Improved real-time simulation of endoprosthesis deployment

Abstract

The present invention relates to a device for medical imaging by X-rays. More specifically, the present invention relates to the simulation of the deployment of an endoprosthesis in order to assist a surgeon during an intravascular procedure. The present invention makes use of a single 2D image to determine certain features of a simplified model of an endoprosthesis: the 2D position and the deployment value of the stent; the determination of an intrinsic rotation of at least one stent; and then the determination of the deployment of a model representing the stent structure in a 3D model of the vascular structure, said model being initialized on the basis of the preceding steps.

Description

TECHNICAL FIELD

[0001] The present invention relates to the field of medical X-ray systems, and more specifically, to a radiological system for endovascular surgery of an aneurysm of the abdominal aorta. BACKGROUND

[0002] Aneurysms of the abdominal aorta can be treated by conventional open surgery or by endovascular surgery. During an endovascular intervention, the surgeon cannot directly access the surgical site. On the contrary, in endovascular surgery, the surgeon makes an incision in the femoral artery in the groin area and inserts a very flexible metal wire. By pushing on this wire, the surgeon can then move his tools, including an endoprosthesis, to the aneurysm area in the abdominal aorta. When the surgeon considers that the endoprosthesis is in the right place, he can decide to release the endoprosthesis, which automatically deploys.

[0003] Therefore, the correct positioning of the endoprosthesis is crucial. Indeed, this prosthesis must be correctly placed and must not obstruct the arteries branching from the aorta. In the most complex cases, so-called fenestrated endoprostheses include openings that must be precisely positioned to face the secondary arterial orifices. For example, these openings must be positioned to face the junctions between the aorta and the renal arteries, which branch out from the renal arteries. Therefore, to avoid obstructing these junctions and the renal arteries, it is necessary to correctly position the endoprosthesis.

[0004] To guide these actions, the surgeon uses mobile interventional radiological systems in order to precisely position the endoprosthesis, which will redirect the blood flow. These systems are also called mobile C-arms (or block magnifiers), which allow the surgeon to acquire X-ray images during the intervention and to monitor the position of the tools (catheters, prostheses, etc.) in real time and in a minimally invasive manner. Most of these systems make it possible to obtain two-dimensional images with video image streams of up to thirty images per second. The physician then uses these images to reconstruct the geometry of the tools and the arteries in his mind in order to verify their positioning in real time. This X-ray imaging requires the injection of a contrast agent. This contrast agent is essential to make the aorta visible to X-rays, but it has the drawback of being toxic. Therefore, the possible number of injections and image captures is limited.

[0005] In some cases, the step of installing the endoprosthesis in place is very complex and requires multiplication of the image captures and, as a result, multiplication of the amount of radiation to which the patient is subjected and of the contrast agent injected. The probability of post-operative complications is also higher. In the short term, this is due to blood loss and poor irrigation of the areas obstructed by the surgical tools. In the medium-long term, the imprecise positioning of the endoprosthesis leads to a risk of leakage and thrombosis. The deployment of the endoprosthesis in the aorta is performed in 3D. Therefore, a single 2D image can not be sufficient to allow the surgeon to clearly assess the deployment of the endoprosthesis. Therefore, the possibility of obtaining a three-dimensional visualization of the surgical site would be a great advantage for the surgeon, allowing him to quickly and accurately position his tools, while reducing the number of angiographies.

[0006] Currently there are several methods that allow this 3D visualization. However, these methods are still based on taking several 2D images from different perspectives for 3D reconstruction. Therefore, they involve multiple injections of contrast agent and an increase in operating time due to the fact that several images must be taken at different angles.

[0007] Therefore, there is a need for a tool to assist in surgical procedures that allows the surgeon to visualize his tools and their configuration in the patient's aorta in 3D, almost in real time. SUMMARY

[0008] To this end, the present invention relates to a method comprising: capturing a 2D image of a vascular structure by X-ray; acquiring a 3D model of the vascular structure; acquiring a model of an endoprosthesis in the vascular structure, the endoprosthesis comprising a plurality of stents; determining, from the 2D image and for each stent, at least one position, at least one orientation and at least one deployment value; simulating, for each stent, a deployment of a model of the stent representing the stent structure in the 3D model of the vascular structure, initializing said model of the stent based on the model of the endoprosthesis; displaying the deployed stent model.

[0009] Advantageously, the 2D image defines a 3D reference coordinate system comprising a vertical axis, a horizontal axis and a depth axis of the image; in the model of the endoprosthesis, each stent is defined by: an orientation and at least one position of at least one feature point, the orientation and the at least one position being defined by at least 6 degrees of freedom comprising: a 3D position of a first feature point of the stent in the reference coordinate system; an intrinsic rotation angle; at least one deployment value of the stent, the deployment value being defined around a central axis of the stent; the model of the stent is formed by a plurality of interconnected beam elements; the method comprises: determining, from the 2D image and for each stent, at least one position, at least one orientation and at least one deployment value; determining at least one feature point along the vertical and horizontal axes and at least one deployment value of the stent; determining, for at least one stent, its intrinsic rotation angle.

