Bronchial stenosis degree evaluation method and system

Abstract

The invention discloses a bronchial stenosis degree evaluation method and system, and belongs to the technical field of medical imaging. The method comprises the following steps: constructing a three-dimensional lung bronchial model in combination with lung CT image data; under the three-dimensional lung bronchial model, a fluid dynamic model of lung tissue is established based on an SPH method, fluid flowing before and after an operation is simulated, and fluid dynamic and tissue mechanical behaviors in the operation process are simulated by simulating interaction between airflow and the lung tissue; on the basis of fluid dynamics and tissue mechanical behaviors in the simulated operation process, a physical evaluation index is constructed to evaluate the tracheal stenosis degree. The method is a lung bronchial preoperative planning scheme simulation method based on smoothing particle fluid dynamics, and can provide intuitive preoperative planning and operation simulation for surgeons.

Description

Technical Field

[0001] The present application proposes a method and system for evaluating the degree of bronchial stenosis, which belongs to the technical field of medical imaging. Background Art

[0002] Bronchial stenosis is a common respiratory disease characterized by partial or complete obstruction of the airway lumen. Traditional methods for assessing the degree of bronchial stenosis mainly rely on medical imaging examinations (such as CT, MRI) and airway function tests. However, these methods can usually only provide static geometric information and have certain limitations in evaluating the impact of airway stenosis on airflow dynamics and the dynamic changes in airway function before and after surgery.

[0003] SPH (Smooth Particle Hydrodynamics) is a meshless Lagrangian numerical method that has significant advantages in dealing with complex problems such as large deformation and free surface flow. In recent years, the SPH method has been widely used in the field of biomedical engineering, such as simulating blood flow and tissue deformation. By numerically simulating bronchial stenosis using the SPH method, detailed information such as the velocity field and pressure distribution of the airflow in the narrow airway can be obtained, providing a new idea for quantitatively evaluating the degree of airway stenosis.

[0004] At present, some studies have tried to use computational fluid dynamics (CFD) methods to simulate respiratory airflow, but this method usually uses the finite volume method or finite element method to mesh the airway and then solve the Navier-Stokes equations. However, for complex airway geometry and diseased states, mesh generation and quality control is a difficult problem. There are still certain challenges in simulating airflow under complex airway anatomical structures and diseased states.

[0005] Finite element analysis (FEA) is also a technology commonly used to simulate the mechanical behavior of tissues. It simulates the stress and strain distribution of tissues by dividing the tissues into a finite number of elements and nodes. However, FEA has limitations in dealing with fluid dynamics problems, especially in simulating complex fluid-structure interaction problems in lung bronchial surgery. Its computational efficiency is low and it is difficult to accurately capture rapidly changing dynamic processes.

[0006] A hybrid method combining FEA and CFD attempts to simulate the mechanical behavior of tissues through FEA and fluid dynamics using CFD. However, this hybrid method has several problems in practical applications: first, the coupling calculation of FEA and CFD is very complex and requires a lot of computing resources; second, the mesh systems of the two methods do not match, making data exchange and boundary condition processing difficult; finally, this hybrid method is difficult to update in real time and cannot provide dynamic feedback during surgery. Summary of the invention

[0007] In view of the limitations of the existing technology, the present application proposes a method and system for evaluating the degree of bronchial stenosis. The method is a simulation method for preoperative planning of pulmonary bronchial surgery based on smoothed particle fluid dynamics. By simulating the fluid flow before and after the operation, the degree of bronchial stenosis and the surgical effect can be more accurately evaluated, and surgeons can be provided with intuitive preoperative planning and surgical simulation.

[0008] In order to solve the above technical problems, the technical solution adopted in this application is: In a first aspect, the present application provides a method for assessing the degree of bronchial stenosis, comprising: Combined with lung CT image data, a three-dimensional lung bronchial model was constructed; Based on the SPH method, a fluid dynamics model of lung tissue was established under the three-dimensional lung bronchial model to simulate the fluid flow before and after surgery. By simulating the interaction between airflow and lung tissue, the fluid dynamics and tissue mechanical behaviors during surgery were simulated. Based on the fluid dynamics and tissue mechanical behaviors during simulated surgery, a physics-based evaluation index was constructed to assess the degree of tracheal stenosis.

