A method and system for evaluating the degree of damage to biological tissue by an ultrasonic scalpel

Abstract

The application discloses an ultrasonic scalpel biological tissue damage degree evaluation method and system, and belongs to the technical field of damage degree evaluation. The method comprises the following steps: acquiring multi-dimensional input data for damage evaluation, constructing a biological tissue damage evaluation model, and fusing the following mechanisms in the modeling process: calculating the coupling energy flux of the ultrasonic scalpel head-biological tissue interface, analyzing target working condition characteristic indexes, obtaining a coupling energy flux deviation value, determining biological tissue damage degree evaluation first execution information, calculating biological tissue heat flux based on a two-dimensional Pennes biological heat transfer model, determining biological tissue damage degree evaluation second execution information, and obtaining an ultrasonic scalpel biological tissue damage degree evaluation result. The application can more accurately predict the tissue heat dose, necrosis depth and heat affected zone range, and improve the precision and reliability of the ultrasonic scalpel biological tissue damage degree evaluation.

Description

Technical Field

[0001] This invention relates to the field of damage assessment technology, and in particular to a method and system for assessing the degree of damage to biological tissues by an ultrasonic scalpel. Background Technology

[0002] An ultrasonic scalpel is a surgical instrument that uses high-frequency mechanical vibration to cut and stop bleeding in tissue. Its working principle involves converting electrical energy into mechanical energy through ultrasonic vibration of the scalpel tip. When applied to biological tissue, this mechanical energy generates friction and cavitation effects, thereby achieving tissue cutting, coagulation, or hemostasis.

[0003] In existing technologies, the following methods are commonly used to assess the damage to biological tissues under the action of an ultrasonic scalpel: Electrical parameter characterization methods: Measuring electrical parameters such as output power, voltage, current, duty cycle, or cumulative energy of the scalpel generator serves as the basis for analyzing the energy input to the tissue. Mechanical vibration analysis methods: Detecting the amplitude, frequency, and vibration mode of the scalpel tip to assess the intensity of the scalpel tip's effect on the tissue and indirectly inferring the stress or heat exposure of the tissue. Contact state detection methods: Using sensors to acquire information such as the contact area, contact force, and sliding speed between the scalpel tip and the tissue to characterize the interfacial interaction conditions. Thermal detection methods: Measuring the surface and deep temperature distribution of the tissue using infrared thermal imaging, fiber optic temperature sensors, or fiber Bragg gratings (FBGs) to obtain the tissue's thermal diffusion characteristics for analyzing heat dose and heat-affected zone. Model prediction methods: Combining the above electrical, mechanical, contact, and thermal data, calculating tissue temperature rise, heat dose, necrosis depth, or heat-affected zone using thermal models or thermal damage models (such as the Arrhenius model) to predict and analyze tissue damage.

[0004] For example, Chinese invention patent application CN119361139B discloses a method and system for predicting the probability of radiation-induced damage to normal tissues based on deep learning. The method includes: acquiring the patient's tumor dose data, basic information, and tumor diagnosis information; the tumor dose data includes data formulated by the doctor based on the patient's tumor diagnosis information before radiotherapy; the basic information includes at least the patient's age; acquiring the patient's dose-volume histogram based on the tumor dose data; acquiring the volume parameters and bioequivalent dose of the patient's normal tissues based on the dose-volume histogram; and inputting the volume parameters and bioequivalent dose of the patient's normal tissues, the patient's basic information, and the tumor diagnosis information into a normal tissue damage probability prediction model constructed based on deep learning to obtain the probability of damage to the patient's normal tissues.

[0005] For example, Chinese invention patent application CN115798726A discloses a method for measuring thermal damage to biological tissues based on an improved Arrhenius model. The method utilizes the relaxation loss principle of small-sized magnetic nanoparticles to excite magnetic nanoparticles in the target treatment area to generate heat. Through heat conduction, blood perfusion, and heat generation from the biological tissue's own metabolism, the method analyzes the temperature distribution of biological tissues during magnetothermal therapy. Finally, based on the improved Arrhenius model of the Vogel-Tammann-Fulcher theory, it accurately predicts the apoptosis rate of tumor cells.

[0006] The above-mentioned technology has at least the following technical problems:

[0007] In existing technologies, to assess the degree of thermal damage to biological tissues, the energy input of the device is often used as a key input factor. This typically involves directly using electrical parameters such as generator display power, power level, duty cycle, energizing time, or cumulative energy displayed by the device to estimate tissue temperature rise, thermal dose, or necrosis depth for treatment planning. However, for ultrasonic scalpels, which primarily generate heat through mechanical vibration and friction, the system exhibits adaptive resonance and automatic tuning. Tissue contact also causes changes in equivalent mechanical impedance and resonance / quality factor. The electrical parameters displayed include significant reactive components and piezoelectric / structural internal damage. The power level and duty cycle are merely control parameters and do not equal the actual acoustic / frictional energy flux at the scalpel-tissue interface. Therefore, directly using these electrical parameters as energy input for damage assessment leads to: systematic overestimation or underestimation of interface energy flux, resulting in insufficient assessment accuracy; incomparability of results under different load conditions or between different devices / batches, leading to poor reproducibility; and instability in the calculated thermal dose and damage threshold, making it difficult to accurately reflect the true degree of thermal damage. Summary of the Invention

[0008] To address the aforementioned technical problems in the existing technology, embodiments of the present invention provide a method and system for assessing the degree of damage to biological tissue caused by an ultrasonic surgical scalpel. The technical solution is as follows:

[0009] On the one hand, a method for assessing the degree of damage to biological tissue by an ultrasonic scalpel is provided, including:

[0010] S1, acquire multidimensional input data for damage assessment, including multidimensional information characterizing the action of the ultrasonic scalpel.

[0011] S2, a biological tissue damage assessment model is constructed based on multidimensional input data. The biological tissue damage assessment model incorporates the following mechanisms during the modeling process:

[0012] The coupling energy flux at the interface between the ultrasonic scalpel tip and the biological tissue is calculated. The target working condition characterization index is analyzed simultaneously to obtain the adaptive energy flux reference value. Combined with the coupling energy flux at the interface between the ultrasonic scalpel tip and the biological tissue, the coupling energy flux deviation value is obtained.

[0013] The first execution information for assessing the degree of biological tissue damage is determined based on the coupling energy flux deviation value. When the first execution information for assessing the degree of biological tissue damage is to perform heat flux analysis, the heat flux of biological tissue is calculated based on the two-dimensional Pennes biological heat transfer model.

[0014] By comprehensively analyzing the heat flux of biological tissue and the coupling energy flux of the ultrasonic scalpel tip-biological tissue interface, and then analyzing the deviation value of the heat flux variable, the second execution information for assessing the degree of biological tissue damage is determined.

[0015] S3, when the first execution information or the second execution information for assessing the degree of damage to biological tissue is to perform an assessment of the degree of damage to biological tissue, the thermal dose, necrosis depth and heat-affected zone range of the biological tissue under the action of the ultrasonic scalpel are predicted to obtain the assessment result of the degree of damage to the biological tissue by the ultrasonic scalpel.

[0016] On the other hand, an ultrasonic scalpel is provided to assess the degree of damage to biological tissues. The system includes: a multidimensional input data acquisition module, a biological tissue damage assessment model construction module, and a damage assessment result output module.

