Multi-scene universal elastic cavity fluid dynamics research test method and system

Abstract

This invention discloses a multi-scenario universal elastic cavity fluid dynamics research and testing method and system. It can automatically identify the cavity type based on the compliance coefficient of the elastic cavity and adjust the fluid injection mode, realizing unified adaptation for various intracavitary treatment scenarios such as laparoscopy, arthroscopy, ureteroscopy, and cystoscopy. The system can provide customized fluid dynamics environment according to the physical characteristics of different anatomical organs, such as compliance, pressure threshold, and inherent volume. It effectively solves the technical bottleneck of existing R&D equipment having single function and being unable to be universally applicable across scenarios, realizing universal simulation and research across organs and multiple scenarios.

Description

Technical Field

[0001] This invention relates to the field of medical device simulation testing technology, specifically to a multi-scenario universal elastic cavity fluid dynamics research and testing method and system for simulating various natural cavities or body cavity environments of the human body to conduct performance testing of minimally invasive intracavitary treatment devices. Background Technology

[0002] Minimally invasive endovascular treatment techniques have become mainstream in modern surgery, encompassing various procedures such as laparoscopy, arthroscopy, ureteroscopy, and cystoscopy. The core commonality of these surgeries lies in the necessity of injecting a fluid medium (gas or liquid) into the body's natural cavities or potential spaces to create operating space and maintain a clear view. However, different human organs possess drastically different physical properties, meaning their "elastic reservoir" characteristics vary significantly.

[0003] The abdominal cavity is a large-volume, elastic cavity, typically filled with CO2 gas, requiring a low, constant pressure and relatively low flow rate. Joint cavities are small, closed spaces with a rigid (semi-rigid) structure, requiring high-flow-rate flushing with saline to remove debris; excessive pressure can easily lead to extravasation. The bladder in the urinary system is a large-volume, highly compliant cavity, requiring protection against rupture; while the ureters and renal calyces are tiny tubular cavities with a volume of only 5-10 ml, extremely sensitive to pressure fluctuations, and even slight mishaps can lead to hydronephrosis or infection.

[0004] However, existing endovascular treatment device research and testing platforms face significant technical bottlenecks: Existing testing equipment is mostly designed for single organs and lacks standardized tools that can simulate the characteristics of isolated biological tissues and achieve multidimensional parameter quantitative evaluation. Pneumoperitoneum testing platforms are only for large-volume abdominal cavities, and joint pump testing platforms are only for rigid joint cavities. There is a lack of a universal system that can integrate multiple media (gas / liquid) and adapt to different anatomical features. Summary of the Invention

[0005] Technical objective: To address the shortcomings of existing intracavitary treatment research and testing equipment, this invention discloses a multi-scenario universal elastic reservoir fluid dynamics research and testing method and system.

[0006] Technical solution: To achieve the above technical objectives, the present invention adopts the following technical solution: A multi-scenario universal elastic reservoir fluid dynamics research and testing method includes the following steps: S01. Identify reservoir type based on the compliance coefficient of elastic reservoir; S02. Switch to the corresponding fluid injection mode based on the reservoir type; each reservoir type's fluid injection mode includes a limit detection sub-mode and a steady-state simulation sub-mode. S03. In the limit detection sub-mode, the rate of change of the internal pressure, surface tension and visual volume data of the elastic storage cavity is detected in real time to obtain the fluid physical bearing limit data of the corresponding elastic storage cavity. S04. In the steady-state simulation sub-mode, the fluid physical bearing limit data of step S03 is used as the boundary to set a test safety red line. During each test, when the elastic reservoir data approaches the set test safety red line, the protection mechanism is triggered to protect the reservoir, and finally the optimal combination of fluid dynamic parameters under the corresponding elastic reservoir is obtained.

[0007] Preferably, the elastic reservoir of the present invention includes a bladder cavity, a ureteral cavity, a joint cavity, and a peritoneal cavity, and the corresponding fluid injection modes include cystoscopy mode, ureteroscopy mode, arthroscopy mode, and laparoscopy mode; in step S01, the reservoir type is identified according to the numerical range of the compliance coefficient C and the slope of its nonlinear change, wherein, for the peritoneal cavity: C > 150 mL / cm O; Bladder cavity: 30 <C≤150 mL / cm O; Ureteral lumen: 1 <C≤20 mL / cm O; Joint cavity: C≤1 mL / cm O.

[0008] Preferably, in step S01 of the present invention, the process of identifying the reservoir type includes: S011. Inject pulsed fluid into the elastic reservoir; S012. Record the pressure and volume change data inside the elastic storage cavity and establish a pressure-volume characterization model; S013. Calculate the compliance coefficient of the elastic reservoir based on the pressure-volume characterization model, and identify the reservoir type based on the slope of the nonlinear change of the compliance coefficient.

[0009] Preferably, the steady-state simulation sub-mode of the present invention includes a steady-state maintenance phase and a dynamic active intervention phase; During the steady-state maintenance phase, a certain characteristic of the elastic reservoir is selected as the main control variable based on its characteristics. During fluid injection, the fluid injection process is controlled by this main control variable, and the main control variable is kept stable by controlling the fluid input and suction rate. During the dynamic active intervention phase, debris is introduced into the fluid state changes within the elastic reservoir during the simulated surgical procedure. By altering the fluid flow parameters, the debris within the elastic reservoir is cleared. A correlation model is established by combining the fluid physical bearing capacity limit data of the elastic reservoir with the debris removal rate. Iterative testing is then conducted to determine the optimal combination of fluid dynamic parameters under the current reservoir characteristics.

