Microcatheter shaping device and method

Abstract

The embodiment of the present specification provides a microcatheter shaping device and method, which can be applied to the field of microcatheter intervention technology. The method comprises the following steps: constructing a target model according to scanning data; the target model comprises a key region distribution position; constructing a preliminary access path according to the key region distribution position in the target model and a target state parameter; generating a simulated microcatheter model through the preliminary access path; simulating a microcatheter advancing process by using the target model and the simulated microcatheter model, and obtaining a simulated advancing parameter; adjusting the preliminary access path and / or the simulated microcatheter model based on the simulated advancing parameter, respectively, to obtain a target access path and a target microcatheter model; the target microcatheter model is used for manufacturing an application microcatheter; and the target access path is used for indicating an advancing path of the application microcatheter. The above scheme can adjust the shape of the microcatheter according to the simulation result, and ensures the actual application effect of the microcatheter.

Description

Technical Field

[0001] This specification relates to the field of microcatheter interventional technology, and in particular to a microcatheter shaping device and method. Background Technology

[0002] Microcatheters are commonly used medical devices in interventional procedures, particularly in intracranial vascular and liver interventions. They are inserted into the patient's body through natural openings or tiny incisions on the skin's surface, guiding the catheter to the lesion area based on vascular distribution, allowing for minimally invasive treatment. This method offers advantages such as minimal trauma and rapid recovery.

[0003] In practical applications, for severely tortuous blood vessels, to ensure effective insertion of the microcatheter into the lesion area, it is necessary to pre-shape the tip of the microcatheter to match the vessel's curvature. Currently, pre-shaping of the microcatheter tip often relies on the physician's subjective judgment or directly on the three-dimensional morphology of the blood vessel to determine the microcatheter's shape. However, current methods for determining the microcatheter's shape often depend only on the correspondence between the vessel morphology and the microcatheter morphology reflected by relevant experience or rules. Due to varying circumstances in actual applications, after the microcatheter is inserted into the blood vessel, incomplete matching between the microcatheter and the vessel may affect the effectiveness of the interventional procedure. Therefore, there is an urgent need for a microcatheter shaping method that can guarantee the surgical outcome of microcatheter insertion into blood vessels. Summary of the Invention

[0004] The purpose of the embodiments in this specification is to provide a microcatheter shaping device and method to solve the problem of how to ensure the surgical effect of microcatheter insertion into blood vessels based on microcatheter shaping.

[0005] To address the aforementioned technical problems, this specification provides a microcatheter shaping device, comprising: a target model construction module for constructing a target model based on scanning data; the target model including the distribution locations of key regions; a preliminary access path construction module for constructing a preliminary access path based on the distribution locations of key regions and target state parameters in the target model; a simulated microcatheter model generation module for generating a simulated microcatheter model using the preliminary access path; a simulated propulsion parameter acquisition module for simulating the microcatheter propulsion process using the target model and the simulated microcatheter model, and acquiring simulated propulsion parameters; and a target microcatheter model acquisition module for adjusting the preliminary access path and / or the simulated microcatheter model based on the simulated propulsion parameters to obtain a target access path and a target microcatheter model; the target microcatheter model is used to manufacture an application microcatheter; and the target access path is used to indicate the propulsion path of the application microcatheter.

[0006] In some implementations, the target model construction module is used to: distinguish target scan data and key region scan data in scan data; wherein, it includes: using a segmentation model to distinguish target scan data and key region scan data from scan data; the segmentation model includes a deep learning model trained based on training samples; and constructing the target model using the target scan data and key region scan data respectively.

[0007] Based on the above implementation, distinguishing target scan data and key area scan data in the scan data includes: dividing the scan data into segmented scan data corresponding to at least two segments; distinguishing target scan data and key area scan data in each segmented scan data; correspondingly, constructing the target model using the target scan data and key area scan data respectively includes: combining the target scan data and key area scan data of each segment to construct the target model.

[0008] Based on the above implementation, dividing the target scanning data into vascular segment data corresponding to at least two segments includes: dividing the target scanning data into point cloud data corresponding to at least two segments; correspondingly, distinguishing target scanning data and key area scanning data in each vascular segment data includes: using a point cloud classification algorithm to distinguish target scanning data and key area scanning data in each point cloud data.

[0009] In some embodiments, the target model construction module is used to: acquire vascular detection parameters from target scanning data; the vascular detection parameters include target soft spot parameters and target calcification parameters; determine target surface data by combining the target soft spot parameters, target calcification parameters, key region distribution locations, and scanning data; and construct a target model based on the target surface data; the target model is an internal tetrahedral model.

[0010] Based on the above implementation, the step of constructing a target model based on the target surface data includes: calculating the normal vector corresponding to the blood vessel based on the target surface data; constructing a triangular mesh corresponding to the target surface data using a triangulation algorithm; and constructing a target model by combining the normal vector corresponding to the blood vessel and the triangular mesh corresponding to the target surface data.

