Radiofrequency hyperthermia equipment test system

Abstract

The present invention discloses a radio frequency hyperthermia equipment testing system, which relates to the technical field of equipment testing and is used to solve the problems of increased uncertainty in the energy transmission process and reduced system output stability and response accuracy. The system receives the original signal during the operation of the radio frequency hyperthermia equipment, removes high-frequency noise through a first-order passive RC low-pass filter, converts it into a current signal, and calculates the output power in combination with an analog multiplier, and performs difference analysis in conjunction with the ideal power. At the same time, a fast Fourier transform is performed on the original signal to extract the frequency concentration and calculate the heat concentration coefficient. The tissue temperature at the needle tip is monitored based on an optical fiber fluorescence sensor, and the fluorescence detection temperature and the observed temperature value are calculated in combination with the fluorescence lifetime. A difference analysis is performed to obtain a thermal response deviation factor. The two are combined to obtain a feedback calibration result, which is used for equipment performance optimization to achieve real-time monitoring of the energy state and identification of abnormal heat accumulation.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment testing, and more particularly to a radio frequency hyperthermia equipment testing system. Background Art

[0002] Radio frequency thermal technology is widely used in a variety of industrial and experimental systems to achieve energy transmission and thermal field control of specific materials or target areas. Such systems usually output radio frequency energy to a specific location through high-frequency signal driving to form a localized thermal effect.

[0003] The existing technology has the following deficiencies:

[0004] At present, in actual application, the RF energy output state, frequency stability, power control accuracy and thermal response of the target area are all affected by various environmental and equipment parameters. It is impossible to associate power fluctuations with frequency energy distribution for effective judgment, resulting in the inability to issue adjustment prompts in time when the thermal output is abnormal, increasing the uncertainty of the energy transmission process and reducing the output stability and response accuracy of the system. Therefore, a RF hyperthermia equipment testing system is proposed.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a radio frequency hyperthermia equipment testing system, which solves the problems raised in the above-mentioned background technology by utilizing a multi-channel processing mechanism of the original signal, a power-frequency correlation modeling method and a feedback judgment mechanism based on thermal effect response.

[0007] To achieve the above objectives, the present invention provides the following technical solutions: a radio frequency hyperthermia device testing system, comprising a signal acquisition and processing module, a power measurement module, a frequency analysis module, and a temperature detection module, wherein the electrical signals of the modules are connected:

[0008] The signal acquisition and processing module is used to receive the original signal from the radio frequency hyperthermia device and distribute the original signal to the power measurement module and the frequency analysis module for processing;

[0009] The power measurement module uses a low-pass filter to remove high-frequency components from the original signal, converts the processed original signal into current, and detects it through an ammeter. The analog multiplier calculates the output power of the radiofrequency hyperthermia device based on the ammeter detection result and the real-time voltage, and transmits the calculated value to the frequency analysis module.

[0010] The frequency analysis module is used to receive the output power of the radio frequency hyperthermia device and process it to obtain the power difference of the radio frequency hyperthermia device, and perform fast Fourier transform on the original signal to extract the frequency concentration index, integrate the power difference of the radio frequency hyperthermia device, obtain the heat concentration coefficient and transmit it to the temperature detection module;

[0011] The temperature detection module measures the temperature distribution of the tissue contacting the needle based on a fiber optic fluorescence sensor, calculates the fluorescence detection temperature value using the relationship between the fluorescence afterglow lifetime and temperature, and then processes the thermal response deviation factor based on the average temperature of the contact electrode area, and comprehensively considers the heat concentration coefficient to determine and issue a calibration prompt.

[0012] In a preferred embodiment, in the signal acquisition and processing module, the original signal generated by the radiofrequency hyperthermia device during operation is acquired;

[0013] The cutoff frequency is calculated by the resistance and capacitance of the low-pass filter;

[0014] Input the original signal into the low-pass filter to obtain the processed original signal:

[0015] If the signal frequency component in the original signal is lower than the cutoff frequency, the signal frequency component is retained; otherwise, the signal frequency component is filtered;

[0016] The processed original signal is converted into a current signal that is linearly proportional to the corresponding original signal, and the current value of the current signal is detected by an ammeter.

[0017] In a preferred embodiment, in the power measurement module, the voltage value of the radiofrequency hyperthermia device is collected in real time;

[0018] The product of the current value of the current signal and the voltage value of the radio frequency hyperthermia device is used as the output power of the radio frequency hyperthermia device.

