Applicability analysis to evaluate credibility of an in silico thrombectomy procedure

Developing and Validating a Model of Humeral Stem Primary Stability, Intended for In Silico Clinical Trials

In silico clinical trials (ISCT) can contribute to demonstrating a device's performance via credible computational models applied on virtual cohorts. Our purpose was to establish the credibility of a model for assessing the risk of humeral stem loosening in total shoulder arthroplasty, based on a twofold validation scheme involving both benchtop and clinical validation activities, for ISCT applications. A finite element model computing bone-implant micromotion (benchtop model) was quantitatively compared to a bone foam micromotion test (benchtop comparator) to ensure that the physics of the system was captured correctly. The model was expanded to a population-based approach (clinical model) and qualitatively evaluated based on its ability to replicate findings from a published clinical study (clinical comparator), namely that grit-blasted stems are at a significantly higher risk of loosening than porous-coated stems, to ensure that clinical performance of the stem can be predicted appropriately. Model form sensitivities pertaining to surgical variation and implant design were evaluated. The model replicated benchtop micromotion measurements (52.1 ± 4.3 µm), without a significant impact of the press-fit ("Press-fit": 54.0 ± 8.5 µm, "No press-fit": 56.0 ± 12.0 µm). Applied to a virtual population, the grit-blasted stems (227 ± 78µm) experienced significantly larger micromotions than porous-coated stems (162 ± 69µm), in accordance with the findings of the clinical comparator. This work provides a concrete example for evaluating the credibility of an ISCT study. By validating the modeling approach against both benchtop and clinical data, model credibility is established for an ISCT application aiming to enrich clinical data in a regulatory submission.

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.

Credibility assessment of computational models according to ASME V&V40: Application to the Bologna Biomechanical Computed Tomography solution

BACKGROUND AND OBJECTIVE

When a computational model aims to be adopted beyond research purposes, e.g. to inform a clinical or regulatory decision, trust must be placed in its predictive accuracy. This practically translates into the need to demonstrate its credibility. In fact, prior to its adoption for regulatory purposes, an in silico methodology should be proven credible enough for the scope. This has become especially relevant as, although evidence of the safety and efficacy of new medical products or interventions has been traditionally provided to the regulator experimentally, i.e., in vivo or ex vivo, recently the idea to inform a regulatory decision in silico has made its way in the regulatory scenario. While a harmonised technical standard is currently missing in the EU regulatory system, in 2018 the ASME issued V&V40-2018, where a risk-based framework to assess the credibility of a computational model through the performance of predefined credibility activities is provided. The credibility framework is here applied to Bologna Biomechanical Computed Tomography (BBCT) solution, which predicts the absolute risk of fracture at the femur for a subject. BBCT has recently been the object of a qualification advice request to the European Medicine Agency.

METHODS

The full implementation of ASME V&V40-2018 framework on BBCT is shown. Starting from BBCT proposed context of use the whole credibility plan is presented and the credibility activities (Verification, Validation, Applicability) described together with the achieved credibility levels.

RESULTS

BBCT risk is judged medium, and the credibility levels achieved considered acceptable. The uncertainties intrinsically present in the material properties assignment affected BBCT predictions to the highest extent.

CONCLUSIONS

This work provides the practical application of the ASME V&V40-2018 risk-based credibility assessment framework, which could be applied to demonstrate model credibility in any field and support future regulatory submissions and foster the adoption of In Silico Trials.

Recommendations for finite element modelling of nickel-titanium stents-Verification and validation activities

