Validation evidence with experimental and clinical data to establish credibility of TAVI patient-specific simulations.

PURPOSE: The objective of this study is to validate a novel workflow for implementing patient-specific finite element (FE) simulations to virtually replicate the Transcatheter Aortic Valve Implantation (TAVI) procedure. METHODS: Seven patients undergoing TAVI were enrolled. Patient-specific anatomical models were reconstructed from pre-operative computed tomography (CT) scans and subsequentially discretized, considering the native aortic leaflets and calcifications. Moreover, high-fidelity models of CoreValve Evolut R and Acurate Neo2 valves were built. To determine the most suitable material properties for the two stents, an accurate calibration process was undertaken. This involved conducting crimping simulations and fine-tuning Nitinol parameters to fit experimental force-diameter curves. Subsequently, FE simulations of TAVI procedures were conducted. To validate the reliability of the implemented implantation simulations, qualitative and quantitative comparisons with post-operative clinical data, such as angiographies and CT scans, were performed. RESULTS: For both devices, the simulation curves closely matched the experimental data, indicating successful validation of the valves mechanical behaviour. An accurate qualitative superimposition with both angiographies and CTs was evident, proving the reliability of the simulated implantation. Furthermore, a mean percentage difference of 1,79 ± 0,93 % and 3,67 ± 2,73 % between the simulated and segmented final configurations of the stents was calculated in terms of orifice area and eccentricity, respectively. CONCLUSION: This study shows the successful validation of TAVI simulations in patient-specific anatomies, offering a valuable tool to optimize patients care through personalized pre-operative planning. A systematic approach for the validation is presented, laying the groundwork for enhanced predictive modeling in clinical practice.

Discussing on the Aortic Coverage in Type B Aortic Dissection Treatment: A Comprehensive Scoping Review.

OBJECTIVE: The objective of this study is to investigate and address the question surrounding the determination of the optimal endograft length of coverage during TEVAR for type B aortic dissection (TBAD), with a particular emphasis on the distal landing zone (DLZ). DATA SOURCES: MEDLINE, Scopus, and Web of Science databases were used. METHODS: The PRISMA-ScR statement was followed. RESULTS: Several variables can contribute to the length of coverage during TEVAR in TBAD patient. Baseline patient's characteristics, TBAD-related features, the type of endoprosthesis, and postoperative graft behaviour may contribute to the choice of coverage. CONCLUSIONS: No robust data have been published regarding the optimal length of TEVAR. Therefore, reporting the percentage of covered aorta and improving computational studies should be valorised to improve postoperative outcomes.

Shear Stress Quantification in Tissue Engineering Bioreactor Heart Valves: A Computational Approach.

Tissue-engineered heart valves can grow, repair, and remodel after implantation, presenting a more favorable long-term solution compared to mechanical and porcine valves. Achieving functional engineered valve tissue requires the maturation of human cells seeded onto valve scaffolds under favorable growth conditions in bioreactors. The mechanical stress and strain on developing valve tissue caused by different pressure and flow conditions in bioreactors are currently unknown. The aim of this study is to quantify the wall shear stress (WSS) magnitude in heart valve prostheses under different valve geometries and bioreactor flow rates. To achieve this, this study used fluid-structure interaction simulations to obtain the valve's opening geometries during the systolic phase. These geometries were then used in computational fluid dynamics simulations with refined near-wall mesh elements and ranges of prescribed inlet flow rates. The data obtained included histograms and regression curves that characterized the distribution, peak, and median WSS for various flow rates and valve opening configurations. This study also found that the upper region of the valve near the commissures experienced higher WSS magnitudes than the rest of the valve.

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.

Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions.

Artificial intelligence, computational simulations, and extended reality, among other 21st century computational technologies, are changing the health care system. To collectively highlight the most recent advances and benefits of artificial intelligence, computational simulations, and extended reality in cardiovascular therapies, we coined the abbreviation AISER. The review particularly focuses on the following applications of AISER: 1) preprocedural planning and clinical decision making; 2) virtual clinical trials, and cardiovascular device research, development, and regulatory approval; and 3) education and training of interventional health care professionals and medical technology innovators. We also discuss the obstacles and constraints associated with the application of AISER technologies, as well as the proposed solutions. Interventional health care professionals, computer scientists, biomedical engineers, experts in bioinformatics and visualization, the device industry, ethics committees, and regulatory agencies are expected to streamline the use of AISER technologies in cardiovascular interventions and medicine in general.