[0019] In a preferred embodiment, in the frequency analysis module, the target power setting value input by the user and the real-time monitoring parameters are combined, and a preset prediction model is used to obtain the ideal power of the radiofrequency hyperthermia device;

[0020] The absolute difference between the output power of the radio frequency hyperthermia device and the ideal power of the radio frequency hyperthermia device is calculated to obtain the power difference of the radio frequency hyperthermia device.

[0021] In a preferred embodiment, in the frequency analysis module, the original signal is subjected to fast Fourier transform processing to extract the frequency concentration index. The specific process is as follows:

[0022] The original signal from the receiving signal acquisition and processing module is converted into a frequency domain signal through fast Fourier transform to generate a normalized spectrum. The ratio of the main frequency band energy to the total energy in the normalized spectrum is used as the frequency concentration index;

[0023] The power difference and frequency concentration index of the radiofrequency hyperthermia device were normalized.

[0024] In a preferred embodiment, in the frequency analysis module, the power difference and frequency concentration index of the radiofrequency hyperthermia device after normalization are substituted into the inverse tangent mapping function based on the difference to obtain the heat concentration coefficient, which is specifically expressed as follows:

[0025] ;

[0026] Where, is the heat concentration coefficient, is the frequency concentration index after normalization, is the power difference of the radiofrequency hyperthermia device after normalization, 、 are the influence weights corresponding to the power difference and frequency concentration index of the radiofrequency hyperthermia equipment after normalization, Because the function itself has nonlinear compression characteristics, the outer accomplish Standardized processing.

[0027] In a preferred embodiment, in the temperature detection module, the temperature distribution of the tissue contacting the needle is measured based on the optical fiber fluorescence sensor, and the relationship between the fluorescence afterglow lifetime and temperature is used to calculate the fluorescence detection temperature value;

[0028] By emitting an excitation light pulse to the area where the needle contacts the tissue, the fluorescent material is stimulated to produce a fluorescent response, and the afterglow decay process of the fluorescence signal is received and recorded to obtain the fluorescence afterglow lifetime. The fluorescence detection temperature value is obtained using the functional relationship model between the fluorescence afterglow lifetime and temperature.

[0029] The observed temperature value is obtained based on the average temperature of the contact electrode area.

[0030] In a preferred embodiment, in the temperature detection module, based on the infrared temperature sensing array element, the temperature of the preset points in the contact electrode area is measured to obtain a set of discrete temperature values. The discrete temperature values ​​are statistically analyzed according to the preset electrode area division scheme, and the observed temperature value is obtained by weighted average calculation.

[0031] Substitute the fluorescence detection temperature value and the observed temperature value into the dual-temperature fusion comparison strategy to obtain the thermal response deviation factor. The specific steps are as follows:

[0032] The deviations between the fluorescence detection temperature value and the observed temperature value and the target temperature zone are calculated respectively to obtain the observed temperature deviation factor and the fluorescence temperature deviation factor. The weight coefficient is introduced to fuse the two types of temperature response information to obtain the thermal response deviation factor. The specific formula is as follows:

[0033] ;

[0034] in, is the thermal response deviation factor, is the observed temperature deviation factor, is the fluorescence temperature deviation factor, is the observed temperature weight, is the fluorescence detection temperature weight.

[0035] In a preferred embodiment, in the temperature detection module, after normalizing the thermal response deviation factor, the thermal response deviation factor and the heat concentration coefficient are substituted into the product amplification difference adjustment model to obtain the thermal effect calibration coefficient. The specific formula is as follows:

[0036] ;

[0037] Where, is the thermal effect calibration coefficient, is the thermal response deviation factor after normalization, is the heat concentration coefficient, is the nonlinear response tuning parameter.

[0038] In a preferred embodiment, in the temperature detection module, the thermal effect calibration coefficient is compared with a preset calibration threshold, and if the thermal effect calibration coefficient is greater than or equal to the preset calibration threshold, a calibration prompt is issued;

[0039] If the thermal effect calibration factor is less than the preset calibration threshold, no calibration reminder is required.

