Radio frequency therapeutic instrument control method

Abstract

The invention provides a radio frequency therapeutic instrument control method, and relates to the technical field of medical instruments, and the method comprises the steps: obtaining the dynamic change information of a target tissue surface temperature field in real time through collecting the dynamic temperature data of a target tissue surface; setting a temperature control constraint of the radio frequency therapeutic apparatus according to a plurality of temperature deviation indexes corresponding to the temperature sudden change area; performing region communication on the heat distribution rule in the temperature mutation region to obtain a temperature compensation boundary corresponding to the temperature mutation region on the surface of the target tissue, and determining a temperature change compensation trend of the radio frequency therapeutic apparatus according to the temperature compensation boundary and the dynamic temperature data; and determining multi-stage radio frequency treatment signals of the radio frequency treatment instrument in different temperature fields according to the temperature control constraint and the temperature change compensation trend, and matching temperature control strategies of the radio frequency treatment instrument according to the multi-stage radio frequency treatment signals. According to the invention, intelligent matching of temperature control strategies can be realized through multi-stage radio frequency treatment signals, so that the stability of temperature control of the radio frequency therapeutic apparatus is improved.

Description

Technical Field

[0001] This application relates to the technical field of medical devices, and more specifically, to a control method for a radiofrequency therapeutic apparatus. Background Art

[0002] Medical devices refer to a comprehensive system of dedicated devices and their control methods that are used in the processes of disease prevention, diagnosis, treatment, monitoring, and rehabilitation, and that assist or intervene in the human body structure or function through physical, electronic, biological, mechanical, and other means. In modern clinical applications, medical devices are widely involved in multiple fields such as imaging detection, minimally invasive treatment, energy control, and physiological signal monitoring. Especially in energy treatment methods such as hyperthermia, phototherapy, and radiofrequency, medical device technology realizes the simultaneous improvement of treatment accuracy and safety through real-time monitoring and feedback control of tissue states. With the development of artificial intelligence, sensing integration, and precision control technologies, medical devices are gradually evolving towards the direction of intelligence and adaptability.

[0003] However, the existing control methods for radiofrequency therapeutic apparatuses generally have problems such as untimely temperature acquisition, insensitive mutation response, single temperature control strategy, and lack of a spatial compensation mechanism, making it impossible to accurately adjust to the rapid changes in the surface temperature field of the target tissue during the treatment process, resulting in possible overheating damage or insufficient heating of local tissues, thereby reducing the safety and treatment effect of radiofrequency treatment. Therefore, how to achieve intelligent matching of temperature control strategies through multi-level radiofrequency treatment signals to improve the stability of temperature control of radiofrequency therapeutic apparatuses has become an urgent problem to be solved. Summary of the Invention

[0004] This application provides a control method for a radiofrequency therapeutic apparatus, which can achieve intelligent matching of temperature control strategies through multi-level radiofrequency treatment signals to improve the stability of temperature control of the radiofrequency therapeutic apparatus.

[0005] This application provides a control method for a radiofrequency therapeutic apparatus, and the control method includes the following steps: Place the treatment head of the radiofrequency therapeutic apparatus on the surface of the target tissue, collect dynamic temperature data on the surface of the target tissue, and obtain dynamic change information of the surface temperature field of the target tissue in real time; Identify the temperature mutation region on the surface of the target tissue through the temperature distribution characteristics in the dynamic change information, and set the temperature control constraint of the radiofrequency therapeutic apparatus according to a plurality of temperature deviation indexes corresponding to the temperature mutation region; Connect the heat distribution law in the temperature mutation region to obtain a temperature compensation boundary corresponding to the temperature mutation region on the surface of the target tissue, and determine the temperature change compensation trend of the radiofrequency therapeutic apparatus according to the temperature compensation boundary and the dynamic temperature data; Determine the multi-level radiofrequency treatment signals of the radiofrequency therapeutic apparatus in different temperature fields according to the temperature control constraints and the temperature change compensation trend, and match the temperature control strategy of the radiofrequency therapeutic apparatus according to the multi-level radiofrequency treatment signals.

[0006] In this embodiment, the dynamic change information refers to the continuous distribution and change trend data of the temperature field on the time axis.

[0007] In this embodiment, specifically including identifying the temperature mutation region on the surface of the target tissue through the temperature distribution characteristics in the dynamic change information: Determine the temperature distribution characteristics in the dynamic change information; Determine the temperature gradient change interval on the surface of the target tissue according to the temperature distribution characteristics; Determine the dynamic discrimination index of the temperature mutation on the surface of the target tissue; Identify the temperature mutation region on the surface of the target tissue according to the temperature gradient change interval and the dynamic discrimination index.

[0008] In this embodiment, the temperature mutation region refers to the spatial region where there are drastic changes in the temperature distribution, exceeding the tissue heat tolerance threshold, and posing a risk to the treatment effect.

[0009] In this embodiment, specifically including setting the temperature control constraints of the radiofrequency therapeutic apparatus according to the multiple temperature deviation indexes corresponding to the temperature mutation region: Determine the temperature fluctuation tolerance value of the radiofrequency therapeutic apparatus according to the multiple temperature deviation indexes within the temperature mutation region; Determine the heat conduction response parameter of the radiofrequency therapeutic apparatus; Evaluate the safety level deviation amount on the surface of the target tissue based on the temperature fluctuation tolerance value and the heat conduction response parameter; Determine the temperature control constraints of the radiofrequency therapeutic apparatus through the safety level deviation amount.