[0010] Advantageously, the position and the orientation of each stent are defined by the 3D positions of three feature points respectively corresponding to the center, the upper end and the lower end of the stent along its central axis, and the intrinsic rotation of the stent around its central axis.

[0011] Advantageously, determining the intrinsic rotation angle for at least one stent comprises determining the intrinsic rotation angle for which at least one 3D position of at least one radiopaque marker on the stent is projected closest to match at least one image of at least one marker on the 2D image.

[0012] Advantageously, the intrinsic rotation angle is obtained by performing a loop that minimizes the distance between at least one projection and at least one image of at least one marker on the 2D image, said loop being a function of said intrinsic rotation angle.

[0013] Advantageously, determining the intrinsic rotation angle for at least one stent comprises modeling the stent in the form of beam elements of a finite element model between a feature point representing the upper end of the central axis of the stent and a feature point representing the lower end of the central axis of the stent, wherein the feature points have no displacement along the depth axis.

[0014] Advantageously, the endoprosthesis is represented in the form of a finite element model, wherein: each stent is modeled by beam elements, successive stents are connected to each other by at least one beam element; the positions of the stent feature points are fixed along the vertical axis, the horizontal axis and the depth axis, the maximum deployed diameter of the stent is greater than or equal to the diameter of the vascular structure at the deployment location; the positions of the stent feature points are fixed along the vertical axis and the horizontal axis and are free to displace along the depth axis, the maximum deployed diameter of the stent is less than the diameter of the vascular structure at the deployment location; the positions of the stent feature points along the depth axis are determined by the mechanical equilibrium of the finite element model, the maximum deployed diameter of the stent is less than the diameter of the vascular structure at the deployment location.

[0015] Advantageously, the display of the deployed stent model comprises the superimposed display of the projection of the stent model on the 2D image of the vascular structure.

[0016] Advantageously, the display of the deployed stent model comprises the 3D display of the deployed stent model and of a 3D model of the vascular structure.

[0017] Advantageously, the 3D model of the vascular structure is a finite element model representing the centerline of the vascular structure by beam elements.

[0018] The application also describes a computer program product comprising computer code elements configured to execute a method according to one of the embodiments of the application.

[0019] The invention also describes a device comprising at least one input port configured to receive a 2D image of a blood vessel structure captured by X-ray, at least one computing unit configured to perform the method according to one of the embodiments of the invention.

[0020] The method generally allows a reliable and fast computation of the deployment of an endoprosthesis in the aorta. For example, the method can be performed on a standard computing device in about thirty seconds, which allows to model the deployment of the endoprosthesis in almost real-time.

[0021] The method of the invention provides the surgeon with a real-time visualization of the deployment of the endoprosthesis based on its actual position. This therefore makes it possible to significantly improve the precision of the treatment performed by the surgeon.

[0022] The method of the invention requires a single image capture to simulate the deployment of the endoprosthesis, which avoids multiple injections of contrast agent.

[0023] The method is applicable to a deployed endoprosthesis and also to an endoprosthesis that is not deployed or partially deployed. BRIEF DESCRIPTION OF DRAWINGS

[0024] Other characteristics, details and advantages of the invention will become apparent on reading the description, given as an example and in which:

[0025] Figure 1 A medical imaging system in which the invention can be implemented is shown;

[0026] Figure 2a A perioperative 2D image showing an endoprosthesis in the aorta with injection of contrast agent is shown;

[0027] Figure 2b A perioperative 2D image showing an endoprosthesis in the aorta without injection of contrast agent is shown;

[0028] Figure 2c An endoprosthesis deployed in a simulated aorta according to a set of embodiments of the invention is shown;

[0029] Figure 3 A method of simulating the deployment of an endoprosthesis according to a set of embodiments of the invention is shown;

[0030] Figure 4 Modeling of a stent within a model of an endoprosthesis according to a set of embodiments of the invention is shown;

[0031] Figure 5 Deployment of a stent within the context of a model of an endoprosthesis is shown;

[0032] Figure 6 determination of the vertical and horizontal position of the feature points of the stent based on 2D images and the deployment of the stent is shown;

[0033] Figure 7a a first example of modeling the deployment of a stent according to a set of embodiments of the present application is shown;

[0034] Figure 7b a second example of modeling the deployment of a stent according to a set of embodiments of the present application is shown;

[0035] Figure 8 superimposition on a perioperative image of a simulation of the deployment of a stent according to a set of embodiments of the present application is shown. DETAILED DESCRIPTION

[0036] Figure 1 a medical imaging system in which the present application can be implemented is shown.

[0037] The system 100 is a mobile interventional radiology system.

[0038] It comprises a unit called C-arm 110 which allows to take X-ray images of the body of a patient. The C-arm is able to rotate around different axes in order to capture images of a still patient at different angles. The C-arm comprises a control interface which allows the medical team to control the orientation and the image capture.

[0039] The C-arm 110 is connected to a computing device (for example, a computer 120) which is able to produce on a display device (for example, a screen 121) a display of the X-ray images taken by the C-arm 110. To this end, the computing device 120 comprises an entry port for receiving the perioperative images. The computing device 120 also comprises at least one computing unit (for example, a processor) for processing the images taken by the C-arm. For example, the processor can perform a pre-analysis of the images and can superimpose on the images items of information which can be of interest to the medical team (for example, the time at which the images were captured, the temperature of the patient, his or her blood pressure, etc.).