[0011] Based on the aforementioned implementation method, the step of constructing a preliminary access path according to the key region distribution location and target state parameters in the target model includes: determining target state parameters based on the target model; the target state parameters include the vessel diameter and vessel curvature; determining the vessel midline based on the target state parameters; and determining the preliminary access path based on the vessel midline and the key region distribution location; wherein, it includes: determining lesion state parameters based on target scanning data; the lesion state parameters include the key region distribution location and lesion morphology parameters; and determining the starting point and ending point of the reshaped vessel based on the vessel midline, combined with the lesion state parameters and the target state parameters.

[0012] In some embodiments, the simulation propulsion parameter acquisition module is used to: acquire blood flow simulation parameters; the blood flow simulation parameters include state parameters of blood flow in the target model based on fluid dynamics simulation; combine the blood flow simulation parameters, use the target model and the simulated microcatheter model to simulate the microcatheter propulsion process, and acquire simulation propulsion parameters; determine control parameters and boundary conditions based on microcatheter intervention requirements; combine the blood flow simulation parameters, the target model and the simulated microcatheter to acquire propulsion values; and process the propulsion values ​​using the control parameters and boundary conditions to obtain simulation propulsion parameters.

[0013] In some implementations, the simulated propulsion parameters also include fine-tuning instructions input by the user; the fine-tuning instructions are instructions from the user to adjust the simulated microcatheter model and / or the initial access path during the simulated microcatheter propulsion process.

[0014] This specification also proposes a microcatheter shaping method, comprising: constructing a target model based on scanning data; the target model including the distribution locations of key regions; constructing a preliminary access path based on the distribution locations of key regions and target state parameters in the target model; generating a simulated microcatheter model using the preliminary access path; simulating the microcatheter advancement process using the target model and the simulated microcatheter model, and obtaining simulated advancement parameters; adjusting the preliminary access path and / or the simulated microcatheter model based on the simulated advancement parameters to obtain a target access path and a target microcatheter model; the target microcatheter model being used to manufacture an application microcatheter; and the target access path being used to indicate the advancement path of the application microcatheter.

[0015] This specification also proposes a computer-readable storage medium storing a computer program / instruction thereon, which, when executed, implements the above-described microcatheter shaping method.

[0016] As can be seen from the technical solutions provided in the embodiments of this specification above, the device first constructs a target model based on the target scanning data, and then constructs a preliminary access path based on the key area distribution and target state parameters in the target model. A simulated microcatheter model is generated based on the preliminary access path, and the microcatheter advancement process is simulated based on the target model and the simulated microcatheter model, and simulated advancement parameters are obtained. Finally, the preliminary access path and / or the simulated microcatheter model are adjusted based on the simulated advancement parameters to obtain the target access path and the target microcatheter model, thereby manufacturing and applying the microcatheter and performing interventional procedures based on the target access path. This solution allows for the pre-construction of relevant models of blood vessels and microcatheters, and then the simulation of the microcatheter advancement process based on the constructed models. This enables adjustments to the microcatheter morphology based on the simulation results, ensuring the actual application effect of the microcatheter and optimizing the final interventional procedure results. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a microcatheter shaping method according to an embodiment of this specification;

[0019] Figure 2 This is a schematic diagram of a target model including blood vessels and lesions, as described in an embodiment of this specification.

[0020] Figure 3 This is a schematic diagram illustrating a process for performing soft spot and calcification segmentation according to an embodiment of this specification;

[0021] Figure 4 This is a schematic diagram illustrating the process of constructing a target model according to an embodiment of this specification.

[0022] Figure 5 This is a schematic diagram of a process for extracting the midline of a blood vessel according to an embodiment of this specification;

[0023] Figure 6 This is a schematic diagram of a blood vessel midline according to an embodiment of this specification;

[0024] Figure 7 This is a schematic diagram of a process for determining a preliminary access path according to an embodiment of this specification;

[0025] Figure 8 This is a schematic diagram of a simulated microcatheter model as described in an embodiment of this specification;

[0026] Figure 9 This is a schematic diagram of a model intraoperative catheter intervention process according to an embodiment of this specification;

[0027] Figure 10 This is a schematic diagram of the structure of a shaping device according to an embodiment of this specification;

[0028] Figure 11 This is a schematic diagram of the structure of a microcatheter as described in an embodiment of this specification;

[0029] Figure 12 This is a schematic flowchart illustrating the calculation process for simulated propulsion parameters in an embodiment of this specification.

[0030] Figure 13 This is a schematic flowchart of a microcatheter shaping method according to an embodiment of this specification;

[0031] Figure 14 This is a block diagram of a microcatheter shaping device according to an embodiment of this specification. Detailed Implementation

[0032] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0033] To address the aforementioned technical problems, embodiments of this specification propose a microcatheter shaping method. The execution entity of the microcatheter shaping method can be a corresponding computing device, such as a physician's control unit within the surgical environment, an imaging cart, or a cloud server, or other computing devices. Figure 1 As shown, the microcatheter shaping method includes the following specific implementation steps.

[0034] S110: Construct a target model based on the scan data; the target model includes the distribution location of key areas.

