Computer-Implemented Method and Non-Transitory Computer-Readable Medium Containing Instructions for Implementing the Same

Abstract

In summary, the present invention provides a technical solution that performs one or more implantable medical devices to determine the optimal device for a patient's vessel. This technical solution advantageously ensures that clinicians can take into account many of the important factors for placement, such as wall contact, porosity, flow reduction and obstruction, and vessel geometry, when planning the deployment of the implantable medical device. In addition, a computationally efficient method for performing deployment planning of the implantable medical device is provided.

Description

[Technical field]

[0001] The present invention relates generally to the simulation of implantable medical devices, such as blood flow altering devices or implantable intravascular devices, within a patient's body to determine the optimal device prior to surgery. [Background technology]

[0002] Clinicians using implantable medical devices, such as stents and other intravascular or implantable neurovascular devices, often place them in a radially compressed state in a delivery system in difficult to access areas of the patient's body. Once positioned, the implantable medical device is then deployed by the delivery system. The effective function of the device after a particular procedure depends on the particular final deployed dimensions and configuration of the implantable medical device. The quality of the "fit" of the device in this final position depends on many factors, including the characteristics of the implantable device, the forces applied during deployment, and the forces applied by the patient's body.

[0003] If the implantable medical device is too short after deployment, it may not adequately serve its intended purpose, and conversely, if the implantable medical device is too long after deployment, it may block blood flow that it was not intended to block.

[0004] An implantable medical device may have a variable diameter along its longitudinal axis in its deployed configuration, and may expand or contract in length along its longitudinal axis relative to the diameter along its longitudinal axis. Thus, if the diameter of the implantable medical device is incorrect, this may then affect the length of the device, causing the problems mentioned above. An incorrectly fitting device may further cause poor performance, migration of the device from its intended location, and / or thromboembolic complications. In addition to the overall deployed dimensions of the device, certain final configuration features, such as wire placement, also affect the performance of the implantable device.

[0005] It is therefore important for a clinician or other medical professional to ensure that the correct size implantable medical device is used with the appropriate characteristics for a particular application and to plan where the implantable medical device will be deployed by the delivery system, particularly since a radially compressed implantable medical device will expand into the area in which it is placed and its final configuration depends on several factors, making it difficult to accurately predict the final configuration of the device after deployment.

[0006] Current systems that allow clinicians to plan the deployment of implantable medical devices often utilize two- or three-dimensional images of the patient's placement position. However, these systems do not allow the clinician to consider many of the important factors mentioned above to objectively and reproducibly determine the optimal device for a particular procedure. Thus, the decisions made by individual clinicians may vary widely depending on personal preferences and experience. Summary of the Invention [Problem to be solved by the invention]

[0007] Thus, there is a need for software to determine which implantable medical devices have characteristics that will perform best when placed in particular areas within a patient's body, and to assist clinicians in determining the best location to place the selected implantable medical device prior to initiating a surgical procedure to place the device in the patient. [Means for solving the problem]

[0008] In a first aspect, the present invention provides a computer-implemented method for simulating the placement of a plurality of implantable medical devices to determine an optimal implantable medical device at a target placement location within a patient's vasculature, the method including receiving image data corresponding to the patient's vasculature; creating a three-dimensional model of the patient's vasculature based on the image data; simulating deployment configurations of the plurality of implantable medical devices at target locations within the three-dimensional model of the vasculature; determining a suitability metric for each of the simulated implantable medical devices, the suitability metric providing a measure of suitability of the deployed implantable medical device within the patient's vasculature; and outputting a representation of the optimal implantable medical device based on the suitability metric.

[0009] By simulating the placement positions of multiple implantable medical devices and calculating a suitability metric for each simulated device, a clinician, or medical professional, can determine the optimal device prior to surgery. Given that it may be difficult to accurately predict the effects of device characteristics, the patient's body, and placement procedures on device performance prior to surgery, the present method allows for accurate prediction of the optimal device and can assist clinicians in selecting the optimal device for a particular procedure. By determining the optimal device prior to surgery, the chances of success are significantly increased, improving patient outcomes and reducing the chances of subsequent surgery. Automating the selection of the optimal device provides a more objective measure compared to existing methods that rely heavily on the clinician's personal preferences and biases based on past experience.

[0010] Broadly speaking, the present invention provides a technical solution that allows endovascular implantable medical devices to be simulated inside a patient's body in order to determine the optimal device. This technical solution advantageously ensures that when planning the deployment of an implantable medical device, a clinician or other medical professional can take into account many of the important factors for placement, such as wall contact, porosity, blood flow obstructions, as well as vessel geometry, in easily understandable and automatically generated metrics. Furthermore, the present invention provides a computationally efficient method for performing deployment planning of an implantable medical device.

[0011] As used herein, the term implantable medical device is intended to mean a medical device that is implanted, for example, in a body cavity, in particular in the vasculature, by minimally invasive surgical procedures.

[0012] In a preferred embodiment, the implantable medical device is a blood flow modification device such as an implantable intravascular device, a braided stent, or an intracapsular device, but may alternatively be a stent graft, a laser cut stent, or an implantable neurovascular medical device. The implantable neurovascular medical device may include, for example, a stent such as an arterial stent, an intracranial stent, or a carotid stent, an embolic coil, an aneurysm coil, a flow diverter, an embolic protection device, or a neurothrombectomy device. A blood flow modification device is a device that treats by occluding a diseased blood vessel that forms an aneurysm and redirecting normal blood flow. Stent grafts are often used to treat aortic aneurysms and aortic dissections, while laser cut stents are also used to treat stenosis. Embolic coils are often used to treat intracranial aneurysms by inducing thrombus.

[0013] An instrument or tool used in implanting an implantable medical device, such as a catheter, balloon system, guidewire, or stent retriever, may additionally be simulated when simulating a deployed configuration of multiple implantable medical devices at a target location. The instrument or tool may be simulated to simulate use in implanting an implantable medical device or use in aborting implantation of an implantable medical device. Alternatively or additionally, the instrument or tool may be simulated to aid in simulating the placement of an implantable medical device.

[0014] The target location is the location within the vasculature where the implantable medical device is embedded. The target location may be defined between a start point and an end point, where the implantable medical device is preferably deployed at the start point and extends toward the end point during deployment. The target location is preferably a portion of the vessel within the vasculature, i.e., the length of the vessel between a distal point and a proximal point. The implantable device preferably begins deployment at the distal point and extends toward the proximal point during deployment. The length between the start point (distal) and the end point (proximal) of the target location is defined as the target length. The percentage of the target length that the device extends (from the distal point toward the proximal point) depends on several factors, including one or more of the unconstrained length of the implantable device (the length of the device in a fully expanded state assuming no external forces are applied), the forces applied by the patient's vasculature, the forces applied by the delivery system during deployment, and the mechanical properties of the device. In some examples, the target location may be within an aneurysm. This is particularly the case for intrasaccular devices. In this case, the target location may be defined by the inner wall of the aneurysm.

[0015] Preferably, simulating the deployment configuration of the plurality of implantable medical devices at the target location within the three-dimensional model of the vascular structure includes performing a numerical simulation of the placement of the implantable medical devices based on one or more characteristics of the implantable medical devices and one or more characteristics of the patient's vascular structure. In particular, the simulation can include a mechanical and / or geometric simulation of the device's expansion. More specifically, the numerical simulation preferably includes simulating the expansion of the implantable medical devices within constraints imposed by the shape of the patient's vascular structure. In some examples, the simulation includes simulating forces applied to the implantable medical devices by the patient's vascular structure and, optionally, a delivery system used to place the devices. The method can include numerically simulating the expansion configuration of the implantable medical devices within constraints imposed by the patient's vascular shape as defined in the three-dimensional model, the numerical simulation preferably also being based on mechanical constraints of the implantable medical devices, such as the braiding of the wires of the devices.

[0016] Some examples of simulating a deployed configuration of an implantable medical device may include the following steps: a. Determine a ratio that indicates the change in stent length as a function of the local morphology of the vascular structure; b. Obtaining a 3D centerline from a 3D model of the vascular structure; c. Defining the location of the starting point for placing the device on the three-dimensional model of the vascular structure; d. Divide the centerline of the vascular structure into multiple parts; e. determining descriptive parameters of the morphology of the vascular structure for a first segment of the plurality of segments, where the descriptive parameters include geometric parameters and / or mechanical factors; f. calculating a stent length for the first segment using the exponential ratio of step a); g. The length of the segment calculated in step f) is subtracted from the nominal length of the stent to obtain a new nominal length; if the new nominal length is different from zero, steps e) to g) are repeated for the preceding and successive segments; if the new nominal length is approximately zero, all distances for each segment are summed and this sum becomes the final length of the stent after deployment.

[0017] The ratio in step a) may be determined based on mathematical modeling.

[0018] The suitability metric preferably includes a measure of correspondence between the dimensions of the implantable medical device in the deployed configuration and the corresponding dimensions of the target location. In this way, the assessment of optimality is based on the correspondence of the dimensions of the device in the deployed configuration to the surrounding target locations. The dimensions of the device in the deployed configuration may include length, volume, thickness, diameter, or height. Preferably, the target location is a vessel portion having a target length between a distal location and a proximal location, and the suitability metric provides a measure of correspondence between the deployed length of the device and the target length of the target location. Alternatively, the target location may be an aneurysm having a target diameter, and the suitability metric provides a measure of correspondence between the deployed diameter of the device and the target diameter. The measure of correspondence between the dimensions of the device in the deployed configuration and the corresponding dimensions of the device may be referred to as a size index. The size index may take the form of a value between 0 and 1, with 1 indicating optimality and 0 indicating poor suitability. The size index may take a value of 1 if the dimensions of the deployed device are within a predetermined range of the target dimensions.

[0019] The compatibility metric preferably comprises a measure of adhesion between the implantable medical device in the deployed configuration and the wall of the vasculature, in particular a measure of adhesion between a surface of the implantable device in the deployed configuration and an adjacent wall of the blood vessel, where a portion of the blood vessel wall corresponding to the aneurysm neck is preferably excluded. The measure of adhesion may be referred to as an adhesion index. The measure of adhesion preferably comprises a measure of the distance between an outer surface of the implantable medical device in the deployed configuration and the wall of the vasculature. Preferably, the method comprises determining an average distance between an outer surface of the implantable medical device in the deployed configuration and the wall of the vasculature, preferably excluding a portion of the surface area of ​​the implantable medical device corresponding to the aneurysm neck.