[0040] The division of the system into two devices, the C-arm 110 for taking the images and the computing device 120 for processing and displaying them, allows a great flexibility in the use of the C-arm 110, even if the position of the display screen 121 remains fixed, the C-arm 110 can remain mobile.

[0041] In a set of embodiments of the present application, the device 120 also makes it possible to generate a visualization of the deployment of the endoprosthesis and to generate its display in 2D or 3D, as will be explained below.

[0042] The system 100 is given as an example of a system in which the application can be implemented. The application can be implemented in many other medical systems. For example, depending on the different image capture modes, the processing and display of the images can be performed in a single device. It is also possible to capture the images at one location and send the images to another site (for example, on a remote server) for processing and display of the images.

[0043] Figure 2a Figure 2b and Figure 2c show perioperative 2D images according to a set of embodiments of the application, showing an endoprosthesis in the aorta with and without injection of contrast agent and an endoprosthesis deployed in a simulated aorta.

[0044] Figure 2a shows a perioperative image of an aorta taken by X-ray (for example, by a device such as the device 100) and taken with contrast agent. This image allows the visualization of the aorta boundary. In particular, it makes it possible to know the diameter of the aorta at each point and to visualize from where the adjacent veins branch off.

[0045] Figure 2b shows a perioperative image 200b of an aorta taken by X-ray (for example, by a device such as the device 100) without contrast agent and before stent deployment. Without contrast agent, the boundary of the aorta is no longer discernible, but the stents 211b, 212b, 213b, 214b, 215b, 216b, 217b and 218b, 219b, 220b of the endoprosthesis are apparent. The stents 211b to 218b are not deployed, the stent 219b is partially deployed, and the stent 220b is fully deployed. The radiopaque markers (for example, markers 230b and 231b) are also apparent. Perioperative imaging also makes it possible to locate certain key points of interest, which can be visualized, for example, by markers such as markers 230b and 231b. These markers can be located at points particularly important on the endoprosthesis in order to allow the surgeon to locate them on the perioperative image.

[0046] When the endoprosthesis is introduced, the surgeon can capture a first image with injection of contrast agent to visualize the boundary of the aorta, then one or more images without contrast agent to visualize the position of the stents and the radiopaque markers. The two views can be displayed superimposed to visualize the position of the stents within the aorta.

[0047] At this stage, the endoprosthesis can be undeployed, partially deployed or fully deployed. However, as Figure 2b the image in allows to determine the position of the stents, as will be explained below.​

[0048] Therefore, this type of perioperative 2D image allows the surgeon to have a general idea of the position and deployment of the endoprosthesis in the artery. However, this 2D view can often prove insufficient to assess the deployment which, by its nature, occurs in 3D.

[0049] Figure 2c An image showing an endoprosthesis deployed in a solid model is shown. This image is similar to the image seen by the surgeon in the superimposition of the perioperative image with contrast agent and the superimposition of the perioperative image without contrast agent, that is to say, both the endoprosthesis and the space in which the endoprosthesis is deployed are visualized. In the example shown, the endoprosthesis is completely deployed. This image shows an endoprosthesis deployed in a solid model of the aorta 220. The endoprosthesis is formed by a plurality of stents 211, 212, 213, 214, 215, 216, 217, 218. Therefore, the perioperative image allows the position and deployment of the stents within the artery to be visualized in 2D. Figure 2c

[0050] As will be explained below, the present application makes it possible to obtain a 3D simulation and visualization of the deployment of an endoprosthesis based on a 2D image. In the remainder of the present description, the 3D deployment will be expressed based on three axes x, y and z, corresponding respectively to a vertical axis, a horizontal axis and a depth axis, according to a reference coordinate system R im However, this reference coordinate system is given by way of example only and the person skilled in the art will have the possibility, upon reading the present disclosure, to choose any 3D reference coordinate system which meets his needs.

[0051] Figure 3 A method of simulating the deployment of an endoprosthesis according to a set of embodiments of the present application is shown.

[0052] The aim of the method 300 is to simulate the deployment of an endoprosthesis and to allow the surgeon to visualize the deployment of the endoprosthesis in the artery, if appropriate, in 3D.

[0053] The method 300 comprises a step 310 of capturing a 2D image 311 of the vascular structure by X-ray. This 2D image is a perioperative image and can be taken, for example, by a C-arm type device such as the device 100. Figure 2a and Figure 2b ​The images in FIG. 1 are two examples of such images. As mentioned above, the capture of such images by X-ray can include the injection of contrast agent into the vascular structure. It should be noted that in the rest of the specification, the method will be illustrated by examples related to the simulation of an endoprosthesis in the aorta. However, these examples are given as non-limiting examples and the method can be applied to simulate the deployment of an endoprosthesis in any vascular structure. There is no fundamental difference between the deployment of an endoprosthesis in the aorta and in another vascular structure, and therefore the method can be applied directly to other vascular structures. The method can also be applied to simulate the deployment of an endoprosthesis in a surgical physical model.