[0035] The scan data can be data obtained from scanning a target area of ​​the patient. The target area can be, for example, the patient's vascular region, or a region including blood vessels, or other areas of the patient suitable for microcatheter intervention; there are no limitations on this. The scan data includes subcutaneous scan results for the patient, enabling the construction of a corresponding target model based on the target scan data.

[0036] It should be noted that the scan data may not only be scan data of the patient's target tissues and organs, but may also include scan data of key areas within the target area, as well as scan data of calcifications, etc. Key areas may be, for example, the lesion area of ​​the patient, or other areas where surgical procedures will be performed. Where the scan data includes scan results of key areas, the target model constructed based on the scan data includes the distribution location of the key areas. For example, the distribution location of the key areas can be used to indicate the specific location of the lesion within a blood vessel. The blood vessel may be, for example, a cerebral blood vessel, and the lesion may be a brain tumor growing on a cerebral blood vessel.

[0037] In some specific examples, the scan data may be, for example, CTA and / or CT image data, thereby ensuring the scanning effect on the patient's blood vessels and effectively completing the construction of the target model. Other forms of scan data may also be used in practical applications, and there are no restrictions on this.

[0038] The target model is a three-dimensional model constructed based on the scan data. Since scan data cannot intuitively reflect the corresponding location, such as the morphology of blood vessels, and the tortuosity of blood vessels directly affects the insertion of microcatheters during interventional surgery, a corresponding target model can be constructed based on the scan data.

[0039] Since the scan data obtained from the scan can reflect the spatial distribution of blood vessels, the scan data corresponding to the blood vessels can be extracted from the scan data, and the corresponding target model can be constructed based on the spatial location of this part of the data.

[0040] In some implementations, constructing a target model based on scan data can involve first distinguishing between target scan data and key region scan data. The target scan data and key region scan data correspond to blood vessels and lesions, respectively, ensuring that the constructed target model can effectively differentiate between them. After distinguishing between the target scan data and key region scan data, the target model is then constructed by combining both data.

[0041] In some examples, distinguishing between target scan data and key region scan data can be achieved using a segmentation model. The segmentation model is a deep learning model trained on training samples. Before applying the segmentation model, it can be pre-trained using labeled training sample data. In the training sample data, blood vessels and lesions are effectively labeled, enabling the segmentation model to effectively distinguish between blood vessels and lesions through training on the training sample data.

[0042] Specifically, the segmentation model can be, for example, the 3DUnet network model. 3DUnet uses three-dimensional data input, thus enabling effective semantic segmentation of medical images. To improve the segmentation model's performance, skip connections can be added to enhance segmentation accuracy.

[0043] like Figure 2 The diagram shown is a schematic of the constructed target model containing blood vessels and lesions, which can effectively distinguish and identify the location of blood vessels and lesions.

[0044] In practical applications, segmentation can also be achieved in other ways, and is not limited to the segmentation model described above.

[0045] In practical applications, segmentation and labeling can also be performed on other types of areas besides blood vessels and lesions. For example, corresponding labels can be set for soft plaques and calcifications in blood vessels, and soft plaques and calcifications can be identified from the target scan data. Since the parameters of soft plaques and calcifications can directly reflect the differences from those of blood vessels, the corresponding blood vessel detection parameters can be obtained directly from the target scan data, and then the relevant parameters for soft plaques and calcifications can be determined by analyzing the blood vessel detection parameters.

[0046] Specifically, vascular detection parameters can be identified from target scan data based on pre-defined definitions of soft spot and calcification parameters. These vascular detection parameters include the target soft spot and target calcification parameters corresponding to the defined parameters. In some examples, the median CT value of the blood vessel can be calculated as an adaptive threshold to segment and obtain the soft spot and calcification labels of the blood vessel.

[0047] like Figure 3 The diagram illustrates the process of segmenting soft spots and calcifications. Based on vascular labels and CT images, an adaptive threshold can be calculated. This threshold is then used to segment soft spots and calcifications, assigning them corresponding labels to ensure effective subsequent applications.

[0048] The target soft plaque parameters and target calcification parameters may include location- and state-related parameters. Based on the determined vascular detection parameters, the locations of soft plaques and calcifications can be located in the target model, thereby further improving the accuracy of the model and ensuring that the target model can be used more effectively in subsequent processes.

[0049] In practical applications, distinguishing between different tissues can be challenging. For example, lesions, including tumors, may be small and connected to cerebral blood vessels, making it difficult to directly differentiate them from the target scan data. Therefore, in some implementations, the scan data can be segmented, dividing it into segmented scan data corresponding to at least two segments. Segmenting the scan data not only simplifies the process of dividing the scan data but also improves the accuracy of distinguishing between blood vessels and lesions.

[0050] The specific segmentation method can be determined according to actual needs. For example, it can be segmented according to a fixed length or according to the degree of tortuosity of the blood vessel. The specific segmentation criteria can be set according to the actual application, and will not be elaborated here.