[0020] The measure of adhesion preferably includes an adhesion index that includes the percentage of the surface of the implantable medical device that is within a threshold distance from the wall of the vasculature, preferably excluding the portion of the surface area of ​​the implantable medical device that corresponds to the aneurysm neck. The threshold distance may be 0.1-1 mm, preferably 0.5 mm, where a distance between the surface of the implantable medical device and the adjacent wall of the vasculature within this range indicates good adhesion (and therefore indicates a device with good compatibility).

[0021] If the target location includes a blood vessel containing an aneurysm, the adhesion index can be calculated by determining a portion of the blood vessel corresponding to the aneurysm neck, excluding a portion of the outer surface of the implantable medical device that corresponds to the determined portion of the blood vessel, and calculating the adhesion index over the remaining portion of the outer surface of the implantable medical device. In this manner, an improved measure of adhesion is provided when adhesion around an aneurysm is not expected.

[0022] Determining the portion of the vessel or vascular structure corresponding to the aneurysm neck may include one or more of the following: determining a portion of the vessel where the radius of the vessel portion is greater than the average radius over the remainder of the vessel at the target location; determining a portion of the vessel where the radius of the vessel portion is greater than the centerline vessel radius by more than a threshold value; determining a portion of the vessel where the vessel radius has an apex along the length of the vessel at the target location.

[0023] The centerline radius can be defined as the minimum distance between the centerline of a vessel and the vessel wall, or the average distance between the centerline of a vessel and the vessel wall.

[0024] When the target location includes a vessel containing an aneurysm, the suitability metric can include a landing zone index, which includes a measure of the length of the landing zone of the implantable medical device, the landing zone including longitudinal sections of the deployed implantable medical device located distal and proximal to the aneurysm neck at the target location, and the landing zone index indicates improved suitability of the device when the length of the landing zone exceeds a threshold or within a threshold range. When the length of the landing zone exceeds the threshold, this ensures good origination, good adhesion, and avoids device migration. By including a measure of the length of the landing zone of the implantable intravascular device or blood flow modifying device in the suitability metric, the optimal device for the target deployment location in the patient's vasculature can be more accurately determined, especially when the landing zone exceeds the threshold, and preferably when the adhesion in the landing zone exceeds the threshold, since the landing zone indicates a more compatible device. The landing zone index in some embodiments can provide a measure of the length of the longitudinal sections of the device located proximal and distal to the aneurysm neck having an adhesion index above the threshold.

[0025] The landing zone index may include a measure of the fit of the landing zone of the device. The landing zone index may include a measure of the percentage difference between the diameter of the vessel and the diameter of the device within the landing zone. The percentage difference may be determined over a length of the device within the landing zone that corresponds to an optimal landing zone length. In one example, the landing zone index may be calculated by integrating a weighting function over the landing zone that assigns weights from 0 to 1 according to the fit of the device.

[0026] The Landing Zone Index can be calculated as follows: TIFF2025501322000002.tif17170 Where: TIFF2025501322000003.tif18170 TIFF2025501322000004.tif19170 Here, S p is the size exponent of the proximal landing zone, and S d is the size index of the distal landing zone, and L opt is the optimal landing zone length for the implantable medical device, and L device is the length of the placed implantable medical device and Wf is the weighting function.

[0027] The weighting function Wf can take a value of 1 if the device is optimally sized and less than 1 if the device is sub-optimally sized. For example, the weighting function can assign a weight of 0 if the implantable medical device has a deployed diameter that is less than 1%, 5%, or 10% larger or more than 20%, 40%, or 60% larger than the diameter of the vessel in the landing zone. The weighting function can assign a weight of 1 if the implantable medical device has a deployed diameter that is between 0% and 20% larger based on the size of the vessel in the landing zone.

[0028] The weighting function may be a linearly increasing function in the region between the oversized / undersized range and the optimal size range, e.g., 5% to 0% undersized (i.e., when the device has a diameter 0% to 5% smaller than the vessel diameter), taking a value of 0 at 5% undersized and a value of 1 when the diameters match perfectly. Similarly, the weighting function may be a linearly decreasing function in the region between 20% to 60% oversized (i.e., when the deployed device has a diameter 20% to 60% larger than the vessel diameter), taking a value of 1 at 20% oversized and 0 at 60% oversized.

[0029] Preferably, the suitability metric comprises a porosity index. Preferably, the porosity index comprises a measure of the porosity of the blood flow altering device in a deployed configuration.

[0030] By including in the fit metric a measure of the porosity of the implantable endovascular or blood flow altering device in its deployed configuration, an optimal device for a target placement location within a patient's vasculature can be more accurately determined. In particular, the porosity of an implantable endovascular or blood flow altering device can change as the device's mesh deforms, expands and contracts in various regions, depending on its placement location and configuration, and this porosity can affect the performance of the deployed device.

[0031] If the target location includes a blood vessel containing an aneurysm, the porosity index can be calculated by determining a portion of the vascular structure corresponding to the aneurysm neck; selecting a portion of the outer surface of the placed implantable medical device that corresponds to the determined portion of the blood vessel; and determining the porosity of the selected portion of the outer surface of the placed implantable medical device.

[0032] Determining the portion of the vessel or vascular structure corresponding to the aneurysm neck may include one or more of the following: determining a vessel portion where the radius of the vessel portion is greater than the average radius over the remainder of the vessel at the target location; determining a vessel portion where the radius of the vessel portion is greater than the centerline vessel radius by more than a threshold value; determining a vessel portion where the vessel radius has an apex along the length of the vessel at the target location.

[0033] The porosity index is preferably determined such that the porosity index is indicative of a more compatible device with porosity below a threshold value for the selected portion of the exterior surface. An average porosity may be determined over the selected portion of the exterior surface and compared to the threshold value. Alternatively, a weighting function may be integrated over the surface area of ​​the selected site, with the weighting function taking a value of 1 if the porosity is within the target porosity range and a value less than 1 if the porosity is outside the porosity range. The weighting function may be a linear function between 0 and 1 in the transition porosity range between the low porosity range and the optimum porosity range.

[0034] Optionally, the suitability metric is based on an occlusion value that provides a measure of the extent to which a placed implantable intravascular device or blood flow altering device occludes side branches within a three-dimensional model of the vascular structure, with fewer occluded side branches indicating a more suitable device.

[0035] By including an occlusion value that provides a measure of the degree to which a placed implantable intravascular device or flow altering device occludes side branches within a three-dimensional model of the vasculature, the optimal device for the target location within the vasculature can be more accurately determined, as device fit is improved, especially where side branches are less occluded and blood flow impairment is limited.

[0036] Optionally, the suitability metric is based on a vascular shape value that provides a measure of the extent to which a placed implantable intravascular device or blood flow altering device extends across one or more bends in a three-dimensional model of a vascular structure that includes a radius of curvature less than a threshold, the vascular shape value indicating a more suitable device with fewer bends below the radius of curvature threshold at the placement location of the device.

[0037] By including a measure of the extent to which a placed implantable endovascular or blood flow modifying device extends across one or more bends in a three-dimensional model of the vasculature that include a radius of curvature below a threshold in the fit metric, an optimal device for a target placement location within the patient's vasculature can be more accurately determined. In particular, placing an implantable endovascular or blood flow modifying device inside a vascular bend can be difficult, potentially resulting in poor adhesion since a bent implantable endovascular or blood flow modifying device is more difficult to fully expand. Thus, the fewer bends that fall below the device radius of curvature threshold, the better the fit of the device.

[0038] Preferably, the suitability metric includes a blood flow modification index, the blood flow modification index including a measure of change in blood flow through the patient's vasculature. Preferably, the blood flow modification index includes a measure of reduction in blood flow to the aneurysm, for example through the aneurysm neck. Preferably, the blood flow modification index is calculated by simulating blood flow through the patient's vasculature without the presence of the implantable medical device, simulating blood flow through the patient's vasculature including a deployed configuration of the implantable medical device, and determining a blood flow modification index including a measure of change in blood flow due to the deployed implantable medical device. Preferably, the target location includes a blood vessel including an aneurysm, and the measure of change in blood flow due to the deployed implantable medical device includes a measure of reduction in blood flow to the aneurysm, for example through the aneurysm neck.

[0039] The method of these embodiments may include performing a first computational fluid dynamics simulation of blood flow within the patient's vasculature prior to placement of the implantable medical device, performing a second computational fluid dynamics simulation of blood flow within the patient's vasculature, and determining a change in blood flow in the patient's vasculature between the first and second computational fluid dynamics simulations.

[0040] More specifically, determining the change in blood flow in the patient's vascular structure between the first and second computational fluid dynamics simulations includes determining one or both of a maximum blood flow velocity and a spatial average blood flow velocity within the aneurysm for the first and second computational fluid dynamics simulations, and determining a rate of blood flow reduction (blood flow velocity) within the aneurysm.

[0041] Alternatively, determining a change in blood flow in the patient's vascular structure between the first and second computational fluid dynamics simulations may include determining a blood flow velocity (e.g., m) through the aneurysm neck between the first and second computational fluid dynamics simulations. 3 The method includes determining a rate of decrease in blood flow velocity in the second simulation relative to the first simulation (units: per second) and determining a rate of decrease in blood flow velocity in the second simulation relative to the first simulation.

[0042] The blood flow modification index may indicate a more suitable device when the rate of blood flow reduction is above a threshold or within a target range. For example, the blood flow modification index may have a value between 0 and 1, with 1 indicating optimal blood flow modification. The blood flow modification index may have a value of 1 where the rate of blood flow reduction is above a threshold or within a target range, and a value below 1 where the rate of blood flow modification is outside of the optimal range.

[0043] The computational fluid dynamics simulation can include any known method capable of solving the Navier-Stokes equations, such as the finite volume method, the finite element method, the spectral element method, the lattice Boltzmann method.

[0044] Use of suitability metrics, including the flow modification index, allows for the performance of a device to be simulated and determined prior to device surgery, thereby enabling identification of devices with the best performance that may not be evident from other factors alone, such as sizing. Use of the flow modification index also allows for ranking of various types of implantable medical devices, e.g., flow modifying devices such as stents, or intracapsular and implantable neurovascular devices, allowing medical practitioners to identify the type of implantable medical device best suited for a particular case.

[0045] In some examples, the fitness metric includes a plurality of parameters selected from a size index, a fit index, a landing zone index, a blood flow modification index, an obstruction value, and a vessel shape value. Each parameter can take a value between 0 and 1, where 1 indicates a highly compatible device and 0 indicates a less compatible device. The fitness metric can include a weighted sum of each of the selected parameters.

