On the necessity to include arterial pre-stress in patient-specific simulations of minimally invasive procedures.

Transcatheter aortic valve implantation (TAVI) and thoracic endovascular aortic repair (TEVAR) are minimally invasive procedures for treating aortic valves and diseases. Finite element simulations have proven to be valuable tools in predicting device-related complications. In the literature, the inclusion of aortic pre-stress has not been widely investigated. It plays a crucial role in determining the biomechanical response of the vessel and the device-tissue interaction. This study aims at demonstrating how and when to include the aortic pre-stress in patient-specific TAVI and TEVAR simulations. A percutaneous aortic valve and a stent-graft were implanted in aortic models reconstructed from patient-specific CT scans. Two scenarios for each patient were compared, i.e., including and neglecting the wall pre-stress. The neglection of pre-stress underestimates the contact pressure of 48% and 55%, the aorta stresses of 162% and 157%, the aorta strains of 77% and 21% for TAVI and TEVAR models, respectively. The stent stresses are higher than 48% with the pre-stressed aorta in TAVI simulations; while, similar results are obtained in TEVAR cases. The distance between the device and the aorta is similar with and without pre-stress. The inclusion of the aortic wall pre-stress has the capability to give a better representation of the biomechanical behavior of the arterial tissues and the implanted device. It is suggested to include this effect in patient-specific simulations replicating the procedures.

Microcatheter tracking in thrombectomy procedures: A finite-element simulation study.

BACKGROUND AND OBJECTIVE: Mechanical thrombectomy is a minimally invasive procedure that aims at removing the occluding thrombus from the vasculature of acute ischemic stroke patients. Thrombectomy success and failure can be studied using in-silico thrombectomy models. Such models require realistic modeling steps to be effective. We here present a new approach to model microcatheter tracking during thrombectomy. METHODS: For 3 patient-specific vessel geometries, we performed finite-element simulations of the microcatheter tracking (1) following the vessel centerline (centerline method) and (2) as a one-step insertion simulation, where the microcatheter tip was advanced along the vessel centerline while its body was free to interact with the vessel wall (tip-dragging method). Qualitative validation of the two tracking methods was performed with the patient's digital subtraction angiography (DSA) images. In addition, we compared simulated thrombectomy outcomes (successful vs unsuccessful thrombus retrieval) and maximum principal stresses on the thrombus between the centerline and tip-dragging method. RESULTS: Qualitative comparison with the DSA images showed that the tip-dragging method more realistically resembles the patient-specific microcatheter-tracking scenario, where the microcatheter approaches the vessel walls. Although the simulated thrombectomy outcomes were similar in terms of thrombus retrieval, the thrombus stress fields (and the associated fragmentation of the thrombus) were strongly different between the two methods, with local differences in the maximum principal stress curves up to 84%. CONCLUSIONS: Microcatheter positioning with respect to the vessel affects the stress fields of the thrombus during retrieval, and therefore, may influence thrombus fragmentation and retrieval in-silico thrombectomy.

In silico thrombectomy trials for acute ischemic stroke.

BACKGROUND AND OBJECTIVE: In silico trials aim to speed up the introduction of new devices in clinical practice by testing device design and performance in different patient scenarios and improving patient stratification for optimizing clinical trials. In this paper, we demonstrate an in silico trial framework for thrombectomy treatment of acute ischemic stroke and apply this framework to compare treatment outcomes in different subpopulations and with different thrombectomy stent-retriever devices. We employ a novel surrogate thrombectomy model to evaluate the thrombectomy success in the in silico trial. METHODS: The surrogate thrombectomy model, built using data from a fine-grained finite-element model, is a device-specific binary classifier (logistic regression), to estimate the probability of successful recanalization, the outcome of interest. We incorporate this surrogate model within our previously developed in silico trial framework and demonstrate its use with three examples of in silico clinical trials. The first trial is a validation trial for the surrogate thrombectomy model. We then present two exploratory trials: one evaluating the performance of a commercially available device based on the fibrin composition in the occluding thrombus and one comparing the performance of two commercially available stent retrievers. RESULTS: The Validation Trial showed the surrogate thrombectomy model was able to reproduce a similar recanalization rate as the real-life MR CLEAN trial (p=0.6). Results from the first exploratory trial showed that the chance of successful thrombectomy increases with higher blood cell concentrations in the thrombi, which is in line with observations from clinical data. The second exploratory trial showed improved recanalization success with a newer stent retriever device; however, these results require further investigation as the surrogate model for the newer stent retriever device has not yet been validated. CONCLUSIONS: In this novel study, we have shown that in silico trials have the potential to help inform medical device developers on the performance of a new device and may also be used to select populations of interest for a clinical trial. This would reduce the time and costs involved in device development and traditional clinical trials.

