ENDOPROSTHESIS LEAKAGE ANALYSIS

FIELD OF THE INVENTION

Methods and tools for assessing leakage problems with endoprosthesis are provided. More particularly, the methods allow for the analysis of the leakage between a tissue and an endoprosthesis using medical image data.

BACKGROUND

Endoprosthesis are a commonly used way of dealing with diseases in interventional medicine and surgery. Mesh-based endoprosthesis such as stents, stent grafts, heart valve frames, etc. are of particular importance in cardiovascular applications. Also other fields of medicine make use of such endoprosthesis, e.g. pulmonary tract stents, oesophagus stents, etc.

Intraluminal endoprosthesis such as stents are typically designed such that they are deployable by catheter or similar stent delivery system, as it is desirable for endoprosthesis placement procedures to be minimally invasive. Some endoprosthesis are self-expandable, whereas other endoprosthesis are inflated via a balloon inside the endoprosthesis in order to force the endoprosthesis to open.

Currently, the majority of endoprosthesis such as stents and valves have a standard cylindrical outer shape, regardless of the anatomy of the lumen in which the endoprosthesis are to be deployed. Although endoprosthesis typically are flexible, insertion of an endoprosthesis which is not optimized to the patient's anatomy leads to suboptimal intervention results with potential complications. The most frequent occurring complication is para-valvular regurgitation where blood is flowing back into the ventricle through channels between the endoprosthesis and the anatomy in which the endoprosthesis is placed. Typically, an endoprosthesis may comprise a sealing skirt to provide improved sealing between the endoprosthesis and the patient's anatomy, but even when such a sealing skirt is used, leakage problems may occur.

Optimal sealing is of specific importance when using stent grafts for an abdominal aortic aneurysm. To relieve the stress on the aortic wall a stent graft is placed in the abdominal aorta. To ensure a good long-term result, a good seal between the stent graft and the aortic wall above and below the aneurysm is required.

Accordingly there exists a need for methods and systems that are able to check endoprosthesis prior to and/or after surgery for (potential) leakage issues. SUMMARY OF THE INVENTION

Methods and tools are provided herein to allow determination of the fit of an endoprosthesis, and more particularly identification of leakage pathways, including leakage pathways in for aortic valves. This is of interest in pre-interventional planning to optimize endoprosthesis selection and/or design. In such embodiments, a prediction of whether or not leakage paths occur is made based on fitting of a virtual device on images of the anatomy of the patient. Moreover, identification of leakage pathways is of interest in the context of post-intervention analysis to help determine if there is a leakage pathway between the implant and the aorta wall.

Thus, provided herein are methods for determining the presence of one or more leakage paths between an endoprosthesis and the anatomy of a patient in which said endoprosthesis is to be positioned, wherein the method comprises generating a 3D model or a surface geometry of the anatomy in which the endoprosthesis is to be position and of the endoprosthesis and virtually positioning the 3D model or surface geometry of the endoprosthesis in that of the anatomy. Thereafter the distance between the endoprosthesis and the surrounding anatomical tissue parts in this virtual position is analyzed and .the presence of leakage paths between the endoprosthesis and said anatomy in which the endoprosthesis is to be positioned is determined based thereon.

In particular embodiments of the methods envisaged herein, the step of virtual positioning of the (model of the) endoprosthesis in the (model of the) anatomy encompasses virtually deploying the endoprosthesis therein. This may involve the use of one or more numerical simulation methods, such as finite element analysis, virtual morphing techniques and/or virtual unfolding techniques.

In particular embodiments of the methods envisaged herein, the step of generating a 3D model or a surface geometry comprises at least partially segmenting and/or meshing said anatomy in which the endoprosthesis is to be positioned and optionally at least partially segmenting and/or meshing the endoprosthesis, and generating a 3D model or a surface geometry from said segmented and/or meshed feature. In particular embodiments of the methods envisaged herein, the segmented wireframe of the endoprosthesis is virtually wrapped with a surface, thereby virtually recreating a sealing skirt for the endoprosthesis model.

In particular embodiments of the methods envisaged herein, the step of analyzing the distance between the endoprosthesis and the surrounding anatomical tissue parts in the chosen virtual position comprises the use of distance map calculations, volume inversion calculations or fitting structures analysis.

