Method, electronic device and storage medium for simulating coil placement in aneurysms

Abstract

The present disclosure discloses a method, electronic device, and storage medium for simulating coil placement in an aneurysm. The method includes: obtaining a coil model, a three-dimensional rigid body model, and an aneurysm model, wherein the coil model is a non-rigid body model; compressing the coil model using the three-dimensional rigid body model; placing the compressed coil model into the aneurysm model so that the coil model deforms under its own internal force; and obtaining a final simulation result in response to the deformation parameters of the coil model meeting a preset condition. Through the solution of the embodiment of the present disclosure, it is possible to impose constraints on the non-rigid coil model through the three-dimensional rigid body model, and use the internal force of the coil model itself to achieve expansion deformation in the aneurysm model, thereby directly simulating the coil compression and placement process quickly through physical methods, which can improve the simulation speed and have higher clinical value for emergency clinical scenarios.

Description

Technical Field

[0001] The present disclosure generally relates to the field of simulation technology. More specifically, the present disclosure relates to a method, electronic device, and storage medium for simulating coil placement in an aneurysm. Background Art

[0002] Intracranial aneurysms are a common cerebrovascular disease in neurosurgery. They occur when a weak spot in the wall of an intracranial artery bulges abnormally due to blood flow and pressure. Because of their tumor-like appearance, they are called intracranial aneurysms. While the overall prevalence is approximately 3% to 5%, rupture and subarachnoid hemorrhage can have a mortality rate of up to 40%.

[0003] Currently, conventional treatments typically utilize stent-assisted coils to embolize the aneurysm cavity, mitigating the impact of blood flow on the aneurysm wall, inducing thrombosis within the cavity, and ultimately sealing the aneurysm. During treatment, coil selection plays a crucial role in embolization effectiveness. To improve coil selection accuracy, simulation technology can be used to simulate the morphology of various coil types after release within the aneurysm, providing a more accurate and reliable reference for coil selection.

[0004] One existing simulation approach uses finite element analysis (FEA) to simulate the entire coil insertion process, including its contraction into a microcatheter and its gradual release into the aneurysm. This method is slow, typically taking more than a dozen hours or even days, making it less suitable for urgent clinical scenarios.

[0005] In view of this, there is an urgent need to provide a solution for simulating coil placement in aneurysms, so as to speed up the speed of simulating coil placement in aneurysms, facilitate on-site real-time simulation, and adapt to emergency clinical scenarios. Summary of the Invention

[0006] In order to at least solve one or more technical problems mentioned above, the present disclosure proposes a solution for simulating coil placement in an aneurysm in multiple aspects.

[0007] In a first aspect, the present disclosure provides a method for simulating coil placement in an aneurysm, comprising: obtaining a coil model, a three-dimensional rigid body model, and an aneurysm model, wherein the coil model is a non-rigid body model; compressing the coil model using the three-dimensional rigid body model; placing the compressed coil model into the aneurysm model so that the coil model deforms under its own internal force; and obtaining a final simulation result in response to the deformation parameters of the coil model satisfying preset conditions.

[0008] In some embodiments, the deformation parameters include: the number of deformation iterations or the deformation change between two adjacent time steps, and the preset conditions include: the number of deformation iterations is greater than or equal to the preset number of iterations or the deformation change is less than or equal to the deformation threshold.

[0009] In some embodiments, compressing the spring coil model using the three-dimensional rigid body model includes: placing the spring coil model into the three-dimensional rigid body model; and gradually shrinking the three-dimensional rigid body model so that the spring coil model is compressed under the constraint.

[0010] In some embodiments, gradually reducing the three-dimensional rigid body model includes: gradually reducing the three-dimensional rigid body model until its maximum point distance is less than or equal to the inscribed sphere diameter of the aneurysm model, thereby obtaining a compressed coil model; wherein the maximum point distance of the three-dimensional rigid body model refers to the maximum straight-line distance between two points on the three-dimensional rigid body model.

[0011] In some embodiments, where the deformation change is a mean Euclidean distance, after the compressed coil model is placed into the aneurysm model so that the coil model deforms under its own internal force, the method further includes: calculating the mean Euclidean distance between the coil model at the current time step and the coil model at the previous time step; determining whether the mean Euclidean distance is less than or equal to a deformation variable threshold; and if so, determining that the deformation parameters of the coil model meet preset conditions.

[0012] In some embodiments, after the compressed coil model is placed into the aneurysm model so that the coil model deforms under its own internal force, the method further includes: calculating the number of deformation iterations according to the time step; determining whether the number of deformation iterations is greater than or equal to a preset number of iterations; if so, determining that the deformation parameters of the coil model meet the preset conditions; and if not, returning to the step of calculating the number of deformation iterations after the time step is updated until the deformation parameters of the coil model meet the preset conditions.