[0017] The multidimensional input data acquisition module is used to acquire multidimensional input data for damage assessment, including multidimensional information characterizing the action of the ultrasonic scalpel.

[0018] The biological tissue damage assessment model construction module is used to build a biological tissue damage assessment model based on multidimensional input data. The biological tissue damage assessment model incorporates the following mechanisms during the modeling process:

[0019] The coupling energy flux at the interface between the ultrasonic scalpel tip and the biological tissue is calculated. The target working condition characterization index is analyzed simultaneously to obtain the adaptive energy flux reference value. Combined with the coupling energy flux at the interface between the ultrasonic scalpel tip and the biological tissue, the coupling energy flux deviation value is obtained.

[0020] The first execution information for assessing the degree of biological tissue damage is determined based on the coupling energy flux deviation value. When the first execution information for assessing the degree of biological tissue damage is to perform heat flux analysis, the heat flux of biological tissue is calculated based on the two-dimensional Pennes biological heat transfer model.

[0021] By comprehensively analyzing the heat flux of biological tissue and the coupling energy flux of the ultrasonic scalpel tip-biological tissue interface, and then analyzing the deviation value of the heat flux variable, the second execution information for assessing the degree of biological tissue damage is determined.

[0022] The damage assessment result output module is used to predict the thermal dose, necrosis depth and heat-affected zone range of biological tissue under the action of ultrasonic scalpel when the first execution information or the second execution information of biological tissue damage assessment is to perform biological tissue damage assessment, so as to obtain the damage assessment result of the ultrasonic scalpel on the biological tissue.

[0023] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0024] 1. The present invention provides a method for assessing the degree of damage to biological tissue by an ultrasonic scalpel. By acquiring multidimensional input data and constructing a biological tissue damage assessment model, and combining coupled energy flux, adaptive reference correction and heat flux analysis, it can achieve accurate correction of the actual energy transfer at the scalpel-tissue interface, thereby more accurately predicting tissue heat dose, necrosis depth and heat-affected zone range, and improving the accuracy and reliability of assessing the degree of damage to biological tissue under the action of an ultrasonic scalpel.

[0025] 2. This invention analyzes the target operating condition characterization indicators to obtain adaptive energy flux reference values, enabling precise correction of the coupled energy flux for different operating conditions. This effectively eliminates energy transfer deviations caused by resonance drift, higher harmonic enhancement, and contact stiffness fluctuations, improving the accuracy of coupled energy flux estimation. In biological tissue damage models, it can more reliably reflect the actual energy input at the blade-tissue interface, optimizing the prediction results of thermal dose, necrosis depth, and heat-affected zone range. Simultaneously, it can adapt to changes in different blade batches and surgical conditions, achieving repeatability and comparability of assessment results and reducing systematic errors in thermal damage risk assessment.

[0026] 3. This invention determines the first execution information for assessing the degree of biological tissue damage based on the coupling energy flux deviation value. This enables a dynamic response to the actual energy transfer state at the blade-biological tissue interface. When the coupling energy flux deviation value is less than the minimum threshold, standard damage assessment is directly executed, ensuring that the model quickly outputs reliable predictions of heat dose, necrosis depth, and heat-affected zone range. When the coupling energy flux deviation value is greater than or equal to the minimum threshold, the coupling energy flux weight and uncertainty are automatically updated. Heat flux analysis is triggered when the coupling energy flux deviation value is greater than or equal to the maximum threshold, thereby correcting prediction biases caused by local energy transfer anomalies. This improves the accuracy and robustness of tissue damage under non-ideal contact conditions, while reducing the risk of local overheating or underestimation of damage due to energy transfer anomalies, and enhancing the repeatability and comparability of damage degree assessment. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a schematic diagram of a method for assessing the degree of damage to biological tissue by an ultrasonic scalpel, provided in an embodiment of the present invention.

[0029] Figure 2 This is a structural diagram of an ultrasonic scalpel system for assessing the degree of damage to biological tissues, provided in an embodiment of the present invention.

[0030] Figure 3 This is a flowchart of the first execution information analysis process for assessing the degree of damage to biological tissues, as described in an embodiment of the present invention.

[0031] Figure 4 This is a flowchart of the second execution information analysis process for assessing the degree of biological tissue damage in an embodiment of the present invention.

[0032] Figure 5 This is a diagram of the experimental sample management interface of the ultrasonic surgical scalpel monitoring and analysis system involved in the embodiments of the present invention.

[0033] Figure 6 This is a diagram of the evaluation result management interface of the ultrasonic surgical scalpel monitoring and analysis system involved in the embodiments of the present invention. Detailed Implementation

[0034] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0035] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0036] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0037] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0038] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0039] like Figure 5 The diagram shown is an experimental sample management interface of the ultrasonic scalpel monitoring and analysis system according to an embodiment of the present invention. It manages and visualizes experimental samples under the action of ultrasonic scalpel. The experimental samples include biological tissues for damage assessment in this embodiment and other experimental samples related to the effect of ultrasonic scalpel. The interface displays information on five samples by scrolling down and provides a button to jump to the next page at the end of scrolling down. It also supports users to directly retrieve corresponding information by entering the sample number.

[0040] like Figure 1 The diagram shown illustrates a method for assessing the degree of damage to biological tissue caused by an ultrasonic scalpel, including the following steps:

[0041] It needs to be explained that the ultrasonic scalpel causes "damage" to biological tissues. Essentially, it converts high-frequency mechanical energy (usually longitudinal micro-vibrations in the range of 20 to 30 kilohertz) into mechanical stress and heat in the tissue, which is used for "cutting and coagulation".

[0042] S1, acquire multidimensional input data for damage assessment, including multidimensional information characterizing the action of the ultrasonic scalpel.

[0043] In this embodiment, the multidimensional input data includes, but is not limited to: electrical parameters, mechanical vibration parameters, blade-tissue contact state parameters, tissue thermal parameters, and environmental parameters.

[0044] The electrical parameters include, but are not limited to: driving voltage, driving current, duty cycle, rated power, and reactive power.

[0045] Mechanical vibration parameters include, but are not limited to: axial vibration amplitude of the cutter head, vibration frequency, and resonance drift.

[0046] The parameters of the cutter head-tissue contact state include, but are not limited to: contact area, normal contact force, cutting or sliding speed, contact stiffness, etc.

[0047] Tissue thermal parameters include, but are not limited to: tissue surface temperature, tissue deep temperature distribution, thermal diffusion rate, and tissue perfusion parameters.

[0048] Environmental parameters include, but are not limited to: irrigation fluid flow rate, liquid film thickness, humidity and temperature of the surgical area of ​​the ultrasonic scalpel, and scalpel head position information.

[0049] S2, a biological tissue damage assessment model is constructed based on multidimensional input data. The biological tissue damage assessment model incorporates the following mechanisms during the modeling process:

[0050] The coupling energy flux at the interface between the ultrasonic scalpel tip and the biological tissue is calculated. The target working condition characterization index is analyzed simultaneously to obtain the adaptive energy flux reference value. Combined with the coupling energy flux at the interface between the ultrasonic scalpel tip and the biological tissue, the coupling energy flux deviation value is obtained.

