changeable. In a multi-bubble environment, the secondary radiation sound waves of each bubble cannot be simply superimposed.

[0005] The currently established cavitation theory model does not take into account the interaction between bubbles and the sound field in a multi-bubble environment, and is only applicable to the ideal case where bubbles oscillate alone. In the actual treatment process, microbubbles exist in the form of microbubble groups, because microbubbles not only respond to the incident sound pressure, but also respond to the secondary radiation sound waves generated by other microbubbles. The dynamic model of a single bubble obviously cannot meet the dynamic process of bubbles in a multi-bubble environment.

[0006] Therefore, it is very important to develop an integrated platform for precise diagnosis and treatment of acoustic cavitation based on a coupling model. Summary of the invention

[0007] In addition to being affected by the source sound field, the radial vibration of bubbles in the sound field causes secondary sound radiation in the liquid and affects the movement of adjacent bubbles and the sound field distribution in the liquid. Previous models often do not consider propagation and directly superimpose the secondary radiation sound wave energy to another microbubble. In view of this, the purpose of the present invention is to provide an integrated platform for precise diagnosis and treatment based on a coupling model, considering the incident sound wave and the bubble secondary radiation sound wave to form a composite field, coupling the microbubble oscillation with the sound field, solving the dynamic response characteristics of the bubbles in the cavitation cloud and the sound field distribution. The platform can monitor the cavitation intensity in real time during the treatment process, compare the computer simulation results for negative feedback regulation, simulate the real-time oscillation changes of microbubbles under the complex interaction of microbubbles in a multi-bubble system through a coupling model, obtain the real-time changes of cavitation intensity, and participate in disease treatment by adjusting acoustic parameters to affect the microbubble cavitation effect, which can realize an integrated platform for precise diagnosis and treatment of individual differences. It is suitable for ultrasound treatment fields that require precise regulation, such as tumor treatment and vascular disease treatment.

[0008] In order to achieve the above object, the present invention provides the following technical solutions:

[0009] The precision diagnosis and treatment integrated platform based on the coupling model provided by the present invention includes a parameter optimization module, a treatment control module, a cavitation detection module, and a feedback adjustment module;

[0010] The parameter optimization module is used to determine the acoustic parameters and treatment parameters required for treatment;

[0011] The treatment control module is used to determine the treatment control process according to various parameters;

[0012] The cavitation detection module is used to obtain and monitor microbubble cavitation effect parameters, wherein the cavitation effect parameters include cavitation intensity, cavitation distribution, and cavitation dynamic changes;

[0013] The feedback adjustment module is used to determine the adjustment relationship between the cavitation effect parameters and the acoustic parameters.

[0014] Further, the parameter optimization module data acquisition module, preprocessing module, microbubble cavitation simulation module, key feature extraction module, cavitation effect comparison module;

[0015] The data acquisition module is used to obtain acoustic parameters and microbubble characteristic parameters during treatment;

[0016] The preprocessing module is used to preprocess the collected raw data;

[0017] The microbubble cavitation simulation module is used to simulate the cavitation behavior of microbubbles;

[0018] The key feature extraction module is used to extract key cavitation features from the simulation results;

[0019] The cavitation effect comparison module is used to compare and analyze the cavitation effects under different acoustic parameters.

[0020] Furthermore, the treatment control module first uses a signal generator to control the ultrasonic transducer, and achieves precise excitation of microbubbles by adjusting the frequency, power and pulse parameters of the signal. The signal generator controls the ultrasonic transducer to send a signal to treat the diseased area, thereby achieving the purpose of treating the target tissue.

[0021] Furthermore, the cavitation detection module monitors the cavitation state of microbubbles in real time, uses a high-speed acquisition card to capture subharmonic and superharmonic signals and cavitation noise signals in real time through a PCD probe, and evaluates the treatment effect by analyzing the subharmonic and superharmonic signals and cavitation noise signals; extracts the spectral characteristics of microbubble vibration through fast Fourier transform FFT; focuses on monitoring subharmonic and superharmonic components, detecting subharmonic and superharmonic signals, and evaluating the cavitation intensity of microbubbles.

[0022] Furthermore, the feedback adjustment module dynamically adjusts the treatment parameters according to the cavitation detection results to achieve closed-loop control, specifically in the following manner:

[0023] Compare the difference between the theoretical cavitation intensity obtained by numerical simulation during the treatment process and the actual cavitation intensity, monitor and evaluate in real time whether the actual cavitation intensity is within the target range, and ensure that the microbubbles are in a stable cavitation state by adjusting the sound pressure and frequency; feedback adjustment results are recorded in the parameter optimization module to continuously optimize the treatment plan.