[0046] The weights applied to the constituent parameters of the fitness metric can be determined by multiple regression (e.g., linear or polynomial) between the parameters (independent variables) and a measure of clinical outcome (dependent variable), such as aneurysm occlusion success rate or complication rate.

[0047] In a particularly preferred embodiment, the fit metric includes a fit index and a landing zone index, both of which provide an accurate index of a well-fitting device.

[0048] Preferably, the fitness metric includes a neck protrusion value that provides a measure of the distance a placed implantable medical device protrudes from outside the aneurysmal neck of the blood vessel into the blood vessel, with the neck protrusion value approaching zero indicating improved device fitness.

[0049] Preferably, the method for simulating deployed configurations of a plurality of implantable medical devices at target locations within a three-dimensional model of a patient's vasculature includes sequentially simulating the deployed configurations of the plurality of implantable medical devices in order of the unconstrained dimensions of the implantable medical devices.

[0050] Preferably, the method for simulating a deployment configuration of multiple implantable medical devices at target locations within a three-dimensional model of a patient's vasculature includes extracting a centerline from the three-dimensional model of the patient's vasculature, the centerline being a central axis of a blood vessel within the patient's vasculature, and numerically simulating expansion of the implantable medical devices along the centerline within the three-dimensional model of the patient's vasculature.

[0051] Preferably, the method for numerically simulating the expansion of an implantable medical device along a centerline within a three-dimensional model of a patient's vasculature is based on one or more of the properties of the implantable medical device, the geometric constraints imposed by the patient's vasculature, and the forces exerted on the implantable medical device by the patient's vasculature.

[0052] Preferably, the method of simulating the placement of a plurality of implantable intravascular devices to determine an optimal device for a target placement location within a patient's vasculature further includes determining a first selection of implant types in the plurality of implantable intravascular devices based on a first suitability metric, and determining an optimal device from the first selection of implantable intravascular devices based on a second suitability metric.

[0053] By first narrowing down a plurality of implantable intravascular devices to a first selection using a first suitability metric and then further narrowing down using a second suitability metric, the determination of the optimal device can be made more computationally efficient. In particular, the calculation of the first suitability metric may be less computationally intensive than the calculation of the second suitability metric. For example, the first suitability metric may include a size index and the second suitability metric may include one or more of a fit index, a landing zone index, a porosity index, and a blood flow modification index.

[0054] Determining a first selection of the plurality of implantable medical devices based on the first suitability metric may include simulating deployed configurations of the plurality of implantable medical devices, determining a difference between dimensions of the implantable medical devices in the deployed configuration and dimensions of corresponding target locations, and determining a first selection of the plurality of implantable medical devices in which the difference between the dimensions of the implantable medical devices in the deployed configuration and dimensions of the target location is below a threshold value.

[0055] Where the target location includes a vessel segment having a target length, the dimension of the implantable device may be the length of the device in a deployed configuration, and the corresponding dimension of the target location is the target length of the vessel segment.

[0056] The method may include sequentially simulating the deployed configurations of the plurality of implantable medical devices in order of the unconstrained dimensions of the implantable medical devices, preferably in order of increasing unconstrained dimensions. In particular, when the target location includes a vessel portion having a target length, simulating the deployed configurations of the plurality of implantable medical devices includes sequentially simulating the deployed configurations of the plurality of implantable medical devices in order of increasing unconstrained lengths of the plurality of implantable medical devices. In an example where the unconstrained dimension is the unconstrained length, the method includes selecting a first device having an unconstrained length that is less than the length of the target location, and simulating the deployed configuration of the first device to compare the deployed length of the device to the target length, where if the deployed length is less than the target length, selecting a second device having an increased unconstrained length compared to the first device, and repeating these steps until the selected device is determined to be positioned within the target length range based on the target length. The target length range may be centered on the target length, or the target length may be a lower limit of the target length range. The method preferably includes determining a second fitness metric for one or more selected devices having deployed lengths within the correct range. This process can be used for other dimensions, for example, the diameter of an intracapsular device, or the dimensions of a placed implantable device relative to the corresponding dimensions of a target location, coordinates which can be defined relative to within the patient's body.

[0057] By simulating the deployed configurations of multiple implantable intravascular devices sequentially from the shortest device to the longest device (or more generally from the shortest dimension of the device to the longest dimension), the simulation process becomes computationally more efficient. In particular, only a small additional length of the device may need to be simulated, rather than the entire device having to be fully resimulated each time. This reduces the computational burden of simulating multiple devices.

[0058] The method may include that, prior to simulating the deployment configuration of the plurality of implantable medical devices, the plurality of implantable medical devices are selected by determining a maximum vessel diameter at the target locations of the three-dimensional model, excluding a portion of the target locations corresponding to an aneurysm (the location of the aneurysm may be determined as defined above), and accessing a database of candidate devices to select a plurality of implantable medical devices in the database to be simulated as implantable medical devices having an unconstrained diameter within the target range based on the maximum vessel diameter. This provides an additional step of filtering the plurality of candidate devices by first selecting by diameter size. At this stage, no simulation is required, since the devices are selected based on the characteristics and morphology of the vascular structure and the unconstrained diameter of the candidate devices. Thus, the computational efficiency of the process of determining the optimal device from the plurality of candidate devices is improved.

[0059] Determining the optimal device from the first selection of implantable medical devices based on the second suitability metric can be determined using the method of determining a suitability metric described above. In particular, the second suitability metric may include one or more of the following: a fit index, a landing zone index, a porosity, a blood flow modification, an occlusion value, a vessel shape value. In a preferred example, the method includes determining a selection of multiple implantable medical devices based on a correspondence of the deployment dimensions to the corresponding dimensions of the target location, and then determining a fit index for each of the selected implantable medical devices to determine the optimal device.

[0060] Optionally, the method for simulating placement of a plurality of implantable medical devices to determine an optimal device for a target placement location within a patient's vasculature further includes ranking the plurality of simulated implantable medical devices based on a suitability metric.

[0061] Optionally, the plurality of implantable medical devices includes stents, such as braided stents. Alternatively, the plurality of implantable medical devices includes implantable intravascular devices, intracapsular devices, blood flow modification devices, or implantable neurovascular medical devices. The implantable neurovascular medical devices may include, for example, stents, such as arterial, intracranial, or carotid stents, embolic coils, aneurysm coils, flow diverters, embolic protection devices, or neurothrombectomy devices, and the like. An instrument or tool used when implanting an implantable medical device, such as a catheter, balloon system, guidewire, or stent retriever, may additionally be simulated when simulating the deployment configuration of the plurality of implantable medical devices at the target location. The instrument or tool may be simulated to simulate their use when implanting an implantable medical device or their use when aborting implantation of an implantable medical device. Alternatively or additionally, the instrument or tool may be simulated to assist in simulating the placement of the implantable medical device.

[0062] In some examples, the plurality of devices includes a plurality of implantable device types, e.g., a blood flow modifying device and an intracapsular device, or two or more of any of the implantable medical devices mentioned herein. The method may include determining a suitability metric for the different implantable device types, thereby providing an optimal device type for a particular application. In these examples, preferably the suitability metric includes a blood flow modifying metric, and the method selects an optimal device from the plurality of implantable device types based on the suitability metric.

[0063] According to a second aspect of the invention, a server is configured to carry out the method of the first aspect of the invention and optional features thereof.

[0064] According to a third aspect of the present invention, there is provided a non-transitory computer readable medium comprising instructions which, when executed by a processor, cause the processor to perform the method of the first aspect of the present invention and optional features thereof. [Brief description of the drawings]

[0065] Embodiments of the present invention will now be described, by way of example only, with reference to the accompanying drawings in which: [Figure 1] FIG. 1 illustrates generally a system suitable for implementing aspects of the present invention. [Diagram 2] FIG. 1 is a flow diagram illustrating a method for simulating the placement of multiple implantable medical devices performed by a system according to one embodiment. [Diagram 3] FIG. 2 is a flow diagram setting out a method for creating a three-dimensional model performed by a system according to one embodiment. [Figure 4a] FIG. 13 illustrates a user interface for selection of a region of interest according to one embodiment. [Figure 4b] FIG. 1 illustrates an example of a 3D model during the process of creating the 3D model, and in particular during segmentation. [Figure 4c] FIG. 1 illustrates an example of a 3D model during the process of creating the 3D model, and in particular during centerline extraction. [Figure 4d] FIG. 1 shows an example of a three-dimensional model during a simulation of the deployed configuration of an implantable medical device. [Figure 5a] FIG. 13 shows an example of a three-dimensional model for determining a measure of adhesion between an implantable medical device in a deployed configuration and the wall of a vasculature. [Figure 5b] FIG. 13 shows an example of a three-dimensional model when determining a measure of adhesion, with particular emphasis on the aneurysm neck. [Figure 6a]FIG. 1 illustrates an example of a saccular aneurysm within the vasculature. [Figure 6b] FIG. 1 shows an example of a three-dimensional model of a vascular structure with radius differences marked. [Figure 7a] 1 is a graph plotting centerline radius and cross-sectional area radius versus length of a vascular structure. [Figure 7b] FIG. 1 illustrates an example of a fusiform aneurysm within the vasculature. [Figure 8a] 1A-1C illustrate examples of implantable medical devices positioned within a vasculature. [Figure 8b] FIG. 8b shows a key to the size ratio weighting function used in FIG. 8a. [Figure 9a] FIG. 1 shows an example of a model of a vascular structure with size requirements of an implantable medical device marked. [Figure 9b] FIG. 1 shows an example of a model of a vascular structure with size requirements of an implantable medical device marked. [Figure 10] 1 is a table showing examples of manufacturer recommendations for placing particular implantable medical devices within a patient's vasculature. [Figure 11] FIG. 13 illustrates a user interface for selection of an implantable medical device for simulation, according to one embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0066] 1 illustrates a block diagram of a system 100 suitable for implementing embodiments of the present invention. The system 100 includes a server 102 communicatively coupled to a memory device 104 and a processor 106.

[0067] FIG. 2 illustrates a method for simulating the placement of multiple implantable medical devices to determine an optimal device for a target placement in a patient's vasculature. The method of FIG. 2 can be performed by any processor configured to execute the defined method steps, such as the systems described above. FIG. 3 is a flow diagram illustrating an algorithm used in creating a three-dimensional model of a patient's vasculature and simulating the deployment location of an implantable medical device, in this case a stent. Steps 300-306 correspond to steps 202 and 204 of the method according to the invention shown in FIG. 2. The simulation of stent deployment (step 307 of FIG. 3) is then repeated to simulate placement locations of multiple implantable medical devices, where a fitness metric is calculated for each and an optimal device is determined.