Investigating the effect of drug release on in-stent restenosis: A hybrid continuum - agent-based modelling approach.

BACKGROUND AND OBJECTIVE: In-stent restenosis (ISR) following percutaneous coronary intervention with drug-eluting stent (DES) implantation remains an unresolved issue, with ISR rates up to 10%. The use of antiproliferative drugs on DESs has significantly reduced ISR. However, a complete knowledge of the mechanobiological processes underlying ISR is still lacking. Multiscale agent-based modelling frameworks, integrating continuum- and agent-based approaches, have recently emerged as promising tools to decipher the mechanobiological events driving ISR at different spatiotemporal scales. However, the integration of sophisticated drug models with an agent-based model (ABM) of ISR has been under-investigated. The aim of the present study was to develop a novel multiscale agent-based modelling framework of ISR following DES implantation. METHODS: The framework consisted of two bi-directionally coupled modules, namely (i) a drug transport module, simulating drug transport through a continuum-based approach, and (ii) a tissue remodelling module, simulating cellular dynamics through an ABM. Receptor saturation (RS), defined as the fraction of target receptors saturated with drug, is used to mediate cellular activities in the ABM, since RS is widely regarded as a measure of drug efficacy. Three studies were performed to investigate different scenarios in terms of drug mass (DM), drug release profiles (RP), coupling schemes and idealized vs. patient-specific artery geometries. RESULTS: The studies demonstrated the versatility of the framework and enabled exploration of the sensitivity to different settings, coupling modalities and geometries. As expected, changes in the DM, RP and coupling schemes illustrated a variation in RS over time, in turn affecting the ABM response. For example, combined small DM - fast RP led to similar ISR degrees as high DM - moderate RP (lumen area reduction of ∼13/17% vs. ∼30% without drug). The use of a patient-specific geometry with non-equally distributed struts resulted in a heterogeneous RS map, but did not remarkably impact the ABM response. CONCLUSION: The application to a patient-specific geometry highlights the potential of the framework to address complex realistic scenarios and lays the foundations for future research, including calibration and validation on patient datasets and the investigation of the effects of different plaque composition on the arterial response to DES.

Utilizing numerical simulations to prevent stent graft kinking during thoracic endovascular aortic repair.

Numerical simulations of thoracic endovascular aortic repair (TEVAR) may be implemented in the preoperative workflow if credible and reliable. We present the application of a TEVAR simulation methodology to an 82-year-old woman with a penetrating atherosclerotic ulcer in the left hemiarch, that underwent a left common carotid artery to left subclavian artery bypass and consequent TEVAR in zone 2. During the intervention, kinking of the distal thoracic stent graft occurred and the simulation was able to reproduce this event. This report highlights the potential and reliability of TEVAR simulations to predict perioperative adverse events and short-term postoperative technical results.

Thoracic Stent Graft Numerical Models To Virtually Simulate Thoracic Endovascular Aortic Repair: A Scoping Review.

OBJECTIVE: Pre-procedural planning of thoracic endovascular aortic repair (TEVAR) may implement computational adjuncts to predict technical and clinical outcomes. The aim of this scoping review was to explore the currently available TEVAR procedure and stent graft modelling options. DATA SOURCES: PubMed (MEDLINE), Scopus, and Web of Science were systematically searched (English language, up to 9 December 2022) for studies presenting a virtual thoracic stent graft model or TEVAR simulation. REVIEW METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) was followed. Qualitative and quantitative data were extracted, compared, grouped, and described. Quality assessment was performed using a 16 item rating rubric. RESULTS: Fourteen studies were included. Among the currently available in silico simulations of TEVAR, severe heterogeneity exists in study characteristics, methodological details, and evaluated outcomes. Ten studies (71.4%) were published during the last five years. Eleven studies (78.6%) included heterogeneous clinical data to reconstruct patient specific aortic anatomy and disease (e.g., type B aortic dissection, thoracic aortic aneurysm) from computed tomography angiography imaging. Three studies (21.4%) constructed idealised aortic models with literature input. The applied numerical methods consisted of computational fluid dynamics analysing aortic haemodynamics in three studies (21.4%) and finite element analysis analysing structural mechanics in the others (78.6%), including or excluding aortic wall mechanical properties. The thoracic stent graft was modelled as two separate components (e.g., graft, nitinol) in 10 studies (71.4%), as a one component homogenised approximation (n = 3, 21.4%), or including nitinol rings only (n = 1, 7.1%). Other simulation components included the catheter for virtual TEVAR deployment and numerous outcomes (e.g., Von Mises stresses, stent graft apposition, drag forces) were evaluated. CONCLUSION: This scoping review identified 14 severely heterogeneous TEVAR simulation models, mostly of intermediate quality. The review concludes there is a need for continuous collaborative efforts to improve the homogeneity, credibility, and reliability of TEVAR simulations.