[0010] Preferably, in the dynamic active intervention phase, the present invention acquires images within the elastic reservoir cavity via an interventional camera module, and calculates a visual field blur index based on the images. And determine the debris removal rate, ,in, Image coordinates The pixel grayscale value at that location, This represents the average grayscale value of the current image.

[0011] Preferably, in the dynamic active intervention phase, if the intervention camera module detects that the proportion of particle pixels in the image within the elastic storage cavity exceeds a preset threshold or the contrast decreases, the isochoric replacement mode is automatically triggered to clean up debris. In the isochoric replacement mode, the fluid injection input pump and the suction pump satisfy the fluid balance equation: ,in, This is the volumetric error compensation amount based on real-time feedback from the cavity. For input traffic, For suction flow rate.

[0012] Preferably, in the isochoric permutation mode, the present invention calculates the visual blur index in real time. rate of change If the equal-capacity replacement mode is continuously executed for a preset duration, tending to zero and If the flow rate is still higher than the cleaning threshold, the constant flow rate of fluid input and suction is switched to frequency-modulated pulse flow. The input pump and suction pump are controlled to generate pulse waveforms with a phase difference of 180° to produce controlled turbulence. The excitation force generated by the controlled turbulence suspends the settled debris and discharges it through suction.

[0013] Preferably, in the limit detection sub-mode, the present invention uses a stepped gradient pressurization strategy for fluid injection, continuously increasing the output pressure or volume. When a discontinuous change in the cavity geometry of the elastic reservoir is detected, or a sudden drop in pressure or a sudden change in surface tension is detected, the preceding peak data at that moment is recorded, and the preceding peak data is used as the fluid physical bearing limit data of the corresponding elastic reservoir.

[0014] This invention also discloses a multi-scenario universal elastic reservoir fluid dynamics research and testing system for implementing the above-mentioned research and testing methods. The system includes a medium control subsystem configured to provide and adjust the dynamic parameters of the fluid medium. The medium control subsystem includes a fluid medium switching unit, a medium input module, and a medium active suction output module. The fluid medium switching unit is configured to connect to an external liquid source and a gas source, and switches between liquid medium and gas medium output according to control commands. A simulated elastic reservoir assembly is connected to the fluid loop of the medium control subsystem. The simulated elastic reservoir assembly includes a simulated elastic reservoir and a universal adapter interface. The universal adapter interface is configured to be detachably connected to the simulated elastic reservoir for fluid injection. The multi-dimensional monitoring subsystem is configured to collect fluid dynamic parameters and physical state parameters in the elastic storage cavity in real time, including a fluid parameter monitoring unit set on the fluid medium path and a cavity state monitoring unit set on the elastic storage cavity. A central control and analysis unit is electrically connected to both the media control subsystem and the multi-dimensional monitoring system. The central control and analysis unit is configured to dynamically adjust the operating parameters of the media control subsystem based on signals fed back from the multi-dimensional monitoring system. The central control and analysis unit has a built-in objective function. F To search for the optimal combination of parameters, F Different weighting coefficients are preset for different modes. , ;,in, For based on Average visual acuity calculated using the index; Debris removal rate This represents the standard deviation of the intracavitary static pressure.

[0015] Preferably, the fluid parameter monitoring unit of the present invention includes: Flow sensors are respectively installed on the output pipeline of the medium input module and the input pipeline of the medium active suction output module, for real-time monitoring of the input flow rate and suction flow rate of the fluid medium; A pipeline pressure sensor is installed on the fluid transmission path between the fluid medium switching unit and the simulated elastic reservoir assembly to monitor the real-time fluid dynamic pressure in the pipeline. The cavity status monitoring unit includes: A tension sensor is attached to the surface of the simulated elastic cavity assembly to monitor the surface tension signal of the cavity. A visual volume sensor is installed outside the simulated elastic storage cavity assembly to capture cavity deformation in real time and calculate dynamic volume change signals in combination with image algorithms; An internal pressure sensor with a probe extending into the simulated elastic reservoir assembly is used to monitor the real-time hydrostatic pressure signal within the cavity. An intervening camera module is placed inside the simulated elastic storage cavity assembly to acquire images inside the cavity to evaluate the clarity of the field of view and the cleaning efficiency of debris. The central control and analysis unit is equipped with a visual performance evaluation module.

[0016] Beneficial Effects: The multi-scenario universal elastic reservoir fluid dynamics research and testing method and system disclosed in this invention have the following beneficial effects: 1. This invention can automatically identify the cavity type based on the compliance coefficient of the elastic cavity and adjust the fluid injection mode, achieving unified adaptation for various endovascular treatment scenarios such as laparoscopy, arthroscopy, ureteroscopy, and cystoscopy. The system can provide customized fluid dynamics environments based on the physical characteristics of different anatomical organs, such as compliance, pressure threshold, and inherent volume, effectively solving the technical bottleneck of existing R&D equipment being single-function and unable to be universally applicable across scenarios, thus realizing universal simulation and research across organs and multiple scenarios.

[0017] 2. The research and testing method of this invention designs a steady-state maintenance stage and a dynamic active intervention stage under the steady-state simulation sub-mode. It can acquire fluid data during normal operation and determine the clearance rate based on image changes in the reservoir during dynamic active intervention. It can also adjust the clearance strategy in a timely manner and provide corresponding fluid control strategies, providing sufficient data support for actual intracavitary treatment and helping to improve the treatment success rate.

