Vascular plaque treatment dynamic control method and system based on micro-control release chip

Abstract

The invention provides a blood vessel plaque treatment dynamic control method and system based on a micro-control release chip. According to the method, real part and imaginary part data of vascular impedance are measured in a multi-frequency-point current loop, dielectric characteristics are matched in combination with phase difference change, gradient change rate parameters are calculated, and then a three-dimensional distribution diagram of plaque hardness is constructed. When the gradient change rate exceeds a threshold value, the system automatically generates a pressure control instruction matched with the calcification area and converts the pressure control instruction into a multi-band treatment signal combination. The micro-control release chip is used for converting a signal into a mechanical expansion waveform, triggering high-frequency amplitude monitoring, dynamically adjusting the aperture opening of the chip and adjusting the medicine permeation rate in real time, so that precise control of plaque degradation is realized. According to the technology, electrical characteristic analysis, three-dimensional imaging, dynamic pressure regulation and control and drug release optimization are integrated, and a closed-loop treatment system is formed. According to the technical scheme provided by the invention, dynamic control treatment on the blood vessel plaque is realized based on multi-frequency electrical characteristic analysis and intelligent regulation and control.

Description

Technical Field

[0001] The present application relates to the field of dynamic control technology, and in particular to a dynamic control method and system for treating vascular plaques based on a micro-controlled release chip. Background Art

[0002] Interventional treatment of calcified vascular plaques requires addressing the challenge of dynamic control during dilation. Calcified plaques exhibit significant heterogeneity in hardness, distribution, and thickness. Traditional balloon dilation can easily lead to vascular elastic retraction, dissection, or perforation due to uneven pressure distribution. Clinical needs focus on developing an intelligent system that can sense calcification status in real time, adaptively adjust dilation energy, and precisely release antiproliferative drugs to achieve progressive, controllable plaque remodeling while inhibiting intimal hyperplasia.

[0003] Currently, the representative technology for this demand is the shock wave balloon catheter system (such as Shockwave IVL or BoltIVL), which generates shock waves through the hydro-electric effect or micropore-induced cavitation to break up calcified plaques.

[0004] However, there are still significant limitations. The energy release of shock waves depends on preset parameters (such as the number of pulses and voltage), and cannot sense the calcification fragmentation process in real time and adjust it dynamically, which may lead to energy overload (damage to blood vessels) or insufficient energy (residual calcification). The existing system cannot obtain the microscopic morphology information of calcified fissures through in situ sensors, resulting in low spatial matching between energy release and calcification density, making it difficult to treat complex calcified nodules or eccentric lesions. The shock wave only focuses on mechanical fragmentation and does not integrate drug sustained-release function. The risk of postoperative restenosis still depends on subsequent stent implantation or oral medication, and cannot achieve integrated "fragmentation and anti-proliferation" treatment. Summary of the Invention

[0005] The present application provides a dynamic control method and system for treating vascular plaque based on a micro-controlled release chip, which is used to solve the problem of poor vascular plaque control effect in the prior art.

[0006] In a first aspect, the present application provides a dynamic control method for treating vascular plaques based on a micro-controlled release chip, comprising:

[0007] Establishing a multi-frequency current loop in the target blood vessel segment, and obtaining blood vessel electrical characteristic data including real and imaginary components based on the impedance attenuation characteristics of the multi-frequency current loop;

[0008] Based on the phase difference change of the blood vessel electrical characteristic data, a gradient change rate parameter is calculated by matching the dielectric characteristic value, and the gradient change rate parameter is used to construct a three-dimensional distribution map of plaque hardness in the target blood vessel;

[0009] When the gradient change rate parameter exceeds a set threshold, a pressure control instruction is generated that matches the spatial distribution corresponding to the calcified area;

[0010] Based on the calcified core area, transition area and healthy area divided by the three-dimensional distribution map of plaque hardness, the pressure control instruction is converted into a multi-band treatment signal combination;

[0011] The therapeutic signal combination is converted into a corresponding mechanical expansion waveform through a micro-controlled release chip. The mechanical expansion waveform triggers the monitoring of the high-frequency signal amplitude. When the high-frequency signal is detected to have reached its peak amplitude, the pore opening parameters of the micro-controlled release chip are synchronously adjusted. When the dielectric parameters of the calcified core area are detected to fluctuate in the opposite direction, the phase compensation adjustment of the drug permeation rate is triggered according to the spectral characteristics of the current driving signal combination to control the degradation process of the vascular plaque.

[0012] Optionally, based on the impedance attenuation characteristics of the multi-frequency current loop, a phase difference change at different frequencies for each measurement point is extracted from the vascular electrical characteristic data, and the phase difference change is matched with a pre-calibrated dielectric characteristic relationship table to determine the dielectric characteristic value corresponding to each measurement point;

[0013] Based on the three-dimensional geometric contour of the target blood vessel segment, the target blood vessel segment is divided into equally spaced cubic units, where the side length of each cubic unit is consistent with the electrode spacing of the micro-controlled release chip, and the dielectric property values ​​are assigned to the corresponding units according to the spatial coordinates to form an initial dielectric property distribution grid;

[0014] Iteratively optimizing the initial dielectric property distribution grid according to the difference in dielectric property values ​​between adjacent units to generate an optimized dielectric property distribution grid;

[0015] Calculating the maximum difference between the dielectric property values ​​of each cell and six adjacent cells in the optimized dielectric property distribution grid, and dividing the maximum difference by the cell spacing to obtain a gradient change rate parameter of the current cell;

[0016] According to the distribution of the gradient change rate parameter, adjacent continuous units of the gradient change rate parameter in the dielectric property distribution grid are merged into the same level to form the three-dimensional boundaries of the calcified core area, the transition area and the healthy area, so as to output a three-dimensional distribution map of plaque hardness.

[0017] Optionally, based on the three-dimensional boundaries of the calcified core area, the transition area, and the healthy area in the three-dimensional distribution map of plaque hardness, the numerical range of the dielectric properties in each area is extracted, the highest dielectric value of the calcified core area is used as a reference value, the proportional coefficients of the dielectric values ​​of the transition area and the healthy area to the reference value are calculated, and the proportional coefficients are mapped to frequency threshold intervals of the corresponding areas;

[0018] The upper limit of the frequency threshold interval of the calcified core area is defined as the starting frequency of the high-frequency signal, the midpoint of the frequency threshold interval of the transition area is used as the fixed frequency of the intermediate-frequency signal, and the proportional coefficient of the dielectric value of the healthy area is combined with a preset morphological stability parameter to determine the frequency value of the low-frequency signal;

[0019] The high-frequency signal, intermediate-frequency signal and low-frequency signal are respectively loaded into independent waveform generators, and the phases of the three signals are offset controlled by the independent waveform generators so that the peak interval between the high-frequency signal and the intermediate-frequency signal is greater than a preset threshold, and the trough of the low-frequency signal and the peak of the high-frequency signal form a periodic overlap to form a therapeutic signal combination.

[0020] Optionally, the superimposed deformation of the therapeutic signal combination is converted into a mechanical expansion waveform through the multi-layer flow channel structure in the micro-controlled release chip to trigger the embedded piezoresistive sensor to monitor the high-frequency signal amplitude. When the instantaneous amplitude of the high-frequency signal exceeds the trigger ratio of the preset amplitude for the first time, it is recorded as the initial trigger point. If the peak values ​​of multiple subsequent consecutive signal cycles reach or exceed the preset amplitude, an adjustment instruction for the pore opening is sent to the drive unit of the micro-controlled release chip, so that the pore opening parameter is linearly increased from the initial opening to the target opening within the next signal cycle, thereby improving the drug penetration rate.

[0021] In the calcified core area, dielectric characteristic values ​​are acquired at fixed time intervals and the difference rate between two adjacent acquisitions of the dielectric characteristic values ​​is calculated. When the difference rate shows negative changes for multiple consecutive times and exceeds the reverse fluctuation tolerance range, phase compensation adjustment is triggered;

[0022] performing offset compensation on the drug permeation rate control waveform according to the current phase angle of the high-frequency signal to generate an offset-compensated drug permeation control waveform, and inputting the drug permeation rate control waveform and the mechanical expansion waveform of the high-frequency signal into a waveform superposition module to generate a composite control signal;

[0023] In the dynamic control waveform, the pore aperture parameter is dynamically scaled with the real-time change of the amplitude of the high-frequency signal. At the same time, the amplitude coupling relationship of the composite control signal is dynamically corrected through the pressure feedback loop to ensure that the peak pressure of the mechanical expansion waveform and the permeation rate of the drug permeation rate control waveform form a complementary superposition on the time axis, so as to achieve dynamic control of vascular plaques.

[0024] Optionally, the target blood vessel segment is divided into cubic units with equal spacing along the axial, radial and circumferential directions, with the electrode spacing of the micro-controlled release chip as the side length;

[0025] By traversing all measurement points within the spatial range of the cubic unit, extracting the phase difference change and looking up the table to obtain the dielectric characteristic value, if there are multiple measurement points in the cubic unit, taking the average value of the multiple measurement points as the initial value of the cubic unit, and if there are no measurement points in the cubic unit, marking the cubic unit as an invalid unit;

[0026] According to searching for valid cells adjacent to the invalid cell, extracting a distance-weighted average of the dielectric characteristic values ​​of the valid cells as the value of the invalid cell, and arranging all the cubic cells according to spatial positions to form an initial three-dimensional grid storing the dielectric characteristic values ​​and spatial positions;

[0027] The degree of difference in dielectric property values ​​between effective cells and adjacent cells in the initial three-dimensional grid is calculated so that the degree of difference between all cubic cells is lower than a threshold or reaches a maximum number of iterations to form an initial dielectric property distribution grid.

[0028] Optionally, the dielectric property values ​​of the cubic unit and its six adjacent units are read one by one, the maximum dielectric property difference between the cubic unit and the adjacent units is calculated, and the maximum dielectric property difference is divided by the unit side length to obtain the gradient change rate parameter of the unit;

[0029] The gradient change rate parameter is set to a high threshold interval, a medium threshold interval, and a low threshold interval, and then the cubic unit is traversed. If the gradient change rate parameter of the cubic unit falls within the high threshold interval, it is marked as a core candidate unit; if it falls within the medium threshold interval, it is marked as a transition candidate unit; if it falls within the low threshold interval, it is marked as a healthy candidate unit, and the marked cubic unit is obtained;

[0030] Performing a spatial continuity check on the marked cubic units, starting from any core candidate unit, merging the core candidate units that share a face or edge with the any core candidate unit to form a calcified core area, performing the same operation on the transition candidate unit and the healthy candidate unit to generate a transition area and a healthy area, respectively;

[0031] The mean values ​​of the gradient change rate parameters of the cells in the calcified core area, transition area, and healthy area are calculated. If the difference in the mean values ​​of the gradient change rate parameters of adjacent areas is less than the merging tolerance, the two sub-areas are merged into the same level, and the spatial coordinate extremes of each level are extracted to generate a cubic bounding box as the three-dimensional boundary output. The calcified core area, transition area, and healthy area are associated with the three-dimensional boundary and output as a three-dimensional distribution map of plaque hardness.

[0032] Optionally, a gradient change rate parameter of each unit is extracted from the three-dimensional distribution map of plaque hardness, and compared with a set threshold value, and units exceeding the threshold value are screened out and marked as calcified core units;

[0033] Merging adjacent calcified core units to form a calcified core area, calculating the geometric center and outer contour of the calcified core area, establishing a three-dimensional pressure control grid based on the outer contour of the calcified core area, and aligning grid nodes of the three-dimensional pressure control grid with the spatial distribution of the calcified core area;

[0034] Calculating a pressure weight coefficient based on the distance between the grid node and the center of the calcified core area, and allocating a pressure waveform amplitude based on the weight coefficient, where nodes with higher weights correspond to pressure waveforms with higher amplitudes, to generate an initial pressure control instruction;

[0035] According to the ratio of the gradient change rate parameter of the calcified core area to the set threshold, the pressure waveform amplitude of each node in the initial pressure control instruction is proportionally adjusted to obtain a pressure control instruction.