[0013] In some embodiments, obtaining the coil model, the three-dimensional rigid body model and the aneurysm model includes: determining the spatial information and geometric information of the aneurysm and the secondary spiral radius and length information of the coil; constructing the aneurysm model based on the spatial information and geometric information; constructing the coil model based on the secondary spiral radius and length information; calculating the initial size of the three-dimensional rigid body model according to the secondary spiral radius; and constructing the three-dimensional rigid body model based on the initial size and spatial information of the three-dimensional rigid body model.

[0014] In some embodiments, in the coil model, the three-dimensional rigid body model, and the aneurysm model, the offset of the center points between any two models is less than or equal to a preset value.

[0015] In some embodiments, the three-dimensional rigid body model includes a spherical rigid body model, and the initial size of the three-dimensional rigid body model includes an initial diameter.

[0016] In some embodiments, calculating the initial size of the three-dimensional rigid body model includes: sphere =2×(R c +Buffer) to calculate the initial diameter of the spherical rigid body model, where D sphere Represents the initial diameter of the spherical rigid body model, R c It represents the secondary spiral radius of the spring coil, and Buffer represents the center offset.

[0017] In some embodiments, the spring coil model is a discrete elastic rod model.

[0018] In a second aspect, the present disclosure provides an electronic device comprising: a processor; and a memory storing executable program instructions, wherein when the program instructions are executed by the processor, the device implements the method according to any one of the first aspects.

[0019] In a third aspect, the present disclosure provides a computer-readable storage medium having computer-readable instructions stored thereon, which, when executed by one or more processors, implement the method of any one of the first aspects.

[0020] Through the method for simulating coil placement in an aneurysm as provided above, the disclosed embodiment imposes constraints on the non-rigid coil model through a three-dimensional rigid model to achieve rapid simulation of the coil compression process, thereby facilitating the subsequent simulation of the coil placement in the aneurysm. In addition, boundary constraints are set on the expansion deformation of the non-rigid coil model through the aneurysm model, and the expansion deformation is achieved by utilizing the internal force of the coil model itself, thereby completing the rapid simulation of the release morphology after the coil is placed in the aneurysm. In the above process, there is no need to use mathematical approximation methods to define the solution model. The coil placement simulation process can be quickly simulated directly through physical methods. Compared with the finite element analysis method, the simulation speed is improved, and the simulation time can be reduced to seconds, which is more conducive to on-site real-time simulation and has higher clinical value for emergency clinical scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and other objects, features and advantages of the exemplary embodiments of the present disclosure will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present disclosure are shown in an illustrative and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0022] Figure 1 An exemplary flow chart illustrating a method for simulating coil placement in an aneurysm according to some embodiments of the present disclosure is shown;

[0023] Figure 2 An exemplary flow chart showing a method for simulating coil placement in an aneurysm according to other embodiments of the present disclosure;

[0024] Figure 3 An exemplary flow chart showing a method for simulating coil placement in an aneurysm according to yet other embodiments of the present disclosure;

[0025] Figure 4 An exemplary flow chart showing a method for simulating coil placement in an aneurysm according to yet other embodiments of the present disclosure;

[0026] Figure 5 An exemplary flow chart of a model building method according to an embodiment of the present disclosure is shown;

[0027] Figure 6 An exemplary structural block diagram of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0028] The following will clearly and completely describe the technical solutions in the embodiments of this disclosure in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this disclosure, not all of them. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this disclosure.

[0029] It should be understood that the terms “include” and “comprising” used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0030] It should also be understood that the terminology used in this disclosure is for the purpose of describing specific embodiments only and is not intended to limit the disclosure. As used in this disclosure and the claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should be further understood that the term "and / or" as used in this disclosure and the claims refers to any and all possible combinations of one or more of the associated listed items, including and including these combinations.

[0031] As used in this specification and claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0032] The specific embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0033] Example application scenarios

[0034] For cerebrovascular diseases such as intracranial aneurysms, surgical devices such as coils are usually used clinically to embolize the aneurysm cavity, thereby slowing down the impact of blood flow on the aneurysm wall, inducing thrombosis in the aneurysm cavity, and ultimately achieving the effect of sealing the aneurysm cavity.

[0035] Existing technical solutions typically use a finite element analysis (FEA)-based approach to simulate coil placement into intracranial aneurysms and assist physicians in coil selection. This approach uses mathematical approximations to define a solution model and simulate the entire coil placement process, including its contraction into a microcatheter and its gradual release into the aneurysm. This FEA-based simulation is slow, typically taking more than a dozen hours or even days, making it less suitable for urgent clinical scenarios.

[0036] Exemplary application scenarios

[0037] In view of this, the disclosed embodiment provides a solution for simulating coil placement in an aneurysm, which imposes constraints on a non-rigid coil model through a rigid body model, and utilizes the internal force of the coil model itself to achieve expansion deformation, thereby directly simulating the coil compression and placement process quickly through physical methods, which can improve the simulation speed and has higher clinical value for emergency clinical scenarios.