[0024] Furthermore, the microbubble cavitation simulation module uses a coupling model for numerical simulation to simulate the cavitation behavior of microbubbles under specific acoustic conditions. By introducing the coupling model, the changes in the composite sound field and the changes in the microbubble oscillation in a multi-bubble environment are predicted in real time, and the cavitation intensity and range of microbubbles and their interaction with surrounding tissues are better predicted, providing a theoretical basis for optimizing acoustic parameters. The influence of different acoustic parameters on the cavitation effect is verified by simulation, and a better parameter combination is screened out. The coupling model uses numerical simulation to calculate the microbubble response behavior, that is, the modified Hoff model is coupled with the nonlinear acoustic wave equation to solve:

[0025] Nonlinear acoustic wave equation:

[0026]

[0027] Modification of Hoff model using multi-bubble dynamics equation

[0028] The multi-bubble dynamics equation, namely the modified Keller-Miksis model

[0029]

[0030] Hoff Model

[0031]

[0032] Modified Hoff model

[0033]

[0034] Among them, C l represents the speed of sound in liquid; ρ L represents the density of liquid; α is the sound absorption coefficient of liquid; ω is the angular frequency of sound wave; N represents the number density of bubbles; and They represent the bubble radius, the first and second derivatives of the radius with respect to time respectively;

[0035] R represents the bubble radius; R0 represents the bubble equilibrium radius; P0 represents the ambient pressure P drive represents the driving sound pressure; p represents the total sound pressure in the cavitation cloud; η L Indicates the shear viscosity of the liquid; η S represents the shear viscosity of the cladding; d s Indicates the cladding thickness; G S represents the shell shear modulus.

[0036] Furthermore, the key feature extraction module is used to extract key cavitation features from the simulation results, and by extracting the cavitation features, intuitive data support is provided to evaluate the cavitation effects of different acoustic parameters.

[0037] Furthermore, the cavitation effect comparison module is used to compare the cavitation effects under different acoustic parameter combinations to evaluate their therapeutic effects and potential impacts on healthy tissues, automatically generate optimization reports, and recommend parameter combinations to ensure that the cavitation effect is optimal in the target area.

[0038] The method for integrated precision diagnosis and treatment based on a coupling model provided by the present invention comprises the following steps:

[0039] S1: Set treatment parameters; the treatment parameters that need to be set include acoustic parameters, microbubble parameters, and treatment area parameters;

[0040] S2: determining treatment parameters and microbubble characteristics, wherein the microbubble characteristics include a resonant frequency and a rupture threshold of the microbubble; and calculating the microbubble response behavior using numerical simulation;

[0041] S3: Monitor the cavitation effect in the treatment area through the passive detection probe PCD;

[0042] S4: Detect cavitation intensity, calculate theoretical cavitation dose and actual cavitation dose, compare the deviation between actual cavitation intensity and theoretical predicted value, and calculate cavitation dose error:

[0043] S5: evaluating whether the cavitation effect is within the target range, determining whether the treatment effect has been achieved, and if not, optimizing the treatment parameters, and returning to step S2 to determine the treatment parameters;

[0044] S6: If yes, continue treatment according to the original parameters until the end.

[0045] Further, the method further comprises the following steps:

[0046] S21: simulated ultrasound-induced microbubble cavitation;

[0047] S22: cavitation signal processing;

[0048] S23: Calculate the cavitation dose and microbubble oscillation intensity.

[0049] The beneficial effects of the present invention are:

[0050] The present invention provides an integrated precision diagnosis and treatment platform and method based on a coupling model, which establishes a cavitation bubble group dynamics model to describe the movement process of bubbles in a multi-bubble environment, predicts the cavitation effect through numerical simulation, and performs negative feedback regulation on microbubble-mediated ultrasound therapy to achieve precise control of microbubble-mediated ultrasound therapy. Real-time adjustment of acoustic parameters can ensure that the treatment is focused on the lesion area and reduce damage to surrounding healthy tissues, thereby improving the accuracy and safety of treatment; the platform integrates cavitation detection and acoustic feedback mechanisms, which can monitor the microbubble cavitation effect in real time and automatically adjust treatment parameters. Negative feedback closed-loop control can ensure a stable cavitation state, effectively avoid tissue damage caused by excessive cavitation, and improve the stability and reliability of treatment.

[0051] The platform simplifies the operation process of controlling acoustic parameters. Doctors can complete the entire process from treatment to monitoring on the same operation interface through the integrated platform, improving the convenience and efficiency of clinical operations. The platform is not only suitable for tumor treatment, ablation, and drug delivery, but can also be applied to multiple treatment fields such as vascular diseases and neuromodulation, and has broad clinical application prospects and market potential.

