Patent Application
20220338929
The invention relates to systems and methods for assisting a physician in making treatment decisions and to assist in the planning of endovascular surgical procedures. In particular, the invention relates to systems and methods for helping a physician decide if access to the cervical and cerebral arteries is best achieved via a radial artery or femoral artery access route (or other) based on objective assessment of the likelihood of success by a specific access point and having consideration to the available endovascular equipment and a particular patient's anatomy.
The human body has an extensive network of blood vessels including both the venous and arterial systems for circulating blood throughout the body as a whole as well as the organs of the body.
In recent decades, various surgical procedures involving traumatic and highly invasive access to the body have been replaced with procedures that involve the use of one or more catheters being introduced in a minimally invasive fashion through a small skin nick into and advanced through the vascular system of the body. These endovascular procedures are highly effective to diagnose and/or to treat diseases involving the vasculature of a particular organ without requiring large incisions and/or deep surgeries through other tissues to complete the procedure.
For example, strokes (e.g. ischemic strokes caused by blood clot blockages of brain vessels), coronary artery blockages within the heart and various heart defects may be treated by advancing catheters through the vasculature to the affected site where various diagnostic and treatment procedures can be initiated to identify and treat the problem
Well known procedures include the deployment of stents via a catheter into an occluded vessel (both coronary and cerebral). Catheter procedures are also done in other parts of the body including leg vessels, renal arteries and other complex vascular percutaneous vascular procedures including treatment of valvular heart disease, aortic dissections, dysrhythmias and management of shunts for dialysis patients. Similarly, complex aneurysms in the brain and other locations are increasingly treated via a percutaneous endovascular route.
In order to effectively use catheters within the body to complete a medical procedure, generally the catheters must be flexible enough to follow through the tortuous curves of the body's vascular system whilst being stiff enough to gain and hold position during the procedure. This can include the steps of advancing one or more catheters to the desired site as well as the steps of completing a procedure including passing tools through a catheter to the desired site once access to the site has been gained.
As is known, the parameters and variables of the human vasculature including the diameter of vessels, the curves of the vessels and, the angles of vessels relative to one another, catheters and associated equipment are provided with a wide range of properties to enable procedures to be completed.
For example, if the catheter is too flexible, the catheter may fall back into other vessels within the vascular system. If the catheter is too stiff, it may cause damage to the surrounding tissue as it navigates through curves of the vessels, if it is able to be moved at all. In both instances, the use of an ineffective catheter may cause significant time delays in completing the procedure.
Importantly, in certain endovascular interventions and specifically procedures to remove a blood clot from the brain of a patient who has had an ischemic stroke, “time is brain”, meaning that delays in completing a procedure can significantly affect the outcome for the patient.
Importantly, the degree of tortuosity within blood vessels as well as the stiffness of vessels increases with age due to multiple factors including atherosclerotic disease, loss of height of the spine, etc. can affect the ease of completing a procedure. With improving technologies, more and more of these procedures are being done in an older population despite the increased complexity of conducting procedures through tortuous and/or stiffer vessels.
That is, it is well known that there are significant variations in the vascular anatomy of patients with the result being that in some patients, navigation of endovascular equipment from one point to another is straightforward, whereas in others may be impossible with available equipment.
To take a typical catheter procedure as an example and as described in more detail below, to access the blood vessels in the head, the interventionist typically navigates a catheter system up the descending aorta from the femoral artery into the aortic arch and into the left common carotid artery. For the purposes of the description herein a “catheter system” implies various combinations of inner catheters (e.g. diagnostic catheters, guide wires, microcatheters) and outer guide catheters (e.g. distal access catheters and balloon guide catheters) where the inner and outer components are substantially coaxial and can slide over or within the other. This can include coaxial, triaxial and quadra-axial procedures. In most circumstances, the components will move together with a guide wire usually extending beyond the outer guide catheter and inner components such as a diagnostic catheter or microcatheter. Hence, the catheter system may be both a combination of a wire within the catheter during antegrade movement of the catheter system but may also mean just the catheter without the wire. Antegrade movement is generally conducted by a combination of advancing the guide wire followed by advancing the catheter over the wire, all of which may involve twisting or turning the catheter and wire in order to turn the distal end of the guide wire and catheter into the appropriate vessel. After reaching the aortic arch, for example, the catheter system is navigated up the left common carotid artery and into the left internal carotid artery. Depending on the underlying condition and the procedure being conducted, at this stage the interventionist may utilize a variety of different catheters (including microcatheters and microwires) and techniques to gain access to intracranial vessels and ultimately to the site where the procedure is to be conducted.
A stiff catheter system can straighten out tortuous vessels (which may or may not be advantageous) and/or damage the vessel as it is being navigated through a tight curve. However, if the catheter is very flexible, it may not be able to maintain its position within the vessel and, for example, fall back into the aortic arch after it has been successfully guided into the left internal carotid artery (especially as further catheters and tools are being advanced through the catheter to enter the brain vessels and/or as the guide wire is withdrawn). In some cases, additional catheters face friction as they are being advanced and this creates a backward force on the guiding catheter hence preventing the interventionist from completing a procedure and/or wasting time in removing a catheter and selecting and navigating a different catheter into position.
Femoral artery access has been the preferred access point for cerebral artery procedures since the initial development of endovascular procedures, because of the relatively large size of the artery and hence the ability to introduce catheters of a larger diameter. In addition, the artery is quite superficial and easy to compress against the head of femur after the procedure, to stop the bleeding at the end of the procedure. In addition, access from the femoral artery over the aortic arch into the cervical vessels often has favorable, non-acute angles that allow quicker access into the cervical vessels without catheters getting kinked.
The downside of the femoral artery as an access point is that A) it can be relatively deep in obese patients and B) if the site of puncture is slightly high, bleeding from the artery can go into the retroperitoneum and is difficult to stop with compression. Hence, the incision to gain access to the femoral artery is deeper as compared to the radial artery, carries a larger bleeding risk and requires longer post-operative care (with that patient being confined to their bed for several hours) to monitor the incision prior to patient discharge from the care facility and thus typically incurs higher costs.
In comparison, the radial access point provides various advantages including limited need for post-operative monitoring of the incision and thus more rapid discharge of the patient from the care facility. However, while favorable not all procedures can be completed via a radial access.
Access from the radial artery provides two main challenges, namely the small size of the radial artery which limits the size of catheters that can be introduced and different, and usually more acute access angles at or near the aortic arch from this direction.
As noted above, two classes of catheters used in cerebral procedures are diagnostic and guide catheters. Diagnostic catheters are generally those used to gain access to an area of interest whereas guiding catheters are used to support and guide additional equipment including diagnostic catheters, guidewires balloons, other catheters etc. as may be required for a particular surgical technique.