[0051] like Figure 3 The diagram shows a flowchart of the first execution information analysis process for assessing the degree of biological tissue damage according to an embodiment of the present invention. First, the coupling energy flux deviation value of the ultrasonic scalpel tip-biological tissue interface is obtained, and the preset minimum and maximum coupling energy flux deviation thresholds are extracted from the database. Then, the coupling energy flux deviation value is compared with the minimum coupling energy flux deviation threshold. If the coupling energy flux deviation value is less than the minimum coupling energy flux deviation threshold, the first execution information for assessing the degree of biological tissue damage is recorded as "performing biological tissue damage assessment." If the coupling energy flux deviation value is greater than or equal to the minimum coupling energy flux deviation threshold, the first execution information for assessing the degree of biological tissue damage is recorded as "performing the assessment setting adjustment of coupling energy flux in the biological tissue damage assessment model," and further, it is determined whether the coupling energy flux deviation value is greater than or equal to the maximum coupling energy flux deviation threshold. If so, the first execution information for assessing the degree of biological tissue damage is simultaneously recorded as "performing heat flux analysis." If not, the current first execution information setting remains unchanged.

[0052] Furthermore, the coupling energy flux at the interface between the ultrasonic scalpel tip and biological tissue is calculated, and the specific process is as follows:

[0053] The synchronous sampling data of the axial vibration displacement and normal contact force of the cutter head are obtained, the normal velocity sequence is calculated, and then the total positive mechanical work is analyzed.

[0054] In a specific embodiment, axial vibration displacement refers to the instantaneous displacement along the vibration axis of the cutter head, which can be measured by an accelerometer, displacement sensor, or built-in piezoelectric sensor. Normal contact force refers to the real-time force acting between the cutter head and the tissue contact surface in the vertical direction, which can be obtained by a force sensor or a built-in force detection module.

[0055] Synchronous sampling is to ensure that displacement and contact force data are collected on the same time reference so that instantaneous power can be calculated later.

[0056] The normal velocity sequence is obtained by differentiating the displacement sequence on the time axis. It represents the instantaneous motion velocity of the cutter head along the normal direction at the contact interface and is used to calculate the instantaneous mechanical power.

[0057] The positive component of the product of normal contact force and normal velocity is integrated over time within a preset measurement period to obtain the total positive mechanical work.

[0058] The positive part refers to the instantaneous power part that only considers the contact force direction and the velocity direction, that is, the energy of the blade doing positive work on the tissue, excluding the negative work caused by the reverse motion of the blade.

[0059] Time integration refers to the summation of all positive instantaneous power over time within a preset measurement period to obtain the total mechanical energy applied to the tissue by the cutting head during that preset measurement period.

[0060] The total positive mechanical work represents the actual mechanical energy input by the cutter head to the tissue. It can reflect the contribution of frictional heat generation or tissue cutting energy and is the core quantity for calculating the coupled energy flux.

[0061] Obtain the calibrated effective contact area parameters of the scalpel tip, calculate the total coupling energy flux value within the preset measurement period, and record it as the coupling energy flux of the ultrasonic scalpel tip-biological tissue interface.

[0062] The effective contact area of ​​the cutting head refers to the effective area of ​​the cutting head and the tissue under actual contact conditions, which can be obtained through experimental calibration or by calculating the geometry of the cutting head and the contact pressure distribution.

[0063] The coupling energy flux of the ultrasonic scalpel tip-biological tissue interface is defined as the total positive mechanical work divided by the effective contact area of ​​the tip. It represents the energy flux transferred from the tip to the tissue per unit area and can quantify the actual mechanical energy input density of the ultrasonic scalpel to the tissue.

[0064] Furthermore, the target operating condition characterization indicators are analyzed, and the specific analysis process is as follows:

[0065] Obtain the target working condition characterization parameters of the current ultrasonic scalpel action, including resonant drift amplitude, harmonic energy ratio, and contact stiffness.

[0066] The resonance drift amplitude refers to the deviation of the main resonant frequency of the actual vibration of the cutter head from the design or nominal resonant frequency. By installing an acceleration sensor or piezoelectric vibration detector along the vibration axis of the cutter head, the vibration signal of the cutter head is measured and the main frequency component is obtained by spectrum analysis, which reflects the change of the resonance condition of the cutter head under tissue load.

[0067] The harmonic energy ratio refers to the ratio of the energy of higher harmonic components (excluding the fundamental frequency) in the tool head vibration signal to the total vibration energy. It is calculated by performing a Fourier transform (FFT) on the acquired axial vibration displacement or acceleration signal, calculating the sum of squares of the amplitudes of each higher harmonic, and then comparing this sum with the total vibration energy. The harmonic energy ratio reflects the nonlinear vibration of the tool head or the effects of contact interface friction / non-ideal load, serving as an indicator of whether the tool head's operating conditions deviate from ideal conditions.

[0068] Contact stiffness refers to the equivalent stiffness of the interface between the cutting tip and the tissue, that is, the displacement response of the cutting tip under a unit normal force. During the application of a small disturbance or actual vibration of the cutting tip, the normal force and axial displacement sequences are collected simultaneously. It is obtained by dividing the change in normal force (collected by the force sensor) by the change in axial displacement of the cutting tip (collected by the displacement sensor).

[0069] It should be noted that the above-mentioned changes refer to the maximum value minus the minimum value of the corresponding parameters (normal force and axial displacement of the tool head) within the preset monitoring period.

[0070] Extract the reference resonant drift amplitude, reference harmonic energy ratio, and reference contact stiffness stored in the database.

[0071] Extract the preset resonant drift amplitude condition characterization allocation factor, harmonic energy ratio condition characterization allocation factor, and contact stiffness condition characterization allocation factor from the database.

[0072] In this embodiment, the system database is pre-configured with matching relationships for condition characterization allocation factors used in ultrasonic scalpel condition analysis. This quantifies the relative weights of different condition characterization parameters in the overall condition assessment. These matching relationships are managed in the form of a structured allocation factor table. Based on this matching system, the system can directly extract the resonant drift amplitude condition characterization allocation factor, harmonic energy ratio condition characterization allocation factor, and contact stiffness condition characterization allocation factor from the database. Each condition characterization allocation factor is a real value, limited to the range of 0 to 1, and the sum of the three is 1. These factors are used to weight and reflect the contribution of each indicator in the comprehensive condition assessment calculation, ensuring that the condition analysis results are scientific, reasonable, and quantifiable.

[0073] The target working condition characterization index is a quantitative indicator of the working condition of the current ultrasonic scalpel, which is composed of resonant drift amplitude, harmonic energy ratio and contact stiffness. The specific analysis process is as follows: the reference value of contact stiffness is compared with the contact stiffness, the harmonic energy ratio and resonant drift amplitude are compared with the corresponding reference values ​​respectively, and the results of each comparison are coupled with the working condition characterization allocation factor to obtain the target working condition characterization index.