Predicting 1-year in-stent restenosis in superficial femoral arteries through multiscale computational modelling.

In-stent restenosis in superficial femoral arteries (SFAs) is a complex, multi-factorial and multiscale vascular adaptation process whose thorough understanding is still lacking. Multiscale computational agent-based modelling has recently emerged as a promising approach to decipher mechanobiological mechanisms driving the arterial response to the endovascular intervention. However, the long-term arterial response has never been investigated with this approach, although being of fundamental relevance. In this context, this study investigates the 1-year post-operative arterial wall remodelling in three patient-specific stented SFA lesions through a fully coupled multiscale agent-based modelling framework. The framework integrates the effects of local haemodynamics and monocyte gene expression data on cellular dynamics through a bi-directional coupling of computational fluid dynamics simulations with an agent-based model of cellular activities. The framework was calibrated on the follow-up data at 1 month and 6 months of one stented SFA lesion and then applied to the other two lesions. The calibrated framework successfully captured (i) the high lumen area reduction occurring within the first post-operative month and (ii) the stabilization of the median lumen area from 1-month to 1-year follow-ups in all the stented lesions, demonstrating the potentialities of the proposed approach for investigating patient-specific short- and long-term responses to endovascular interventions.

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.

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.

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.

Coronary artery plaque rupture and erosion: Role of wall shear stress profiling and biological patterns in acute coronary syndromes.

AIMS: Wall shear stress (WSS) is involved in coronary artery plaque pathological mechanisms and modulation of gene expression. This study aims to provide a comprehensive haemodynamic and biological description of unstable (intact-fibrous-cap, IFC, and ruptured-fibrous-cap, RFC) and stable (chronic coronary syndrome, CCS) plaques and investigate any correlation between WSS and molecular pathways. METHODS AND RESULTS: We enrolled 24 CCS and 25 Non-ST Elevation Myocardial Infarction-ACS patients with IFC (n = 11) and RFC (n = 14) culprit lesions according to optical coherence tomography analysis. A real-time PCR primer array was performed on peripheral blood mononuclear cells for 17 different molecules whose expression is linked to WSS. Computational fluid dynamics simulations were performed in high-fidelity 3D-coronary artery anatomical models for three patients per group. A total of nine genes were significantly overexpressed in the unstable patients as compared to CCS patients, with no differences between IFC and RFC groups (GPX1, MMP1, MMP9, NOS3, PLA2G7, PI16, SOD1, TIMP1, and TFRC) while four displayed different levels between IFC and RFC groups (TNFα, ADAMTS13, EDN1, and LGALS8). A significantly higher WSS was observed in the RFC group (p < 0.001) compared to the two other groups. A significant correlation was observed between TNFα (p < 0.001), EDN1 (p = 0.036), and MMP9 (p = 0.005) and WSS values in the RFC group. CONCLUSIONS: Our data demonstrate that IFC and RFC plaques are subject to different WSS conditions and gene expressions, suggesting that WSS profiling may play an essential role in the plaque instability characterization with relevant diagnostic and therapeutic implications in the era of precision medicine.

Applicability assessment for in-silico patient-specific TEVAR procedures.

Thoracic Endovascular Aortic Repair (TEVAR) is a minimally invasive technique to treat thoracic aorta pathologies and consists of placing a self-expandable stent-graft into the pathological region to restore the vessel lumen and recreate a more physiological condition. Exhaustive computational models, namely the finite element analysis, can be implemented to reproduce the clinical procedure. In this context, numerical models, if used for clinical applications, must be reliable and the simulation credibility should be proved to predict clinical procedure outcomes or to build in-silico clinical trials. This work aims first at applying a previously validated TEVAR methodology to a patient-specific case. Then, defining the TEVAR procedure performed on a patient population as the context of use, the overall applicability of the TEVAR modeling is assessed to demonstrate the reliability of the model itself following a step-by-step method based on the ASME V&V40 protocol. Validation evidence sources are identified for the specific context of use and adopted to demonstrate the applicability of the numerical procedure, thereby answering a question of interest that evaluates the deployed stent-graft configuration in the vessel.