[0051] After segmenting the vascular data, target scan data and key region scan data can be distinguished within each segment. The target model is then constructed by combining the target scan data and key region scan data from each segment. For example, the target scan data and key region scan data from each segment can be combined separately, and then the combined data can be used to construct the model. Alternatively, models can be constructed separately for each segment, and then the target model is obtained based on the relative positional relationships between the models. The specific method of constructing the target model is not limited.

[0052] Based on the above implementation method, a point cloud classification algorithm can be used to process the target scanning data. Specifically, the target region can be segmented first, and then point cloud data corresponding to at least two segments can be generated using the segmented target regions. Then, the target scanning data and key region scanning data can be distinguished from each point cloud data segment using a point cloud classification algorithm. The specific point cloud classification algorithm and its corresponding model can be set according to the actual application requirements, and will not be elaborated here.

[0053] In some implementations, to ensure processing effectiveness, preprocessing can be performed on the input data after acquisition. Preprocessing may include resampling, such as adjusting the window width and level and normalizing the data by calculating adaptive window width and level values ​​using training data labels. Preprocessing may also include data augmentation, such as using the Frangi algorithm to enhance blood vessels after resampling to ensure the effectiveness of subsequent blood vessel model construction. Preprocessing may also include other processing methods such as denoising, which will not be elaborated here. Preprocessing can optimize the processing of target scan data in subsequent processes.

[0054] Figure 4This is a flowchart illustrating a corresponding example of this implementation process. First, input data is processed, specifically the scan data. Then, the Frangi algorithm is used for vessel enhancement. After obtaining the data, deep learning is used for brain vessel segmentation. Point clouds are then generated based on the segmented vessels, and point cloud classification is used for vessel segmentation. Finally, depth-based segmentation is used for brain tumors to obtain tumor labels. Simultaneously, based on the vessel segmentation results and CT images, soft plaques and calcifications are segmented to obtain plaque and calcification labels. This example completes the processing of the scan data, enabling the construction of the target model.

[0055] S120: Construct a preliminary entry path based on the key area distribution locations and target state parameters in the target model.

[0056] After obtaining the target model, a preliminary access path can be constructed based on it. The preliminary access path is the initially determined path for inserting a microcatheter into the target area; that is, the microcatheter moves along this preliminary access path. Specifically, since the interventional procedure involves navigating tortuous vascular segments and probing the lesion area, the preliminary access path can be constructed based on the distribution of key areas and target state parameters.

[0057] In some implementations, when the target region is a blood vessel, the preliminary approach path can be determined based on the midline of the blood vessel. Since the target model has a certain three-dimensional structure, the corresponding blood vessel midline can be determined directly based on the three-dimensional structural state of the target model.

[0058] Based on the above implementation method, to further improve the accuracy of the initial approach path determination, target surface data can be determined first, and then a target model can be constructed based on the target surface data. The target surface data may include outer surface data and inner surface data, so that the model constructed based on the target surface data is an internal tetrahedral model, that is, simultaneously simulating the passage conditions inside the blood vessel. The corresponding vessel midline is determined based on the internal tetrahedral model, making this vessel midline more consistent with the actual passage conditions of the microcatheter during interventional surgery.

[0059] Preferably, in the case where the target soft spot parameters and target calcification parameters are obtained by segmenting the scan data in the aforementioned embodiments, the target soft spot parameters, target calcification parameters, key region distribution locations and scan data can be combined to determine the corresponding target surface data, so that the target model also takes into account the influence of soft spots, calcification and other factors on the microcatheter intervention process.

[0060] The specific process of constructing a target model in the form of an internal tetrahedron can be as follows: First, calculate the normal vector corresponding to the blood vessel based on the target surface data to effectively determine the direction of blood vessel extension. Then, use a triangulation algorithm to construct a triangular mesh corresponding to the target surface data. Finally, combine the normal vector corresponding to the blood vessel and the triangular mesh corresponding to the target surface data to construct the target model, so that the target model can accurately reflect the internal and external structure of the blood vessel.

[0061] Accordingly, based on the target model, the corresponding target state parameters can be determined. These target state parameters may include the vessel diameter and vessel curvature, reflecting the morphological condition of the blood vessel.

[0062] Then, the vessel midline can be determined based on the target state parameters. For example, the vessel midline can be calculated using FastMarching, or it can be calculated using other methods.

[0063] Figure 5 This is a flowchart illustrating a specific example of extracting the midline of a blood vessel. First, target surface data is input, and the corresponding normal vector is calculated. Using the Delaunary triangulation algorithm, the scattered points are used to generate the required triangular network. Then, based on the normal vectors and the surface network, an inner tetrahedron is generated. The radius and curvature are calculated using a Voronoi diagram, and finally, the midline of the blood vessel is calculated using FastMarching. Figure 6 The diagram shows the extraction of the midline of a blood vessel, where the gray meandering part represents the blood vessel and the white line represents the midline of the corresponding blood vessel.

[0064] After obtaining the vessel midline, the initial approach path can be determined by combining the distribution of key areas. The initial approach path can correspond exactly to the vessel midline, or its location can be optimized based on the spatial distribution of the vessel midline.