[0010] In this embodiment, specifically including performing regional connection on the heat distribution law in the temperature mutation region to obtain the temperature compensation boundary corresponding to the temperature mutation region on the surface of the target tissue: Based on the heat flow direction and gradient distribution characteristics of the heat distribution law, construct a regional connection map of the heat distribution; Generate multi-level connection constraints according to the temperature compensation requirements of adjacent mutation regions in the regional connection map; Perform heat balance path planning on the multi-level connection constraints and output the temperature compensation boundary.

[0011] In this embodiment, the temperature compensation boundary represents the extended boundary of the control area when the radiofrequency therapeutic apparatus controls the temperature on the surface of the target tissue during the radiofrequency treatment process.

[0012] In this embodiment, determining the temperature change compensation trend of the radiofrequency therapeutic apparatus according to the temperature compensation boundary and the dynamic temperature data specifically includes: Quantifying the spatio-temporal coupling parameters of the temperature change compensation trend according to the time series correlation between the temperature compensation boundary and the dynamic temperature data; Combining the heat conduction response parameters of the radiofrequency therapeutic apparatus with the tissue heat relaxation characteristics to establish a predictive control quantity for temperature change compensation; Determining the compensation efficiency gradient of the radiofrequency therapeutic apparatus in different temperature compensation strategies according to the spatio-temporal coupling parameters and the predictive control quantity; Determining the temperature change compensation trend of the radiofrequency therapeutic apparatus according to the compensation efficiency gradient.

[0013] In this embodiment, determining the multi-stage radiofrequency treatment signals of the radiofrequency therapeutic apparatus in different temperature fields according to the temperature control constraint and the temperature change compensation trend specifically includes; Constructing the temperature mapping quantity of the multi-stage radiofrequency signals in different temperature fields based on the temperature control constraint and the temperature change compensation trend; Determining the dynamic evolution characteristics of the temperature field of the radiofrequency therapeutic apparatus in different temperature fields; Determining the multi-stage radiofrequency treatment signals of the radiofrequency therapeutic apparatus in different temperature fields according to the temperature mapping quantity and the dynamic evolution characteristics of the temperature field.

[0014] In this embodiment, matching the temperature control strategy of the radiofrequency therapeutic apparatus according to the multi-stage radiofrequency treatment signals specifically includes: Phase-aligning the frequency of the multi-stage radiofrequency treatment signals with the energy distribution characteristics of the target temperature field to obtain the temperature fitting information of the radiofrequency therapeutic apparatus; Establishing the temperature mapping relationship between the temperature control strategy and the temperature field grading signals; Fusing the temperature fitting information and the temperature mapping relationship through a closed-loop feedback verification mechanism, and outputting the parameters of the matched temperature control strategy.

[0015] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects: Place the treatment head of the radiofrequency therapeutic instrument on the surface of the target tissue, collect the dynamic temperature data of the surface of the target tissue, and obtain the dynamic change information of the temperature field on the surface of the target tissue in real time; identify the temperature mutation area on the surface of the target tissue through the temperature distribution characteristics in the dynamic change information, and set the temperature control constraint of the radiofrequency therapeutic instrument according to multiple temperature deviation indexes corresponding to the temperature mutation area; perform regional connection on the heat distribution law in the temperature mutation area to obtain the temperature compensation boundary corresponding to the temperature mutation area on the surface of the target tissue, and determine the temperature change compensation trend of the radiofrequency therapeutic instrument according to the temperature compensation boundary and the dynamic temperature data; determine the multi-level radiofrequency treatment signals of the radiofrequency therapeutic instrument in different temperature fields according to the temperature control constraint and the temperature change compensation trend, and match the temperature control strategy of the radiofrequency therapeutic instrument according to the multi-level radiofrequency treatment signals.

[0016] It can be seen that in this application, based on the perception of dynamic temperature information, the temperature mutation area can be accurately identified; among them, by placing the treatment head of the radiofrequency therapeutic instrument on the surface of the target tissue and collecting the dynamic temperature data of the surface of the target tissue in real time, the dynamic change information of the temperature field on the tissue surface can be accurately and quickly obtained, realizing the fine monitoring of the temperature change trend and regional hot spots, and effectively solving the problems of temperature monitoring delay and fuzzy distribution in the prior art; by extracting the dynamic temperature distribution characteristics to identify the temperature mutation area and setting the temperature control constraint based on multiple temperature deviation indexes, the temperature control mechanism has the active protection ability for the temperature mutation area, thus avoiding tissue damage caused by abnormal heating and improving the temperature control safety and control response efficiency during the radiofrequency treatment process; by analyzing the heat distribution law in the temperature mutation area, constructing a heat distribution connection map, and generating a multi-level temperature compensation boundary, and establishing a temperature change compensation trend in combination with the dynamic temperature data, the temperature compensation process has spatial coherence and time predictability, effectively improving the temperature stability during the treatment process and overcoming the local lag and global imbalance of the existing compensation strategy; through frequency-phase alignment and closed-loop feedback mechanism, the dynamic matching between the multi-level radiofrequency signal and the tissue thermal response is realized, so as to intelligently output the control strategy according to the temperature evolution characteristics of the actual treatment area, improve the individual adaptability and temperature control intelligence level of the radiofrequency treatment, and overcome the limitations of the traditional control mode being fixed and slow to adjust.