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.

Multiscale agent-based modeling of restenosis after percutaneous transluminal angioplasty: Effects of tissue damage and hemodynamics on cellular activity.

BACKGROUND: Restenosis following percutaneous transluminal angioplasty (PTA) in femoral arteries is a major cause of failure of the revascularization procedure. The arterial wall response to PTA is driven by multifactorial, multiscale processes, whose complete understanding is lacking. Multiscale agent-based modeling frameworks, simulating the network of mechanobiological events at cell-tissue scale, can contribute to decipher the pathological pathways of restenosis. In this context, the present study proposes a fully-automated multiscale agent-based modeling framework simulating the arterial wall remodeling due to the wall damage provoked by PTA and to the altered hemodynamics in the post-operative months. METHODS: The framework, applied to an idealized femoral artery model, integrated: (i) a PTA module (i.e., structural mechanics simulation), computing the post-PTA arterial morphology and the PTA-induced damage (ii) a hemodynamics module (i.e., computational fluid dynamics simulations), quantifying the near-wall hemodynamics, and (iii) a tissue remodeling module simulating cellular activities through an agent-based model. RESULTS: The framework was able to capture relevant features of the 3-month arterial wall response to PTA, namely (i) the impact of the PTA-induced damage and altered hemodynamics on arterial wall remodeling, including the local intimal growth at the most susceptible regions (i.e., elevated damage levels and low wall shear stress), (ii) the lumen area temporal trend resulting from the interaction of the two inputs, and (iii) a 3-month lumen area restenosis of ∼25%, in accordance with clinical evidence. CONCLUSIONS: The overall results demonstrated the framework potentiality in capturing mechanobiological processes underlying restenosis, thus fostering future application to patient-specific scenarios.

Validation and Verification of High-Fidelity Simulations of Thoracic Stent-Graft Implantation.

Thoracic Endovascular Aortic Repair (TEVAR) is the preferred treatment option for thoracic aortic pathologies and consists of inserting a self-expandable stent-graft into the pathological region to restore the lumen. Computational models play a significant role in procedural planning and must be reliable. For this reason, in this work, high-fidelity Finite Element (FE) simulations are developed to model thoracic stent-grafts. Experimental crimp/release tests are performed to calibrate stent-grafts material parameters. Stent pre-stress is included in the stent-graft model. A new methodology for replicating device insertion and deployment with explicit FE simulations is proposed. To validate this simulation, the stent-graft is experimentally released into a 3D rigid aortic phantom with physiological anatomy and inspected in a computed tomography (CT) scan at different time points during deployment with an ad-hoc set-up. A verification analysis of the adopted modeling features compared to the literature is performed. With the proposed methodology the error with respect to the CT is on average 0.92 ± 0.64%, while it is higher when literature models are adopted (on average 4.77 ± 1.83%). The presented FE tool is versatile and customizable for different commercial devices and applicable to patient-specific analyses.

Patient-specific multi-scale design optimization of transcatheter aortic valve stents.

BACKGROUND AND OBJECTIVE: Transcatheter aortic valve implantation (TAVI) has become the standard treatment for a wide range of patients with aortic stenosis. Although some of the TAVI post-operative complications are addressed in newer designs, other complications and lack of long-term and durability data on the performance of these prostheses are limiting this procedure from becoming the standard for heart valve replacements. The design optimization of these devices with the finite element and optimization techniques can help increase their performance quality and reduce the risk of malfunctioning. Most performance metrics of these prostheses are morphology-dependent, and the design and the selection of the device before implantation should be planned for each individual patient. METHODS: In this study, a patient-specific aortic root geometry was utilized for the crimping and implantation simulation of 50 stent samples. The results of simulations were then evaluated and used for developing regression models. The strut width and thickness, the number of cells and patterns, the size of stent cells, and the diameter profile of the stent were optimized with two sets of optimization processes. The objective functions included the maximum crimping strain, radial strength, anchorage area, and the eccentricity of the stent. RESULTS: The optimization process was successful in finding optimal models with up to 40% decrease in the maximum crimping strain, 261% increase in the radial strength, 67% reduction in the eccentricity, and about an eightfold increase in the anchorage area compared to the reference device. CONCLUSIONS: The stents with larger distal diameters perform better in the selected objective functions. They provide better anchorage in the aortic root resulting in a smaller gap between the device and the surrounding tissue and smaller contact pressure. This framework can be used in designing patient-specific stents and improving the performance of these devices and the outcome of the implantation process.