A method for stent virtual implantation and stent optimization for ascending aorta

Abstract

This invention discloses a method and product for virtual stent implantation and stent optimization in the ascending aorta. The method includes: acquiring medical images of the patient's ascending aorta; reconstructing a vessel wall model including the ascending aorta and aortic arch; constructing three-dimensional models of the stent, delivery sheath, and virtual target delivery sheath respectively; assembling the vessel wall model and the three-dimensional models of the stent, delivery sheath, and virtual target delivery sheath to establish a finite element calculation model, assigning material properties, and meshing; setting boundary condition parameters for the ascending aorta during diastole, and obtaining the initial configuration of the vessel wall model through a reverse displacement iteration method; performing virtual implantation calculations on the finite element calculation model; changing the boundary conditions of the ascending aorta to simulate the effects of cardiac contraction and relaxation; outputting stent implantation effect evaluation indicators after virtual stent implantation, and optimizing the stent configuration parameters based on the evaluation indicators.

Description

Technical Field

[0001] This invention belongs to the fields of medical device design and computer technology, and particularly relates to a method for virtual stent implantation and stent optimization for the ascending aorta. Background Technology

[0002] The ascending aorta is a crucial component of the aorta. During systole, blood is pumped from the left ventricle of the heart, passes through the valves, and flows into the ascending aorta. The blood flowing into the ascending aorta is under high pressure and at a high velocity, subjecting the aortic tissue to the impact of this high-pressure, high-velocity blood flow. The ascending aorta has a tortuous structure, exhibiting a high curvature in some patients. Due to its proximity to the heart, the ascending aorta undergoes significant movement in tandem with the heart: during systole and diastole, the ascending aorta swings with the heart, specifically manifested as a general movement towards the left ventricle during left ventricular ejection.

[0003] Due to long-term hypertension or hereditary diseases (such as Marfan syndrome), patients may develop ascending aortic lesions, mainly including ascending aortic dissection (type A dissection) and ascending aortic aneurysm. Aortic dissection is characterized by a tear in the aortic intima, allowing blood to enter the aorta through the tear, causing the media to detach from the adventitia and forming a new, independent lumen (false lumen). Aortic dissection is most common in the ascending aorta. Ascending aortic dissection may extend distally, affecting the aortic arch, brachiocephalic artery, left subclavian artery, left common carotid artery, and thoracic aorta, leading to poor organ perfusion. Ascending aortic dissection can also lead to aortic rupture, endangering personal safety. Ascending aortic aneurysm is characterized by localized dilation of the ascending aorta, significantly increased wall stress, and degradation of the vessel wall's mechanical properties, potentially leading to rupture and endangering the patient's life.

[0004] The preferred treatment for ascending aortic dissection and aortic aneurysm is open-chest surgery, involving procedures such as aortic replacement, repair, or root reconstruction, depending on the type of lesion. Compared to endovascular repair, open-chest surgery for ascending aortic lesions is significantly more invasive, requiring sternotomy, general anesthesia, cardiopulmonary bypass, significant postoperative pain, longer hospital stays, and a higher risk of cardiopulmonary and neurological complications and infection. Furthermore, open-chest surgery demands a more stringent patient condition; elderly patients, those with poor cardiac function, or those with other underlying diseases have lower tolerance and are less likely to meet the surgical requirements. Even if surgery is performed, the recovery period is significantly longer than with minimally invasive endovascular surgery. In addition, open-chest surgery requires a highly skilled medical team, necessitating close collaboration among anesthesiologists, cardiologists, vascular surgeons, neurologists, and monitoring specialists. Therefore, for patients who do not meet the criteria for open-chest surgery, medication is often used to manage blood pressure and heart rate to prevent further disease progression while awaiting surgical intervention. However, studies have shown that medication management significantly reduces patient survival rates, and patients may experience disease deterioration and death during the medication management period.

[0005] Thoracic endovascular aortic repair (TEVAR) is commonly used to repair thoracic aortic dissection and aortic aneurysm. It is a minimally invasive procedure where a draped stent is delivered downstream to the lesion site in the aorta. After deployment, the stent covers the lesion, isolating the aneurysm or dissection tear, restoring normal blood flow to the aorta, and preventing further disease progression. TEVAR does not require open-chest surgery, is minimally invasive, and allows for rapid recovery; it is well-tolerated by elderly and high-risk patients. Currently, clinical trials of TEVAR in the ascending aorta are underway, but these trials are costly, involve rigorous patient selection, have high ethical requirements, and many procedures rely heavily on physician experience, lacking quantitative research.

[0006] Furthermore, the current market lacks dedicated stent products for the ascending aorta. Clinical treatment of ascending aortic lesions often necessitates the off-label use of thoracic aortic stents. Because the ascending aorta has a different geometry than the descending thoracic aorta—characterized by greater curvature, larger diameter, proximity to branches, and closeness to the heart—it exhibits high-frequency and intense pulsation driven by ventricular contraction and relaxation. This can lead to adverse effects such as slippage and endoleak when implanting existing stents. It is generally believed in the art that stable endovascular repair of the ascending aorta is difficult due to its intense pulsation, and existing numerical simulation models for thoracic aortic stent implantation cannot be directly applied to ascending aortic scenarios. Therefore, it is necessary to develop virtual stent implantation methods specifically for the ascending aorta.