[0038] Figure 1An exemplary flow chart of a method 100 for simulating coil placement in an aneurysm according to some embodiments of the present disclosure is shown. As shown in the figure, in step S101, a coil model, a three-dimensional rigid body model, and an aneurysm model are obtained. The three-dimensional rigid body model is a rigid body model, which refers to an object model whose shape and size remain unchanged during motion and after being subjected to force, and the relative positions of various internal points remain unchanged. Although an absolutely rigid body does not actually exist, it is only an ideal model. Because any object will deform to some extent after being subjected to force, if the degree of deformation is extremely small relative to the object's own geometric dimensions, the deformation can be ignored when studying the object's motion.

[0039] In this embodiment, the three-dimensional rigid body model is used to compress the coil model to a shape that can be placed inside the aneurysm. At this time, the three-dimensional rigid body model is equivalent to an object used to simulate the application of force toward the interior of the coil model. Therefore, its deformation is not a content that needs to be considered. In order to reduce the influence of irrelevant variables, step S101 directly regards it as a rigid body model.

[0040] In this embodiment, the aneurysm model can also be a rigid body model. The aneurysm model is a model of the target aneurysm for coil placement during actual clinical procedures. Generally, the aneurysm deforms slightly during coil insertion. Therefore, when simulating coil placement, the aneurysm model can be set as a rigid body model to further improve simulation speed. In other embodiments, where simulation speed is not a requirement, the model can be set as a flexible body to achieve a more realistic simulation.

[0041] In this embodiment, the spring coil model is a non-rigid body model, and its shape and size will change under the influence of the applied force. As an example, the spring coil model can adopt a discrete elastic rod model. The discrete elastic rod (DER) model is a discretized version of Kirchhoff's elastic rod model. It can be calculated using spatial parallel transport and temporal parallel transport methods. The temporal parallel transport method can simulate the motion dynamics of the elastic rod after expansion, contraction, bending, and twisting.

[0042] The following is a brief introduction to the two parallel transport methods. First, it should be noted that for two line segments, their tangent vectors can be calculated first, and then the coordinate frame defined above can be transferred to the other through the tangent vectors of the two line segments.

[0043] At the end of the elastic strip, a random coordinate frame is first defined. This is then iteratively transferred to the end of the strip via parallel transport along the strip's direction. The strip can be discretized into multiple line segments. During the parallel transport process, the coordinate frame on each line segment serves as the initial reference coordinate frame for that line segment. Because the spring forming the coil is a smooth curve, the coordinate frame obtained through parallel transport is called the minimum distortion coordinate frame. The initial reference coordinate frame can be considered a discretized version of the minimum distortion coordinate frame. This parallel transport process is also known as spatial parallel transport.

[0044] After updating the end position of the elastic bar from the first moment to the second moment (the time between the two moments is called a time step), the reference coordinate frame must also be updated. Here, the coordinate frame of each line segment of the elastic bar at the first moment is transported in parallel to the second moment according to the tangent at the first moment and the tangent at the second moment. This transportation process is called time-series parallel transportation.

[0045] The spring coil model constructed based on the DER model can realize the dynamic simulation of objects with elastic strip characteristics. Compared with the traditional finite element analysis method, it greatly simplifies the computational complexity of the simulation while ensuring accuracy.

[0046] In step S102, the coil model is compressed using the 3D rigid body model. Since the 3D rigid body model has a constant shape and size, it acts as a fixed boundary. Wrapping the coil model with the 3D rigid body model can set a boundary constraint for the coil model, thereby compressing the coil model within a fixed boundary to ensure that it can be inserted into the aneurysm model.

[0047] In step S103, the compressed coil model is placed into the aneurysm model. Because the boundary formed by the aneurysm model differs from that formed by the 3D rigid body model, the boundary constraints imposed on the coil model have changed. Therefore, after the compressed coil model is placed into the aneurysm model, it gradually expands and deforms under the influence of the coil model's internal forces, which refer to the spring elastic force.

[0048] Furthermore, in some embodiments, when the spring coil model adopts the DER model, according to the time-series parallel transport method used by the DER model, the unfolding deformation of the spring coil model can be analyzed based on the morphology at different time steps.

[0049] In step S104, in response to the deformation parameters of the spring coil model satisfying preset conditions, a final simulation result is obtained. In some embodiments, the end of the simulation can be determined based on the number of deformation iterations. In other embodiments, the end of the simulation can be determined based on the deformation change. It is understood that the deformation parameter includes: the number of deformation iterations or the deformation change, where the deformation change refers to the deformation change of the spring coil model between two adjacent time steps. Furthermore, the deformation change can be characterized by the mean Euclidean distance.

[0050] As an example, when the deformation parameter includes the number of deformation iterations, the preset condition includes: the number of deformation iterations is greater than or equal to the preset number of iterations. As another example, when the deformation parameter includes the deformation change, the preset condition includes: the deformation change is less than or equal to the deformation change threshold. It should be noted that the above two preset conditions can be used separately or in combination. When used in combination, the simulation is concluded when the deformation parameters of the spring coil model meet either of the preset conditions.

