Vascular surgery drainage equipment and method
By installing an ultrasonic transducer on the outside of the drainage tube, the acoustic impedance difference of the stable flow component is decomposed and identified, thus solving the problem of scattering interference in ultrasonic monitoring and realizing accurate flow monitoring in the vascular surgical drainage process.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-02
- Publication Date
- 2026-03-31
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In existing technologies, during ultrasound monitoring of vascular surgical drainage, scattering bodies and air bubbles in the effusion cause inaccurate flow monitoring, affecting medical staff's judgment of the condition.
An ultrasonic transducer is installed on the outside of the drainage tube. By emitting ultrasonic signals and decomposing the echo signals into reflection components under multiple modes, the stable flow components are identified, and the liquid phase signal is extracted based on the acoustic impedance difference to calculate the liquid phase flow rate.
This reduces the interference of scattering bodies on flow monitoring, ensures that the flow monitoring results reflect the true flow state of the accumulated liquid, and improves the accuracy of monitoring.
Smart Images
Figure CN121754742A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of fluid drainage technology, and more specifically, to a vascular surgical drainage device and method. Background Technology
[0002] In vascular surgery, patients often develop bloody effusions, inflammatory exudates, or interstitial fluid after procedures such as aortic dissection repair, deep vein thrombosis removal, and vascular anastomosis leak repair. If these effusions cannot be drained in time, they can compress surrounding blood vessels and nerve tissue, leading to local circulatory disorders. They may also breed bacteria, causing complications such as incision infection and sepsis, and even delay the healing of vascular anastomoses, increasing the risk of secondary surgery. Therefore, it is necessary to continuously drain the effusion using drainage equipment, and the flow rate of the effusion must be monitored during the drainage process to respond quickly to any abnormalities.
[0003] In existing technologies, ultrasound monitoring has become a common method for monitoring drainage in vascular surgery due to its advantages of not needing to contact the effusion and not disrupting the drainage flow field. However, it has significant technical shortcomings: First, blood clots or connective tissue fragments often detach from the effusion tube. The acoustic impedance difference between these scattering bodies and the effusion can lead to the superposition of ultrasound echo signals. Second, turbulence and air bubbles may occur in the drainage tube due to negative pressure fluctuations. The acoustic impedance difference between the air bubbles and the effusion can also cause additional deviations in flow velocity calculation, making it impossible to accurately reflect the true drainage situation and affecting the medical staff's judgment of the condition. Therefore, how to reduce the impact of scattering bodies in the effusion on drainage flow monitoring has become a challenge for the industry. Summary of the Invention
[0004] This application provides a vascular surgical drainage device and method that can reduce the influence of scattering bodies in the effusion on the monitoring of drainage flow.
[0005] In a first aspect, this application provides a method for monitoring vascular surgical drainage, used for monitoring drainage with vascular surgical drainage equipment, wherein an ultrasound transducer is pre-installed on the outside of the drainage tube, and the method includes: The vascular surgical drainage device is activated to drain the fluid accumulation in the target patient. During the drainage process, an ultrasonic signal is emitted into the drainage tube through the ultrasonic transducer, and the reflected echo signal is collected simultaneously. The echo signal is decomposed into multiple reflection components under different modes. Based on the trend characteristics of each reflection component, the stable flow component corresponding to the stable laminar flow state of the liquid is extracted from all reflection components. For each stable flow component, the scattering interference of impurities on the ultrasonic waves in each stable flow component is identified according to the difference characteristics of acoustic impedance between the scatterer and the liquid in each stable flow component. Extract the target signal of the liquid phase from all stable flow components by eliminating all scattering interferences; The liquid flow rate at the cross-section of the drainage tube is determined based on all target signals and the cross-sectional area of the drainage tube, and the drainage process in vascular surgery is monitored based on the liquid flow rate.
[0006] In some embodiments, decomposing the echo signal into multiple reflection components under different modes specifically includes: Select an echo signal as the selected echo signal and use the selected echo signal as the initial signal; The initial modal components are obtained by removing the local average trend from the initial signal; If the ultrasonic dynamic characteristics of the preliminary modal component do not meet the preset termination condition, the preliminary modal component is used as a new initial signal, and the local average trend in the new initial signal is removed again to obtain a new preliminary modal component. This process continues until the ultrasonic dynamic characteristics of the obtained preliminary modal component meet the termination condition, and the finally obtained preliminary modal component is used as a reflection component. The reflection component is removed from the initial signal to obtain a new initial signal, and the above steps are repeated until the obtained initial signal is a monotonic signal, thereby obtaining multiple reflection components; The remaining echo signal is further decomposed into reflection components in multiple different modes.
[0007] In some embodiments, extracting the stable flow component corresponding to the stable laminar flow state from all reflection components based on the trend characteristics of each reflection component specifically includes: Determine the energy variation curve of the ultrasound in each reflection component; The trend characteristics of each reflection component are determined based on the fluctuation coefficient of the ultrasonic energy change curve under different local windows. All trend features are compared with preset stability thresholds, and then the stable flow component corresponding to the stable laminar flow state of the liquid accumulation is extracted from all reflection components.