[0074] In this embodiment, the target operating condition characterization index is used to describe the operating state of the ultrasonic scalpel tip under actual action, and can serve as a numerical basis for adaptively correcting the coupling energy flux reference value. The target operating condition characterization index consists of three parameters: resonant drift amplitude, harmonic energy ratio, and contact stiffness. This is because these three parameters can reflect the energy transfer characteristics and mechanical response of the tip-biological tissue interface from different perspectives. Specifically, the resonant drift amplitude reflects the degree to which the main resonant frequency of the tip deviates from the nominal resonant frequency under actual load, indicating changes in the effective coupling of vibration energy; the harmonic energy ratio describes the proportion of higher harmonic energy in the vibration signal to the total energy, reflecting the influence of nonlinear vibration and load changes on energy distribution; and the contact stiffness characterizes the mechanical response between the tip and the tissue interface, i.e., the change in tip displacement under unit normal force, directly affecting mechanical work transfer and interface frictional heat generation. By comprehensively analyzing these three parameters, the current dynamic operating state of the tip can be fully characterized, thus providing a basis for the adaptive correction of the coupling energy flux reference value, ensuring that subsequent calculations of coupling energy flux deviation are closer to the actual energy transfer level, and improving the accuracy and reliability of the biological tissue damage assessment model.

[0075] In specific embodiments, the increase in resonance drift amplitude is usually manifested as the vibration frequency of the cutting head deviating from the original resonance point, resulting in a decrease in the effective coupling efficiency of vibration energy between the main frequency and the tissue. At this time, the higher harmonic energy ratio increases, reflecting the enhancement of nonlinearity of the vibration waveform. As the nonlinear component increases, the main resonance frequency shifts further, causing local fluctuations in contact stiffness. That is, the equivalent stiffness of the tissue under the action of the cutting head increases or decreases periodically, which is manifested as instability of the interface coupling strength. The decrease in contact stiffness will weaken the interface energy transfer and enhance the higher harmonic components. Conversely, the increase in contact stiffness will cause the system to tend to a new resonance point and change the distribution of higher harmonics, thereby forming a linkage relationship between resonance drift amplitude, higher harmonic energy ratio and contact stiffness.

[0076] In a specific embodiment, the target operating condition characterization index is specifically represented as follows:

[0077]

[0078] Where A is the target working condition characterization index, a is the resonance drift amplitude, b is the harmonic energy ratio, c is the contact stiffness, a0 is the reference resonance drift amplitude, b0 is the reference harmonic energy ratio, c0 is the reference contact stiffness, y1 is the resonance drift amplitude working condition characterization allocation factor, y2 is the harmonic energy ratio working condition characterization allocation factor, and y3 is the contact stiffness working condition characterization allocation factor.

[0079] Furthermore, the coupling energy flux deviation value is analyzed in detail as follows:

[0080] The target operating condition characterization index is matched with the coupled energy flux reference correction coefficient.

[0081] In this embodiment, a matching table between target operating condition characterization indicators and coupled energy flux reference correction coefficients is pre-established in the system database. This matching table is constructed based on the corrected response of the coupled energy flux calculation model under different operating condition deviations. The matching table is managed in the form of an interval-based structured parameter table, supporting interval retrieval and interpolation calculation of target operating condition indicator values. When the system obtains the target operating condition characterization indicator under the current ultrasonic scalpel action, it uses this target operating condition characterization indicator as an index to retrieve and match the corresponding coupled energy flux reference correction coefficient in the matching table to achieve adaptive correction.

[0082] It should be noted that the coupling energy flux reference correction coefficient, matched based on the target working condition characterization index, is used to adaptively correct the coupling energy flux reference value extracted from the database, making it more accurately reflect the actual working condition of the current cutting head-biological tissue interface. By considering working condition deviation characteristics such as resonance drift amplitude, harmonic energy ratio, and contact stiffness, the reference value is adjusted to reduce errors caused by changes in working conditions. This ensures that the subsequently calculated coupling energy flux deviation value is closer to the actual energy transmission level, improving the accuracy and reliability of the biological tissue damage assessment model.

[0083] Extract the preset coupling energy flux reference value from the database.

[0084] The adaptive energy flux reference value is obtained by multiplying the coupled energy flux reference correction coefficient and the coupled energy flux reference value.

[0085] The coupling energy flux deviation value is obtained by performing difference processing on the coupling energy flux of the ultrasonic scalpel tip-biological tissue interface and the adaptive energy flux reference value.

[0086] Furthermore, the first execution information for assessing the degree of biological tissue damage is determined based on the coupling energy flux deviation value. The specific process is as follows:

[0087] Extract the preset minimum threshold and maximum threshold of coupling energy flux deviation from the database.

[0088] It should be noted that the minimum threshold for coupled energy flux deviation is less than the maximum threshold for coupled energy flux deviation.

[0089] If the coupling energy flux deviation is less than the minimum threshold of coupling energy flux deviation, then the first execution information for assessing the degree of biological tissue damage is recorded as the execution of biological tissue damage assessment.

[0090] If the coupling energy flux deviation is less than the minimum threshold of coupling energy flux deviation, it means that the actual coupling energy flux at the cutter head-biological tissue interface is basically matched with the reference value, the energy transfer and working conditions are stable, and the coupling energy flux in the biological tissue damage assessment model does not need to be modified. At this time, the first execution information of biological tissue damage assessment is recorded as the execution of biological tissue damage assessment.

[0091] If the coupling energy flux deviation value is greater than or equal to the minimum threshold of coupling energy flux deviation, then the first execution information of biological tissue damage assessment is recorded as the assessment setting update of coupling energy flux in the biological tissue damage assessment model. If the coupling energy flux deviation value is greater than or equal to the maximum threshold of coupling energy flux deviation at this time, then the first execution information of biological tissue damage assessment is recorded as the execution of heat flux analysis.

[0092] If the coupling energy flux deviation is greater than or equal to the minimum coupling energy flux deviation threshold, it indicates that the actual coupling energy flux at the blade tip-biological tissue interface deviates from the reference value, which may affect energy transfer efficiency and damage prediction accuracy. In this case, the coupling energy flux needs to be evaluated and updated in the biological tissue damage assessment model. If the coupling energy flux deviation is greater than or equal to the maximum coupling energy flux deviation threshold, it indicates that the actual energy transfer at the ultrasonic scalpel tip-biological tissue interface deviates significantly from the reference value, which may cause nonlinear changes in local tissue temperature rise and heat accumulation, thereby affecting the prediction accuracy of heat dose and tissue damage. Heat flux analysis needs to be performed to further correct the damage prediction.

[0093] The specific execution process for updating the evaluation settings of coupled energy flux in the biological tissue damage assessment model is as follows: Based on the coupled energy flux deviation value, extract the coupled energy flux weight reduction value and the coupled energy flux uncertainty supplement value, thereby completing the evaluation settings update of coupled energy flux in the biological tissue damage assessment model. That is, obtain the coupled energy flux weight and coupled energy flux uncertainty recorded in the model setting log, take the sum of the coupled energy flux weight and the coupled energy flux weight reduction value as the updated coupled energy flux weight, and take the sum of the coupled energy flux uncertainty and the coupled energy flux uncertainty supplement value as the updated coupled energy flux uncertainty.

[0094] It should be noted that the reduction value of the coupling energy flux weight is negative, while the supplementary value of the coupling energy flux uncertainty is positive.

[0095] In this embodiment, the system database pre-stores the mapping relationship between the coupled energy flux deviation value, the coupled energy flux weight reduction value, and the coupled energy flux uncertainty supplement value. This mapping relationship is constructed based on the analysis results of the impact of coupled energy flux deviation on the damage prediction accuracy under different operating conditions, and statistical analysis is performed in conjunction with historical experimental data and model error distribution trends. The mapping relationship is managed in the form of an interval-based structured parameter table, supporting deviation value interval search and linear interpolation strategies. When the system calculates the current coupled energy flux deviation value, it uses this coupled energy flux deviation value as an index to retrieve the corresponding coupled energy flux weight reduction value and coupled energy flux uncertainty supplement value from the mapping table, which are used to update the parameter settings of coupled energy flux in the biological tissue damage assessment model.