[0054] The capture of the 2D images defines a 3D reference frame that will be used in the rest of the method. This 3D reference frame comprises a vertical axis, a horizontal axis and a depth axis of the image capture. In the example of FIG. 1, these axes are respectively labeled x, y and z. However, this naming is given by way of example only and it is a simple matter for a person skilled in the art to provide the axes with names and orientations that meet their needs. Figure 2c

[0055] The method 300 also comprises acquiring a 3D model 321 of the aorta. This 3D model 321 makes it possible to define the profile and the volume of the aorta in 3D. For example, the aorta can be defined by a set of 3D polygons. The boundaries of the aorta can thus be represented in the reference frame defined by the 2D imaging.

[0056] According to different embodiments of the application, the 3D model can be obtained in different ways. For example, it can have been created beforehand for the patient by 3D imaging, obtained beforehand and then registered in real time during the operation, or it can be created from the perioperative 2D images.

[0057] In a set of embodiments of the application, the 3D model 321 of the aorta is a finite element model comprising a centerline of the aorta and a representation of its surface.

[0058] In a set of embodiments of the application, the 3D model of the aorta is obtained from the perioperative 2D images, for example images obtained from a C-arm, by a non-rigid registration method of a previous model of the aorta.

[0059] As mentioned above, the non-rigid registration method of the aorta is based on a finite element model of the arterial centerline. The perioperative information items contained in the projection planes of the perioperative 2D images are used as boundary conditions on the finite element model. The deformations outside the planes are then calculated by a mechanical model.

[0060] In a set of embodiments of the application, the registration method has the following steps:

[0061] ​- The centerline of the artery is extracted using, for example, the Voronoi diagram method introduced by "Antiga, L. (2002). Patient-specific modeling of geometry and blood flow in large arteries. Politecnico di Milano";

[0062] - Implement the centerline in a finite element model based on beam elements. This can be done in different ways. “Duriez, C. (2013). Real-time tactile simulation of medical procedures involving deformation and instrument-tissue interaction (PhD dissertation, Université des Sciences et Technologie de Lille-Lille I)” provides an example of implementing the centerline of the aorta using a finite element model;

[0063] - A first 2D / 2D non-rigid registration is performed between the perioperative image and the projection of the centerline extracted in the preceding steps. This non-rigid registration consists of rigid registration followed by interpolation;

[0064] - Then, 2D information terms related to the position of the aorta or instruments during surgery are implemented in the finite element model. It is assumed that the projection matrix of the perioperative images is known. In this way, the back-projection line of each feature point identified on the 2D images can be calculated. These information terms are then implemented in the mechanical model as boundary conditions, forcing the points of the 3D model to move along the back-projection lines. Therefore, the mechanical model calculates deformations not contained in the projection plane of the perioperative 2D images in order to reach an equilibrium state;

[0065] -Then the volume of the aorta is reconstructed around the updated centerline.

[0066] In one embodiment of the present invention, a 3D model of the aorta is superimposed on perioperative images.

[0067] Method 300 also includes a model 331 for obtaining the built-in prosthesis. In this model, each stent is defined by at least one position and one orientation of the stent and the deployment of the stent, the at least one position and one orientation of the stent being defined by at least six degrees of freedom.

[0068] The degrees of freedom representing the position and orientation of the stent include at least one 3D position of at least one feature point of the stent, and the inherent rotation r of the stent about its central axis. x Depending on the specific embodiment, the 6D position of the stent can be defined in different ways. For example, it can be defined by the 3D position of at least two feature points of the stent and an inherent rotation angle, or by the 3D position of a single feature point of the stent and three rotation angles. Those skilled in the art will be able to readily define the type of stent model that meets their needs.

[0069] Figure 4 Modeling of a stent within an embedded prosthesis model is shown according to a set of embodiments of the present invention.

[0070] Figure 4 Modeling of the stent within the built-in prosthesis model 331 is shown 400.

[0071] In this example, the bracket and its own reference coordinate system R 支架 Relatedly, the reference frame R 支架 Including the initial coordinate system R im The axes (x, y, z) are aligned with the three axes (x', y', z'). The inherent rotation r of the support. x The axis 'x' is defined as the axis around the central axis (which can also be called the vertical axis). This simplified model includes the 3D positions of three feature points P0, P1, and P2, corresponding to the center, top, and bottom of the support along its central axis x', respectively. In this example, the position and orientation of the support are therefore defined by 10 degrees of freedom (9 for the three 3D positions and one for rotation).

[0072] The use of these three feature points allows for further improvement in determining the position and orientation of the stent.

[0073] However, this modeling of the position and orientation of the scaffold is given only as a non-limiting example, and the position and orientation of the scaffold can be represented in other ways. For example, they can be represented by the position and 3 rotations of feature point P0, or by the positions of feature points P1 and P2 and their inherent rotations about axis x'.

[0074] Figure 5 The deployment of the scaffold is shown in the context of a model with an embedded prosthesis.

[0075] In one set of embodiments of the invention, the deployment of the stent is defined by a single value. This value may be, for example, the diameter of the stent, a percentage of deployment, or a ratio.

[0076] Figure 500 shows a simplified deployment of several supports. Axis 510 shows the support deployment in mm. Axis 520 shows the position and length of each support.