The objective of this study is to present a credibility assessment of finite element modelling of self-expanding nickel-titanium (Ni-Ti) stents through verification and validation (VV) activities, as set out in the ASME VV-40 standard. As part of the study, the role of calculation verification, model input sensitivity, and model validation is examined across three different application contexts (radial compression, stent deployment in a vessel, fatigue estimation). A commercially available self-expanding Ni-Ti stent was modelled, and calculation verification activities addressed the effects of mesh density, element integration and stable time increment on different quantities of interests, for each context of use considered. Sensitivity analysis of the geometrical and material input parameters and validation of deployment configuration with in vitro comparators were investigated. Results showed similar trends for global and local outputs across the contexts of use in response to the selection of discretization parameters, although with varying sensitivities. Mesh discretisation showed substantial variability for less than 4 × 4 element density across the strut cross-section in radial compression and deployment cases, while a finer grid was deemed necessary in fatigue estimation for reliable predictions of strain/stress. Element formulation also led to substantial variation depending on the chosen integration options. Furthermore, for explicit analyses, model results were highly sensitive to the chosen target time increment (e.g., mass scaling parameters), irrespective of whether quasistatic conditions were ensured (ratios of kinetic and internal energies below 5%). The higher variability was found for fatigue life simulation, with the estimation of fatigue safety factor varying up to an order of magnitude depending on the selection of discretization parameters. Model input sensitivity analysis highlighted that the predictions of outputs such as radial force and stresses showed relatively low sensitivity to Ni-Ti material parameters, which suggests that the calibration approaches used in the literature to date appear reasonable, but a higher sensitivity to stent geometry, namely strut thickness and width, was found. In contrast, the prediction of vessel diameter following deployment was least sensitive to numerical parameters, and its validation with in vitro comparators offered a simple and accurate (error ~ 1-2%) method when predicting diameter gain, and lumen area, provided that the material of the vessel is appropriately characterized and modelled.

Investigation of Cerebral Hemodynamics During Endovascular Aspiration: Development of an Experimental and Numerical Setup

PURPOSE

Acute ischemic stroke is a life-threatening emergency caused by an occlusion of a cerebral artery through a blood clot. Aspiration thrombectomy is an endovascular therapy for the removal of vessel occlusions. However, open questions regarding the hemodynamics during the intervention remain, motivating investigations of blood flow within cerebral arteries. In this study, we present a combined experimental and numerical approach to analyze hemodynamics during endovascular aspiration.

METHODS

We have developed an in vitro setup for investigations of hemodynamic changes during endovascular aspiration within a compliant model of patient-specific cerebral arteries. Pressures, flows, and locally resolved velocities were obtained. In addition, we established a computational fluid dynamics (CFD) model and compared the simulations during physiological conditions and in two aspiration scenarios with different occlusions.

RESULTS

Flow redistribution within cerebral arteries after ischemic stroke is strongly dependent on the severity of the occlusion and on the volume flow extracted by endovascular aspiration. Numerical simulations exhibit an excellent correlation of R = 0.92 for flow rates and a good correlation of R = 0.73 for pressures. Further on, the local velocity field inside the basilar artery had a good agreement between CFD model and particle image velocimetry (PIV) data.

CONCLUSION

The presented setup allows for in vitro investigations of artery occlusions and endovascular aspiration techniques on arbitrary patient-specific cerebrovascular anatomies. The in silico model provides consistent predictions of flows and pressures in several aspiration scenarios.

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.

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.

Preclinical modeling of mechanical thrombectomy

Mechanical thrombectomy to treat large vessel occlusions (LVO) causing a stroke is one of the most effective treatments in medicine, with a number needed to treat to improve clinical outcomes as low as 2.6. As the name implies, it is a mechanical solution to a blocked artery and modeling these mechanics preclinically for device design, regulatory clearance and high-fidelity physician training made clinical applications possible. In vitro simulation of LVO is extensively used to characterize device performance in representative vascular anatomies with physiologically accurate hemodynamics. Embolus analogues, validated against clots extracted from patients, provide a realistic simulated use experience. In vitro experimentation produces quantitative results such as particle analysis of distal emboli generated during the procedure, as well as pressure and flow throughout the experiment. Animal modeling, used mostly for regulatory review, allows estimation of device safety. Other than one recent development, nearly all animal modeling does not incorporate the desired target organ, the brain, but rather is performed in the extracranial circulation. Computational modeling of the procedure remains at the earliest stages but represents an enormous opportunity to rapidly characterize and iterate new thrombectomy concepts as well as optimize procedure workflow. No preclinical model is a perfect surrogate; however, models available can answer important questions during device development and have to date been successful in delivering efficacious and safe devices producing excellent clinical outcomes. This review reflects on the developments of preclinical modeling of mechanical thrombectomy with particular focus on clinical translation, as well as articulate existing gaps requiring additional research.