[0040] Technical effects and advantages of the present invention:

[0041] The present invention receives the original signal output by the radio frequency hyperthermia device during operation, removes the high-frequency noise component through a first-order passive RC low-pass filter, and then converts the smoothed signal into a current signal. The output power value is calculated through current sampling and analog multiplier operation, and difference analysis is performed in combination with the ideal power. At the same time, a fast Fourier transform is performed on the original signal to extract the frequency concentration, and finally the heat concentration coefficient is calculated. The tissue temperature at the treatment needle tip is monitored in real time based on the optical fiber fluorescence sensor, and the fluorescence detection temperature and the observed temperature value are calculated in combination with the fluorescence lifetime. The difference analysis is performed between the two to obtain the thermal response deviation factor. The thermal response deviation factor and the heat concentration coefficient are combined to output a feedback calibration result for guiding the optimization of equipment performance, thereby realizing real-time monitoring of the radio frequency energy output status and comprehensive evaluation of multi-dimensional parameters, and being able to effectively identify abnormal heat distribution caused by power deviation and frequency imbalance. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flow chart of the implementation of the radiofrequency hyperthermia equipment testing system of the present invention.

[0043] Figure 2 Schematic diagram of the steps of the radiofrequency hyperthermia device testing system of the present invention. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0045] The present invention receives the original signal output by the radio frequency hyperthermia device during operation, removes the high-frequency noise component through a first-order passive RC low-pass filter, and then converts the smoothed signal into a current signal. The output power value is calculated through current sampling and analog multiplier operation, and a difference analysis is performed in combination with the ideal power. At the same time, a fast Fourier transform is performed on the original signal to extract the frequency concentration, and finally the heat concentration coefficient is calculated. The tissue temperature at the treatment needle tip is monitored in real time based on the fiber optic fluorescence sensor, and the fluorescence detection temperature and the observed temperature value are calculated in combination with the fluorescence lifetime. The difference analysis between the two is performed to obtain the thermal response deviation factor. The thermal response deviation factor and the heat concentration coefficient are combined to output a feedback calibration result to guide the performance optimization of the device.

[0046] Example 1

[0047] See also Figures 1 to 2,RF hyperthermia equipment testing system, including signal acquisition and processing module, power measurement module, frequency analysis module and temperature detection module, and electrical signal connection of each module;

[0048] The functions of each module are as follows:

[0049] The signal acquisition and processing module is used to receive the original signal from the radio frequency hyperthermia device and distribute the original signal to the power measurement module and the frequency analysis module for processing;

[0050] The power measurement module uses a low-pass filter to remove high-frequency components from the original signal, converts the processed original signal into current, and detects it through an ammeter. The analog multiplier calculates the output power of the radiofrequency hyperthermia device based on the ammeter detection result and the real-time voltage, and transmits the calculated value to the frequency analysis module.

[0051] The frequency analysis module is used to receive the output power of the radio frequency hyperthermia device and process it to obtain the power difference of the radio frequency hyperthermia device, and perform fast Fourier transform on the original signal to extract the frequency concentration index, integrate the power difference of the radio frequency hyperthermia device, obtain the heat concentration coefficient and transmit it to the temperature detection module;

[0052] The temperature detection module measures the temperature distribution of the tissue contacting the needle based on a fiber optic fluorescence sensor, calculates the fluorescence detection temperature value using the relationship between the fluorescence afterglow lifetime and temperature, and then processes the thermal response deviation factor based on the average temperature of the contact electrode area, and comprehensively considers the heat concentration coefficient to determine and issue a calibration prompt.

[0053] The specific implementation is as follows:

[0054] In the signal acquisition and processing module, the original signal generated by the radiofrequency hyperthermia device during operation is collected through an impedance matching sampling circuit. The original signal is not preprocessed or transformed in any form and is transmitted to the power measurement module and frequency analysis module through a dual-channel output structure to ensure that each module receives a completely consistent original signal.

[0055] It should be noted that the impedance matching sampling circuit is a circuit structure used to achieve non-interference sampling of high-frequency signals and ensure impedance matching of the signal transmission path; the dual-channel output structure is a structure that can output the same original input signal to two functional modules at the same time without changing the physical characteristics of the original input signal.

[0056] In the power measurement module, the original signal transmitted by the signal acquisition and processing module is received and input into the low-pass filter inside the power measurement module. The low-pass filter adopts a first-order passive RC circuit structure, and the specific design satisfies the following formula:

[0057] ;

[0058] in, is the cutoff frequency, is the resistance of the low-pass filter, is the capacitor of the low-pass filter.

[0059] If the signal frequency component in the original signal is lower than the cutoff frequency, the signal frequency component is retained; otherwise, the signal frequency component is filtered.