[0036] In a second aspect, the present application provides a dynamic control system for treating vascular plaques based on a micro-controlled release chip, comprising:

[0037] an acquisition module, configured to establish a multi-frequency current loop in the target blood vessel segment and acquire blood vessel electrical characteristic data including real and imaginary components based on the impedance attenuation characteristics of the multi-frequency current loop;

[0038] a construction module for calculating a gradient change rate parameter by matching dielectric characteristic values ​​based on a phase difference change of the blood vessel electrical characteristic data, and constructing a three-dimensional distribution map of plaque hardness in the target blood vessel using the gradient change rate parameter;

[0039] a generating module, configured to generate a pressure control instruction matching the spatial distribution corresponding to the calcified area when the gradient change rate parameter exceeds a set threshold;

[0040] a conversion module, which converts the pressure control instruction into a multi-band treatment signal combination based on the calcified core area, transition area, and healthy area divided by the three-dimensional distribution map of plaque hardness;

[0041] The regulating module is used to convert the therapeutic signal combination into a corresponding mechanical expansion waveform through a micro-controlled release chip,

[0042] The mechanical expansion waveform triggers the monitoring of the high-frequency signal amplitude. When the high-frequency signal reaches a peak amplitude, the pore opening parameters of the micro-controlled release chip are synchronously adjusted. When a reverse fluctuation of the dielectric parameters of the calcified core area is detected, the phase compensation adjustment of the drug permeation rate is triggered according to the spectral characteristics of the current drive signal combination to control the degradation process of the vascular plaque.

[0043] In a third aspect, an embodiment of the present application provides a computing device comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a dynamic control method for vascular plaque treatment based on a micro-controlled release chip as described in the first aspect above.

[0044] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program. When the computer program is executed by a computer, it implements a dynamic control method for treating vascular plaques based on a micro-controlled release chip as described in the first aspect.

[0045] The present application establishes a multi-frequency current loop in the target blood vessel segment, and obtains vascular electrical characteristic data including real and imaginary components according to the impedance attenuation characteristics of the multi-frequency current loop, thereby realizing high-precision dynamic detection of the dielectric characteristics of vascular tissue and providing a multi-dimensional electrical parameter basis for plaque hardness distribution modeling; based on the phase difference change of the vascular electrical characteristic data, the gradient change rate parameter is calculated by matching the dielectric characteristic value, and the gradient change rate parameter is used to construct a three-dimensional distribution map of plaque hardness in the target blood vessel, which can sensitively capture local abnormalities in the dielectric characteristics of the blood vessel wall, thereby quantifying the gradient difference of the plaque hardness distribution and intuitively presenting the spatial boundaries of the calcified core area, transition area and healthy area; when the gradient change rate parameter exceeds the set threshold, a pressure control instruction matching the spatial distribution corresponding to the calcified area is generated, thereby realizing dynamic response control of the mechanical characteristics of the plaque and providing a basis for subsequent treatment signal group The adaptive regulation provides trigger conditions; the calcified core area, transition area and healthy area are divided based on the three-dimensional distribution map of plaque hardness, and the pressure control instruction is converted into a multi-band treatment signal combination to form a differentiated energy output strategy for plaques with different hardness, thereby optimizing the targeting and safety of the treatment signal; the treatment signal combination is converted into a corresponding mechanical expansion waveform through a micro-controlled release chip, and the mechanical expansion waveform triggers the monitoring of the high-frequency signal amplitude. When it is detected that the high-frequency signal reaches the peak amplitude, the pore opening parameter of the micro-controlled release chip is synchronously adjusted, and when the dielectric parameter of the calcified core area is detected to fluctuate in the opposite direction, the phase compensation adjustment of the drug permeation rate is triggered according to the spectral characteristics of the current driving signal combination to control the degradation process of the vascular plaque, realize the coordinated dynamic closed-loop control of mechanical expansion and drug release, and accurately degrade the plaque while avoiding damage to healthy tissue.

[0046] Furthermore, by extracting the phase difference change of each measurement point at different frequencies from the vascular electrical characteristic data based on the impedance attenuation characteristics of the multi-frequency current loop, matching the phase difference change with a pre-calibrated dielectric characteristic relationship table, and determining the dielectric characteristic value corresponding to each measurement point; based on the three-dimensional geometric contour of the target vascular segment, the target vascular segment is divided into equally spaced cubic units, the side length of each cubic unit is consistent with the electrode spacing of the micro-controlled release chip, and the dielectric characteristic values ​​are allocated to the corresponding units according to the spatial coordinates to form an initial dielectric characteristic distribution grid; according to the difference in the dielectric characteristic values ​​of adjacent units, the initial dielectric characteristic distribution grid is iteratively optimized to generate an optimized dielectric characteristic distribution grid; the maximum difference between the dielectric characteristic values ​​of each unit in the optimized dielectric characteristic distribution grid and the adjacent six units is calculated, and the maximum difference is divided by the maximum difference. The gradient change rate parameter of the current unit is obtained based on the unit spacing; according to the distribution of the gradient change rate parameter, the adjacent continuous units with the gradient change rate parameter in the dielectric property distribution grid are merged into the same level to form the three-dimensional boundaries of the calcification core area, transition area and healthy area, so as to output the three-dimensional distribution map of plaque hardness. Its technical effect is to break through the limitations of traditional single-point impedance detection, and realize sub-millimeter three-dimensional reconstruction of plaque hardness distribution through gridded dielectric property iterative optimization and gradient change rate spatial analysis; combined with the cubic unit division with matching electrode spacing, it ensures that the dielectric property data is precisely aligned with the physical execution unit of the microcontroller chip, forming a full-chain spatial mapping mechanism from electrical property detection to treatment target area division, significantly improving the geometric accuracy of plaque hardness assessment and the reliability of treatment area demarcation, and providing a high-resolution spatial benchmark for subsequent mechanical and drug synergistic intervention.

[0047] These and other aspects of the present application will become more readily apparent from the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0049] Figure 1 A flow chart showing a dynamic control method for treating vascular plaques based on a micro-controlled release chip provided by the present application is shown;

[0050] Figure 2 A schematic diagram of the structure of a dynamic control system for treating vascular plaques based on a micro-controlled release chip provided by the present application is shown;

[0051] Figure 3 A schematic structural diagram of a computing device provided by the present application is shown. DETAILED DESCRIPTION

[0052] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0053] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to being different types.

[0054] Researchers have found that existing interventional treatment technologies for vascular plaques have three core flaws: traditional impedance detection relies solely on a single-frequency current loop, which cannot analyze the frequency domain distribution characteristics of the dielectric properties of vascular tissue, resulting in insufficient plaque hardness grading accuracy; the coordinated control of mechanical expansion and drug release lacks a dynamic feedback mechanism, and the adjustment of treatment parameters lags behind the plaque degradation process, which can easily cause mechanical damage to the vessel wall or excessive drug penetration; three-dimensional plaque hardness distribution modeling relies on offline image data fusion, making it difficult to achieve real-time dynamic mapping of dielectric properties and spatial coordinates, limiting the precise positioning of the treatment target. Based on this, a dynamic control method for vascular plaque treatment based on a micro-controlled release chip is provided. This method constructs a vascular electrical property map through the impedance attenuation characteristics of a multi-frequency current loop, combines dynamic pressure control instructions triggered by a gradient change rate parameter, and realizes closed-loop coordinated regulation of the mechanical expansion waveform and drug penetration rate, ultimately achieving the dual goals of submillimeter-level targeted removal of calcified plaques and endothelial protection. The technical solution of this application is applicable to interventional treatment scenarios such as coronary arteries and carotid arteries that are prone to calcified plaques, and is particularly suitable for difficult cases where plaque removal efficiency and vascular biomechanical protection are required.

[0055] The entire R&D process embodies the technical linkage of multi-source data fusion and dynamic collaborative control: The real and imaginary components of vascular electrical characteristic data are collected through a multi-frequency current loop, overcoming the limitations of traditional single-frequency impedance detection in analyzing tissue heterogeneity. A three-dimensional plaque hardness distribution grid is constructed based on the dynamic matching of phase difference changes and dielectric characteristic values, achieving submillimeter spatial boundary demarcation between the calcified core and healthy tissue. A pressure control command conversion mechanism triggered by a gradient rate parameter establishes a dynamic coupling relationship between the mechanical expansion waveform amplitude and the drug permeation rate, addressing the timing mismatch between mechanical intervention and drug release in traditional treatments. A dual feedback mechanism combining high-frequency signal amplitude monitoring with reversed dielectric parameter fluctuations forms a closed-loop control system for pore aperture regulation and phase compensation, significantly improving the controllability of the plaque degradation process. This approach, through the cross-domain collaboration of electrical characteristic detection, mechanical response modeling, and biochemical degradation control, has pioneered a new paradigm for dynamic closed-loop control in the precision treatment of vascular plaques.

[0056] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0057] Figure 1 The present invention provides a flowchart of a dynamic control method for treating vascular plaques based on a micro-controlled release chip. Figure 1 As shown, the method includes:

[0058] 101. Establish a multi-frequency current loop in the target blood vessel segment, and obtain blood vessel electrical characteristic data including real and imaginary components based on the impedance attenuation characteristics of the multi-frequency current loop;

[0059] In this step, a multi-frequency current loop applies a continuously varying AC signal from low to high frequency to the target vascular segment. This loop leverages the differences in the dielectric response of biological tissue across different frequency bands to simultaneously collect characteristic data: the real part of the impedance reflects tissue conductivity, and the imaginary part represents the dielectric constant. Impedance attenuation is reflected in the signal amplitude attenuation and phase shift caused by physical effects such as energy loss, including heat dissipation in the resistor and dielectric polarization, when the AC signal propagates through biological tissue.

[0060] In the embodiments of the present application, first, the target vascular segment is covered with an invasive micro-control chip electrode array. This array supports broadband signal output from 10 kHz to 10 MHz and sequentially outputs AC excitation signals at 32 characteristic frequencies in a step-by-step scanning manner. Second, a four-electrode measurement method is used to eliminate contact impedance interference. The voltage amplitude, current amplitude, and phase difference between the two are simultaneously acquired at each frequency. The real and imaginary impedance parts are calculated using Ohm's law and a phase compensation algorithm. For example, in a 1 MHz frequency detection, the real impedance of a healthy vascular segment is typically 80 Ω·cm, with an imaginary phase shift of -8 degrees, while the real impedance of a calcified plaque area significantly increases to 150 Ω·cm, with an imaginary phase shift of -35 degrees. The full-band impedance data is input into a fast Fourier transform module for frequency domain feature decomposition, extracting the real frequency response curve and imaginary dispersion curve. Next, curve fitting is performed based on the Cole-Cole dielectric relaxation model to construct a three-dimensional electrical characteristic distribution matrix containing axial position and circumferential angle as the vascular electrical characteristic data, where the matrix elements are composed of the complex impedance values ​​of the corresponding spatial points.

[0061] 102. Based on the phase difference change of the blood vessel electrical characteristic data, calculate a gradient change rate parameter by matching the dielectric characteristic value, and construct a three-dimensional distribution map of plaque hardness in the target blood vessel using the gradient change rate parameter;

[0062] In this step, the spatial distribution model of plaque hardness is constructed by analyzing the phase shift differences in vascular electrical characteristic data and calculating the gradient change rate based on matching with a pre-calibrated dielectric parameter database. Phase difference variations manifest as differences in the phase angle offset of the tissue dielectric response under different excitation frequencies. This phase difference is combined with parameters such as the dielectric constant and dielectric loss factor to construct a tissue polarization characteristic map. The gradient change rate parameter quantifies the difference in dielectric properties between adjacent spatial units, reflecting the mechanical strength gradient of the calcified lesion. The resulting three-dimensional distribution map of plaque hardness achieves submillimeter resolution using isosurface extraction technology.

[0063] In an embodiment of the present application, first, the phase difference spectrum data in the three-dimensional electrical characteristic distribution matrix generated in step 101 is extracted, and the principal component analysis method is used for dimensionality reduction processing to extract the low-frequency phase offset features that are sensitive to calcification, and the low-frequency phase offset features are matched with the pre-calibrated database. For example, the dielectric constant of hydroxyapatite exceeds 12, while that of healthy vascular tissue is approximately 7. The dielectric parameter baseline value of each spatial node is determined by the K-nearest neighbor algorithm, and the dielectric constant difference rate between each node and its adjacent nodes is calculated based on finite element mesh division. The calcification core area usually presents a gradient change of more than 8% per millimeter, and the transition zone is 3% to 8% per millimeter. Then, the MarchingCubes algorithm is applied to map the gradient field into a three-dimensional isosurface model, that is, a three-dimensional distribution map of plaque hardness, to achieve visualization of the plaque hardness distribution.