[0007] Clinical validation of the implantation efficacy of ascending aortic stents is costly and raises ethical concerns. However, using a virtual implantation method, which observes post-implantation effects and adverse reactions and optimizes and updates the stent design, is less costly and time-consuming, enabling the designed novel ascending aortic stents to meet the requirements for endovascular repair of the ascending aorta. Summary of the Invention

[0008] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a method and product for virtual stent implantation and stent optimization in the ascending aorta. By introducing specific motion boundary conditions and an evaluation system that considers shear forces, the technical challenge of precise virtual implantation and stent optimization under dynamic physiological conditions is solved.

[0009] In view of this, the present invention proposes a method for virtual stent implantation and stent optimization in the ascending aorta, comprising: Step 1: Obtain medical images of the patient's ascending aorta; Step 2: Based on medical images, reconstruct a model of the vessel wall, including the ascending aorta and aortic arch. Step 3: Construct 3D models of the support frame, delivery sheath, and virtual target delivery sheath respectively; Step 4: Assemble the vascular wall model from Step 2 and the 3D models of the stent, delivery sheath, and virtual target delivery sheath from Step 3, establish a finite element calculation model, assign material properties, and mesh. Step 5: Set the boundary conditions of the ascending aorta to the parameters of cardiac diastole, and obtain the initial configuration of the vessel wall model through the reverse displacement iteration method; Step 6: Perform virtual implantation calculations on the finite element calculation model. The calculations include: applying initial blood pressure to the initial configuration of the vascular wall model and setting diastolic boundary condition parameters to obtain in vivo stress information of the vascular wall; setting interaction parameters for finite element calculations; and gradually releasing the stent by displacing nodes on the delivery sheath to the corresponding node positions of the virtual target delivery sheath. Step 7: Change the boundary conditions of the ascending aorta to parameters for cardiac systole to simulate the effects of cardiac systole and diastole; Step 8: Output evaluation metrics after virtual stent implantation; Step 9: Optimize the stent configuration parameters based on stent implantation effect evaluation indicators.

[0010] Preferably, the ascending aorta medical imaging in step 1 is CT angiography or magnetic resonance imaging; Step 2 includes: using a dynamic region growth method based on the grayscale threshold method to segment the blood flow domain of the ascending aorta and the aortic arch, including three branch vessels connected to the aortic arch: the brachiocephalic artery, the left common carotid artery, and the left subclavian artery.

[0011] Preferably, step 3 includes: A 3D model of a covered stent or a non-covered stent is constructed on 3D modeling software. The stent system model is straight or curved. The 3D model of the covered stent consists of multiple or a single stent mesh and a covering. The 3D model of the non-covered stent consists of multiple or a single stent mesh. Construct a thin-walled, straight or curved cylinder without top or bottom surfaces, and place it outside the support according to the shape of the support to serve as a three-dimensional model of the delivery sheath. The diameter of the cylinder is slightly larger than that of the film-coated support, and the difference between the two diameters is on the order of mm. Based on the blood flow domain of the ascending aorta and aortic arch, the center points of each section of the blood flow domain or the characteristic points on the greater curvature side are connected to form a curve. Based on this curve, a surface with a set diameter is constructed as a three-dimensional model of the virtual target delivery sheath. The surface constructed with the set diameter is inside the blood vessel wall, and the difference between the two diameters is on the order of mm.

[0012] Preferably, the assembly in step 4 includes: aligning the midpoints of the proximal cross-sections of the three-dimensional models of the support, delivery sheath, and virtual target delivery sheath, and placing them together in the proximal release region of the target; Step 4, assigning material properties and generating a mesh, includes: The coating of the membrane-coated stent is made of PET or ePTFE material and is discretized using membrane units; Both the covered and uncovered scaffolds are made of nickel-titanium alloy metal material and are discretized using beam elements or three-dimensional solid elements; The mechanical behavior of the blood vessel wall model is described by linear elastic or hyperelastic constitutive equations. During the discretization of the blood vessel wall model, three-dimensional solid elements or shell elements are used for mesh generation. The delivery sheath and the virtual target delivery sheath do not specify material properties and are discretized using surface elements or shell elements. The grid is divided so that the number of grid nodes and grid cells of the delivery sheath and the virtual target delivery sheath are the same, and the numbering order is consistent, with a one-to-one correspondence.