[0077] According to different embodiments of the invention, the deployment of the stent can also be represented by a finite number of values, which represent the deployment of the stent at different feature points around its central axis. For example, the deployment of the stent can be represented by deployment values ​​at the upper end of the stent and deployment values ​​at the lower end of the stent.

[0078] Therefore, stent deployment is represented by at least one value indicating the level of stent deployment around its central axis, which allows for the combination of position and orientation values ​​to represent the deployment of each stent within the implanted prosthesis in a highly comprehensive manner using a finite number of parameters, wherein most of the values ​​of the finite number of parameters can be extracted from 2D perioperative images.

[0079] Therefore, the model 331 of the built-in prosthesis allows for simplified modeling of the built-in prosthesis, making it possible to represent the overall positioning of the built-in prosthesis with a finite number of degrees of freedom.

[0080] Back Figure 3 Method 300 includes step 330 of determining, based on a 2D image and for each bracket, at least one position of at least one feature point along a vertical axis (x) and a horizontal axis (y) and at least one deployment value of the bracket.

[0081] This step involves identifying all values ​​of the built-in prosthesis model that can be obtained directly from the 2D image.

[0082] Figure 6 The diagram illustrates the determination of the vertical and horizontal positions of feature points of the scaffold based on a 2D image, as well as the deployment of the scaffold.

[0083] More accurately, Figure 6 It shows Figure 2c The image highlights the different parameters used to model the deployment of the 3D built-in prosthesis. Therefore, Figure 6 The image shows the detection of certain values ​​on perioperative images of the aorta, in a 2D format similar to those that a surgeon could visualize in real time. Although Figure 2c and Figure 6 An embedded prosthesis deployed in a solid model of the aorta is shown, but Figure 6 The elements shown also apply to images illustrating the aorta, highlighted by contrast agent, superimposed on an image of the implanted prosthesis, and also to images of the implanted prosthesis when it is not deployed or partially deployed.

[0084] Three illustrations, 610, 620, and 630, respectively illustrate three examples of determining the location of feature points of the stent on image 200, stent deployment, and association with the centerline of the aorta.

[0085] In particular, such as Figure 2b As shown, the 2D image allows for the direct acquisition of each feature point of the scaffold along the reference coordinate system R. im The x and y axis positions. These can be read manually from the information displayed on the screen, or semi-automatically from the processing of the center of gravity position of the detection bracket. Figure 6 In the example shown, according to Figure 4The model shown, the stent 211 is associated with three feature points 211-P1, 211-P0 and 211-P2. Thus, for each stent, the analysis of the image 200b makes it possible to directly deduce the position of the feature points 211-P0, 211-P1 and 211-P2 along the x and y axes. For example, these points can correspond to the points 211b-0, 211b-1 and 211b-2 of the image 200b, the positions of which can be directly determined by analyzing the image 200b. According to different embodiments of the application, the positions x, y of the feature points can be determined with respect to a single origin of a reference frame R im or to a central point of the reference aorta. Then, by means of the positions of the feature points thus determined, the stents are positioned in the simulation.

[0086] The illustration 620 shows that, for each stent, at least one deployment value of said stent around its central axis is determined. In the example of Figure 6 , each stent is associated with a deployment value at its upper end and a deployment value at its lower end. For example, the stent 211 is associated with a deployment value 211-D1 at its upper end and with a deployment value 211-D2 at its lower end. Here again, the deployment values of the stents can be directly obtained by analyzing the image 200. In the example of the illustration 620, the stents are deployed and the deployment values can be directly obtained by manually or automatically measuring the deployment of the stents on the image.

[0087] In embodiments in which the endoprosthesis is not deployed or not fully deployed, if the maximum deployed diameter of the endoprosthesis is greater than or equal to the diameter of the aorta at the deployment point, the deployment value can be determined as said diameter of the aorta at the deployment point. In the opposite case, the deployment value corresponds to the maximum deployment of the endoprosthesis. Indeed, in this case, the final deployed diameter of the endoprosthesis at this point will be constrained by the aorta diameter or the stent diameter.

[0088] The illustration 630 shows the association between the feature points of the stents and the centerline of the aorta.

[0089] The centerline of the aorta can be obtained by projecting a 3D centerline obtained beforehand, or by a method of skeletonizing the 2D image (many methods of skeletonizing 2D images are known, such as those described in "Couprie, M., Coeurjolly, D., & Zrour, R. (2007). Discrete medial axis and Euclidean skeleton in 2D and 3D, Image and Vision Computing, 25(10), 1543-1556"). In a set of embodiments of the application, the positions of the feature points of the stents along the z axis are initialized on the centerline of the aorta.

[0090] As Figure 6As illustrated, the steps 330 of determining the horizontal and vertical positions of the stents and of deployment can be done by direct analysis of the 2D images of the perioperative period, either manually or automatically by image analysis.

[0091] This determination is therefore very rapid. Thus, the step 330 can be implemented in real time as soon as the 2D images are captured. Furthermore, this step allows a high precision of less than one millimeter on the determined values.