[0018] 3. This invention uses frequency-modulated pulse flow to remove debris that is difficult to clean. It utilizes the phase difference with suction to achieve controlled turbulence in the storage cavity, thereby improving the cleaning effect and ensuring the clarity of the storage cavity.

[0019] 4. This invention selects the corresponding characteristics as the main control variables for fluid injection based on the characteristics of different elastic reservoirs, providing a controlled testing environment for reservoir research and testing, which helps to improve research and testing efficiency.

[0020] 5. The research and testing system of this invention establishes a "bio-physical" hybrid simulation system, significantly improving the clinical fidelity of experimental data. Through a universal adapter interface, it can not only connect to standardized artificial synthetic biomimetic cavity modules, but also connect to pre-treated ex vivo biological tissue specimens (such as ex vivo animal kidneys, bladders, ureters, or joint capsules), and place them in a constant-temperature physiological fluid in the environmental maintenance unit for high-fidelity testing. This design allows researchers to explore parameters under realistic biomechanical feedback, bridging the technological gap between bench testing and clinical trials.

[0021] 6. The research and testing system of this invention establishes a precise multi-dimensional sensing feedback system, quantifies the safe operating limits for endovascular treatment, and integrates four-dimensional monitoring signals of surface tension, intracavitary pressure, dynamic volume, and interventional vision. This enables comprehensive and real-time quantification of the physical impact of the fluid medium on the cavity wall. In particular, it prevents tissue tearing through an attached tension sensor and precisely controls the filling degree using a visual volume sensor to avoid overfilling, providing accurate quantitative safety boundaries for the formulation of clinical surgical plans. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0023] Figure 1 This is a schematic diagram of the research and testing system structure of the present invention; Figure 2 This is a schematic diagram of the fluid parameter monitoring unit of the present invention; Figure 3 This is a schematic diagram of the cavity status monitoring unit of the present invention; Figure 4 This is a schematic diagram showing the slope change of the elastic reservoir compliance coefficient of the present invention; Figure 5 This is a flowchart of the ultimate detection sub-mode of the present invention; Figure 6 This is a flowchart of the test for simulating turbidity / bleeding scenarios in this invention; Among them, 100-Media control subsystem, 110-Fluid media switching unit, 120-Media input module, 121-Fluid media input pump, 130-Media active suction output module, 131-Fluid media suction pump, 140-Waste liquid / waste gas collection box, 200-Simulated elastic storage cavity assembly, 210-Universal adapter interface, 300-Multidimensional monitoring subsystem, 310-Fluid parameter monitoring unit, 311-Flow sensor, 312-Pipeline pressure sensor, 320-Cavity status monitoring unit, 321-Tension sensor, 322-Visual volume sensor, 323-Internal pressure sensor, 324-Intervention camera module, 400-Central control and analysis unit, 410-Visual performance evaluation module. Detailed Implementation

[0024] Reference will now be made in detail to embodiments of the present disclosure, one or more of which are set forth herein. Each embodiment and example is provided by way of explanation of the apparatus, composition, and materials of the present disclosure, and not by way of limitation. Rather, the following description provides convenient illustrations for implementing exemplary embodiments of the present disclosure. Indeed, it will be apparent to those skilled in the art that various modifications and variations can be made to the teachings of the present disclosure without departing from the scope or spirit of the present disclosure.

[0025] This invention discloses a multi-scenario universal elastic reservoir fluid dynamics research and testing method, including the following steps: S01. Identify reservoir type based on the compliance coefficient of elastic reservoir; The process of identifying the type of reservoir includes: S011. Inject pulsed fluid into the elastic reservoir; S012. Record the pressure and volume change data inside the elastic reservoir and establish a pressure-volume (PV) characterization model; S013. Calculate the compliance coefficient C of the elastic reservoir based on the pressure-volume characterization model, and identify the reservoir type based on the slope of the nonlinear change of the compliance coefficient. The compliance coefficient C is essentially the slope of the PV curve. C= in, The change in the volume of the elastic storage cavity is measured by capturing the cavity deformation in real time using a visual volume sensor, and then calculating the dynamic volume signal using image algorithms. The change in internal pressure of the elastic reservoir is recorded by an internal pressure sensor, showing the difference in static pressure before and after pulse injection. This ensures that the data directly reflects the actual hydrostatic pressure response inside the reservoir.

[0026] and These represent the intracavitary static pressure before and after injection.

[0027] Different elastic reservoirs exhibit different patterns of compliance coefficient variation. By pre-setting basic comparison data based on the elastic reservoirs being studied and tested, the type of reservoir being tested can be directly determined based on the data comparison during the study and testing process, thus providing a data basis for the subsequent selection of fluid injection modes.

[0028] In embodiments of the present invention, the elastic reservoir includes the bladder cavity, ureteral cavity, joint cavity, and abdominal cavity, and may be increased or decreased accordingly based on research and testing needs.