[0008] In some embodiments, determining the trend characteristics of each reflection component based on the fluctuation coefficient of the ultrasound energy variation curve in each reflection component under different local windows specifically includes: Pre-set multiple local windows with different durations; Select a local window of a certain time length as the selected local window, and divide each energy change curve into multiple continuous sub-intervals according to the time length of the selected local window; Determine the standardized range of ultrasound energy variation within each sub-interval; The fluctuation coefficient of each energy change curve under a selected local window is determined based on the standardized range of all sub-intervals corresponding to each energy change curve. Continue to determine the fluctuation coefficient of each energy change curve within the remaining local window; The trend characteristics of each energy change curve are determined based on all the fluctuation coefficients of each energy change curve.
[0009] In some embodiments, identifying the scattering interference of impurities on ultrasound in each stable flow component based on the difference in acoustic impedance between the scatterer and the accumulated liquid in each stable flow component specifically includes: Select a stable flow component as the selected stable flow component, and discretize the stable flow component into a discrete signal; Based on the discrete signal, determine the acoustic impedance difference characteristics between the scatterer and the accumulated liquid in the selected stable flow component; Based on the aforementioned differences, the scattering interference of ultrasonic waves by impurities in the selected stable flow component is determined. Further investigation was conducted to determine the scattering interference of impurities on ultrasound in the remaining stable flow component.
[0010] In some embodiments, extracting the target signal of the liquid phase from all stable flow components through all scattering interference specifically includes: Obtain the acoustic impedance of a gas-phase scattering body; The interference threshold of the gas phase is determined based on the acoustic impedance of the gas phase scatterer. The interference threshold of the solid phase was determined based on preliminary experiments; All scattering interferences are compared with various interference thresholds to extract the target signal in the liquid phase.
[0011] In some embodiments, determining the liquid flow rate at the cross-section of the drainage tube based on all target signals and the cross-sectional area of the drainage tube specifically includes: Reconstruct all target signals into flow velocity signals; The liquid flow rate at the cross-section of the drainage tube is determined based on the Doppler frequency shift of the flow velocity signal and the cross-sectional area of the drainage tube.
[0012] Secondly, this application provides a vascular surgical drainage device, which includes a drainage monitoring unit, the drainage monitoring unit comprising: The acquisition module is used to activate the vascular surgical drainage device to drain the effusion of the target patient. During the drainage process, the ultrasonic transducer emits an ultrasonic signal into the drainage tube and simultaneously acquires the reflected echo signal. The processing module is used to decompose the echo signal into multiple reflection components under different modes, extract the stable flow component corresponding to the stable laminar flow state of the liquid from all reflection components based on the trend characteristics of each reflection component, and for each stable flow component, identify the scattering interference of impurities on the ultrasonic waves in each stable flow component based on the difference characteristics of acoustic impedance between the scatterer and the liquid in each stable flow component. The processing module is also used to extract the target signal of the liquid phase from all stable flow components through all scattering interferences. The execution module is used to determine the liquid flow rate at the cross-section of the drainage tube based on all target signals and the cross-sectional area of the drainage tube, and to monitor the drainage process in vascular surgery based on the liquid flow rate.
[0013] Thirdly, this application provides a computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described vascular surgical drainage monitoring method.
[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described vascular surgical drainage monitoring method.
[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The vascular surgical drainage device and method provided in this application firstly activate the vascular surgical drainage device to drain the effusion of the target patient. During the drainage process, an ultrasonic signal is emitted into the drainage tube through the ultrasonic transducer, and the reflected echo signal is acquired simultaneously. The echo signal is decomposed into multiple reflection components under different modes. Based on the trend characteristics of each reflection component, a stable flow component corresponding to the stable laminar flow state of the effusion is extracted from all reflection components. For each stable flow component, the scattering interference of impurities on the ultrasonic waves in each stable flow component is identified based on the difference in acoustic impedance between the scatterer and the effusion in each stable flow component. The target signal of the liquid phase is extracted from all stable flow components through all scattering interferences. The liquid phase flow rate at the cross-section of the drainage tube is determined based on all target signals and the cross-sectional area of the drainage tube. The vascular surgical drainage process is monitored based on the liquid phase flow rate.