[0068] The plurality of implantable medical devices to be simulated may be obtained from a database of candidate devices and their associated manufacturer's guidance. The database may be stored on and retrieved from the memory device 104. The database may include various models of candidate devices manufactured by various manufacturers, each of which may include various sizes (e.g., various diameters and lengths), each of which may have a recommended vessel deployment diameter range specified in the manufacturer's guidance. The associated manufacturer's guidance may include the size of the device required for a particular size vessel, as well as the relationship between the length of the device after deployment and its diameter. By assuming that the expansion of the device is limited by the vessel diameter, it is possible to obtain an estimate of the deployed length of the device. However, this is an oversimplification that assumes that the vessel has a regular circular cross section, which may not be the case in reality. Thus, in one embodiment, the manufacturer's guidance may be used to select an initial plurality of devices from each manufacturer's model that have a minimum diameter greater than the maximum vessel diameter at the target location and simulated before working sequentially through the length sizes. FIG. 10 is an example of a table showing manufacturer's recommendations for placing a particular implantable medical device within a patient's vasculature.

[0069] At step 202, image data corresponding to a patient's vasculature is received. The image data may be a series of 2D images of the patient's vasculature and may be read in the form of single or multi-frame Digital Imaging and Communications in Medicine (DICOM) images, as shown at 300 in FIG. 3. The image data may be received by the processor 106 from a memory device 104. The image data may be stored on the memory device 104 communicatively coupled to the processor 106 for transferring the image data to the processor 106, for example, via a public network such as the Internet, or a private or virtual private network, or a data bus.

[0070] Optionally, a maximum intensity projection (MIP) model, volume rendering, or other three-dimensional rendering may also be created based on the image data before performing a complete three-dimensional reconstruction of the vessel shape and proceeding to step 204. These three-dimensional rendering techniques may be used to display the contents of the image data prior to the actual reconstruction of the vessel shape. Once the MIP model or volume rendering is created, user input, e.g., a mouse, trackpad, keyboard, may be used to rotate, move, and / or zoom the MIP model or volume rendering to allow the user to view all aspects of the model and select regions of interest.

[0071] In step 301 of FIG. 3, a region volume initialization is performed. In this step, a region of interest is selected. The selection may be made by a user manually defining the region of interest using a user interface, or the region of interest may be selected automatically by the software. FIG. 4a shows an example of a user interface for a user to select a region of interest. The user interface shows details of the image data file in the upper left corner, including the patient identification number for the image data, and the date and time the image data was taken. The user interface further shows a three-dimensional box superimposed on the initial three-dimensional rendering of the vessel shape. This three-dimensional box is the region of interest selection area, and can be rotated, moved, and / or enlarged using user input, e.g., mouse, trackpad, keyboard, to allow the user to see all sides of the model and select the appropriate region of interest. The user interface further includes a widget on the right side that includes a slide bar for adjusting the selection size of the region of interest.

[0072] The user interface further includes a banner menu located on the lower right side that includes multiple buttons for the user to select options such as opening a new set of image data, selecting a region of interest, selecting a display option for the model, selecting a stent to place, selecting hints to assist the program, saving the model, or exiting the program. If the option to select a stent to place is selected in the user interface, the widget of FIG. 11 is displayed, which allows the user to select the device manufacturer model, device diameter, and device length, and the deployed length of the device is displayed as it is simulated. As each of these is changed by the user, the corresponding display of the simulated device is changed as shown in FIG. 4d.

[0073] The region of interest is a selected region within the patient's vasculature where an implantable medical device may be placed, e.g., the location of an aneurysm. By focusing only on the region of interest within the patient's vasculature, rather than the entire imaged region, the amount of data to be processed is reduced, thereby reducing computational costs and speeding up the remaining steps of the method. As described above, rather than receiving a user's selection of the region of interest, e.g., by providing a UI with an ROI selection tool as described above, the region of interest may be determined automatically by the software. For example, the software may search the image to determine the location of the aneurysm (e.g., using one of the techniques described below) and automatically define an ROI around the identified aneurysm. If multiple possible aneurysms or regions of interest are identified by the software, the software may present several candidate ROIs to the user so that the user can select the intended ROI in further processing steps of the method.

[0074] If a region of interest is user selected, the model may be viewed in different display options to aid in region of interest selection, such as a shell mode (or hourglass mode) in which only the shell of the vasculature is shown (along with the centerline of the vasculature as described below), or an opaque mode in which the vasculature is made opaque to obtain a clear image of the entire vasculature. When a region of interest is selected, the method may proceed to step 204.

[0075] In step 204, a three-dimensional model of the patient's vasculature is created based on the image data. The three-dimensional model may be created by extracting clinically relevant information about the patient's vasculature from the image data that is used to reconstruct a three-dimensional model of the vessel shape to aid in pre-operative planning. The three-dimensional model may further show a centerline of the patient's vasculature. The centerline represents the central axis of a vessel within the vasculature and may be extracted as described below. The centerline radius is a measure of the general radius of a vessel. It may be calculated in many ways. For example, it may be defined as the minimum distance from a point on the centerline to the closest point on the patient's vessel wall within the region of interest. It may also be defined as the average or maximum distance from a point on the centerline to the closest point on the vessel wall in its circumference / cross section.

[0076] The creation of the three-dimensional model can be performed by segmenting the volume rendering of the image data, as shown in step 302 of FIG. 3, into separate portions of the volume corresponding, for example, to the blood vessels and aneurysms as the foreground, and the remaining volume as the background, as shown in FIG. 4b. The separate portions of the volume may be labeled as such, or may be identified by the blood vessels and aneurysms with the contrast agent used during image processing. FIG. 4b is an example of a three-dimensional model showing this separation as the foreground by coloring the blood vessels and aneurysms, and the remaining portion designated as the background. The example is shown in opacity mode, which makes the vascular structures opaque in order to obtain a clear image of the entire vascular structure. This example clearly shows the advantage of segmenting the rendering in this way, so that the vascular structures of the patient can be easily identified. The automated segmentation of the vascular structures can be obtained by one of the following methods: thresholding, region growing, and deformable models such as active contours and level set methods.

[0077] The creation of the three-dimensional model is further performed by meshing, as shown in step 303 of FIG. 3, to convert the labels generated during segmentation into a surface mesh of the patient's vasculature.

[0078] This step consists of creating a polygonal surface representation of the isosurface through a 3D scalar field sampled on a rectangular grid, i.e. on the DICOM image. For meshing, the Marching Cubes algorithm can be used. The Marching Cubes algorithm is an iterative algorithm for generating surfaces from 3D scalar fields. In one embodiment, the 3D scalar field is the intensity of the original DICOM image, or a derived function, e.g. a level set function obtained from a level set segmentation method.

[0079] Then, post-processing is applied to the generated surface mesh to simplify and clean up the surface to generate a good quality mesh, as shown in 304 of Figure 3. Mesh post-processing can include a step of identifying the largest connected components (e.g., using graph theory, depth-first search, discarding small disconnected components), a mesh simplification step to reduce the number of triangles and simplify the mesh (e.g., using edge collapse methods), and a mesh smoothing step to normalize the surface of the mesh and remove noise (e.g., using Laplacian smoothing or another algorithm suitable for smoothing polygonal meshes).

[0080] The creation of the three-dimensional model is shown in 305 of FIG. 3 and may further require centerline extraction, as illustrated by FIG. 4c. The centerline may represent, for example, the central axis of the vascular structure and provide a reduced representation of the vessel and a means to guide the simulated placement of implantable medical devices. The extraction of the centerline may be performed as described in Antiga, L., & Remuzzi, A. (2002); Patient-Specific Modeling of Geometry and Blood Flow in Large Arteries, which requires the specification of source and target seed points located at the ends of the vessel, which may be selected manually or in a fully automated manner. FIG. 4c is an example of a three-dimensional model showing the extracted centerline as a line representing the central axis of the vascular structure, with the vascular structure itself rendered in a transparent shell. The illustration of this example is in shell mode, where only the shell of the vascular structure is shown along with the vascular structure's centerline. The extracted centerline may be subjected to further post-processing, as illustrated in 306 of FIG. 3. The point coordinates and associated radii may be normalized by smoothing and re-interpolation.

[0081] In steps 206 and 307, deployed configurations of a plurality of implantable medical devices at target locations within the three-dimensional model of the vascular structure are simulated. The simulation may include mechanical and / or geometric simulation of device expansion. The simulation in steps 206 and 307 may include performing a numerical simulation of the expansion of the implantable medical devices based on one or more properties of the implantable medical devices and one or more properties of the patient's vascular structure. The one or more properties of the implantable medical devices may include mechanical properties of the devices, geometric constraints of the devices, or non-constrained dimensions of the devices, such as length, volume, thickness, diameter, radius, or height. The one or more properties of the patient's vascular structure may include geometric constraints of the structures, dimensions of the structures, or local morphology of the structures. The numerical simulation is performed as described in EP3025638 "Method for determining the final length of a stent before deployment" or Ma, D., Dumont, TM, Kosukegawa, H. et al. High Fidelity Virtual Stenting (HiFiVS) for Intracranial Aneurysm Flow Diversion: In Vitro and In Silico. Ann Biomed Eng 41, 2143-2156 (2013), or by other simulation techniques. The numerical simulation may include simulating the expansion of the implantable medical device under constraints imposed by the geometry of the patient's vasculature. The simulation may include simulating forces applied to the implantable medical device by the patient's vasculature, and optionally a delivery system, device or tool used to deploy or position the device. The method may include numerically simulating an expanded configuration of the implantable medical device within constraints imposed by the patient's vasculature geometry defined in a three-dimensional model, the numerical simulation preferably also being based on mechanical constraints of the implantable medical device, such as the braiding of the wires of the device.

[0082] Some examples of simulating a deployed configuration of an implantable medical device may include the following steps: h. determining a ratio indicating the change in stent length as a function of the local morphology of the vascular structure; i. Obtaining a 3D centerline from a 3D model of the vascular structure; j. Defining the location of the starting point for placing the device on the three-dimensional model of the vascular structure; k. Divide the centerline of the vascular structure into multiple segments; l. determining descriptive parameters of the morphology of the vascular structure for a first segment of the plurality of segments, the descriptive parameters including geometric parameters and / or mechanical factors; m. calculating a stent length for the first segment using the exponential ratio of step a); n. The length of the segment calculated in step f) is subtracted from the nominal length of the stent to obtain a new nominal length; if the new nominal length is different from zero, steps e) to g) are repeated for the preceding and successive segments; if the new nominal length is approximately zero, all distances for each segment are summed and this sum becomes the final length of the stent after deployment.