[0009] As a further improvement of the present application, the SPH method includes: under a three-dimensional lung bronchial model, dividing the airflow to be simulated into discrete particles, estimating the physical quantity of each particle through a smooth kernel function, and making it satisfy the overall physical laws, and then calculating the physical quantity of each particle in each frame through continuous iteration, so that each particle can perform corresponding movements.

[0010] As a further improvement of the present application, the fluid dynamics model of lung tissue is established based on the SPH method under the three-dimensional lung bronchial model, including: In the three-dimensional lung bronchial model, the airflow is set as the initial parameters of the particle radius, boundary conditions, etc. Calculate the density and pressure of the airflow as particles using a smooth kernel function; Calculate the pressure gradient force, viscosity force and gravity force on each particle; Update the particle's velocity and position based on the calculated force; Couple the airflow with the air pipe to calculate and solve the collision feedback force; Establish a fluid dynamics model of lung tissue.

[0011] As a further improvement of the present application, the fluid dynamics model of lung tissue is established based on the SPH method to simulate the fluid flow before and after surgery, including: For an air particle , Expressed in a general form:

[0012] in , , Particles , Location, For adjacent particles Quality, For adjacent particles The density of The required particle The physical quantity, is the smooth kernel function; The Poly6 kernel function is used as the smooth kernel function:

[0013] Then, based on the smooth kernel function, the cumulative functions related to the density, pressure, and velocity of a certain point in the fluid are deduced one by one, and then the acceleration is derived to simulate the movement trend of the fluid. The force acting on a particle is expressed by the following formula:

[0014] This solves for the particle's acceleration:

[0015] In the formula, is the acceleration of particle i, is the other external force on particle i, and Represents the pressure and viscosity of the surrounding particles on particle i.

[0016] As a further improvement of the present application, the method of simulating the interaction between airflow and lung tissue to simulate the fluid dynamics and tissue mechanical behavior during surgery includes: The solid boundary is modeled by boundary particles and interacts with fluid particles. The coupling between the boundary and the airflow is divided into two forces, one is the pressure between the two, and the other is the friction between the two:

[0017] in is the net force on the particle, represents the pressure on the particle, represents the friction force on the particle; the pressure is expressed as:

[0018] The friction force on the particle is expressed as:

[0019] in represents the viscosity coefficient. Substituting the above two force formulas into it, we get the formula for the interaction force between fluid particles and solid boundaries:

[0020] Through the interaction force between fluid particles and solid boundaries, the movement trend of the fluid is obtained, and the relevant equations are solved frame by frame to simulate the entire process and solve the collision feedback force.

[0021] As a further improvement of the present application, the fluid dynamics model based on lung tissue is used to construct a physics-based evaluation index to evaluate the degree of tracheal stenosis, including: The Monte Carlo method is used to estimate the overall pressure value upstream and downstream of the narrow area, that is, and ; The calculation process is expressed as:

[0022] in, is the total number of particles at the upstream or downstream boundary, is the number of randomly sampled particles, represents the modulus of the total force on the particle; Based on the simulated pressure ratio between the front and rear ends of the stenosis, a physics-based evaluation index is constructed:

[0023] in, is the pressure of the tracheal wall upstream of the stenosis, It is the pressure of the tracheal wall downstream of the stenosis.

[0024] In a second aspect, the present application provides a system for assessing the degree of bronchial stenosis, comprising: A model building module is used to build a three-dimensional lung bronchial model by combining lung CT image data; The mechanical simulation module is used to establish a fluid dynamics model of lung tissue based on the SPH method under a three-dimensional lung bronchial model, simulate the fluid flow before and after surgery, and simulate the fluid dynamics and tissue mechanical behavior during surgery by simulating the interaction between airflow and lung tissue; The indicator building module is used to construct a physics-based evaluation indicator to assess the degree of tracheal stenosis based on the fluid dynamics and tissue mechanical behaviors during simulated surgery.

[0025] In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the method for assessing the degree of bronchial stenosis is implemented when the processor executes the computer program.

[0026] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for assessing the degree of bronchial stenosis is implemented.

[0027] In a fifth aspect, the present application provides a computer program product, wherein the computer program product comprises computer instructions, wherein the computer instructions instruct a computer to execute the method for assessing the degree of bronchial stenosis.