Typical diagnostic catheters will range from 4F to 6F (French) and have lengths of 65-125 cm. They may have braided wall structures and they will generally have a soft tip with a range of shapes formed into the tip.
Guide catheters are generally larger (e.g. 6-8F) and are 80-100 cm in length. They generally have reinforced construction with a significantly stiffer shaft to provide back-up support and stability for the advancement of any additional equipment as mentioned above.
From an anatomical perspective, catheters generally pass through different zones of the vasculature, namely the abdominal and thoracic vasculature between the femoral artery and aortic arch (approximately 50-75 cm), the cervical vasculature (approximately 15-20 cm) and the cephalic/cerebral vasculature (approximately 10-15 cm), with vessel diameters constantly changing and being smallest in the cerebral vasculature.
Various properties and geometries may also be engineered into both diagnostic and guide catheters including:
In particular, diagnostic catheters are provided with a wide range of tips having the above shapes to allow the surgeon to choose an optimal tip shape that is best for an individual patient's anatomy when conducting a procedure.
Each catheter may be constructed from a plurality of materials, having various structures and/or layers within the catheter wall structure to give the catheter particular properties or functional characteristics. These may include:
The choice of a particular catheter or system of catheters may be determined by the skill and experience of a particular surgeon.
Typical properties of different catheters are summarized in Table 1.
In accordance with the invention, systems for enabling analysis of a patient's vasculature and providing output to physicians in conducting endovascular procedures are described.
In a first aspect, a system for analyzing tortuosity of a patient vasculature to provide input to a physician preparing for an endovascular surgical procedure is described, the system comprising: a database having a plurality of past patient image records (PPIR) wherein each PPIR includes a visual representation of a patient's vasculature, the database enabling access and assessment by one or more experts and wherein each PPIR can be updated to include one or more success scores where a success score is a rating of difficulty for completing an endovascular procedure (EP) access from an access point to a target vessel.
In various embodiments, the system includes a current patient input system for uploading a current patient image record (CPIR); a comparison system for comparing the CPIR to the plurality of PPIRs to determine a closest match between one or more PPIRs and the CPIR; and a success score display system for displaying one or more success scores from the closest match.
In another embodiment, the database includes separate success scores from two or more access points.
In various embodiments:
In another embodiment, the system further includes:
In one embodiment, the VTMS enables identification of one or more of vessel apex, vessel inflection point, vessel segment length, branch point angle, vessel support zone and vessel unsupported zone in 3D space.
In various embodiments, the VTMS enables identification of one or more of vessel looping, vessel kinking, vessel coiling, vessel corkscrew in 3D space and/or tortuosity measure includes sum of angles (SOAM), tortuosity index (TI), and curvature metric (CM).
In another embodiment, the success score further includes a risky manoeuvre (RM) output score and where the RM output score includes any one of or a combination of a measure of risk of local injury to a blood vessel and risk of dislodging a plaque or thrombus.
In one embodiment, the success score further includes a time factor score representing a time to complete an EP from any one of or a combination of a radial artery or femoral artery access point to a target vessel.
In one embodiment, the system further includes a vasculature modelling system (VMS) enabling modelling of the vasculature in 3D space where the VMS utilizes PPIRs and/or CPIRs and where the VMIS determines 3D surface coordinates for vessel walls, vessel centerlines, branch point angles and vessel apexes.
In one embodiment, the vasculature modelling system calculates tortuosity parameters for a modelled vasculature from the 3D surface coordinates for vessel walls, vessel centerlines, branch point angles and vessel apexes.
In another embodiment, the system includes an endovascular equipment (EE) database and where each PPIR can be updated to include recommended EE to complete an EP from one or more access points to one or more target vessels.
In another embodiment, the system includes a recommended EE display system for displaying an output of one or more pieces of EE recommended to conduct a procedure.
In another embodiment, the EE database enables a user to filter for available EE at a treatment facility and update success scores based on available EE.
In another embodiment, the system further comprises a hooked catheter reform module (HCRM) where the HCRM calculates vessel volumes within defined vessel segments and determines, based on physical size parameters of a hooked catheter, if the hooked catheter can be reformed in one or more vessel segments.
In another embodiment, the EE database includes modelled parameters of EE and the system further comprises an EE advancement module (EEAM) enabling simulation of EE advancement within a modelled vasculature wherein modelled EE is progressively advanced within a modelled vasculature and the EE advancement module tests progressive movement of modelled EE within the modelled vasculature to determine if the modelled EE can be advanced based on the modelled parameters.
In another embodiment, the EEAM includes an output module to display the feasibility of advancing specific EE within a vasculature.
In another embodiment, the EEAM output module displays color coded zones within a modelled vasculature and where a displayed color represents relative feasibility of advancing EE through a zone of the modelled vasculature.
In another embodiment, the EE database includes EE physical dimension and performance parameters for different EE, the EE selected from any one of a combination of guide wires, diagnostic catheters, guide catheters and stents.
In another embodiment, performance parameters include any one of or a combination of stiffness and torqueability.
In another embodiment, the EE database includes physical dimension and performance parameters for one or more combinations of guide wires and diagnostic catheters.
In another embodiment, the EE database includes physical dimension and performance parameters for one or more combinations of guide wires, diagnostic catheters and guide catheters.
In another embodiment, the EEAM evaluates the feasibility of advancing a guide catheter over a combined guide wire and diagnostic catheter based on a combined stiffness of each of the guide wire, diagnostic catheter and guide catheter.
In another embodiment, the past patient database includes a questionnaire module enabling experts reviewing PPIRs to assign success scores to a past patient image record.
In another embodiment, the system enables a training physician to access the PPIRs to review the success scores and EE used in past EPs.
In another embodiment, each PPIR is assembled into a PPIR 3D model and the system further includes a PPIR parameter measurement module for determining any one of or a combination of branch points, apex points, branch point distances and apex point distances.
In another embodiment, each CPIR is assembled into a CPIR 3D model and the system further includes a CPIR parameter measurement module for determining any one of or a combination of branch points, apex points, branch point distances and apex point distances.
In another embodiment, the system includes a comparison module where any one of or a combination of the branch points, apex points, branch point distances and apex point distances from the PPIR 3D models and a CPIR 3D model are compared in 3D space to identify one or more PPIR 3D models most closely matching the CPIR 3D model.
In another aspect, the invention provides a system for analyzing a patient vasculature to assign a success score for completing an endovascular procedure (EP) from an access point to a target vessel, the system including: a database having a plurality of past patient image records (PPIR) wherein each PPIR includes a visual representation of a patient's vasculature and success scores assigned to each PPIR; a PPIR analysis module for calculating a success score for a current patient image record (CPIR) wherein the PPIR analysis module calculates branch point angles and vessel tortuosity between the access point and the target vessel of CPIR and compares the branch point angles and vessel tortuosity of the CPIR to branch point angles and vessel tortuosity of PPIRs to obtain a best fit to the current patient and assign a success score based on the best fit.