[0052] Achieve precise treatment. Based on the coupling model combined with computer simulation, the platform can monitor the cavitation intensity in real time during the treatment process and make fine parameter adjustments to ensure the safety and effectiveness of the treatment. By introducing the coupling model, the ability to predict and control the cavitation effect is improved. The integrated diagnosis and treatment functions enable the platform to achieve more precise and efficient treatment in an integrated operation, greatly improving the safety and accuracy of the treatment.

[0053] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for explanation.

[0055] Figure 1 This is a relationship diagram of the integrated precision diagnosis and treatment modules based on the coupling model.

[0056] Figure 2 This is the timing diagram of the parameter optimization module for integrated precision diagnosis and treatment based on the coupling model.

[0057] Figure 3 This is a flow chart of the integrated method of precision diagnosis and treatment based on the coupling model.

[0058] Figure 4This is an example diagram of numerical simulation of the coupled model.

[0059] Figure 5 This is a diagram of the mutual coupling relationship between multiple bubbles and the acoustic field. DETAILED DESCRIPTION

[0060] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0061] Example 1

[0062] like Figure 1 , as shown in 2, the integrated platform for precise diagnosis and treatment based on the coupling model provided in this embodiment includes a parameter optimization module, a treatment control module, a cavitation detection module, and a feedback adjustment module;

[0063] The parameter optimization module uses the coupling model to simulate the microbubble cavitation characteristics in real time, and combines with the cavitation detection module to evaluate the treatment effect, and adjusts the parameters according to the target treatment effect to determine the acoustic parameters and treatment parameters required for treatment;

[0064] The treatment control module is used to determine the treatment control process according to various parameters;

[0065] The cavitation detection module is used to obtain and monitor microbubble cavitation effect parameters, wherein the cavitation effect parameters include cavitation intensity, cavitation distribution, and cavitation dynamic changes;

[0066] The feedback adjustment module is used to accept the treatment parameters adjusted by the parameter optimization module, determine the adjustment relationship between the cavitation effect parameters and the acoustic parameters, and adjust the initial treatment parameters according to the ideal treatment effect;

[0067] The function of the parameter optimization module in this embodiment is to optimize the acoustic parameters (such as frequency, sound intensity, pulse width, etc.) required for treatment based on the coupling model to adapt to the specific treatment environment. Provide real-time treatment parameter adjustment function to ensure that the microbubble cavitation effect reaches the optimal state and improve the accuracy and safety of treatment. Reduce the complexity of manual adjustment by doctors and achieve the optimal configuration of treatment parameters through an automated process.

[0068] The function of the treatment control module in this embodiment is to manage and execute the output of acoustic energy during treatment, including precise control of power and focus. Ensure that the ultrasonic energy is always concentrated on the lesion area to avoid unnecessary damage to healthy tissue. Integrate a negative feedback closed-loop control mechanism to adjust the output according to the real-time monitored cavitation state to ensure treatment stability and effectiveness.

[0069] The functions of the cavitation detection module in this embodiment are: real-time monitoring of the cavitation effect of microbubbles, including cavitation intensity, cavitation distribution and dynamic changes. Providing accurate data on the cavitation state as a basis for feedback adjustment. Detecting abnormal cavitation phenomena (such as excessive cavitation or insufficient cavitation) and providing alarms and adjustment suggestions for the treatment control module.

[0070] The function of the feedback adjustment module in this embodiment is to dynamically adjust the acoustic parameters according to the data fed back by the cavitation detection module to achieve closed-loop control of treatment. Maintain the stability of the cavitation state, reduce the risk of tissue damage by avoiding excessive cavitation, and improve the reliability of treatment. Provide real-time acoustic feedback to ensure that the energy output during treatment matches the target tissue state and optimize the treatment effect.

[0071] In this embodiment, multiple functional modules are integrated together, and the integration effect is: through the joint action of four modules, a highly intelligent diagnosis and treatment closed-loop system is formed. Through the pre-configuration of the parameter optimization module, the precise execution of the treatment control module, the real-time monitoring of the cavitation detection module, and the dynamic optimization of the feedback regulation module, the platform can achieve the following functions: precise control of microbubble-mediated ultrasound therapy; improve the safety and effectiveness of treatment; simplify the operation process and improve the efficiency of clinical application; expand the applicability of various treatment scenarios, including tumors, vascular diseases, and neuromodulation.