In particular embodiments of the methods envisaged herein, the step of determining from the distance analysis the presence of leakage paths between the endoprosthesis and the anatomy in which the endoprosthesis is to be positioned, comprises determining if a continuous fluid flow path between said endoprosthesis and said patient's anatomy is present in said virtual position.

In particular embodiments of the methods envisaged herein, the analysis of the distance between the endoprosthesis and the surrounding anatomical tissue parts in said virtual position additionally comprises further geometrical analysis such as determination of the ellipticity and/or circumference of the anatomical tissue and/or the endoprosthesis.

In particular embodiments, the methods envisaged herein comprise the step of visualizing calcifications and taking these into account in the calculations.

In particular embodiments the methods envisaged herein encompass determining leakage paths for different types of endoprosthesis, said different types of endoprosthesis having a different size and/or shape.

In particular embodiments of the methods envisaged herein, the steps of positioning and distance analysis for the determination of leakage paths are performed for a first endoprosthesis model and at least once repeated for a further endoprosthesis model. In particular embodiments, the further endoprosthesis model is an optimized model based on the analysis of the leakage paths for the first endoprosthesis model.

In particular embodiments the methods envisaged herein comprise determining leakage paths for different virtual positions of said endoprosthesis.

In particular embodiments of the methods envisaged herein the endoprosthesis is an intraluminal endoprosthesis, such as a stent, graft, stent-graft, vena cava filter, tubular expandable framework or heart valve frame.

As indicated above, the methods envisaged herein are also of interest in determining leakage pathways for and endoprosthesis after implantation thereof. Accordingly also provided herein are methods for determining the presence of one or more leakage paths between an endoprosthesis and the anatomy of a patient in which said endoprosthesis has been positioned, which methods comprise generating a 3D model or a surface geometry of the endoprosthesis and of the anatomy in which said endoprosthesis has been positioned, based on one or more images thereof and analyzing the distance between the endoprosthesis and the surrounding anatomical tissue parts based on these 3D models or surface geometries. The analysis of these distances makes it possible to determine the presence of leakage paths between the endoprosthesis and the anatomy in which the endoprosthesis is positioned.

Also provided herein are computer program, which, when run on a computer, perform a method for determining leakage paths between an endoprosthesis and a patient's anatomy as described above. BRIEF DESCRIPTION OF THE DRAWINGS

The following description of the figures of specific embodiments is merely exemplary in nature and is not intended to limit the present teachings, their application or uses. Throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features.

Figure 1 Figure 1 illustrates the structure of a typical stent (1 ) for a valve (2) comprising a wire structure (3) and a sealing skirt (4).

Figure 2 Figure 2 illustrates how, starting from post-interventional medical images (A) the implant and the surrounding tissue are segmented (B) and a 3D model is generated (C).

Figure 3 Figure 3 illustrates how, from a 3D model of the patient's anatomy and the implant and using distance mapping between the implant and the border of the surrounding tissue a distance map can be generated showing regions where good sealing is obtained (10 - dark regions) and regions where poor sealing occurs (1 1 - light regions). Leakage paths (12) can be detected from these generated images.

Figure 4 Figure 4 illustrates how, starting from the pre- (A) and post- interventional (B) medical images, the anatomy and, in case of the post-interventional images, the implant is segmented and a 3D model is built. In addition the calcifications are segmented and reconstructed in both pre- and post-interventional images.

Figure 5 Figure 5 illustrates the traditional measurement of the geometry of the annulus in a plane perpendicular to the annulus in both pre- (A) and post-interventional (B) images. Figure 5 C and D illustrates the additional information 3D models offers (C) and the result of a distance map calculation showing the distance between the implant and the surrounding tissue (D). Figure 6 Figure 6 illustrates the results of calcification volume measurement. The calcifications are separated along the leaflets, thereby evaluating the calcification distribution.

Figure 7 Figure 7 illustrates the results of the distance map calculation. Leakage paths and the interaction with calcifications can be detected from these images.

DETAILED DESCRIPTION

The present invention will be described with respect to particular embodiments but the invention is not limited thereto.

As used herein, the singular forms "a", "an", and "the" include both singular and plural referents unless the context clearly dictates otherwise.

The terms "comprising", "comprises" and "comprised of" as used herein are synonymous with "including", "includes" or "containing", "contains", and are inclusive or open-ended and do not exclude additional, non-recited members, elements or method steps. The terms "comprising", "comprises" and "comprised of when referring to recited members, elements or method steps also include embodiments which "consist of" said recited members, elements or method steps.