The invention is described with reference to the drawings in which:
For the purposes of describing the invention, the following definitions and terms apply to the description:
In accordance with the invention, systems and methods are described that can provide a range of information that can assist a physician in deciding about treatment approaches for patients undergoing endovascular cerebral procedures where access to the cerebral arteries is required. In particular, the invention provides information about the degree of difficulty in accessing a brain vessel and the risk of complications while doing so via a radial artery or femoral artery access route, thereby assisting the physician in deciding about the optimal access route. In various embodiments, the system allows the physician to simulate different access routes to compare the difficulty and risk of complications.
For the purposes of initial general description,
Each of the above vessels and its relationship with respect to a distal or proximal (parent or daughter) vessel, that is the branching between two vessels can be described in terms of an angle between the two vessels and the direction one is approaching that vessel branch point from that is, either an RA or FA access point.
Branch points relevant to accessing each of the above vessels via one or more branch points (referred to herein as B1-B6) are characterized by the access point and the proximal arteries (vessel towards the site of the access point prior to the branch point) and distal arteries (vessel towards the brain vessel, beyond the branch point) that define take-off angles (R (Radial) or F (Femoral) referring to the access point). Representative take-off angles are shown in Table 2. As shown, as the direction that one is approaching a vessel junction is different, the take-off angle for a vessel junction will generally be different depending on the access site, i.e. the direction from which the vessel is approached. In most cases, as EE moves through a branch point, the EE will have to pass through an unsupported vessel zone.
In addition, features of vessel curvature that define the degree of tortuosity are relevant in accessing each of the above vessels. There will usually be sections along a desired vessel path with various features such as curvatures, apex and inflection points, different take-off angles and distances between apex/inflection points as well as the number and length of unsupported vessel zones branch-points, c- and s-shaped curves, kinked or coiled vessels. All these features contribute to determining overall access difficulty for a desired access route.
Navigating EE through vessels with tight curves, and numerous apex/tight inflection points requires the EE to be flexible. In addition, the translation of forward force and torque from a catheter end (outside the patient) to the catheter tip (inside the patient, in the vessels) gets less, and less predictable with an increase in overall tortuosity. Thus, in most cases, the access route with lower curvatures and a fewer number of apex/inflection points and fewer unsupported vessel zones will be the one with the highest likelihood of success.
As shown in Table 2, variations in take-off angles are substantial wherein individual branch points and/or a combination of branch points can readily enable, interfere with or prevent access from a RA or FA access point.
In addition to the above, vessel diameter, atherosclerotic burden and other parameters may also be considered in assessing a degree of difficulty from a particular access point as shown in Table 3.
In various embodiments, as shown in
Quantitative measurement of tortuosity may be achieved according to the following general protocol:
As described below, identifying points/zones to be measured may be conducted manually or automatically via various algorithms including machine learning algorithms.
Navigation of catheter systems through branch points can range from being relatively easy to difficult to impossible from different access points.
For example,
Similarly,
As such, it is readily understood that there are any number of intermediary examples where for example, it is unclear whether one route is better than the other and a decision may be based on a physician's qualitative feel of the overall situation. While experience may often enable a physician to make the right decision, less experienced physicians and those in training will not have the experience to make a decision based on qualitative feel of a patient's anatomy or be able to fully anticipate where problems may occur.
Generally, accessing cervical vessels from the RRA will often require navigation through branch points where the branch point angles are more acute and where a higher proportion of the overall route consists of unsupported vessel zones. For these procedures, the use of diagnostic catheters that have a “hooked”, i.e. a double-curved (“recurved”) catheter tip as the means of initially placing EE into a desired artery are required (
The use of a hooked DC poses various problems from a RA access point as explained below in describing a representative procedure of gaining access into the LCCA from the RA.
As shown in
After gaining radial artery access, the SIM is assembled with the GW such that the GW protrudes a short distance from the tip of the SIM. This straightens the distal tip of the SIM allowing it to be advanced and steered through the brachial, subclavian and innominate vessels to the aorta as shown in
Rarely, and only if the anatomy is favourable, the curve of the SIM can be reformed in the right subclavian or vertebral artery or the right common carotid artery.
The decision to re-form the hooked DC tip in the ascending or descending aorta and/or utilize the aortic valve/left ventricle as an abutment surface will depend on the patient's anatomy and generally whether or not the combined DC and GW can be navigated from a RA access point to the descending aorta. Whenever feasible, it is generally preferred to first try to utilize the descending aorta, then the ascending aorta and then the aortic valve as zones/surfaces for re-forming the hooked DC shape. This is because using the ascending aorta/aortic valve or left heart chamber as a surface to assist re-forming carries the risk of potential heart valve damage, embolization of plaques resulting in subsequent strokes and/or causing heart rhythm disorders.
It is generally also easier and quicker to re-form the hooked DC tip in the descending aorta and hence, will be preferred for a greater number of physicians as it generally requires less skill and experience. In contrast, reforming the SIM tip in the ascending aorta may be more difficult, take more time, increase the risk of complication and be more difficult to complete by less experienced physicians.
Once the DC has been reformed and regained its hooked shape, the physician will place the tip in a position to select the desired vessel origin and advance the GW and DC further into the vessel as shown in
In addition, when a GW/DC has been introduced into a target vessel, it is also necessary that other catheters including guide catheters (GCs) can be positioned in the cervical vessels over the DC and GW. Accordingly, it is also important to ensure that once the GW has been positioned and the DC is advanced, that the GC does not dislocate the entire system as shown in
In accordance with the invention, decision assist tools (DATs) are described that can be activated or utilized at different stages of the overall treatment planning process to assist the physician in assessing:
The DAT models are generally described as DAT1-DAT5 with increasing levels of information being provided or made available to the physician with each model and with increasing sophistication of simulating the performance of EE in a model vasculature. An “A” model utilizes expert opinion data, a “B” model utilizes a database consisting of data from past patients and a “C” model enables simulation of a procedure. That is, each DAT model can be built based on either or both of expert opinion providing input to the model and/or automatic review and assessment of data based on algorithms including machine learning algorithms and structural equation modeling.
In addition, in various embodiments, the prediction of success scores, likelihood of RMs being needed etc. are based on expert opinion (DATs 1A-4A; i.e. “A” designation). In other embodiments, once the past patient database has reached a sufficient size, the predictions can be based on a past patient database (DATs 1 B-4B; i.e. “B” designation). In other embodiments, once the past patient database has reached a sufficient size, the system may allow operators to practice either the whole procedure or critical procedure steps (DATs 1C-4C; i.e. “C” designation).