[0072] The parameter optimization module provided in this embodiment includes a data acquisition module, a preprocessing module, a microbubble cavitation simulation module, a key feature extraction module, and a cavitation effect comparison module;

[0073] The data acquisition module is used to obtain acoustic parameters and microbubble characteristic parameters during treatment;

[0074] The preprocessing module is used to preprocess the collected raw data and extract acoustic parameters and various treatment parameters;

[0075] The microbubble cavitation simulation module is used to simulate the cavitation behavior of microbubbles;

[0076] The key feature extraction module is used to extract key cavitation features from the simulation results;

[0077] The cavitation effect comparison module is used to compare and analyze the cavitation effects under different acoustic parameters;

[0078] This embodiment describes in detail the functions of each submodule in the parameter optimization module (data acquisition module, preprocessing module, microbubble cavitation simulation module, key feature extraction module, cavitation effect comparison module):

[0079] The function of the data acquisition module provided in this embodiment is to collect acoustic parameters (frequency, sound pressure, pulse width, etc.) and microbubble characteristics (such as size, distribution, etc.) from the treatment environment in real time. Provide high-precision data input to provide a basis for processing and analysis of subsequent modules. Cooperate with the cavitation detection module to ensure that the collected data is timely and accurate.

[0080] The functions of the preprocessing module provided in this embodiment are: to process the collected raw data, including operations such as denoising, smoothing, and normalization, to improve data quality. To eliminate abnormal or invalid data, reduce calculation errors, and provide reliable input data sets for simulation and analysis modules. To achieve data format standardization, to ensure that the data can be efficiently parsed and processed by subsequent modules.

[0081] The function of the microbubble cavitation simulation module provided in this embodiment is to simulate the cavitation behavior of microbubbles under specific acoustic conditions by numerical simulation based on the coupling model. The cavitation intensity and range of microbubbles and their interaction with surrounding tissues are predicted to provide a theoretical basis for optimizing acoustic parameters. The influence of different acoustic parameters on the cavitation effect is verified by simulation, and a better parameter combination is screened out.

[0082] The coupling model adopts a modified hoff model and a nonlinear acoustic wave equation. The coupling model provided in this embodiment solves the spatiotemporal complexity of the prediction of the microbubble cavitation effect, simulates the real-time changes in the cavitation intensity, and also takes into account the complex interactions between bubbles and bubbles, and between bubbles and the sound field in a multi-bubble environment. Therefore, the coupling model can more accurately predict the changes in the microbubble cavitation intensity under different parameters, and can better realize precision treatment in combination with actual cavitation detection. By coupling and solving the nonlinear acoustic wave equation and the multi-bubble dynamics equation, the acoustic field distribution in the cavitation cloud and the change law of the bubble radius can be obtained.

[0083] The function of the key feature extraction module provided in this embodiment is to extract key cavitation features, such as microbubble rupture threshold, cavitation intensity, cavitation stability and other indicators from the simulation results. By extracting cavitation features, intuitive data support is provided to help quickly evaluate the cavitation effects of different acoustic parameters. Quantitative features are provided to provide decision-making basis for the cavitation effect comparison module and the feedback adjustment module.

[0084] The function of the cavitation effect comparison module provided in this embodiment is to compare the cavitation effects under different acoustic parameter combinations to evaluate their therapeutic effects and potential effects on healthy tissues. Automatically generate an optimization report and recommend parameter combinations to ensure that the cavitation effect is optimal in the target area while avoiding excessive effects on surrounding tissues. Provide a graphical display to intuitively present the differences in cavitation intensity and distribution, and assist doctors or researchers in selecting the optimal solution.

[0085] The synergy between the submodules in the parameter optimization module provided in this embodiment is: the data acquisition module provides basic data, the preprocessing module ensures data quality, the microbubble cavitation simulation module restores microbubble behavior through simulation, the key feature extraction module provides important quantitative indicators, and the cavitation effect comparison module completes optimization evaluation and recommendation based on these indicators. Through the synergy of the above submodules, the parameter optimization module can dynamically adjust the acoustic parameters so that the cavitation effect meets the treatment goals while ensuring the safety and effectiveness of the treatment. A full-chain closed loop from data acquisition to parameter optimization is achieved, which improves the accuracy, efficiency and reliability of treatment.

[0086] The parameter optimization module of this embodiment predicts the cavitation effect according to the input initial treatment parameters, and adopts the hoff model coupled with the nonlinear acoustic wave equation to simulate the movement process of the cavitation bubble group under the action of ultrasound. The acoustic field is calculated by the finite difference method, and the bubble dynamics equation is calculated by the Runge-Kutta method. The nonlinear acoustic wave equation and the bubble dynamics equation are solved by coupling the finite difference method and the Runge-Kutta method to obtain the time-domain acoustic pressure signal in the microbubble group and the information related to the change of the bubble radius;

[0087] In the data acquisition and preprocessing module, Visual Studio software was used with the C++ programming language to simulate the microbubble cavitation process and obtain key parameters such as microbubble vibration characteristics and sound field sound pressure changes.