[0013] Preferably, step 5 specifically includes: Step 5-1: Determine the diastolic pressure based on the patient's clinical data. Set the boundary conditions of the three branches of the ascending aorta—proximal, distal, and arch—to parameters for cardiac diastole. Specifically, fix the circumferential direction and set the corresponding pre-stretch amount in the axial direction based on imaging methods, all between 0.8 and 2. After setting, perform finite element calculations. Step 5-2: Obtain the coordinates of each node in the blood vessel wall model after the finite element calculation is completed. and the coordinates of each node before calculation Calculate the coordinate difference between the two. And set a coefficient k, k Calculate the coordinates of each node in the new model. : Using the new model Then perform finite element calculations again; Step 5-3: Perform iterative calculations as in Step 5-2 until the coordinates of all nodes are obtained after the nth calculation. All meet Coordinates before this calculation The represented configuration is the initial configuration without applied blood pressure and boundary conditions.

[0014] Preferably, step 6 specifically includes: Step 6-1: Apply initial blood pressure and diastolic boundary condition parameters to the initial blood vessel wall model to obtain in-situ stress information of the blood vessel wall; Step 6-2: Export the coordinate values ​​and corresponding node numbers of each node on the transport sheath and the virtual target transport sheath. Calculate the coordinate difference between the corresponding nodes of the transport sheath model and the virtual target transport sheath model. Drive the nodes of the transport sheath model to generate corresponding displacements through the displacement control subroutine method of the finite element software, so as to move the nodes on the transport sheath to the corresponding node positions of the virtual target transport sheath. Step 6-3: Release the stent step by step in the set sequence, while activating the interaction between the stent and the blood vessel wall, so that the stent contacts the blood vessel wall. The contact can be hard or soft, and a specific amount of friction is specified.

[0015] Preferably, step 7 specifically includes: Based on the patient's clinical data, the systolic blood pressure was determined and applied to the finite element model. Using imaging methods, the displacement and velocity of the three branches of the ascending aorta—proximal, distal, and arch—during cardiac systole were measured. Based on the measurement results, the boundary conditions of the ascending aorta were modified. Specifically, the corresponding systolic displacement or velocity of the three branches of the ascending aorta were set as their respective boundary conditions to simulate the motion of the ascending aorta during cardiac systole and diastole.

[0016] Preferably, the stent implantation effect evaluation indicators output in step 8 include: the coverage of each wire section of the stent within the vessel wall before and after changing the boundary conditions of the ascending aorta, the maximum principal stress of the vessel wall, the maximum value and location of the Von Mises stress, and the maximum value and location of the shear stress of the vessel wall.

[0017] Preferably, step 9 includes: An orthogonal experimental design method was used to optimize at least one of the following structural parameters: diameter of the support, number of wires, wire height, number of crests and troughs, and wire thickness.

[0018] Preferably, the method further includes a verification step: using medical images of multiple other patients, virtual implantation simulations are performed using stent configurations before and after optimization, and the stent implantation effect evaluation indicators are compared to verify the universality of the optimization effect.

[0019] Compared with the prior art, the advantages of the present invention are: 1. The simulation takes into account the motion state of the ascending aorta, which is closer to the in vivo situation: that is, during systole, the root of the ascending aorta will move roughly towards the left ventricle as the heart pumps blood. This motion may cause the implanted stent to have an adverse effect on the aorta.

[0020] 2. The physical quantities after stent deployment include the shear force between the stent and the vessel wall caused by the movement of the aortic root. This is a key point that needs to be considered in the simulation of the ascending aorta.

[0021] 3. Creatively optimize the design of ascending aortic stents: Combine the virtual stent implantation situation with orthogonal experimental design to optimize the stent configuration, and select multiple patient images to verify the optimization effect.

[0022] 4. By constructing a virtual target delivery sheath and using a node-specific displacement control subroutine, the stent can be directly delivered to the target position by gripping the delivery sheath during simulation. This avoids numerical calculation problems caused when simulating the entire clinical stent delivery process. Furthermore, this method requires less calculation time and has higher computational efficiency.

[0023] 5. This invention overcomes technical bias and develops a method for virtual stent deployment and optimization for ascending aortic lesions. Targeting the unique motion characteristics of the ascending aorta, it constructs boundary conditions highly characteristic of ascending aortic motion. Furthermore, this method can optimize the ascending aortic stent based on deployment conditions. This method has significant implications for clinical surgical planning and medical device optimization design. Attached Figure Description

[0024] Figure 1 This is a flowchart of the method for virtual stent deployment and optimization for ascending aortic lesions according to the present invention; Figure 2 This is a finite element calculation model, where the left side of the image has the computational mesh, and the right side of the image hides the computational mesh.

[0025] Figure 3 It is a method for constructing a virtual target delivery sheath. Detailed Implementation

[0026] This invention aims to propose a method for virtual stent deployment and optimization in the ascending aorta. Primarily using finite element method (FEM) simulation, a covered stent is virtually implanted into the ascending aorta of a patient by directly bending the delivery sheath, and the implantation effect is evaluated. Unlike traditional methods applicable to the descending thoracic aorta, virtual implantation of ascending aortic stents must fully consider the large-amplitude movements of the ascending aorta with cardiac motion. The stent configuration is then continuously modified based on the implantation effect to improve its deployment, thereby achieving optimized ascending aortic stent configuration. The evaluation of implantation effect includes the stent's apposition to the vessel wall after implantation, the stress exerted by the stent on the vessel wall, and the additional shear stress exerted by the stent on the vessel wall due to aortic root movement during the cardiac cycle. Poor apposition may lead to stent endoleak, failing to completely seal the lesion site; high stress in the ascending aorta may lead to new ruptures, potentially causing highly lethal retrograde type A aortic dissection.