[0096] In this embodiment, a larger coupling energy flux deviation indicates a significant difference between the actual energy flux at the ultrasonic scalpel tip-biological tissue interface and the adaptive reference value, meaning the model's prediction of this variable deviates significantly from actual conditions. To reduce the impact of this deviation on the biological tissue damage assessment results, a larger absolute value of the extracted coupling energy flux weight reduction value is used to reduce the contribution of this variable in the assessment model, thereby reducing the impact of the deviation on the overall damage prediction. Simultaneously, a larger coupling energy flux uncertainty supplement value is used to expand the uncertainty range of this variable in the model, enabling the model to fully consider the uncertainties of actual conditions when predicting thermal dose, necrosis depth, and heat-affected zone range, thus improving the robustness and reliability of the prediction.

[0097] The first execution information for assessing the degree of biological tissue damage is determined based on the coupling energy flux deviation value. When the first execution information for assessing the degree of biological tissue damage is to perform heat flux analysis, the heat flux of biological tissue is calculated based on the two-dimensional Pennes biological heat transfer model.

[0098] Furthermore, the heat flux of biological tissues was calculated based on the two-dimensional Pennes biological heat transfer model, and the analysis process is as follows:

[0099] The infrared thermal imaging temperature field sequence calibrated by emissivity and optical transmittance is acquired and non-uniformity correction and spatiotemporal registration are completed.

[0100] In this embodiment, a high-sampling-rate infrared thermal imaging device is used to continuously measure the temperature of the tissue surface under the action of an ultrasonic scalpel, acquiring raw temperature field data. To ensure measurement accuracy, the infrared data needs to be calibrated for emissivity and optical transmittance. The calibration process includes: selecting a known temperature reference plate and correcting the temperature response of the infrared camera to compensate for the emissivity difference between the tissue surface and the infrared detector, as well as the optical transmittance attenuation caused by air or irrigation fluid. Subsequently, the temperature sequence is corrected for non-uniformity (to compensate for differences in detector pixel response) and spatiotemporal registration is performed (to correct for temporal and spatial offsets between multiple frames), ultimately obtaining an infrared temperature field sequence that continuously describes the surface temperature changes in the scalpel tip's action area.

[0101] A two-dimensional Pennes biological heat transfer model was established, and the thermal conductivity, density, specific heat, blood perfusion parameters, and metabolic heat source parameters of biological tissue were set. The interface was the contact boundary between the cutting head and the biological tissue.

[0102] In this embodiment, a two-dimensional Pennes bio-heat transfer model is used to describe the influence of heat conduction, blood perfusion, and metabolic heat sources within the tissue on the temperature field. The model input parameters include: thermal conductivity of the biological tissue, density of the biological tissue, specific heat of the biological tissue, blood perfusion rate of the biological tissue, intensity of the metabolic heat source in the biological tissue, and boundary conditions at the blade-tissue interface (i.e., interface temperature, obtained directly through calibrated infrared thermography). The model output is a time-varying sequence of temperature distribution within the biological tissue. The model establishment process is based on analytical methods of the physical heat transfer equations; the predicted temperature field can be generated using known tissue parameters and boundary conditions.

[0103] It should be noted that the thermal conductivity, density, specific heat, blood perfusion rate, and metabolic heat source intensity of biological tissues can be directly extracted from the preset basic parameters table of biological tissues in the database, using biological tissue as the query key.

[0104] The interface normal heat flux time series is obtained, and the positive half axis intercept is performed to obtain the heat flux sequence in the direction of incident biological tissue, thereby obtaining the total heat transfer of biological tissue.

[0105] In this embodiment, the time series of interface normal heat flux is solved by finite element inversion.

[0106] In this embodiment, the interfacial normal heat flux refers to the heat flux density per unit area along the normal direction (i.e., perpendicular to the contact surface) at the interface between the scalpel tip and the biological tissue. Its physical meaning is the thermal energy transferred to the tissue through the interface per unit time, expressed in W / m². The time series of the interfacial normal heat flux obtained by the finite element inversion method can dynamically reflect the intensity and variation of energy entering the tissue in the form of heat during the action of the ultrasonic scalpel.

[0107] In this embodiment, to obtain the actual heat flux at the blade-tissue interface, the two-dimensional Pennes model is discretized into a finite element mesh, and the infrared-measured surface temperature field is used as a constraint for inversion. The inversion method is based on minimizing the error between the predicted and measured temperatures, and iteratively optimizes the interface heat flux distribution to make the model output temperature field as consistent as possible with the infrared measurements. The result of the inversion solution is the time-varying sequence of the interface normal heat flux. By truncating the positive half-axis, only the heat flux component pointing towards the biological tissue is retained, thus obtaining the actual heat flux sequence in the direction of incident on the biological tissue.

[0108] The total amount of heat transferred to biological tissue is obtained by integrating the normal heat flux at the interface over time and integrating it over the effective contact area of ​​the cutting head within a preset measurement period.

[0109] The analysis of biological tissue heat flux is based on the total amount of heat transfer in biological tissue. Specifically, the total value of biological tissue heat flux is calculated using the measurement period length and the effective contact area of ​​the cutting head as normalization factors. The total value of biological tissue heat flux is equal to the total amount of heat transfer in biological tissue divided by the measurement period length and the effective contact area, and is denoted as biological tissue heat flux.

[0110] By comprehensively analyzing the heat flux of biological tissue and the coupling energy flux of the ultrasonic scalpel tip-biological tissue interface, and then analyzing the deviation value of the heat flux variable, the second execution information for assessing the degree of biological tissue damage is determined.

[0111] like Figure 4 The diagram shows a flowchart of the second execution information analysis process for assessing the degree of biological tissue damage according to an embodiment of the present invention. First, the deviation value of the biological tissue heat flux variable is obtained, and a preset heat flux variable deviation threshold is extracted from the database. Then, the heat flux variable deviation value is compared with the heat flux variable deviation threshold. If the heat flux variable deviation value is less than the heat flux variable deviation threshold, the second execution information for assessing the degree of biological tissue damage is recorded as "performing biological tissue damage assessment." If the heat flux variable deviation value is greater than or equal to the heat flux variable deviation threshold, the second execution information for assessing the degree of biological tissue damage is recorded as "performing assessment setting adjustment of heat flux variables in the biological tissue damage assessment model," and a heat flux variable influence reduction value is extracted based on the heat flux variable deviation value to complete the assessment setting adjustment of heat flux variables in the biological tissue damage assessment model.

[0112] Furthermore, the heat flux of biological tissue and the coupled energy flux at the interface between the ultrasonic scalpel tip and biological tissue are comprehensively analyzed to further analyze the deviation value of the heat flux variable. The specific analysis process is as follows:

[0113] The first correction value for extracting the thermal flux of biological tissue based on the coupling energy flux of ultrasonic scalpel tip-biological tissue interface.