[0088] The collected cavitation signals were processed using MATLAB software, and the spectrum features were extracted using fast Fourier transform (FFT). The cavitation signals were processed using a comb bandpass filter to extract the time-frequency domain features in the cavitation signals. The key features extracted included subharmonics, superharmonic components, etc. According to the processed data, the key features of cavitation behavior related to the microbubble cavitation behavior and the therapeutic effect were determined;

[0089] Obtain the cavitation effect of microbubbles under different parameter conditions, and compare it with the intensity of the cavitation effect produced by actual treatment, so as to optimize the parameters and provide subsequent treatment control;

[0090] The treatment control module provided in this embodiment first uses a signal generator to control the ultrasonic transducer, and achieves precise excitation of microbubbles by adjusting the frequency, power and pulse parameters of the signal. The signal generator controls the ultrasonic transducer to send a signal to treat the diseased area, thereby achieving the purpose of treating the target tissue.

[0091] The cavitation detection module provided in this embodiment monitors the cavitation state of microbubbles in real time, and evaluates the treatment effect by analyzing subharmonic and superharmonic signals; uses a high-speed acquisition card (PicoScope5000 series) to capture cavitation noise signals in real time through a PCD probe; extracts the spectrum characteristics of microbubble vibration through fast Fourier transform (FFT); focuses on monitoring subharmonic (integer multiple harmonics of the fundamental wave) and superharmonic (odd multiple harmonics of the 1 / 2 subharmonic) components, detects subharmonic and superharmonic signals, and evaluates the cavitation intensity of microbubbles;

[0092] Collect cavitation effect data through sensors and process them in real time;

[0093] The quantitative stable cavitation dose (SCD) is the integrated value of the superharmonic intensity and is used to evaluate the steady-state cavitation intensity;

[0094] The quantitative inertial cavitation dose (ICD) is the integrated value of broadband noise and is used to evaluate the inertial cavitation intensity;

[0095] The feedback adjustment module provided in this embodiment dynamically adjusts the treatment parameters based on the cavitation detection results to achieve closed-loop control;

[0096] The difference between the theoretical cavitation intensity obtained by numerical simulation during the treatment process and the actual cavitation intensity is compared, and the actual cavitation intensity is monitored and evaluated in real time to see if it is within the target range. By adjusting the sound pressure and frequency, the microbubbles are ensured to be in a stable cavitation state to avoid excessive cavitation leading to tissue damage. The feedback adjustment results are recorded in the parameter optimization module to continuously optimize the treatment plan.

[0097] Compare the theoretical cavitation dose with the actual cavitation dose to evaluate whether the cavitation dose is within the target range and determine whether the cavitation effect has achieved the desired effect;

[0098] Link the steady-state cavitation dose obtained by numerical simulation and the steady-state cavitation dose generated during the actual treatment process, compare the target cavitation dose range, and automatically adjust the treatment parameters (sound pressure, frequency, pulse time, duty cycle) based on real-time feedback to ensure that the cavitation effect is stable and safe. Maintain the stable cavitation state of microbubbles through a negative feedback loop to avoid excessive cavitation or tissue damage.

[0099] Example 2

[0100] like Figure 3 As shown, the integrated method of precise diagnosis and treatment based on the coupling model provided in this embodiment includes the following steps:

[0101] S1: Set treatment parameters; the treatment parameters that need to be set include:

[0102] Acoustic parameters, ultrasonic frequency: 1 MHz, pulse repetition frequency: 1000, pulse duration: 100 μs;

[0103] Microbubble parameters, microbubble concentration: 2×10 9 MBs / m 3 ;

[0104] Microbubble size: 2.5 μm;

[0105] Treatment area parameters, target tissue location and size;

[0106] Ultrasound focal range and depth;

[0107] S2: Determine treatment parameters and microbubble characteristics;

[0108] Determine the resonance frequency and rupture threshold of the microbubbles through experimental measurements or literature search;

[0109] Use numerical simulation to calculate the microbubble response behavior (modified Hoff model coupled with nonlinear acoustic wave equation solution):

[0110] Nonlinear acoustic wave equation:

[0111]

[0112] Modification of Hoff model using multi-bubble dynamics equation

[0113] Multi-bubble dynamics equation (modified Keller-Miksis (KM) model)

[0114]

[0115] Hoff Model

[0116]

[0117] Modified Hoff model

[0118]