Data from past and current patients who have undergone a CT angiogram (CTA) of the aorta, neck and intracranial vessels can be a source of raw patient data for building 3D models of the relevant vasculature and be subject to analysis for quantifying vessel tortuosity. Magnetic resonance angiogram (MRA) may also be used as a raw patient data source. Typically, raw CTA images will be assembled and analyzed at a typical voxel size of 0.5 by 0.5 by 0.625 mm. Thus, 3D models built will enable measurements and parameter analysis at a high resolution. In various embodiments, 3D models may be further adapted to provide pulsatility information that includes vessel movement during the heart cycle.
Table 4 is a summary of the general functionality of each DAT model.
At a first level and as shown in
The past patient database includes a plurality of images from previous patients (patient records) 6a that may or may not have undergone endovascular procedures. Ideally, the patient records provide a representation of the scope of anatomies that an interventionist may encounter. The past patient database may include image data from patients of different sex, height, age and having a range of anatomical variations. Patient records 6a may also include associated data about past endovascular procedures undertaken and equipment used during those procedures. Such information may include information about procedures that may have been successfully or unsuccessfully completed.
Typically, images are available as a 2D layered model or a rendered 3D model as shown in
The initial measurements and analysis may be completed by expert review (DAT 1a) and include general success scores 6d for accessing each vessel by each route.
Current patient images 6e are compared to the past patient images to find the closest match 6f wherein success score information corresponding to one or more of the past patient images is displayed 6g. This information may be useful to the physician in making a treatment decision.
In further embodiments (DAT 1b), once a sufficiently large past patient database has been built which may include additional information regarding the success of completing procedures in a particular patient with particular EE, the classification of tortuosity, difficulty of navigating a catheter etc. can be based on analysis conducted on the past patient database rather than additional expert opinion.
In more advanced embodiments (DAT 1c), a full simulation environment based on information from earlier embodiments (DATs 1a and 1b) is offered to the operator, who can then practice certain procedure steps or the entire procedure prior to the “real” treatment.
That is, for each patient record, a series of images will have been analyzed by modelling software to a) assemble the images into a 2D or 3D model and b) enable measurements/analysis of relevant anatomical data.
In one embodiment, after assembly of a model, one or more physicians would review the set of patient images and/or model from a patient case and would identify zones of interest to provide a subjective assessment of the likelihood of success for accessing particular vessels (as per
By way of example, the model shown in
From this review, the record can be marked with general success scores 6d for getting past each branch point from each access point where general success scores will be numbers on a scale representing categories of relative difficulty.
Once assembled, the database with general success scores can be reviewed by users with or without a current patient. For example, a training physician may simply study the database to obtain both a qualitative and quantitative impression of the range of anatomies and the likelihood of success should he/she encounter similar real-case anatomies.
In addition, if the DAT is being used with a current patient and images from the current patient 6e, the DAT can be used to identify those records in the database that most closely match the current patient's anatomy.
This comparison may be done in a number of ways, for example, via groupings of past patient images into categories according to branch point angles, target vessels, access points or categories that are based on qualitative parameters around procedures.
As such, when a physician is reviewing a current patient and has identified a desired vessel (e.g. LCCA) and is looking to answer the question whether RA or FA access is possible, they may search the database and filter for records with similar anatomical features to the current patient.
Once a small number of past patient records has been identified whose characteristics may most closely match the current patient, those records may be examined more closely to review the general success scores of those past patients.
Thus, on review the physician may formulate a clearer picture of the likelihood of success from a particular access point to a particular target and base treatment decisions from that review.
As shown in
For example,
For example, after marking positions at B2, B3 and B4, the physician may note that that to gain access to the LCCA from either the FA or RA would be difficult due to the approximate 160 degrees branch point from the aorta to LCCA or from the BCT to the aorta. Alternatively, from the model, anatomical points may be estimated/calculated by the software, and tortuosity scores automatically calculated.
In addition, as shown schematically in
As such, difficult branch points and/or tortuous sections between branch points may be identified, and specific points marked at positions within the section at the locations along the centerline for quantification.
For example, for a c-shaped curve as per
As shown in
In one embodiment, the current patient images are automatically assembled into a 3D model and the centerlines of vessels and segments automatically calculated as per
For example, if
By repeating the comparison across a plurality of patient records, one or more past patient record(s) most similar to the current patient can be identified.
Importantly, the ultimate selection of the “closest” record may include additional refinements.
Furthermore, when looking to match records, if with the current patient, it is known that the target vessel is the LCCA, data relating to non-relevant vessels may be ignored.
In various embodiments, the single best matched past images/data is presented and/or a ranking of the closest past images/data is presented.
Once the closest match to past patient image/data is determined (or the physician is presented with a ranked list), the physician can examine the assessments within that record(s). For example, the model may provide an output as shown in Table 4. Importantly, while the past patient data will likely include data from all branch point measurements, certain measurements may not be relevant to a procedure that is being planned for with the current patient. Hence, if the physician has entered the target, only relevant data may be displayed.
Data may also be output as shown in
EE is available from many manufacturers and in many different product forms. As such, different EE products that may be produced by different manufacturers may be referenced as “GW1” or “GW2”, etc. as generic descriptors of Guide Wires. Similarly, other EE such as Diagnostic Catheters may referenced as “DC1”, “DC2”, etc.
Thus, when the best match between the current patient's data and the past patient database has been made, the physician can examine the likelihood of success relating to access points and target vessels. From Table 5 above, if the target vessel is the LCCA, the past data shows a moderately faster procedure and higher success rate from the FA together with EE that has been used.
With this data, the physician can evaluate which access point may be preferable having regard to the likelihood of success and the possible time to complete. The physician may also make a decision based on their own skill level.
As understood by those skilled in the art, many combinations of data can be presented to the physician where the format and content of that data is derived from the granularity of data within the past patient database and the inputs that may be provided by the physician for the current patient. Importantly, with an appropriate level of granularity and filterable outputs, the physician has an objective basis on which to base a decision.
In various embodiments (e.g. DAT 1A), the process to obtain an objective assessment of past patient data may be refined by a standardized questionnaire/interview process of the expert physicians. That is, to obtain an objective assessment, during the review process as shown in
Notable curvatures, apex and inflection points, atherosclerotic burden, EE that is likely to work, time factors and other relevant questions may be also asked.
In other embodiments (e.g. DAT 1 B), once a sufficiently large past patient database has been built, the classification of tortuosity, difficulty of navigating a catheter etc. can be derived from analysis of the past patient database rather than expert opinion per as noted above.