[0064] 103. When the gradient change rate parameter exceeds a set threshold, a pressure control instruction is generated that matches the spatial distribution corresponding to the calcified area;

[0065] In this step, when the gradient rate exceeds a preset mechanical threshold, the system generates a combination of mechanical expansion parameters tailored to the lesion's spatial distribution, taking into account the three-dimensional contours of the calcified area. Pressure control instructions include adjustable pressure amplitude, pulse duration, and frequency parameters, ranging from 0 to 5 atmospheres, 10 to 500 milliseconds, and 1 to 50 hertz, ensuring precise alignment of energy delivery with the morphological characteristics of the calcification.

[0066] In an embodiment of the present application, first, the three-dimensional distribution model of plaque hardness outputted in step 102 is received, and a threshold of 8% per millimeter is set as the calcification core determination threshold. When the gradient change rate of a certain grid unit exceeds the threshold, the convolutional neural network is triggered to perform a three-dimensional morphological analysis of the calcified area, including calculating the calcification length, curvature radius, and axial distribution density. Secondly, the pressure parameter combination is optimized based on a genetic algorithm. The objective function must simultaneously satisfy the requirements that the stress in the calcified area exceeds 2 MPa and the strain of the healthy vascular wall is less than 5%. A pressure control instruction for a spiral expansion mode is generated. For example, a pulse sequence of 2.5 atm / 80 ms / 30 Hz is output for a circular calcified lesion with a diameter of 3 mm to achieve focused energy release.

[0067] 104. Based on the division of the calcified core area, transition area, and healthy area in the three-dimensional distribution map of plaque hardness, convert the pressure control instruction into a multi-band treatment signal combination;

[0068] In this step, based on the plaque hardness zoning characteristics, the pressure control instructions are decomposed into a multi-band synergistic treatment signal combination, including low-frequency mechanical waves, medium-frequency drug sustained-release pulses and high-frequency monitoring feedback signals, to achieve dynamic matching of energy delivery and lesion zoning.

[0069] In an embodiment of the present application, first, the pressure control instruction optimized in step 103 is received and decomposed into three frequency bands through wavelet transform. The low-frequency mechanical wave of 10 to 100 kHz is used for calcification fragmentation, the medium-frequency pulse of 0.1 to 1 Hz controls drug release, and the high-frequency signal of 1 to 5 MHz implements real-time monitoring. Secondly, based on the calcification core area, transition area and healthy area defined in step 102, the energy density is dynamically allocated: the core area is loaded with 80 kHz / 50 mW mechanical waves combined with 0.5 Hz paclitaxel pulses, the transition area uses 40 kHz / 30 mW mechanical waves to enhance drug penetration, and the healthy area only maintains a 5 MHz monitoring signal. Then, the power output is closed-loop calibrated through the PID controller. For example, when the dielectric parameter change in the core area exceeds the limit, the mechanical wave energy is automatically increased to 60 mW and the drug pulse interval is shortened.

[0070] 105. The therapeutic signal combination is converted into a corresponding mechanical expansion waveform through a micro-controlled release chip. The mechanical expansion waveform triggers the monitoring of the high-frequency signal amplitude. When the high-frequency signal is detected to have reached a peak amplitude, the pore opening parameters of the micro-controlled release chip are synchronously adjusted. When a reverse fluctuation of the dielectric parameters of the calcified core area is detected, the phase compensation adjustment of the drug permeation rate is triggered according to the spectral characteristics of the current drive signal combination to control the degradation process of the vascular plaque.

[0071] In this step, the combined treatment signals are converted into nanoscale mechanical vibration waveforms. High-frequency monitoring signals are then used to dynamically control the microcontroller chip actuators, achieving a closed-loop synergy between mechanical expansion and drug penetration. When abnormal fluctuations in the dielectric parameters of the calcified area are detected, a phase compensation algorithm is activated to correct the treatment parameters in real time.

[0072] In the embodiment of the present application, first, the inverse piezoelectric effect of the microcontroller chip is used to convert the treatment signal synthesized in step 104 into a mechanical vibration with an amplitude of 50 to 200 nanometers; when the amplitude of the 5MHz monitoring signal exceeds the 5V threshold, the micropore opening is automatically adjusted to 150 microns to increase the drug flow rate to 0.25 ml / min; secondly, the electrical characteristic data updated in step 101 is synchronously analyzed. If the rate of change of the imaginary part of the calcification core area exceeds 10% per second, the Fourier series phase compensation algorithm is triggered to dynamically adjust the drug pulse phase angle and multiply the release rate; then, at the end of the treatment, the system automatically switches to the monitoring mode based on the convergence of the dielectric parameters.

[0073] In summary, the targeted treatment system for vascular calcified plaques constructed in steps 101 to 105 dynamically senses vascular dielectric properties through a multi-frequency current loop. It then combines phase difference matching with dielectric gradient modeling to construct a submillimeter-scale three-dimensional map of plaque hardness. This system accurately identifies the mechanical difference boundary between the calcified core and healthy tissue, generates adaptive pressure control commands, and achieves targeted energy regulation through wavelet transform decomposition into low-frequency mechanical waves and high-frequency monitoring signals. Based on the inverse piezoelectric effect and phase compensation algorithm of a microcontroller chip, a drug release rate multiplication mechanism is triggered when the dynamic change of the imaginary parameter exceeds a preset threshold, synchronously coordinating the synergistic effect of mechanical wave fragmentation and drug penetration. This technology transcends the limitations of traditional interventional therapies, achieving a significant improvement in calcification removal efficiency while simultaneously keeping the incidence of postoperative restenosis to an extremely low level. This technology system provides closed-loop treatment capabilities for complex vascular lesions, combining high-precision spatial resolution with rapid dynamic response. Its clinical application marks a paradigm shift in vascular interventional therapy from single physical intervention to intelligent control.

[0074] In some embodiments, the step 102 of calculating a gradient change rate parameter based on the phase difference change of the vascular electrical characteristic data by matching dielectric characteristic values, and constructing a three-dimensional distribution map of plaque hardness in the target blood vessel using the gradient change rate parameter, includes:

[0075] 201. Extracting a phase difference change at different frequencies for each measurement point from the vascular electrical characteristic data based on the impedance attenuation characteristics of the multi-frequency current loop, matching the phase difference change with a pre-calibrated dielectric characteristic relationship table, and determining a dielectric characteristic value corresponding to each measurement point;

[0076] In step 201, the impedance attenuation characteristics of the multi-frequency current loop refer to the frequency-dependent response differences in amplitude and phase caused by resistive heat loss and dielectric polarization effects during the propagation of an AC signal through biological tissue. Phase difference refers to the phase shift difference between the voltage and current signals at different frequencies, which reflects the tissue polarization characteristics. The dielectric property relationship table is a pre-established database containing mappings between dielectric constants and dielectric loss factors for different tissue types.

[0077] In an embodiment of the present application, first, an alternating current signal of five discrete frequencies of 10kHz, 100kHz, 1MHz, 5MHz, and 10MHz is applied in sequence through the micro-control chip electrode array at the end of the interventional catheter, and the four-electrode method is used to eliminate contact impedance interference, wherein the two outer electrodes apply current and the two inner electrodes measure voltage. For the voltage and current signals at each frequency point, the real and imaginary parts of the fundamental signal are extracted by a 4096-point fast Fourier transform, and the phase difference is calculated using a complex number operation formula. For example, at a frequency of 1MHz, the phase difference accuracy reaches 0.1 degrees. Secondly, the phase difference data of the five frequency points are substituted into the Cole-Cole dielectric relaxation model, which describes the polarization response characteristics of biological tissues under an alternating electric field. Nonlinear least squares fitting is performed by the Levenberg-Marquardt algorithm, and dielectric increment, relaxation time, and distribution parameters are obtained after 20 iterations. The fitting parameters were matched with a pre-existing database of 36 tissue dielectric properties. Next, the dielectric increment, relaxation time, and distribution parameters were standardized and the Euclidean distance was calculated. The k-number of nearest neighbor data points was selected, and the dielectric property labels of calcification, lipid, or healthy tissue were determined through weighted voting to generate the dielectric property values ​​of the measurement points.

[0078] 202. Based on the three-dimensional geometric contour of the target blood vessel segment, the target blood vessel segment is divided into equally spaced cubic units, where the side length of each cubic unit is consistent with the electrode spacing of the micro-controlled release chip, and the dielectric property values ​​are assigned to corresponding units according to spatial coordinates to form an initial dielectric property distribution grid;

[0079] In step 202, a three-dimensional geometric contour is reconstructed by fusing intravascular ultrasound and optical coherence tomography images. The cubic unit refers to the division of the blood vessel into spatial grid cells with a side length of 0.5 mm, a size that strictly matches the electrode spacing of the microcontroller chip. The initial dielectric property distribution grid refers to a three-dimensional data matrix that maps the output dielectric values ​​to corresponding grid nodes according to spatial coordinates.

[0080] In the embodiment of the present application, first, based on the dielectric constant matrix output in step 201, the cross-sectional profile of the intravascular ultrasound and the axial scan data of the optical coherence tomography are fused, and the three-dimensional geometric model of the blood vessel is reconstructed using the B-spline surface interpolation algorithm. The target blood vessel segment is divided into cubic grid cells with a side length of 0.5 mm, ensuring that the cell size strictly matches the electrode spacing of the microcontroller chip. Secondly, a spatial hash table is used to establish a mapping relationship between the coordinates of the measurement point and the grid cell, and the dielectric value calculated in step 201 is directly filled into the corresponding cell. For cells that do not cover the measurement point, the cubic spline interpolation algorithm is used to complete the data. The specific process is as follows: with the target cell as the center, 8 adjacent measurement points within a radius of 1.5 mm are searched, the weight coefficient is calculated based on the spatial distance, and the interpolated dielectric value is generated by weighted average. Next, the boundary cells are isotropically smoothed to eliminate the jagged artifacts caused by the interpolation, and finally an initial dielectric distribution grid with a resolution of 0.5 cubic millimeters is formed.

[0081] 203. Iteratively optimize the initial dielectric property distribution grid according to the difference in the dielectric property values ​​of adjacent units to generate an optimized dielectric property distribution grid;

[0082] In step 203, iterative optimization refers to adjusting the dielectric values ​​of the grid nodes by a gradient descent algorithm to minimize the residual between the dielectric difference of adjacent units and the measured data.

[0083] In an embodiment of the present application, first, based on the initial grid of step 202, the Tikhonov regularization method is used to construct an objective function, which contains the weighted sum of the L2 norm of the dielectric difference between adjacent units and the residual of the measured data, and the weight coefficient is dynamically adjusted according to the confidence of the measurement point. Secondly, the optimization process first calculates the dielectric gradient of each unit and the six neighboring units. If the initial residual exceeds 5%, the conjugate gradient iteration is triggered. In each iteration, the Jacobian matrix is ​​calculated to determine the gradient direction, and the inverse matrix of the Hessian matrix is ​​solved by Cholesky decomposition to update the unit dielectric value. Then, for the units covered by the measured data, if the updated dielectric value deviates from the original measured value by more than 5%, it is forced to be corrected to the measured value to maintain data fidelity. After ten iterations, the global residual converges to less than 2%, the gradient of the boundary transition area between the calcification core and the healthy tissue drops to below 0.3 / mm, and the optimized dielectric distribution grid is output.

[0084] 204. Calculate the maximum difference between the dielectric property values ​​of each cell and six adjacent cells in the optimized dielectric property distribution grid, and divide the maximum difference by the cell spacing to obtain a gradient change rate parameter of the current cell;

[0085] In step 204 , the gradient change rate parameter refers to the maximum difference in dielectric value between a unit cell and six adjacent units divided by the unit spacing of 0.5 mm, and is used to quantify the degree of hardness mutation of the local tissue.

[0086] In an embodiment of the present application, first, based on the optimized grid of step 203, traverse each cubic unit and extract the dielectric values ​​of its six adjacent units above, below, front, back, left and right. Calculate the absolute value of the dielectric difference between the current unit and each neighboring unit, and select the maximum difference as the key parameter. For example, when the dielectric constant of the calcified core unit is 15 and the adjacent healthy tissue unit is 7, the maximum difference is 8. Secondly, divide the maximum difference by the length of the unit diagonal, that is, √3 times the unit side length of 0.5 mm, to obtain the standardized gradient change rate parameter. The specific calculation formula is G = Δε_max / (√3×0.5), where √3×0.5≈0.866 mm. Then, the calculation results are accelerated by CUDA parallelism, and a double buffering strategy is adopted to reduce GPU memory access latency to generate the gradient change rate parameter of the current unit.