[0114] In this embodiment, a mapping table is pre-established in the system database between the coupling energy flux of the blade-tissue interface and the first correction value of the biological tissue heat flux reference. This mapping table is constructed based on the response results of the heat flux model under different coupling energy flux deviation levels, and combined with the analysis of tissue thermal response characteristics in historical surgical data. The mapping relationship is managed in the form of an interval-based structured parameter table, supporting index lookup and linear interpolation matching for continuous numerical segments. When the system calculates the coupling energy flux of the current blade-tissue interface, it uses the coupling energy flux of the blade-tissue interface as an index to retrieve the corresponding first correction value of the biological tissue heat flux reference in the mapping table, which is used for adaptive correction in subsequent heat flux analysis and damage prediction.

[0115] In this embodiment, the extraction of the first correction value for the biological tissue heat flux reference based on the coupled energy flux of the ultrasonic scalpel tip-biological tissue interface is used to quantify and correct the relationship between the actual mechanical energy input and the tissue thermal response. Since the coupled energy flux directly reflects the actual energy transfer from the scalpel tip to the tissue, mapping it to the heat flux reference correction value corrects the previously set heat flux reference, making subsequent heat flux calculations closer to the actual tissue heating conditions, thereby improving the accuracy of heat dose estimation and damage prediction. This correction mechanism ensures that the model can adaptively adjust the heat flux input under different scalpel tip loads, tissue contact states, and operating conditions, reducing systematic deviations caused by inconsistencies between the power display value or control parameters and the actual energy flux.

[0116] The second correction value for the heat flux of biological tissues is matched based on the target operating condition characterization index.

[0117] In this embodiment, matching the target working condition characterization index with the second correction value of biological tissue heat flux reference is achieved by comparing the current working condition of the cutter head-tissue interaction with a preset working condition reference table in the database. The specific process is as follows: A mapping relationship table between the target working condition characterization index and the second correction value of biological tissue heat flux reference is pre-established in the system database. The mapping relationship is managed using a range-structured parameter table, supporting index lookup and linear interpolation matching for continuous numerical ranges. After the system calculates the current working condition characterization index, it uses this index combination as an index to retrieve the corresponding second correction value of biological tissue heat flux reference in the mapping table, thereby adaptively correcting the heat flux prediction based on the working condition and improving the accuracy of heat dose and damage prediction.

[0118] In this embodiment, matching the second correction value of the biological tissue heat flux reference based on the target working condition characterization index is to adaptively correct the biological tissue heat flux reference value extracted from the database, making the biological tissue heat flux reference value more accurately reflect the current actual working condition. By considering the working condition deviation characteristics such as resonance drift amplitude, harmonic energy ratio, and contact stiffness, the reference value is adjusted to reduce the error caused by changes in working conditions, thereby ensuring that the deviation value of the heat flux variable calculated subsequently is closer to the actual level, and improving the accuracy and reliability of the biological tissue damage assessment model.

[0119] Extract the preset reference values ​​for heat flux of biological tissues from the database.

[0120] The corrected reference value for biological tissue heat flux is obtained based on the first corrected reference value, the second corrected reference value, and the reference value of biological tissue heat flux. That is, the product of the first corrected reference value, the second corrected reference value, and the reference value of biological tissue heat flux is used as the corrected reference value for biological tissue heat flux.

[0121] The difference between the heat flux of biological tissue and the corrected reference value of heat flux of biological tissue is processed to obtain the deviation value of heat flux variable.

[0122] Furthermore, the second set of information for assessing the degree of biological tissue damage was determined, and the specific analysis process is as follows:

[0123] Extract the preset deviation threshold of heat flux variable from the database.

[0124] If the deviation value of the heat flux variable is less than the deviation threshold of the heat flux variable, then the second execution information of the biological tissue damage assessment is recorded as the execution of the biological tissue damage assessment.

[0125] If the deviation value of the heat flux variable is less than the deviation threshold of the heat flux variable, it means that the deviation between the current heat flux prediction and the reference correction value is small, and the tissue heating state is basically consistent with the model expectation. Therefore, the assessment of the degree of biological tissue damage can be performed directly without additional adjustment to the heat flux variable.

[0126] If the deviation value of the heat flux variable is greater than or equal to the deviation threshold of the heat flux variable, the second execution information of the biological tissue damage assessment is recorded as the assessment setting update of the heat flux variable in the biological tissue damage assessment model. Specifically, the heat flux variable influence reduction value is extracted based on the deviation value of the heat flux variable, and the assessment setting update of the heat flux variable in the biological tissue damage assessment model is performed accordingly. That is, the current influence of the heat flux variable is obtained from the model setting log, and the sum of the current influence of the heat flux variable and the influence reduction value of the heat flux variable is used as the updated influence of the heat flux variable.

[0127] If the deviation value of the heat flux variable is greater than or equal to the deviation threshold of the heat flux variable, it indicates that there is a significant difference between the current heat flux prediction and the reference correction value, and the tissue heating state may deviate from the model expectation. At this time, it is necessary to perform an update of the assessment settings of the heat flux variable in the biological tissue damage assessment model. By extracting the influence reduction value of the heat flux variable, the influence of the heat flux variable in the model is adjusted to correct the contribution of heat flux to damage prediction, thereby improving the accuracy of the prediction of heat dose, necrosis depth and heat-affected zone range.

[0128] It should be noted that the reduction value of the influence of the heat flux variable is negative.

[0129] In this embodiment, the extraction of heat flux variable impact reduction values ​​based on heat flux variable deviation values ​​is achieved through a heat flux variable deviation-impact reduction mapping table in the system database. The specific process is as follows: A mapping relationship between heat flux variable deviations and corresponding impact reduction values ​​is pre-established in the system database. This mapping relationship is constructed based on model prediction stability at different deviation levels and historical surgical experimental data, combined with tissue thermal response sensitivity analysis. The mapping relationship is managed in the form of an interval-based structured parameter table, supporting numerical range lookup and linear interpolation matching. After calculating the current heat flux variable deviation value, the system uses this deviation value as an index to retrieve the corresponding heat flux variable impact reduction value from the mapping table, and combines linear interpolation to accurately match the values ​​within the interval, thereby obtaining the heat flux variable impact reduction value used to update the biological tissue damage assessment model. This corrects the model's weight allocation of heat flux variables and improves damage prediction accuracy.

[0130] The larger the deviation value of the heat flux variable, the more significant the difference between the currently predicted heat flux of biological tissue and the reference correction value, and the greater the degree to which the actual heating state of the tissue deviates from the model's expectations. To reduce the impact of this deviation on the damage prediction results, the contribution weight of the heat flux variable needs to be reduced in the model, thereby avoiding over-reliance on heat flux data that deviates from reality. Therefore, the larger the absolute value of the reduced influence value of the extracted heat flux variable, the more significantly the influence of this variable will be reduced in the biological tissue damage assessment model, thus ensuring more robust and accurate predictions of heat dose, necrosis depth, and the extent of the heat-affected zone.

[0131] In this embodiment, the biological tissue damage assessment model assigns weights to each input variable, meaning each variable contributes differently to the prediction of the final heat dose, necrosis depth, and heat-affected zone extent. When the predicted heat flux variable deviates significantly from the actual value, directly using this variable may lead to systematic errors in the damage assessment results. By extracting and applying the influence reduction value of the heat flux variable, the weight of this variable in the model can be reduced in a targeted manner, thereby minimizing the impact of deviation on the overall prediction and enabling fine-tuning of the model. This adjustment maintains the model's normal response to other reliable input variables while avoiding excessive deviations in the prediction results caused by abnormal heat flux data, thus improving the accuracy and robustness of the damage assessment.