[0029] like Figure 4 As shown, during reservoir type identification, pulse injection is performed through the control medium regulation subsystem, and the pressure response is monitored in real time. The calculated compliance coefficient C and PV curve characteristics are then compared with a preset database. Bladder cavity identification: If the C value is in the preset high compliance level range and the PV curve shows a linear and gentle upward trend within the tolerance area, it is determined to be a bladder cavity pattern; Ureteral lumen identification: If the C value is in the preset low compliance level range, and the PV curve shows an exponential increase in slope with a rapid increase in volume injection, it is determined to be a ureteral lumen pattern. Joint cavity identification: If the C value is in the extremely low compliance level range and the PV curve shows a near-vertical instantaneous pressure response characteristic, it is determined to be a joint cavity pattern; Peritoneal cavity identification: If the C value is in the range of extremely high compliance level, but the slope of the curve turns significantly upward after the injection of a preset large volume of medium, it is determined to be the peritoneal cavity mode.

[0030] Table 1 shows the classification of compliance coefficient C for each type of storage cavity in this embodiment of the invention.

[0031] Table 1. Compliance Level Classification Table Furthermore, in step S01 of the present invention, the pathological state of the elastic reservoir can be simulated and identified based on the set reservoir type identification data and the PV curve during the fluid injection process. For example, if the compliance is significantly lower than the standard value or a nonlinear mutation occurs, the system determines it to be a pathological adhesion or stenosis model and automatically narrows the safe pressure threshold range for subsequent tests, for example, by reducing it according to a fixed ratio.

[0032] S02. Switch to the corresponding fluid injection mode based on the reservoir type; each reservoir type's fluid injection mode includes a limit detection sub-mode and a steady-state simulation sub-mode. Corresponding to the elastic reservoir type of the present invention, the fluid injection modes are divided into cystoscopy mode, ureteroscopy mode, arthroscopy mode and laparoscopy mode.

[0033] The steady-state simulation sub-mode includes a steady-state maintenance phase and a dynamic active intervention phase; During the steady-state maintenance phase, a certain characteristic of the elastic reservoir is selected as the main control variable based on its characteristics. During fluid injection, the fluid injection process is controlled by this main control variable, and the main control variable is kept stable by controlling the fluid input and suction rate. During the dynamic active intervention phase, debris is introduced into the fluid state changes within the elastic reservoir during the simulated surgical procedure. By altering the fluid flow parameters, the debris within the elastic reservoir is cleared. A correlation model is established by combining the fluid physical bearing capacity limit data of the elastic reservoir with the debris removal rate. Iterative testing is then conducted to determine the optimal combination of fluid dynamic parameters under the current reservoir characteristics.

[0034] During the dynamic active intervention phase, images of the reservoir cavity are acquired using an interventional camera module within the elastic reservoir cavity, and the visual field blur index is calculated based on the images. And determine the debris removal rate, ,in, Image coordinates The pixel grayscale value at that location, This represents the average grayscale value of the current image. The squared term in the exponential formula is used to amplify the grayscale difference and improve the recognition sensitivity in complex and murky environments.

[0035] Specifically as follows: In ureteroscopy mode: The ureter and renal calyces are tiny tubular cavities with a volume of only 5-10 ml, making them extremely sensitive to pressure fluctuations. Even slightly elevated pressure can cause fluid to flow back into the bloodstream, potentially leading to hydronephrosis or infection. Therefore, a pressure threshold shearing strategy is implemented, using intracavitary pressure as the primary control variable and setting a maximum pressure cutoff threshold. When the real-time pressure approaches... When the set safety margin is reached, the decay is proportional. The suction module is controlled to maintain a small, continuous negative pressure of -5 to -15 mmHg to maintain a low Reynolds number laminar flow field of view.

[0036] In an embodiment of the present invention, during the steady-state maintenance phase: a maximum pressure cutoff threshold (30cmH2O, approximately 22mmHg) is set to prioritize ensuring that the pressure inside the cavity is below the cutoff threshold; during the dynamic active intervention phase: the active suction output module is controlled to generate a small negative pressure of -5 to -15mmHg, while the medium input module is controlled to inject the medium at a low flow rate of 10-30mL / min to establish a unidirectional laminar flow channel to remove debris. In cystoscopy mode: The bladder in the urinary system is a large-volume, highly compliant cavity that needs to be protected against rupture; a volume-priority strategy is implemented, using real-time volume signals as the primary control variable for dynamic adjustment. To maintain the cavity volume fluctuation within the target value Within the range; Input flow rate for the fluid. This represents the fluid suction flow rate.

[0037] The real-time volume signal fed back by the visual volume sensor is used as the first priority feedback variable. The central control and analysis unit uses the real-time volume signal fed back by the visual volume sensor as the first priority feedback variable; adjusts the power of the active medium suction output module to maintain the volume of the simulated elastic reservoir assembly within the preset tolerance range (±10%) of the target filling value.

[0038] In an embodiment of the present invention: Steady-state maintenance phase: Using the visual volume signal as the main feedback variable, the volume is maintained within ±10% of the target value; Dynamic active intervention phase: Remove input flow rate restrictions and inject the medium at a high flow rate of 300-500 mL / min. At the same time, use a feedforward control algorithm to adjust the suction pump to offset the volume increase and ensure that the volume fluctuation is <20 mL.

[0039] In arthroscopic mode: The joint cavity is filled with bone and cartilage fragments, requiring high-flow irrigation for visualization. However, the joint capsule is rigid, making it prone to fluid extravasation and limb swelling. A preset high-flow-rate constant fluid medium is output to ensure effective debris removal. The joint cavity is a small, closed space with a rigid (semi-rigid) structure, requiring high-flow irrigation with saline to remove debris; excessive pressure can lead to fluid extravasation. The system controls the input pump to output a constant high flow rate to ensure powerful irrigation; simultaneously, the suction pump speed is dynamically adjusted based on the intracavitary pressure to establish a dynamic balance of "high perfusion - high suction," preventing pressure from exceeding the joint capsule's limits (e.g., 60 mmHg).