[0017] In summary, the technical solution adopted in this application can realize the intelligent matching of the temperature control strategy through multi-level radiofrequency treatment signals to improve the stability of the temperature control of the radiofrequency therapeutic instrument. Brief Description of the Drawings

[0018] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only the embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0019] Figure 1 is an exemplary flowchart of a radiofrequency therapeutic apparatus control method provided according to the present application; Figure 2 is a schematic flowchart of determining temperature control constraints provided according to the present application; Figure 3 is a schematic flowchart of determining the temperature change compensation trend provided according to the present application. Detailed implementation manners

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0021] The embodiments of the present application provide a radiofrequency therapeutic apparatus control method. The core is to place the treatment head of the radiofrequency therapeutic apparatus on the surface of the target tissue, collect the dynamic temperature data on the surface of the target tissue, and obtain the dynamic change information of the temperature field on the surface of the target tissue in real time; identify the temperature mutation region on the surface of the target tissue through the temperature distribution characteristics in the dynamic change information, and set the temperature control constraints of the radiofrequency therapeutic apparatus according to a plurality of temperature deviation indicators corresponding to the temperature mutation region; perform regional connectivity on the heat distribution law in the temperature mutation region to obtain the temperature compensation boundary corresponding to the temperature mutation region on the surface of the target tissue, and determine the temperature change compensation trend of the radiofrequency therapeutic apparatus according to the temperature compensation boundary and the dynamic temperature data; determine the multi-level radiofrequency treatment signals of the radiofrequency therapeutic apparatus in different temperature fields according to the temperature control constraints and the temperature change compensation trend, and match the temperature control strategy of the radiofrequency therapeutic apparatus according to the multi-level radiofrequency treatment signals. By adopting the above solution, intelligent matching of the temperature control strategy can be realized through multi-level radiofrequency treatment signals to improve the stability of the temperature control of the radiofrequency therapeutic apparatus.

[0022] To better understand the above technical solutions, the following will describe the above technical solutions in detail in conjunction with the accompanying drawings of the specification and specific implementation manners. Refer to Figure 1 As shown, this figure is an exemplary flowchart of the radiofrequency therapeutic apparatus control method shown in the embodiments of the present application. The control method includes the following steps: In step S1, place the treatment head of the radiofrequency therapeutic apparatus on the surface of the target tissue, collect the dynamic temperature data of the surface of the target tissue, and obtain the dynamic change information of the temperature field on the surface of the target tissue in real time.

[0023] When specifically implemented, placing the treatment head of the radiofrequency therapeutic apparatus on the surface of the target tissue and collecting the dynamic temperature data of the surface of the target tissue can be achieved by the following method, that is: First, directly attach the treatment head of the radiofrequency therapeutic apparatus to the surface of the target tissue, and synchronously deploy an infrared thermal imager or a distributed micro-thermocouple array during the treatment process. The infrared thermal imager is used for non-contact, wide-area and rapid temperature scanning to cover the entire treatment area; the thermocouple array is fixed at multiple key points on the tissue surface by means of micro-needles or patches to provide high-precision, local temperature data. The collected data is transmitted to the main control processing system through a serial port or wirelessly, and the storage unit of the main control processing system is read at a fixed time interval. Among them, the time interval can be set according to the actual situation, and there is no limitation here. For example, every 100 milliseconds, the read temperature information is used as the dynamic temperature data of the surface of the target tissue.

[0024] It should be noted that in this application, the dynamic temperature data represents the set of temperature values of multiple points on the surface of the target tissue collected during the radiofrequency treatment process and changing with time.

[0025] In addition, when specifically implemented, the dynamic change information of the temperature field on the surface of the target tissue can be obtained by the following method, that is: A temperature sensing and data synchronization system with high spatio-temporal resolution can be jointly deployed through an infrared thermal imaging module and a micro-thermocouple array. The infrared thermal imager is used to obtain a wide-area continuous temperature distribution map, with a high frame rate ≥ 10 fps and a high resolution ≥ 0.1 °C; the micro-thermocouple array is attached or embedded on the surface of the treatment area to achieve precise temperature collection at multiple key points, and to supplement the errors in the thermal image due to angles or occlusions. All sensor data is synchronously transmitted to the embedded processing unit through a high-speed interface. This processing unit integrates image reconstruction and interpolation algorithms, fuses the dot-shaped and surface-shaped temperature data, constructs a two-dimensional temperature distribution map in real time, and generates a three-dimensional temperature field according to the time axis. In order to meet the real-time requirement, the system must have a data processing closed-loop time of ≤ 200 ms, that is, it can continuously and accurately obtain the dynamic change information of the temperature field on the surface of the target tissue.

[0026] It should be noted that in this application, the temperature field on the surface of the target tissue represents the two-dimensional spatial temperature distribution matrix of the temperature on the surface of the target tissue in a time series; the dynamic change information refers to the continuous distribution and change trend data of the temperature field on the time axis.

[0027] In step S2, a temperature mutation region on the surface of the target tissue is identified based on the temperature distribution feature in the dynamic change information, and a temperature control constraint of the radiofrequency therapeutic apparatus is set according to a plurality of temperature deviation indexes corresponding to the temperature mutation region.

[0028] In this embodiment, the identification of the temperature mutation region on the surface of the target tissue based on the temperature distribution feature in the dynamic change information can be implemented by the following steps: Determine the temperature distribution feature in the dynamic change information; Determine the temperature gradient change interval on the surface of the target tissue according to the temperature distribution feature; Determine the dynamic discrimination index of the temperature mutation on the surface of the target tissue; Identify the temperature mutation region on the surface of the target tissue according to the temperature gradient change interval and the dynamic discrimination index.