[0092] Certain characteristics of the model of the endoprosthesis cannot be determined directly by direct analysis of the images. For example, the position of the characteristic points on the depth axis z and the intrinsic rotation of the stent cannot be determined directly. These values can be initialized to default values. For example, the position of the points on the depth axis can be initialized so that these points are located on the centerline of the aorta and the intrinsic rotation of the stent around the axis x' can be initialized to 0.

[0093] In a set of embodiments of the application, the endoprosthesis assembly is modeled in the form of a finite element model in which each stent is modeled by a beam element and the stents are connected to each other by small beam elements.

[0094] In a set of embodiments of the application, a plurality of connecting beam elements, for example five, are arranged in series between the ends of the beam elements representing the stents. These connecting beam elements can be associated with a stiffness matrix whose mechanical properties are different from those of the stiffness matrix representing the beam elements of the stents. Thus, these connecting beam elements will have a less rigid behavior. This makes it possible to model the mechanical equilibrium between the successive stents accurately.

[0095] At the deployment site, the stents whose maximum deployed diameter is greater than or equal to the diameter of the aorta are considered to be constrained: their positions of characteristic points are fixed along the axes x, y and z, in fact, their positions will be completely constrained by the aortic volume at the time of their deployment. Conversely, those whose maximum deployed diameter is less than the aortic diameter are considered to be "free": their characteristic points are displaced along the horizontal axis x and the vertical axis y, but are free to displace along the z axis. Their position along the depth axis z is then defined by the mechanical equilibrium of the finite element model.

[0096] This makes it possible to obtain an accurate 3D position of the stents while taking into account the balance of the mechanical forces within the aorta, whose position is not completely constrained by the aortic volume.

[0097] The positioning of the characteristic points of the stents on the centerline of the aorta offers a good compromise between calculation time and accuracy of the method.

[0098] Returning to Figure 3 , the method 300 comprises a step 340 of determining the intrinsic rotation angle of at least one stent of the endoprosthesis.

[0099] According to different embodiments of the invention, this step, which is performed separately on each stent, can be performed on all or some stents of the implanted prosthesis. For example, it can be performed on each stent of the implanted prosthesis. It can also be performed only on certain key stents, such as stents that include windows that will face the inflow port. The surgeon can also manually select the stent on which the step will be performed, as needed.

[0100] In one set of embodiments of the present invention, for at least one support, its inherent rotation angle r is determined. x 'Including determining such an inherent rotation angle r' x ', for this inherent rotation angle r x ', at least the projection of the location of the non-transparent marker best matches the image of that marker on the 2D image. For example, in Figure 6 In the illustrations 610, 620, and 630, also shown in image 200, the support 211 includes a number of transmissive markings, such as markings 230 and 231. The positions of these transmissive markings are known in the simplified model of the support. Therefore, knowing the deployment values ​​of the support, for the inherent rotation angle r... x For each value of ', the 3D position of the radiopaque marker is projected onto the 2D image, and its position is checked to see if it matches the position of the radiopaque marker on the 2D image. This comparison can be performed on one or more markers.

[0101] r x The determination of ' can therefore be achieved in different ways. For example, the inherent rotation angle r can be obtained by executing a loop that minimizes the distance between the projection of the 3D position and the image of at least one marker on the 2D image. x The cycle is the inherent rotation angle r. x The function of '.

[0102] Therefore, angle r x It can be modified iteratively, and in each iteration, the positional difference between the projection of each marker's 3D position onto the model in the 2D image and its position in the X-ray-taken image can be calculated. If several markers are used, the absolute values ​​of the positional differences can be summed or obtained individually. Therefore, it can be obtained, for example, through gradient descent in a stochastic method, or through any other algorithm as an inherent rotation r. x The angle r is determined iteratively by the function '. xThe algorithm can identify a global minimum of the difference between the projection of the 3D position of the marker and its image, by minimizing the value of the cost function on the 2D images, with respect to the position of the projection of the 3D position of the marker, so as to minimize the position difference between the image of the marker on the 2D images and the projection of the 3D position. According to different embodiments of the application, this algorithm can be initialized with a single starting point or with multiple starting points, to avoid converging towards a local minimum. Any minimization algorithm can be used here.

[0103] This provides a simple and fast way of determining the intrinsic rotation r x of the stent.

[0104] The method 300 then comprises, for each stent, simulating the deployment of a model 351 of the stent in the 3D model 321 of the aorta, the model 351 of the stent being formed of a plurality of beam elements and being initialized based on the model 331 of the endoprosthesis 210.

[0105] Once the parameter values of the model 331 of the endoprosthesis have been determined, in which each stent is represented in a simplified manner, this step comprises initializing a more complex model of each stent using these parameter values and simulating its deployment in the 3D model of the aorta.

[0106] This makes it possible to 3D simulate the actual deployment of the endoprosthesis, in the case where it has been deployed. In the case where the endoprosthesis has not been deployed or has not been deployed completely, this allows the surgeon to visualize what the deployment of the endoprosthesis would look like if he decided to deploy the endoprosthesis in its current position.

[0107] Figure 7a and Figure 7b Two examples of the modeling of the deployment of a stent according to a set of embodiments of the application are shown.