[0016] Therefore, this application decomposes the echo signal of ultrasound into multiple reflection components under different modes, and extracts the stable flow component corresponding to the stable laminar flow state of the accumulated liquid based on the trend characteristics of each reflection component. This avoids the ultrasound signal fluctuation caused by negative pressure fluctuations. Subsequently, for each stable flow component, scattering interference is identified based on the difference in acoustic impedance between the scatterer and the accumulated liquid. By utilizing the essential difference in acoustic impedance between the scatterer and the accumulated liquid, the degree of interference of the scatterer on the ultrasound is located, and the interference signals generated by the ultrasound scattered by different scatterers are extracted. Finally, the liquid flow rate is determined based on the target liquid phase signal and the cross-sectional area of the drainage tube, completely eliminating the superposition effect of the scatterer reflection signal on the flow rate calculation, ensuring that the flow rate monitoring results only reflect the true flow state of the accumulated liquid, and significantly reducing the interference of the scatterer on the drainage flow rate monitoring. In summary, the scheme of this application can reduce the impact of scatterers in the accumulated liquid on the drainage flow rate monitoring. Attached Figure Description
[0017] Figure 1 This is an exemplary flowchart of a vascular surgical drainage monitoring method according to some embodiments of this application; Figure 2 This is an exemplary flowchart illustrating the determination of scattering interference according to some embodiments of this application; Figure 3 This is an exemplary flowchart illustrating the determination of liquid phase flow rate according to some embodiments of this application; Figure 4 This is a schematic diagram of the structure of a drainage monitoring unit according to some embodiments of this application; Figure 5 This is a schematic diagram of the structure of a computer device for implementing a vascular surgical drainage monitoring method according to some embodiments of this application. Detailed Implementation
[0018] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.
[0019] refer to Figure 1 The figure is an exemplary flowchart of a vascular surgical drainage monitoring method according to some embodiments of this application. The vascular surgical drainage monitoring method mainly includes the following steps: In step 101, the vascular surgical drainage device is activated to drain the fluid accumulation in the target patient. During the drainage process, the ultrasound transducer transmits ultrasound signals into the drainage tube, and the reflected echo signals are collected simultaneously.
[0020] In some embodiments, before activating the vascular surgical drainage device to drain the fluid in the target patient, the method further includes: pre-installing an ultrasound transducer on the outside of the drainage tube. As a preferred embodiment, the pre-installation of the ultrasound transducer on the outside of the drainage tube in this application can be achieved in the following manner: selecting an ultrasound transducer that matches the diameter of commonly used vascular surgical drainage tubes, for example, the diameter of commonly used vascular surgical drainage tubes is 8-20 Fr; then, selecting a straight section on the outside of the drainage tube as the installation position; wiping the installation position and applying medical ultrasound coupling agent; then, attaching the ultrasound transducer to the installation position and fixing it in place, thus completing the installation of the ultrasound transducer.
[0021] In specific implementation, during the drainage process, the ultrasonic transducer emits ultrasonic signals into the drainage tube and simultaneously collects the reflected echo signals. This can be achieved in the following way: the signal transmitting unit of the ultrasonic transducer emits pulsed ultrasonic signals along a preset emission angle with the cross-section of the drainage tube, and at the same time, the signal receiving unit of the ultrasonic transducer captures the echo signals reflected by the fluid in the drainage tube. The preset emission angle can be preset according to the requirements. Under normal circumstances, the emission angle can be preset to 45°.
[0022] In step 102, the echo signal is decomposed into multiple reflection components under different modes. Based on the trend characteristics of each reflection component, the stable flow component corresponding to the stable laminar flow state of the liquid is extracted from all reflection components. For each stable flow component, the scattering interference of impurities on the ultrasonic waves in each stable flow component is identified according to the difference in acoustic impedance between the scatterer and the liquid in each stable flow component.
[0023] In some embodiments, decomposing the echo signal into multiple reflection components under different modes can be achieved by the following steps: Select an echo signal as the selected echo signal and use the selected echo signal as the initial signal; The initial modal components are obtained by removing the local average trend from the initial signal; If the ultrasonic dynamic characteristics of the preliminary modal component do not meet the preset termination condition, the preliminary modal component is used as a new initial signal, and the local average trend in the new initial signal is removed again to obtain a new preliminary modal component. This process continues until the ultrasonic dynamic characteristics of the obtained preliminary modal component meet the termination condition, and the finally obtained preliminary modal component is used as a reflection component. The reflection component is removed from the initial signal to obtain a new initial signal, and the above steps are repeated until the obtained initial signal is a monotonic signal, thereby obtaining multiple reflection components; The remaining echo signal is further decomposed into reflection components in multiple different modes.
[0024] In specific implementation, removing the local average trend from the initial signal to obtain the preliminary modal components can be achieved in the following way: First, extract all the maxima and minima in the initial signal. Then, perform curve fitting on all the maxima and minima respectively, and average the two curves. Use the averaged curve as the local average trend in the initial signal. Finally, subtract the average trend from the initial signal and use the resulting curve as the preliminary modal components.
[0025] It should be noted that the average trend in this application is a curve that describes the local basic change trend of the initial signal.
[0026] It should be noted that, in this application, the preliminary modal component refers to the signal component obtained by subtracting the corresponding local average trend from the initial signal, which is a preliminary stripping away of the basic trend. It is merely a process quantity and has no actual meaning.