If the images being reviewed by the physician experts show a generally average anatomy, the experts may conclude that for this average anatomy that access from both the FA and RA is relatively easy to the LCCA and rank the likelihood of success from both routes in terms of difficulty (e.g. Scores of 1) and how much additional time it would take from one approach relative to the other one. For example, both routes may be ranked as “straightforward” but the RA access route may have a +X minute time factor (e.g. +4 minutes) added. This may be particularly important information for the physician to consider, if the patient's condition is time-sensitive.
From the same patient images, the experts may reach different conclusions for accessing different vessels. That is, input provided for accessing the RCCA may determine that the likelihood of success from the RA may remain at greater than 90% (e.g. a 1 score) but the likelihood of success from the FA may drop to 70-80% (e.g. a 2 score). The reason that the experts may conclude that FA access drops (despite the patient having a generally “average” anatomy) may be presence of apex points in the BCT that would have to be navigated from the FA route but not from the RA route.
In practice, the decision assist tool is useful in providing input to a physician after a decision has been made that it is worthwhile to conduct a particular endovascular procedure and the physician has determined the desired target vessel.
In various applications, the system can also be useful when a complete cerebral angiogram needs to be performed that requires access to both the right and the left carotid and vertebral arteries. In such a situation, if the system outputs a low success score for one of the four vessels from a RA route for example, the physician may decide to use a FA route, even if the remaining 3 vessels might be easy to access from a RA access route.
In various embodiments, the system is activated after non-invasive vascular imaging data has been collected from the current patient. That is, as soon as a non-invasive scan, for example a CTA or MRA, has been completed and while the physician is generally beginning their review of the current patient images, the system has completed or is concurrently conducting an analysis of current patient anatomy including take-off angles, vessel curvature, apex and inflection points of the vasculature.
As soon as the calculations have been made, the physician is advised and invited to input a desired target vessel. If all four cervical vessels need to be accessed as is often the case for the work up, for example in patients with acute sub-arachnoid hemorrhage, the physician can choose a “four-vessel option” to get an overall assessment for all four vessels as well as a separate assessment with potential points of difficulty for each vessel. The model receives that information and accesses the past patient database and calculates the likelihood of success (output) scores as described above.
Upon receiving the output scores, the physician can make a decision to conduct a procedure from a RA or FA or to take no action depending on the circumstances.
Utilizing fully modelled information from the patient's imaging data, expert input from DAT 1a and past patient data from DAT 1 b, DAT-1c allows a physician to plan for an intended procedure for example when a patient is being prepared for a procedure. That is, in one embodiment, the physician may input the desired vessel and available EE and the model determines if access to the desired vessel is possible using a generic selection of catheters.
In one embodiment, the DAT 1c model is connected to a neuroangiography operating console and allows physicians to practice and/or train in a realistic environment for single procedure steps or the whole procedure, by using a library of patient data, for example as part of a first “in vitro simulation phase” of their interventional training, prior to treating actual patients.
Additional functionalities can be provided in further embodiments as described below.
In further embodiments, the DAT introduces functionalities that provide information about the likelihood for successful GW and DC placement in the target vessel within an appropriate time frame based on the specific GW and DC properties. In various embodiments, the DAT2 model expands upon the functionality of DAT1. As with DAT1, DAT2 assembles current patient imaging data and enables measurement of anatomical features and various tortuosity parameters within zones of interest (i.e. between various anatomical points as described above). The physician inputs target vessel information.
As with DAT-1, measurements and analysis may be completed by expert review (DAT 2A;
In further embodiments (DAT 2B), once a sufficiently large past patient database has been built, the classification of tortuosity, difficulty of navigating a catheter etc. can be based on analysis of the past patient database rather than expert opinion per se. In various embodiments, classification may be a combination of both database analysis and physician input.
In more advanced embodiments (DAT 2c), a full simulation environment based on information from earlier embodiments (DATs 2a and 2b) is offered to the operator, who can then practice certain procedure steps or the entire procedure prior to the “real” treatment as described above.
Utilizing fully modelled information from the patient's imaging data, expert input from DAT 2a and past patient data from DAT 2b as well as information on properties of the selected GW and DC DAT-2c allows a physician to plan for an intended procedure with the selected GW and DC. The physician may input the desired vessel and available GW and DC he/she intends to use, and the model determines if access to the desired vessel is possible using the intended GW/DC combination.
In one embodiment, the DAT 2c model is connected to a neuroangiography operating console and allows physicians to practice and/or train in a realistic environment for single procedure steps or the whole procedure.
In addition, in one embodiment, the DAT2A model allows the physician to input data about recommended EE. In this embodiment, expert physicians may add recommendations for specific EE that may be utilized for a particular access route based on their observations of the patient's anatomy.
For example, with the LCCA as the target vessel, the physician may consider that as the time to complete an RA access procedure is longer and has a lower likelihood of success and that a FA procedure would be preferred in that the recommended EE (GW1 and DC3a) are on hand. However, the physician may decide based on this information that RA access is preferred because the recommended EE (GW1 and DC3a) are not on hand whereas the GW1+DC(SIM2) are on hand.
In another example, the experts may note that in considering access from the RA, a SIM catheter of a particular design may be more likely to succeed than others. The experts may note that a skilled practitioner should be able to access the relevant vessel in X minutes through the RA route and Y minutes through the FA route using catheter system A from the RA route and catheter system B from the FA route.
In one embodiment, the system accesses physical property data, e.g. data on stiffness, compliance and torquability of catheter systems stored in a catheter system database as shown in
The catheter system database includes physical property and performance data of individual catheters and combined EE systems from a EE database 7a explained in greater detail below.
In this embodiment, the DAT2 model evaluates the ability of EE such as GW and DC combinations to reach the target vessel(s).
Thus, the DAT2 model can output an estimated success score to gain access to the target vessel(s) via different access points utilizing specific combinations of GW and DC. For example, access from the RA to the BCT in a patient with a severely tortuous anatomy may be easier with a stiff GW and DC since they provide more stability and can “straighten out” the vessel. With a more flexible and thus less stable GW/DC system, access from the RA in the very same patient may be much more difficult.
The input may also provide specific information about any steps requiring “hooked” SIM type catheters.
For example, recommendations around SIM catheters may note one SIM catheter is soft at the point of the main curve and can be easily straightened out whereas a second SIM catheter is stiffer at the point of main curve and thus has a greater tendency to hold onto its shape. Both catheters will have advantages and disadvantages: the stiffer catheter may be better to hook the vessel and to advance wire; however, it may not advance over the wire.