[0051] Taking the case where the deformation parameter includes the deformation variation as an example, Figure 2 An exemplary flow chart of a method 200 for simulating coil placement in an aneurysm according to another embodiment of the present disclosure is shown. Figure 2 As shown, in step S201, a coil model, a three-dimensional rigid body model, and an aneurysm model are obtained. It should be noted that, in this embodiment, the content of step S201 is consistent with step S101 in the above embodiment, and will not be repeated here.

[0052] In step S202, the spring coil model is compressed using the three-dimensional rigid body model. It should be noted that, in this embodiment, the content of step S202 is consistent with step S102 in the above embodiment, and will not be repeated here.

[0053] In step S203, the compressed coil model is placed into the aneurysm model. It should be noted that in this embodiment, the content of step S203 is consistent with step S103 in the above embodiment and will not be repeated here.

[0054] In step S204, the mean Euclidean distance between the spring coil model at the current time step and the spring coil model at the previous time step is calculated. When the spring coil model adopts the DER model, the morphology of the spring coil model at each time step can be simulated and calculated using the time-series parallel transport method. The deformation change of the spring coil model can be calculated based on the morphology at two adjacent time steps. This deformation change can be represented by the mean Euclidean distance.

[0055] The Euclidean distance measures the absolute distance between two points in a multidimensional space. In this embodiment, step S204 can calculate the Euclidean distance of each point in the spring coil model at two time steps, and then obtain the mean of the Euclidean distances of all points in the spring coil model by taking the mean, thereby measuring the absolute distance of the entire spring coil model at two time steps, and further reflecting the deformation change of the spring coil model in two adjacent time steps.

[0056] In step S205, it is determined whether the mean Euclidean distance is less than or equal to the deformation threshold. If so, step S206 is executed; if not, the process returns to step S204. The deformation threshold can be set to 0 or another positive number. When the mean Euclidean distance is equal to 0, it can be considered that the shape of the coil model is consistent in two adjacent time steps, indicating that the coil model has been expanded and deformed to the limit. The limit here refers to the limit under the constraint of the aneurysm model. The shape of the coil model will no longer change with time steps, so the simulation can be determined to be over. Similarly, when the mean Euclidean distance is less than or equal to the deformation threshold, it can be considered that the deformation of the coil model in the next time step is negligible, so the simulation can be determined to be over.

[0057] Conversely, if the mean Euclidean distance is greater than the deformation threshold, it is necessary to continue determining whether the spring coil model has reached its deformation limit compared to the current time step. That is, after determining that the mean Euclidean distance is greater than the deformation threshold, it is necessary to return to recalculate the mean Euclidean distance after the time step is updated.

[0058] In step S206, the final simulation result is obtained. In this embodiment, when the mean Euclidean distance is less than or equal to the deformation variable threshold, the deformation parameter of the spring coil model is determined to meet the preset condition. In this case, the preset condition is that the deformation change is less than or equal to the deformation variable threshold. The simulation ends and the final simulation result is obtained.

[0059] The following example takes the case where the deformation parameters include the number of deformation iterations. Figure 3 An exemplary flow chart illustrating a method 300 for simulating coil placement in an aneurysm according to yet other embodiments of the present disclosure is shown.

[0060] like Figure 3 As shown, in step S301, a coil model, a three-dimensional rigid body model, and an aneurysm model are obtained. It should be noted that, in this embodiment, the content of step S301 is consistent with step S101 and step S201 in the above embodiment, and will not be repeated here.

[0061] In step S302, the spring coil model is compressed using a three-dimensional rigid body model. It should be noted that, in this embodiment, the content of step S302 is consistent with step S102 and step S202 in the above embodiment, and will not be repeated here.

[0062] In step S303, the compressed coil model is placed into the aneurysm model. It should be noted that in this embodiment, the content of step S303 is consistent with step S103 and step S203 in the above embodiment, and will not be repeated here.

[0063] In step S304, the number of deformation iterations is calculated based on the time step. In this embodiment, when the spring coil model adopts the DER model, the morphology of the spring coil model at each time step can be simulated and calculated using the time-series parallel transport method. In this case, it can be considered that the morphology of the spring coil model completes an iterative update with each time step, so the number of deformation iterations can be calculated based on the time step.

[0064] In step S305, a determination is made as to whether the number of deformation iterations is greater than or equal to a preset number of iterations. If so, step S306 is executed; if not, the process returns to step S304. In this embodiment, to prevent the spring coil model from looping indefinitely, a preset number of iterations is set as a condition for terminating the iterations. This preset number of iterations can be set based on actual needs and is not subject to excessive restrictions.

[0065] In step S306, the final simulation result is obtained. When the number of deformation iterations reaches the preset number of iterations, the deformation parameters of the spring coil model are determined to meet the preset conditions, the simulation ends, and the final simulation result is obtained. Conversely, if the number of deformation iterations does not reach the preset number of iterations, the process returns to the step of calculating the number of deformation iterations after the time step is updated, and the process continues until the number of deformation iterations reaches the preset number of iterations and the deformation parameters of the spring coil model meet the preset conditions.