[0027] This invention aims to overcome technological bias and develop a method for virtual stent deployment and optimization for ascending aortic lesions. It constructs boundary conditions highly characteristic of the ascending aorta, taking into account its unique motion characteristics. Furthermore, this method can optimize the ascending aortic stent based on deployment conditions. This method has significant implications for clinical surgical planning and medical device optimization design.

[0028] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0029] Example 1 Embodiment 1 of the present invention proposes a method for virtual stent implantation and stent optimization for the ascending aorta.

[0030] like Figure 1 As shown, the specific steps are as follows: S1: Obtain CTA (CT angiography) or MRI (magnetic resonance imaging) images of the patient's ascending aorta.

[0031] S2: Reconstruct the ascending aortic vessel wall model based on CTA images.

[0032] Using medical image processing software based on the grayscale thresholding method, the blood flow domains of the ascending aorta and aortic arch (starting from the aortic valve and ending behind the left subclavian artery) are segmented. It should be noted that although this invention focuses on the ascending aorta, segmenting a portion further away from the aorta is necessary to accurately define boundary conditions in the finite element simulation, resulting in a more accurate simulation. The three branch vessels connected to the aortic arch (brachial artery, left common carotid artery, and left subclavian artery) also need to be reconstructed for subsequent application of boundary conditions.

[0033] After the blood flow domain is reconstructed, the blood flow domain is expanded outward by a certain thickness (generally 2 mm, based on the thickness of the patient's ascending aorta) to obtain the expanded model.

[0034] Using Boolean subtraction, the blood flow domain is subtracted from the expanded model to obtain the blood vessel wall model.

[0035] The segmented blood vessel wall model was reconstructed using the reverse modeling software Geomagic Studio to obtain a solidified blood vessel wall .igs / .step file.

[0036] S3: Construct a three-dimensional model of the covered scaffold.

[0037] Based on the instruction manual or 3D scan results of a covered scaffold, a covered scaffold model is constructed in 3D modeling software (such as Solidworks, Catia, etc.), consisting of multiple or a single scaffold mesh and a covering. If it is an uncovered scaffold model, it consists of multiple or a single scaffold mesh.

[0038] Construct a three-dimensional model of the delivery sheath.

[0039] Construct a delivery sheath placed outside the support system. Its shape is determined by the support system. The diameter of the delivery sheath should be slightly larger than that of the film-coated support system, with the difference in diameter being on the order of mm.

[0040] Construct a three-dimensional model of the virtual target delivery sheath.

[0041] Construct a virtual delivery sheath at the target location within the aorta. Based on the blood flow domain of the ascending aorta and aortic arch, connect the center points of each cross-section of the blood flow domain or the characteristic points on the greater curvature side with a curve, as shown in the appendix. Figure 3 Using 3D modeling software, a surface with a certain diameter is constructed based on the curve. This diameter is required to be smaller than the diameter of the blood vessel wall. This surface is the virtual delivery sheath at the target location.

[0042] S4: Assemble the finite element calculation model.

[0043] The covered or uncovered stent, the vessel wall, the delivery sheath, and the virtual target delivery sheath are imported into the finite element software (Abaqus is used in this embodiment).

[0044] The covered or uncovered stent, vessel wall, delivery sheath, and virtual target delivery sheath are assembled into a single assembly. The midpoints of the proximal cross-sections of the covered stent, delivery sheath, and virtual target delivery sheath must coincide, and they must be placed together in the proximal release region of the target.

[0045] S5: Grid the material and assign material properties.

[0046] Material properties are assigned to the stent and vessel wall, and meshes are generated and specified. Preferably, if there is a membrane, the membrane is specified as PET or ePTFE material and discretized using membrane elements; the stent is specified as nickel-titanium alloy material and discretized using beam elements or 3D solid elements; the vessel wall is described using linear elastic and hyperelastic constitutive models and discretized using 3D solid elements. Furthermore, the delivery sheath and the virtual target delivery sheath are discretized using surface elements and do not require specifying material properties. It is required that the number of mesh nodes and mesh elements of the delivery sheath and the virtual target delivery sheath are consistent, and their numbering order is consistent, with a one-to-one correspondence.

[0047] S6: Set boundary condition parameters for the ascending aorta during diastole.

[0048] First, determine the initial blood pressure of the model, which is the patient's diastolic blood pressure. This value is between 40-100 mmHg, and it is usually higher for hypertensive patients. In addition, set the patient's diastolic boundary conditions for the three branches of the aorta: proximal, distal, and arch. Specifically, the circumferential boundary is generally fixed, while the axial boundary needs to be set according to medical imaging measurements. Each pre-stretch value is between 0.8 and 2.