[0027] It should be noted that the ultrasonic dynamic feature in this application is a parameter value used to measure the degree of fluctuation of the corresponding ultrasonic echo component in the preliminary modal component. The larger the ultrasonic dynamic feature, the more chaotic the degree of fluctuation of the corresponding ultrasonic echo component in the preliminary modal component, that is, the preliminary modal component corresponds to the ultrasonic echo of multiple scatterers, which needs to be further separated. As a preferred embodiment, the ultrasonic dynamic feature in this application can be determined in the following way: subtract the number of zero-crossing points from the number of local extreme points in the preliminary modal component, and take the difference as the ultrasonic dynamic feature.
[0028] Additionally, it should be noted that the preset termination condition in this application refers to the ultrasonic dynamic characteristic being less than or equal to 1. In other embodiments, the termination condition can also be set to the ultrasonic dynamic characteristic being less than or equal to other smaller values greater than 0, which is not limited here.
[0029] In a specific implementation, removing the reflection component from the initial signal to obtain a new initial signal can be achieved in the following way: subtracting the reflection component from the initial signal to obtain the new initial signal.
[0030] It should be noted that, in this application, a monotonic signal refers to a signal that is monotonically increasing or monotonically decreasing.
[0031] In some embodiments, extracting the stable flow component corresponding to the stable laminar flow state from all reflection components based on the trend characteristics of each reflection component can be achieved by the following steps: Determine the energy variation curve of the ultrasound in each reflection component; The trend characteristics of each reflection component are determined based on the fluctuation coefficient of the ultrasonic energy change curve under different local windows. All trend features are compared with preset stability thresholds, and then the stable flow component corresponding to the stable laminar flow state of the liquid accumulation is extracted from all reflection components.
[0032] In practice, the energy change curve of ultrasound in each reflection component can be determined in the following way: the curve obtained by squaring each reflection component is used as the energy change curve of ultrasound in each reflection component.
[0033] It should be noted that the energy change curve in this application is a curve used to describe the energy change of ultrasonic waves reflected by the scatterer in the effluent.
[0034] In some embodiments, determining the trend characteristics of each reflection component based on the fluctuation coefficient of the ultrasound energy variation curve in each reflection component under different local windows can be achieved by the following steps: Pre-set multiple local windows with different durations; Select a local window of a certain time length as the selected local window, and divide each energy change curve into multiple continuous sub-intervals according to the time length of the selected local window; Determine the standardized range of ultrasound energy variation within each sub-interval; The fluctuation coefficient of each energy change curve under a selected local window is determined based on the standardized range of all sub-intervals corresponding to each energy change curve. Continue to determine the fluctuation coefficient of each energy change curve within the remaining local window; The trend characteristics of each energy change curve are determined based on all the fluctuation coefficients of each energy change curve.
[0035] It should be noted that the duration of the local window in this application can be preset according to the length of the energy change curve. For example, the duration of the local window in this application is preset to 1 / 40, 1 / 35, 1 / 30, 1 / 25, 1 / 20, 1 / 15, 1 / 10, and 1 / 5 of the length of the energy change curve, respectively.
[0036] In practice, dividing each energy change curve into multiple continuous sub-intervals according to the selected local window time length can be achieved in the following way: the energy change curve is evenly divided into multiple sub-intervals of the same length according to the selected local window time length. For example, if the selected local window time length is 1 / 20 of the length of the energy change curve, then the energy change curve is divided into 20 sub-intervals of the same length, and no two sub-intervals overlap.
[0037] In specific implementation, the standardized range of ultrasound energy change within each sub-interval can be determined as follows: First, calculate the average value of ultrasound energy change within each sub-interval, and subtract the average value of ultrasound energy change within each sub-interval from the ultrasound energy change curve within each sub-interval to obtain the deviation sequence corresponding to each sub-interval. Then, sum the deviation sequences in chronological order to obtain the cumulative deviation curve. That is, the initial cumulative deviation is 0, and the cumulative deviation at time t is the sum of all deviations before time t. Then, the difference between the maximum and minimum values in the cumulative deviation curve of each sub-interval is taken as the range of each sub-interval. Finally, the ratio of the range of each sub-interval to the standard deviation of ultrasound energy change within each sub-interval is taken as the standardized range of each sub-interval. Here, calculating the average value of ultrasound energy change within each sub-interval means calculating the average value of the ultrasound energy change curve within the corresponding sub-interval, and the standard deviation of the ultrasound energy change curve within the corresponding sub-interval can be taken as the standard deviation of ultrasound energy change within the corresponding sub-interval.
[0038] It should be noted that, in this application, the standardized range is a parameter value that measures the relative severity of ultrasonic energy fluctuations within a single sub-interval.
[0039] In practice, the fluctuation coefficient of each energy change curve under a selected local window can be determined by the following method based on the standardized range of all sub-intervals corresponding to each energy change curve: the average of the standardized ranges of all sub-intervals corresponding to each energy change curve is used as the fluctuation coefficient of each energy change curve under a selected local window.
[0040] It should be noted that the fluctuation coefficient in this application is a parameter value used to measure the fluctuation of the energy change curve under a selected local window.