[0119] Among them, C l represents the speed of sound in liquid; ρ L represents the density of liquid; α is the sound absorption coefficient of liquid; ω is the angular frequency of sound wave; N represents the number density of bubbles; and They represent the bubble radius, the first and second derivatives of the radius with respect to time respectively;

[0120] R represents the bubble radius; R0 represents the bubble equilibrium radius; P0 represents the ambient pressure P drive represents the driving sound pressure; p represents the total sound pressure in the cavitation cloud; η L Indicates the shear viscosity of the liquid; η S represents the shear viscosity of the cladding; d sIndicates the cladding thickness; G S represents the shell shear modulus;

[0121] like Figure 5 As shown, Figure 5 This is a diagram of a coupled model numerical simulation example. The meaning of the diagram is as follows:

[0122] After the simulated ultrasound is generated by the focused ultrasonic transducer, it acts on a target cavitation area, where the parameters of the transducer and the target cavitation area are shown in the figure.

[0123] like Figure 5 As shown, Figure 5 The diagram of the mutual coupling relationship between multiple bubbles and the acoustic field. Figure 5 The meanings of the letters are as follows:

[0124] P n―1 represents the sound pressure at the focus at time n-1; P n represents the sound pressure at the focus at time n; P n+1 represents the sound pressure at the focus at time n+1; R n―1 represents the bubble radius at time n-1; R n represents the bubble radius at time n; R n+1 Indicates the bubble radius at time n+1;

[0125] By coupling the Hoff model with the nonlinear acoustic wave equation, the radius change of the bubble after oscillation caused by the incident sound wave is solved according to the initial driving sound pressure and the initial radius of the bubble. At the same time, considering that the bubble oscillates under the influence of the incident sound wave and generates secondary radiation sound waves, a composite sound field is formed. The composite sound pressure at time n-1 is solved, and then the radius of the bubble at time n-1 that oscillates under the action of the sound pressure is solved from the composite sound field sound pressure at time n-1. The radius change of the bubble at different times and the change of the composite sound field are solved by coupling.

[0126] S3: Monitoring cavitation effects in the treatment area through PCD probe

[0127] Monitoring area parameters:

[0128] Cavitation intensity: Analyzed by receiving signal amplitude and spectrum width.

[0129] Cavitation Type: Monitors steady-state cavitation (low-frequency harmonics) and transient cavitation (high-frequency noise).

[0130] Cavitation Distribution: Monitors the spatial uniformity of the cavitation effect.

[0131] Monitoring methods:

[0132] Use a passive cavitation detector (PCD) to locate the source of cavitation sound signals.

[0133] Analyze frequency domain characteristics (harmonic signals, superharmonic signals, broadband noise) and time domain characteristics.

[0134] S4: Detect cavitation intensity and compare theoretical cavitation dose with actual cavitation dose;

[0135] Actual cavitation dose: Calculate the cavitation intensity based on the cavitation signal collected by PCD

[0136] First, the time signal X recorded in a sampling period i (n) (n = 0, 1, ..., N-1; i = 1, 2, ..., M) (N is the number of sampling points in a sampling period T; M is the number of sampling periods) and the spectrum is obtained by performing FFT transformation:

[0137]

[0138] k is the frequency point in the spectrum. In order to characterize the strength of the signal at different frequencies, the power spectrum (p) of the signal is calculated:

[0139] P i (k) = X i (k) 2

[0140] First, a peak filter with a fixed bandwidth of 0.1 MHz is used to extract the superharmonics, and then the superharmonic intensity within a sampling period T is calculated, where U i express:

[0141]

[0142] Among them, a and c are the number of superharmonics and frequency points within the 0.1MHz bandwidth, respectively. Therefore, the steady-state cavitation dose (SCD) during the entire exposure time can be obtained by the following formula, where U is used to represent the steady-state cavitation dose:

[0143]

[0144] Among them, U is and U ic These are the superharmonic intensity with and without microbubbles, respectively;

[0145] A notch filter with a 0.2MHz stopband is used to extract the broadband noise signal. Then the broadband noise intensity within a sampling period is calculated, where B i express

[0146]

[0147] Among them, d and e are the number of broadband components and the number of frequency points in each broadband, respectively. From this, the inertial cavitation dose (ICD) during the entire exposure time can be obtained. Here B is used to represent the inertial cavitation dose:

[0148]

[0149] Among them, B is and B ic are the broadband noise signal intensities with and without microbubbles, respectively.