[0060] The low-pass filter only allows signal frequency components with frequencies lower than the cutoff frequency to pass through, reduces the high-frequency noise interference components in the original signal, and smoothes the peak shape, thereby removing the high-frequency signal frequency components in the original signal.

[0061] The low-pass filter filters the frequency components of the signal to obtain the processed original signal, and performs current conversion and electric power calculation operations on the processed original signal:

[0062] The processed original signal is converted into a current signal that is linearly proportional to the corresponding original signal through a precision current sampling resistor, and the current signal is detected using an ammeter to obtain the current value of the current signal.

[0063] The voltage value of the radio frequency hyperthermia device is collected in real time through a voltmeter, and the current value of the current signal and the voltage value of the radio frequency hyperthermia device are input into an analog multiplier for electric power calculation. The analog multiplier performs a product operation on the current value of the current signal and the voltage value of the radio frequency hyperthermia device to obtain the output power of the radio frequency hyperthermia device.

[0064] The output power of the radiofrequency hyperthermia device is transmitted to the frequency analysis module for subsequent power analysis and calculation of the heat concentration factor.

[0065] It should be noted that a low-pass filter is an analog signal processing circuit with frequency selectivity; a first-order passive RC circuit structure is a first-order linear filter circuit composed of a resistor element and a capacitor element connected in a specific way; a precision current sampling resistor is a resistor device used to convert a passing voltage signal into a current signal according to Ohm's law; an analog multiplier is an analog computing circuit device with the function of performing multiplication operations on two continuously changing analog signals, which will not be described in detail here.

[0066] In the frequency analysis module, after receiving the output power of the radiofrequency hyperthermia device, the ideal power of the radiofrequency hyperthermia device is simultaneously acquired;

[0067] The ideal power of the RF hyperthermia device is a power baseline value determined based on the device design parameters, the set treatment power target, and a pre-calibrated performance model. It usually corresponds to the expected power level output by the device under standard operating conditions. The acquisition logic is to combine the target power setting value entered by the user and the real-time monitoring parameters, and use a preset prediction model to obtain the ideal power of the RF hyperthermia device.

[0068] Specifically, the target power setting value input by the user is obtained through the device operation interface or the input module in the control system. The real-time monitoring parameters include but are not limited to the voltage, current, load impedance, temperature sensor data of the RF signal, etc. The specific monitoring parameters are determined by the experimenters based on actual application requirements and are not detailed here.

[0069] It should be noted that the preset prediction model is established by our experimental staff based on the historical operating data of the equipment, environmental parameters, and empirical rules set by the treatment plan. The specific model can be set as a linear regression model, support vector machine model, neural network model, or other machine learning model. The selection and calling of the model is determined by our experimental staff based on experimental requirements and data performance, and will not be elaborated here.

[0070] Calculate the absolute difference between the output power of the radiofrequency hyperthermia device and the ideal power of the radiofrequency hyperthermia device to obtain the power difference of the radiofrequency hyperthermia device;

[0071] Furthermore, the original signal is processed by fast Fourier transform to extract the frequency concentration index. The specific process is as follows:

[0072] A1: Collect the original signal from the output of the radiofrequency hyperthermia device. This signal is a high-frequency AC signal in the time domain, containing the main frequency components of the radiofrequency excitation and its harmonic components, which can be expressed as:

[0073] ;

[0074] Where, is the signal amplitude, is the center frequency, is the phase, is the time-varying disturbance term, is a time variable, representing the instantaneous state of the signal, is the instantaneous voltage that changes with time;

[0075] A2: For the original time signal Perform fast Fourier transform processing and convert it into frequency domain signal , obtain the mapping relationship between frequency and amplitude:

[0076] ;

[0077] Where, It is the abbreviation of Fast Fourier Transform;

[0078] Obtain a spectrum image, including main frequency components, harmonics, and background noise;

[0079] A3: Normalize the spectrum to obtain the unit energy density spectrum;

[0080] ;

[0081] Where, Indicates the center frequency The relative energy density at represents an infinitesimal increment of frequency change, specifically, The role of is to indicate who is being integrated in the integral. In the frequency domain energy density normalization integral formula, It is a standard calculus symbol that cannot be omitted;

[0082] A4: Identify the main frequency point, that is The frequency point corresponding to the maximum value and the symmetrical bandwidth range are set:

[0083] ;

[0084] Where, The main frequency point, is the symmetrical bandwidth range, is a frequency variable;