[0041] In practice, determining the trend characteristics of each energy change curve based on all fluctuation coefficients of each energy change curve can be achieved in the following way: First, select an energy change curve as the selected energy change curve, and then perform curve fitting after taking the natural logarithm of all fluctuation coefficients and all local window time lengths of the energy change curve. The independent variable is the natural logarithm of the local window time length, and the dependent variable is the natural logarithm of the fluctuation coefficient. Finally, the coefficient of the first-order term in the fitted curve is taken as the trend characteristics of the energy change curve, and the trend characteristics of the remaining energy change curves are further determined.
[0042] It should be noted that the trend feature in this application is a parameter value used to measure the overall trend stability of the change in ultrasonic energy in the reflection component.
[0043] Additionally, it should be noted that the trend characteristic in this application is a value between 0 and 1. Since the negative pressure of the automated vascular drainage equipment in vascular surgery is stable, the fluid in the drainage tube is theoretically a stable laminar flow. The energy change of the reflected ultrasound should have a fixed trend rather than random fluctuation. The closer the trend characteristic is to 0.5, the closer the energy change of the reflected ultrasound is to random fluctuation. That is, the more turbulent components caused by bubbles are contained in the reflected component. Therefore, the stability threshold can be preset to 0.5.
[0044] In practice, the stable flow component corresponding to the stable laminar flow state of the liquid accumulation can be extracted from all reflection components by comparing all trend features with the preset stability threshold. This can be achieved in the following way: First, calculate the relative deviation between all trend features and the preset stability threshold, and take the frequency components with a relative deviation greater than 40% as the stable flow component corresponding to the stable laminar flow state of the liquid accumulation.
[0045] It should be noted that, in this application, the steady flow component refers to the ultrasonic component reflected by the accumulated liquid corresponding to the steady flow in the drainage tube.
[0046] In some embodiments, reference Figure 2 The figure is an exemplary flowchart illustrating the determination of scattering interference according to some embodiments of this application. In this application, the scattering interference of impurities on ultrasonic waves in each stable flow component can be identified based on the difference in acoustic impedance between the scatterer and the accumulated liquid in each stable flow component, which can be achieved by the following steps: In step 1021, a stable flow component is selected as the selected stable flow component, and the stable flow component is discretized into a discrete signal; In step 1022, the acoustic impedance difference characteristics between the scatterer and the accumulated liquid in the selected stable flow component are determined based on the discrete signal; In step 1023, the scattering interference of impurities on ultrasonic waves in the selected stable flow component is determined based on the difference characteristics. In step 1024, the scattering interference of impurities on ultrasound in the remaining stable flow component is further determined.
[0047] In a specific implementation, the stable flow component can be discretized into a discrete signal in the following way: the stable flow component is sampled discretely at a preset sampling frequency, and the signal obtained from the discrete sampling is used as the discrete signal of the stable flow component. The sampling frequency can be preset according to the highest frequency of the emitted ultrasonic signal. For example, if the highest frequency of the emitted ultrasonic signal in this application is 7.5 MHz, then the sampling frequency is set to twice the highest frequency, i.e., 15 MHz.
[0048] It should be noted that, in this application, discrete signal refers to the stable flow component after discrete sampling.
[0049] In specific implementation, the acoustic impedance difference characteristics between the scatterer and the accumulating liquid in the selected stable flow component can be determined in the following way based on the discrete signal: First, for every two adjacent sampling points in the discrete signal, calculate the conjugate product between the data of these two adjacent sampling points. Then, sum all the obtained conjugate products and use the sum as the acoustic impedance difference characteristics between the scatterer and the accumulating liquid in the selected stable flow component.
[0050] It should be noted that the difference feature in this application is a quantitative parameter reflecting the magnitude of the acoustic impedance difference between different scatterers such as accumulated liquid and impurities within a selected stable flow component.
[0051] In specific implementation, the scattering interference of impurities on ultrasonic waves in the selected stable flow component can be determined according to the difference characteristics in the following way: First, the difference characteristics are plotted as corresponding vectors on the complex plane. Then, the length of the vector is calculated. Finally, the length is divided by the number of sampling points in the discrete signal, and the quotient is taken as the scattering interference of impurities on ultrasonic waves in the selected stable flow component.
[0052] It should be noted that, in this application, scattering interference is a parameter value that measures the degree of scattering interference of impurities on ultrasonic waves within a selected stable flow component.
[0053] In step 103, the target signal of the liquid phase is extracted from all stable flow components through all scattering interferences.
[0054] In some embodiments, extracting the target signal of the liquid phase from all stable flow components through all scattering interferences can be achieved by the following steps: Obtain the acoustic impedance of a gas-phase scattering body; The interference threshold of the gas phase is determined based on the acoustic impedance of the gas phase scatterer. The interference threshold of the solid phase was determined based on preliminary experiments; All scattering interferences are compared with various interference thresholds to extract the target signal in the liquid phase.