[0065] Furthermore, the initial approach can also include the initiation and endpoint of the reshaping vessel. Specifically, the initiation and endpoint of the vessel that will affect the curvature of the microcatheter can be determined based on the location, morphology, and tortuosity of the lesion. Specifically, lesion status parameters, including the distribution location of key areas and lesion morphology parameters, can be determined first based on the target scan data. This allows the initiation and endpoint of the reshaping vessel to be determined based on the vessel midline, combined with the lesion status parameters and target status parameters.

[0066] To illustrate with a specific example, based on the segmented brain tumor and vascular labels, it is necessary to calculate the location of the brain tumor on the blood vessel. Then, parameters such as the angle between the aneurysm and the parent artery, the distance between the two bends (the distal bend and the proximal bend), the direction of the proximal end of the parent artery, the direction of the aneurysm, and the morphology of the aneurysm are calculated as shaping reference parameters. Then, based on the tumor location and the access route location, the access route is planned, and the start and end points of the shaped blood vessel are calculated, thereby completing the initial construction of the access route.

[0067] Figure 7 This is a flowchart illustrating an example of determining a preliminary access path. Based on the segmented brain tumor and vessel labels, the location of the brain tumor within the vessel needs to be calculated. Then, parameters such as the angle between the aneurysm and the parent artery, the distance between the two bends (the distal and proximal bends), the direction of the proximal end of the parent artery's bend, the direction of the aneurysm, and the aneurysm morphology are calculated as shaping reference parameters. Next, based on the tumor location and access path location, the access path is planned. The start and end points of the shaped vessel are then calculated. After obtaining the shaped segment of the vessel, the vessel is reconstructed, and the shaping model is calculated to obtain the calculated preliminary access path.

[0068] S130: Generate a simulated microcatheter model through the preliminary access path.

[0069] After obtaining the initial access path, a simulated microcatheter model can be generated based on it. The simulated microcatheter model can be generated according to the rules adapting to the access path, combined with the geometric features of the initial access path. For example, it can be generated based on the curvature of the initial access path, or the process of inserting the microcatheter can be determined based on the initial access path, and the shaping method of the microcatheter's tip can be determined based on this process, thereby generating the simulated microcatheter model. Figure 8 The diagram shown is a schematic representation of the determined simulated microcatheter model. In practical applications, the simulated microcatheter model can be determined according to specific requirements, and there are no restrictions on this.

[0070] Correspondingly, when the preliminary access path includes the initiation and end points of the reshaped vessel, the simulated microcatheter model can be constructed based on the preliminary access path between the initiation and end points of the reshaped vessel, so that the constructed model is more consistent with the actual insertion state.

[0071] S140: Simulate the microcatheter propulsion process using the target model and / or simulated microcatheter model, and obtain the simulated propulsion parameters.

[0072] Based on the constructed target model and simulated microcatheter model, the advancement process of the microcatheter can be simulated. Since both the target model and the simulated microcatheter model correspond to the corresponding tissues and instruments in actual applications, the simulation effect based on the above models is consistent with the actual execution effect of interventional surgery, thus enabling the simulation results to reflect the execution effect corresponding to the actual surgical operation.

[0073] Specifically, a simulated microcatheter model can be placed in the corresponding position within the target model, and the simulated microcatheter can be controlled by relevant instructions input by the doctor, thereby completing the advancement of the microcatheter in the blood vessel. Figure 9 This is a schematic diagram simulating the microcatheter intervention process during surgery.

[0074] Simulated propulsion parameters are the parameters related to the propulsion results reflected in the simulation process. These parameters may include, for example, the microcatheter propulsion speed, microcatheter propulsion resistance, and the contact condition between the microcatheter and the target model. These simulated propulsion parameters can quantitatively reflect the propulsion results of the microcatheter within the target model.

[0075] In some implementations, the simulated advancement parameters may also include adjustment instructions from the physician. During the simulated advancement process, if the physician determines, based on real-time feedback, that the advancement process is obstructed or the microcatheter cannot pass through the blood vessel effectively, they can input relevant adjustment instructions to adjust the simulated microcatheter model and / or the initial access path, thereby further optimizing the advancement process.

[0076] In some implementations, to ensure the accuracy of the simulation results, the influence of blood in the blood vessels on the propulsion effect of the simulated microcatheter can also be considered.

[0077] Specifically, blood flow simulation parameters can be obtained first. These parameters are state parameters of blood flow in the target model, simulated based on fluid dynamics. These parameters can be determined based on blood-related parameters reflected in scan data or other detection data. The specific process for obtaining these parameters can be set according to the needs of the actual application and will not be elaborated here.

[0078] By introducing blood flow simulation parameters, the advancement process of the microcatheter is made closer to the actual surgical environment, thereby further improving the realism and effectiveness of the simulation results.

[0079] Based on this, simulation propulsion parameters can be obtained by setting corresponding control parameters and boundary conditions. Specifically, control parameters and boundary conditions can be determined first based on the requirements of microcatheter intervention. Control parameters can be used to limit the relevant parameters of microcatheter model propulsion, and boundary conditions are used to control the relevant constraints for solving the simulation of microcatheter propulsion process.