A low dimensional surrogate model for a fast estimation of strain in the thrombus during a thrombectomy procedure.

BACKGROUND: Intra-arterial thrombectomy is the main treatment for acute ischemic stroke due to large vessel occlusions and can consist in mechanically removing the thrombus with a stent-retriever. A cause of failure of the procedure is the fragmentation of the thrombus and formation of micro-emboli, difficult to remove. This work proposes a methodology for the creation of a low-dimensional surrogate model of the mechanical thrombectomy procedure, trained on realizations from high-fidelity simulations, able to estimate the evolution of the maximum first principal strain in the thrombus. METHOD: A parametric finite-element model was created, composed of a tapered vessel, a thrombus, a stent-retriever and a catheter. A design of experiments was conducted to sample 100 combinations of the model parameters and the corresponding thrombectomy simulations were run and post-processed to extract the maximum first principal strain in the thrombus during the procedure. Then, a surrogate model was built with a combination of principal component analysis and Kriging. RESULTS: The surrogate model was chosen after a sensitivity analysis on the number of principal components and was tested with 10 additional cases. The model provided predictions of the strain curves with correlation above 0.9 and a maximum error of 28%, with an error below 20% in 60% of the test cases. CONCLUSIONS: The surrogate model provides nearly instantaneous estimates and constitutes a valuable tool for evaluating the risk of thrombus rupture during pre-operative planning for the treatment of acute ischemic stroke.

Combined stent-retriever and aspiration intra-arterial thrombectomy performance for fragmentable blood clots: A proof-of-concept computational study.

Mechanical thrombectomy (MT) treatment of acute ischemic stroke (AIS) patients typically involves use of stent retrievers or aspiration catheters alone or in combination. For in silico trials of AIS patients, it is crucial to incorporate the possibility of thrombus fragmentation during the intervention. This study focuses on two aspects of the thrombectomy simulation: i) Thrombus fragmentation on the basis of a failure model calibrated with experimental tests on clot analogs; ii) the combined stent-retriever and aspiration catheter MT procedure is modeled by adding both the proximal balloon guide catheter and the distal access catheter. The adopted failure criterion is based on maximum principal stress threshold value. If elements of the thrombus exceed this criterion during the retrieval simulation, then they are deleted from the calculation. Comparison with in-vitro tests indicates that the simulation correctly reproduces the procedures predicting thrombus fragmentation in the case of red blood cells rich thrombi, whereas non-fragmentation is predicted for fibrin-rich thrombi. Modeling of balloon guide catheter prevents clot fragments' embolization to further distal territories during MT procedure.

Self-expandable stent for thrombus removal modeling: Solid or beam finite elements?

BACKGROUND: The performance of self-expandable stents is being increasingly studied by means of finite-element analysis. As for peripheral stents, transcatheter valves and stent-grafts, there are numerous computational studies for setting up a proper model, this information is missing for stent-retrievers used in the procedure of thrombus removal in cerebral arteries. It is well known that the selection of the appropriate finite-element dimensions (topology) and formulations (typology) is a fundamental step to set up accurate and reliable computational simulations. In this context, a thorough verification analysis is here proposed, aimed at investigating how the different element typologies and topologies - available to model a stent-retriever - affect simulation results. METHOD: Hexahedral and beam element formulations were analyzed first individually by virtually replicating a crimping test on the device, and then by replicating the thrombectomy procedure aiming at removing a thrombus from a cerebral vessel. In particular, three discretization refinements for each element type and different element formulations including both full and reduced integration were investigated and compared in terms of the resultant radial force of the stent and the stress field generated in the thrombus. RESULTS: The sensitivity analysis on the element formulation performed with the crimping simulations allowed the identification of the optimal setting for each element family. Both setting lead to similar results in terms of stent performance in the virtual thrombectomy and should be used in future studies simulating the mechanical thrombectomy with stent-retrievers. CONCLUSIONS: The carried out virtual thrombectomy procedures confirmed that the beam element formulation results were sufficiently accurate to model the radial force and the performance of the stent-retriever during the procedure. For different self-expandable stents, hexahedral formulation could be essential in stress analysis.