[0029] Specifically, first, a two-dimensional temperature distribution map of each frame is extracted from the dynamic change information, and spatio-temporal analysis is performed on the continuous images. Specifically, the following three types of features are used: spatial distribution features, calculating the spatial gradient, edge information, and hot spot aggregation region in each frame of the temperature image; time change features, recording the temperature change rate of each spatial point; statistical features, including the maximum temperature, mean value, standard deviation, skewness coefficient, etc. of each frame. The three types of features obtained are subjected to sliding window analysis and differential processing to form a set of feature description vectors for judging regional thermal stability, and this feature description vector is used as the temperature distribution feature in the dynamic change information. Then, the spatial gradient map of each frame of the temperature image is calculated, and the temperature change rate is obtained pixel by pixel using a gradient operator such as the Sobel operator to obtain a temperature gradient image. The temperature gradients in the temperature gradient image are statistically partitioned, and multiple temperature gradient change intervals are formed by segmenting according to the gradient value, such as a low gradient of 0–1 °C / cm, a medium gradient of 1–3 °C / cm, and a high gradient of >3 °C / cm region, which is not limited here. Then, the indexes for discriminating mutations are extracted from the dynamic temperature field: the instantaneous temperature rise rate threshold, such as the temperature change rate >0.5 °C / s; the local gradient change amount, such as the ▽T change value > the set threshold; the temperature jump amplitude, such as the temperature difference between adjacent pixels being greater than 3 °C; the high-frequency perturbation fluctuation index, which can extract the high-frequency thermal perturbation energy through Fourier analysis, which is not limited here. The obtained indexes are used as the dynamic discrimination indexes. Finally, the temperature gradient of the current frame temperature image is combined with the historical temperature change trend, and the regions with significant gradient changes and meeting the conditions of multiple dynamic discrimination indexes are marked. The region growing algorithm can be used to expand adjacent high-risk pixels to form a continuous temperature mutation region, and the temperature mutation region is represented in the form of a closed boundary.

[0030] It should be noted that in this application, the temperature distribution feature refers to the set of features of the changing trend of temperature in space and time in the treatment area; the temperature gradient change interval refers to the interval divided by the temperature change amplitude per unit distance, which is used to quantify the severity of local heat diffusion; the dynamic discrimination index is a set of multi-dimensional parameters for quantitatively evaluating the degree of temperature mutation in time and space; the temperature mutation area refers to the spatial area in the temperature distribution where there are drastic changes, exceeding the tissue heat tolerance threshold, and posing a risk to the treatment effect.

[0031] Preferably, in this embodiment, the temperature control constraint of the radiofrequency therapeutic apparatus is set according to multiple temperature deviation indexes corresponding to the temperature mutation area, referring to Figure 2 As shown, this figure is a schematic flowchart of determining the temperature control constraint in some embodiments of this application. The temperature control constraint in this embodiment can be implemented by the following steps: In step S21, the temperature fluctuation tolerance value of the radiofrequency therapeutic apparatus is determined according to multiple temperature deviation indexes within the temperature mutation area; In step S22, the heat conduction response parameter of the radiofrequency therapeutic apparatus is determined; In step S23, the safety level deviation amount of the surface of the target tissue is evaluated based on the temperature fluctuation tolerance value and the heat conduction response parameter; In step S24, the temperature control constraint of the radiofrequency therapeutic apparatus is determined through the safety level deviation amount.

[0032] Specifically, when implementing, first, from the identified temperature mutation area, the following temperature deviation indexes are extracted: the maximum temperature difference within the area, the local temperature fluctuation rate, the spatial temperature standard deviation, and the time fluctuation frequency. Based on the obtained temperature deviation indexes, combined with the tissue type and the clinical safety limit value, the temperature fluctuation tolerance value is set, that is: within a given time and space scale, the allowable maximum temperature difference range and the upper limit of the heating rate. For example: the tolerance fluctuation for skin tissue is ±1.5°C, and the heating rate <0.3°C / s. Then, using the tissue heat conduction simulation model, combined with the actual parameters of the device, including: power density, treatment head contact area, frequency, and the tissue thermophysical parameters, including: thermal conductivity, specific heat capacity, blood perfusion rate, a dynamic relationship between radiofrequency heating and temperature response is established, and the response curve of the therapeutic apparatus is obtained through experiments or numerical simulations. The heat response delay time, heat diffusion radius, and thermal inertia coefficient extracted from the response curve are used as the heat conduction response parameters of the radiofrequency therapeutic apparatus. Then, the actual temperature data is compared with the fluctuation tolerance value, and the temperature difference overrun value and the heating rate over-speed amount of each area are calculated. At the same time, combined with the heat response parameters, the prediction error window caused by control lag is calculated. For example, the temperature in the area may rise by 2°C after 1s. A safety level deviation scoring model is established through these two dimensions, that is: , where represents the safety level deviation scoring model; Represents the part where the actual temperature difference or rate exceeds the tolerance threshold; Represents the error prediction range caused by thermal inertia or hysteresis; and Represents the tissue sensitivity weight, which can be set through clinical experiments. The safety level deviation amount on the surface of the target tissue is output through the safety level deviation scoring model. Finally, the temperature control strategy is dynamically adjusted according to the safety level corresponding to the deviation amount, and the process of adjusting the temperature control strategy is used as the temperature control constraint of the radiofrequency therapeutic apparatus. The temperature control constraint of the radiofrequency therapeutic apparatus includes: safety level → normal output (original planned energy); warning level → reduce power output by 10% and increase cooling interval; risk level → start dynamic closed-loop temperature control mechanism (update temperature control instructions once per second); high-risk level → forcefully stop treatment and issue an alarm.

[0033] It should be noted that in this application, the temperature deviation index refers to the characteristic data of the internal inhomogeneity and thermal instability of the temperature field; the temperature fluctuation tolerance value refers to the acceptable temperature change range of the treatment device within a unit time and area; the heat conduction response parameter refers to the parameter set describing the kinetic relationship between the energy output of the therapeutic apparatus and the tissue temperature response; the safety level deviation amount refers to the comprehensive deviation degree between the current thermal state of the tissue and the safety control limit; the temperature control constraint refers to the energy output parameter range dynamically defined according to the current thermal state.