[0040] Specifically, during the steady-state maintenance phase: a constant high flow rate of 300-1500 mL / min is maintained to keep the joint cavity full; Dynamic active intervention stage: Debris is flushed with a large flow of fluid. For hard-to-clean dead corner areas, the input pump and suction pump are controlled to generate pulse waveforms with a 180° phase difference to create controlled turbulence in the joint cavity. The kinetic energy of the fluid inlet pulse is used to flush and suspend the debris in the hidden places. Then, the opposite phase suction pulse is used to quickly remove it. The cleaning efficiency is greatly improved without increasing the average pressure in the joint.

[0041] In laparoscopic mode: The abdominal cavity is a large-volume elastic cavity, typically using CO2 gas, requiring a low and constant pressure, with relatively low flow rate requirements. The system uses pneumoperitoneum pressure as the sole core target and employs a PWM pulse inflation algorithm. When air leakage (pressure drop) is detected due to the entry or exit of surgical instruments, gas is rapidly replenished; when the pressure exceeds the limit, inflation is stopped and regulated by a passive pressure relief valve. A constant pressure compensation strategy is required, switching to a gas medium, with pneumoperitoneum pressure as a closed-loop feedback variable. When the pressure drop rate exceeds a preset threshold, stepwise pressure compensation is performed at the maximum set flow rate.

[0042] The specific embodiments of the present invention are as follows: Steady-state maintenance phase: Implement a constant pressure maintenance strategy, using real-time air pressure signals as the core feedback variable to maintain the pneumoperitoneum pressure within the preset range of 12-15 mmHg; Dynamic active intervention phase: When the pressure drop rate is detected to exceed 5 mmHg / s, the input pump is immediately triggered to compensate at a maximum flow rate of 40 L / min, and the flow rate is reduced in advance based on the pressure recovery slope to prevent overcharging; Extreme destructive testing phase: Simulate a high-pressure pneumoperitoneum environment, continuously increase the air pressure until it reaches 30-45 mmHg, and determine the extreme pneumoperitoneum pressure that would cause abnormal respiratory dynamics or seal failure.

[0043] S03. In the limit detection sub-mode, the rate of change of the internal pressure, surface tension and visual volume data of the elastic reservoir is detected in real time to obtain the fluid physical bearing limit data of the corresponding elastic reservoir.

[0044] like Figure 5 As shown, in the limit detection sub-mode, the present invention uses a stepped gradient pressurization strategy to inject fluid, continuously increasing the output pressure or volume, and judging whether the state of the reservoir triggers the melting hard index. For example, when the geometry of the elastic reservoir changes discontinuously, the pressure drops instantaneously, or the surface tension changes abruptly, the preceding peak data at that moment is recorded, and the preceding peak data is used as the fluid physical bearing limit data of the corresponding elastic reservoir.

[0045] The testing process for various types of elastic reservoirs in this embodiment of the invention is as follows: During ureteroscopy, the input pressure is increased linearly at a rate of 0.5 cmH2O / s, and the pressure decay curve is monitored simultaneously. When a non-linear decrease in pressure maintenance ability is detected, it is identified as a mucosal leakage point or micro-tear point, and the pressure value is recorded.

[0046] During cystoscopy, fluid is continuously injected until physical rupture occurs. The nonlinear inflection point of surface tension and volume is monitored to determine the ultimate tensile strength and maximum safe capacity of the bladder wall.

[0047] During arthroscopic testing, the aspiration outlet is sealed, and a step-by-step pressurization method is used to monitor the linear relationship between pressure and injection volume. When the relationship curve shows hysteresis characteristics, it is determined to be the critical pressure point where gravity extravasation of fluid occurs.

[0048] During laparoscopic testing, gas is injected to simulate a high-pressure pneumoperitoneum environment. The gas pressure is continuously increased until it reaches 30-45 mmHg, and the ultimate pneumoperitoneum pressure that would lead to abnormal respiratory dynamics or seal failure is measured.

[0049] S04. In the steady-state simulation sub-mode, the fluid physical bearing limit data of step S03 is used as the boundary to set a test safety red line. During each test, when the elastic reservoir data approaches the set test safety red line, the protection mechanism is triggered to protect the reservoir, and finally the optimal combination of fluid dynamic parameters under the corresponding elastic reservoir is obtained.

[0050] The optimal parameter combination is achieved through the following objective function F The calculation shows that: in, For based on Average visual acuity calculated using the index; The debris removal rate is determined by using image recognition from an intervening camera within the elastic storage cavity. Particle tracking analysis is employed to statistically analyze the residual quantity or area ratio of pre-set standard debris within the simulated storage cavity, thereby calculating the mass or volume of debris pumped out per unit time. This is the debris removal rate. The standard deviation of the static pressure within the cavity represents the fluctuation or instability of the pressure within the reservoir. During fluid circulation, excessive pressure fluctuations (high standard deviation) increase the risk of tissue damage. Therefore, in the objective function, this term is preceded by a negative sign (−γ), meaning that increased fluctuations will lower the overall score. The system aims to maintain stable pressure while achieving efficient cleaning.