[0028] The beneficial effects of this application compared to the prior art are: The method for evaluating the degree of bronchial stenosis provided in this application, SPH, is a gridless calculation method that is particularly suitable for simulating fluid dynamics and fluid-structure interaction problems. Compared with traditional FEA and CFD, SPH can handle free surface flows and complex boundary conditions more naturally while maintaining high computational efficiency. This application takes advantage of the SPH method, combines lung CT image data, constructs a three-dimensional lung bronchial model, and simulates the fluid dynamics and tissue mechanical behavior during surgery, providing surgeons with intuitive preoperative planning and surgical simulation, thereby improving the success rate and safety of surgery. Based on the SPH method, combined with lung CT image data, a three-dimensional lung bronchial model is constructed, and the fluid dynamics and tissue mechanical behavior during surgery are simulated. By simulating the interaction between airflow and lung tissue, a new physics-based evaluation index is constructed to evaluate the degree of tracheal stenosis before and after stent implantation, providing surgeons with intuitive preoperative planning and surgical simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following introduction is made to the drawings of the embodiments of the present application or the related technical solutions in the prior art. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 A flow chart of a method for assessing the degree of bronchial stenosis provided in this application; Figure 2 A simulation framework diagram of the preoperative planning scheme for pulmonary bronchial tuberculosis proposed for this application; Figure 3 Model a schematic diagram of a complete bronchus; Figure 4 This is a simplified schematic diagram of the model; Figure 5 Flowchart of the SPH algorithm used in this application; Figure 6 This is a schematic diagram of the tracheal stenosis site; Figure 7 Schematic diagram of particle subjected to boundary pressure; Figure 8 A schematic diagram of the SPH method simulation proposed in this application; Fig. 9 It is a schematic diagram of the simulation process; Fig.10 A device for assessing the degree of bronchial stenosis provided in this application; Fig.11 A schematic diagram of an electronic device provided for this application. DETAILED DESCRIPTION

[0031] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and are not to be construed as limitations on the present application. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0032] In the description of this application, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in this application based on the specific content of the technical solution.

[0033] Explanation of relevant terms: SPH (Smoothed Particle Hydrodynamics) is a meshless Lagrangian method for simulating continuous media dynamics, such as fluid flow and solid mechanics problems. It simulates fluid behavior by simulating the fluid as a series of particles, each with properties such as mass, velocity, and pressure, and by the interaction between particles.

[0034] Lung CT imaging is a medical imaging technology used to observe the structure and function of the lungs. It can provide detailed images of the lungs and help doctors diagnose various lung diseases such as pneumonia, tuberculosis, lung cancer, etc.

[0035] CFD (Computational Fluid Dynamics) is the abbreviation of computational fluid dynamics. It is a method of predicting the flow of physical fluids by mathematical calculations and using computers to solve the governing equations. CFD technology is widely used in engineering and scientific fields such as aerospace, automotive industry, energy production, etc. to optimize design and improve performance.

[0036] FEA (Finite Element Analysis) is an engineering numerical analysis method used to solve mechanical problems of complex structures and objects. It divides a complex structure into many simple small elements (finite elements) and then performs numerical calculations on these elements to approximate the mechanical behavior of the structure. The basic principles and steps of finite element analysis include structural discretization, establishing nodes and elements, defining material properties and constraints, establishing finite element models, applying loads and boundary conditions, solving mathematical models, and analyzing results.

[0037] The Spiky kernel is a kernel function used in Smoothed Particle Hydrodynamics (SPH) that has special properties when dealing with particle interactions. In the SPH method, kernel functions are used to approximate the interactions between particles, especially for calculating physical quantities such as particle density and pressure. The Spiky kernel function is designed because it can remain positive when particles are very close, which helps avoid instabilities when calculating pressure gradients.

[0038] In bronchial stenosis surgery, the evaluation of the degree of tracheal stenosis is very important for the evaluation of the postoperative effect of tracheal stent surgery, and can provide timely feedback to doctors. However, a simple geometry-based evaluation method cannot fully reflect the effect of the surgery and the difference before and after. Therefore, this application research plan simulates the reaction between the trachea and airflow before and after the stent based on the SPH method, and establishes a new physics-based evaluation index to evaluate the degree of tracheal stenosis, and then judge the effect of the surgery.