Realistic computer modelling of stent retriever thrombectomy: a hybrid finite-element analysis-smoothed particle hydrodynamics model

Stent retriever thrombectomy is a pre-eminent treatment modality for large vessel ischaemic stroke. Simulation of thrombectomy could help understand stent and clot mechanics in failed cases and provide a digital testbed for the development of new, safer devices. Here, we present a novel, in silico thrombectomy method using a hybrid finite-element analysis (FEA) and smoothed particle hydrodynamics (SPH). Inspired by its biological structure and components, the blood clot was modelled with the hybrid FEA-SPH method. The Solitaire self-expanding stent was parametrically reconstructed from micro-CT imaging and was modelled as three-dimensional finite beam elements. Our simulation encompassed all steps of mechanical thrombectomy, including stent packaging, delivery and self-expansion into the clot, and clot extraction. To test the feasibility of our method, we simulated clot extraction in simple straight vessels. This was compared against in vitro thrombectomies using the same stent, vessel geometry, and clot size and composition. Comparisons with benchtop tests indicated that our model was able to accurately simulate clot deflection and penetration of stent wires into the clot, the relative movement of the clot and stent during extraction, and clot fragmentation/embolus formation. In this study, we demonstrated that coupling FEA and SPH techniques could realistically model stent retriever thrombectomy.

Multiscale Computational Modeling of Vascular Adaptation: A Systems Biology Approach Using Agent-Based Models

The widespread incidence of cardiovascular diseases and associated mortality and morbidity, along with the advent of powerful computational resources, have fostered an extensive research in computational modeling of vascular pathophysiology field and promoted in-silico models as a support for biomedical research. Given the multiscale nature of biological systems, the integration of phenomena at different spatial and temporal scales has emerged to be essential in capturing mechanobiological mechanisms underlying vascular adaptation processes. In this regard, agent-based models have demonstrated to successfully embed the systems biology principles and capture the emergent behavior of cellular systems under different pathophysiological conditions. Furthermore, through their modular structure, agent-based models are suitable to be integrated with continuum-based models within a multiscale framework that can link the molecular pathways to the cell and tissue levels. This can allow improving existing therapies and/or developing new therapeutic strategies. The present review examines the multiscale computational frameworks of vascular adaptation with an emphasis on the integration of agent-based approaches with continuum models to describe vascular pathophysiology in a systems biology perspective. The state-of-the-art highlights the current gaps and limitations in the field, thus shedding light on new areas to be explored that may become the future research focus. The inclusion of molecular intracellular pathways (e.g., genomics or proteomics) within the multiscale agent-based modeling frameworks will certainly provide a great contribution to the promising personalized medicine. Efforts will be also needed to address the challenges encountered for the verification, uncertainty quantification, calibration and validation of these multiscale frameworks.

In silico trials for treatment of acute ischemic stroke: Design and implementation

An in silico trial simulates a disease and its corresponding therapies on a cohort of virtual patients to support the development and evaluation of medical devices, drugs, and treatment. In silico trials have the potential to refine, reduce cost, and partially replace current in vivo studies, namely clinical trials and animal testing. We present the design and implementation of an in silico trial for treatment of acute ischemic stroke. We propose an event-based modelling approach for the simulation of a disease and injury, where changes to the state of the system (the events) are assumed to be instantaneous. Using this approach we are able to combine a diverse set of models, spanning multiple time scales, to model acute ischemic stroke, treatment, and resulting brain tissue injury. The in silico trial is designed to be modular to aid development and reproducibility. It provides a comprehensive framework for application to any potential in silico trial. A statistical population model is used to generate cohorts of virtual patients. Patient functional outcomes are also predicted with a statistical model, using treatment and injury results and the patient's clinical parameters. We demonstrate the functionality of the event-based modelling approach and trial framework by running proof of concept in silico trials. The proof of concept trials simulate the same cohort of patients twice: once with successful treatment (successful recanalisation) and once with unsuccessful treatment (unsuccessful treatment). Ways to overcome some of the challenges and difficulties in setting up such an in silico trial are discussed, such as validation and computational limitations.

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.