[0083] The ratio in step a) may be determined based on mathematical modeling.

[0084] The deployed stent configuration can be output in step 310. Figure 4c is an exemplary 3D model showing the extracted centerline as a line representing the central axis of the vascular structure, along with a transparent shell rendering of the vascular structure itself and the simulated placed implantable medical device as a mesh.

[0085] The method requires defining target locations within the vasculature where an implantable medical device is to be placed during the simulation. The nature and definition of the target locations will depend on the particular type of device and how it is placed. For example, for a stent or other type of blood flow modifying device, the target locations will likely be vessel portions within the vasculature defined by a start location and an end location (such that the vessel portion has a length defined as the length of the vessel portion between a start location and an end location). These may be defined as distal and proximal locations based on their location relative to an entry location where the device is inserted into the body (or relative to the blood flow within the vessel). In contrast, an intrasaccular device is intended to expand within an aneurysm, and so the target locations may be defined as the volume of the aneurysm rather than as the length of the vessel between a start location and an end location.

[0086] In this embodiment, a simulation of a stent is shown, and the target location is defined as a portion of the vessel within the vasculature that extends between a start location and an end location of the vessel. In the illustrated example, these are referred to as distal and proximal locations. FIG. 4d shows a distal location on the centerline marked "D" and a proximal location on the centerline marked "P". FIGS. 9a and 9b further illustrate a distal location on the centerline marked "distal" and a proximal location on the centerline marked "proximal". The target location in this example is a portion of the vasculature that has a target length between the distal and proximal locations.

[0087] This type of target location corresponding to the length of the vessel containing the aneurysm may be defined in alternative ways. For example, the target location may be defined as a portion of the vessel structure extending distally and proximally a predetermined length from the identified aneurysm. In some examples, the distal and proximal locations (or start and end locations) may be automatically selected based on a recommended length from the location of the aneurysm selected by a user using a user interface. Alternatively, the aneurysm may be automatically detected as described below, and a recommended length from the detected aneurysm may be used to automatically select the distal and proximal locations.

[0088] In this example, a distal location and a proximal location may be selected by the user and marked on the centerline of the three-dimensional model. This allows the user to select the length of the vessel where the device should be placed. The target length should be long enough to ensure that the implantable medical device is not too short after deployment and can fully serve its intended purpose. The target length should be short enough to ensure that flow that is not intended to be blocked by the implantable medical device is not blocked.

[0089] The deployed length and deployed configuration of the implantable medical device can be obtained by a numerical simulation of the expansion of the implantable medical device in a three-dimensional model of the patient's vasculature, represented by a centerline. In particular, the deployed configuration is simulated based on one or more characteristics of the implantable medical device and / or one or more characteristics of the patient's vasculature, such as the geometric constraints imposed by the patient's vasculature and / or the forces exerted on the implantable medical device by the patient's vasculature, and optionally the delivery system. The numerical simulation is performed as described in EP3025638 "Method for determining the final length of a stent before deployment" or as described in Ma, D., Dumont, TM, Kosukegawa, H. et al. High Fidelity Virtual Stenting (HiFiVS) for Intracranial Aneurysm Flow Diversion: In Vitro and In Silico. Ann Biomed Eng 41, 2143-2156 (2013), or by other simulation techniques.

[0090] Using this method, deployed dimensions of a device, such as length, volume, thickness, diameter, radius, or height, can be determined by simulation without the need to calculate the complete deployed configuration of the implantable medical device, and can be determined at a later stage if desired. In this manner, a two-stage simulation can be performed, where an initial simulation having less computational requirements can be performed first for a larger range of devices to determine one or more deployed dimensions of the devices. A second, more computationally intensive simulation step is then performed for a selected number of the initial devices, and a complete simulation of the final configuration is performed.

[0091] When a deployed configuration of multiple implantable medical devices is simulated, the devices may be positioned starting from a distal location of the target location and extending toward a proximal location.

[0092] Optionally, the simulated deployed configuration of each of the plurality of implantable medical devices within the three-dimensional model of the vasculature may be displayed to a user. As shown in FIG. 4d, the simulated deployed configuration may be displayed to a user.

[0093] At step 208, a fit metric is determined for each simulated implantable medical device. The fit metric provides a measure of the fit of the implantable medical device placed within the target location of the patient's vasculature. The fit metric may optionally take into account manufacturer recommendations regarding placement of the implantable medical device within the patient's vasculature, such as a recommended stent model, length, or diameter.

[0094] FIG. 10 is a table showing an example of a manufacturer's recommendation for the placement of a particular implantable medical device within a patient's vasculature. The table includes various diameter options for the device model with a corresponding unconstrained diameter, a corresponding recommended vessel diameter, and a corresponding number of wires in the mesh of the device. The table further includes various length options for the device model in each of the various diameter options, and the corresponding device model number for each option. FIG. 9a further shows the vessel diameter (Dvessel) at a point proximal to the target location.

[0095] The fitness metric may include and take into account multiple different parameters, as described below. The computer-implemented method outputs an optimal device indication depending on the device that scores highest according to the fitness metric. Optionally, in some examples, a user may be able to weight different parameters of the fitness metric so that the fitness metric promotes devices with metrics that are particularly essential for a particular scenario. In other examples, the weighting of the various configuration parameters of the fitness metric is performed automatically, for example, based on the type and target location of the implantable medical device.

[0096] The fit metric may include a measure of correspondence between one or more dimensions of the implantable medical device in a deployed configuration (as predicted by the simulation) and the corresponding dimensions of the target location. For example, if the target location is a longitudinal portion of a blood vessel defined between a distal point and a proximal point (which may be user selected or automatically selected to define the target location), the fit metric may provide a measure of discrepancy between the length of the deployed device as determined by the simulation and the length of the blood vessel between the distal point and the proximal point. If the device is an intrasaccular device, the dimension may be the radius or diameter of the deployed device compared to the measured diameter of the aneurysm. Alternatively, the dimensions of the deployed device may be determined and compared to the dimensions of the aneurysm. The dimensions may include length, volume, thickness, diameter, or other dimensions. The fit metric depends on the measure of correspondence such that a closer match between the simulated deployed dimensions and the corresponding target dimensions indicates a better match.

[0097] The measure of correspondence between the length of the implantable medical device and the length of the target location can be calculated using the following formula: TIFF2025501322000005.tif19170 Here, L target is the length of the target location (i.e., the target vessel segment for placement), and L device is the deployment length of the device based on the simulation. Correspondence of other device dimensions may be determined in the same manner and considered within the fit metric. The size index may be defined as 1-size difference as defined above to provide a value of 1 for an exactly fitting device. Alternatively, a weighting function may be used to assign a value of 1 if the dimension is within a target range based on the target dimension.

[0098] The fit metric may additionally or alternatively include a measure of adhesion between the implantable medical device in the deployed configuration and the wall of the vasculature. Adhesion measures how close two items are to each other, for example, a particular point on the implantable medical device in the deployed configuration and the closest point on the wall of the vasculature. In an example scenario where the implantable medical device is being used for aneurysm healing, incomplete adhesion may result in residual blood flow to the aneurysm, affecting the occlusion of the aneurysm and reducing the healing of the aneurysm. Poor adhesion is also associated with adverse events such as thromboembolic complications and migration of the implantable medical device.

[0099] The measure of adhesion includes a measure of the distance between an outer surface of the implantable medical device in the deployed configuration and a wall of the vasculature. A plurality of points on the outer surface of the implantable medical device in the deployed configuration may be measured to a corresponding closest point on the wall of the vasculature for each of the plurality of points on the outer surface of the implantable medical device.

[0100] The measure of adhesion may include an adhesion index that includes the percentage of the surface of the implantable medical device that is within a threshold from the wall of the vasculature. Figure 5a shows an example of a three-dimensional model showing a transparent shell rendering of the vasculature and a simulated placed implantable medical device as a mesh. The mesh is shaded with different colors to indicate to the user areas of good and poor adhesion of the placed implantable medical device.

[0101] Alternatively, the measure of adhesion may include an adhesion index that includes the percentage of the surface area of ​​the implantable medical device that is in contact with the wall of the vasculature, hi one embodiment, the higher the percentage of the surface area of ​​the implantable medical device that is in contact with the wall of the vasculature, the better the device adheres and fits.

[0102] In calculating the adhesion index, the area corresponding to the aneurysm neck should be excluded from this calculation since the aneurysm neck obviously does not have good adhesion. In particular, the surface area of ​​the implanted medical device in close proximity to the aneurysm neck should be excluded, and the distance from this portion of the surface area to the vessel wall is not used in calculating the adhesion index. Figure 5b shows an example of a three-dimensional model showing a transparent shell rendering of the vessel structure and a highlighted area of ​​adhesion abnormality at the aneurysm neck that should be excluded. Detection of the portion of the vessel structure corresponding to the aneurysm neck can be determined as described below.

[0103] In the case of blood flow alteration devices, the aneurysm neck is seen endovascularly into the dome of the aneurysm. In the case of intrasaccular devices, the aneurysm neck is seen endovascularly from within the dome of the aneurysm. In both embodiments, good coverage and low porosity are desired for best fit. In the intrasaccular device embodiment, high fit of the device is desired for best fit so that the device blocks as much of the entrance to the dome of the aneurysm as possible. Fit of the flow diverter at the aneurysm neck is not considered since the flow diverter does not enter the dome of the aneurysm (whereas the intrasaccular device does).

[0104] The corresponding portion of the vessel can be determined by determining the portion of the vessel structure at the target location where the radius of the vessel structure is abnormal. More specifically, the location of the aneurysm can be identified when the radius of the vessel in the model is much larger than the rest of the vessel. These sudden changes in the measured vessel radius can be used to identify the portion of the vessel that corresponds to the aneurysm, and then the portion of the surface area of ​​the deployed device directly adjacent to this portion of the vessel can be excluded from the calculation.