[0085] A5: Based on the distribution of spectrum energy in the main frequency band, the frequency concentration index is calculated. It is defined as the ratio of the main frequency band energy to the total energy:

[0086] ;

[0087] In the formula, the numerator represents the energy ratio within the frequency concentration interval, reflecting the degree to which the RF signal energy is concentrated near the main frequency, and the denominator represents the energy in the total frequency domain. is the frequency concentration index, 、 are the upper and lower limits of the analysis frequency range, respectively;

[0088] Specifically, the closer the value of the frequency concentration index is to 1, the more concentrated the energy is near the main frequency, indicating a more focused heat output. The closer the frequency concentration index is to 0, the more scattered the frequency distribution may be, which may lead to heat diffusion or poor focusing.

[0089] It should be noted that the original signal transmitted to the frequency analysis module retains the high-frequency components in the original signal to ensure the accuracy and integrity of the frequency analysis. Specifically, a bandpass filter or a high-pass filter is used to retain and extract the high-frequency components. The filtering parameters are set according to the operating frequency range of the radiofrequency hyperthermia device and are not described in detail here.

[0090] Normalizing the power difference and frequency concentration index of the radiofrequency hyperthermia device so that the power difference and frequency concentration index of the radiofrequency hyperthermia device are kept in the same dimension;

[0091] It should be noted that the standardization methods include but are not limited to standard linear transformation based on interval scaling, Z-Score standardization method based on statistics, or normalization method based on nonlinear mapping function. The application methods of standardization are not described in detail here.

[0092] Substitute the normalized power difference and frequency concentration index of the radiofrequency hyperthermia device into the inverse tangent mapping function based on the difference to obtain the heat concentration coefficient. The specific formula is expressed as follows:

[0093] ;

[0094] Where, is the heat concentration coefficient, is the frequency concentration index after normalization, is the power difference of the radiofrequency hyperthermia device after normalization, 、 are the influence weights corresponding to the power difference and frequency concentration index of the radiofrequency hyperthermia equipment after normalization, Because the function itself has nonlinear compression characteristics, it can enhance the sensitivity of discrimination at the critical point. accomplish Standardized processing;

[0095] It should be noted that when the power difference of the radiofrequency hyperthermia device after normalization is larger and the frequency concentration index after normalization is smaller, the heat concentration coefficient is lower, indicating that the heat distribution of the radiofrequency hyperthermia device is dispersed;

[0096] On the contrary, if the power difference of the radio frequency hyperthermia device after normalization is smaller and the frequency concentration index after normalization is larger, the heat concentration coefficient is higher, indicating that the heat distribution of the radio frequency hyperthermia device is concentrated.

[0097] In the temperature detection module, the temperature distribution of the tissue contacting the needle is measured based on the optical fiber fluorescence sensor, and the fluorescence detection temperature value is calculated based on the relationship between the fluorescence afterglow lifetime and temperature;

[0098] The fluorescence detection temperature value is based on the fluorescence afterglow lifetime measured by the fiber optic fluorescence sensor. The instantaneous temperature value of the tissue contact needle area is calculated through the quantitative functional relationship between the fluorescence afterglow lifetime and temperature. The acquisition logic is to emit an excitation light pulse to the tissue contact needle area to stimulate the fluorescent material to produce a fluorescent response, receive and record the afterglow decay process of the fluorescence signal, and obtain the fluorescence afterglow lifetime. The fluorescence detection temperature value is obtained using the functional relationship model between the fluorescence afterglow lifetime and temperature.

[0099] It should be noted that fiber optic fluorescence sensors are a type of highly sensitive temperature detection device built on the principle of coupling fluorescent materials with optical fibers. They induce fluorescence emission by introducing an excitation light signal of a specific wavelength into the fluorescent material pre-placed in the contact area, and detect changes in its luminescence characteristics through the optical fiber. This sensor has the characteristics of fast response speed, strong anti-electromagnetic interference ability, and suitability for operation in radio frequency electromagnetic field environments. It is particularly suitable for non-electrical contact temperature measurement of tissue surfaces or contact points during radio frequency hyperthermia treatment.

[0100] Fluorescence afterglow lifetime refers to the time required for the emission intensity of a fluorescent material to decay from its initial peak to a preset proportion of its original intensity after the excitation light stops irradiating it. The unit is microseconds or nanoseconds. This parameter reflects the average lifetime of the excited state of the fluorescent material and has the physical property of being highly sensitive to ambient temperature.