[0080] Subsequently, by combining blood flow simulation parameters, the target model, and the simulated microcatheter, advancement values ​​can be obtained. These advancement values ​​reflect the relevant values ​​of the simulated microcatheter during the advancement process in interventional surgery. The advancement values ​​are then processed according to the determined control parameters and boundary conditions to obtain the simulated advancement parameters. Specifically, for example, a mesh generation strategy and numerical method can be determined to complete the post-processing of the advancement values.

[0081] The following is combined Figure 12 The simulation process described above is illustrated below. First, governing equations are established, and initial and boundary conditions are determined. Then, a computational grid is created, and discrete equations are established, while simultaneously determining discrete initial and boundary conditions. Given the control parameters, the discrete equations are solved iteratively. After the discrete equations converge, post-processing analysis is used to output the final simulation propulsion parameters.

[0082] The above implementation method can automatically obtain simulated propulsion parameters according to the corresponding settings, ensuring the convenience and effectiveness of practical applications.

[0083] S150: Based on the simulated propulsion parameters, the preliminary access path and / or the simulated microcatheter model are adjusted to obtain the target access path and the target microcatheter model; the target microcatheter model is used to manufacture the application microcatheter; the target access path is used to indicate the propulsion path of the application microcatheter.

[0084] After obtaining the simulated advancement parameters, the initial access path and / or simulated microcatheter model can be adjusted based on the advancement results reflected by the simulated advancement parameters, or directly according to the adjustment instructions contained in the simulated advancement parameters, to obtain a target access path and target microcatheter model that better matches the actual application effect. Based on the target microcatheter model, a physical application microcatheter can be manufactured, and the target access path can be used to indicate the actual advancement path of the application microcatheter, enabling the interventional surgery to be effectively completed by using the application microcatheter according to the target access path.

[0085] Specifically, based on the target microcatheter model, a mold can be generated using 3D printing. The microcatheter is then placed in the mold for heating and shaping, resulting in the final application microcatheter. For example... Figure 10 The image shows a schematic diagram of a sculptor generated by 3D printing based on a target microcatheter model. The schematic diagram of the microcatheter adjusted according to this sculptor is shown below. Figure 11 As shown, this ensures that the manufacturing and adjustment of microcatheters can be completed quickly and effectively. In practical applications, microcatheters can also be manufactured and applied using other methods, and there are no restrictions on this.

[0086] The following is in conjunction with the appendix Figure 13The overall process is described exemplarily. First, the input CTA and CT images are segmented to obtain the segmentation results. Then, vascular reconstruction is performed based on the segmentation results, including midline calculation, curvature calculation, tumor location, tumor parameter measurement, and calculation of the initiation and termination points of the shaped vessel. Next, the shaping model is calculated to obtain the shaped model. After simulation, the shaped microcatheter is placed in the blood vessel according to the vascular reconstruction results. The doctor performs a surgical simulation. During the simulation, the doctor can fine-tune the shaped model and record the optimal approach. Finally, the 3D printing of the shaping device is performed based on the optimized model, and then the microcatheter is shaped to complete the entire process.

[0087] Based on the above embodiments and examples, it can be seen that the microcatheter shaping method first constructs a target model based on the target scanning data, and then constructs a preliminary access path based on the key area distribution and target state parameters in the target model. A simulated microcatheter model is generated based on the preliminary access path, and then the microcatheter advancement process is simulated based on the target model and the simulated microcatheter model, and simulated advancement parameters are obtained. Finally, the preliminary access path and / or the simulated microcatheter model are adjusted based on the simulated advancement parameters to obtain the target access path and the target microcatheter model, thereby manufacturing and applying the microcatheter and performing interventional procedures based on the target access path. This approach allows for the pre-construction of relevant models of blood vessels and microcatheters, and then the simulation of the microcatheter advancement process based on the constructed models. This enables adjustments to the microcatheter morphology based on the simulation results, ensuring the actual application effect of the microcatheter and thus optimizing the final interventional procedure results.

[0088] based on Figure 1 The corresponding microcatheter shaping method, as described in the embodiments of this specification, also proposes a microcatheter shaping device. For example... Figure 14 As shown, the microcatheter shaping device may include the following modules.

[0089] The target model construction module 1410 is used to construct a target model based on the scan data; the target model includes the distribution location of key areas.

[0090] The preliminary entry path construction module 1420 is used to construct a preliminary entry path based on the key area distribution location and target state parameters in the target model.

[0091] The simulated microcatheter model generation module 1430 is used to generate a simulated microcatheter model through the preliminary access path.

[0092] The simulation propulsion parameter acquisition module 1440 is used to simulate the microcatheter propulsion process using the target model and the simulated microcatheter model, and to acquire the simulation propulsion parameters.