[0051] , , These are preset coefficients for weighting different scenarios. For improved visual clarity, For debris removal rate, These coefficients, representing the standard deviation of stress, are used to prioritize different scenarios.

[0052] Arthroscopic mode: weighted order: β>α>γ The joint cavity is a rigid structure with the lowest compliance and high pressure tolerance. The core clinical need is high-flow irrigation to remove bone and tissue debris generated during surgery. β is set with the highest weight because efficient cleaning is the primary goal in this scenario. α is secondary, used to help observe the cleaning effect. γ is relatively the lowest weight because the joint structure is rigid and insensitive to pressure fluctuations.

[0053] Ureteroscopy mode: weighted order: γ>α>β The ureter has low compliance and a small volume, making it extremely sensitive to pressure. γ is set as the highest weight. The core objective is to prevent renal pelvis pressure from exceeding the safe threshold and to avoid urine reflux causing injury. α is crucial for the procedure because the ureter is narrow and easily obstructed; a clear view is essential. β is performed while maintaining pressure and has a relatively lower priority.

[0054] Cystoscopy mode: weighted order: α≈γ>β The bladder is a highly compliant organ and its volume needs to be maintained within a specific range (e.g., 500ml ± 10%) to ensure operating space and prevent rupture. Both α and γ have high weights, and a stable volume means a stable space, which is a prerequisite for maintaining a field of vision. β is set to a medium weight, as the bladder has a large space and obstructions are relatively easy to handle. Cleaning needs are ranked after volume control.

[0055] Laparoscopic mode: weighted order: γ>α≫β The abdominal cavity has extremely high compliance, primarily maintained by inflating (CO2) to create space. γ is assigned the highest weight. Maintaining stable pneumoperitoneum pressure is crucial for laparoscopic surgery; pressure fluctuations can cause abdominal collapse, affecting the procedure. α is essential for the three-dimensional operating space of large body cavities. β has a very low or even negligible weight because the gaseous medium does not have a direct cleaning function; debris removal is usually accomplished through additional flushing and suction devices, rather than relying on this pressure control module.

[0056] In the dynamic active intervention phase of this invention, if the intervention camera module detects that the proportion of particle pixels in the image within the elastic storage cavity exceeds a preset threshold or the contrast decreases, it automatically triggers an isochoric replacement mode to clean up debris. In the isochoric replacement mode, the fluid injection input pump and the suction pump satisfy the fluid balance equation: ,in, The volumetric error compensation based on real-time feedback from the cavity can be calculated using the compliance coefficient identified in step S1. The system monitors the difference between the actual pressure inside the cavity and the set target pressure in real time. compliance coefficient C, For input traffic, For suction flow rate.

[0057] This invention calculates the visual blur index in real time under isochoric permutation mode. rate of change If the equal-capacity replacement mode is continuously executed for a preset duration, tending to zero and If the flow rate is still higher than the cleaning threshold, the constant flow rate of fluid input and suction is switched to frequency-modulated pulse flow. The input pump and suction pump are controlled to generate pulse waveforms with a phase difference of 180° to produce controlled turbulence. The excitation force generated by the controlled turbulence suspends the settled debris and discharges it through suction.

[0058] like Figures 1-3 As shown, the present invention also discloses a multi-scenario universal elastic reservoir fluid dynamics research and testing system for implementing the above-mentioned research and testing methods. The system includes a medium control subsystem 100, configured to provide and adjust the dynamic parameters of the fluid medium. The medium control subsystem includes a fluid medium switching unit 110, a medium input module 120, and a medium active suction output module 130. The fluid medium switching unit 110 is configured to connect to an external liquid source and a gas source, and switches between liquid medium and gas medium output according to control commands. A simulated elastic reservoir assembly 200 is connected to the fluid loop of the media control subsystem 100. The simulated elastic reservoir assembly 200 includes a simulated elastic reservoir and a universal adapter interface 210. The universal adapter interface 210 is configured to be detachably connected to the simulated elastic reservoir for fluid injection. The media is transported by a fluid media input pump 121, and the fluid is drawn out of the elastic reservoir by a fluid media suction pump 131. A waste liquid / waste gas collection box 140 is connected to the outlet end of the fluid media suction pump 131 for collecting and treating waste media.

[0059] The simulated elastic reservoir includes an artificially synthesized biomimetic cavity module and an ex vivo biological tissue specimen.

[0060] The artificially synthesized biomimetic cavity modules include a highly elastic sac module (simulating the bladder), a low-compliance micro-module (simulating the ureter), a rigid constraint module (joint cavity), and an airtight body cavity module (abdominal cavity). These modules are mainly used for the initial iteration of algorithms, large-scale parameter scanning, and repeatability verification, and have the advantages of low cost and good consistency.

[0061] Ex vivo biological tissue specimens include pretreated ex vivo animal (such as pig) bladders, kidneys, ureters, or joint capsules. Through dilatation cannulation and sealing ligation, biological tissues can be directly connected to fluid medium circuits for simulation testing.

[0062] During the research and testing process, each simulated elastic reservoir can be placed in a preset environmental maintenance unit. The environmental maintenance unit is equipped with a constant temperature physiological fluid to simulate the actual environment of the reservoir and conduct high-fidelity testing.