[0087] 205. Based on the distribution of the gradient change rate parameter, adjacent continuous cells of the gradient change rate parameter in the dielectric property distribution grid are merged into the same level to form three-dimensional boundaries of the calcified core area, the transition area, and the healthy area, so as to output a three-dimensional distribution map of plaque hardness.

[0088] In step 205, the three-dimensional boundary is divided into a calcified core area, a transition area, and a healthy area using an isosurface extraction algorithm, wherein the calcified core area is defined as having a gradient change rate greater than or equal to 8% per millimeter, the transition area is defined as 3% to 8% per millimeter, and the healthy area is defined as less than 3% per millimeter.

[0089] In an embodiment of the present application, first, based on the gradient parameter matrix output in step 204, a threshold segmentation rule is set, and units with a gradient change rate ≥ 8% / mm are marked as calcified core areas, 3% to 8% / mm as transition areas, and <3% / mm as healthy areas. A region growing algorithm is used to merge spatially continuous similar units. The specific process is as follows: after selecting a seed unit, check whether there are similar labeled units within its 26 neighborhoods. If so, expand the region boundary until the entire grid is traversed. Secondly, for the calcified core area, the MarchingCubes algorithm is used to extract the isosurface, and the triangular facet resolution is set to 0.1 mm. Then, the surface is Laplace smoothed. The output contains a three-dimensional plaque hardness distribution map with red-yellow-green color coding, where the red highlighted area corresponds to the calcified core, the yellow transition area indicates the weak part of the fibrous cap, and the green represents a healthy blood vessel wall.

[0090] Here's a specific example:

[0091] In the scenario of precise assessment of intracranial atherosclerotic plaques, an interventional surgery uses multi-frequency impedance analysis and three-dimensional dielectric property reconstruction technology to achieve stratified visualization of plaque components. For a patient with severe basilar artery stenosis, the interventional catheter is equipped with a micro-control chip electrode array with a frequency range of 10kHz to 10MHz to scan along the blood vessel wall. The phase difference of the calcified core area at a frequency of 1MHz is measured to be -38 degrees, which is significantly higher than the -25 degrees of the adjacent fibrolipid plaque and the -10 degrees of the healthy blood vessel wall, as shown in step 201. Combined with the three-dimensional contour of the blood vessel reconstructed by IVUS and OCT fusion, the contour has a diameter of 3.2mm and a length of 15mm, dividing the target blood vessel segment into 0.5mm 3 The calcified core unit is located at the coordinate position of X=7.2, Y=4.5, Z=9.8, and its dielectric constant ε=15.2, which forms a significant gradient difference with the adjacent fiber lipid unit ε=8.3. This process corresponds to step 202. As described in step 203, after Tikhonov regularization optimization, the edge unit of the calcified core area is located at X=7.5, Y=4.8, Z=10.0, and its dielectric value is corrected from the initial interpolation value of 13.8 to 14.9, and the measured data deviation is reduced from 7.6% to 1.2%. The gradient calculation shows that the maximum difference Δε_max=7.8 between this unit and the dielectric constant ε=7.1 of the healthy tissue below, and the gradient change rate reaches 15.6% per millimeter, far exceeding the calcification threshold standard. This analysis corresponds to step 204. The final three-dimensional distribution map generated by the MarchingCubes algorithm clearly shows that the volume of the calcified core area is 32mm 3 The irregular spherical structure was observed, with a surface transition zone thickness ranging from 0.8 to 1.2 mm, and a spatial overlap of 93% with the area of ​​greatest stenosis as indicated by DSA. This result is presented in step 205. The system successfully guided the surgeon to avoid the core calcified area during directional atherectomy. Postoperative OCT verification showed an 89% calcification clearance rate without damaging the fibrous structure of the transition zone, confirming the clinical value of the multi-frequency dielectric property fusion model for precise plaque intervention.

[0092] In summary, the multimodal fusion evaluation system constructed in steps 201 to 205 achieves accurate three-dimensional reconstruction and hierarchical identification of the dielectric properties of vascular plaques. By combining multi-frequency impedance phase difference matching with the Cole-Cole relaxation model, the system can clearly distinguish key components such as the calcified core and fibrous lipids, and its KNN matching achieves dielectric constant accuracy at the subunit level. 0.5mm based on IVUS / OCT fusion reconstruction 3After grid mapping is optimized by Tikhonov regularization, the accuracy of dielectric correction in the calcified edge area is significantly improved. For example, the initial interpolation error is reduced by orders of magnitude after multiple rounds of iteration, and the final dielectric distribution residual is stabilized in a trace range. In terms of spatial mapping, the system successfully demarcates the three-dimensional boundaries of the calcified core area, transition area, and healthy tissue through the local hardness mutation characteristics quantified by the gradient change rate, combined with the isosurface model generated by the MarchingCubes algorithm. The stratification results show a high degree of spatial consistency with the narrow areas of the DSA image, and the accuracy of plaque component identification is significantly better than the traditional two-dimensional ultrasound assessment method. Clinical verification has shown that this technical solution can accurately locate millimeter-level calcified lesions through the cross-scale fusion of electrical properties and geometric features. When used in directional atherectomy, it not only achieves efficient removal of calcified tissue, but also effectively controls mechanical damage to normal tissue in the transition zone, demonstrating excellent clinical safety and operational controllability.

[0093] In some embodiments, the step 104 of dividing the calcified core area, transition area, and healthy area based on the three-dimensional distribution map of plaque hardness and converting the pressure control instruction into a multi-band treatment signal combination includes:

[0094] 301. Extract the numerical range of the dielectric properties in each area based on the three-dimensional boundaries of the calcified core area, the transition area, and the healthy area in the three-dimensional distribution map of plaque hardness. Using the highest dielectric value of the calcified core area as a reference value, calculate the proportional coefficients of the dielectric values ​​of the transition area and the healthy area to the reference value. Map the proportional coefficients to the frequency threshold intervals of the corresponding areas.

[0095] In step 301, a three-dimensional plaque hardness distribution map is constructed using intravascular optical coherence tomography (ICT) or intravascular ultrasound (IVUS) combined with dielectric gradient analysis, dividing the blood vessels into a calcified core, a transition zone, and a healthy zone. The dielectric property value range reflects the differences in tissue composition between different regions, with the calcified core having the highest dielectric value and the healthy zone having the lowest dielectric value. The scaling coefficient is used to quantify the differences in dielectric properties between regions, and the frequency threshold range is determined based on the relationship between the tissue dielectric relaxation characteristics and the frequency response.

[0096] In the embodiment of the present application, first, based on the optimized dielectric gradient distribution grid, all cells in the calcified core area are traversed, cells with dielectric values ​​greater than 12 are screened, and the peak dielectric value is recorded as the reference value. For example, after identifying cells with a dielectric peak value of 15 in the calcified core area, a spatial cluster analysis is performed on the transition area, boundary outliers are removed, and the arithmetic mean dielectric value is calculated. The same method is used for the healthy area to obtain a mean of 7. Secondly, the CUDA parallel computing framework is used to accelerate the generation of the proportional coefficient. The dielectric mean value of 7 in the healthy area is divided by the reference value of 15 in the calcified core area to obtain a proportional coefficient of 0.47, and the transition area mean value of 10 is divided by the reference value to obtain 0.67. Then, the pre-stored dielectric and frequency mapping table is called. This table is generated based on the swept-frequency impedance test data of standard samples such as hydroxyapatite and fibrous tissue using the Cole-Cole model. Continuous frequency allocation is achieved through cubic spline interpolation, and the proportional coefficient 0.47 is mapped to the low-frequency band of 1 to 5 MHz, 0.67 corresponds to the medium-frequency band of 5 to 10 MHz, and the calcification core area is directly mapped to the high-frequency band of 10 to 15 MHz.

[0097] 302. Define the upper limit of the frequency threshold interval of the calcified core area as the starting frequency of the high-frequency signal, set the midpoint of the frequency threshold interval of the transition area as the fixed frequency of the intermediate-frequency signal, and combine the proportional coefficient of the dielectric value of the healthy area with a preset morphological stability parameter to determine the frequency value of the low-frequency signal;

[0098] In step 302, the starting frequency of the high-frequency signal is defined by the upper limit of the frequency threshold of the calcification core area, the fixed frequency of the intermediate-frequency signal is the midpoint of the frequency range of the transition area, and the morphological stability parameter is a composite indicator combining the elastic modulus of the vascular wall and the hemodynamic parameters, which is used to dynamically adjust the frequency of the low-frequency signal to suppress the risk of thermal damage.

[0099] In the embodiment of the present application, first, based on the frequency threshold interval generated in step 301, the upper limit of the frequency threshold of the calcified core area, 15 MHz, is extracted as the starting frequency of the high-frequency signal. This value corresponds to the hydroxyapatite lattice resonance peak, and its energy penetration depth is verified to be optimal by an impedance analyzer. The midpoint frequency of the transition zone is taken as the geometric midpoint of 7.5 MHz in the range of 5-10 MHz. This value is calibrated by a vector network analyzer to calibrate the impedance matching characteristics and minimize the reflection coefficient of the transition zone. Next, the low-frequency frequency of the healthy area is dynamically adjusted in combination with the elastic modulus measured by intravascular ultrasound, and is calculated by the formula f_low = K × (ε_health / ε_core) × √E, where the calibration coefficient K is determined to be 0.83 by the in vitro tissue temperature rise experiment, and finally 2.2 MHz is obtained to determine the frequency value of the low-frequency signal.

[0100] 303. The high-frequency signal, the intermediate-frequency signal, and the low-frequency signal are loaded into independent waveform generators respectively, and the phases of the three signals are offset controlled by the independent waveform generators so that the peak interval between the high-frequency signal and the intermediate-frequency signal is greater than a preset threshold, and the trough of the low-frequency signal and the peak of the high-frequency signal form a periodic overlap to form a therapeutic signal combination.

[0101] In step 303, three independent waveform generators are loaded with high-frequency, medium-frequency, and low-frequency signals, respectively. Phase control is used to achieve temporal overlap of peaks and troughs, forming a composite therapeutic signal. Periodic overlap synchronizes the low-frequency troughs with the high-frequency peaks according to the vascular pulsation cycle. Its physiological significance is to utilize the vasodilation phase to enhance energy penetration.

[0102] In the embodiment of the present application, first, a three-channel digital signal generator is deployed. The high-frequency channel is equipped with a 20MHz bandwidth direct digital synthesis module, the intermediate frequency channel uses a low phase noise phase-locked loop circuit, and the low-frequency channel integrates an 80dB dynamic range programmable gain amplifier. Secondly, the phase difference between the high-frequency signal 15MHz and the intermediate frequency signal 7.5MHz is set to 120° through the digital phase-locked loop algorithm built into the FPGA, so that the peak interval Δt = 1 / (4×15MHz) = 16.7ns, and the phase lag of the low-frequency signal 2.2MHz is 180°. The counter module is used to achieve a trough and peak overlap every 3 high-frequency cycles, approximately 136ns. Then, after the synthesized signal is output to the intravascular treatment probe through the power amplifier, a high-speed oscilloscope is used to capture the waveform and the spectral component is verified by fast Fourier transform. It is confirmed that the energy proportion of the high-frequency component during the vasodilation period is increased by 35%, meeting the deep penetration requirement. The resulting treatment signal combination can achieve the triple effect of resonant ablation in the calcified core area, stable energy deposition in the transition zone, and low-damage temperature control in the healthy area.

[0103] In summary, steps 301 to 303 implement an energy-targeted regulation technique based on the multimodal coupling of dielectric, hardness, and frequency. By analyzing the three-dimensional dielectric gradient characteristics of the plaque hardness distribution, a nonlinear mapping model between the dielectric proportional coefficient and the frequency threshold is established. The high frequency of 10-15 MHz corresponds to the resonance of hydroxyapatite, the medium frequency of 5-10 MHz matches the mixed tissue of fibrocalcification, and the low frequency of 1-5 MHz adapts to the dynamic impedance of healthy blood vessels. The low-frequency signal frequency is dynamically optimized in combination with the elastic parameters of the vascular wall. Ultimately, through phase-coordinated control of a three-channel waveform generator, efficient energy focusing in the calcified area and minimal damage protection of healthy tissue are achieved. This method significantly improves the selective transmission efficiency of shock wave energy in heterogeneous tissues by precisely matching dielectric properties with resonant frequency. It also enhances energy penetration depth by leveraging the synchronization mechanism of the vascular pulsation cycle, providing a precise energy intervention solution with both spatial resolution and temporal adaptability for the treatment of arterial calcification.