[0150] Theoretical cavitation dose calculation uses the finite difference method and Runge-Kutta method to couple the nonlinear acoustic wave equation and bubble dynamics equation to obtain the time-domain acoustic pressure signal in the microbubble group and information related to the change of bubble radius. The calculated time-domain acoustic pressure signal is subjected to fast Fourier transform (FFT) to extract the superharmonic signal and broadband noise signal. Then, the integral value of the superharmonic signal and broadband noise signal under different intensities of ultrasound is calculated to characterize the steady-state cavitation and inertial cavitation intensity.

[0151] Comparison method:

[0152] Compare the deviation between the actual cavitation intensity and the theoretical prediction value and calculate the cavitation dose error:

[0153] S5: evaluating whether the cavitation effect is within the target range, determining whether the treatment effect has been achieved, and if so, optimizing the treatment parameters, and returning to step S2 to determine the treatment parameters;

[0154] Evaluation process:

[0155] Cavitation effect parameters: steady-state cavitation ratio; cavitation signal amplitude range; cavitation distribution uniformity;

[0156] Treatment effect parameters: target tissue temperature rise; tissue damage volume;

[0157] Judging criteria:

[0158] The cavitation intensity in the treatment focal area reaches the preset target range;

[0159] The cavitation intensity of the surrounding tissue does not exceed the safety threshold;

[0160] S6: If yes, continue treatment according to the original parameters until the end;

[0161] The following steps are also included:

[0162] S21: simulated ultrasound-induced microbubble cavitation;

[0163] Use Visual Studio to simulate the oscillation characteristics of bubbles in complex acoustic fields, considering the complex interactions of bubbles under the action of acoustic fields.

[0164] Input actual treatment parameters and calculate microbubble cavitation dose;

[0165] S22: cavitation signal processing;

[0166] Treatment method:

[0167] Spectral analysis: separation of harmonics, superharmonics and broadband noise;

[0168] Time domain analysis: identifying the time window in which cavitation events occur;

[0169] S23: Calculate cavitation dose and microbubble oscillation intensity;

[0170] Cavitation dose calculation:

[0171] Calculate the integral values ​​of superharmonic signals and broadband noise signals under different acoustic parameters;

[0172] The oscillation intensity is described by the change in bubble radius;

[0173] The method provided in this embodiment forms a complete diagnosis and treatment process through precise data collection, simulation calculation, real-time monitoring and closed-loop optimization, thereby ensuring the accuracy, safety and efficiency of treatment.

[0174] This embodiment sets initial acoustic parameters according to the patient's diagnostic information, starts the treatment process, monitors and provides feedback in real time during the treatment process, monitors the cavitation intensity through the cavitation detection module, identifies subharmonics, superharmonics and broadband noise characteristics, and calculates SCD and ICD respectively; runs numerical simulation through the coupled model module of the treatment control module to predict the cavitation effect under the current parameters; adjusts the ultrasonic parameters through the feedback adjustment module to ensure the optimal treatment effect; this embodiment achieves closed-loop control through repeated detection, simulation and parameter adjustment. When the treatment is completed, the platform automatically saves all data for subsequent evaluation and research.

[0175] The above-described embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or changes made by those skilled in the art based on the present invention are within the protection scope of the present invention. The protection scope of the present invention shall be subject to the claims.

Claims

1. An integrated platform for precise diagnosis and treatment based on a coupling model, characterized by: It includes parameter optimization module, treatment control module, cavitation detection module and feedback adjustment module; The parameter optimization module is used to determine the acoustic parameters and treatment parameters required for treatment; The treatment control module is used to determine the treatment control process according to the treatment parameters; The cavitation detection module is used to obtain and monitor microbubble cavitation effect parameters, wherein the cavitation effect parameters include cavitation intensity, cavitation distribution, and cavitation dynamic changes; The feedback adjustment module is used to determine the adjustment relationship between the cavitation effect parameters and the acoustic parameters.

2. The precision diagnosis and treatment integrated platform based on the coupling model as claimed in claim 1, characterized in that: The parameter optimization module includes a data acquisition module, a preprocessing module, a microbubble cavitation simulation module, a key feature extraction module, and a cavitation effect comparison module; The data acquisition module is used to obtain acoustic parameters and microbubble characteristic parameters during treatment; The preprocessing module is used to preprocess the collected raw data; The microbubble cavitation simulation module is used to simulate the cavitation behavior of microbubbles; The key feature extraction module is used to extract key cavitation features from the simulation results; The cavitation effect comparison module is used to compare and analyze the cavitation effects under different acoustic parameters.

3. The precision diagnosis and treatment integrated platform based on the coupling model according to claim 1, characterized in that: The treatment control module is performed in the following manner: first, a signal generator is used to control the ultrasonic transducer, and the microbubbles are excited by adjusting the frequency, power and pulse parameters of the signal, and the ultrasonic transducer is controlled by the signal generator to send a signal.