[0063] The multi-dimensional monitoring subsystem 300 is configured to collect fluid dynamic parameters and physical state parameters in the elastic storage cavity in real time, including a fluid parameter monitoring unit 310 set on the fluid medium path and a cavity state monitoring unit 320 set on the elastic storage cavity. The central control and analysis unit 400 is electrically connected to the media control subsystem 100 and the multidimensional monitoring system 300, respectively. The central control and analysis unit 400 is configured to dynamically adjust the operating parameters of the media control subsystem 100 based on the signals fed back by the multidimensional monitoring system 300.

[0064] The fluid parameter monitoring unit 310 of the present invention includes: Flow sensors 311 are respectively installed on the output pipeline of the medium input module 120 and the input pipeline of the medium active suction output module 130, and are used to monitor the input flow rate and suction flow rate of the fluid medium in real time. The pipeline pressure sensor 312 is installed on the fluid transmission path between the fluid medium switching unit 110 and the simulated elastic storage cavity assembly 200, and is used to monitor the real-time fluid dynamic pressure in the pipeline. The cavity status monitoring unit 320 includes: Tension sensor 321 is attached to the surface of the simulated elastic cavity assembly to monitor the surface tension signal of the cavity. A visual volume sensor 322 is disposed outside the simulated elastic storage cavity assembly to capture cavity deformation in real time and calculate dynamic volume change signals in combination with image algorithms; An internal pressure sensor 323 has a probe that extends into the interior of the simulated elastic reservoir assembly to monitor the real-time hydrostatic pressure signal within the cavity. An intervening camera module 324 is placed inside the simulated elastic reservoir assembly to acquire images within the cavity to assess the clarity of the field of view and the efficiency of debris removal.

[0065] In addition, based on the need for dynamic active intervention testing, a "simulated turbidity / bleeding scenario test" has been added. This involves manually injecting dye or particles into the cavity through a tubing. This step can be performed manually or by setting up automatic equipment. The test aims to determine whether the system can quickly replace the water in the elastic reservoir without rupturing the cavity (volume / pressure not exceeding the limit) through the "equal volume replacement" logic, thereby maintaining the clarity of the field of vision in the elastic reservoir during the operation and providing operational data benchmarks for actual operation.

[0066] During the "simulated turbidity / bleeding scenario test," the central control and analysis unit 400 is equipped with a visual efficacy evaluation module 410, configured to process the images acquired by the interventional camera module 324 in real time; during the dynamic active intervention phase, the visual efficacy evaluation module 410 calculates the visual field blur index. The indicators determine the clarity of vision, among which , Image coordinates The pixel grayscale value at that location, The average grayscale value of the current image is used as the reference value. Simultaneously, the visual performance evaluation module 410 calculates the debris removal rate using a particle tracking algorithm and transmits this indicator to the central control and analysis unit 400 in real time. This is used to trigger the isocapacitive permutation mode or frequency modulation pulse stream during the dynamic active intervention phase. The central control and analysis unit 400 has a built-in objective function. F To search for the optimal combination of parameters, F Different weighting coefficients are preset for different modes. , The optimal combination of hydrodynamic parameters suitable for the corresponding elastic reservoir was obtained.

[0067] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A multi-scenario universal elastic reservoir fluid dynamics research and testing method, characterized in that, Including the following steps: S01. Identify reservoir type based on the compliance coefficient of elastic reservoir; S02. Switch to the corresponding fluid injection mode based on the reservoir type; each reservoir type's fluid injection mode includes a limit detection sub-mode and a steady-state simulation sub-mode. S03. In the limit detection sub-mode, the rate of change of the internal pressure, surface tension and visual volume data of the elastic storage cavity is detected in real time to obtain the fluid physical bearing limit data of the corresponding elastic storage cavity. S04. In the steady-state simulation sub-mode, the fluid physical bearing limit data of step S03 is used as the boundary to set a test safety red line. During each test, when the elastic reservoir data approaches the set test safety red line, the protection mechanism is triggered to protect the reservoir, and finally the optimal combination of fluid dynamic parameters under the corresponding elastic reservoir is obtained.

2. The multi-scenario universal elastic reservoir fluid dynamics research and testing method according to claim 1, characterized in that, The elastic reservoir includes the bladder cavity, ureteral cavity, joint cavity and abdominal cavity, and the corresponding fluid injection modes include cystoscopy mode, ureteroscopy mode, arthroscopy mode and laparoscopy mode; In step S01, the reservoir type is identified based on the numerical range and nonlinear change slope of the compliance coefficient C, wherein, for peritoneal cavity: C > 150 mL / cm O; Bladder cavity: 30 <C≤150mL / cm O; Ureteral lumen: 1 <C≤20mL / cm O; Joint cavity: C≤1mL / cm O.

3. The multi-scenario universal elastic reservoir fluid dynamics research and testing method according to claim 1, characterized in that, In step S01, the process of identifying the reservoir type includes: S011. Inject pulsed fluid into the elastic reservoir; S012. Record the pressure and volume change data inside the elastic storage cavity and establish a pressure-volume characterization model; S013. Calculate the compliance coefficient of the elastic reservoir based on the pressure-volume characterization model, and identify the reservoir type based on the slope of the nonlinear change of the compliance coefficient.