[0093] The target microcatheter model acquisition module 1450 is used to adjust the preliminary access path and / or the simulated microcatheter model based on the simulated propulsion parameters to obtain the target access path and the target microcatheter model; the target microcatheter model is used to manufacture the application microcatheter; the target access path is used to indicate the propulsion path of the application microcatheter.

[0094] In some implementations, the target model construction module is used to: distinguish target scan data and key region scan data in scan data; wherein, it includes: using a segmentation model to distinguish target scan data and key region scan data from scan data; the segmentation model includes a deep learning model trained based on training samples; and constructing the target model using the target scan data and key region scan data respectively.

[0095] Based on the above implementation, distinguishing target scan data and key area scan data in the scan data includes: dividing the scan data into segmented scan data corresponding to at least two segments; distinguishing target scan data and key area scan data in each segmented scan data; correspondingly, constructing the target model using the target scan data and key area scan data respectively includes: combining the target scan data and key area scan data of each segment to construct the target model.

[0096] Based on the above implementation, dividing the target scanning data into vascular segment data corresponding to at least two segments includes: dividing the target scanning data into point cloud data corresponding to at least two segments; correspondingly, distinguishing target scanning data and key area scanning data in each vascular segment data includes: using a point cloud classification algorithm to distinguish target scanning data and key area scanning data in each point cloud data.

[0097] In some embodiments, the target model construction module is used to: acquire vascular detection parameters from target scanning data; the vascular detection parameters include target soft spot parameters and target calcification parameters; determine target surface data by combining the target soft spot parameters, target calcification parameters, key region distribution locations, and scanning data; and construct a target model based on the target surface data; the target model is an internal tetrahedral model.

[0098] Based on the above implementation, the step of constructing a target model based on the target surface data includes: calculating the normal vector corresponding to the blood vessel based on the target surface data; constructing a triangular mesh corresponding to the target surface data using a triangulation algorithm; and constructing a target model by combining the normal vector corresponding to the blood vessel and the triangular mesh corresponding to the target surface data.

[0099] Based on the aforementioned implementation method, the step of constructing a preliminary access path according to the key region distribution location and target state parameters in the target model includes: determining target state parameters based on the target model; the target state parameters include the vessel diameter and vessel curvature; determining the vessel midline based on the target state parameters; and determining the preliminary access path based on the vessel midline and the key region distribution location; wherein, it includes: determining lesion state parameters based on target scanning data; the lesion state parameters include the key region distribution location and lesion morphology parameters; and determining the starting point and ending point of the reshaped vessel based on the vessel midline, combined with the lesion state parameters and the target state parameters.

[0100] In some embodiments, the simulation propulsion parameter acquisition module is used to: acquire blood flow simulation parameters; the blood flow simulation parameters include state parameters of blood flow in the target model based on fluid dynamics simulation; combine the blood flow simulation parameters, use the target model and the simulated microcatheter model to simulate the microcatheter propulsion process, and acquire simulation propulsion parameters; determine control parameters and boundary conditions based on microcatheter intervention requirements; combine the blood flow simulation parameters, the target model and the simulated microcatheter to acquire propulsion values; and process the propulsion values ​​using the control parameters and boundary conditions to obtain simulation propulsion parameters.

[0101] In some implementations, the simulated propulsion parameters also include fine-tuning instructions input by the user; the fine-tuning instructions are instructions from the user to adjust the simulated microcatheter model and / or the initial access path during the simulated microcatheter propulsion process.

[0102] based on Figure 1 The corresponding microcatheter shaping method, according to embodiments of this specification, provides a computer-readable storage medium storing a computer program / instruction. The computer-readable storage medium can be read by a processor via the device's internal bus, and the processor can then implement the program instructions in the computer-readable storage medium.

[0103] In this embodiment, the computer-readable storage medium can be implemented in any suitable manner. The computer-readable storage medium includes, but is not limited to, random access memory (RAM), read-only memory (ROM), cache, hard disk drive (HDD), memory card, etc. The computer storage medium stores computer program instructions. When the computer program instructions are executed, this specification is implemented. Figure 1 The program instructions or modules corresponding to the embodiments.

[0104] It should be noted that the above-mentioned microcatheter shaping device and method can be applied to the field of microcatheter intervention technology, and can also be applied to other technical fields without limitation.

[0105] Although the process described above includes multiple operations that occur in a specific order, it should be clearly understood that these processes may include more or fewer operations, which may be executed sequentially or in parallel (e.g., using parallel processors or a multithreaded environment).