[0066] Furthermore, the above combined Figure 2 and Figure 3 The described methods can also be combined to determine the end of the simulation using both the number of deformation iterations and the amount of deformation change. Specifically, when the number of deformation iterations is greater than or equal to a preset number of iterations, or the mean Euclidean distance is less than or equal to a deformation threshold, the deformation parameters of the spring coil model are determined to meet the preset conditions, and the simulation ends. When the number of deformation iterations is less than the preset number of iterations, and the mean Euclidean distance is greater than the deformation threshold, the deformation parameters of the spring coil model are determined to not meet the preset conditions, and the simulation continues.

[0067] Combined with the previous Figure 1-Figure 3In the embodiment described, in order to ensure that the compressed coil model can be smoothly placed inside the aneurysm model, it is necessary to design the boundary constraints imposed on the three-dimensional rigid body model. Figure 4 The simulation method shown here explains the compression process of the spring coil model.

[0068] Figure 4 An exemplary flow chart of a method 400 for simulating coil placement in an aneurysm according to some other embodiments of the present disclosure is shown. Figure 4 As shown, in step S401, a coil model, a three-dimensional rigid body model, and an aneurysm model are obtained. It should be noted that, in this embodiment, the content of step S401 is consistent with steps S101, S201, and S301 in the above embodiments, and will not be repeated here.

[0069] In step S402, the spring coil model is placed into the three-dimensional rigid body model. At the beginning of compression, the spring coil model needs to be wrapped with the three-dimensional rigid body model. In order to form a wrapped shape, the initial size and initial shape of the three-dimensional rigid body model need to be designed according to the size and shape of the spring coil model.

[0070] It should be noted that clinically used coils come in different sizes and models from different manufacturers. Each coil has corresponding identification information describing its structural parameters. Therefore, a coil model with a pre-set geometric shape can be constructed based on this identification information. The three-dimensional rigid body model used in step S402 can calculate its initial size and shape based on the size and shape of the coil model with the pre-set geometric shape.

[0071] As an example, the three-dimensional rigid body model used in this embodiment may be a spherical rigid body model. The spherical three-dimensional rigid body model can better fit the shape of the spring coil model and better complete the wrapping.

[0072] In step S403, the three-dimensional rigid body model is gradually reduced. In this step, the three-dimensional rigid body model is gradually reduced. Since the shape and size of the rigid body model are not affected by the applied force, the spring coil model is compressed under the action of the constraint during the process of gradually reducing the three-dimensional rigid body model. However, the boundary constraint imposed on the three-dimensional rigid body model is not changed due to the elastic force of the spring coil model.

[0073] In the present disclosure, the purpose of compressing the coil model is to enable the compressed coil model to be smoothly placed in the aneurysm model. Therefore, the coil model needs to be compressed to a smaller size. In order to avoid unlimited or excessive compression, this embodiment sets a compression stop condition.

[0074] As an example, the diameter of the inscribed sphere of the aneurysm model can be used as a reference standard for the compression stop condition. Specifically, in step S403, the 3D rigid model is gradually reduced until its maximum point distance is less than or equal to the inscribed sphere diameter of the aneurysm model, thereby obtaining a compressed coil model. The maximum point distance of the 3D rigid model refers to the maximum straight-line distance between two points on the 3D rigid model. For example, if the 3D rigid model is a spherical rigid model, step S403 can gradually reduce the diameter of the spherical rigid model until the diameter of the spherical rigid model is less than or equal to the inscribed sphere diameter of the aneurysm model.

[0075] Since the coil model is wrapped inside the three-dimensional rigid body model, when the maximum point distance of the three-dimensional rigid body model is less than or equal to the inscribed sphere diameter of the aneurysm model, it means that the maximum point distance of the coil model is less than or equal to the inscribed sphere diameter of the aneurysm model. At this time, when the centers of the coil model and the aneurysm model coincide, it can be guaranteed that any point on the coil model is located inside the aneurysm model, that is, the coil model can be completely placed in the aneurysm model.

[0076] Furthermore, when the aneurysm model is set as a rigid body model, its inscribed sphere diameter is determined as a fixed value. When the aneurysm model is set as a flexible body model, the inscribed sphere diameter is calculated based on the static morphology of the target aneurysm under natural conditions without human intervention. For example, considering the influence of patient blood flow parameters on the target aneurysm morphology, the inscribed sphere diameter can be determined based on the 3D medical images used during modeling to obtain a fixed value.

[0077] In step S404, the compressed coil model is placed into the aneurysm model. During the placement process, the center of the compressed coil model is aligned with the center of the aneurysm model to ensure that the coil model can be completely placed into the aneurysm model.

[0078] In step S405, in response to the deformation parameters of the spring coil model meeting the preset conditions, the final simulation result is obtained. It should be noted that in this embodiment, the content of step S405 is consistent with step S104 in the above embodiment and will not be repeated here.