[0105] This type of deviation in radius can be determined in a number of ways. For example, the portion of the vessel corresponding to the aneurysm may be determined by determining the portion of the vessel structure at the target location where the radius of the vessel structure is greater than the average of the rest of the target location by more than a threshold amount. If there is a large discrepancy in the radii of the vessel structure, it can be assumed that a saccular aneurysm is located at this determined location. Figure 6a shows an example of an aneurysm in a vessel structure. The centerline of the vessel is shown as a dotted line, and the inner ring (centered on the dotted line) represents the centerline radius. As mentioned above, the centerline radius provides a measure of the average radius of the vessel portion. One approximation is calculated by using the minimum distance between the centerline and the vessel wall. The outer ring (surrounding the inner ring) represents the actual radius of the vessel structure at the selected location in the model. With a large discrepancy between the centerline radius and the actual radius, it is clear that a saccular aneurysm is present.

[0106] FIG. 6b shows an example of a three-dimensional model with radius difference shown by a magnification of the centerline of the vascular structure. The radius difference shown is obtained using the following formula: TIFF2025501322000006.tif19170 where abs is the absolute value and R centerline is the centerline radius, R cross-section is the radius at the point where the cross section is taken.

[0107] Alternatively, the portion may be determined by determining a portion of the vasculature at the target location where the cross-sectional radius of the vasculature is greater than the centerline radius of the remainder of the target location by more than a threshold value. If there is a large peak in the radius of the vasculature, it can be assumed that a fusiform aneurysm is located at this determined site, since normal physiological arteries taper slowly distally. Figure 7a is a graph plotting centerline radius and cross-sectional radius over the length of the vasculature. A large peak in the cross-sectional radius compared to the centerline radius indicates that a fusiform aneurysm is located over the length of this peak. A vertical line on the graph indicates the boundary of this detected fusiform aneurysm. Figure 7b shows an example three-dimensional model showing a transparent shell rendering of the vasculature, centerline, and mesh shaded with various colors to indicate the cross-sectional radius at each point on the centerline. This figure shows a fusiform aneurysm within the vasculature, characterized by a change in shading of the mesh.

[0108] The adhesion index may be calculated by excluding the portion of the outer surface of the implantable medical device that corresponds to the determined portion of the vascular structure that corresponds to the aneurysm, and finally, calculating the adhesion index for the remaining portion of the outer surface of the implantable medical device.

[0109] As mentioned above, Figures 5a and 5b show the calculation of the adhesion index for a flow diverter device. The adhesion index for a flow diverter device can be calculated using the following integral: TIFF2025501322000007.tif19170 Here, S FD is the total surface area of ​​the deployed flow diverter devices, and S Neck is the surface area of ​​the blood vessel corresponding to the aneurysm neck, and Γ FD is the surface area of ​​the flow diverter device, and Γ Neck is the surface area of ​​the flow diverter device corresponding to (i.e., adjacent to) the aneurysm neck, and GA is abs(d FD-Wall )≦d threshold GA is 1 when (abs(d FD-Wall )>d threshold) is 0.

[0110] Optionally, the suitability metric includes a neck coverage value that provides a measure of the percentage of the aneurysm neck wall that is covered by the implantable medical device, which in this embodiment is preferably an intrasaccular device. The neck wall can be classified as the extent of the wall of the vasculature that is within a threshold value from the aneurysm neck. In one example, the higher the percentage of the aneurysm neck wall that is covered by the implantable medical device, the higher the suitability of the device. Alternatively, the neck coverage value provides a measure of the percentage of the aneurysm neck wall that is in contact with or within a threshold distance of the implantable medical device, which in this embodiment is preferably an intrasaccular device. In one example, the higher the percentage of the aneurysm neck wall that is in contact with or within a threshold range of the implantable medical device, the higher the suitability of the device.

[0111] Optionally, the fit metric includes a neck protrusion value that is a measure of the distance the implantable medical device protrudes from outside the aneurysm neck into the blood vessel. The neck protrusion value is preferably zero for an optimal fit, and the closer the neck protrusion value is to zero, the better the device fits. In this embodiment, the implantable medical device is preferably an intracapsular device.

[0112] The suitability metric may additionally or alternatively include a blood flow modification index that provides a measure of blood flow modification achieved by the deployed device. The blood flow modification index may indicate a more suitable device where a greater amount of blood flow modification is achieved by the deployed implantable medical device. For example, the blood flow modification index may indicate optimal blood flow modification when the simulated blood flow modification is above a threshold or within a predetermined range. In particular, the blood flow modification metric may provide a measure of the reduction in blood flow to the aneurysm achieved by the deployed implantable medical device.

[0113] To calculate the degree of blood flow alteration, the method may include comparing two computational fluid dynamics (CFD) simulations: a first simulation of blood flow within the patient's vasculature without the implantable medical device, which serves as a baseline, and a simulation when the implantable medical device is placed in its final configuration. The maximum velocity as well as the spatially averaged velocity (both calculated within the aneurysm) can then be used to calculate the percentage of blood flow reduction within the aneurysm.

[0114] Another method for calculating the blood flow reduction is to calculate the total flow (m 3 This can be accomplished by directly measuring the time (s) and then calculating the rate of reduction between instrumented and non-instrumented simulations.

[0115] The two simulations mentioned above can be performed using any of the well-known CFD methods capable of solving the Navier-Stokes equations (e.g., finite volume method, finite element method, spectral element method, lattice Boltzmann method).

[0116] The suitability metric may additionally or alternatively include a landing zone index. The landing zone index includes a measure of the length of the landing zone of the implantable medical device. The landing zone is denoted by S in FIG. d and S pAs labeled, the distal and proximal landing zones include longitudinal portions of the deployed implantable medical device positioned just distal and proximal to the aneurysm neck at the target location. Preferably, the distal and proximal landing zones are in straight vessel portions to ensure good adhesion with the wall. The landing zones are indicative of a highly compliant device with a landing zone length above a threshold. A landing zone length above a threshold ensures good origination, good adhesion, and avoids device migration. FIG. 8a shows an example model showing the contours of the vascular structure and a mesh representing the deployed implantable medical device, where the mesh is shaded to indicate the size ratio weighting function (shown in FIG. 8b) applied to each portion of the implantable medical device. The proximal landing zone is S p The distal landing zone is illustrated by the box marked S. d FIG. 8b shows the shading key used to indicate the size ratio weighting function applied, as explained below.

[0117] The fit at the landing zone can be calculated by using the ratio between the diameter of the implantable medical device and the diameter of the vessel at the landing zone to determine a size ratio that helps determine how appropriately sized the implantable medical device is for that particular vessel segment.

[0118] The Landing Zone Index can be calculated using the following two integrals: TIFF2025501322000008.tif20164 TIFF2025501322000009.tif19164 Here, S p is the size exponent of the proximal landing zone as shown in Figure 8a, and S d is the size exponent of the distal landing zone as shown in Figure 8a, and L optis the optimal landing zone length for a particular implantable medical device (e.g., as indicated in the manufacturer's guidance) as shown in FIG. 8a, and L device is the length of the deployed implantable medical device and Wf is the weighting function as shown in Figure 8b. The landing zone size index S is calculated according to the following formula: TIFF2025501322000010.tif16164 If the implantable medical device is the proper size and length, S will tend towards 1. If the implantable medical device is not the proper size or the landing zone is too short, S will tend towards 0.

[0119] The weighting function Wf can be used to penalize regions of the implantable medical device by assigning the regions a weight less than 1. Figure 8b shows the key to the size ratio weighting function used in Figure 8a. In this example, the weighting function is constructed as follows: The weighting function assigns a weight of 0 if the deployed diameter of the implantable medical device is less than 5% larger than the diameter of the vessel in the landing zone. The weighting function is a linearly increasing function between 5% and 0% undersizing (i.e., when the diameter of the device is 0% to 5% smaller than the vessel diameter), taking a value of 0 for 5% undersizing and a value of 1 for a perfect match of the diameter. The weighting function assigns a weight of 1 if the deployed diameter of the implantable medical device is 0% to 20% larger than the vessel size in the device landing zone. The weighting function is a linearly decreasing function between 20% and 60% oversizing (i.e., when the diameter of the deployed device is 20% to 60% larger than the vessel diameter), taking a value of 1 for 20% oversizing and 0 for 60% oversizing. The weighting function applies a weight of 0 if the device is 60% or more oversized. As noted above, this undersizing or oversizing is determined based on the deployed diameter of the device relative to the local diameter of the vessel. The above weighting function is only one example of a function that can be used to take into account the detrimental effects of a device when undersized or oversized. In general, if the deployed diameter corresponds to or is slightly larger than the vessel diameter, the metric should indicate that the device is a good fit.

[0120] The conformance metric may additionally or alternatively include a porosity index. The porosity index includes a measure of the porosity of the implantable medical device in a deployed configuration. Porosity is the ratio of the volume of voids in the mesh to the total volume of the mesh. The porosity of the implantable medical device may change as the mesh of the device reshapes, expands, and contracts in various regions depending on its deployed configuration. The porosity index may indicate a more conforming device in which the porosity is below a threshold value in a selected portion of the outer surface of the deployed implantable medical device. The selected portion of the outer surface of the deployed implantable medical device may be located near the aneurysm neck (i.e., Γ in FIG. 5b). neck ) in the neck region. Low porosity in the neck region expedites occlusion of the aneurysm. Porosity can be controlled, for example, by applying some "push-pull" (i.e., force applied by the user with the deployment system) during deployment to compact the device. The "push-pull" force can be applied by the user pushing or pulling the deployed implantable medical device with the deployment system to contract or expand the device in different regions. This changes the density of the mesh of the device in different regions, allowing the porosity of the device to be controlled.

[0121] The porosity index may be calculated by determining a portion of the vascular structure that corresponds to the aneurysm. This portion may be determined by determining a portion of the vascular structure at the target location where the radius of the vascular structure is greater than the average of the rest of the target location by more than a threshold amount (or more specifically, one of the methods described above with respect to the adhesion index). Further, a portion of the outer surface of the deployed implantable medical device is selected that corresponds to the determined portion of the vascular structure that corresponds to the aneurysm. Finally, the porosity of the selected portion of the outer surface of the deployed implantable medical device is determined. This may be determined by simulating the configuration of the deployed implantable medical device and calculating the ratio of the volume of voids in the mesh to the total volume of the mesh. As above, a weighting function may be applied to apply a value of 1 where the porosity is within the optimal range, a value of 0 where the porosity is below or above the threshold, and a linear function may be applied to apply a value that varies between values ​​0 and 1 where the porosity is just outside the optimal range, as described above with respect to the landing zone index.