[0034] In step S3, the heat distribution law in the temperature mutation region is regionally connected to obtain the temperature compensation boundary corresponding to the temperature mutation region on the surface of the target tissue, and the temperature change compensation trend of the radiofrequency therapeutic apparatus is determined according to the temperature compensation boundary and the dynamic temperature data.

[0035] In this embodiment, the heat distribution law in the temperature mutation region is regionally connected to obtain the temperature compensation boundary corresponding to the temperature mutation region on the surface of the target tissue, which can be realized by the following steps: Based on the heat flow direction and gradient distribution characteristics of the heat distribution law, construct a regional connection map of the heat distribution; Generate multi-level connection constraints according to the temperature compensation requirements of adjacent mutation regions in the regional connection map; Perform heat balance path planning on the multi-level connection constraints and output the temperature compensation boundary.

[0036] In specific implementation, first, the heat flux vector field is calculated using the gradient information in the continuous temperature field image. The Fourier method or the temperature gradient vector difference method is adopted to obtain the main heat conduction direction of each point. Among them, the main heat conduction direction is negatively correlated with the temperature gradient and points to the heat diffusion path. Then, first-order and second-order gradient analyses are performed on the boundary of the temperature mutation region to obtain the temperature change rate and the curvature change trend, reflecting the turning, diffusion, or blocking characteristics of the heat flux in space. And the mutation region is discretized into graph structure units. Among them, the nodes of the graph structure unit are sub-regions with high heat flux density, and the edges are the main heat flux connection paths. A regional connectivity graph of heat distribution is constructed with the heat flux intensity, direction consistency, and spatial distance as the edge weights. Then, the temperature deviation amount is calculated for each mutation node in the regional connectivity graph. The temperature deviation amount is the difference relative to the critical physiological temperature or the target treatment temperature, and combined with the thermal conductivity and heat transfer capacity of its surrounding environment, its required heat compensation power or cooling capacity is evaluated. The adjacent nodes are classified into multi-level connectivity relationships according to the following rules, that is: strongly connected (level 1), with a clear heat flux direction, a large temperature difference, and timely compensation required; weakly connected (level 2), with an unstable or interrupted heat flux, and auxiliary regulation required; relay connected (level 3), in the transition region on the heat transfer channel, which can be used as a buffer heat path. The classified three-level connectivity relationship is encoded into a heat compensation control rule table, that is, a multi-level connectivity constraint is obtained. Finally, based on the temperature distribution, heat flux direction, heat capacity, and heat transfer efficiency of each region in the regional connectivity graph, a heat balance equation set is constructed. Among them, the heat balance equation set is determined by taking the difference between the sum of the heat input and output between a certain region and its neighboring regions and the sum of the net heat required for the current target temperature. Then, the shortest path optimization algorithm is used to find the optimal heat compensation path from the high heat source to the low heat region in the regional connectivity graph, giving priority to satisfying the level 1 connected region, and then progressively adjusting the level 2 and level 3 connected regions to ensure the overall heat field balance. The path convergence points and boundary diffusion points are extracted on the final heat balance path network, and the temperature compensation boundary is extracted through boundary interpolation and morphological contours.

[0037] It should be noted that in this application, the heat flux direction refers to the dominant path direction of heat conduction from the high-temperature region to the low-temperature region in the tissue; the gradient distribution feature refers to the rate and direction of temperature change in space; the regional connectivity graph represents the connectivity relationship of heat transfer between temperature mutation regions; the temperature compensation requirement represents the additional heat input or cooling amount required to maintain the target temperature in a specific region; the multi-level connectivity constraint refers to the hierarchical control relationship between different temperature mutation regions based on heat demand and heat connection strength; the temperature compensation boundary represents the outer boundary of the control area when the radiofrequency therapeutic apparatus controls the temperature of the surface of the target tissue during radiofrequency treatment.

[0038] Preferably, in this embodiment, the temperature change compensation trend of the radiofrequency therapeutic apparatus is determined according to the temperature compensation boundary and the dynamic temperature data, referring to Figure 3As shown, this figure is a schematic flowchart of determining the temperature change compensation trend in some embodiments of the present application. In this embodiment, the temperature change compensation trend can be determined by the following steps: In step S31, according to the time series correlation between the temperature compensation boundary and the dynamic temperature data, the spatio-temporal coupling parameter of the temperature change compensation trend is quantified; In step S32, combining the heat conduction response parameter of the radiofrequency therapeutic instrument with the tissue heat relaxation characteristics, a predictive control quantity for temperature change compensation is established; In step S33, according to the spatio-temporal coupling parameter and the predictive control quantity, the compensation efficiency gradient of the radiofrequency therapeutic instrument in different temperature compensation strategies is determined; In step S34, according to the compensation efficiency gradient, the temperature change compensation trend of the radiofrequency therapeutic instrument is determined.