Furthermore, the terms first, second, third and the like in the description, are used for distinguishing between similar elements and not necessarily for describing a sequential or chronological order, unless specified. It is to be understood that the terms so used are interchangeable under appropriate circumstances and that the embodiments described herein are capable of operation in other sequences than described or illustrated herein.

All documents cited in the present specification are hereby incorporated by reference in their entirety.

Unless otherwise defined, all terms used in the present disclosure, including technical and scientific terms, have the meaning as commonly understood by one of ordinary skill in the art to which it belongs. By means of further guidance, definitions for the terms used in the description are included to better appreciate the present teaching. The terms or definitions used herein are provided solely to aid in the understanding of the embodiments.

Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment as described herein. Thus, appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment, but may. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to a person skilled in the art from this disclosure, in one or more embodiments. Furthermore, while some embodiments described herein include some but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the present scope, and form different embodiments, as would be understood by those in the art.

Method and tools are provided which may be used for assessing leakage problems with an endoprosthesis. More particularly, the methods and tools allow the analysis of the quality of contact between an endoprosthesis and the surrounding tissue, more particularly with the aim of identifying leakage paths between the tissue and the endoprosthesis.

As used in the present context the term "leakage path" or "leakage pathway" generally refers to a channel between the endoprosthesis or implant and the patient's anatomy or vessel wall through which a fluid (e.g. blood) can flow or wherein fluid can accumulate, thereby reducing the function of the endoprosthesis or implant (e.g. block or allow flow). Typically, the channel of the leakage pathway extends for some distance along the outer surface of the endoprosthesis or implant and allows an uncontrolled amount of fluid to pass along the outer wall of the endoprosthesis or implant. A leakage pathway results in an undesired flow outside of the endoprosthesis or implant thereby causing a suboptimal functioning of the endoprosthesis or implant and potentially leading to complexities during or after implantation.

The nature of the endoprosthesis is not critical. The term "endoprosthesis" refers to any prosthetic device placed within the body. The term "intraluminal prosthesis" refers to a prosthetic device placed within a lumen, vessel or duct of the body. The term "lumen" refers to any cavity or passageway within the body, and particularly refers to the inside space of a tubular structure, for example the inside space of an artery, intestine, etc.

An intraluminal endoprosthesis is typically an expandable prosthesis for implantation into a body lumen and includes devices such as stents, grafts, stent-grafts, vena cava filters, tubular expandable frameworks, heart valve frames, etc. The methods and tools provided herein are not limited to particular types of endoprosthesis such that suitable examples include, but are not limited to CoreValve ^® , Edwards ^® , Jenavalve ^® and Symetis ^® . The therapeutic objective may include but is not limited to the objective of restoring or enhancing flow of fluids through a body lumen or duct. The objective may alternatively be the prevention of flow of fluid or other material through the body lumen. In particular embodiments, the endoprosthesis is an aortic stent. More particularly it may be a transcatheter aortic valve implant containing a metal stent, a biological valve and sealing skirt.

The endoprosthesis is typically placed or envisaged to be placed in the lumen by a medical intervention. The term "intervention" as used herein refers to typical surgical and operative interventions comprising also minimally invasive intervention methods.

The methods described herein are for assessing the quality of contact between an endoprosthesis and the anatomy, and more particularly for determining leakage paths between an endoprosthesis and the anatomy in which the endoprosthesis is to be or has been positioned, typically comprise the steps of:

- generating a 3D model or a surface geometry of said endoprosthesis and said anatomy in which the endoprosthesis is to be or has been positioned, for example based on one or more images thereof;

- analyzing the distance between said endoprosthesis and the surrounding anatomical tissue parts; and

- determining from said distance analysis (potential) leakage paths between said endoprosthesis and the surface of the anatomical region in which the endoprosthesis has been or is to be positioned.

Typically the methods described herein to determine leakage paths start from the analysis of medical image data obtained from the anatomical region of the implant, i.e. the anatomy in which the implant is envisaged to be placed or is placed. The nature of these data can depend on the application of the method. Indeed, the methods described herein may be used as a pre-surgical step. Additionally or alternatively, the methods described herein may be used in post-intervention analysis to determine if there is a leakage pathway between the implant and the vessel wall. Thus, the methods described herein may be used as pre-intervention and/or post-intervention methods.