[0039] Existing technologies have significant shortcomings in preoperative planning of pulmonary bronchial surgery, including low computational efficiency of finite element analysis (FEA) and computational fluid dynamics (CFD) methods when dealing with complex fluid-structure interaction problems, difficulty in achieving real-time dynamic simulation, and dependence on grid systems leading to loss of accuracy when dealing with complex biological tissues and fluid interfaces. At the same time, data exchange and boundary condition processing are complex, and there is a lack of intuitive preoperative planning tools.

[0040] In response to these shortcomings, the purpose of this application is to introduce a method based on smoothed particle hydrodynamics (SPH) to provide a new simulation tool with high computational efficiency, capable of real-time simulation of dynamic changes during surgery, without grid dependence, simplifying data exchange and boundary condition processing, and providing intuitive preoperative planning, so as to improve the accuracy of surgical planning and the success rate of surgery. like Figure 1 As shown, the first purpose of the present application is to provide a method for assessing the degree of bronchial stenosis, comprising: S1, combining lung CT image data to build a three-dimensional lung bronchial model; S2, based on the SPH method, a fluid dynamics model of lung tissue was established under the three-dimensional lung bronchial model to simulate the fluid flow before and after surgery. By simulating the interaction between airflow and lung tissue, the fluid dynamics and tissue mechanical behaviors during surgery were simulated; S3, based on the fluid dynamics and tissue mechanical behaviors during simulated surgery, a physics-based evaluation index was constructed to assess the degree of tracheal stenosis.

[0041] This application introduces a method based on smoothed particle hydrodynamics (SPH) to achieve three-dimensional dynamic simulation of pulmonary bronchial surgery to improve the accuracy of preoperative planning and the safety of surgery. Through SPH simulation, an evaluation index based on physical quantities is established to more comprehensively reflect the impact of the degree of airway stenosis on airflow dynamics. It is more targeted for preoperative planning and postoperative evaluation of bronchial stenosis surgery. Combined with the clinical needs of bronchial stenosis surgery, it is expected to make breakthroughs in the quantitative evaluation of airway stenosis and provide clinicians with more accurate and reliable decision-making basis.

[0042] The SPH method is used in airflow tracheal simulation to achieve accurate simulation of fluid-structure interaction during surgery, and a new physics-based evaluation index is established to evaluate the degree of tracheal stenosis, thereby judging the surgical effect. The degree of tracheal stenosis is evaluated through the algorithm implementation of the SPH method in bronchial surgery planning, the visualization display technology of surgical simulation, and the new physics-based evaluation index.

[0043] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0044] Figure 2 A simulation framework diagram for preoperative planning of pulmonary bronchial surgery is provided. A method for assessing the degree of bronchial stenosis based on the SPH method includes the following steps: First, the 3D structural model of the lung bronchi is reconstructed using CT image data. The construction of the 3D lung bronchi model specifically includes: Data acquisition: First, extract key information from the patient's lung CT image data, remove noise and artifacts through image preprocessing, and perform grayscale standardization;.

[0045] 3D modeling: Then, the bronchial area was precisely separated, and the 3D surface model was generated by the Marching Cubes surface reconstruction algorithm, and optimization such as mesh smoothing, simplification, and hole repair was performed; finally, the reconstructed model was compared with the original CT image and quantitatively analyzed, and manual correction was performed to ensure the accuracy of the model. The model not only contains the geometric shape of the bronchus, but also reflects its complex internal structure.

[0046] Complete bronchial modeling Figure 3 As shown in Figure 1, the overall modeling is relatively complex. Considering that an overly detailed model will affect the computational efficiency, and mainly studying the pressure changes before and after the stenosis, the reconstructed model is simplified. The simplified model is shown in Figure 1. Figure 4 shown.

[0047] Secondly, a fluid dynamics model of lung tissue was established based on the SPH method to simulate the fluid flow before and after surgery; specifically, it includes: Specifically, the application of the SPH method is mainly to introduce the SPH method on the basis of the constructed three-dimensional lung bronchial model to establish a fluid dynamics model of lung tissue. The SPH method is a particle-based fluid dynamics simulation method that can well handle complex flow fields and the interaction between fluids and solids.

[0048] Simulating fluid flow: This model is used to simulate the flow of air in the bronchi before and after surgery. By adjusting the parameters, the airflow conditions under different degrees of stenosis can be simulated.

[0049] Simulation of tissue mechanical behavior: In addition to fluid dynamics simulation, this method also takes into account the mechanical behavior of lung tissue. By simulating the deformation and stress distribution of tissue during surgery, the surgical effect can be more comprehensively evaluated.