[0122] Alternatively, the porosity index can be calculated by determining the portion of the blood vessel that corresponds to the aneurysm neck and calculating the average porosity over the cross-sectional area of ​​the aneurysm neck opening. The lower the average porosity over the cross-sectional area of ​​the aneurysm neck opening, the better the device conforms. For example, the more the aneurysm neck opening is covered as much as possible, the better the device conforms. In one example, some intrasaccular devices have lower porosity at the top / bottom, so ideally these low porosity surfaces are placed perpendicular to the aneurysm neck, and the more area of ​​the neck wall that is covered, the lower the porosity at the neck opening and the better the device conforms.

[0123] The suitability metric may additionally or alternatively include an occlusion value, which provides a measure of the degree to which a placed implantable medical device occludes side branches within a three-dimensional model of the vasculature. The occlusion value indicates a more suitable device that occludes fewer side branches and limits blood flow obstruction. Shorter implantable medical devices are preferred as they provide the greatest limit of blood flow obstruction and occlude fewer side branches.

[0124] The fitness metric may additionally or alternatively include a vessel shape value. The vessel shape value provides a measure of the extent to which a deployed implantable medical device extends across one or more bends in a three-dimensional model of a vascular structure that includes a radius of curvature below a threshold. The vessel shape value indicates fewer bends below the radius of curvature threshold, improving the fitness of the device. It is difficult to deploy an implantable medical device inside a vessel bend, and a bent implantable medical device may have difficulty in fully expanding, resulting in poor adhesion. Thus, a shorter deployed device that covers fewer vessel bends is more compliant and preferred. As with each of the fitness metric parameters described herein, the vessel shape value and occlusion value can take values ​​between 1 and 0, with 1 indicating an optimal device and 0 indicating a less compliant device.

[0125] Optionally, a representation of the fit metric or any one of its configuration parameters may be displayed on a corresponding simulated deployed configuration of each of the plurality of implantable medical devices within the three-dimensional model of the vasculature. The representation of the fit metric may indicate the fit of the placed implantable medical device at each point within the three-dimensional model. This may be displayed as a color range, with red areas marking areas where the placed implantable medical device has a poor fit or fit, and green areas marking areas where the placed implantable medical device has a good fit or fit.

[0126] The suitability metric may be summarized as a numerical value and displayed next to the model of the device or devices. In particular, after simulating multiple implantable medical devices and determining the suitability metric, one or more of the devices may be displayed with a numerical value representing the suitability metric. The devices may be ranked and listed in order of suitability based on the suitability metric.

[0127] In certain embodiments, each constituent parameter of the fitness metric takes a value between 0 and 1, with 1 indicating a good fit and 0 indicating a poor fit. The fitness metric may be calculated based on the sum of the constituent parameters, which may optionally be weighted by coefficients to select their relative importance in the calculation.

[0128] Optionally, based on this indication, as set in step 308, the user may move the placement location of the simulated implantable medical device and rerun the simulation to improve the fit of the implantable medical device. Specifically, in certain embodiments, the user may adjust the start and end points (alternatively, the proximal and distal points) to change the target location where the device should be placed. This may be accomplished by dragging the start and end points (e.g., points P and D displayed in FIG. 4d), which causes the simulation to be rerun and the fit metric to be recalculated. Alternatively, this may be done automatically, in which case the fit metric of the device would be improved by moving its placement location. For example, the simulation may automatically change the target location to determine the optimal location.

[0129] At step 210, an indication of an optimal implantable medical device is output based on the suitability metric. As described above, the suitability metric may include one or more of a measure of correspondence between the dimensions of the placed device and the corresponding dimensions of the target location (a size index), a measure of adhesion between the implantable medical device in the deployed configuration and the wall of the vasculature (an adhesion index), a landing zone index, a porosity index, a blood flow modification index, an occlusion value, and a neck coverage value. The indication of an optimal implantable medical device may include one or more identifiers of the implantable medical device, such as the manufacturer of the implantable medical device, the manufacturer model of the implantable medical device, the diameter, the length, the material from which the device is made, or the placement of the device within the vasculature. The indication may alternatively be an indication of a plurality of optimal implantable medical devices ranked based on their individual suitability metrics. The indication may be output on the display in a format suitable for interpretation by a user.

[0130] In an alternative embodiment, a first selection of a plurality of implantable medical devices is determined based on a first suitability metric. Then, an optimal implantable medical device from the first selection of implantable medical devices is determined based on a second suitability metric. This determination can be performed using the determination methods described above, in particular the determination methods described in steps 208 and 210. An indication of this optimal implantable medical device is output based on the first suitability metric and the second suitability metric. The indication may be output on a display in a format suitable for a user to interpret.

[0131] By first narrowing down the plurality of implantable medical devices to a first selection using a first fitness metric, and then further narrowing down using a second fitness metric, the determination of the optimal device can be made more computationally efficient. In one example, the first fitness metric is a computationally simple calculation, such as determining an appropriate range of implantable medical device lengths and diameters, or a measure of correspondence between the length of the implantable medical device in the deployed configuration and the target length of the target location. The second fitness metric may then include more computationally expensive calculations, such as one or more of the measures of adhesion between the implantable medical device in the deployed configuration and the wall of the vasculature, a landing zone index, a porosity index, a blood flow modification index, an occlusion value, a neck coverage value, a neck protrusion value, and a vessel shape value. This method is computationally efficient because the selection of implantable medical devices has already been narrowed down before performing the computationally expensive calculations. However, the first and second fitness metrics may be based on any one or more of the fitness metric parameters described above.

[0132] In one embodiment, the implantable medical devices to be simulated may be selected by first determining the maximum vessel diameter at the target location of the three-dimensional model, excluding a portion of the target location corresponding to the aneurysm. A database of candidate devices is then accessed, and the implantable medical devices are selected by determining the implantable medical devices in the database that have an unconstrained diameter within the target range based on the maximum vessel diameter. FIG. 9a shows the vessel diameter at a proximal location in the vessel that is used to determine the target range. The target range may be defined by the manufacturer's guidance that defines the diameter of the device to be used for the vessel diameter size, as shown in FIG. 10. In general, the diameter of the device should be equal to or greater than the maximum vessel diameter. Thus, the target range may have a minimum boundary equal to the maximum vessel diameter and a maximum boundary determined by an additional percentage of the maximum vessel diameter.

[0133] Preferably, the selected implantable medical devices have a minimum unconstrained diameter that exceeds the maximum vessel diameter to ensure good adhesion. The selected implantable medical devices to be simulated can be expanded in diameter and length by sampling around the initial size device.

[0134] Determining a first selection of the plurality of implantable medical devices based on the first suitability metric includes simulating a deployed configuration of the plurality of implantable medical devices and determining a difference between a length of the implantable medical devices in the deployed configuration and a target length at the target location.

[0135] The simulation of the deployed configurations of the multiple implantable medical devices may be performed sequentially in the order of the unconstrained lengths of the implantable medical devices. In one example, the simulations may be performed sequentially in the order of increasing deployed length from the shortest device having the selected diameter to the longest device having the selected diameter until the deployed length of the device is longer than the vessel portion. In another example, the order may be in the order of increasing length from a device having a length slightly shorter than the target length with the selected diameter to the longest device having the selected diameter. By simulating the deployed configurations of the multiple implantable medical devices sequentially from the shortest device to the longest device, the computational efficiency of the simulation process is increased. This is because the entire device does not need to be completely resimulated each time, but only the portion of the device that adds a little extra length needs to be simulated. This reduces the computational burden of simulating multiple devices. Figures 9a and 9b show the results of simulations in which the deployed length of the device is increased by the L of Figure 9b. vessel 13 shows an example of the device being placed at progressively longer lengths until it is longer than the vessel segment marked with .

[0136] Determining the first selection of the plurality of implantable medical devices based on the first suitability metric further includes determining a first selection of the plurality of implantable medical devices in which a difference between a length of the implantable medical device in the deployed configuration and a target length at the target location is less than a length difference threshold.

[0137] A particularly advantageous implementation of the method using two fitness metrics in a two-stage process is described as follows.

[0138] First, the maximum vessel diameter within the target location is determined from a model of the vascular structure, as described above. This excludes the portion of the vessel that contains the aneurysm. The aneurysm may be identified as described above based on the difference in the vessel radius (e.g., compared to the centerline radius). Thus, the maximum vessel diameter is the maximum vessel diameter excluding the aneurysm neck or any bifurcations.

[0139] Secondly, at least one device is selected from the database, the device model having a diameter greater than the maximum vessel diameter. As mentioned above, the database includes one or more different implantable device models. Each of these models is available in a range of different diameter sizes, and in each diameter size, in a range of lengths. Thus, a single device having an appropriate diameter may be selected for subsequent simulations of a range of lengths at that diameter. More preferably, multiple devices having the correct size diameter are selected to proceed to subsequent simulations at various lengths. These may correspond to a variety of different models from a variety of manufacturers, having diameters suitable for the target vessel. They may also include various diameter sizes of the same model to carry over to subsequent simulations. In particular, the software may not only select a device having a minimum diameter greater than the maximum diameter, but may optionally select all devices within a specified diameter range. In this way, the diameter size of each model may be carried over to subsequent simulations. The diameter range may be altered to vary the number of devices selected. At the end of this step, the method identifies one or more instruments, preferably multiple instruments, different models having the same diameter, a single model having different diameter sizes, or multiple different models having multiple different diameter sizes, all of which meet the required diameter range criteria.

[0140] Third, for each of these multiple devices, if the initial length size is smaller than the length of the target location, an initial length size is selected. The smallest available length size may be selected as the initial length size, or a length size that is a percentage or absolute value shorter than the target location is selected. The deployed configuration is then simulated for the initial length size to determine the deployed length. If the deployed length is within the target range of the length of the target location ("target length"), the device (i.e., the particular model, diameter size, and length) proceeds to determine the second suitability metric. In this way, the correspondence between the deployed length and the target length can be considered as the first suitability metric, and in this case, the device proceeds to calculate the second suitability metric only if this meets the requirements (which may be computationally intensive). If the deployed length does not fall within the target length range, an increased length size is simulated (e.g., the next length size from the initial length) and it is determined whether it falls within the target range. As described above, this incremental increase in length size is computationally efficient, since only small additional components need to be added on top of the already simulated device. The process of increasing the length size of the device and re-simulating continues until the device (its model and diameter) is determined to meet the first requirement (length compatibility). This process is then repeated for each of the remaining plurality of devices (different models and / or different diameter sizes) to determine a selection of the plurality of devices for which a second suitability metric is determined.