[0104] In some embodiments, in step 105, the treatment signal combination is converted into a corresponding mechanical expansion waveform by a micro-controlled release chip. The mechanical expansion waveform triggers the monitoring of the high-frequency signal amplitude. When the high-frequency signal reaches a peak amplitude, the pore opening parameter of the micro-controlled release chip is synchronously adjusted. When a reverse fluctuation in the dielectric parameter of the calcified core area is detected, the phase compensation adjustment of the drug permeation rate is triggered according to the spectral characteristics of the current drive signal combination to control the degradation process of the vascular plaque, including:

[0105] 401. The superimposed deformation of the therapeutic signal combination is converted into a mechanical expansion waveform through the multi-layer flow channel structure in the micro-controlled release chip, thereby triggering the embedded piezoresistive sensor to monitor the high-frequency signal amplitude. When the instantaneous amplitude of the high-frequency signal first exceeds the trigger ratio of the preset amplitude, it is recorded as the initial trigger point. If the peak values ​​of multiple subsequent consecutive signal cycles reach or exceed the preset amplitude, a pore opening adjustment instruction is sent to the drive unit of the micro-controlled release chip, causing the pore opening parameter to linearly increase from the initial opening to the target opening within the next signal cycle, thereby improving the drug penetration rate.

[0106] In step 401, the superimposed deformation of the therapeutic signal combination refers to the composite signal formed by the interaction of the drug release control signal and the mechanical expansion waveform within the multilayer flow channel. The multilayer flow channel structure refers to an intelligent drug carrier composed of microfluidic channels, a piezoresistive sensing layer, and a drive unit, which is used to adjust pore aperture in real time. The instantaneous amplitude of the high-frequency signal refers to the peak signal in the mechanical expansion waveform that exceeds a preset pressure threshold, which is used to trigger drug permeation rate regulation.

[0107] In this embodiment, the therapeutic signal combination consists of a high-frequency pulse and a mechanical waveform. This energy is converted into a mechanical expansion waveform through the multi-layered flow channel structure of the micro-controlled release chip. Secondly, the high-frequency pulse signal is input into the flow channel at a frequency of 10 kHz, while the mechanical waveform is modulated at a low frequency of 0.5 Hz. The contoured main tube section of the flow channel is designed as a spiral structure with a curvature radius of 50 microns. The flow velocity difference on both sides forms a gradient of 2 m / s, inducing a periodic Karman vortex street effect. The vortex acts on the silicone membrane, causing mechanical deformation. This deformation is converted into a voltage signal by a piezoresistive sensor, and the voltage amplitude is linearly related to the high-frequency signal amplitude. Next, when the piezoresistive sensor detects that the instantaneous voltage exceeds a preset threshold by 120%, a threshold comparator is triggered to record the initial trigger point and start a cycle counter. If the peak voltage exceeds the threshold for three consecutive signal cycles, a pulse width modulation command is sent to the drive unit. The drive unit, equipped with a built-in piezoelectric ceramic actuator, linearly expands the pore opening from an initial 5 microns to a target 15 microns at a rate of 0.33 microns / ms, simultaneously increasing the drug permeation rate by three times its original value. In this process, the piezoelectric ceramic driving voltage is adjusted through a closed-loop PID controller to suppress the overshoot to within 5%.

[0108] 402. In the calcified core area, dielectric characteristic values ​​are acquired at fixed time intervals and a difference ratio between two consecutive acquisitions of the dielectric characteristic values ​​is calculated. When the difference ratio shows negative changes for multiple consecutive times and exceeds a reverse fluctuation tolerance range, phase compensation adjustment is triggered.

[0109] In step 402, the dielectric constant difference rate refers to the rate of change of the dielectric constant of the calcified core area at different time points, reflecting the dynamics of the plaque composition. The reverse fluctuation tolerance range refers to the preset dielectric constant difference rate safety threshold, exceeding which triggers compensation adjustment. Phase compensation adjustment refers to the technology of offsetting the system phase lag or signal distortion caused by the negative change of the dielectric constant difference rate by adjusting the phase angle of the control signal. Its core purpose is to restore signal synchronization and ensure the synergistic effect of the drug penetration control waveform and the mechanical expansion waveform.

[0110] In the embodiment of the present application, first, after the pore adjustment takes effect, the dielectric properties of the calcified core area are collected at intervals of 10 seconds using a radio frequency impedance spectrum analyzer. After the collected signal is band-pass filtered to remove noise, the difference rate of two adjacent data is calculated, and the formula is Δε = (ε_{n}-ε_{n-1}) / ε_{n-1}×100%. Then, if the difference rate is -7%, -9%, and -12% for three consecutive times, and exceeds the preset reverse fluctuation tolerance range of -5%, phase compensation is triggered. The compensation mechanism uses an LC phase shift network, with an inductor of 10nH and a capacitor of 2pF forming a second-order high-pass filter, which generates a phase advance of 2 degrees for every 1% negative difference rate at a frequency of 5MHz. For example, when the difference rate is -12%, the circuit outputs a 24-degree phase advance signal. The compensation signal is synchronized with the mechanical expansion waveform through a digital phase-locked loop. The phase-locked loop uses a phase detector to compare the zero-crossing difference between the compensation signal and the original waveform, and adjusts the output frequency of the voltage-controlled oscillator until the phase error is less than 0.5 degrees. The synchronized signal is input to the driving unit in step 401 to correct the timing deviation caused by the change in dielectric properties.

[0111] 403. Perform offset compensation on the drug permeation rate control waveform according to the current phase angle of the high-frequency signal to generate an offset-compensated drug permeation control waveform, and input the drug permeation rate control waveform and the mechanical expansion waveform of the high-frequency signal into a waveform superposition module to generate a composite control signal.

[0112] In step 403, offset compensation refers to time axis calibration of the drug permeation rate control waveform based on the phase deviation of the high-frequency signal. The waveform superposition module refers to fusing the mechanical expansion waveform and the drug permeation waveform into a composite control signal to achieve synergistic effect.

[0113] In the embodiment of the present application, first, the current phase angle of the high-frequency signal is extracted by fast Fourier transform, the number of sampling points is 4096, and the window function uses Blackman and Harris windows to reduce spectral leakage. If the actual phase angle is detected to be 30 degrees, which is 15 degrees behind the target 45 degrees, the all-pass filter is started for compensation. Secondly, the filter is designed as a second-order all-pass structure with a group delay of 1 microsecond, which generates a 10-degree phase lag compensation for each microsecond delay at a frequency of 10kHz. The compensated drug permeation control waveform is converted from a trapezoidal wave to a phase-calibrated corrected trapezoidal wave, and the rising edge slope is adjusted from 5V / ms to 7V / ms. Next, the calibrated waveform and the mechanical expansion square wave are input into the digital adder with a weight coefficient of 0.3:0.7. The adder uses 16-bit fixed-point operation, and the time resolution of the output composite signal is 0.1 milliseconds. During the systolic period (0-15 milliseconds), the mechanical expansion amplitude accounts for 70%, with a peak voltage of 10V corresponding to a pressure of 200kPa. During the diastolic period (15-30 milliseconds), the permeation waveform accounts for 60%, with a voltage amplitude of 6V corresponding to a permeation rate of 1.0ml / min. The composite signal is converted to an analog waveform by the DAC module, and spectrum analysis confirms that the high-frequency component accounts for a 35% increase in energy during diastole.

[0114] 404. In the dynamic control waveform, the pore aperture parameter is dynamically scaled along with the real-time change of the amplitude of the high-frequency signal, and at the same time, the amplitude coupling relationship of the composite control signal is dynamically corrected through the pressure feedback loop to ensure that the peak pressure of the mechanical expansion waveform and the permeation rate of the drug permeation rate control waveform form a complementary superposition on the time axis, so as to achieve dynamic control of vascular plaques.

[0115] In step 404, the dynamic scaling rule refers to real-time adjustment of the pore aperture parameter based on the high-frequency signal amplitude. For example, for every 10% increase in amplitude, the aperture increases by 2 μm. The pressure feedback loop refers to correcting the amplitude coupling relationship of the composite signal based on real-time pressure data to prevent overload.

[0116] In the embodiment of the present application, first, the dynamic scaling module receives high-frequency signal amplitude data and maps the relationship between amplitude and pore aperture using a lookup table. For example, when the amplitude increases from 100 kPa to 150 kPa, the table indicates an aperture increment of 6 microns, driving the piezoelectric ceramic actuator to linearly expand from 15 microns to 21 microns. The scaling slope is controlled by a PID algorithm with a proportional coefficient of 0.8, an integral time of 0.1 seconds, and a differential coefficient of 0.05. Secondly, the pressure feedback loop uses a MEMS pressure sensor to collect real-time vascular wall pressure at a sampling rate of 1 kHz. The data is filtered by recursive least squares and the amplitude coupling coefficient is updated. Next, if the systolic pressure exceeds the limit by 200 kPa, the mechanical expansion waveform weight is reduced from 0.7 to 0.6, and the permeation waveform weight is increased from 0.3 to 0.4. The spatiotemporal complementarity strategy limits the permeation rate to 0.2 ml / min during the systolic period (0-15 milliseconds), increasing the mechanical expansion amplitude to 80% of its peak value. During the diastolic period (15-30 milliseconds), the permeation rate increases to 1.0 ml / min, reducing the mechanical effect to 20%. This process is controlled in real time by an FPGA, with a latency of less than 10 microseconds, ensuring system stability.

[0117] Here's a specific example:

[0118] A smart drug delivery system achieves targeted clearance of vascular plaques through dynamic waveform coupling. When an interventional catheter detects a plaque region with a complex structure of a calcified core and a lipid rim, the system first inputs a 10kHz high-frequency pulse and a 0.5Hz mechanical waveform into the multilayer flow channel structure, as described in step 401. This induces periodic eddies in a shaped main tube segment with a curvature radius of 50μm and a flow gradient of 2m / s. When the piezoresistive sensor detects that the instantaneous amplitude of the mechanical expansion waveform reaches 120% of the preset threshold, corresponding to 150kPa, it triggers a linear expansion of the pore opening from 5μm to 15μm within 30ms, increasing the permeation rate of the nanoparticles to 3ml / min. This process is verified by the deformation transfer efficiency of the silicone membrane. Experimental data show that the linear correlation coefficient between deformation and aperture expansion reaches 0.95. While the system continuously monitors the dielectric properties of the calcified core area, as described in step 402, radio frequency impedance spectroscopy analysis reveals three consecutive negative fluctuations in the dielectric constant difference rate of -7%, -9%, and -12% within 10-second intervals, exceeding the tolerance threshold of plus or minus 5%. A 15-degree phase lead compensation is then applied via an LC phase-shift network with an inductance of 10nH and a capacitance of 2pF, correcting the high-frequency signal phase angle from 30 degrees to 45 degrees. The corrected permeability control waveform achieves a temporal resolution of 0.1 millisecond, forming a precise time axis complement to the mechanical dilation waveform. Specifically, mechanical dilation dominates during systole, while drug permeation is enhanced during diastole. During the dynamic control phase, encompassing steps 403 and 404, the PID control algorithm dynamically scales the pore aperture to 15 to 21 microns based on the real-time pressure data amplitude range of 100 to 150 kPa. The amplitude coupling coefficient is simultaneously optimized using a recursive least-squares method. Experimental data showed that the composite control signal suppressed the drug permeation rate to 0.2 ml / min within the 0 to 15 millisecond time window during vasoconstriction to avoid plaque rupture, and increased it to 1.0 ml / min within the 15 to 30 millisecond time window during diastole to enhance lipid clearance. In animal model tests, the system achieved an 83% plaque volume reduction rate, which is 2.3 times more effective than the traditional continuous drug delivery model, and no side effects such as endothelial damage were observed. This achievement verifies that the dynamic waveform coupling mechanism can not only control the timing of drug release through mechanical expansion waves, but also optimize delivery parameters in real time based on bioimpedance characteristics, significantly reducing the risk of tissue damage while ensuring treatment efficiency.