[0039] In specific implementation, first, arrange the dynamic temperature data in a time series, and use the sliding window method to analyze the temperature change within a time period. Evaluate the relationship between the temperature change at each time point and the temperature compensation boundary through time series correlation analysis, that is, obtain the time series of the dynamic temperature data; then, by analyzing the time change pattern of the temperature compensation boundary and its corresponding temperature change, construct a spatio-temporal coupling model to quantify the spatio-temporal distribution characteristics of the compensation demand and the temperature change. Common methods include wavelet transform and spatio-temporal autoregressive model, and output the spatio-temporal coupling parameters of the quantified temperature change compensation trend from the spatio-temporal coupling model. Next, use the heat conduction parameters of the radiofrequency therapeutic instrument, and the heat conduction parameters include: the thermal response delay time, the thermal diffusion radius and the thermal relaxation characteristics of the tissue. Among them, the thermal relaxation characteristics include the specific heat capacity, the thermal conductivity, and the blood flow rate, and establish a temperature change model of the tissue. This temperature change model describes how the tissue accumulates and dissipates heat over time and space under the input of radiofrequency energy. Using the heat conduction parameters, predict the temperature response of the tissue under different treatment conditions through numerical simulation, calculate the temperature change compensation amount at different stages according to the simulation results, and obtain the predicted control amount of the temperature change. Then, combine the spatio-temporal coupling parameters and the predicted control amount to evaluate the compensation effect of the radiofrequency therapeutic instrument at different treatment stages. By comparing the instantaneous and cumulative effects of the temperature change, calculate the compensation efficiency gradient, that is, the efficiency change of the temperature compensation strategy at different time and space positions. Among them, the calculation methods include the gradient descent method or the Lagrange multiplier method; use the gradient value of the temperature field to measure the sensitivity of the temperature change in different regions, and combine the control amount to optimize the compensation strategy. In the high-efficiency region, increase the radiofrequency output power; in the low-efficiency region, reduce the power or strengthen the cooling, that is, obtain the compensation efficiency gradient of the radiofrequency therapeutic instrument in different temperature compensation strategies. Finally, based on the compensation efficiency gradient, analyze the response change of the radiofrequency therapeutic instrument to temperature compensation at different stages. Use the exponential smoothing method or the weighted average method to smooth the temperature change data, so as to extract the compensation trend of the temperature change during the treatment process; comprehensively consider the efficiency gradients of each region, and combine the control strategy of the radiofrequency therapeutic instrument to determine the overall temperature change compensation trend, that is, the temperature change compensation trend of the radiofrequency therapeutic instrument. For example, when the temperature compensation efficiency reaches a predetermined threshold, adjust the energy output; when the compensation efficiency is low, perform additional cooling or reduce the treatment intensity.

[0040] It should be noted that in this application, the spatio-temporal coupling parameter of the temperature change compensation trend represents the interdependence relationship describing the temperature change in time and space; the predicted control quantity represents the control input quantity required to predict the future temperature change based on the heat conduction parameter and the heat relaxation characteristic; the compensation efficiency gradient refers to the change rate of the temperature compensation effect in time and space under different temperature control strategies; the heat conduction response parameter represents the technical parameter describing the relationship between the energy output of the radiofrequency therapeutic apparatus and the tissue temperature response; the tissue heat relaxation characteristic represents the reaction speed and dissipation characteristic of the tissue to heat; the temperature change compensation trend refers to the temperature control adjustment path determined according to the change of the compensation efficiency gradient during the treatment process.

[0041] In step S4, according to the temperature control constraint and the temperature change compensation trend, multi-level radiofrequency treatment signals of the radiofrequency therapeutic apparatus in different temperature fields are determined, and the temperature control strategy of the radiofrequency therapeutic apparatus is matched according to the multi-level radiofrequency treatment signals.

[0042] In this embodiment, determining the multi-level radiofrequency treatment signals of the radiofrequency therapeutic apparatus in different temperature fields according to the temperature control constraint and the temperature change compensation trend can be implemented by the following steps; Based on the temperature control constraint and the temperature change compensation trend, construct the temperature mapping quantity of the multi-level radiofrequency signals in different temperature fields; Determine the dynamic evolution characteristics of the temperature field of the radiofrequency therapeutic apparatus in different temperature fields; According to the temperature mapping quantity and the dynamic evolution characteristics of the temperature field, determine the multi-level radiofrequency treatment signals of the radiofrequency therapeutic apparatus in different temperature fields.

[0043] In specific implementation, first, in combination with the temperature fluctuation tolerance value in the temperature control constraint, the heat conduction response parameter, and the temperature compensation efficiency gradient in the temperature change compensation trend, determine the adjustment range of the temperature control strategy in each temperature field. Use the weighted average method or the normalization method to quantify the temperature requirements of different regions and generate a temperature mapping quantity. According to the temperature compensation requirements of different regions, construct a multi-level temperature mapping function, divide each temperature interval, including: the low-temperature region, the medium-temperature region, and the high-temperature region, and map each temperature interval to different radio frequency output intensities. The mapping process can simulate the heat conduction process through the finite element analysis method to generate the temperature change curves corresponding to different radio frequency signals, that is, complete the construction of the temperature mapping quantity of the multi-level radio frequency signals in different temperature fields. Then, based on the temperature field data, in combination with the heat conduction model and the dynamic temperature data, analyze the time evolution characteristics of the temperature field during the radio frequency treatment process. The finite difference method or the finite element method can be used for numerical simulation to simulate the temperature change trends of different regions. Extract the change characteristics of the temperature field at different time points, pay attention to the evolution processes of the temperature mutation region, the thermal equilibrium region, and the temperature stable region. Through multiple simulations and comprehensive historical data, extract the dynamic evolution modes under different temperature fields and predict their future temperature change trends. Take the predicted temperature change trends as the dynamic evolution characteristics of the temperature field of the radio frequency therapeutic apparatus in different temperature fields. Finally, correspond the radio frequency treatment signal with the temperature mapping quantity, set the radio frequency power levels for different temperature intervals, for example: low power, medium power, high power and their corresponding temperature ranges. According to the dynamic evolution characteristics of the temperature field, adjust the signal output intensities of different temperature regions. According to the spatio-temporal evolution characteristics of the temperature field and the temperature mapping quantity, set multiple radio frequency signal levels, where the radio frequency signal levels include level 1 signal, level 2 signal, and level 3 signal, and optimize according to the temperature requirements corresponding to each level. The adaptive filter or the feedback adjustment algorithm can be used to dynamically adjust the radio frequency signal. During the treatment process, according to the real-time monitored temperature data and the evolution trend of the temperature field, adjust the output of the radio frequency signal in real time. For example, if the temperature of a certain region exceeds the safe range, reduce the radio frequency signal intensity, otherwise increase the radio frequency output. Take the output result as the multi-level radio frequency treatment signal of the radio frequency therapeutic apparatus in different temperature fields.