4. The precision diagnosis and treatment integrated platform based on the coupling model according to claim 1, characterized in that: The cavitation detection module is used to monitor the cavitation state of microbubbles in real time, and uses a high-speed acquisition card to capture subharmonic and superharmonic signals and cavitation noise signals in real time through a PCD probe; evaluates the treatment effect by analyzing the intensity of subharmonic and superharmonic signals and cavitation noise signals; extracts the spectrum characteristics of microbubble vibration through fast Fourier transform FFT; focuses on monitoring subharmonic and superharmonic components, detecting subharmonic and superharmonic signals, and evaluating the cavitation intensity of microbubbles.

5. The precision diagnosis and treatment integrated platform based on the coupling model according to claim 1, characterized in that: The feedback adjustment module dynamically adjusts the treatment parameters according to the cavitation detection results to achieve closed-loop control, specifically in the following manner: Compare the difference between the theoretical cavitation intensity obtained by numerical simulation during the treatment process and the actual cavitation intensity, monitor and evaluate in real time whether the actual cavitation intensity is within the target range, and ensure that the microbubbles are in a stable cavitation state by adjusting the sound pressure and frequency; The feedback adjustment results are recorded in the parameter optimization module to continuously optimize the treatment plan.

6. The precision diagnosis and treatment integrated platform based on the coupling model according to claim 2, characterized in that: The microbubble cavitation simulation module uses a coupling model and numerical simulation technology to simulate the cavitation behavior of microbubbles under specific acoustic conditions, predict the cavitation intensity and range of microbubbles and their interaction with surrounding tissues; verify the influence of different acoustic parameters on the cavitation effect through simulation, and screen out the optimal parameter combination; the coupling model uses numerical simulation to calculate the microbubble response behavior, that is, the modified Hoff model is coupled with the nonlinear acoustic wave equation to solve: Nonlinear acoustic wave equation: Modification of Hoff model using multi-bubble dynamics equation The multi-bubble dynamics equation, namely the modified Keller-Miksis model Hoff Model Modified Hoff model Among them, C l represents the speed of sound in liquid; ρ L represents the density of liquid; α is the sound absorption coefficient of liquid; ω is the angular frequency of sound wave; N represents the number density of bubbles; and They represent the bubble radius, the first and second derivatives of the radius with respect to time respectively; R represents the bubble radius; R0 represents the bubble equilibrium radius; P0 represents the ambient pressure P drive represents the driving sound pressure; p represents the total sound pressure in the cavitation cloud; η L Indicates the shear viscosity of the liquid; η S represents the shear viscosity of the cladding; d s Indicates the thickness of the cladding; G S represents the shell shear modulus.

7. The precision diagnosis and treatment integrated platform based on the coupling model as claimed in claim 2, characterized in that: The key feature extraction module is used to extract key cavitation features from the simulation results, and by extracting the cavitation features, provides intuitive data support to evaluate the cavitation effects of different acoustic parameters.

8. The precision diagnosis and treatment integrated platform based on the coupling model as claimed in claim 2, characterized in that: The cavitation effect comparison module is used to compare the cavitation effects under different acoustic parameter combinations to evaluate their therapeutic effects and potential impacts on healthy tissues, automatically generate optimization reports, and recommend parameter combinations to ensure that the cavitation effect is optimal in the target area.

9. An integrated method of precision diagnosis and treatment based on a coupling model, characterized by: The following steps are involved: S1: Set treatment parameters; the treatment parameters that need to be set include acoustic parameters, microbubble parameters, and treatment area parameters; S2: Determine treatment parameters and microbubble characteristics; the microbubble characteristics include the resonance frequency and rupture threshold of the microbubble; Use numerical simulation to calculate microbubble response behavior; S3: Monitor the cavitation effect in the treatment area through the passive detection probe PCD; S4: Detect cavitation intensity, calculate theoretical cavitation dose and actual cavitation dose, compare the deviation between actual cavitation intensity and theoretical predicted value, and calculate cavitation dose error: S5: evaluating whether the cavitation effect is within the target range, determining whether the treatment effect has been achieved, and if not, optimizing the treatment parameters, and returning to step S2 to determine the treatment parameters; S6: If yes, continue treatment according to the original parameters until the end.

10. The method for integrated precision diagnosis and treatment based on a coupling model according to claim 9, characterized in that: The following steps are also included: S21: simulated ultrasound-induced microbubble cavitation; S22: cavitation signal processing; S23: Calculate the cavitation dose and microbubble oscillation intensity.

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