When the methods described herein are used as a pre-interventional step, a 3D model of the pathological patient's anatomy can be generated using images thereof and a virtual endoprosthesis can be placed within the 3D model. After the positioning of a virtual endoprosthesis, the methods described herein make it possible to assess whether or not and to what degree leakage would occur when such an endoprosthesis would be positioned as planned into the patient's anatomy. This way differently sized and/or shaped endoprostheses may be evaluated. Additionally or alternatively, the position of an endoprosthesis can be varied. Thus, the methods may allow for determining, prior to the actual intervention, the optimal size, form and position of the endoprosthesis. Thus, methods are disclosed for selecting the optimal implant and/or implant position prior to the intervention, which methods involve determining the presence of leakage paths upon virtual introduction of the implant into the patient's anatomy.

When the methods described herein are used as a post-interventional step, the methods may be used in post-intervention analysis to determine if there is a leakage pathway between the implant and the vessel wall. Thus, in these embodiments, the medical image data are post-interventional medical image data.

As detailed above, in particular embodiments pre-interventional methods are provided for analysis prior to actual positioning of the endoprosthesis into the anatomy of a patient. The information generated via these methods may further be used in the actual intervention, resulting in a minimum of surgical interventions required and also reducing the duration of the surgical intervention dramatically. Accordingly, the predictive clinical methods and tools are provided herewith for the qualitative assessment of endoprosthetic intervention, and more particularly evaluation of potential leakage paths between an endoprosthesis and the anatomy in which the endoprosthesis is to be placed. These methods may comprise the steps of:

a1. generating a 3D model or a surface geometry of the anatomy in which the endoprosthesis is to be positioned based on one or more images of said anatomy;

a2. generating or providing a 3D model or surface geometry of an endoprosthesis;

a3. virtually positioning the 3D model or surface geometry of the endoprosthesis in the 3D model of the anatomy in which the endoprosthesis is to be positioned; more particularly using numerical simulation methods which can include one or a combinations of techniques such as but not limited to finite element analysis, virtual morphing techniques and/or virtual unfolding techniques;

b1. analyzing the distance between the endoprosthesis and the surrounding anatomical tissue parts in the virtual position obtained in step a3; and

c1. determining from this distance analysis the presence of leakage paths between the endoprosthesis and the anatomy in which the endoprosthesis is to be positioned in the virtual position. In certain embodiments, the envisaged methods may be post-interventional methods whereby the endoprosthesis has already been positioned into the anatomy of a patient. In these embodiments, the methods may comprise the steps of:

A1. generating a 3D model or a surface geometry of an endoprosthesis and the anatomy in which the endoprosthesis is positioned based on one or more images thereof;

B1. analyzing the distance between the endoprosthesis and the surrounding anatomical tissue parts based on the 3D models or surface geometries generated in step A1 ; and

C1. determining from this distance analysis the presence of leakage paths between the endoprosthesis and the anatomy in which the endoprosthesis is positioned.

The pre-interventional and post-interventional methods described herein will be explained more in detail herein below. The envisaged methods typically rely on one or more images of the patient's anatomy in which the endoprosthesis has either already been positioned or where the endoprosthesis is envisaged to be positioned. Typically, the latter is a defective region of the patient's anatomy. In particular embodiments, the anatomical region is part of a blood vessel or valve. In particular embodiments, the methods described herein include the step of taking images of the patient's anatomy in the region in which the endoprosthesis has been positioned or images of the patient's anatomy where the positioning of the endoprosthesis is planned. The images may be any type of image that can be used to create a 2D or 3D image or model of the anatomical region. It is not required that the images are of the entire patient. Indeed, typically, only part of the patient is reflected in the image, provided that this part also includes the area of the anatomy in which the endoprosthesis has been or is envisaged to be positioned.

In particular embodiments, the images are 2D or 3D images. The images can be taken using any type of imaging apparatus or imaging technique which allows imaging or scanning the defective object in an accurate manner. These may include equipment such as cameras and scanners for industrial, household or medical use. In particular embodiments the imaging techniques and appliances used are typical medical imaging tools such as, but not limited to radiography, X-ray, ultrasound or fluoroscopy for 2D images and computer tomography (CT) scans, magnetic resonance imaging (MRI) scans for 3D images. It is noted that from a combination of 2D images a 3D model can be constituted (according to US 61/579,927 which is incorporated herein by reference). A summary of medical imaging has been described in "Fundamentals of Medical imaging", by P. Suetens, Cambridge University Press, 2002.