Another issue with a stiffer catheter is that it may require more manipulation to regain its shape in the aorta and hence increase the chance of dislodging plaque. Thus, the DAT2 model may provide this output to the user.
Further still, in many hospitals, only a limited choice of EE is available. Thus, it is possible that, for example, access from the RA in a certain patient is generally feasible, but very difficult with the GW and DC equipment that are available at the physician's hospital. DAT2 allows the physician to restrict the GW and DC choice to the locally available EE and will provide the operator with information on how difficult various access routes when using the locally available DC/GW combinations.
Representative details EE properties included in an EE database are shown in Tables 6 (Diagnostic Catheters) and Table 7 (Guide Wires).
Third DAT (DAT3)—Success Scores for Guide Catheter Placement after Successful GW/DC Placement
The DAT3 estimates the likelihood for successful GC placement in the target vessel within an appropriate time frame after the GW and DC have been placed based on the specific GW and DC properties. The DAT3 system expands upon the functionality of DATs 1 and 2. As with DAT1 and DAT2, DAT3 assembles current patient imaging data and enables measurement of anatomical features. The physician inputs target vessel information.
As with DATs 1 and 2, in one embodiment, analysis may be completed by expert review (DAT 3A).
In other embodiments (DAT 3B), once a sufficiently large past patient database has been built, the classification of tortuosity, difficulty of navigating a catheter etc. can be based on analysis of the past patient database rather than expert opinion per se.
In more advanced embodiments (DAT 3c), a full simulation environment based on information from earlier embodiments (DATs 3a and 3b) is offered to the operator, who can then practice certain procedure steps or the entire procedure prior to the “real” treatment.
Utilizing fully modelled information from the patient's imaging data, expert input from DAT 3a and past patient data from DAT 3b as well as information on properties of the selected GW, DC and GC, DAT-3c allows a physician to plan for an intended procedure with the selected GW/DC and GC. The physician may input the desired vessel, available GW/DC and GC he/she intends to use, and the model determines if access to the desired vessel and GC placement is possible using the intended GW/DC and GC.
In one embodiment, DAT 3c model is connected to a neuroangiography operating console and allows physicians to practice and/or train in a realistic environment for single procedure steps (e.g. placement of the GC after the GW/DC have been advanced) or the whole procedure (including GW/DC navigation and GC placement; “from beginning to end”.
Similar to DAT2, DAT3 accesses physical property data, e.g. data on stiffness, compliance and torqueability of GW systems stored in a catheter system database.
In addition to the features of DAT 1 and DAT2, DAT3 also accesses physical property data, e.g. data on stiffness, compliance and torqueability of GC/DC systems stored in a catheter system database.
The catheter system database includes physical property and performance data of individual GC catheters and combined EE systems that contain GCs explained in greater detail below.
The DAT3 model estimates the likelihood of success of a GC in combination with different GW/DC combinations to reach the target vessel.
Specifically, the DAT3 model may output an estimated success score to navigate the GC to the target vessel via different access points utilizing specific combinations of GW and DC.
In many hospitals, only a limited choice of EE is available. Thus, it is possible that, for example, access from the RA in a certain patient is generally feasible, but very difficult with the GW/DC and GC that are available at the physician's hospital. DAT3 allows the physician to restrict the GW, DC and GC choice to the locally available EE and will provide the operator with information on how difficult various access routes are and how high the risk of dislocating the GW/DC into the aorta is when the GC is advanced (see
Fourth DAT (DAT4)—Success Scores for Placement of Additional Equipment that is Needed after Successful GW/DC and GC Placement
The DAT4 system expands upon the functionality of DATs 1, 2 and 3. As with the previous DATs, DAT4 assembles current patient imaging data and automatically measures anatomical features. The physician inputs target vessel information, the available EE and the model identifies combinations of GW/DC and GC that is available to access to the target vessel. The DAT4 model may further assess the likelihood of success of positioning additional EE that is needed for the procedure at the target vessel site within an appropriate time frame (e.g. stent-retriever in case of mechanical thrombectomy [fast placement required because of the time-sensitive nature of the disease], coiling catheter in case of an elective aneurysm coiling [time-insensitive procedure]), and the risk of dislocating the EE system from the target vessel into the aortic arch.
In various embodiments, the model may also take input from the physician regarding degree of stability of the GC that is needed once it is in position and is being used to advance other EE through it to proceed with the intervention. In general, if stiffer intracranial catheters and devices the operator intends to use are, and the more tortuous the vessels through which they are to be navigated, the more stable the GC needs to be. The physician can estimate the degree of stiffness of the EE to be used and the degree of intracranial tortuosity and input this estimate to DAT4. DAT4 can then calculate based on access route, GC GW and DC chosen, stiffness of the EE intended to use, and tortuosity, whether the GC would fulfill that degree of stability or not when the EE is advanced.
For example, the DAT4 model may show that access to a vessel is achievable using different combinations of DW and DC and GC to gain access to the cervical/cerebral vessels. However, as noted above, having gained access to a cervical/cerebral vessel does not ensure that additional EE can be advanced without causing the GW, DC and GC from dislocating out of the vessel and “falling back” into the aortic arch when the additional EE is advanced (See
With the DAT4 model, in one embodiment, the physician inputs that they wish to introduce a specific piece of EE, for example a stent-retriever, over a specific GW/DC/GC combination and the DAT4 determines that based on the combined stiffnesses of the GW/DC/GC and their position, whether or not introducing and navigating the stent-retriever would cause the GW/DC/GC combination to dislocate from the cervical vessel into the aortic arch.
In one embodiment, the DAT4 may select possible types of EE, e.g. certain types of stent-retrievers, from a library of EE that would or would not enable advancement to a specific position. Further still, the DAT4 may also highlight specific procedure steps with high risk of failure, i.e. steps during which dislocation of the system from the cervical vessel into the aortic arch is likely.
As with DATs 1-3, in one embodiment, measurements and analysis may be completed by expert review (DAT 4A).
In other embodiments (DAT 4B), once a sufficiently large past patient database has been built, the classification of tortuosity, difficulty of navigating a catheter etc. can be based on analysis of the past patient database rather than expert opinion per se.
In the more advanced embodiments (DAT 4c), a full simulation environment based on information from earlier embodiments (DATs 4a and 4b) is offered to the operator, who can then practice certain procedure steps or the entire procedure prior to the “real” treatment.
Utilizing fully modelled information from the patient's imaging data, expert input from DAT 4a and past patient data from DAT 4b as well as information on properties of the selected GW, DC, GC and additional EE, DAT-4c allows a physician to plan for an intended procedure with the selected GW/DC, GC and additional EE. The physician may input the desired vessel, available GW/DC, GC and additional EE he/she intends to use, and the model determines if access to the desired vessel and EE placement and usage is possible using the intended GW/DC, GC and EE.