[0050] Among them, the SPH algorithm divides the fluid to be simulated into discrete particles, estimates the physical quantity of each particle through the smooth kernel function, and makes it satisfy the overall physical laws, and then iteratively calculates the physical quantity of each particle in each frame so that each particle can perform corresponding movements and finally obtain the expected results.

[0051] Figure 5 This is the SPH algorithm flow chart, which is used for computational fluid dynamics (CFD) or similar simulations. The process is as follows: Step 1. Initialize simulation parameters: set initial parameters such as particle radius and boundary conditions.

[0052] Step 2. Calculate the density and pressure of the particles using the Poly6 kernel function: This is a mathematical method used to calculate the interactions between particles.

[0053] Step 3. Calculate the pressure gradient force, viscosity force and gravity force on each particle: these forces will affect the movement of the particles.

[0054] Step 4. Update the particle’s velocity and position based on the calculated forces: This is the core step in the simulation and determines the dynamic behavior of the particles.

[0055] Step 5. Calculate the coupling between airflow and air pipe to solve the collision feedback force: This step may involve the interaction between fluid and solid structure.

[0056] Step 6. Output the corresponding simulation results: Finally, output the simulation results for further analysis or use.

[0057] An iterative process is performed, wherein steps 2 to 5 may be repeated until the termination condition of the simulation is reached.

[0058] Based on the above solution, this embodiment provides a specific process: For a particle , its physical quantity It can be expressed in a general form:

[0059] in , , Particles , Location, For adjacent particles Quality, For adjacent particles The density of The required particle The physical quantity, is a smooth kernel function.

[0060] Optionally, this embodiment uses the poly6 kernel function as the smooth kernel function, and the poly6 kernel function expression is as follows:

[0061] Then, based on the smooth kernel function, the cumulative functions related to the density, pressure, and velocity of a certain point in the fluid are deduced one by one, and then the acceleration here is derived to simulate the movement trend of the fluid. The force acting on a particle can be expressed by the following formula:

[0062] From this, we can solve for the particle's acceleration (rate of change and direction):

[0063] In the formula, is the acceleration of particle i, is other external forces (such as gravity) on particle i, and Represents the pressure and viscosity of the surrounding particles on particle i.

[0064] Optionally, the present application uses boundary particles to model the solid boundary and interact with the fluid particles. The coupling between the boundary and the airflow can be divided into two forces, one is the pressure between the two, and the other is the friction between the two. The former is similar to the calculation method of the pressure inside the fluid, and the latter is similar to the viscosity between the airflow particles.

[0065]

[0066] in is the net force on the particle, represents the pressure on the particle, represents the friction force on the particle. The pressure can be expressed as:

[0067] The friction force on the particle can be expressed as:

[0068] in represents the viscosity coefficient. Substituting the above two force formulas into it, we get the formula for the interaction force between fluid particles and solid boundaries:

[0069] Through the above equations, the present application can obtain the movement trend of the fluid, solve the relevant equations frame by frame, and then simulate the entire process.

[0070] Finally, the simulation results are displayed through visualization technology, and the degree of tracheal stenosis is evaluated through physical-based evaluation indicators to provide a reference for surgical planning. The evaluation indicators include: Physics-based evaluation indicators: Based on the fluid dynamics and tissue mechanical behaviors during simulated surgery, a series of physics-based evaluation indicators are constructed. These indicators can quantify the degree of bronchial stenosis and the impact of surgery on airflow and tissue.

[0071] Comprehensive evaluation: Through comprehensive analysis of these evaluation indicators, a more accurate assessment of the degree of bronchial stenosis can be made, and strong support can be provided for the formulation of surgical plans.

[0072] Figure 6 Schematic diagram of the location of tracheal stenosis; the traditional method of evaluating the degree of tracheal stenosis is usually based on area calculation, and the common calculation method is:

[0073] However, calculations based solely on geometry will result in errors and it is difficult to select the corresponding cross-section. Therefore, this application establishes a similar indicator for calculation with reference to the criteria for determining the degree of coronary artery stenosis. Figure 7 Schematic diagram of the particle being subjected to boundary pressure.

[0074] This application uses the Monte Carlo method to estimate the overall pressure value upstream and downstream of the narrow area, that is, and

[0075] Its calculation can be expressed as:

[0076] in is the total number of particles at the upstream or downstream boundary, is the number of randomly sampled particles, Represents the modulus of the total force on the particle.