[0049] S7: Obtain the initial configuration of the blood vessel wall using the reverse displacement iteration method.

[0050] Because the blood vessel walls in CTA images are actually subjected to stress due to the impact of blood flow, the initial model for finite element analysis needs to obtain this stress information. Therefore, the inverse displacement iteration method is used to obtain the initial configuration of the blood vessel wall when it is not under stress. The requirement is to apply blood pressure and in-situ boundary conditions to the aorta in the initial configuration to obtain the in-situ stress information of the aorta. Specifically, the steps are as follows: Obtain the coordinates of each node in the blood vessel wall model after the finite element calculation is completed. and the coordinates of each node before calculation Calculate the coordinate difference between the two. And set a coefficient k, k Calculate the coordinates of each node in the new model. : Using the new model Then perform finite element calculations again; The above steps are repeated iteratively until the coordinates of all nodes are obtained after the nth calculation. All meet Coordinates before this calculation The represented configuration is the initial configuration without applied blood pressure and boundary conditions.

[0051] S8: Finite element calculation of stent virtual implantation in the ascending aorta during diastole Finite element method calculations require setting the interactions between components. The covered stent and the stent mesh are connected by a tie constraint. The delivery sheath and the covered stent, in this embodiment, are in hard or soft contact with the vessel wall, and a specified friction coefficient is set, which is typically 0-0.5.

[0052] Perform the calculation steps in the following order: Step 1: Apply diastolic blood pressure to the ascending aorta model to obtain in vivo stress information of the vessel wall. The proximal, distal, and arched branches of the ascending aorta are all subject to fixed boundary conditions in both the axial and circumferential directions.

[0053] Step-2: Press the delivery sheath to the virtual target delivery sheath position to manipulate the support to the pressing position.

[0054] The transport sheath manipulation is controlled by manipulating the nodes of the transport sheath. By calculating the coordinate position difference between each corresponding node on the transport sheath and the virtual target transport sheath, the Abaqus VDISP subroutine is used to drive the transport sheath to the position of the virtual target transport sheath.

[0055] Step 3: In this embodiment, the contact between the virtual sheath and the covered stent is released sequentially, from proximal to distal, one stent loop at a time, while simultaneously activating the contact between the covered stent and the vessel wall. This allows the covered stent to contact the vessel wall.

[0056] S9: Change the boundary conditions for the motion of the ascending aorta.

[0057] The displacement and velocity of the ascending aorta during systole (corresponding to diastole) were measured using imaging methods. The boundary conditions of the ascending aorta were then modified for calculation, thus simulating the motion of the ascending aorta during systole. In this embodiment, a uniform motion towards the heart was applied to all nodes at the root of the ascending aorta, stretching it by 10 mm within 0.3 seconds.

[0058] S10: Output evaluation metrics after virtual stent implantation.

[0059] Before and after changing the boundary conditions of the ascending aorta, the coverage of each wire section of the stent within the vessel wall, the maximum principal stress of the vessel wall, the maximum value and location of Von Mises stress, and the maximum value and location of shear stress of the vessel wall were measured.

[0060] S11: Optimize the design of the covered stent.

[0061] The above three physical parameters are optimized by continuously adjusting the diameter of the coating support, the number of support wires, the wire height, the number of crests and troughs, and the wire thickness. Orthogonal experimental design and other methods are used to reduce the number of computational examples and improve the optimization speed.

[0062] S12: Validate the stent optimization effect using multiple patients.

[0063] Then, using medical images of multiple patients (preferably 3), simulations were conducted using the optimized covered stent and the unoptimized covered stent to verify the optimization effect and see if the optimized effect was better.

[0064] Example 2 Embodiment 2 of the present invention proposes a method for virtual stent implantation and stent optimization in the ascending aorta, such as... Figure 1 The diagram shown is a flowchart of the invention.

[0065] S1 consists of CTA (CT angiography) or MRI (magnetic resonance imaging) images of patients with ascending aortic lesions (ascending aortic dissection, ascending aortic aneurysm, etc.). Generally, CTA is the first-line treatment for patients with ascending aortic lesions. However, for patients who have contraindications to CTA, such as iodine allergy, renal impairment, or pregnancy, MRI can be used as an alternative examination method. These medical images are in DICOM format and are stored on a computer using storage devices.

[0066] S2 reconstructs the ascending aortic vessel wall model based on medical images. DICOM format medical images are opened using medical image processing software such as Mimics. Based on grayscale thresholding, a dynamic region growing method is used to segment the blood flow domain of the ascending aorta and aortic arch (starting from the aortic valve and ending behind the left subclavian artery) in the software. The three branch vessels of the aortic arch (brachial artery, left common carotid artery, and left subclavian artery) also need to be reconstructed for subsequent application of boundary conditions. After the blood flow domain reconstruction is completed, it is expanded outward by a certain thickness (generally 2mm, based on the thickness of the patient's ascending aorta) to obtain the expanded model. Boolean subtraction is used to subtract the blood flow domain from the expanded model to obtain the vessel wall model. The segmented vessel wall model is then reconstructed using the inverse modeling software Geomagic Studio to obtain a solidified vessel wall .igs / .step file.