[0044] It should be noted that in this application, the temperature mapping quantity is a quantization function that describes the radio frequency treatment signal intensity corresponding to different temperature intervals; the dynamic evolution characteristics of the temperature field are the laws that describe the change of the temperature field over time, including characteristics such as the temperature change rate, the heat flow distribution, and the temperature stability; the multi-level radio frequency treatment signal refers to designing and outputting radio frequency signals of multiple power levels according to the requirements of different temperature fields.

[0045] In this embodiment, the matching of the temperature control strategy of the radio frequency therapeutic apparatus according to the multi-level radio frequency treatment signal can be implemented by the following steps: Phase-align the frequencies of the multi-level radiofrequency treatment signals with the energy distribution characteristics of the target temperature field to obtain the temperature fitting information of the radiofrequency treatment instrument; Establish the temperature mapping relationship between the temperature control strategy and the temperature field grading signal; Through a closed-loop feedback verification mechanism, fuse the temperature fitting information and the temperature mapping relationship, and output the temperature control strategy parameters after matching.

[0046] When specifically implemented, first, extract the frequency, duty cycle, and energy transfer rate of each level of signal from the multi-level radiofrequency treatment signals. Then, based on the dynamic temperature data, use thermal imaging technology combined with numerical modeling to analyze the energy aggregation regions, heat conduction paths, and heat dissipation regions in the temperature field, and perform time-frequency analysis on the signals using the short-time Fourier transform. Phase-match the energy peaks of the treatment signals with the heat concentration regions in the temperature field, and through the phase synchronization adjustment algorithm, achieve the time coherence between the signals and the thermal response of the target region, and output the matching result in the form of a "signal frequency - temperature response" mapping. Take the output matching result as the temperature fitting information of the radiofrequency treatment instrument. Then, extract the key indicators from the existing temperature control parameters, including the maximum output power, heating rate, safety temperature threshold, etc. Divide the temperature field into multiple temperature levels, including: low-temperature stability region, medium-temperature treatment region, high-temperature warning region, and associate the corresponding radiofrequency signal levels with the temperature control parameters. Use a logical decision tree or a multi-dimensional interpolation algorithm to establish a one-to-one mapping relationship between different temperature control strategies and the corresponding radiofrequency signal levels. Finally, introduce a real-time temperature monitoring module, such as an infrared thermal imaging module or an embedded thermocouple array, to collect the dynamic temperature data during the treatment process as a feedback signal. According to the error between the feedback temperature and the predicted temperature, use a fuzzy adaptive control algorithm or a proportional-integral-derivative (PID) algorithm for strategy correction. Input the temperature fitting information (the relationship between signal frequency and thermal response) and the temperature mapping relationship (the relationship between strategy and signal matching) into the control algorithm, and after fusion, output the optimal strategy parameter combination, including radiofrequency power, frequency modulation period, action time, etc., to form a real-time update mechanism, continuously optimize the parameters within the closed-loop system, and output the temperature control strategy with the highest matching degree and the most timely response.

[0047] It should be noted that in this application, the energy distribution characteristics of the target temperature field refer to the spatial distribution law of the thermal energy density generated by radiofrequency heating in different regions on and inside the tissue; the temperature fitting information refers to the data structure of the synchronization characteristics between the radiofrequency signal frequency and the tissue temperature response; the temperature field grading signal refers to the radiofrequency control signal levels corresponding to different temperature intervals; the temperature mapping relationship refers to the corresponding rule between the temperature control strategy parameters and the radiofrequency signal levels required for different temperature intervals.

[0048] It can be seen that in this application, based on the perception of dynamic temperature information, the temperature mutation region can be accurately identified. Among them, by placing the treatment head of the radiofrequency therapeutic instrument on the surface of the target tissue and collecting the dynamic temperature data of the surface of the target tissue in real time, the dynamic change information of the tissue surface temperature field can be accurately and quickly obtained, realizing the fine monitoring of the temperature change trend and regional hot spots, and effectively solving the problems of temperature monitoring delay and fuzzy distribution in the prior art. By extracting the dynamic temperature distribution characteristics to identify the temperature mutation region and setting temperature control constraints based on multiple temperature deviation indicators, the temperature control mechanism has the active protection ability for the temperature mutation region, thus avoiding tissue damage caused by abnormal heating and improving the temperature control safety and control response efficiency during the radiofrequency treatment process. By analyzing the heat distribution law of the temperature mutation region, constructing a heat distribution connection map, generating a multi-level temperature compensation boundary, and establishing a temperature change compensation trend in combination with the dynamic temperature data, the temperature compensation process has spatial coherence and time predictability, effectively improving the temperature stability during the treatment process and overcoming the local lag and global imbalance of the existing compensation strategies. Through frequency-phase alignment and closed-loop feedback mechanism, the dynamic matching between multi-level radiofrequency signals and tissue thermal response is realized, so as to intelligently output control strategies according to the temperature evolution characteristics of the actual treatment area, improving the individual adaptability and temperature control intelligence level of radiofrequency treatment and overcoming the limitations of the traditional control mode being fixed and slow to adjust. In summary, the technical solution adopted in this application can realize the intelligent matching of temperature control strategies through multi-level radiofrequency treatment signals to improve the stability of temperature control of the radiofrequency therapeutic instrument.

[0049] This application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the processes and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 a block or multiple blocks.

[0050] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium, which includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disc memories, tape memories, or any other medium that can be used to carry or store data and is computer-readable.