[0055] In practice, the acoustic impedance of the gas phase scatterer can be obtained in the following way: the acoustic impedance of the gas phase scatterer can be directly obtained by querying the acoustic impedance of air through the network, and the acoustic impedance of air can be directly used as the acoustic impedance of the gas phase scatterer.
[0056] In specific implementation, the interference threshold of the gas phase based on the acoustic impedance of the gas phase scatterer can be determined in the following way: Under normal circumstances, the acoustic impedance of the gas phase is much larger than that of the liquid phase and the solid phase. For example, the acoustic impedance of the gas phase is 40 kg / m²*s, while the acoustic impedance of the liquid or solid phase is 200,000 kg / m²*s. This difference in acoustic impedance will lead to scattering interference of ultrasonic signals reflected by different scatterers. That is, the scattering interference of ultrasonic signals reflected by the gas phase scatterer is significantly different from that of the solid phase scatterer and the liquid phase. Therefore, all scattering interference can be directly divided into two categories by K-clustering, and the maximum value in the category with the smaller cluster center can be used as the interference threshold of the gas phase.
[0057] In practice, the interference threshold of the solid phase can be determined based on preliminary experiments in the following way: First, collect the scattering interference data of the reflected ultrasound signals from the liquid phase accumulation and solid phase impurities, namely blood clots and human connective tissue, respectively. Then, use data statistics tools to draw the probability density function graph of the scattering interference of the three scatterers. Next, identify the overlapping interval between the upper limit of the liquid phase scattering interference and the lower limit of the solid phase scattering interference in the probability density function graph, and take the midpoint of the interval as the interference threshold of the solid phase.
[0058] In practice, the target signal of the liquid phase can be extracted by comparing all the scattering interferences with each interference threshold. This can be achieved as follows: First, all reflection components with scattering interference less than or equal to the interference threshold of the gas phase are taken as the gas phase interference signal. Then, the reflection components with scattering interference less than or equal to the interference threshold of the solid phase are taken as the solid phase interference signal, and the remaining reflection components are taken as the target signal of the liquid phase.
[0059] It should be noted that, in this application, the interference signal refers to the component of ultrasound reflected by bubbles or solid impurities in the liquid, including interference signals in the gas phase and interference signals in the solid phase.
[0060] Additionally, it should be noted that the target signal in this application refers to the ultrasonic component reflected by the liquid phase in the accumulated liquid.
[0061] In step 104, the liquid flow rate at the cross-section of the drainage tube is determined based on all target signals and the cross-sectional area of the drainage tube, and the drainage process of the vascular surgery is monitored based on the liquid flow rate.
[0062] In some embodiments, reference Figure 3 The figure is an exemplary flowchart illustrating the determination of liquid flow rate according to some embodiments of this application. The determination of the liquid flow rate at the cross-section of the drainage tube based on all target signals and the cross-sectional area of the drainage tube can be achieved using the following steps: In step 1041, all target signals are reconstructed into flow velocity signals; In step 1042, the liquid flow rate at the cross-section of the drainage tube is determined based on the Doppler frequency shift of the flow velocity signal and the cross-sectional area of the drainage tube.
[0063] In practice, reconstructing all target signals into flow velocity signals can be achieved by adding all target signals together to obtain the flow velocity signal.
[0064] In specific implementation, the liquid flow rate at the cross-section of the drainage tube can be determined based on the Doppler frequency shift of the flow velocity signal and the cross-sectional area of the drainage tube in the following manner: First, the Doppler frequency shift of the flow velocity signal is calculated using the autocorrelation function method in the prior art. Then, the calculated Doppler frequency shift is substituted into the Doppler effect formula, i.e., flow velocity = Doppler frequency shift / 2 times the speed of sound x the cosine of the angle, where the emission angle in this application is the angle, and the flow velocity is calculated. Then, the flow rate is calculated according to the formula flow rate = flow velocity x cross-sectional area, and this flow rate is used as the liquid flow rate at the cross-section of the drainage tube. The cross-sectional area of the drainage tube can be obtained directly from the product manual of the drainage tube in advance.
[0065] In practice, monitoring the drainage process in vascular surgery based on the liquid flow rate can be achieved in the following way: a flow rate reference value is preset, and the relative error between the liquid flow rate and the flow rate reference value is calculated. If the relative error is greater than 10%, an alarm is triggered. The flow rate reference value can be set by medical staff specializing in vascular surgery.