[0077] Figure 8 The figure is a simulation diagram of the SPH method. The method selected in this application is based on the simulated pressure ratio of the front and rear ends of the stenosis. The calculation method can be expressed as:

[0078] in, is the pressure of the tracheal wall upstream of the stenosis, It is the pressure of the tracheal wall downstream of the stenosis.

[0079] By simulating the interaction between airflow and lung tissue, a new physics-based evaluation index is constructed to assess the degree of tracheal stenosis before and after stent implantation, such as Fig. 9 As shown, the simulation process can be realized to provide surgeons with intuitive preoperative planning and surgical simulation.

[0080] Furthermore, the above simulation process is based on physical principles and has a solid theoretical foundation, which makes the simulation results more reliable and can provide strong support for surgical planning. By constructing a series of physics-based evaluation indicators, the degree of bronchial stenosis can be evaluated more accurately. These indicators can quantify the impact of surgery on airflow and tissue, providing strong support for the formulation of surgical plans. This scheme uses particle methods to simulate fluid movement and uses visualization technology and physics-based evaluation indicators to evaluate the degree of tracheal stenosis. This method has the advantages of high precision, flexibility, visualization, physical basis and comprehensive evaluation, which can provide strong support for surgical planning.

[0081] Compared with the FEA-based method, the SPH method used in this application has higher computational efficiency and better simulation accuracy when dealing with fluid-structure interaction problems. In addition, this application can provide more intuitive surgical simulation and preoperative planning, which helps to improve the success rate and safety of surgery. Therefore, this application has the following advantages: High precision: Through the combination of three-dimensional modeling and SPH method, high-precision simulation and evaluation of the degree of bronchial stenosis can be achieved.

[0082] Comprehensiveness: It not only takes into account the flow of air in the bronchi, but also the mechanical behavior of lung tissue, making the evaluation results more comprehensive and accurate.

[0083] Practicality: This method can provide doctors with intuitive predictions of surgical results, help formulate more reasonable surgical plans, and reduce surgical risks.

[0084] like Fig.10 As shown, the third object of the present application is to provide a system for assessing the degree of bronchial stenosis, comprising: The model building module 100 is used to build a three-dimensional lung bronchial model in combination with lung CT image data; The mechanical simulation module 200 is used to establish a fluid dynamics model of lung tissue based on the SPH method under a three-dimensional lung bronchial model, simulate the fluid flow before and after the operation, and simulate the fluid dynamics and tissue mechanical behavior during the operation by simulating the interaction between the airflow and the lung tissue; The indicator construction module 300 is used to construct a physics-based evaluation indicator to evaluate the degree of tracheal stenosis based on the fluid dynamics and tissue mechanical behaviors during the simulated surgery.

[0085] The bronchial stenosis degree assessment system of the present application is based on the above-mentioned bronchial stenosis degree assessment method.

[0086] like Fig.11As shown, the third object of the embodiment of the present application is to provide an electronic device, including a memory 701, a processor 702, and a computer program stored in the memory 701 and executable on the processor, wherein the processor implements the above-mentioned bronchial stenosis degree assessment method when executing the computer program. It also includes a communication interface 703 and a bus 704.

[0087] A fourth objective of an embodiment of the present application is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method for assessing the degree of bronchial stenosis is implemented.

[0088] A fifth objective of an embodiment of the present application is to provide a computer program product, wherein the computer program product comprises computer instructions, and the computer instructions instruct a computer to execute the above-mentioned method for assessing the degree of bronchial stenosis.

[0089] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0090] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0091] The present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, readable storage medium, optical storage, etc.) containing computer-usable program codes.

[0092] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0093] Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application rather than to limit it. Although the present application has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present application can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present application should be included in the scope of protection of the claims of the present application.

Claims

1. A method for assessing the degree of bronchial stenosis, characterized in that: include: Combined with lung CT image data, a three-dimensional lung bronchial model was constructed; Based on the SPH method, a fluid dynamics model of lung tissue was established under the three-dimensional lung bronchial model to simulate the fluid flow before and after surgery. By simulating the interaction between airflow and lung tissue, the fluid dynamics and tissue mechanical behaviors during surgery were simulated. Based on the fluid dynamics and tissue mechanical behaviors during simulated surgery, a physics-based evaluation index was constructed to assess the degree of tracheal stenosis.