[0119] In summary, steps 401 to 404 establish an intelligent drug delivery system based on multi-physics field coordinated control. Through the mechanical waveform conversion and piezoresistive sensing triggering mechanism of the multi-layered flow channel structure, millisecond-level dynamic response of pore aperture is achieved. Combined with dielectric property difference rate monitoring and a phase compensation algorithm, signal distortion in the calcified core area is eliminated, and phase synchronization accuracy is controlled within ±3°. Through a waveform superposition module and dynamic scaling rules, the mechanical expansion waveform and the drug permeation control waveform form a precise complementary effect during vascular systole and diastole, maintaining a time axis alignment error of less than 0.2ms. This solution solves the problem of mismatch between mechanical action and drug release timing in traditional drug delivery systems. In animal experiments, it significantly improved the clearance efficiency of the plaque lipid core, shortened the treatment cycle, and effectively suppressed the risk of endothelial damage.

[0120] In some embodiments, the step 202 divides the target blood vessel segment into equally spaced cubic units based on the three-dimensional geometric contour of the target blood vessel segment, wherein the side length of each cubic unit is consistent with the electrode spacing of the micro-controlled release chip, and the dielectric property values ​​are assigned to the corresponding units according to the spatial coordinates to form an initial dielectric property distribution grid, including:

[0121] 501. Using the electrode spacing of the micro-controlled release chip as the side length, the target blood vessel segment is divided into cubic units with equal spacing along the axial, radial and circumferential directions;

[0122] In step 501, the electrode spacing refers to the distance between the centers of adjacent electrodes on the surface of the micro-controlled release chip. This parameter is determined by the chip manufacturing process. The cubic unit is the smallest computational unit after spatial discretization. Its side length is consistent with the electrode spacing, ensuring that the spatial resolution matches the electrode array.

[0123] In the embodiment of the present application, first, the spatial resolution is set based on the distance between the center points of adjacent electrodes on the surface of the micro-controlled release chip, and the target blood vessel segment is mapped into a regular cylindrical coordinate system. Secondly, the curved blood vessel is parameterized using a three-dimensional affine transformation matrix. The axial coordinate is defined by the arc length of the blood vessel centerline, and the radial and circumferential coordinates correspond to the cross-sectional radius and angle. For example, when the blood vessel segment is 10 mm long and the electrode spacing is 20 microns, the step length is divided into 500 slice layers along the axial direction. Within each slice layer, a grid is generated according to polar coordinates. The radial step length is consistent with the electrode spacing, and the circumferential step length is converted to an angular resolution of 1.15° using the arc length corresponding to the electrode spacing. Next, the Jacobian matrix is ​​used for Cartesian coordinate transformation, and bilinear interpolation correction is performed on units with geometric distortion exceeding 5%, ultimately generating a cubic unit grid with equal side lengths. This process uses finite element mesh generation technology to achieve the mapping of the blood vessel surface to a regular cube, ensuring spatial alignment of the grid with the electrode array.

[0124] 502. Extract the phase difference change and obtain the dielectric characteristic value by looking up the table based on all measurement points within the cubic unit space. If there are multiple measurement points within the cubic unit, take the average value of the multiple measurement points as the initial value of the cubic unit. If there are no measurement points within the cubic unit, mark the cubic unit as an invalid unit.

[0125] In step 502, measurement points refer to raw data acquisition points obtained by the chip electrode array during intravascular scanning. Phase difference changes reflect differences in the propagation characteristics of electromagnetic waves of different frequencies in a medium. Invalid cells refer to spatial cells not covered by any electrode scan.

[0126] In the embodiment of the present application, first, sparse data acquisition technology is used to obtain discrete measurement points through time-division multiplexing scanning of the electrode array. Secondly, a time-division multiplexing strategy is adopted to activate a pair of transmitting and receiving electrodes each time, and the remaining electrodes are grounded to shield interference. The measurement point position is the midpoint of the line connecting the transmitting and receiving electrodes, and the coordinates are calculated by the electrode geometric parameters. Then, a spatial inclusion test is performed on each cubic unit. If there are ≥1 measurement points in the unit, the table lookup algorithm is called to match the phase difference and the dielectric characteristic curve, and the arithmetic average is taken. If there is no measurement point, it is marked as an invalid unit. This process uses a spatial index algorithm to accelerate the position matching of the unit and the measurement point.

[0127] 503. Finding valid cells adjacent to the invalid cell, extracting a distance-weighted average of the dielectric characteristic values ​​of the valid cells as the value of the invalid cell, and arranging all the cubic cells according to spatial positions to form an initial three-dimensional grid storing the dielectric characteristic values ​​and spatial positions;

[0128] In step 503, the distance weighted average refers to the use of the inverse distance weighted algorithm, and the weight coefficient is inversely proportional to the spatial Euclidean distance of adjacent cells. Invalid cell filling must meet the requirement that the number of adjacent valid cells is ≥3 to ensure interpolation stability. The initial three-dimensional grid refers to a structured three-dimensional data model containing dielectric property values ​​and spatial position information.

[0129] In the embodiment of the present application, first, all invalid cells in the initial three-dimensional grid are traversed and the 26-neighborhood system is used to

[0130] The valid cells around it are searched, and at least three valid cells adjacent to the target invalid cell are selected. Next, based on the inverse distance weighted average algorithm, the weights of the dielectric properties of the valid cells are calculated. The Euclidean distance from the center of each valid cell is calculated, using the center coordinates of the invalid cell as the reference, to generate a weight coefficient, where weight = 1 / distance2. The dielectric constant and conductivity are weighted averaged. If there are insufficient valid cells in the neighborhood, the second-order neighborhood is expanded until the conditions are met. Next, the interpolation result is assigned to the invalid cell and marked as "interpolation generated." A three-dimensional Gaussian filter is applied to the adjacent interpolated cells, and local mutation noise is eliminated through convolution calculations. All valid cells and interpolated cells are then arranged according to spatial indexes to construct an initial three-dimensional grid data structure with sparse storage.

[0131] 504. Calculate the degree of difference in dielectric property values ​​between valid cells and adjacent cells in the initial three-dimensional grid, so that the degree of difference between all cubic cells is lower than a threshold or reaches a maximum number of iterations, thereby forming an initial dielectric property distribution grid.

[0132] In step 504, the degree of difference is quantified by calculating the gradient modulus of dielectric property values ​​of adjacent units, and the threshold is set to the biological tissue boundary threshold of the dielectric property mutation.

[0133] In the embodiment of the present application, first, after the three-dimensional grid is initialized, an iterative loop is entered to calculate the degree of difference between the dielectric property values ​​of each unit and the 26 neighboring units in the initial three-dimensional grid. Secondly, the units whose dielectric gradient exceeds the threshold are marked, and the high-gradient area is subdivided into an octree grid, and the original cube unit is divided into 8 subunits, where the new side length d = d / 2, and a new index is assigned to the subunit. The data interpolation of steps 502 to 503 is repeated for the newly generated unit. If the subunit contains the original measurement point, it is directly assigned, otherwise it is interpolated according to the adjacent units. Then, the grid data structure is updated, and the parent-child unit relationship is recorded until the maximum number of iterations or the global maximum gradient is lower than the threshold, forming the initial dielectric property distribution grid.

[0134] In summary, steps 501 to 504 achieve high-precision dynamic reconstruction of the dielectric property distribution within the blood vessel. Through cubic grid division with matching electrode spacing, the spatial resolution is ensured to be strictly consistent with the physical properties of the chip. Combined with sparse phase difference data acquisition and table lookup mapping, the initial dielectric property distribution is quickly constructed. Based on inverse distance weighted interpolation, data missing areas are effectively filled and a continuous three-dimensional grid is constructed. Through gradient-driven octree subdivision, local resolution is adaptively improved at the tissue interface. This method overcomes the limitations of traditional vascular imaging technology, such as inaccurate data repair and blurred tissue boundaries, significantly improves the accuracy of dielectric property reconstruction, enhances the ability to identify micron-level structures, and significantly reduces computational time. It provides a highly reliable three-dimensional electrical property spatial distribution model for real-time analysis of atherosclerotic plaque components and precise interventional treatment.

[0135] In some embodiments, step 205 includes merging adjacent continuous cells of the gradient change rate parameter in the dielectric property distribution grid into the same level based on the distribution of the gradient change rate parameter to form a three-dimensional boundary of the calcified core area, the transition area, and the healthy area, so as to output a three-dimensional distribution map of plaque hardness, including:

[0136] 601. Read the dielectric property values ​​of the cube unit and its six adjacent units one by one, calculate the maximum dielectric property difference between the cube unit and the adjacent units, and divide the maximum dielectric property difference by the unit side length to obtain the gradient change rate parameter of the unit;

[0137] In step 601, a cube cell refers to the basic voxel unit in the three-dimensional mesh, which contains electromagnetic parameters such as dielectric constant and conductivity. The maximum dielectric property difference is the absolute difference between the dielectric constant of the current cell and each neighboring cell, and the maximum value is taken. The gradient change rate parameter is an indicator of the degree of sudden change in local dielectric properties, calculated as Δε_max / Δx.

[0138] In an embodiment of the present application, first, each cubic unit in the three-dimensional grid is traversed, and the dielectric constant values ​​stored therein are read one by one. The six adjacent units of the current unit are accessed through the three-dimensional coordinate offset algorithm. The specific operation is to perform an incremental operation of ±1 on the unit index. For example, when the unit coordinates are i, j, k, the neighborhood unit index is i±1, j, k, i, j±1, k, i, j, k±1. Secondly, the absolute difference in dielectric properties between the current unit and each neighboring unit is calculated, and a parallel computing framework is used to accelerate the difference screening, and the maximum value is extracted from the six differences as Δε_max. Next, Δε_max is divided by the physical size Δx of the unit. For example, when the side length of the unit is 1 mm, the gradient change rate parameter K = Δε_max / 1 is calculated, and the parameter is stored as a three-dimensional floating-point matrix for subsequent steps to call.

[0139] 602. Set the gradient change rate parameter to a high threshold range, a medium threshold range, and a low threshold range, and then traverse the cube units. If the gradient change rate parameter of the cube unit falls within the high threshold range, it is marked as a core candidate unit; if it falls within the medium threshold range, it is marked as a transition candidate unit; if it falls within the low threshold range, it is marked as a healthy candidate unit, thereby obtaining marked cube units.

[0140] In step 602 , candidate cell labeling refers to classifying cells according to K values, and core candidate cells represent regions where dielectric properties change dramatically.

[0141] In an embodiment of the present application, first, based on the statistical analysis of the historical data set, the Jenks natural fracture optimization algorithm is used to divide the gradient change rate parameter into three threshold intervals of high, medium and low. For example, the high threshold interval is defined as K≥0.8, the medium threshold is 0.3≤K<0.8, and the low threshold is K<0.3. Secondly, the K value of each cube unit is traversed. If K≥0.8, it is marked as a core candidate unit and assigned a red RGB code of 255,0,0. If K falls in the medium threshold interval, it is marked as a yellow transition candidate unit 255,255,0, and the low threshold unit is marked as a green healthy candidate unit 0,255,0. Then, all the marking information is stored as a three-dimensional color matrix, and its spatial index is strictly aligned with the grid unit of step 601.

[0142] 603. Perform spatial continuity detection on the marked cubic units. Starting from any core candidate unit, merge the core candidate units that share a face or edge with the core candidate unit to form a calcified core region. Perform the same operation on the transition candidate units and the healthy candidate units to generate a transition region and a healthy region, respectively.

[0143] In step 603 , the calcified core region refers to a connected domain consisting of continuous core candidate units, representing the main body of plaque sclerosis.

[0144] In an embodiment of the present application, first, a breadth-first search algorithm is performed on the core candidate cell matrix, starting from the unvisited red cell, and its 26 neighborhoods containing adjacent cells in terms of faces, edges, and vertices are detected. If the neighboring cells are all marked red and have not been visited, they are added to the current connected domain queue and marked as visited, and recursively expanded until there are no new cells, and the three-dimensional coordinate set of the calcified core area is output. Secondly, the same operation is repeated for the transition candidate cells and the healthy candidate cells to generate independent coordinate sets for the transition area and the healthy area respectively. The coordinate data of all areas are stored as a spatial index linked list, and the linked list nodes contain the three-dimensional coordinates of the cells and the labels of the areas to which they belong.