[0132] like Figure 6 The diagram shown is an evaluation result management interface of the ultrasonic scalpel monitoring and analysis system involved in this embodiment of the invention. It is one of the sub-interfaces for biological tissue damage assessment, which visualizes the damage status of experimental samples and sets up an export interactive area where users can adaptively select the content to export.

[0133] S3, when the first execution information or the second execution information for assessing the degree of damage to biological tissue is to perform an assessment of the degree of damage to biological tissue, the thermal dose, necrosis depth and heat-affected zone range of the biological tissue under the action of the ultrasonic scalpel are predicted to obtain the assessment result of the degree of damage to the biological tissue by the ultrasonic scalpel.

[0134] Furthermore, when the first or second execution information for assessing the degree of damage to biological tissue is used, the thermal dose, necrosis depth, and heat-affected zone range of the biological tissue under the action of the ultrasonic scalpel are predicted to obtain the assessment result of the degree of damage to the biological tissue by the ultrasonic scalpel. The specific execution process is as follows:

[0135] Multidimensional input data is input into the biological tissue damage assessment model to determine the existence of assessment setting updates for coupled energy flux and heat flux variables.

[0136] If neither the evaluation setting update for coupled energy flux nor the evaluation setting update for heat flux variables exists, the baseline prediction process is executed to construct a two-dimensional Pennes biological heat transfer model and solve the temperature field time series. Based on the Arrhenius thermal damage model, the total heat dose, necrosis depth, and thermally affected zone range are calculated to generate damage severity scores and grading labels.

[0137] In this embodiment, the heat transfer equation is discretized and solved using the finite element method, and an implicit or explicit stepping algorithm is used in the time direction to obtain the temperature field time series.

[0138] If the evaluation settings for coupled energy flux are updated but the evaluation settings for heat flux variables are not updated, the weights and uncertainties corresponding to coupled energy flux in the biological tissue damage assessment model are updated based on the weight reduction value and the uncertainty supplement value of coupled energy flux. Under the updated parameter settings, the temperature field is solved and the Arrhenius thermal damage is calculated. The total heat dose, necrosis depth and thermally affected zone range are output, and the damage degree score and grading label are generated.

[0139] If both the evaluation settings for coupled energy flux and the evaluation settings for heat flux variables exist, the weights and uncertainties of coupled energy flux and the influence of heat flux variables in the biological tissue damage assessment model are updated based on the weight reduction value of coupled energy flux, the supplementary value of coupled energy flux uncertainty, and the reduction value of the influence of heat flux variables. Under the updated parameter settings, the temperature field is solved and the Arrhenius thermal damage is calculated, outputting the total heat dose, necrosis depth, and thermally affected zone range, and generating a damage degree score and grading label.

[0140] like Figure 2 The diagram shows a structural diagram of a system for assessing the degree of damage to biological tissue by an ultrasonic scalpel. The system includes: a multi-dimensional input data acquisition module, a biological tissue damage assessment model construction module, and a damage assessment result output module.

[0141] The multidimensional input data acquisition module is used to acquire multidimensional input data for damage assessment, including multidimensional information characterizing the action of the ultrasonic scalpel.

[0142] The biological tissue damage assessment model construction module is used to build a biological tissue damage assessment model based on multidimensional input data. The biological tissue damage assessment model incorporates the following mechanisms during the modeling process:

[0143] The coupling energy flux at the interface between the ultrasonic scalpel tip and the biological tissue is calculated. The target working condition characterization index is analyzed simultaneously to obtain the adaptive energy flux reference value. Combined with the coupling energy flux at the interface between the ultrasonic scalpel tip and the biological tissue, the coupling energy flux deviation value is obtained.

[0144] The first execution information for assessing the degree of biological tissue damage is determined based on the coupling energy flux deviation value. When the first execution information for assessing the degree of biological tissue damage is to perform heat flux analysis, the heat flux of biological tissue is calculated based on the two-dimensional Pennes biological heat transfer model.

[0145] By comprehensively analyzing the heat flux of biological tissue and the coupling energy flux of the ultrasonic scalpel tip-biological tissue interface, and then analyzing the deviation value of the heat flux variable, the second execution information for assessing the degree of biological tissue damage is determined.

[0146] The damage assessment result output module is used to predict the thermal dose, necrosis depth and heat-affected zone range of biological tissue under the action of ultrasonic scalpel when the first execution information or the second execution information of biological tissue damage assessment is to perform biological tissue damage assessment, so as to obtain the damage assessment result of the ultrasonic scalpel on the biological tissue.

[0147] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0148] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0149] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0150] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0151] Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0152] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0153] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0154] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0155] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating the degree of damage to biological tissue by an ultrasonic scalpel, characterized by, The method comprises the following steps: S1, obtaining multi-dimensional input data for damage assessment, the multi-dimensional input data comprising multi-dimensional information under the action of an ultrasonic scalpel; S2, constructing a biological tissue damage assessment model based on the multi-dimensional input data, the biological tissue damage assessment model incorporating the following mechanisms during modeling: Obtaining synchronous sampling data of axial vibration displacement and normal contact force of the tool head, calculating a normal velocity sequence, and then analyzing to obtain a total forward mechanical work, obtaining a calibrated effective contact area parameter of the tool head, calculating a total coupling energy flux value in a preset measurement period, and recording as the coupling energy flux of the ultrasonic scalpel tool head-biological tissue interface; Synchronously analyzing target working condition characterization indicators, obtaining an adaptive energy flux reference value, matching a coupling energy flux reference correction coefficient based on the target working condition characterization indicators, extracting a preset coupling energy flux reference value from a database, obtaining the adaptive energy flux reference value based on the coupling energy flux reference correction coefficient and the coupling energy flux reference value, and performing difference processing on the coupling energy flux of the ultrasonic scalpel tool head-biological tissue interface and the adaptive energy flux reference value to obtain a coupling energy flux deviation value; Determining biological tissue damage degree assessment first execution information according to the coupling energy flux deviation value, when the biological tissue damage degree assessment first execution information is to execute heat flux analysis, obtaining an infrared thermal imaging temperature field sequence calibrated by emissivity and optical transmission rate and completing non-uniformity correction and space-time registration, establishing a two-dimensional Pennes biological heat transfer model, setting biological tissue thermal conductivity, density, specific heat, blood perfusion parameters and metabolic heat source parameters, the interface being a tool head-biological tissue contact boundary, obtaining an interface normal heat flux time sequence, executing positive half-axis truncation to obtain a heat flux sequence in the incident biological tissue direction, and then obtaining a total biological tissue heat transfer amount, and analyzing biological tissue heat flux based on the total biological tissue heat transfer amount; Extracting a biological tissue heat flux reference first correction value based on the coupling energy flux of the ultrasonic scalpel tool head-biological tissue interface, matching a biological tissue heat flux reference second correction value based on the target working condition characterization indicators, extracting a preset biological tissue heat flux reference value from a database, obtaining a biological tissue heat flux correction reference value based on the biological tissue heat flux reference first correction value, the biological tissue heat flux reference second correction value and the biological tissue heat flux reference value, and performing difference processing on the biological tissue heat flux and the biological tissue heat flux correction reference value to obtain a heat flux variable deviation value, thereby determining biological tissue damage degree assessment second execution information; S3, when the biological tissue damage degree assessment first execution information or the biological tissue damage degree assessment second execution information is to execute biological tissue damage degree assessment, predicting the thermal dose, necrosis depth and thermal influence zone range of the biological tissue under the action of the ultrasonic scalpel, and obtaining an ultrasonic scalpel biological tissue damage degree assessment result.