[0079] In this embodiment, the preset conditions may also include: the number of deformation iterations is greater than or equal to the preset number of iterations or the deformation change is less than or equal to the deformation threshold. The judgment process of the two preset conditions has been combined in the previous text. Figure 2 and Figure 3 The embodiments described are described in detail and will not be elaborated here.

[0080] The following will continue to explain the construction process of the three models disclosed in this disclosure: the coil model, the three-dimensional rigid body model, and the aneurysm model. Figure 5FIG1 shows an exemplary flow chart of the model building method 500 of the embodiment of the present disclosure. It can be understood that the model building method is a specific implementation of the aforementioned steps S101, S201, S301 and S401. Figure 5 The features described can be similarly applied to the above combined Figure 1-4 Described method.

[0081] It should be noted that in Figure 5 The illustrated method relies on spatial and geometric information of the aneurysm and coil to complete model construction. Spatial information is used to determine the model's center point during model placement, enabling operations such as inserting the coil model into the aneurysm model. Geometric information provides structural parameters to construct a matching model.

[0082] like Figure 5 As shown, in step S501, the spatial and geometric information of the aneurysm and the secondary spiral radius and length information of the coil are determined. Here, the aneurysm refers to the target aneurysm identified based on the patient's three-dimensional medical image, and is also the target surgical area where the coil is actually placed for treatment.

[0083] In this embodiment, spring coils are categorized into two types based on shape: 2D and 3D. 3D coils are primarily used for basket formation and are often the preferred starting point for packing. 2D coils are primarily used for filling. The primary structure of a coil can be understood as a coil formed by winding a thin wire around a cylinder, representing the basic spring form. The winding radius in this case can also be understood as the primary helical radius. A 2D coil is formed by winding a thin wire around a cylinder to form a helical structure. The radius of the secondary winding is the secondary helical radius. A 3D coil is formed by winding the primary structure of the coil into a sphere. The radius of this sphere is the secondary helical radius of the 3D coil. The coil length information represents the length of the coils that make up the 2D and 3D coils.

[0084] In step S502, an aneurysm model is constructed based on the spatial and geometric information. In this embodiment, the spatial information of the aneurysm is primarily used to calculate the spatial center point of the aneurysm model, which can be the average of the coordinates of all points. The geometric information of the aneurysm reflects the size and shape of the aneurysm. Using this geometric information, a 1:1 restored aneurysm model can be constructed, thereby better simulating the internal space of the aneurysm and providing more realistic boundary constraints for the deformation of the coil model.

[0085] In step S503, a coil model is constructed based on the secondary helical radius and length information. In some embodiments, before step S503, the type of coil may be determined. For example, after confirming that the coil is a 3D coil, a coil model of the 3D coil may be constructed based on the secondary helical radius and length information.

[0086] It should be noted that the above-mentioned secondary spiral radius and length information may be the content in the identification information of the spring coil, and a spring coil model with a preset geometric shape may be constructed based on the information.

[0087] In step S504, the initial size of the three-dimensional rigid body model is calculated based on the secondary helical radius. Since the spring coil model needs to be wrapped with the three-dimensional rigid body model at the beginning of compression, in order to form the wrapped shape, the initial size and initial shape of the three-dimensional rigid body model need to be calculated based on the size and shape of the spring coil model. As an example, the three-dimensional rigid body model includes a spherical rigid body model, and the initial size of the three-dimensional rigid body model includes an initial diameter. Furthermore, the calculation formula for the initial diameter of the spherical rigid body model is as follows:

[0088] D sphere =2×(R c +Buffer);

[0089] Among them, D sphere Represents the initial diameter of the spherical rigid body model, R c It represents the secondary spiral radius of the spring coil, and Buffer represents the center offset.

[0090] It's important to note that the center offset is set to prevent the 3D rigid body model from completely enveloping the coil model due to misalignment of their spatial centers when wrapping the coil model. This could affect the coil model's compression process. This center offset provides an allowable deviation range for the center alignment of the coil model and the 3D rigid body model.

[0091] Similar to the above description, in this embodiment, the center alignment operation of the coil model and the aneurysm model also has an allowable deviation range. Therefore, in this embodiment, it is required that the offset between the center points of the coil model, the three-dimensional rigid body model, and the aneurysm model is less than or equal to a preset value. The preset value can be 0 or a positive number. When the preset value is 0, the spatial center points of the three models are required to coincide. When the preset value is a positive number, a certain deviation between the spatial center points of the three models is allowed. In this case, the deviation of the spatial center points can be compensated by setting the center offset when calculating the initial size of the three-dimensional rigid body model to ensure that the three-dimensional rigid body model can completely enclose the coil model.

[0092] In step S505, a three-dimensional rigid body model is constructed based on the initial size and spatial information of the three-dimensional rigid body model. It should be noted that the spatial information in this step refers to the spatial information of the aneurysm model.