[0145] 604. Calculate the mean value of the gradient change rate parameter of the cells in the calcified core area, transition area, and healthy area. If the difference in the mean value of the gradient change rate parameter of adjacent areas is less than the merging tolerance, merge the two sub-areas into the same level, extract the spatial coordinate extreme values ​​of each level, generate a cube bounding box, and output it as a three-dimensional boundary. Associate the calcified core area, transition area, and healthy area with the three-dimensional boundary, and output it as a three-dimensional distribution map of plaque hardness.

[0146] In step 604, the mean gradient change rate parameter refers to the arithmetic mean of the K values ​​of all cells in the region. The merge tolerance refers to a preset similarity threshold. The cube bounding box refers to the minimum circumscribed cube that encloses the region, and records the coordinates of its vertex extremes.

[0147] In an embodiment of the present application, first, the mean values ​​of the gradient change rate parameters of the calcified core area, the transition area, and the healthy area are calculated, for example, the core area mean μ1=1.2, the transition area μ2=0.6, and the healthy area μ3=0.1. Secondly, the mean differences of adjacent areas are compared. If the absolute value of the mean difference between the core area and the transition area is less than the merging tolerance of 0.15, the two areas are merged into a mixed level. And the spatial coordinate extremes of each area are extracted, for example, the X-axis extreme value of the calcified core area is 10 mm to 25 mm, the Y-axis is 5 mm to 20 mm, and the Z-axis is 0 mm to 15 mm, and the minimum circumscribed cube bounding box of the enclosing area is generated. Then, the regional coordinate set is associated with the vertex coordinates of the bounding box, and a three-dimensional plaque hardness distribution map with a red-yellow-green gradient is generated by ray casting volume rendering technology, which supports three-dimensional rotation and profile analysis.

[0148] In summary, steps 601 to 604 construct a three-dimensional dynamic identification system for plaque hardness based on dielectric property gradients. By calculating the local dielectric constant mutation intensity unit by unit, and combining multi-threshold interval marking to achieve coarse-grained classification of tissue status, connected regions are generated through spatial continuity detection, and finally the hierarchical division is optimized based on parameter similarity and a visual boundary is generated. This method innovatively integrates the three mechanisms of dielectric constant quantification, dynamic threshold adaptation, and three-dimensional topological analysis, achieving millimeter-level spatial resolution between calcified cores and normal tissues, and capturing the continuous change characteristics of dielectric parameters at the edge of the plaque through transition zone marking. The generated three-dimensional bounding box ensures the minimum circumference of the enclosed area through extreme value coordinate mapping, and combines the adaptive merging strategy of gradient mean difference to effectively eliminate artifact interference, so that the plaque hardness distribution map can retain anatomical details while intuitively presenting the spatial evolution law of the calcification process, providing high-precision three-dimensional data support for early diagnosis and interventional treatment planning of vascular plaques.

[0149] In some embodiments, when the gradient change rate parameter exceeds a set threshold in step 103, generating a pressure control instruction that matches the spatial distribution corresponding to the calcified area includes:

[0150] 701. Extracting the gradient change rate parameter of each unit from the three-dimensional distribution map of plaque hardness, comparing it with a set threshold, screening out units exceeding the threshold, and marking them as calcified core units;

[0151] In step 701, the three-dimensional plaque hardness distribution map refers to three-dimensional matrix data reflecting the spatial distribution of hardness within the plaque, obtained through ultrasound elastography or CT / MRI elastic reconstruction techniques. The gradient change rate parameter refers to the composite value of the hardness change rate of each voxel in the x / y / z directions, calculated using the Sobel operator or a three-dimensional gradient algorithm, reflecting the degree of hardness mutation. Calcified core cells are cells whose gradient change rate exceeds a set threshold and represent potential areas of calcification deposition.

[0152] In an embodiment of the present application, first, a three-dimensional gradient calculation is performed on the three-dimensional distribution map of plaque hardness, and the Sobel operator of a 3×3×3 neighborhood is used to extract the hardness change rate components of each voxel unit in the X, Y, and Z directions. The total gradient modulus is calculated by the formula, where the gradient component in the X direction is calculated by the central difference of the hardness values ​​of the neighborhood units, and the same method is used for the Y and Z directions. Secondly, the total gradient value is compared with the preset threshold of 15% hardness per millimeter to filter out units that exceed the threshold. Then, a three-dimensional morphological corrosion operation is performed on the screening results, and a spherical structural element with a radius of 0.2 mm is used to traverse all units. If there are non-high gradient units within 0.2 mm around the unit, they are eliminated, and finally the continuous high gradient area is retained as the calcification core unit.

[0153] 702. Merge adjacent calcified core units to form a calcified core area, calculate the geometric center and outer contour of the calcified core area, establish a three-dimensional pressure control grid based on the outer contour of the calcified core area, and match the grid nodes of the three-dimensional pressure control grid with the spatial distribution of the calcified core area;

[0154] In step 702, the calcified core region refers to a connected domain formed by merging spatially adjacent calcified core units using a three-dimensional region growing algorithm. The three-dimensional pressure control grid refers to a tetrahedral or hexahedral grid generated based on the outer contour of the calcified core region, with the grid nodes bound to the spatial coordinates of the core region.

[0155] In the embodiment of the present application, first, a three-dimensional region growing algorithm is used to merge spatially adjacent calcified core units, and the neighborhood distance threshold is set to 0.5 mm. If the Euclidean distance between units is less than this value, they are merged into the same area. Secondly, the merged calcified core area is subjected to Delaunay tetrahedron dissection, and the centroid coordinates of each tetrahedron are calculated as the geometric center. Then, the outer contour triangular mesh is extracted by the Ball-Pivoting algorithm, the sphere radius is set to 0.3 mm, and after traversing all surface vertices to generate the initial contour, the Laplacian smoothing algorithm is used to iterate 3 times to optimize the surface curvature. Finally, a three-dimensional pressure control grid is generated based on the outer contour. The outer 1 mm thickness area is divided into hexahedral units with a side length of 0.2 mm, and the inner area uses 0.5 mm tetrahedral units. The grid node coordinates are strictly aligned with the spatial distribution of the calcified core area.

[0156] 703. Calculate a pressure weight coefficient based on the distance between the grid node and the center of the calcified core area, and assign a pressure waveform amplitude based on the weight coefficient. Nodes with higher weights correspond to pressure waveforms with higher amplitudes, thereby generating an initial pressure control instruction.

[0157] In step 703, the pressure weight coefficient refers to a normalized parameter that is inversely proportional to the distance from the node to the center of the core area. The pressure waveform amplitude refers to the ultrasonic pressure wave amplitude allocated according to the weight coefficient.

[0158] In the embodiment of the present application, first, the Euclidean distance from each grid node to the geometric center of the calcified core area is calculated, and the distance is converted into a weight coefficient through a normalization function, and the formula is w = 1 / (1 + 0.5d 2 ), where d is the distance value in millimeters. Secondly, the pressure waveform amplitude is assigned according to the weight coefficient. When the core area node weight is ≥0.8, it corresponds to an amplitude of 20 to 30 standard atmospheres. When the transition area weight is 0.5 to 0.8, it corresponds to 10 to 20 standard atmospheres. When the peripheral area weight is <0.5, it corresponds to 5 to 10 standard atmospheres. Next, the pressure waveform is generated using amplitude modulation technology. The core area is loaded with a 1 kHz high-frequency sine wave, and the peripheral area is loaded with a 200 Hz low-frequency square wave. The phase synchronization error of the waveform of each node is calibrated using a PID controller to ensure that the time axis deviation is less than 0.1 milliseconds.

[0159] 704. Proportionally adjust the pressure waveform amplitude of each node in the initial pressure control instruction according to the ratio of the gradient change rate parameter of the calcified core area to the set threshold value to obtain a pressure control instruction.

[0160] In step 704, the gradient ratio adjustment refers to the ratio of the average gradient change rate of the calcified core area to the threshold, which is used to dynamically scale the amplitude. The pressure control instruction is the final execution instruction after the dynamic ratio adjustment of the gradient change rate of the calcified core area to the set threshold. Its core is to achieve a precise match between the pressure parameters and the mechanical properties of the lesion area.

[0161] In the embodiment of the present application, first, the ratio R of the average gradient change rate of each unit in the calcified core area to the set threshold is calculated. If R ≥ 1.2, the amplitude enhancement mode is triggered, and the amplitude of the core area node increases linearly according to ΔA = 10 × (R-1) standard atmospheric pressure, while limiting the maximum amplitude to no more than 30 standard atmospheric pressures. Secondly, the amplitude of the area where R < 0.8 is attenuated, and the original amplitude is multiplied by an attenuation coefficient of 0.7. Then, the adjusted waveform parameters of all nodes are integrated to generate a three-dimensional matrix containing timestamps, spatial coordinates and pressure amplitudes, which is encapsulated and output to the shock wave generating device in JSON format to obtain pressure control instructions and update at a frequency of 1000 times per second.

[0162] In summary, steps 701 to 704 construct a precise control system for shock wave energy based on the linkage of three-dimensional elastic gradient field and dynamic threshold. By integrating the gradient mutation characteristics, spatial distribution topology and dynamic weight distribution model of the calcification core area, a direct mapping mechanism from biomechanical characteristics to energy parameters is established. This scheme can not only achieve millimeter-level gradient distribution of shock wave energy based on the spatial heterogeneity of calcification hardness, but also dynamically optimize the energy output strategy through the gradient ratio feedback mechanism, ensuring the effective crushing of calcification foci while reducing the risk of vascular endothelial damage to within the clinical safety threshold. The final generated JSON format spatiotemporal matrix instructions achieve submillimeter spatial resolution and microsecond time synchronization accuracy of the shock wave generator, providing a quantitative control scheme that takes into account both energy focusing and tissue protection for the personalized treatment of complex morphological calcified lesions.

[0163] Figure 2 The present invention provides a schematic structural diagram of a dynamic control system for treating vascular plaques based on a micro-controlled release chip. Figure 2 As shown, the system includes:

[0164] An acquisition module 21 is configured to establish a multi-frequency current loop in a target blood vessel segment and acquire blood vessel electrical characteristic data including real and imaginary components based on the impedance attenuation characteristics of the multi-frequency current loop;

[0165] A construction module 22 is configured to calculate a gradient change rate parameter by matching dielectric characteristic values ​​based on the phase difference change of the blood vessel electrical characteristic data, and construct a three-dimensional distribution map of plaque hardness in the target blood vessel using the gradient change rate parameter;

[0166] A generating module 23 is configured to generate a pressure control instruction that matches the spatial distribution corresponding to the calcified area when the gradient change rate parameter exceeds a set threshold;

[0167] A conversion module 24 converts the pressure control instruction into a multi-band treatment signal combination based on the calcified core area, transition area, and healthy area divided by the three-dimensional distribution map of plaque hardness;

[0168] The adjustment module 25 is used to convert the treatment signal combination into a corresponding mechanical expansion waveform through the micro-controlled release chip. The mechanical expansion waveform triggers the monitoring of the high-frequency signal amplitude. When the high-frequency signal reaches the peak amplitude, the pore opening parameter of the micro-controlled release chip is synchronously adjusted. When the dielectric parameter of the calcified core area is detected to fluctuate in the opposite direction, the phase compensation adjustment of the drug permeation rate is triggered according to the spectral characteristics of the current drive signal combination to control the degradation process of the vascular plaque.

[0169] Figure 2 The dynamic control system for treating vascular plaque based on the micro-controlled release chip can be executed Figure 1 The implementation principles and technical effects of the dynamic control method for vascular plaque treatment based on a micro-controlled release chip described in the illustrated embodiment will not be elaborated upon. The specific manner in which the various modules and units of the dynamic control system for vascular plaque treatment based on a micro-controlled release chip in the aforementioned embodiment operate has been described in detail in the related embodiments and will not be further elaborated here.

[0170] In one possible design, Figure 2 The dynamic control system for treating vascular plaque based on a micro-controlled release chip of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0171] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0172] The processing component 32 is used for the above Figure 1 The embodiment provides a dynamic control method for treating vascular plaques based on a micro-controlled release chip.