2. The method according to claim 1, wherein the method is characterized by, The analysis of the target working condition characterization indicators is specifically as follows: Obtaining target working condition characterization parameters of the current ultrasonic scalpel, including resonance drift amplitude, harmonic energy ratio and contact stiffness; The target working condition representation index is a quantitative index of the working condition state of the combined effect of the resonance drift amplitude, the harmonic energy ratio and the contact stiffness on the current ultrasonic scalpel, and the specific analysis process is as follows: the reference value of the contact stiffness is compared with the contact stiffness, the harmonic energy ratio and the resonance drift amplitude are compared with the corresponding reference values respectively, and the results of the comparison are coupled by the working condition representation allocation factor to obtain the target working condition representation index.

3. The method of claim 1, wherein the method further comprises: The specific process of determining the biological tissue damage degree evaluation first execution information according to the coupling energy flux deviation value is as follows: Extract the preset coupling energy flux deviation minimum threshold and coupling energy flux deviation maximum threshold in the database; If the coupling energy flux deviation value is less than the coupling energy flux deviation minimum threshold, the biological tissue damage degree evaluation first execution information is recorded as executing the biological tissue damage degree evaluation; If the coupling energy flux deviation value is greater than or equal to the coupling energy flux deviation minimum threshold, the biological tissue damage degree evaluation first execution information is recorded as executing the coupling energy flux evaluation setting update in the biological tissue damage evaluation model, and if the coupling energy flux deviation value is greater than or equal to the coupling energy flux deviation maximum threshold at this time, the biological tissue damage degree evaluation first execution information is recorded as executing the heat flux analysis at the same time. The specific execution process of executing the coupling energy flux evaluation setting update in the biological tissue damage evaluation model is as follows: based on the coupling energy flux deviation value, the coupling energy flux weight reduction value and the coupling energy flux uncertainty supplement value are extracted, thereby completing the coupling energy flux evaluation setting update in the biological tissue damage evaluation model.

4. The method of claim 1, wherein the method further comprises: determining the degree of damage to the biological tissue based on the received ultrasound signals. The specific analysis process of determining the biological tissue damage degree evaluation second execution information is as follows: Extract the preset heat flux variable deviation threshold in the database; If the heat flux variable deviation value is less than the heat flux variable deviation threshold, the biological tissue damage degree evaluation second execution information is recorded as executing the biological tissue damage degree evaluation; If the heat flux variable deviation value is greater than or equal to the heat flux variable deviation threshold, the biological tissue damage degree evaluation second execution information is recorded as executing the heat flux variable evaluation setting update in the biological tissue damage evaluation model, and the specific process is as follows: based on the heat flux variable deviation value, the heat flux variable influence degree reduction value is extracted to execute the heat flux variable evaluation setting update in the biological tissue damage evaluation model.

5. The method of claim 1, wherein the method further comprises: determining the degree of damage to the biological tissue based on the received ultrasound signals. When the biological tissue damage degree evaluation first execution information or the biological tissue damage degree evaluation second execution information is executing the biological tissue damage degree evaluation, the heat dose, the necrosis depth and the heat affected zone range of the biological tissue under the action of the ultrasonic scalpel are predicted to obtain the damage degree evaluation result of the ultrasonic scalpel on the biological tissue, and the specific execution process is as follows: Input the multi-dimensional input data into the biological tissue damage evaluation model to determine the existence of the coupling energy flux evaluation setting update and the heat flux variable evaluation setting update; If neither the evaluation setting update of the coupled energy flux nor the evaluation setting update of the heat flux variable exists, a baseline prediction process is performed, a two-dimensional Pennes bio-heat transfer model is constructed and a time series of temperature field is solved, a total value of thermal dose, a depth of necrosis and a range of thermal impact zone are calculated based on an Arrhenius thermal damage model, and a damage degree score and a grading label are generated; If the evaluation setting update of the coupled energy flux exists and the evaluation setting update of the heat flux variable does not exist, the weight and the uncertainty corresponding to the coupled energy flux in the biological tissue damage evaluation model are updated based on the coupled energy flux weight reduction value and the coupled energy flux uncertainty supplement value, and the temperature field solving and the Arrhenius thermal damage calculation are completed under the updated parameter setting, and the total value of thermal dose, the depth of necrosis and the range of thermal impact zone are output, and the damage degree score and the grading label are generated; If the evaluation setting update of the coupled energy flux and the evaluation setting update of the heat flux variable both exist, the weight and the uncertainty corresponding to the coupled energy flux and the influence degree of the heat flux variable in the biological tissue damage evaluation model are updated based on the coupled energy flux weight reduction value, the coupled energy flux uncertainty supplement value and the heat flux variable influence degree reduction value, and the temperature field solving and the Arrhenius thermal damage calculation are completed under the updated parameter setting, and the total value of thermal dose, the depth of necrosis and the range of thermal impact zone are output, and the damage degree score and the grading label are generated.

6. An ultrasonic scalpel damage degree evaluation system for biological tissue, which is used to realize the method for evaluating the damage degree of an ultrasonic scalpel to biological tissue according to any one of claims 1-5, characterized in that, The system comprises a multi-dimensional input data acquisition module, a biological tissue damage evaluation model construction module and a damage degree evaluation result output module; The multi-dimensional input data acquisition module is configured to acquire multi-dimensional input data for damage evaluation, wherein the multi-dimensional input data comprises multi-dimensional information representing an ultrasonic surgical knife under action; The biological tissue damage evaluation model construction module is configured to construct a biological tissue damage evaluation model based on the multi-dimensional input data, wherein the biological tissue damage evaluation model integrates the following mechanisms in the modeling process: The coupled energy flux of the ultrasonic surgical knife head-biological tissue interface is calculated, the target working condition representation index is analyzed synchronously, the adaptive energy flux reference value is obtained, the coupled energy flux deviation value is obtained based on the coupled energy flux of the ultrasonic surgical knife head-biological tissue interface; The biological tissue damage degree evaluation first execution information is determined according to the coupled energy flux deviation value, and the biological tissue heat flux is calculated based on the two-dimensional Pennes bio-heat transfer model when the biological tissue damage degree evaluation first execution information is to execute heat flux analysis; The biological tissue heat flux and the coupled energy flux of the ultrasonic surgical knife head-biological tissue interface are comprehensively analyzed, and then the heat flux variable deviation value is analyzed, and the biological tissue damage degree evaluation second execution information is determined; The damage degree evaluation result output module is configured to predict the thermal dose, the depth of necrosis and the range of thermal impact zone of the biological tissue under the action of the ultrasonic surgical knife when the biological tissue damage degree evaluation first execution information or the biological tissue damage degree evaluation second execution information is to execute biological tissue damage degree evaluation, and obtain the damage degree evaluation result of the ultrasonic surgical knife on the biological tissue.

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