[0067] S3 involves constructing a 3D model of the covered scaffold. This embodiment, based on the covered scaffold's instruction manual, constructs the model using 3D modeling software (Solidworks is used in this embodiment). The covered scaffold model consists of multiple scaffold wires and a covering.

[0068] Construct a three-dimensional model of the delivery sheath. The delivery sheath is modeled as a thin-walled cylinder without top and bottom surfaces, and placed outside the coating support. The diameter of the delivery sheath is slightly larger than that of the coating support (preferably 1 mm larger).

[0069] Construct a three-dimensional model of the virtual target delivery sheath. Based on the blood flow domain of the ascending aorta and aortic arch, obtain the centerline of the blood flow domain. Using three-dimensional modeling software, construct a surface with a certain diameter based on this centerline. This diameter should be smaller than the diameter of the vessel wall (preferably, by 4-10 mm). This surface is the virtual target delivery sheath.

[0070] S4 is the assembly of the finite element calculation model. The covered stent, vessel wall, delivery sheath, and virtual target delivery sheath are imported into the finite element software (Abaqus is used in this embodiment). The covered stent, vessel wall, delivery sheath, and virtual target delivery sheath are then assembled into a single assembly. The midpoints of the proximal cross-sections of the covered stent, delivery sheath, and virtual target delivery sheath must coincide, and they must be placed together in the proximal release region of the target.

[0071] S5 meshes and assigns material properties. Material properties are assigned to the covered stent and the vessel wall, and the mesh is generated and the mesh type is specified. Preferably, the covered stent is specified as PET or ePTFE material, discretized using membrane elements; the stent is specified as nickel-titanium alloy material, discretized using beam elements or 3D solid elements; the vessel wall is described using linear elastic and hyperelastic constitutive models, discretized using 3D solid elements. Furthermore, the delivery sheath and the virtual target delivery sheath are discretized using surface elements, without specifying material properties. It is required that the number of mesh nodes and mesh elements of the delivery sheath and the virtual target delivery sheath are consistent, and their numbering order is consistent, with a one-to-one correspondence. The assembled and meshed finite element model is shown in the appendix. Figure 2 The left image shows the computational grid, while the right image hides the computational grid. In this embodiment, the endothelial membrane uses the M3D4R unit type, the stent uses the C3D4R unit type, the vessel wall uses the C3D4 unit type, and the delivery sheath uses the SFM3D4R unit type.

[0072] S6 sets the boundary condition parameters for ascending aortic diastole. First, determine the initial blood pressure of the model, which is the patient's diastolic blood pressure. This value is between 40-100 mmHg, and it is usually higher for hypertensive patients. In addition, set the patient's diastolic boundary conditions for the three branches of the aorta: proximal, distal, and arch. Specifically, the circumferential boundary is generally fixed, while the axial boundary needs to be set according to medical imaging measurements. Each pre-stretch value is between 0.8 and 2.

[0073] S7 uses the inverse displacement iteration method to obtain the initial configuration of the blood vessel wall. Because the blood vessel wall in CTA images is actually subjected to stress due to the impact of blood flow, the initial model for finite element analysis needs to obtain this stress information. Therefore, the inverse displacement iteration method is used to obtain the initial configuration of the blood vessel wall when it is not under stress. Assuming the blood pressure inside the aorta is 80 mmHg during CTA imaging, applying a blood pressure of 80 mmHg to the aorta yields the in-situ stress information of the aorta. Specifically, this includes: After setting up S6, perform finite element calculations. Obtain the coordinates of each node in the blood vessel wall model after the finite element calculation is completed. and the coordinates of each node before calculation Calculate the coordinate difference between the two. And set a coefficient k, k Calculate the coordinates of each node in the new model. : Using the new model Then perform finite element calculations again; The above steps are repeated iteratively until the coordinates of all nodes are obtained after the nth calculation. All meet Coordinates before this calculation The represented configuration is the initial configuration without applied blood pressure and boundary conditions.

[0074] S8: Finite element calculation of stent virtual implantation in the ascending aorta during diastole Finite element method (FEM) calculations require setting up interactions between components. The stent membrane and stent mesh are connected by a tie constraint. In this embodiment, the nodes of the stent mesh are connected to the surface of the membrane, and the nodes of the stent mesh cannot be more than 0.3 mm away from the membrane surface. The delivery sheath and the covered stent, and the covered stent and the vessel wall, are in hard contact, with a specified coefficient of friction. In this embodiment, the coefficient of friction between the delivery sheath and the covered stent is 0, and the coefficient of friction between the covered stent and the vessel wall is 0.1. The Coulomb friction model is used to describe the friction.

[0075] Performing finite element calculations involves four steps.