In one embodiment, the DAT 4c model is connected to a neuroangiography operating console and allows physicians to practice and/or train in a realistic environment for single procedure steps (e.g. use of a stent-retriever to treat an intracranial occlusion after the GW/DC have been advanced and the GC has been placed) or the whole procedure (including GW/DC navigation, GC placement and stent-retriever navigation and placement; “from beginning to end”).
In each embodiment of the DATs (DATs 1-4), as noted above the initial objective is to provide information about the likelihood of success of a certain access route to the physician based on the current patient's anatomy, the desired vessel (DAT1), available and required EE (DATs 2-4) and to allow for in vitro simulation of the procedure in the specific patient anatomy incorporating all the information mentioned above (DATs 1 c-4c). As discussed, varying levels of information can be provided with progressive and greater granularity of information.
As noted, a particular objective is to provide information to the physician of the likelihood of success from a RA and FA access point and/or output regarding catheters/catheter systems, and possibly additional EE if it is required for the procedure, most likely to enable access and/or the relative degree of difficulty from a RA or FA.
Various methods of collecting and processing this information in accordance with various embodiments are described below.
As described above and shown inter alia in
3D models of the aortic arch and associated vessels are preferably obtained automatically from CT angiogram data and input into modelling software such as Syngo.Via (Siemens Healthineers).
In various embodiments, the following steps are undertaken:
From the current patient and past patient data, the data is analyzed to present output success scores to the physician.
In various embodiments, analysis is based on a primary success prediction and secondary success prediction.
The 1° (primary) success prediction success is hereby defined as safe and successful access to the relevant vessel in an appropriate time frame. This time frame would vary based on whether the underlying condition is time-sensitive or not. This 1° success prediction is determined by the percentage of procedures from the past patients' database that were successful from the same access point with similar anatomical features (i.e. allowing only for a small, pre-defined range of deviation from the current patient's features, e.g. take-off angles within a range of ±5 degrees of the current patient's take-off angles), taking into account the mechanical properties of the EE the operator intends to use.
The 2° (secondary) success prediction is determined by a weighted comparison of the current patient's anatomical features, including vessel curvature, tortuosity indices, inflection and apex points, branch points and take-off angles, with the anatomical features of the past patients database.
Note that, in contrast to the 1° success prediction, where all anatomical features had to be similar to the current patient, the 2° success prediction is performed on a per vessel-segment basis. A vessel segment is generally a uniform segment volume relative to a fixed anatomical position. For example, the aortic arch relative to the aortic valve can be sectioned into uniform segments each having a consistent length (relative to its central axis) and radius. Each segment abuts an adjacent segment at a particular angle thus defining an assembly of interconnected segments. Daughter vessels may be defined by similar lengths but will have smaller radii. Branch angles are defined by angles of segments relative to one another. It should be noted that other vessel segmenting methodologies may be employed.
This means that the number of similar cases in the past patient's database that are available may be different for each vessel segment. For example, there may be 10 cases in the past patient database with a B1:R take-off angle within the ±5% range of the current patient's B1:R take-off angle, but for the B2:R take-off angle, there might be 8 or 12 or any other number of cases in the past patient database within the ±5% range of the current patient's angle. This approach allows for utilization of all available information for each vessel segment.
In summary, in this embodiment, the model objectively calculates how well the current patient data correlates to past patient data when procedures have been successful and unsuccessful.
In addition, the system can highlight to the physician how the current vessel segments, and in particularly their curvature, inflection and apex points, branch points and take-off angles, differ from past patients with successful/unsuccessful procedures performed via the same access point with the same target vessel, and thus suggest which vessel segments are the ones with the highest risk of dislocation and/or access failure.
This forgoing may be applied to procedures performed from any access point, i.e. a right and/or left FA and/or RA access.
As described above, Endovascular equipment (EE) generally includes various wires and catheters that are assembled into co-axial systems to gain access to various vessels and enable various endovascular procedures to be conducted. Generally, EE includes guide wires (GWs) and microwires (MWs), diagnostic catheters (DCs), microcatheters (MCs), aspiration catheters (ACs), guide catheters (GCs) and balloon guide catheters (BGCs). As such, different pieces of EE are variable in terms of specific physical dimensional properties and performance properties in different vessels. That is, the physical measurements of different EE as well as the materials from which individual EE is constructed result in the overall functional/performance properties of each piece of EE. Moreover, as is known, EE may be constructed to have different dimensional and material properties along their lengths to enable specific functional properties in different zones to enable navigation through different levels of the vasculature and to provide certain functionalities (e.g. aspiration).
For example, diameters, wall thicknesses and materials of construction can be varied from a proximal end to a distal end of a catheter.
For example, a guide wire manufactured from a specific alloy with a consistent diameter along its length will have consistent properties including stiffness and torqueability in all zones of the wire. That is, all locations of the wire along its length will have a consistent minimum bending radius along its length.
Similarly, a microcatheter having a consistent material and wall thickness along its length will also have a consistent minimum bending radius along its length. If either the wall thickness or material is varied along its length, the stiffness (i.e. minimum bending radius) will vary along the length. The torqueability may also vary.
An assembly of a guide wire and microcatheter will also have different properties as compared to the individual components. For example, the distal tip of a microcatheter with a guide wire protruding 1 cm from the distal end of the MC will have different properties compared to the distal tip of an MC with a GW having a distal tip 1 cm proximal to the distal tip of the MC.
Thus, depending on the individual and collective properties of various pieces of EE, overall behaviour of catheters and catheter systems can be modelled with varying degrees of granularity. Greater granularity of modelled performance may be desired for the more distal regions of a catheter where physical dimensions of the vessels in which such pieces of equipment are interacting become smaller.
In one embodiment, a database of EE is assembled containing dimensional and functional data of individual pieces of EE and assemblies of EE for use in conjunction with 3D model data of a patient's vessels to predict the performance of EE within specific vessels. Table 8 shows representative data of a modelled guide wire and Table 9 shows representative data of a modelled microcatheter.
Calculate Feasibility of Introducing a Catheter/Catheter System into RA and/or FA to Gain Access to Position Past Desired Junction
From these measured properties, the EE is assembled as EE virtual models that can be moved through a virtual model of a patient's vasculature such that the behaviour of the modelled EE and assembled EE is predicted in a specific modelled vasculature, for example within the modelled vasculature of a current patient in preparing for a procedure.
Importantly, as noted above, a key consideration of a RA route is the high likelihood of requiring a “hooked” SIM type catheter, which has to be re-formed in the aorta. Hence, in various embodiments, the system determines the likelihood of being able to reform the hooked catheter in the descending aorta, ascending aorta or elsewhere after it has generally been determined that the hooked catheter can reach these vessels from an RA access point.