4. The multi-scenario universal elastic reservoir fluid dynamics research and testing method according to claim 1, characterized in that, The steady-state simulation sub-mode includes a steady-state maintenance phase and a dynamic active intervention phase; During the steady-state maintenance phase, a certain characteristic of the elastic reservoir is selected as the main control variable based on its characteristics. During fluid injection, the fluid injection process is controlled by this main control variable, and the main control variable is kept stable by controlling the fluid input and suction rate. During the dynamic active intervention phase, debris is introduced into the fluid state changes within the elastic reservoir during the simulated surgical procedure. By altering the fluid flow parameters, the debris within the elastic reservoir is cleared. A correlation model is established by combining the fluid physical bearing capacity limit data of the elastic reservoir with the debris removal rate. Iterative testing is then conducted to determine the optimal combination of fluid dynamic parameters under the current reservoir characteristics.

5. The multi-scenario universal elastic reservoir fluid dynamics research and testing method according to claim 4, characterized in that, During the dynamic active intervention phase, images of the reservoir cavity are acquired using an interventional camera module within the elastic reservoir cavity, and the visual field blur index is calculated based on the images. And determine the debris removal rate, ,in, Image coordinates The pixel grayscale value at that location, This represents the average grayscale value of the current image.

6. The multi-scenario universal elastic reservoir fluid dynamics research and testing method according to claim 5, characterized in that, During the dynamic active intervention phase, if the intervention camera module detects that the proportion of particle pixels in the image within the elastic storage cavity exceeds a preset threshold or the contrast decreases, it automatically triggers the isochoric replacement mode to clean up debris. In the isochoric replacement mode, the fluid injection input pump and the suction pump satisfy the fluid balance equation: ,in, This is the volumetric error compensation amount based on real-time feedback from the cavity. For input traffic, For suction flow rate.

7. The multi-scenario universal elastic reservoir fluid dynamics research and testing method according to claim 6, characterized in that, In the isochoric permutation mode, the visual blur index is calculated in real time. rate of change If the equal-capacity replacement mode is continuously executed for a preset duration, tending to zero and If the flow rate is still higher than the cleaning threshold, the constant flow rate of fluid input and suction is switched to frequency-modulated pulse flow. The input pump and suction pump are controlled to generate pulse waveforms with a phase difference of 180° to produce controlled turbulence. The excitation force generated by the controlled turbulence suspends the settled debris and discharges it through suction.

8. The multi-scenario universal elastic reservoir fluid dynamics research and testing method according to claim 1, characterized in that, In the limit detection sub-mode, a step-by-step strategy is used for fluid injection, continuously increasing the output pressure or volume. When a discontinuous change in the cavity geometry of the elastic reservoir is detected, or a sudden drop in pressure or a sudden change in surface tension is detected, the preceding peak data at that moment is recorded, and the preceding peak data is used as the corresponding fluid physical bearing limit data of the elastic reservoir.

9. A multi-scenario universal elastic reservoir fluid dynamics research and testing system, using the research and testing method described in any one of claims 1-8, characterized in that, The system includes a media control subsystem (100) configured to provide and regulate the dynamic parameters of the fluid medium. The media control subsystem includes a fluid medium switching unit (110), a media input module (120), and a media active suction output module (130). The fluid medium switching unit (110) is configured to connect to an external liquid source and a gas source, and to switch between liquid medium and gas medium output according to control commands. A simulated elastic reservoir assembly (200) is connected to the fluid loop of the medium control subsystem (100). The simulated elastic reservoir assembly (200) includes a simulated elastic reservoir and a universal adapter interface (210). The universal adapter interface (210) is configured to detachably connect to the simulated elastic reservoir for fluid injection. The multi-dimensional monitoring subsystem (300) is configured to collect fluid dynamic parameters and physical state parameters in the elastic storage cavity in real time, including a fluid parameter monitoring unit (310) set on the fluid medium path and a cavity state monitoring unit (320) set on the elastic storage cavity. The central control and analysis unit (400) is electrically connected to the media control subsystem (100) and the multidimensional monitoring system (300), respectively. The central control and analysis unit (400) is configured to dynamically adjust the operating parameters of the media control subsystem (100) according to the signals fed back by the multidimensional monitoring system (300). The central control and analysis unit (400) has a built-in objective function. F To search for the optimal combination of parameters, F Different weighting coefficients are preset for different modes. , ,in, For based on Average visual acuity calculated using the index; Debris removal rate This represents the standard deviation of the intracavitary static pressure.

10. The multi-scenario universal elastic reservoir fluid dynamics research and testing system according to claim 9, characterized in that, The fluid parameter monitoring unit (310) includes: A flow sensor (311) is respectively installed on the output pipeline of the medium input module (120) and the input pipeline of the medium active suction output module (130) for real-time monitoring of the input flow rate and suction flow rate of the fluid medium. A pipeline pressure sensor (312) is installed on the fluid transmission path between the fluid medium switching unit (110) and the simulated elastic reservoir assembly (200) to monitor the real-time fluid dynamic pressure in the pipeline; The cavity status monitoring unit (320) includes: Tension sensor (321) is attached to the surface of the simulated elastic cavity assembly to monitor the surface tension signal of the cavity; A visual volume sensor (322) is disposed outside the simulated elastic cavity assembly for capturing cavity deformation in real time and calculating dynamic volume change signals in combination with image algorithms; An internal pressure sensor (323) with a probe extending into the simulated elastic reservoir assembly is used to monitor the real-time hydrostatic pressure signal within the cavity; An intervening camera module (324) is placed inside the simulated elastic storage cavity assembly to acquire images inside the cavity to evaluate the clarity of the field of view and the cleaning efficiency of debris. The central control and analysis unit (400) is equipped with a visual performance evaluation module (410).

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