2. The method for evaluating the degree of bronchial stenosis according to claim 1, characterized in that: The SPH method includes: in a three-dimensional lung bronchial model, dividing the airflow to be simulated into discrete particles, estimating the physical quantity of each particle through a smooth kernel function and making it satisfy the overall physical law, and then calculating the physical quantity of each particle in each frame through continuous iteration so that each particle can perform corresponding movement.

3. The method for evaluating the degree of bronchial stenosis according to claim 2, characterized in that: The fluid dynamics model of lung tissue is established based on the SPH method under the three-dimensional lung bronchial model, including: In the three-dimensional lung bronchial model, the airflow is set as the initial parameters of the particle radius, boundary conditions, etc. Calculate the density and pressure of the airflow as particles using a smooth kernel function; Calculate the pressure gradient force, viscosity force and gravity force on each particle; Update the particle's velocity and position based on the calculated force; Couple the airflow with the air pipe to calculate and solve the collision feedback force; Establish a fluid dynamics model of lung tissue.

4. The method for evaluating the degree of bronchial stenosis according to claim 3, characterized in that: The fluid dynamics model of lung tissue is established based on the SPH method to simulate the fluid flow before and after surgery, including: For an air particle , Expressed in a general form: in , , Particles , Location, For adjacent particles Quality, For adjacent particles The density of The required particle The physical quantity, is the smooth kernel function; The Poly6 kernel function is used as the smooth kernel function: Then, based on the smooth kernel function, the cumulative functions related to the density, pressure, and velocity of a certain point in the fluid are deduced one by one, and then the acceleration is derived to simulate the movement trend of the fluid. The force acting on a particle is expressed by the following formula: This solves for the particle's acceleration: In the formula, is the acceleration of particle i, is the other external force on particle i, and Represents the pressure and viscosity of the surrounding particles on particle i.

5. The method for evaluating the degree of bronchial stenosis according to claim 3, characterized in that: The method simulates the interaction between airflow and lung tissue to simulate the fluid dynamics and tissue mechanical behavior during surgery, including: The solid boundary is modeled by boundary particles and interacts with fluid particles. The coupling between the boundary and the airflow is divided into two forces, one is the pressure between the two, and the other is the friction between the two: in is the net force on the particle, represents the pressure on the particle, represents the friction force on the particle; the pressure is expressed as: The friction force on the particle is expressed as: in represents the viscosity coefficient. Substituting the above two force formulas into it, we get the formula for the interaction force between fluid particles and solid boundaries: Through the interaction force between fluid particles and solid boundaries, the movement trend of the fluid is obtained, and the relevant equations are solved frame by frame to simulate the entire process and solve the collision feedback force.

6. The method for evaluating the degree of bronchial stenosis according to claim 3, characterized in that: The fluid dynamics model based on lung tissue is used to construct a physical-based evaluation index to evaluate the degree of tracheal stenosis, including: The Monte Carlo method is used to estimate the overall pressure value upstream and downstream of the narrow area, that is, and ; The calculation process is expressed as: in, is the total number of particles at the upstream or downstream boundary, is the number of randomly sampled particles, represents the modulus of the total force on the particle; Based on the simulated pressure ratio between the front and rear ends of the stenosis, a physics-based evaluation index is constructed: in, is the pressure of the tracheal wall upstream of the stenosis, It is the pressure of the tracheal wall downstream of the stenosis.

7. A bronchial stenosis degree assessment system, characterized in that: include: A model building module is used to build a three-dimensional lung bronchial model by combining lung CT image data; The mechanical simulation module is used to establish a fluid dynamics model of lung tissue based on the SPH method under a three-dimensional lung bronchial model, simulate the fluid flow before and after surgery, and simulate the fluid dynamics and tissue mechanical behavior during surgery by simulating the interaction between airflow and lung tissue; The indicator building module is used to construct a physics-based evaluation indicator to assess the degree of tracheal stenosis based on the fluid dynamics and tissue mechanical behaviors during simulated surgery.

8. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for assessing the degree of bronchial stenosis according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for assessing the degree of bronchial stenosis according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising computer instructions, characterized in that: The computer instructions instruct the computer to execute the method for assessing the degree of bronchial stenosis according to any one of claims 1 to 6.

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