[0066] In another aspect, in some embodiments, this application provides a vascular surgical drainage device, which includes a drainage monitoring unit, as referenced. Figure 4 The figure is a schematic diagram of the structure of a drainage monitoring unit 400 according to some embodiments of this application. The drainage monitoring unit 400 includes: a data acquisition module 401, a processing module 402, and an execution module 403, which are described below: Acquisition module 401, in this application, is mainly used to start the drainage device to drain the fluid in the target patient. During the drainage process, the ultrasonic transducer emits an ultrasonic signal into the drainage tube and simultaneously acquires the reflected echo signal. Processing module 402, in this application, is mainly used to decompose the echo signal into multiple reflection components under different modes, extract the stable flow component corresponding to the stable laminar flow state of the liquid from all reflection components based on the trend characteristics of each reflection component, and for each stable flow component, identify the scattering interference of impurities on the ultrasonic waves in each stable flow component based on the difference characteristics of acoustic impedance between the scatterer and the liquid in each stable flow component. It should be noted that the processing module 402 in this application is also used to classify each stable flow component into interference signal and target signal of liquid phase through all scattering interference; The execution module 403 in this application is mainly used to determine the liquid flow rate at the cross-section of the drainage tube based on all target signals and the cross-sectional area of the drainage tube, and to monitor the drainage process of vascular surgery based on the liquid flow rate.
[0067] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described vascular surgical drainage monitoring method.
[0068] In some embodiments, reference Figure 5 This figure is a schematic diagram of the structure of a computer device for implementing a vascular surgical drainage monitoring method according to some embodiments of this application. The vascular surgical drainage monitoring method in the above embodiments can be implemented through... Figure 5 The computer device shown is used to implement this, and the computer device 500 includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.
[0069] Processor 501 can be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).
[0070] The communication bus 502 can be used to transmit information between the aforementioned components.
[0071] Memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CDROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory 503 may exist independently and be connected to processor 501 via communication bus 502. Memory 503 may also be integrated with processor 501.
[0072] The memory 503 stores program code for executing the solution of this application, and its execution is controlled by the processor 501. The processor 501 executes the program code stored in the memory 503. The program code may include one or more software modules. In the above embodiments, the vascular surgical drainage monitoring method can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.
[0073] Communication interface 504 uses any transceiver-like device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.
[0074] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single CPU) processor or a multi-core (multi CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).
[0075] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.
[0076] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described vascular surgical drainage monitoring method.
[0077] In summary, the vascular surgical drainage device and method disclosed in this application firstly involves activating the vascular surgical drainage device to drain the effusion of the target patient. During the drainage process, an ultrasonic signal is emitted into the drainage tube via the ultrasonic transducer, and the reflected echo signal is simultaneously acquired. The echo signal is decomposed into multiple reflection components under different modes. Based on the trend characteristics of each reflection component, a stable flow component corresponding to the stable laminar flow state of the effusion is extracted from all reflection components. For each stable flow component, the scattering interference of impurities on the ultrasonic waves in each stable flow component is identified based on the difference in acoustic impedance between the scatterer and the effusion in each stable flow component. The target signal of the liquid phase is extracted from all stable flow components through all scattering interferences. The liquid flow rate at the cross-section of the drainage tube is determined based on all target signals and the cross-sectional area of the drainage tube, and the vascular surgical drainage process is monitored based on the liquid flow rate.
[0078] Therefore, this application decomposes the echo signal of ultrasound into multiple reflection components under different modes, and extracts the stable flow component corresponding to the stable laminar flow state of the accumulated liquid based on the trend characteristics of each reflection component. This avoids the ultrasound signal fluctuation caused by negative pressure fluctuations. Subsequently, for each stable flow component, scattering interference is identified based on the difference in acoustic impedance between the scatterer and the accumulated liquid. By utilizing the essential difference in acoustic impedance between the scatterer and the accumulated liquid, the degree of interference of the scatterer on the ultrasound is located, and the interference signals generated by the ultrasound scattered by different scatterers are extracted. Finally, the liquid flow rate is determined based on the target liquid phase signal and the cross-sectional area of the drainage tube, completely eliminating the superposition effect of the scatterer reflection signal on the flow rate calculation, ensuring that the flow rate monitoring results only reflect the true flow state of the accumulated liquid, and significantly reducing the interference of the scatterer on the drainage flow rate monitoring. In summary, the scheme of this application can reduce the impact of scatterers in the accumulated liquid on the drainage flow rate monitoring.
[0079] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.
[0080] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.
Claims
1. A method of extracorporeal surgery drainage monitoring for a vascular surgery drainage device for drainage monitoring, wherein, The method is characterized in that the method comprises: starting a vascular surgical drainage device to drain a hydrops of a target patient, emitting ultrasonic signals into the drainage tube through the ultrasonic transducer during the drainage process, and synchronously collecting reflected echo signals; decomposing the echo signals into reflected components in different modalities, extracting stable flow components corresponding to a stable laminar flow state of the hydrops from all the reflected components based on trend characteristics of each reflected component, and identifying scattering interference of impurities in each stable flow component on ultrasonic waves according to a difference characteristic of acoustic impedance between scatterers and the hydrops in each stable flow component; extracting target signals of liquid phases from all the stable flow components through all the scattering interference; determining a liquid phase flow rate at a cross section of the drainage tube based on all the target signals and a cross sectional area of the drainage tube, and monitoring the vascular surgical drainage process according to the liquid phase flow rate.