Reliable Numerical Models of Nickel-Titanium Stents: How to Deduce the Specific Material Properties from Testing Real Devices.

The current interest of those dealing with medical research is the preparation of digital twins. In this frame, the first step to accomplish is the preparation of reliable numerical models. This is a challenging task since it is not common to know the exact device geometry and material properties unless in studies performed in collaboration with the manufacturer. The particular case of modeling Ni-Ti stents can be highlighted as a worst-case scenario due to both the complex geometrical features and non-linear material response. Indeed, if the limitations in the description of the geometry can be overcome, many difficulties still exist in the assessment of the material, which can vary according to the manufacturing process and requires many parameters for its description. The purpose of this work is to propose a coupled experimental and computational workflow to identify the set of material properties in the case of commercially-resembling Ni-Ti stents. This has been achieved from non-destructive tensile tests on the devices compared with results from Finite Element Analysis (FEA). A surrogate modeling approach is proposed for the identification of the material parameters, based on a minimization problem on the database of responses of Ni-Ti materials obtained with FEA with a series of different parameters. The reliability of the final result was validated through the comparison with the output of additional experiments.

Development of a patient-specific cerebral vasculature fluid-structure-interaction model.

Development of in-silico models of patient-specific cerebral artery networks presents several significant technical challenges: (i) The resolution and smoothness of medical CT images are much lower than the required element/cell length for FEA/CFD/FSI models; (ii) contact between vessels, and indeed self contact of high tortuosity vessel segments are not clearly identifiable from medical CT images. Commercial model construction software does not provide customised solutions for such technical challenges, with the result that accurate, efficient and automated development of patient-specific models of the cerebral vessels is not facilitated. This paper presents the development of a customised and highly automated platform for the generation of high resolution patient-specific FEA/CFD/FSI models from clinical images. This platform is used to perform the first fluid-structure-interaction patient-specific analysis of blood flow and artery deformation of an occluded cerebral vessel. Results demonstrate that in addition to flow disruption, clot occlusion significantly alters the geometry and strain distribution in the vessel network, with the blocked M2 segment undergoing axial elongation. The new computational approach presented in this study can be further developed as a clinical diagnostic tool and as a platform for thrombectomy device design.

Semi-Automatic Reconstruction of Patient-Specific Stented Coronaries based on Data Assimilation and Computer Aided Design.

PURPOSE: The interplay between geometry and hemodynamics is a significant factor in the development of cardiovascular diseases. This is particularly true for stented coronary arteries. To elucidate this factor, an accurate patient-specific analysis requires the reconstruction of the geometry following the stent deployment for a computational fluid dynamics (CFD) investigation. The image-based reconstruction is troublesome for the different possible positions of the stent struts in the lumen and the coronary wall. However, the accurate inclusion of the stent footprint in the hemodynamic analysis is critical for detecting abnormal stress conditions and flow disturbances, particularly for thick struts like in bioresorbable scaffolds. Here, we present a novel reconstruction methodology that relies on Data Assimilation and Computer Aided Design. METHODS: The combination of the geometrical model of the undeployed stent and image-based data assimilated by a variational approach allows the highly automated reconstruction of the skeleton of the stent. A novel approach based on computational mechanics defines the map between the intravascular frame of reference (called L-view) and the 3D geometry retrieved from angiographies. Finally, the volumetric expansion of the stent skeleton needs to be self-intersection free for the successive CFD studies; this is obtained by using implicit representations based on the definition of Nef-polyhedra. RESULTS: We assessed our approach on a vessel phantom, with less than 10% difference (properly measured) vs. a customized manual (and longer) procedure previously published, yet with a significant higher level of automation and a shorter turnaround time. Computational hemodynamics results were even closer. We tested the approach on two patient-specific cases as well. CONCLUSIONS: The method presented here has a high level of automation and excellent accuracy performances, so it can be used for larger studies involving patient-specific geometries.

The first virtual patient-specific thrombectomy procedure.