[0141] In a fourth step, each of the selected plurality of instruments that meet the length requirement is then simulated to determine a deployment configuration and calculation of a second fitness metric. This may be a more computationally intensive calculation that requires calculating a large number of points on the instrument to determine an accurate measure of, for example, a fit index, a landing zone index, or a porosity index. A second fitness metric is calculated for each of the selected instruments and a ranking of the best instrument or instruments is displayed along with the numerical values ​​of their fit metrics and / or configuration parameters.

[0142] In an alternative embodiment, instead of step 210, a plurality of simulated implantable medical devices are ranked based on the individual suitability metrics determined in step 208. The user is provided with a ranking of the devices in a form suitable for the user to interpret. Optionally, the user can weight various aspects of the suitability metric, such as the porosity index, so that the ranking of the devices can favor devices having particularly essential metrics.

[0143] Having described aspects of the present disclosure in detail, it will be apparent that modifications and variations are possible without departing from the scope of the aspects of the present disclosure as defined in the appended claims. Various changes can be made in the above-described structures, products, and methods without departing from the scope of the aspects of the present disclosure, and it is intended that all matter contained in the above description and shown in the accompanying drawings be interpreted as illustrative and not in a limiting sense.

[0144] For example, the examples shown in the figures use the example of a stent to illustrate the method, but the method is equally applicable to other types of implantable devices. For example, the method can be similarly applied to an intrasaccular device for implantation within an aneurysm. Each of the above parameters may be calculated for an intrasaccular device. In this case, other dimensions are used rather than the "length" of the device relative to the length of the target vessel location. In particular, three dimensions that define the interior shape of the aneurysm and the corresponding dimensions of the device.

[0145] It will be appreciated that the above-described processes can be implemented using a computer, where "computer" is understood to refer broadly to any collection of processing resources capable of operating on digital data, including traditional physical computers such as laptops, desktop computers, tablets, mobile phones, and virtual computers such as cloud-based virtual machines, servers, and server clusters.

[0146] As used herein, the term "non-transitory computer-readable medium" is intended to represent any tangible computer-based device implemented in any manner or technique for short-term and long-term storage of information, such as computer-readable instructions, data structures, program modules and sub-modules, or other data in any device. Thus, any one or more steps of the methods described herein may be encoded as executable instructions embodied in a tangible non-transitory computer-readable medium, including, but not limited to, storage devices and / or memory devices. Such instructions, when executed by a processor, cause the processor to perform at least a portion of the methods described herein. Furthermore, as used herein, the term "non-transitory computer-readable medium" includes all tangible computer-readable media, including, but not limited to, non-transitory computer storage devices, including volatile and non-volatile media, as well as removable and non-removable media, such as firmware, physical and virtual storage devices, CD-ROMs, DVDs, and any other digital source, such as a network or the Internet, and digital means yet to be developed, with the only exception being transitory propagating signals.

[0147] As will be appreciated based on the foregoing specification, the above-described embodiments of the present disclosure may be implemented using computer programming or engineering techniques including computer software, firmware, hardware, or any combination or subset thereof, with the technical effect being to enable planning of implantable medical device deployment, such that clinicians can take into account many of the important factors for placement, such as wall contact, porosity, blood flow obstruction, and vessel geometry. Furthermore, a computationally efficient method for executing deployment planning of implantable medical devices is provided. Any such resulting program having computer readable code means may be embodied or provided in one or more computer readable mediums, thereby creating a computer program product, i.e., an article of manufacture, according to the discussed embodiments of the present disclosure. An article of manufacture including computer code may be manufactured and / or used by executing the code directly from one medium, by copying the code from one medium to another, or by transmitting the code over a network.

Claims

1. 1. A computer-implemented method for simulating the placement of a plurality of implantable medical devices to determine optimal placement of the implantable medical devices at target placement locations within a patient's vasculature, comprising: Receiving image data corresponding to a patient's vasculature (202); generating (204) a three-dimensional model of the patient's vasculature based on the image data; simulating (206) a deployment configuration of a plurality of implantable medical devices at target locations within the three-dimensional model of the patient's vasculature; determining (208) a fit metric for each simulated implantable medical device, the fit metric providing a measure of fit of the deployed implantable medical device within the patient's vasculature, the fit metric including a measure of fit between the implantable medical device in a deployed configuration and a wall of the vasculature; and outputting (210) an indication of an optimal implantable medical device based on the fitness metric.

2. The computer-implemented method of claim 1 , wherein the fit metric comprises a measure of match between dimensions of the implantable medical device in the deployed configuration and corresponding dimensions of the target location.

3. The computer-implemented method of claim 1 or 2, wherein the measure of adhesion comprises an adhesion index comprising a percentage of a surface of the implantable medical device that is within a first threshold from the wall of the vasculature.

4. the target location comprises a blood vessel containing an aneurysm; The adhesion index is determining a portion of the blood vessel corresponding to a neck of the aneurysm; excluding a portion of an outer surface of the implantable medical device corresponding to the determined portion of the blood vessel; calculating an adhesion index for the remainder of the exterior surface of the implantable medical device; The computer-implemented method of claim 3 , wherein the calculation is performed by:

5. the target location comprises a blood vessel containing an aneurysm, and the suitability metric comprises a landing zone index, the landing zone index being:

10. The computer-implemented method of claim 1, further comprising: a measure of a length of a landing zone of the implantable medical device, the landing zone comprising a longitudinal section of the deployed implantable medical device positioned just distal and proximal to the aneurysm neck at the target location; and the landing zone indicating an improved conformance device when the length of the landing zone is above a threshold.

6. The suitability metric includes a porosity index, the porosity index comprising a measure of porosity of the blood flow altering device in the deployed configuration, the target location comprises a blood vessel containing an aneurysm, and the porosity index is: determining a portion of the vascular structure corresponding to the aneurysm neck; selecting a portion of an exterior surface of the placed implantable medical device that corresponds to the determined portion of the blood vessel; determining the porosity of a selected portion of an exterior surface of the deployed implantable medical device; is calculated by The computer-implemented method of claim 1 , wherein the porosity index indicates a highly compliant device if the porosity is below a threshold value on a selected portion of an exterior surface.

7. The suitability metric is an occlusion value that provides a measure of the degree to which the placed implantable medical device occludes side branches within the three-dimensional model of the vascular anatomy, the occlusion value indicating a more suitable device with fewer occluded side branches; a vessel shape value that provides a measure of the extent to which the placed implantable medical device extends across one or more bends in a three-dimensional model of the vasculature that have a radius of curvature below a threshold, the vessel shape value indicating a more compatible device having fewer bends with a radius of curvature below the threshold; The computer-implemented method of claim 1 , comprising one or more of:

8. The fitness metric includes a blood flow modification index, the blood flow modification index being: Simulating blood flow through a vascular structure without the use of an implantable medical device; simulating blood flow through a vasculature of a patient, including a deployed configuration of an implantable medical device; determining a blood flow modification index comprising a measure of a change in blood flow due to the deployed implantable medical device; The computer-implemented method of claim 1 , wherein the calculation is performed by:

9. the target location comprises a blood vessel containing an aneurysm; 2. The computer-implemented method of claim 1, wherein the fitness metric includes a neck protrusion value that measures the distance a placed implantable medical device protrudes into the vessel from outside the aneurysm neck, the neck protrusion value approaching zero indicating a more fit device.

10. simulating a deployed configuration of a plurality of implantable medical devices at target locations within the three-dimensional model of the patient's vasculature includes:

10. The computer-implemented method of claim 1, comprising numerically simulating expansion of the implantable medical device within a three-dimensional model of the patient's vasculature.

11. simulating a deployed configuration of a plurality of implantable medical devices at target locations within the three-dimensional model of the patient's vasculature includes:

10. The computer-implemented method of claim 1, comprising sequentially simulating the deployed configurations of the plurality of implantable medical devices in order of unconstrained dimensions of the implantable medical devices.

12. simulating a deployed configuration of a plurality of implantable medical devices at target locations within the three-dimensional model of the patient's vasculature includes: extracting a centerline from the three-dimensional model of the patient's vasculature, the centerline being a central axis of a blood vessel within the patient's vasculature; and numerically simulating expansion of the implantable medical device along a centerline within a three-dimensional model of the patient's vasculature.

13. Numerically simulating the expansion of the implantable medical device within a three-dimensional model of the patient's vasculature includes:

13. The computer-implemented method of claim 10 or 12, based on one or more of the characteristics of the implantable medical device, geometric constraints imposed by the patient's vasculature, and forces exerted on the implantable medical device by the patient's vasculature.

14. The computer-implemented method comprises: determining a first selection of a plurality of implantable medical devices based on the first suitability metric; and determining an optimal device from the first selection of implantable medical devices based on a second suitability metric.

15. Determining a first selection of a plurality of implantable medical devices based on the first suitability metric includes: simulating a deployed configuration of a plurality of implantable medical devices and determining a difference between a length of the implantable medical devices in the deployed configuration and a length of the target location; and determining a first selection of a plurality of implantable medical devices having a difference between a length of the implantable medical device in the deployed configuration and a length of the target location that is less than or equal to a length difference threshold.

16. simulating a deployed configuration of the plurality of implantable medical devices comprises:

16. The computer-implemented method of claim 15, comprising sequentially simulating deployed configurations of a plurality of implantable medical devices in order of increasing unconstrained lengths of the implantable medical devices.

17. Prior to simulating a deployed configuration of the plurality of implantable medical devices, the plurality of implantable medical devices are determining a maximum vessel diameter at the target location of the three-dimensional model excluding a portion of the target location corresponding to the aneurysm; 17. The computer-implemented method of claim 15 or 16, wherein the implantable medical devices to be simulated are selected by accessing a database of candidate devices and selecting the plurality of implantable medical devices to be simulated as implantable medical devices in the database that have an unconstrained diameter within a target range based on the maximum vessel diameter.

18. The computer-implemented method of any one of claims 14 to 16, wherein determining an optimal device from the first selection of implantable medical devices based on the second suitability metric comprises the computer-implemented method of any one of claims 1, 2, 5 to 12.

19. The computer-implemented method of claim 1 , wherein the plurality of implantable medical devices comprises a plurality of implantable neurovascular medical devices.

20. A non-transitory computer-readable medium comprising instructions that, when executed by a processor, cause the processor to perform the computer-implemented method of any one of claims 1, 2, 5-12, 14-16 and 19.

Images