[0101] Furthermore, the predetermined ratio of the emission light intensity decaying from the initial peak to the original intensity is determined by the experimenter based on the fluorescence decay characteristic parameters of the selected fluorescent material and the experimental data of the temperature response stability, and will not be elaborated here;

[0102] The functional relationship model between the fluorescence afterglow lifetime and temperature is usually a monotonically changing analytical function, the form of which can be determined according to the temperature response characteristics of the selected fluorescent material. Commonly used models include but are not limited to exponential decay models, linear models, or empirical fitting models, etc., which will not be described in detail here.

[0103] The observed temperature value is obtained based on the average temperature of the contact electrode area;

[0104] The contact electrode area is the area range set by the experimenters based on the device structural parameters and the actual distribution characteristics of the RF energy. The specific setting rules and area change period are not limited, but are set by the experimenters based on the specific scenario and will not be elaborated here.

[0105] The observed temperature value refers to the average temperature parameter of the overall thermal effect of the region obtained by spatially sampling and processing the temperature distribution of the contact electrode area during radiofrequency hyperthermia. Its acquisition logic is based on infrared temperature sensing array elements, which measure the temperature of preset points in the contact electrode area to obtain a set of discrete temperature values. Based on the preset electrode area division scheme, the discrete temperature values ​​are statistically analyzed and weighted averaged to obtain the observed temperature value.

[0106] Among them, infrared temperature sensing array elements refer to two-dimensional or multi-dimensional imaging detection components composed of multiple infrared sensitive units. They have non-contact, high spatial resolution, and real-time response temperature sensing capabilities. They can perform multi-point synchronous temperature measurement of the target area in an array manner. They are suitable for radiofrequency thermal therapy application scenarios where electromagnetic interference is strong or where electrical contact sensors are not suitable.

[0107] The preset points in the contact electrode area are determined by our researchers based on the electrode's geometric structure characteristics and the results of the energy conduction path simulation analysis. The spatial location of these points can correspond to the central axis, edge radiation area, or temperature-sensitive area of ​​the RF electrode. The specific distribution is not limited.

[0108] The preset electrode area division scheme is a spatial division rule set by the experimenter based on the electrode area size, shape structure and expected area. It can be a symmetrical grid division, an isoenergetic and isothermal distribution division, or a non-uniform area division based on thermal field simulation results.

[0109] Furthermore, each preset point in the corresponding divided area is assigned a different weight in the weighted average calculation process. The weight value can be set based on the location of the point, the energy density simulation result, or the historical temperature measurement response curve. The spatial coordinates, number, and weight function form of the specific point are not limited and are independently configured by the experimenter according to the application requirements. Furthermore, the weighted average algorithm is common knowledge among the experimenters and will not be described in detail here.

[0110] Substitute the fluorescence detection temperature value and the observed temperature value into the dual-temperature fusion comparison strategy to obtain the thermal response deviation factor. The specific steps are as follows:

[0111] Calculate the deviation between the fluorescence detection temperature value and the observed temperature value and the target temperature zone respectively. The target temperature zone is the target temperature range preset by the experimenter. The specific range size is not limited. The specific calculation process is as follows:

[0112] ;

[0113] Where, is the observed temperature value, is the fluorescence detection temperature value, is the center temperature of the target temperature zone, is the maximum value of the preset target temperature range, is the minimum value of the preset target temperature range, is the observed temperature deviation factor, reflecting the degree of deviation of the surface thermal response. is the fluorescence temperature deviation factor, which reflects the degree of deviation of the contact interface or internal thermal response;

[0114] Furthermore, the calculation formula for the center temperature of the standard temperature zone is:

[0115] ;

[0116] Where, is the center temperature of the target temperature zone;

[0117] The observation temperature deviation factor and the fluorescence temperature deviation factor are introduced into the weight coefficient to fuse the two types of temperature response information to obtain the thermal response deviation factor. The specific formula is as follows:

[0118] ;

[0119] in is the thermal response deviation factor, is the observed temperature weight, is the fluorescence detection temperature weight;

[0120] Specifically, the weight coefficient is set by the experimenter based on the device response delay, the importance of the measurement location, and actual clinical needs, and will not be described in detail here;

[0121] Normalize the thermal response deviation factor so that the thermal response deviation factor and the heat concentration coefficient are kept in the same dimension;

[0122] Substitute the thermal response deviation factor and the heat concentration coefficient into the product amplification difference adjustment model to obtain the thermal effect calibration coefficient. The specific formula is as follows:

[0123] ;

[0124] Where, is the thermal effect calibration coefficient, is the thermal response deviation factor after normalization, is the heat concentration coefficient, is the nonlinear response adjustment parameter;

[0125] It should be noted that when the thermal response deviation factor is larger and the heat concentration coefficient is smaller, the thermal effect calibration coefficient is smaller, and the current energy output process deviates from the target range and the heat concentration effect is poor, and a calibration prompt needs to be issued. Conversely, when the thermal response deviation factor is smaller and the heat concentration coefficient is larger, the thermal effect calibration coefficient is larger, and the current energy output process responds accurately and has good energy concentration, maintaining the current power control state and running stably, and no calibration prompt needs to be issued.

[0126] Compare the thermal effect calibration coefficient with the preset calibration threshold. If the thermal effect calibration coefficient is greater than or equal to the preset calibration threshold, it means that the response accuracy and heat concentration of the current energy output process meet the expected standards, and a calibration prompt is issued. If the thermal effect calibration coefficient is less than the preset calibration threshold, it means that there is a response deviation or the heat distribution is not concentrated in the current energy output process, and no calibration prompt is required.

[0127] It should be noted that the preset calibration thresholds are obtained by the experimenters based on the safety tolerance range and the evaluation benchmarks preset by typical application conditions, and will not be elaborated here;

[0128] Optionally, the calibration prompt can set different calibration prompt rules according to the specific values ​​of the heat concentration coefficient and the thermal response deviation factor. The specific examples are as follows:

[0129] When the thermal effect calibration coefficient is greater than or equal to the preset calibration threshold, the specific values ​​of the heat concentration coefficient and the thermal response deviation factor are analyzed. If the heat concentration coefficient is still within (e.g., approximately 0.7 to 0.85), but the thermal response deviation factor is slightly higher (e.g., 0.15 to 0.3), the system will issue a prompt and enter the calibration mode.

[0130] When the heat concentration coefficient is low (e.g. less than 0.7) and the thermal response deviation factor is significantly high (e.g. greater than 0.3), the system issues a significant calibration prompt to check the energy output consistency;

[0131] If the heat concentration coefficient is lower than the preset critical value (e.g. below 0.5), regardless of the value range of the thermal response deviation factor, it is considered a potential heat accumulation abnormality state, and the system issues a high-priority calibration prompt and enters the safety protection process;

[0132] It should be noted that the above rules are examples. The specific threshold settings and prompt level divisions can be flexibly configured by the experimenters based on system performance parameters, custom scenario requirements and feedback strategies, and will not be elaborated here.

[0133] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0134] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0135] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0136] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0137] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. Radiofrequency hyperthermia equipment testing system, characterized by: It includes signal acquisition and processing module, power measurement module, frequency analysis module and temperature detection module. The electrical signal connections of each module are as follows: The signal acquisition and processing module is used to receive the original signal from the radio frequency hyperthermia device and distribute the original signal to the power measurement module and the frequency analysis module for processing; The power measurement module uses a low-pass filter to remove high-frequency components from the original signal, converts the processed original signal into current, and detects it through an ammeter. The analog multiplier calculates the output power of the radiofrequency hyperthermia device based on the ammeter detection result and the real-time voltage, and transmits the calculated value to the frequency analysis module. The frequency analysis module is used to receive the output power of the radio frequency hyperthermia device and process it to obtain the power difference of the radio frequency hyperthermia device, and perform fast Fourier transform on the original signal to extract the frequency concentration index, integrate the power difference of the radio frequency hyperthermia device, obtain the heat concentration coefficient and transmit it to the temperature detection module; The temperature detection module uses a fiber optic fluorescence sensor to measure the temperature distribution of the tissue contacting the needle. The relationship between the fluorescence afterglow lifetime and temperature is used to calculate the fluorescence detection temperature value. The thermal response deviation factor is then processed based on the average temperature of the contact electrode area. The heat concentration coefficient is then used to determine the calibration prompt. In the frequency analysis module, the original signal is processed by fast Fourier transform to extract the frequency concentration index. The specific process is as follows: The original signal from the receiving signal acquisition and processing module is converted into a frequency domain signal through fast Fourier transform to generate a normalized spectrum. The ratio of the main frequency band energy to the total energy in the normalized spectrum is used as the frequency concentration index; Normalize the power difference and frequency concentration index of the radiofrequency hyperthermia device; Substitute the normalized power difference and frequency concentration index of the radiofrequency hyperthermia device into the inverse tangent mapping function based on the difference to obtain the heat concentration coefficient. The specific formula is expressed as follows: ； Where, is the heat concentration coefficient, is the frequency concentration index after normalization, is the power difference of the radiofrequency hyperthermia device after normalization, 、 are the influence weights corresponding to the power difference of the radiofrequency hyperthermia equipment and the frequency concentration index after normalization, Because the function itself has nonlinear compression characteristics, the outer accomplish Standardized processing.