Treatment of acute ischemic stroke has been recently improved with the introduction of endovascular mechanical thrombectomy, a minimally invasive procedure able to remove a clot using aspiration devices and/or stent-retrievers. Despite the promising and encouraging results, improvements to the procedure and to the stent design are the focus of the recent efforts. Computational studies can pave the road to these improvements, providing their ability to describe and accurately reproduce a real procedure. A patient with ischemic stroke due to intracranial large vessel occlusion was selected and after the creation of the cerebral vasculature from computed tomography images and a histologic analysis to determine the clot composition, the entire thrombectomy procedure was virtually replicated. As in the real situation, the computational replica showed that two attempts were necessary to remove the clot, as a result of the position of the stent retriever with respect to the clot. Furthermore, the results indicated that clot fragmentation did not occur as the deformations were mainly in a compressive state without the possibility for clot cracks to propagate. The accurate representation of the procedure can be used as an important step for operative optimization planning and future improvements of stent designs.

Applicability analysis to evaluate credibility of an in silico thrombectomy procedure.

Intra-arterial thrombectomy is a minimally invasive procedure in which an obstructing thrombus (clot) is removed using a minimally-invasive device: a stent-retriever. The stent-retriever is first deployed, and then the thrombus is removed during stent-retriever retraction. This procedure can be simulated using a detailed computational model. However, to be useful for an in silico trial in a clinical setting, model credibility should be demonstrated. The aim of this work is to apply a credibility process for the validation phases to the thrombectomy procedure in order to deem it credible for use in an in silico trial. Validation evidence is proposed for the identified context of use and then used to build credibility to the numerical model. Applicability of the proposed model is justified and assessed using a rigorous step-by-step method based on the ASME V&V40 protocol.

Impact of the Internal Carotid Artery Morphology on in silico Stent-Retriever Thrombectomy Outcome.

The aim of this work is to propose a methodology for identifying relationships between morphological features of the cerebral vasculature and the outcome of in silico simulations of thrombectomy, the mechanical treatment for acute ischemic stroke. Fourteen patient-specific cerebral vasculature segmentations were collected and used for geometric characterization of the intracranial arteries mostly affected by large vessel occlusions, i.e., internal carotid artery (ICA), middle cerebral artery (MCA) and anterior cerebral artery (ACA). First, a set of global parameters was created, including the geometrical information commonly provided in the clinical context, namely the total length, the average diameter and the tortuosity (length over head-tail distance) of the intracranial ICA. Then, a more exhaustive geometrical analysis was performed to collect a set of local parameters. A total of 27 parameters was measured from each patient-specific vascular configuration. Fourteen virtual thrombectomy simulations were performed with a blood clot with the same length and composition placed in the middle of the MCA. The model of TREVO ProVue stent-retriever was used for all the simulations. Results from simulations produced five unsuccessful outcomes, i.e., the clot was not removed from the vessels. The geometric parameters of the successful and unsuccessful simulations were compared to find relations between the vascular geometry and the outcome. None of the global parameters alone or combined proved able to discriminate between positive and negative outcome, while a combination of local parameters allowed to correctly identify the successful from the unsuccessful simulations. Although these results are limited by the number of patients considered, this study indicates a promising methodology to relate patient-specific geometry to virtual thrombectomy outcome, which might eventually guide decision making in the treatment of acute ischemic stroke.

Applicability assessment of a stent-retriever thrombectomy finite-element model.

An acute ischaemic stroke appears when a blood clot blocks the blood flow in a cerebral artery. Intra-arterial thrombectomy, a mini-invasive procedure based on stent technology, is a mechanical available treatment to extract the clot and restore the blood circulation. After stent deployment, the clot, trapped in the stent struts, is pulled along with the stent towards a receiving catheter. Recent clinical trials have confirmed the effectiveness and safety of mechanical thrombectomy. However, the procedure requires further investigation. The aim of this study is the development of a numerical finite-element-based model of the thrombectomy procedure. In vitro thrombectomy tests are performed in different vessel geometries and one simulation for each test is carried out to verify the accuracy and reliability of the proposed numerical model. The results of the simulations confirm the efficacy of the model to replicate all the experimental setups. Clot stress and strain fields from the numerical analysis, which vary depending on the geometric features of the vessel, could be used to evaluate the possible fragmentation of the clot during the procedure. The proposed in vitro/in silico comparison aims at assessing the applicability of the numerical model and at providing validation evidence for the specific in vivo thrombectomy outcomes prediction.