2. The method of claim 1, wherein, The step of decomposing the echo signals into reflected components in different modalities specifically comprises: selecting an echo signal as a selected echo signal, and taking the selected echo signal as an initial signal; removing a local average trend from the initial signal to obtain a preliminary modal component; if an ultrasonic fluctuation characteristic of the preliminary modal component does not satisfy a preset termination condition, taking the preliminary modal component as a new initial signal, removing a local average trend from the new initial signal to obtain a new preliminary modal component, and repeating the above steps until the ultrasonic fluctuation characteristic of the obtained preliminary modal component satisfies the termination condition, and taking the finally obtained preliminary modal component as a reflected component; removing the reflected component from the initial signal to obtain a new initial signal, and repeating the above steps until the obtained initial signal is a monotonic signal, and thereby obtaining a plurality of reflected components; continuing to decompose the remaining echo signals into reflected components in different modalities.
3. The method of claim 1, wherein, The step of extracting stable flow components corresponding to a stable laminar flow state of the hydrops from all the reflected components based on trend characteristics of each reflected component specifically comprises: determining an energy variation curve of ultrasonic waves in each reflected component; determining a trend characteristic of each reflected component according to fluctuation coefficients of the energy variation curve of ultrasonic waves in each reflected component in different local windows; comparing all the trend characteristics with a preset stable threshold, and thereby extracting stable flow components corresponding to a stable laminar flow state of the hydrops from all the reflected components.
4. The method of claim 3, wherein, The step of determining a trend characteristic of each reflected component according to fluctuation coefficients of the energy variation curve of ultrasonic waves in each reflected component in different local windows specifically comprises: presetting a plurality of local windows with different time lengths; selecting a local window with a time length as a selected local window, and dividing each energy variation curve into a plurality of continuous subintervals according to the time length of the selected local window; determining a standardized range of ultrasonic energy variation in each subinterval; determining a fluctuation coefficient of each energy variation curve in the selected local window according to standardized ranges of all the subintervals corresponding to each energy variation curve; continuing to determine fluctuation coefficients of each energy variation curve in the remaining local windows; Determine the trend feature of each energy variation curve according to all fluctuation coefficients of each energy variation curve.
5. The method of claim 1, wherein, The scattering interference of impurities in each stable flow component to ultrasonic waves is identified according to the difference feature of acoustic impedance between scatterers and the accumulation liquid in each stable flow component, and specifically includes: Discretize the stable flow components into discrete signals by selecting one stable flow component as a selected stable flow component; Determine the difference feature of acoustic impedance between scatterers and the accumulation liquid in the selected stable flow component according to the discrete signals; Determine the scattering interference of impurities in the selected stable flow component to ultrasonic waves according to the difference feature; Continue to determine the scattering interference of impurities in the remaining stable flow components to ultrasonic waves.
6. The method of claim 1, wherein, Extract the target signal of the liquid phase from all the stable flow components through all the scattering interferences, and specifically includes: Obtain the acoustic impedance of the gas-phase scatterers; Determine the interference threshold of the gas phase based on the acoustic impedance of the gas-phase scatterers; Determine the interference threshold of the solid phase based on a pre-experiment; Compare all the scattering interferences with the interference thresholds, and then extract the target signal of the liquid phase.
7. The method of claim 1, wherein, Determine the liquid phase flow at the cross section of the drainage tube based on all the target signals and the cross-sectional area of the drainage tube, and specifically includes: Reconstruct all the target signals into flow rate signals; Determine the liquid phase flow at the cross section of the drainage tube based on the Doppler frequency shift of the flow rate signals and the cross-sectional area of the drainage tube.
8. An extravascular surgical drain device comprising a drain monitoring unit, wherein, Pre-install an ultrasonic transducer outside the drainage tube, and the drainage monitoring unit comprises: A collection module is configured to start the extracorporeal surgical drainage device to drain the accumulation liquid of a target patient, emit ultrasonic signals into the drainage tube through the ultrasonic transducer during the drainage process, and synchronously collect reflected echo signals; A processing module is configured to decompose the echo signals into reflection components in multiple different modalities, extract stable flow components corresponding to the stable laminar flow state of the accumulation liquid from all the reflection components based on the trend feature of each reflection component, and for each stable flow component, identify the scattering interference of impurities in each stable flow component to ultrasonic waves according to the difference feature of acoustic impedance between scatterers and the accumulation liquid in each stable flow component. The processing module is further configured to extract the target signal of the liquid phase from all the stable flow components through all the scattering interferences. An execution module is configured to determine the liquid phase flow at the cross section of the drainage tube based on all the target signals and the cross-sectional area of the drainage tube, and monitor the drainage process of the extracorporeal surgery according to the liquid phase flow.
9. A computer device, comprising: The computer device comprises a memory and a processor, the memory stores a code, and the processor is configured to obtain the code and execute the extracorporeal surgical drainage monitoring method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The computer program is executed by the processor to implement the extracorporeal surgical drainage monitoring method according to any one of claims 1 to 7.