[0106] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0107] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0108] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0109] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0110] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0111] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0112] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of computer program products implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0113] The embodiments described in this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0114] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, system embodiments are basically similar to method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. In the description of this specification, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments in this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0115] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A microcatheter shaping device, comprising: The application comprises the following steps: a target model construction module is used to construct a target model according to scanning data; the target model comprises a key region distribution position; a preliminary access path construction module is used to construct a preliminary access path according to the key region distribution position in the target model and a target state parameter; a simulated microcatheter model generation module is used to generate a simulated microcatheter model through the preliminary access path; a simulated propulsion parameter acquisition module is used to simulate a microcatheter propulsion process by using the target model and the simulated microcatheter model, and to acquire simulated propulsion parameters; a target microcatheter model acquisition module is used to adjust the preliminary access path and / or the simulated microcatheter model based on the simulated propulsion parameters, so as to obtain a target access path and a target microcatheter model; the target microcatheter model is used to manufacture an application microcatheter; and the target access path is used to indicate a propulsion path of the application microcatheter; the simulated propulsion parameter acquisition module is specifically used to: acquire blood flow simulation parameters; determine control parameters and boundary conditions based on microcatheter intervention requirements; acquire propulsion values in combination with the blood flow simulation parameters, the target model and the simulated microcatheter; and process the propulsion values by using the control parameters and the boundary conditions to obtain simulated propulsion parameters.

2. The microcatheter shaping device of claim 1, wherein, The target model construction module is used to: distinguish target scanning data and key region scanning data in scanning data; wherein, the target scanning data and the key region scanning data are distinguished from the scanning data by using a segmentation model; the segmentation model comprises a deep learning model trained based on training samples; the target model is constructed by using the target scanning data and the key region scanning data respectively.

3. The microcatheter shaping device of claim 2, wherein, The target scanning data and the key region scanning data are distinguished in the scanning data, comprising: the scanning data is divided into segmented scanning data corresponding to at least two segments; the target scanning data and the key region scanning data are distinguished in each segmented scanning data respectively; correspondingly, the target model is constructed by using the target scanning data and the key region scanning data respectively, comprising: the target scanning data and the key region scanning data of each segment are combined to construct the target model.

4. The microcatheter shaping device of claim 3, wherein, The scanning data is divided into segmented scanning data corresponding to at least two segments, comprising: the scanning data is divided into point cloud data corresponding to at least two segments; correspondingly, the target scanning data and the key region scanning data are distinguished in each segmented scanning data, comprising: the target scanning data and the key region scanning data are distinguished in each point cloud data by using a point cloud classification algorithm.

5. The microcatheter shaping device of claim 1, wherein, The target model construction module is used to: acquire a blood vessel detection parameter in the target scanning data; the blood vessel detection parameter comprises a target soft spot parameter and a target calcification parameter; determine target surface data by comprehensively considering the target soft spot parameter, the target calcification parameter, the key region distribution position and the scanning data; construct a target model according to the target surface data; the target model is an internal tetrahedral model.

6. The microcatheter shaping device of claim 5, wherein, The target model is constructed according to the target surface data, comprising: a normal vector corresponding to a blood vessel is calculated according to the target surface data; The triangulation algorithm is used to construct a triangular mesh corresponding to the target surface data; The target model is constructed in combination with the normal vector corresponding to the blood vessel and the triangular mesh corresponding to the target surface data.

7. The microcatheter shaping device of claim 5, wherein, The preliminary access path is constructed according to the key region distribution position and the target state parameter in the target model, and the preliminary access path includes: The target state parameter is determined based on the target model; the target state parameter includes the inner diameter of the blood vessel and the curvature of the blood vessel; The blood vessel centerline is determined according to the target state parameter; The preliminary access path is determined according to the key region distribution position based on the blood vessel centerline; wherein, the lesion state parameter is determined according to the target scanning data; the lesion state parameter includes the key region distribution position and the lesion shape parameter; the shaping blood vessel starting point and the shaping blood vessel ending point are determined based on the blood vessel centerline, in combination with the lesion state parameter and the target state parameter.

8. The microcatheter shaping device of claim 1, wherein the microcatheter shaping device is configured to be inserted into a patient's vasculature. The blood flow simulation parameter includes the state parameter of the blood flow in the target model based on the fluid mechanics simulation.

9. The microcatheter shaping device of claim 1, wherein, The simulation advancing parameter further includes a fine-tuning instruction input by a user; the fine-tuning instruction is an instruction for the user to adjust the simulation microcatheter model and / or the preliminary access path during the simulation microcatheter advancing process.

10. A method of microcatheter shaping, comprising: The method includes: The target model is constructed according to the scanning data; The key region distribution position is included in the target model; The preliminary access path is constructed according to the key region distribution position and the target state parameter in the target model; The simulation microcatheter model is generated through the preliminary access path; The microcatheter advancing process is simulated by using the target model and the simulation microcatheter model, and the simulation advancing parameter is obtained; The preliminary access path and / or the simulation microcatheter model are adjusted based on the simulation advancing parameter respectively, to obtain a target access path and a target microcatheter model; The target microcatheter model is used for manufacturing a microcatheter; The target access path is used for indicating the advancing path of the microcatheter; The microcatheter advancing process is simulated by using the target model and the simulation microcatheter model, and the simulation advancing parameter is obtained, and the simulation advancing parameter includes: The blood flow simulation parameter is obtained; The control parameter and the boundary condition are determined based on the microcatheter intervention requirement; The advancing value is obtained in combination with the blood flow simulation parameter, the target model and the simulation microcatheter; The simulation advancing parameter is obtained by processing the advancing value by using the control parameter and the boundary condition.

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