[0093] When compressing the coil model, since the coil model has been placed in the three-dimensional rigid body model and the spatial center point of the coil model is aligned with the spatial center point of the three-dimensional rigid body model, the spatial information of the aneurysm model can be referenced when constructing the three-dimensional rigid body model, so that the spatial center points of the three-dimensional rigid body model and the aneurysm model can be aligned. Then, after the compression of the coil model is completed, it is only necessary to remove the three-dimensional rigid body model to complete the action of placing the coil in the aneurysm model, using the spatial center point of the three-dimensional rigid body model as a bridge. At this time, it can also be ensured that the spatial center points of the coil model and the aneurysm model are aligned.

[0094] In summary, the disclosed embodiments provide a method for simulating coil placement in an aneurysm. This method uses a three-dimensional rigid model to constrain a non-rigid coil model, enabling rapid simulation of the coil compression process. The aneurysm model then sets boundary constraints on the expansion deformation of the non-rigid coil model, utilizing the coil model's own internal forces to achieve expansion deformation, thereby rapidly simulating the coil's release morphology after placement in the aneurysm. Compared to methods based on finite element analysis, the disclosed embodiments do not require mathematical approximation to define the solution model. Instead, the coil placement process can be rapidly simulated directly through physical methods, improving simulation speed and reducing simulation time to seconds. This is more conducive to on-site real-time simulation and has higher clinical value for emergency clinical scenarios.

[0095] In addition, another embodiment of the present disclosure provides a method for simulating coil placement in an aneurysm, which uses the number of deformation iterations or the amount of deformation change as a judgment condition for the end of the simulation to prevent unlimited simulation iterations and unnecessary loss of computing resources.

[0096] In addition, another embodiment of the present disclosure provides a method for simulating coil placement in an aneurysm. This method compresses the coil model by gradually reducing the size of the three-dimensional rigid body model, and uses the diameter of the sphere inscribed in the aneurysm model as the compression end condition. While ensuring that the coil model can be successfully placed in the aneurysm model, the time and resources required for compression are minimized as much as possible.

[0097] In order to implement the method steps described in the above text of this disclosure in conjunction with the accompanying drawings at the software and hardware level, the present disclosure embodiment also provides the following Figure 6 The electronic device shown. Specifically, Figure 6 An exemplary structural block diagram of an electronic device 600 according to an embodiment of the present disclosure is shown.

[0098] like Figure 6 As shown, the electronic device 600 disclosed herein may include a processor 610 and a memory 620. Specifically, the memory 620 stores executable program instructions. When the program instructions are executed by the processor 610, the electronic device implements the aforementioned Figure 1-Figure 5 Described method steps.

[0099] It is understood that in order to clearly illustrate the solution of the present disclosure and avoid confusion with the prior art, Figure 6 The electronic device 600 only shows the components related to the embodiment of the present disclosure, and omits those components that may be necessary for implementing the embodiment of the present disclosure but belong to the scope of the prior art. Therefore, based on the content disclosed in the present disclosure, a person skilled in the art can clearly understand that the electronic device 600 of the present disclosure may also include components related to the embodiment of the present disclosure. Figure 6 The constituent elements shown in are different from the common constituent elements.

[0100] In an exemplary implementation scenario, the above-mentioned processor 610 can control the overall operation of the electronic device 600. For example, the processor 610 can control the operation of the electronic device 600 by executing the program stored in the memory 620. In terms of implementation, the processor 610 of the present disclosure can be implemented by a central processing unit (CPU), an application processor (AP), an artificial intelligence processor chip (IPU), etc. provided in the electronic device 600. Further, the processor 610 of the present disclosure can also be implemented in any appropriate manner. For example, the processor 610 can take the form of a computer-readable medium, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc., such as a microprocessor or a processor and a computer-readable program code (such as software or firmware) that can be executed by the (micro) processor.

[0101] In terms of storage content, the memory 620 can be used to store hardware for various data and instructions processed by the electronic device 600. For example, the memory 620 can store processed data and data to be processed by the electronic device 600. The memory 620 can also store data sets that have been processed or are to be processed by the processor 610. Furthermore, the memory 620 can store applications, drivers, and the like to be driven by the electronic device 600. For example, the memory 620 can store various programs related to model building and conditional judgment to be executed by the processor 610. The memory 620 can be DRAM, but the present disclosure is not limited to this. In terms of type, the memory 620 can include at least one of volatile memory and non-volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, phase-change RAM (PRAM), magnetic RAM (MRAM), resistive RAM (RRAM), ferroelectric RAM (FRAM), and the like. The volatile memory may include dynamic RAM (DRAM), static RAM (SRAM), synchronous DRAM (SDRAM), PRAM, MRAM, RRAM, ferroelectric RAM (FeRAM), etc. In an embodiment, the memory 620 may include at least one of a hard disk drive (HDD), a solid-state drive (SSD), a high-density flash memory (CF), a secure digital (SD) card, a micro secure digital (Micro-SD) card, a mini secure digital (Mini-SD) card, an extreme digital (xD) card, caches, or a memory stick.