2. The radiofrequency hyperthermia device testing system according to claim 1, characterized in that: In the signal acquisition and processing module, the original signal generated by the radiofrequency hyperthermia device during operation is collected; The cutoff frequency is calculated by the resistance and capacitance of the low-pass filter; Input the original signal into the low-pass filter to obtain the processed original signal: If the signal frequency component in the original signal is lower than the cutoff frequency, the signal frequency component is retained; otherwise, the signal frequency component is filtered; The processed original signal is converted into a current signal that is linearly proportional to the corresponding original signal, and the current value of the current signal is detected by an ammeter.

3. The radiofrequency hyperthermia device testing system according to claim 2, characterized in that: In the power measurement module, the voltage value of the radiofrequency hyperthermia device is collected in real time; The product of the current value of the current signal and the voltage value of the radio frequency hyperthermia device is used as the output power of the radio frequency hyperthermia device.

4. The radiofrequency hyperthermia device testing system according to claim 3, characterized in that: In the frequency analysis module, the target power setting value entered by the user and the real-time monitoring parameters are combined, and the preset prediction model is used to obtain the ideal power of the radiofrequency hyperthermia device; The absolute difference between the output power of the radio frequency hyperthermia device and the ideal power of the radio frequency hyperthermia device is calculated to obtain the power difference of the radio frequency hyperthermia device.

5. The radiofrequency hyperthermia device testing system according to claim 1, characterized in that: In the temperature detection module, the temperature distribution of the tissue contacting the needle is measured based on the optical fiber fluorescence sensor, and the fluorescence detection temperature value is calculated based on the relationship between the fluorescence afterglow lifetime and temperature; By emitting an excitation light pulse to the area where the needle contacts the tissue, the fluorescent material is stimulated to produce a fluorescent response, and the afterglow decay process of the fluorescence signal is received and recorded to obtain the fluorescence afterglow lifetime. The fluorescence detection temperature value is obtained using the functional relationship model between the fluorescence afterglow lifetime and temperature. The observed temperature value is obtained based on the average temperature of the contact electrode area.

6. The radiofrequency hyperthermia device testing system according to claim 5, characterized in that: In the temperature detection module, based on the infrared temperature sensing array element, the temperature of the preset points in the contact electrode area is measured to obtain a set of discrete temperature values. Based on the preset electrode area division scheme, the discrete temperature values ​​are statistically analyzed and the observed temperature value is obtained based on the weighted average calculation; Substitute the fluorescence detection temperature value and the observed temperature value into the dual-temperature fusion comparison strategy to obtain the thermal response deviation factor. The specific steps are as follows: The deviations between the fluorescence detection temperature value and the observed temperature value and the target temperature zone are calculated respectively to obtain the observed temperature deviation factor and the fluorescence temperature deviation factor. The weight coefficient is introduced to fuse the two types of temperature response information to obtain the thermal response deviation factor. The specific formula is as follows: ； in, is the thermal response deviation factor, is the observed temperature deviation factor, is the fluorescence temperature deviation factor, is the observed temperature weight, is the fluorescence detection temperature weight.

7. The radiofrequency hyperthermia device testing system according to claim 6, characterized in that: In the temperature detection module, after normalizing the thermal response deviation factor, the thermal response deviation factor and the heat concentration coefficient are substituted into the product amplification difference adjustment model to obtain the thermal effect calibration coefficient. The specific formula is as follows: ； Where, is the thermal effect calibration coefficient, is the thermal response deviation factor after normalization, is the heat concentration coefficient, is the nonlinear response tuning parameter.

8. The radiofrequency hyperthermia device testing system according to claim 7, characterized in that: In the temperature detection module, the thermal effect calibration coefficient is compared with the preset calibration threshold. If the thermal effect calibration coefficient is greater than or equal to the preset calibration threshold, a calibration prompt is issued; If the thermal effect calibration factor is less than the preset calibration threshold, no calibration reminder is required.

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