[0108] The model 351 of the stent is formed of a plurality of beam elements modeling the stent. The number of beam elements can vary according to the desired complexity. The model 351 of the stent can be formed of, for example, approximately one hundred beam elements.

[0109] Figure 7a The initialization of a model 700a (corresponding to an example of the model 351) in the 3D model of the aorta 330 is shown. As mentioned above, the steps 330 and 340 make it possible to determine the characteristics of the simplified model for each stent: the position of the characteristic points, the rotation around the central axis, etc. These values allow the initialization of the position and orientation of the beam elements of the model 351, 700a representing the stent structure.

[0110] In the example of Figure 7a , the stent has not yet been deployed. In order to simulate the deployment of the stent, it is then sufficient to simulate the extension of the beam elements from the initial position to the limits of the 3D model of the aorta 330.

[0111] Figure 7b A stent model is shown deployed in a 3D model of the aorta 330. As mentioned above, the model 700b is formed of a plurality of beam elements, for example elements 710b, 71 1 b, 712b, 713b. Thus, the stent can be deployed to its maximum extension, or until the beam elements reach the limits of the aorta, for example at points 720b, 721 b.

[0112] The finite element model makes it possible to take into account simultaneously the constraints within the stent and the interaction between the stent and the aorta.

[0113] Since the finite element model representing the structure of the stent is initialized on the basis of a pre-computed simplified model, a simple simulation of the deployment of the stent can be achieved quickly, while very accurately simulating the deployment of the stent.

[0114] The method 300 therefore allows, as a whole, a reliable and fast computation of the deployment of an endoprosthesis in an aorta. For example, this method can be performed on a standard computing device in about thirty seconds, which allows to model the deployment of an endoprosthesis in almost real time.

[0115] This result is allowed by the fact that the complete model modeling the structure of each stent of the endoprosthesis (models 351, 700a, 700b) is initialized by the preceding steps and only needs to be deployed. Although it is possible to model the deployment of the complete model representing the structure of each stent of the endoprosthesis without prior assumption, this would take a considerable amount of time and would not be compatible with the execution of a real-time operation.

[0116] Returning to Figure 3 , the method 300 comprises a step 360 of displaying the model of the deployed stent. This display can be in 2D by superimposing a projection of the deployment of the stent on a 2D image of the perioperative period, for example the image 200, or in 3D by displaying the deployment of the stent and the model of the aorta 330 in 3D. For example, this display can be displayed on the screen 121 of the medical imaging device.

[0117] Assuming that this method allows to simulate the deployment of an endoprosthesis in a very precise manner and in real time, the display 360 allows the surgeon to visualize the deployment of the endoprosthesis in real time based on the actual position of the endoprosthesis. This therefore makes it possible to significantly improve the precision of the treatment performed by the surgeon.

[0118] In the case where this method is applied to a deployed endoprosthesis, the surgeon can visualize said deployment in 3D. In the case where this method is applied to an undeployed endoprosthesis, if the surgeon decides to deploy the endoprosthesis based on the current position, the surgeon can visualize how the deployment of the endoprosthesis will look like in 3D.

[0119] Moreover, the method requires a single image capture to simulate the deployment of the endoprosthesis, which avoids multiple injections of contrast agent.

[0120] Figure 8 The superimposition of the simulation of the deployment of the stent according to a set of embodiments of the present application on the perioperative images is shown.

[0121] The image 800 shows the superimposition of the simulation of the deployment of the endoprosthesis on the 2D imaging obtained from a C-arm. As mentioned above, the present application also allows a 3D representation of the simulation of the deployment of the endoprosthesis on the 3D model of the aorta. In the case of 3D visualization, the surgeon can manipulate the representation to visualize the prediction of the deployment at different perspectives.

[0122] In both cases, this allows the surgeon to visualize in real time the simulation of the deployment of the endoprosthesis.

[0123] The above examples demonstrate the ability of the present application to determine the deployment of the endoprosthesis. However, they are given by way of example only and do not limit in any way the scope of the present application as defined in the following claims.

Claims

1. A method (300) for simulating deployment of an endoprosthesis implemented by an imaging system, the imaging system comprising an imaging device and a computing device, the computing device comprising a computing unit, the imaging device being connected to the computing device, wherein, The method comprises: - capturing (310), by the imaging device, 2D images (311) of a vascular structure and of an endoprosthesis comprising a plurality of stents by X-ray; - acquiring, by the computing unit (120), a 3D model (321) of the vascular structure; - obtaining, by the computing unit (120), a model (331) of the endoprosthesis (210) comprising a plurality of stents in the blood vessel structure, wherein in the model (331) of the endoprosthesis (210) each stent is defined by at least one position, an intrinsic rotation angle (r x ) and at least one deployment value of the stent; - determining (330, 340), by the computing unit (120), from the 2D images and for each stent, the at least one position, the intrinsic rotation angle (r x ) and the at least one deployment value, wherein the intrinsic rotation angle (r x ) is the rotation angle of the stent around its central axis; - simulating (350), by the computing unit (120), for each stent, the deployment of a model (351) of the stent representing the structure of the stent in the 3D model (321) of the vascular structure according to the values determined in the step of determining (330, 340), the model of the stent being initialized on the basis of a model (331) of the endoprosthesis (210); - displaying (360), by the computing device, on one or more display screens, the model of the stent deployed in the step of simulating (350); The method is characterized in that the calculation unit determines (340) the inherent rotation angle (r) of at least one support. x This includes: determining the inherent rotation angle (r) described below. x '), for the inherent rotation angle (r) x '), at least one 3D position projection of at least one transmissive marker on the support most closely corresponds to at least one image of at least one transmissive marker on the 2D image.