That is, for a current patient anatomy, the system determines whether there is room/volume within the ascending or descending aorta (or elsewhere) to re-form the tip of the hooked catheter and whether the catheter can reach the ascending or descending aorta.
To do this, the following general steps are completed:
In one embodiment, the system determines the recommended location to re-form by comparing the current patient anatomy to data within a past patient database and make the determination by a comparison of take-off angles and volumes as generally described above.
In one embodiment, the system may virtually advance modelled EE through a model of the current patient vessels and based on that simulation determine the likelihood of success of completing access to the target vessel by examining the results of one or more combinations of EE moving virtually to the aorta, descending aorta and ascending aorta. To do this, modelled combinations of EE are advanced through the modelled vessels in a series of steps where with each virtual advancement, the feasibility of each step is tested by the limitations of the modelled EE. Torqueing steps may be included (and highlighted to the physician).
In various embodiments, for each step of advancement, the system may assign a score to that step including, yes, the step is possible, no, the step is not possible or yes, step is possible with the chance of success being approximately X % (e.g. 10%). This score may be utilized to determine the difficulty of the different procedure steps, and to bring to the physician's attention what the most difficult steps are in which problems may be encountered.
In one embodiment, the steps of virtually advancing the modelled EE through a modelled vasculature may include a graphical presentation to the physician.
In one embodiment, with each step of advancement, the step is graphically displayed and each step of advancement, color coded according to the degree of difficulty/likelihood of success, with the step score described above. For example, if a specific procedure step has a high chance of success, the modelled EE or modelled vasculature may be overlayered with a green color. Similarly, if a certain other procedure step has a low chance of success, the modelled EE or modelled vasculature may be overlayered with a red color. Yet another procedure step that has a chance of success near 50% may be displayed with a yellow color. See
Besides the difficulty of the single procedure steps, an overall success estimate (1° and 2° success predictions) may be displayed to the physician.
This forgoing may be applied to procedures performed from any access point, i.e. a right and/or left FA and/or RA access.
If the system determines that the EE can be oriented to enable selecting/placement of the EE in a target vessel, in various embodiments, the system will then determine if the GW/DC can be advanced into the target vessel without dislocation from the selected vessel into the aorta.
In these embodiments, the system introduces additional parameters to those discussed above in connection with the modelled vasculature and modelled EE.
In one embodiment, the modelled EE takes into consideration the stiffness/flexibility of larger GCs that may be advanced over a DC/GW combination, and additional devices that may be required for the procedure (e.g. stent-retrievers to remove a blood clot, or coiling catheters to treat an aneurysm). It could also take into account the tortuosity of intracranial vessels and degree of forward pushability that would be needed to reach the point of interest. In general, the higher the requirement of pushability, the more stable the GC has to be in the neck. For example, within the simulation a DC/MW may have been successfully advanced into the cervical vessels with the distal tips of this EE ultimately positioned in the upper neck. In conducting this step during an actual procedure, a physician does not want the DC/GW to dislocate from the cervical vessels as the GC is being advanced or when the DC/GW are being withdrawn after the GC has been positioned in the upper neck.
In one embodiment, the simulation is continued as described above in which step-wise advancement or step-wise removal of EE is simulated.
For example, the simulation may show that a specific combination of a DC/GW can be successfully maneuvered from the RA to the LCCA with chances of success for passing the B4:R take-off angle being at approximately 75%. The initial stages of the simulation may therefore be positive. However, in continuing the simulation, when it is desired to advance a GC over the DC/GW, the stiffness of the distal tip of a chosen GC may indicate that chances of successfully pushing the GC around through the B4:R junction/angle are close to 0%, because the stiffness of the DC/GW may cause. them to dislocate from the cervical vessels into the aorta when the GC is pushed forward.
As above, in one embodiment, the presentation of graphical information may include color-coded displays to indicate where a problem is likely to occur.
In all of the above, the simulations may also determine a time-estimate to complete a procedure from a particular access point and with particular EE. When simulated from different access points and using different EE, a time-comparison of different simulated procedures may be presented to the physician.
As shown in
As described above, in various embodiments, various inputs may include EE specifications, the target vessel site and individual patient anatomy.
In the case of EE specifications, this information may be selected by the user via a graphical user interface such as a drop-down menu that includes information about specific commercial equipment used in endovascular procedures.
Similarly, a target vessel (including both vessel name and position within that vessel) may be input via a graphical user interface.
Individual patient anatomy may be input from existing imaging software and equipment such as via a DICOM communication protocol/interface.
Upon collection of each of the inputs, the data may be combined (e.g. the anatomical patient data may be combined with the EE and target vessel the surgeon has selected via the graphical user interface) and the combined data is then analyzed.
Generally, as described above, each model may undertake various analyses to assess one more difficulty scores. Various modelling methods may be utilized including “structural equation modelling”.
Structural equation modelling (SEM) is a mathematical method that allows for representation, estimation and testing of a network of complex relationships between variables, such as vessel tortuosity, vessel length and diameter, and the interplay between endovascular equipment and vessel anatomy. SEM includes measured variables, e.g. vessel length, and latent variables. Latent variables are variables that are not directly observed but can be inferred from other variables that are observed. In one example, the degree of difficulty when navigating through a particular vessel segment or the probability of a RM cannot be directly measured, but it can be inferred when combining information from several measured variables such as vessel tortuosity, branch point angles and EE properties. SEM includes path analysis and accounts for complex multi-directional relationships, mediation effects and interaction effects. For example, patient age influences atherosclerotic burden (with increasing age, atherosclerotic burden increases since vessels tend to calcify with age). Patient age also directly influences vessel wall fragility (with increasing age, vessel wall fragility increases because of degradation of the collagen and elastin fibers in the vessel wall). At the same time, atherosclerotic burden influences vessel wall fragility (vessels with atherosclerotic disease are more rigid and thus more prone to injury compared to non-diseased vessel segments). Thus, there is both direct effect of patient age on vessel wall fragility (patient age>vessel wall fragility) and an indirect effect of patient age on vessel wall fragility via atherosclerotic burden (patient age>atherosclerotic burden>vessel wall fragility). In other words, part of the effect of patient age on vessel wall fragility is mediated by atherosclerotic burden. Such complex relationships are very common in medicine, and SEM is able to accurately reflect them.
In various embodiments, these analyses can include assessing the degree of difficulty to:
Upon completion of these analyses, various outputs may be presented to a user. These can include:
Additional recommendations may be presented including:
Examples of the various inputs, analyses and outputs are shown in
| Number | Date | Country | |
|---|---|---|---|
| 63179924 | Apr 2021 | US |