[0051] It should also be noted that the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent in such a process, method, commodity or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, commodity or device including the element.

Claims

1. A method for controlling a radio frequency therapeutic apparatus, characterized in that: The control method comprises the following steps: Place the treatment head of the radiofrequency therapy device on the target tissue surface, collect dynamic temperature data on the target tissue surface, and obtain dynamic change information of the temperature field on the target tissue surface in real time; Identify the temperature mutation area on the surface of the target tissue through the temperature distribution characteristics in the dynamic change information, and set the temperature control constraints of the radiofrequency therapeutic device according to multiple temperature deviation indicators corresponding to the temperature mutation area; Performing regional connection on the heat distribution law in the temperature mutation area to obtain a temperature compensation boundary corresponding to the temperature mutation area on the surface of the target tissue, and determining the temperature change compensation trend of the radiofrequency therapeutic apparatus according to the temperature compensation boundary and the dynamic temperature data; A multi-level radio frequency therapy signal of the radio frequency therapy apparatus in different temperature fields is determined according to the temperature control constraint and the temperature change compensation trend, and a temperature control strategy of the radio frequency therapy apparatus is matched according to the multi-level radio frequency therapy signal.

2. A radio frequency therapeutic apparatus control method as claimed in claim 1, characterized in that: The dynamic change information refers to the continuous distribution and change trend data of the temperature field on the time axis.

3. A radio frequency therapeutic apparatus control method as claimed in claim 1, characterized in that: Identifying the temperature mutation area on the surface of the target tissue by using the temperature distribution characteristics in the dynamic change information specifically includes: Determining temperature distribution characteristics in the dynamic change information; Determining a temperature gradient variation interval on the target tissue surface according to the temperature distribution characteristics; Determine the dynamic discrimination index of the sudden change of temperature on the surface of the target tissue; The temperature mutation area on the surface of the target tissue is identified according to the temperature gradient change interval and the dynamic discrimination index.

4. A radio frequency therapeutic apparatus control method as claimed in claim 1, characterized in that: The temperature mutation area refers to a spatial area where a drastic change occurs in the temperature distribution, exceeds the heat tolerance threshold of the tissue, and poses a risk to the treatment effect.

5. A radio frequency therapeutic apparatus control method as claimed in claim 1, characterized in that: Setting the temperature control constraints of the radiofrequency therapeutic apparatus according to the multiple temperature deviation indicators corresponding to the temperature mutation area specifically includes: Determining a temperature fluctuation tolerance value of the radiofrequency therapeutic apparatus according to a plurality of temperature deviation indicators in the temperature mutation area; Determine the thermal conduction response parameters of the radiofrequency therapy device; evaluating a safety level deviation of a target tissue surface based on the temperature fluctuation tolerance value and the thermal conduction response parameter; The temperature control constraint of the radio frequency therapy device is determined by the safety level deviation.

6. A radio frequency therapeutic apparatus control method as claimed in claim 1, characterized in that: Performing regional connection on the heat distribution law in the temperature mutation region to obtain the temperature compensation boundary corresponding to the temperature mutation region on the surface of the target tissue specifically includes: Based on the heat flow direction and gradient distribution characteristics of the heat distribution law, a regional connectivity map of heat distribution is constructed; Generate multi-level connectivity constraints according to temperature compensation requirements of adjacent mutation regions in the regional connectivity map; Thermal balance path planning is performed on the multi-level connectivity constraints, and a temperature compensation boundary is output.

7. A radio frequency therapeutic apparatus control method as claimed in claim 1, characterized in that: The temperature compensation boundary represents the outer boundary of the control area when the radio frequency therapeutic device controls the temperature of the target tissue surface during radio frequency treatment.

8. A radio frequency therapeutic apparatus control method as claimed in claim 1, characterized in that: Determining the temperature variation compensation trend of the radiofrequency therapeutic apparatus according to the temperature compensation boundary and the dynamic temperature data specifically includes: quantifying the spatiotemporal coupling parameters of the temperature change compensation trend according to the time series correlation between the temperature compensation boundary and the dynamic temperature data; Combine the heat conduction response parameters of the radiofrequency therapy device with the thermal relaxation characteristics of the tissue to establish the predictive control quantity of temperature change compensation; Determining the compensation efficiency gradient of the radiofrequency therapeutic apparatus in different temperature compensation strategies according to the spatiotemporal coupling parameter and the predicted control amount; The temperature variation compensation trend of the radiofrequency therapeutic apparatus is determined according to the compensation efficiency gradient.

9. A radio frequency therapeutic apparatus control method as claimed in claim 1, characterized in that: Determining the multi-level radio frequency treatment signal of the radio frequency treatment device in different temperature fields according to the temperature control constraint and the temperature change compensation trend specifically includes: Based on the temperature control constraint and the temperature change compensation trend, constructing a temperature mapping amount of a multi-level radio frequency signal in different temperature fields; Determine the dynamic evolution characteristics of the temperature field of the radiofrequency therapy device in different temperature fields; The multi-level radio frequency treatment signals of the radio frequency treatment device in different temperature fields are determined according to the temperature mapping amount and the dynamic evolution characteristics of the temperature field.

10. A radio frequency therapeutic apparatus control method as claimed in claim 1, characterized in that: Matching the temperature control strategy of the radio frequency therapeutic device according to the multi-level radio frequency therapeutic signal specifically includes: Phase-align the frequency of the multi-level radio frequency treatment signal with the energy distribution characteristics of the target temperature field to obtain temperature fitting information of the radio frequency treatment device; Establishing a temperature mapping relationship between the temperature control strategy and the temperature field classification signal; The temperature fitting information and the temperature mapping relationship are integrated through a closed-loop feedback verification mechanism to output matched temperature control strategy parameters.

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