The term "medical imaging" as used herein refers to techniques and processes used to create images of the human or animal body (or parts and function thereof), typically for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and physiology).

Based on these images, a virtual anatomical structure, more particularly a 2D or 3D model of the anatomy in which the endoprosthesis has been or will be positioned is made. This 2D or 3D model allows a detailed analysis of the anatomical region (which often includes a defective region) and/or the position of the endoprosthesis. Preferably, a 3D model of the anatomy in which the endoprosthesis has been or will be positioned is made.

The 3D model of the anatomy with or without endoprosthesis is typically generated by extracting data from the medical images. For instance, in particular embodiments of the methods described herein the 3D model is represented by a surface geometry obtained by segmenting and/or meshing the anatomy in which the endoprosthesis has been or is to be positioned and optionally segmenting and/or meshing the endoprosthesis, and generating a 3D model or a surface geometry from said segmented and/or meshed features. However, other methods are known to the skilled person.

More particularly, the anatomy in which the endoprosthesis is to be positioned, or the implanted device (endoprosthesis) and the surrounding anatomical tissue, may be extracted through e.g., but not limited to, segmentation, grey value based thresholding, region of interest selection, volume rendering, manual region selection or any other method to select a subset of data from medical image data as known in the art.

When the methods described herein are used as a pre-interventional method, the extraction allows the generation of a 3D model of the anatomy in which the endoprosthesis is to be placed. For example, the anatomy into which the endoprosthesis is to be placed may be segmented or meshed at least partially with the aim of defining the surface geometry of the anatomy in a 3D model, preferably by converting the segmented data into a typical virtual 3D file format. Suitable visualization methods include, but are not limited to STL format or any other known triangulated mesh format, surface geometries, ISO surfaces, IGES, STEP, commercial CAD package file formats, volume rendering or any other method, etc. This allows the generation of a 3D model of the anatomy in which the endoprosthesis is to be placed.

When the methods described herein are used as a post-interventional method, the extraction allows the generation of a 3D model of the endoprosthesis, the surrounding anatomical tissue and the position of the endoprosthesis in the anatomy in which the endoprosthesis is placed. For example, the implanted device (endoprosthesis) and the surrounding anatomical tissue may be segmented or meshed at least partially with the aim of defining the surface geometry of both in a 3D model, preferably by converting the segmented data into a typical virtual 3D file format. Suitable visualization methods include, but are not limited to STL format or any other known triangulated mesh format, surface geometries, ISO surfaces, IGES, STEP, commercial CAD package file formats, volume rendering or any other method, etc. This allows the generation of a 3D model of the endoprosthesis, the surrounding anatomical tissue and the position of the endoprosthesis in the anatomy in which the endoprosthesis is placed.

Segmentation is typically done using a sequence of potential filtering, thresholding, region growing and editing the geometrical surface in 3D to remove artifacts, for example due to the metal of the implanted device. This can for instance be done using the injection of contrast fluid into the blood flow during image acquisition. The contrast fluid provides the blood with a relatively high and constant grey value. By applying a grey value threshold the blood can be segmented from the image. Using regiongrowing the segmented geometry is limited to connected pixels of the lumen(s), for example heart chambers. In a final step the lumens or chambers may be separated from each other and artifacts are removed manually by editing the segmented geometry in 3D.

In particular embodiments, the segmented wireframe of the endoprosthesis is wrapped with a surface in order to virtually recreate the sealing skirt of the implant, for example because it is not visible on the images.

As detailed above, in particular embodiments, particularly when the methods are used as pre-interventional methods, the methods involve performing virtual surgery to introduce one or more endoprostheses into the relevant anatomical region of the patient. In this way, a 3D model of a virtual implanted device can be obtained. More particularly, in certain embodiments, the virtual introduction or positioning of the endoprosthesis may encompass virtually deploying the endoprosthesis in a virtual anatomical structure, such as the 3D model generated based on step a1 as described above. In certain embodiments, the virtual surgery may be performed through numerical simulation of the implantation process, which can include one or more combinations of techniques such as but not limited to finite element analysis, virtual morphing techniques and/or virtual unfolding techniques.