[0102] In summary, the specific functions implemented by the memory 620 and processor 610 of the electronic device 600 provided in the embodiments of this specification can be interpreted in comparison with the aforementioned embodiments in this specification, and can achieve the technical effects of the aforementioned embodiments, and will not be repeated here.

[0103] Additionally or optionally, the present disclosure may also be implemented as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) on which computer program instructions (or computer program, or computer instruction code) are stored. When the computer program instructions (or computer program, or computer instruction code) are executed by a processor of an electronic device (or electronic device, server, etc.), the processor is caused to perform part or all of the various steps of the above-mentioned method according to the present disclosure.

[0104] Although a plurality of embodiments of the present disclosure have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art may conceive of many modifications, changes, and alternatives without departing from the ideas and spirit of the present disclosure. It should be understood that in practicing the present disclosure, various alternatives to the embodiments of the present disclosure described herein may be adopted. The appended claims are intended to define the scope of protection of the present disclosure and therefore cover equivalents or alternatives within the scope of these claims.

Claims

1. A method for simulating coil placement in an aneurysm, characterized in that: include: obtaining a coil model, a three-dimensional rigid body model, and an aneurysm model, wherein the coil model is a non-rigid body model; compressing the coil model using the three-dimensional rigid body model, and using the inscribed sphere diameter of the aneurysm model as a reference standard for compression stop conditions; inserting the compressed coil model into the aneurysm model so that the coil model deforms under its own internal force; during the insertion process, aligning the center of the compressed coil model with the center of the aneurysm model; as well as In response to the deformation parameters of the spring coil model meeting a preset condition, obtaining a final simulation result; The deformation parameter includes: the deformation change between two adjacent time steps; the preset condition includes: the deformation change is less than or equal to the deformation threshold; The spring coil model is a discrete elastic rod model. The shape of the spring coil model at each time step is simulated and calculated by a time-series parallel transport method. The deformation change of the spring coil model can be calculated based on the shapes at two adjacent time steps. The three-dimensional rigid body model is a spherical rigid body model, and the calculation formula of the initial diameter of the spherical rigid body model is as follows: D sphere =2×(R c +Buffer), where D sphere Represents the initial diameter of the spherical rigid body model, R c It represents the secondary spiral radius of the spring coil, and Buffer represents the center offset.

2. The method according to claim 1, characterized in that The deformation parameter further includes: the number of deformation iterations, and the preset condition further includes: the number of deformation iterations is greater than or equal to the preset number of iterations.

3. The method according to claim 1, characterized in that Wherein compressing the spring coil model by using the three-dimensional rigid body model comprises: placing the spring coil model into the three-dimensional rigid body model; and The three-dimensional rigid body model is gradually reduced so that the spring coil model is compressed under the constraint.

4. The method according to claim 3, characterized in that Wherein gradually reducing the three-dimensional rigid body model comprises: gradually reducing the three-dimensional rigid body model until the maximum point distance is less than or equal to the inscribed sphere diameter of the aneurysm model, thereby obtaining a compressed coil model; The maximum point distance of the three-dimensional rigid body model refers to the maximum straight-line distance between two points on the three-dimensional rigid body model.

5. The method according to claim 2, characterized in that The deformation change is the mean of the Euclidean distance, and after the compressed coil model is placed into the aneurysm model so that the coil model is deformed under its own internal force, the method further includes: Calculate the mean Euclidean distance between the spring coil model at the current time step and the spring coil model at the previous time step; Determining whether the mean Euclidean distance is less than or equal to a deformation variable threshold; and If so, it is determined that the deformation parameters of the spring coil model meet the preset conditions.

6. The method according to claim 2, characterized in that The compressed coil model is placed into the aneurysm model so that the coil model is deformed under its own internal force, and the method further comprises: Calculate the number of deformation iterations based on the time step; Determine whether the number of deformation iterations is greater than or equal to the preset number of iterations; If so, it is determined that the deformation parameters of the spring coil model meet the preset conditions; and If not, the process returns to the step of calculating the number of deformation iterations after the time step is updated, until the deformation parameters of the spring coil model meet the preset conditions.

7. The method according to claim 1, characterized in that The acquisition of coil models, 3D rigid body models and aneurysm models includes: Determine the spatial and geometric information of the aneurysm and the secondary spiral radius and length information of the coil; constructing the aneurysm model based on the spatial information and the geometric information; Constructing the spring coil model based on the secondary helix radius and the length information; Calculating the initial size of the three-dimensional rigid body model according to the secondary helical radius; and The three-dimensional rigid body model is constructed based on the initial size of the three-dimensional rigid body model and the spatial information.

8. The method according to claim 7, characterized in that In the spring coil model, the three-dimensional rigid body model, and the aneurysm model, the offset of the center point between any two models is less than or equal to a preset value.

9. The method according to claim 7, characterized in that in, The initial size of the three-dimensional rigid body model includes: an initial diameter.

10. An electronic device, characterized in that: include: processor; as well as A memory storing executable program instructions, which, when executed by the processor, enables the device to implement the method according to any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by one or more processors, the method according to any one of claims 1 to 9 is implemented.

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