[0076] Step 1: Apply a blood pressure of 80 mmHg to the aortic model to obtain in vivo stress information of the vessel wall. The three branches of the aorta—proximal, distal, and arch—are all subject to fixed boundary conditions in both the axial and circumferential directions.

[0077] Step 2: Press the delivery sheath to the virtual target delivery sheath position to manipulate the support to the pressing position. The delivery sheath is manipulated by controlling the nodes of the delivery sheath. In this embodiment, firstly, Abaqus software is used to export the coordinate values ​​and corresponding node numbers of each node on both the delivery sheath and the virtual target delivery sheath. Then, MATLAB software is used to calculate the displacement between the corresponding nodes, which is then written into the Abaqus VDISP subroutine to drive the delivery sheath to the virtual target delivery sheath position.

[0078] Step 3: Starting from the proximal end and moving towards the distal end, release the contact between the virtual sheath and the covered stent one stent loop at a time, while simultaneously activating the contact between the covered stent and the vessel wall. This brings the covered stent into contact with the vessel wall. In this embodiment, if there are three stent wires, release them in three steps: first, release the one closest to the heart, then the middle one, and finally the one furthest away.

[0079] S9 modifies the boundary conditions for the motion of the ascending aorta. Based on the measurement of the systolic displacement of the ascending aorta using imaging methods, the boundary conditions applied to the ascending aorta are modified to accurately simulate its systolic motion. In this embodiment, a uniform axial stretch of 10 mm towards the left ventricle is applied within 0.5 s to simulate the systolic motion of the ascending aorta.

[0080] S10 is an evaluation index for the effectiveness of stent implantation. It includes the stent coverage within the vessel wall, the maximum principal stress and Von Mises stress of the vessel wall and their locations, and the maximum shear stress of the vessel wall and its location for each stent wire profile.

[0081] S11 involves optimizing the design of the laminated stent. This is achieved by continuously adjusting the stent's diameter, the number of stent wires, wire height, the number of crests and troughs, and wire thickness to optimize the three physical parameters mentioned above. In this embodiment, orthogonal experimental design is used to reduce the number of computational examples and increase the optimization speed. In another embodiment, Isight software is used for automatic parametric modeling, allowing the software to perform optimization automatically and reducing human workload.

[0082] S12 involves validating the optimization effect using multiple patients. Medical images from multiple patients (preferably three) are then used to simulate the optimization using both the optimized covered stent and the unoptimized covered stent, to verify the optimization effect and see if the optimized result is better.

[0083] Example 3 Embodiments of the present invention may also provide a computer program product, including a computer program. When the computer program is executed by a processor, it can implement the various steps in the above method embodiments.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for virtual stent implantation and stent optimization in the ascending aorta, comprising: Step 1: Obtain medical images of the patient's ascending aorta; Step 2: Based on medical images, reconstruct a model of the vessel wall, including the ascending aorta and aortic arch. Step 3: Construct 3D models of the support frame, delivery sheath, and virtual target delivery sheath respectively; Step 4: Assemble the vascular wall model from Step 2 and the 3D models of the stent, delivery sheath, and virtual target delivery sheath from Step 3, establish a finite element calculation model, assign material properties, and mesh. Step 5: Set the boundary conditions of the ascending aorta to the parameters of cardiac diastole, and obtain the initial configuration of the vessel wall model through the reverse displacement iteration method; Step 6: Perform virtual implantation calculations on the finite element calculation model. The calculations include: applying initial blood pressure to the initial configuration of the vascular wall model and setting diastolic boundary condition parameters to obtain in vivo stress information of the vascular wall; setting interaction parameters for finite element calculations; and gradually releasing the stent by displacing nodes on the delivery sheath to the corresponding node positions of the virtual target delivery sheath. Step 7: Change the boundary conditions of the ascending aorta to parameters for cardiac systole to simulate the effects of cardiac systole and diastole; Step 8: Output evaluation metrics after virtual stent implantation; Step 9: Optimize the stent configuration parameters based on stent implantation effect evaluation indicators.

2. The method for virtual stent implantation and stent optimization in the ascending aorta according to claim 1, characterized in that, The ascending aorta medical imaging in step 1 is CT angiography or magnetic resonance imaging. Step 2 includes: using a dynamic region growth method based on the grayscale threshold method to segment the blood flow domain of the ascending aorta and the aortic arch, including three branch vessels connected to the aortic arch: the brachiocephalic artery, the left common carotid artery, and the left subclavian artery.

3. The method for virtual stent implantation and stent optimization in the ascending aorta according to claim 2, characterized in that, Step 3 includes: A 3D model of a covered stent or a non-covered stent is constructed on 3D modeling software. The stent system model is straight or curved. The 3D model of the covered stent consists of multiple or a single stent mesh and a covering. The 3D model of the non-covered stent consists of multiple or a single stent mesh. Construct a thin-walled, straight or curved cylinder without top or bottom surfaces, and place it outside the support according to the shape of the support to serve as a three-dimensional model of the delivery sheath. The diameter of the cylinder is slightly larger than that of the film-coated support, and the difference between the two diameters is on the order of mm. Based on the blood flow domain of the ascending aorta and aortic arch, the center points of each section of the blood flow domain or the characteristic points on the greater curvature side are connected to form a curve. Based on this curve, a surface with a set diameter is constructed as a three-dimensional model of the virtual target delivery sheath. The surface constructed with the set diameter is inside the blood vessel wall, and the difference between the two diameters is on the order of mm.