In particular embodiments, different endoprosthesis are virtually introduced, which may vary in type, size and/or shape. By determining potential leakage paths for the different models, and comparing them it can be determined which type, size, shape would generate the most ideal placement of the endoprosthesis, having no or only a minimal amount of leakage. Additionally or alternatively, the virtual surgery involves introducing the endoprosthesis in different positions. By determining potential leakage paths for the different positions and comparing them, the optimal position for the endoprosthesis can be determined.

Once the 3D model of the (virtual) implanted device and the surrounding anatomical tissue are generated, the distance between the surface of the (virtual) implanted device and the surrounding anatomical tissue parts is analyzed. In the methods described herein, this distance is measured using the 3D model. Accordingly, the distance measurements do not require a direct measurement or interaction with the patient. The measurement can be done using multiple available methods, including for instance the use of distance map calculations, inversion of the volumes leaving the non-filled areas or virtually growing small geometrical structures (e.g. circles) into the space between the surface of the implanted device and the surrounding anatomical tissue parts and color plotting the diameters of the largest fitting objects (e.g. spheres).

In particular embodiments the step of analyzing the distance between said endoprosthesis and the surrounding anatomical tissue parts comprises the use of distance map calculations or volume inversion calculations.

Thus, in particular embodiments, using the surface geometry or the 3D model a distance map between the implant and the border of the surrounding tissue can be visualized by calculating, for each point on one object the distance to the closest point on the other object. A distance map shows regions of poor and good contact between the implant and the tissue. Alongside the vascular implants, leakage paths can be detected, by determining whether regions of poor contact extend over the entire length of the implant.

Volume inversion calculations may involve creating, from the surface geometry or the 3D model, a negative volume of the union between the implant and the surrounding tissue, leaving the gaps between implant and tissue. Again, leakage paths are determined by identifying whether regions of poor contact extend longitudinally from one end to the other end of the implant.

It should be noted that the analysis of the distance between the implanted device and the surrounding anatomical tissue parts may additionally include other types of geometrical analysis including for instance determination of the ellipticity and circumference of the anatomical tissue and/or the endoprosthesis. Accordingly, in particular embodiments the analysis of the distance between said endoprosthesis and said surrounding anatomical tissue parts additionally comprises further geometrical analysis chosen from determination of the ellipticity and/or circumference of said anatomical tissue and/or said endoprosthesis.

In particular embodiments the step of determining from said distance analysis the presence of leakage paths between said endoprosthesis and said anatomy in which the endoprosthesis has been or is to be positioned, comprises determining if a continuous fluid flow path between said endoprosthesis and said patient's anatomy is present. Determining the leakage paths may be done using maximal fitting sphere size measurements of the distance map. In particular embodiments this method can also be used to predict the degree of regurgitation. Also visual detection of leakage paths based on the distance map is envisaged.

The accurate determination of potential leakage paths prior to surgery provides valuable information for surgical planning, and may resulting in a minimum of surgical interventions required, reduce the duration of the surgical intervention dramatically, and/or improve the outcome of the surgery. The accurate determination of leakage paths may further be crucial in clinical studies and post-surgical studies as it will allow long-term result clinical studies or patient specific risk assessment. More particularly, the methods allow determining after the surgical intervention whether the endoprosthesis has been positioned well and if there are any leakages. When leakages are noticed, the application of the methods described above allow the assessment of the degree of leakage and will help during the decision making process whether or not additional intervention is required.

In particular embodiments of the methods for determining the presence of leakage paths described herein, calcifications are visualized and taken into account. More particularly, the methods may further comprise visualization and consideration in the calculations of calcifications located on or near the defective patient's anatomy. Calcification is typically encountered in blood vessels, such as in coronary arteries. It can be limited spotty calcification, linear calcification involving one or more sides of the lumen or can be dense and span the circumference of the lumen. Calcifications may interfere with endoprosthesis fit. For instance, calcifications at the base of the leaflets of a valve can interfere with the sealing skirt. Thus, when calcifications are present, these may be also taken into account. The information regarding the calcifications may be extracted from the images during the segmentation step.

In certain embodiments, the calcifications in both the pre- and post-interventional images may be visualized and 3D models can be generated. This offers the possibility to analyze the movement of the calcifications and the interaction with the implant. Their position with respect to implant deformation and possible leakage paths is assessed. As detailed above, depending on the application of the methods described herein, further steps can be envisaged. In particular embodiments, the methods are used as pre- interventional methods and may involve evaluating possible leakage paths for different types of endoprosthesis, whereby different types of endoprosthesis refers to endoprosthesis of different sizes and/or shapes.