2. The method according to claim 1, wherein: - said 2D image (311) defines a 3D reference coordinate system (R im ), said 3D reference coordinate system (R im ) comprising a vertical axis (x) and a horizontal axis (y) of said 2D image and a depth axis (z); - in the model of the endoprosthesis, each stent is defined by: - an orientation and at least one position of at least one characteristic point (P0, P1, P2), the orientation and the at least one position being defined by at least 6 degrees of freedom, the at least 6 degrees of freedom comprising: - a 3D position of a first characteristic point (P0) of the stent in the 3D reference frame; - the intrinsic rotation angle (r x ’) ; - at least one deployment value of the stent, the at least one deployment value being defined around a central axis of the stent; - the model of the stent is formed of a plurality of interconnected beam elements; The method comprises: - determining (330, 340), by the computing unit, for each stent, at least one position, at least one orientation and at least one deployment value of the stent from the 2D images and; - determining (340), by the computing unit, for at least one support, its intrinsic rotation angle (r x ’).

3. The method of claim 2, wherein, The position and the orientation of each stent are defined by the 3D positions of three characteristic points (P0, P1, P2) respectively corresponding to the center, the upper end and the lower end of the stent along its central axis (x') and by the intrinsic angle of rotation of the stent around its central axis (x').

4. The method of claim 2, wherein, The inherent rotation angle (r) is obtained by executing a loop that minimizes the distance between the at least one 3D position projection and the at least one image of the at least one transmissive marker on the 2D image. x The cycle is the inherent rotation angle (r) x The function of ').

5. The method of claim 2, wherein, determining (340), by the computing unit, for at least one stent its intrinsic rotation angle (r x ) comprises modeling the stent in the form of beam elements of a finite element model between a feature point (P1) representing an upper end of the central axis of the stent and a feature point (P2) representing a lower end of the central axis of the stent, wherein the feature points have no displacement along the depth axis (z).

6. The method according to claim 5, wherein: - the endoprosthesis is represented in the form of a finite element model, wherein: - each stent is modeled by a beam element, successive stents being connected to each other by at least one beam element; - the positions of the characteristic points of the stent are fixed along the vertical axis (x), the horizontal axis (y) and the depth axis (z), the maximum deployed diameter of the stent being greater than or equal to the diameter of the vascular structure at the deployment position; - the positions of the characteristic points of the stent are fixed along the vertical axis (x) and the horizontal axis (y) and are free to displace along the depth axis (z), the maximum deployed diameter of the stent being less than the diameter of the vascular structure at the deployment position; - the positions of the characteristic points of the stent along the depth axis (z) are determined by the mechanical equilibrium of the finite element model, the maximum deployed diameter of the stent being less than the diameter of the vascular structure at the deployment position.

7. The method according to one of claims 1 to 6, wherein, displaying (360) the model of the deployed stent comprises a superimposed display of a projection of the model of the stent (351) on the 2D image (311) of the vascular structure.

8. The method according to one of claims 1 to 6, wherein, displaying (360) the model of the deployed stent comprises a 3D display of the model of the deployed stent and the 3D model (321) of the vascular structure.

9. The method according to one of claims 1 to 6, wherein, the 3D model (321) of the vascular structure is a finite element model representing a centerline of the vascular structure by beam elements.

10. A computer program product comprising computer code means configured to perform the method according to one of claims 1 to 9 when the program is executed on a computing unit of a computing device.

11. An imaging system for simulating deployment of an endoprosthesis, the imaging system comprising an imaging device and a computing device, the imaging device being connected to the computing device, wherein: the imaging device is configured to capture a 2D image (311) of a vascular structure and an endoprosthesis comprising a plurality of stents by X-ray; the computing device (120) comprises: at least one input port configured to receive a 2D image of the vascular structure captured by X-ray; at least one computing unit configured to: obtain a 3D model of the vascular structure; obtain a model (331) of an endoprosthesis in the vascular structure; According to the 2D images and for each stent, values are determined comprising at least one position, an intrinsic rotation angle (r x ) around a central axis of the stent and at least one deployment value; for each stent, simulate deployment of a model of the stent representing a structure of the stent in the 3D model of the vascular structure according to values determined in a determining step, the model of the stent being initialized based on the model of the endoprosthesis; the computing device is configured to display the model of the stent deployed in the simulating step on one or more display screens; wherein determining, by the computing unit, for at least one support its intrinsic rotation angle (r x ) comprises determining the intrinsic rotation angle (r x ) for which at least one 3D position of at least one radiopaque marker on the support is most closely corresponding to at least one image of the at least one radiopaque marker on the 2D image. x ) for which at least one 3D position of at least one radiopaque marker on the support is most closely corresponding to at least one image of the at least one radiopaque marker on the 2D image.

Images