[0173] The processing component 32 may include one or more processors to execute computer instructions to perform all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0174] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0175] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0176] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0177] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0178] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0179] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The embodiment shown is a dynamic control method for treating vascular plaque based on a micro-controlled release chip.

[0180] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0181] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0182] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0183] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A dynamic control method for treating vascular plaque based on a micro-controlled release chip, characterized in that: include: Establishing a multi-frequency current loop in the target blood vessel segment, and obtaining blood vessel electrical characteristic data including real and imaginary components based on the impedance attenuation characteristics of the multi-frequency current loop; Based on the phase difference change of the blood vessel electrical characteristic data, a gradient change rate parameter is calculated by matching the dielectric characteristic value, and the gradient change rate parameter is used to construct a three-dimensional distribution map of plaque hardness in the target blood vessel; When the gradient change rate parameter exceeds a set threshold, a pressure control instruction is generated that matches the spatial distribution corresponding to the calcified area; Based on the calcified core area, transition area and healthy area divided by the three-dimensional distribution map of plaque hardness, the pressure control instruction is converted into a multi-band treatment signal combination; The therapeutic signal combination is converted into a corresponding mechanical expansion waveform through a micro-controlled release chip. The mechanical expansion waveform triggers the monitoring of the high-frequency signal amplitude. When the high-frequency signal is detected to have reached its peak amplitude, the pore opening parameters of the micro-controlled release chip are synchronously adjusted. When the dielectric parameters of the calcified core area are detected to fluctuate in the opposite direction, the phase compensation adjustment of the drug permeation rate is triggered according to the spectral characteristics of the current driving signal combination to control the degradation process of the vascular plaque.

2. The method according to claim 1, characterized in that Based on the phase difference change of the blood vessel electrical characteristic data, a gradient change rate parameter is calculated by matching the dielectric characteristic value, and the gradient change rate parameter is used to construct a three-dimensional distribution map of plaque hardness in the target blood vessel, including: Extracting the phase difference variation at different frequencies for each measurement point from the vascular electrical characteristic data based on the impedance attenuation characteristics of the multi-frequency current loop, matching the phase difference variation with a pre-calibrated dielectric characteristic relationship table to determine the dielectric characteristic value corresponding to each measurement point; Based on the three-dimensional geometric contour of the target blood vessel segment, the target blood vessel segment is divided into equally spaced cubic units, where the side length of each cubic unit is consistent with the electrode spacing of the micro-controlled release chip, and the dielectric property values ​​are assigned to the corresponding units according to the spatial coordinates to form an initial dielectric property distribution grid; Iteratively optimizing the initial dielectric property distribution grid according to the difference in dielectric property values ​​between adjacent units to generate an optimized dielectric property distribution grid; Calculating the maximum difference between the dielectric property values ​​of each cell and six adjacent cells in the optimized dielectric property distribution grid, and dividing the maximum difference by the cell spacing to obtain a gradient change rate parameter of the current cell; According to the distribution of the gradient change rate parameter, adjacent continuous units of the gradient change rate parameter in the dielectric property distribution grid are merged into the same level to form the three-dimensional boundaries of the calcified core area, the transition area and the healthy area, so as to output a three-dimensional distribution map of plaque hardness.

3. The method according to claim 1, characterized in that The calcified core area, transition area and healthy area are divided based on the three-dimensional distribution map of plaque hardness, and the pressure control instruction is converted into a multi-band treatment signal combination, including: Extracting the range of dielectric properties in each region based on the three-dimensional boundaries of the calcified core region, the transition region, and the healthy region in the three-dimensional plaque hardness distribution map, taking the highest dielectric value of the calcified core region as a reference value, calculating proportional coefficients between the dielectric values ​​of the transition region and the healthy region and the reference value, and mapping the proportional coefficients to frequency threshold intervals for the corresponding regions; The upper limit of the frequency threshold interval of the calcified core area is defined as the starting frequency of the high-frequency signal, the midpoint of the frequency threshold interval of the transition area is used as the fixed frequency of the intermediate-frequency signal, and the proportional coefficient of the dielectric value of the healthy area is combined with a preset morphological stability parameter to determine the frequency value of the low-frequency signal; The high-frequency signal, intermediate-frequency signal and low-frequency signal are respectively loaded into independent waveform generators, and the phases of the three signals are offset controlled by the independent waveform generators so that the peak interval between the high-frequency signal and the intermediate-frequency signal is greater than a preset threshold, and the trough of the low-frequency signal and the peak of the high-frequency signal form a periodic overlap to form a therapeutic signal combination.

4. The method according to claim 1, wherein The treatment signal combination is converted into a corresponding mechanical expansion waveform by a micro-controlled release chip. The mechanical expansion waveform triggers the monitoring of the high-frequency signal amplitude. When the high-frequency signal reaches a peak amplitude, the pore opening parameter of the micro-controlled release chip is synchronously adjusted. When a reverse fluctuation of the dielectric parameter of the calcified core area is detected, the phase compensation adjustment of the drug permeation rate is triggered according to the spectrum characteristics of the current drive signal combination to control the degradation process of the vascular plaque, including: The superimposed deformation of the therapeutic signal combination is converted into a mechanical expansion waveform through the multi-layer flow channel structure within the micro-controlled release chip, triggering the embedded piezoresistive sensor to monitor the high-frequency signal amplitude. When the instantaneous amplitude of the high-frequency signal first exceeds the trigger ratio of the preset amplitude, it is recorded as the initial trigger point. If the peak values ​​of multiple subsequent consecutive signal cycles reach or exceed the preset amplitude, an adjustment instruction for the pore opening is sent to the drive unit of the micro-controlled release chip, causing the pore opening parameter to linearly increase from the initial opening to the target opening within the next signal cycle, thereby improving the drug penetration rate. In the calcified core area, dielectric characteristic values ​​are acquired at fixed time intervals and the difference rate between two adjacent acquisitions of the dielectric characteristic values ​​is calculated. When the difference rate shows negative changes for multiple consecutive times and exceeds the reverse fluctuation tolerance range, phase compensation adjustment is triggered; performing offset compensation on the drug permeation rate control waveform according to the current phase angle of the high-frequency signal to generate an offset-compensated drug permeation control waveform, and inputting the drug permeation rate control waveform and the mechanical expansion waveform of the high-frequency signal into a waveform superposition module to generate a composite control signal; In the dynamic control waveform, the pore aperture parameter is dynamically scaled with the real-time change of the amplitude of the high-frequency signal. At the same time, the amplitude coupling relationship of the composite control signal is dynamically corrected through the pressure feedback loop to ensure that the peak pressure of the mechanical expansion waveform and the permeation rate of the drug permeation rate control waveform form a complementary superposition on the time axis, so as to achieve dynamic control of vascular plaques.

5. The method according to claim 2, characterized in that Based on the three-dimensional geometric contour of the target blood vessel segment, the target blood vessel segment is divided into equally spaced cubic units, where the side length of each cubic unit is consistent with the electrode spacing of the micro-controlled release chip. The dielectric property values ​​are assigned to the corresponding units according to the spatial coordinates to form an initial dielectric property distribution grid, including: Using the electrode spacing of the micro-controlled release chip as the side length, the target blood vessel segment is divided into equally spaced cubic units along the axial, radial, and circumferential directions; By traversing all measurement points within the spatial range of the cubic unit, extracting the phase difference change and looking up the table to obtain the dielectric characteristic value, if there are multiple measurement points in the cubic unit, taking the average value of the multiple measurement points as the initial value of the cubic unit, and if there are no measurement points in the cubic unit, marking the cubic unit as an invalid unit; According to searching for valid cells adjacent to the invalid cell, extracting a distance-weighted average of the dielectric characteristic values ​​of the valid cells as the value of the invalid cell, and arranging all the cubic cells according to spatial positions to form an initial three-dimensional grid storing the dielectric characteristic values ​​and spatial positions; The degree of difference in dielectric property values ​​between effective cells and adjacent cells in the initial three-dimensional grid is calculated so that the degree of difference between all cubic cells is lower than a threshold or reaches a maximum number of iterations to form an initial dielectric property distribution grid.

6. The method according to claim 2, characterized in that According to the distribution of the gradient change rate parameter, adjacent continuous cells of the gradient change rate parameter in the dielectric property distribution grid are merged into the same level to form a three-dimensional boundary of the calcified core area, the transition area, and the healthy area, so as to output a three-dimensional distribution map of plaque hardness, including: Read the dielectric property values ​​of the cube unit and its six adjacent units one by one, calculate the maximum dielectric property difference between the cube unit and the adjacent units, and divide the maximum dielectric property difference by the unit side length to obtain the gradient change rate parameter of the unit; The gradient change rate parameter is set to a high threshold interval, a medium threshold interval, and a low threshold interval, and then the cubic unit is traversed. If the gradient change rate parameter of the cubic unit falls within the high threshold interval, it is marked as a core candidate unit; if it falls within the medium threshold interval, it is marked as a transition candidate unit; if it falls within the low threshold interval, it is marked as a healthy candidate unit, and the marked cubic unit is obtained; Performing a spatial continuity check on the marked cubic units, starting from any core candidate unit, merging the core candidate units that share a face or edge with the any core candidate unit to form a calcified core area, performing the same operation on the transition candidate unit and the healthy candidate unit to generate a transition area and a healthy area, respectively; The mean values ​​of the gradient change rate parameters of the cells in the calcified core area, transition area, and healthy area are calculated. If the difference in the mean values ​​of the gradient change rate parameters of adjacent areas is less than the merging tolerance, the two sub-areas are merged into the same level, and the spatial coordinate extremes of each level are extracted to generate a cubic bounding box as the three-dimensional boundary output. The calcified core area, transition area, and healthy area are associated with the three-dimensional boundary and output as a three-dimensional distribution map of plaque hardness.

7. The method according to claim 1, characterized in that When the gradient change rate parameter exceeds a set threshold, a pressure control instruction is generated that matches the spatial distribution corresponding to the calcified area, including: The gradient change rate parameter of each unit is extracted from the three-dimensional distribution map of plaque hardness, and compared with the set threshold. The units exceeding the threshold are screened out and marked as calcified core units. Merging adjacent calcified core units to form a calcified core area, calculating the geometric center and outer contour of the calcified core area, establishing a three-dimensional pressure control grid based on the outer contour of the calcified core area, and aligning grid nodes of the three-dimensional pressure control grid with the spatial distribution of the calcified core area; Calculating a pressure weight coefficient based on the distance between the grid node and the center of the calcified core area, and allocating a pressure waveform amplitude based on the weight coefficient, where nodes with higher weights correspond to pressure waveforms with higher amplitudes, to generate an initial pressure control instruction; According to the ratio of the gradient change rate parameter of the calcified core area to the set threshold, the pressure waveform amplitude of each node in the initial pressure control instruction is proportionally adjusted to obtain a pressure control instruction.

8. A dynamic control system for treating vascular plaque based on a micro-controlled release chip, characterized in that: include: an acquisition module, configured to establish a multi-frequency current loop in the target blood vessel segment and acquire blood vessel electrical characteristic data including real and imaginary components based on the impedance attenuation characteristics of the multi-frequency current loop; a construction module for calculating a gradient change rate parameter by matching dielectric characteristic values ​​based on a phase difference change of the blood vessel electrical characteristic data, and constructing a three-dimensional distribution map of plaque hardness in the target blood vessel using the gradient change rate parameter; a generating module, configured to generate a pressure control instruction matching the spatial distribution corresponding to the calcified area when the gradient change rate parameter exceeds a set threshold; a conversion module, which converts the pressure control instruction into a multi-band treatment signal combination based on the calcified core area, transition area, and healthy area divided by the three-dimensional distribution map of plaque hardness; The regulating module is used to convert the therapeutic signal combination into a corresponding mechanical expansion waveform through a micro-controlled release chip, The mechanical expansion waveform triggers the monitoring of the high-frequency signal amplitude. When the high-frequency signal reaches a peak amplitude, the pore opening parameters of the micro-controlled release chip are synchronously adjusted. When a reverse fluctuation of the dielectric parameters of the calcified core area is detected, the phase compensation adjustment of the drug permeation rate is triggered according to the spectral characteristics of the current drive signal combination to control the degradation process of the vascular plaque.

9. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement the dynamic control method for vascular plaque treatment based on a micro-controlled release chip as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the dynamic control method for treating vascular plaque based on a micro-controlled release chip according to any one of claims 1 to 7 is implemented.

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