It can further be envisaged that the latter may also be of interest in the context of optimizing patient-specific endoprosthesis designs. In such methods, a first model can be virtually introduced into the patient region and identification of potential leakage paths by the methods described herein can be used to further optimize the patient-specific endoprosthesis. More particularly, in particular embodiments, method steps a2, a3, b1 and c1 described above are performed for a first endoprosthesis model and at least once repeated for a further endoprosthesis model, wherein the further endoprosthesis model is an optimized model based on the first endoprosthesis model.

In certain embodiments, the pre-interventional methods described herein involve evaluating possible leakage paths for different positions of an endoprosthesis in the patient lumen.

In particular embodiments of the methods described herein, the endoprosthesis is an intraluminal endoprosthesis, more particularly an endoprosthesis chosen from stents, grafts, stent-grafts, vena cava filters, tubular expandable frameworks, heart valve frames, etc.

In a further aspect, methods are provided for reducing the risk of leakage paths upon implantation of a prosthesis such as an endoluminal endoprosthesis, which methods involve one or both of the following:

- pre-interventionally identifying the optimal implant based on the leakage pathway analysis methods described herein using virtual surgery; and/or

- determining the presence of leakage pathways after implantation based on the leakage pathway analysis methods described herein.

In particular embodiments, the methods are applied in the context of reducing the risk for paravalvular regurgitation upon implantation of an aortic valve or a pacemaker. Thus, methods are provided for reducing the risk of complications of endoprosthesis implantation resulting from leakage paths, which methods involve the identification of (potential) leakage paths described herein.

A further aspect provides computer programs and systems and tools comprising computer programs for carrying out the methods described herein. In particular embodiments, computer programs and systems and tools comprising computer programs are provided, which, when run on a computer, provide a leakage path evaluation according to one or more embodiments as described herein above. In particular embodiments the computer programs may be adapted to perform the different steps of the methods described above. In further embodiments, computer programs comprise software code adapted to perform the steps of the methods as described herein. The data processing system or computer program envisaged in this context particularly refer to computer aided analysis and design systems and programs such as CAD/CAM systems or programs. Said computer programs typically comprise tools for loading images of the anatomy in which the endoprosthesis has been or will be positioned, tools for generating a 3D model of said patient's anatomy (optionally including the endoprosthesis positioned therein) based on the images, tools virtually deploying the endoprosthesis into the virtual anatomical structure, tools analyzing and/or determining the distance between the implanted device and the surrounding anatomical tissue parts, and tools evaluating and/or determining leakage paths. Typically, such tools include Finite Element Analysis solvers as described in the art. The present invention will be illustrated by the following non-limiting embodiments.

1. Post-interventional leakage path analysis for an endoprosthesis An example of an endoprosthesis for which the methods described herein can be used is illustrated in Figure 1. However, as indicated herein, the methods claimed herein are not limited to a specific endoprosthesis structure.

Where the analysis is post-interventional, images are taken from the region of the implant, as illustrated for one embodiment in Figure 2. A 3D model (Figure 2C) is then generated, e.g. by segmenting the images. The distance between the implant and the border of the surrounding tissue is then analyzed and a distance map is generated showing regions where good sealing is obtained as illustrated in Figure 3 (10 - dark regions) and regions where poor sealing occurs (1 1 - light regions). Leakage paths (12) can be detected from these generated images.

2. Taking into account calcifications in leakage path analysis

Pre- and post-interventional medical images were provided from the region where the endoprosthesis is introduced. The images are segmented and a 3D model is generated of the implant and the surrounding anatomical tissue. The calcifications are segmented and reconstructed in both pre- and post-interventional images, so as to determine the movement thereof. This is illustrated for the pre-interventional images in Figure 4A and the post-interventional images in Figure 4B.

3. Further embodiments

Figure 5 illustrates the traditional measurement of the geometry of the annulus in a plane perpendicular to the annulus in both pre- (A) and post-interventional (B) images. Figure 5 C and D illustrates the additional information 3D models offers (C) and the result of a distance map calculation showing the distance between the implant and the surrounding tissue (D).

Figure 6 illustrates the results of calcification volume measurement. The calcifications are separated along the leaflets, thereby evaluating the calcification distribution.

Figure 7 illustrates the results of the distance map calculation. Leakage paths and the interaction with calcifications can be detected from these images.