4. The method for virtual stent implantation and stent optimization in the ascending aorta according to claim 3, characterized in that, The assembly in step 4 includes: aligning the midpoints of the proximal cross-sections of the three-dimensional models of the support, delivery sheath, and virtual target delivery sheath, and placing them together in the proximal release area of ​​the target; Step 4, assigning material properties and generating a mesh, includes: The coating of the membrane-coated stent is made of PET or ePTFE material and is discretized using membrane units; Both the covered and uncovered scaffolds are made of nickel-titanium alloy metal material and are discretized using beam elements or three-dimensional solid elements; The mechanical behavior of the blood vessel wall model is described by linear elastic or hyperelastic constitutive equations. During the discretization of the blood vessel wall model, three-dimensional solid elements or shell elements are used for mesh generation. The delivery sheath and the virtual target delivery sheath do not specify material properties and are discretized using surface elements or shell elements. The grid is divided so that the number of grid nodes and grid cells of the delivery sheath and the virtual target delivery sheath are the same, and the numbering order is consistent, with a one-to-one correspondence.

5. The method for virtual stent implantation and stent optimization in the ascending aorta according to claim 2, characterized in that, Step 5 specifically includes: Step 5-1: Determine the diastolic pressure based on the patient's clinical data. Set the boundary conditions of the three branches of the ascending aorta—proximal, distal, and arch—to parameters for cardiac diastole. Specifically, fix the circumferential direction and set the corresponding pre-stretch amount in the axial direction based on imaging methods, all between 0.8 and 2. After setting, perform finite element calculations. Step 5-2: Obtain the coordinates of each node in the blood vessel wall model after the finite element calculation is completed. and the coordinates of each node before calculation Calculate the coordinate difference between the two. And set a coefficient k, k Calculate the coordinates of each node in the new model. : Using the new model Then perform finite element calculations again; Step 5-3: Perform iterative calculations as in Step 5-2 until the coordinates of all nodes are obtained after the nth calculation. All meet Coordinates before this calculation The represented configuration is the initial configuration without applied blood pressure and boundary conditions.

6. The method for virtual stent implantation and stent optimization in the ascending aorta according to claim 1, characterized in that, Step 6 specifically includes: Step 6-1: Apply initial blood pressure and diastolic boundary condition parameters to the initial blood vessel wall model to obtain in-situ stress information of the blood vessel wall; Step 6-2: Export the coordinate values ​​and corresponding node numbers of each node on the transport sheath and the virtual target transport sheath. Calculate the coordinate difference between the corresponding nodes of the transport sheath model and the virtual target transport sheath model. Drive the nodes of the transport sheath model to generate corresponding displacements through the displacement control subroutine method of the finite element software, so as to move the nodes on the transport sheath to the corresponding node positions of the virtual target transport sheath. Step 6-3: Release the stent step by step in the set sequence, while activating the interaction between the stent and the blood vessel wall, so that the stent contacts the blood vessel wall. The contact can be hard or soft, and a specific amount of friction is specified.

7. The method for virtual stent implantation and stent optimization in the ascending aorta according to claim 5, characterized in that, Step 7 specifically includes: Based on the patient's clinical data, the systolic blood pressure was determined and applied to the finite element model. Using imaging methods, the displacement and velocity of the three branches of the ascending aorta—proximal, distal, and arch—during cardiac systole were measured. Based on the measurement results, the boundary conditions of the ascending aorta were modified. Specifically, the corresponding systolic displacement or velocity of the three branches of the ascending aorta were set as their respective boundary conditions to simulate the motion of the ascending aorta during cardiac systole and diastole.

8. The method for virtual stent implantation and stent optimization in the ascending aorta according to claim 1, characterized in that, The stent implantation effect evaluation indicators output in step 8 include: the coverage of each wire section of the stent in the vessel wall before and after changing the boundary conditions of the ascending aorta, the maximum principal stress of the vessel wall, the maximum value and location of Von Mises stress, and the maximum value and location of shear stress of the vessel wall.

9. The method for virtual stent implantation and stent optimization in the ascending aorta according to claim 1, characterized in that, Step 9 includes: An orthogonal experimental design method was used to optimize at least one of the following structural parameters: diameter of the support, number of wires, wire height, number of crests and troughs, and wire thickness.

10. The method for virtual stent implantation and stent optimization in the ascending aorta according to claim 1, characterized in that, The method also includes a verification step: using medical images of multiple other patients, virtual implantation simulations are performed using stent configurations before and after optimization, and the stent implantation effect evaluation indicators are compared to verify the universality of the optimization effect.

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