Experimental validation of more realistic computer models for stent‐graft repair of abdominal aortic aneurysms, including pre‐load assessment

Biomech Model Mechanobiol

Kalender

et al. 2019

Non-negligible postinterventional complication rates after endovascular aneurysm repair (EVAR) leave room for further improvements. Since the potential success of EVAR depends on various patientspecific factors, such as the complexity of the vessel geometry and the physiological state of the vessel, in silico models can be a valuable tool in the preinterventional planning phase. A suitable in silico EVAR methodology applied to patient-specific cases can be used to predict stent-graft (SG) related complications, such as SG migration, endoleaks or tissue remodeling-induced aortic neck dilatation, and to improve the selection and sizing process of SGs. In this contribution, we apply an in silico EVAR methodology that predicts the final state of the deployed SG after intervention to three clinical cases. A novel qualitative and quantitative validation methodology, that is based on a comparison between in silico results and postinterventional CT data, is presented. The validation methodology compares average stent diameters pseudo-continuously along the total length of the deployed SG. The validation of the in silico results shows very good agreement proving the potential of using in silico approaches in the preinterven

Section: Strain Energy Functionmentioning

confidence: 99%

Patient-specific in silico endovascular repair of abdominal aortic aneurysms: application and validation

Biomech Model Mechanobiol

Kalender

et al. 2019

“…Hence, numerical modeling of this process is challenging and the methodology how the SG is placed and deployed within the vessel are essential for the efficiency and robustness of the approach. Stent predeformation [72] as well as in vivo non-stress-free vessel geometries [30] require special computational techniques which have to be consistently integrated into the mechanical framework. High complexity of vessel and SG shapes and their large inter-patient variability are further challenges of the presented in silico EVAR methodology.…”

Section: Landing Zonementioning

confidence: 99%

“…Stent predeformation should be considered in an in silico EVAR simulation to be able to compute contact forces between SG and vessel more accurately [72]. We propose a stent predeformation methodology which is based on the alteration of the stress-free reference configuration of the stent after SG assembly.…”

Section: Landing Zonementioning

confidence: 99%

“…Among others, Humphrey and Holzapfel [40], Gasser et al [27], Maier et al [54], Vande Geest et al [76] and Fillinger et al [25] focused on computational models of AAAs mainly to assess the rupture risk. Kleinstreuer et al [46], De Bock et al [15], Demanget et al [20,21] and Roy et al [72] performed experimental and numerical tests on marketed SGs considering the mechanical behavior of stent and graft.…”

Section: Landing Zonementioning

confidence: 99%

“…Perrin et al [65] developed a mechanically sophisticated SG assembling strategy for Anaconda TM SGs (Vascutek, Inchinnan,UK) which considered the predeformed stent configuration. Roy et al [72], who called this effect "stent pre-load", developed a more general rule for Cook Zenith R SGs (Cook Medical, Bloomington, Indiana, USA). They augmented the Young's modulus of the stent by a factor of 2 to consider the effect of stent predeformation.…”

Section: Landing Zonementioning

confidence: 99%

See 2 more Smart Citations

A methodology for in silico endovascular repair of abdominal aortic aneurysms

Biomech Model Mechanobiol

Reeps

et al. 2018

Endovascular aneurysm repair (EVAR) can involve some unfavorable complications such as endoleaks or stent-graft (SG) migration. Such complications, resulting from the complex mechanical interaction of vascular tissue, SG and blood flow or incompatibility of SG design and vessel geometry, are difficult to predict. Computational vascular mechanics models can be a predictive tool for the selection, sizing and placement process of SGs depending on the patient-specific vessel geometry and hence reduce the risk of potential complications after EVAR. In this contribution, we present a new in silico EVAR methodology to predict the final state of the deployed SG after intervention and evaluate the mechanical state of vessel and SG, such as contact forces and wall stresses. A novel method to account for residual strains and stresses in SGs, resulting from the precompression of stents during the assembly process of SGs, is presented. We suggest a parameter continuation approach to model various different sizes of SGs within one in silico EVAR simulation which can be a valuable tool when investigating the issue of SG oversizing. The applicability and robustness of the proposed methods are demonstrated on the example of a synthetic abdominal aortic aneurysm geometry.

In silico study of vessel and stent‐graft parameters on the potential success of endovascular aneurysm repair

Numer Methods Biomed Eng

Reeps

et al. 2019

The variety of stent‐graft (SG) design variables (eg, SG type and degree of SG oversizing) and the complexity of decision making whether a patient is suitable for endovascular aneurysm repair (EVAR) raise the need for the development of predictive tools to assist clinicians in the preinterventional planning phase. Recently, some in silico EVAR methods have been developed to predict the deployed SG configuration. However, only few studies investigated how to assess the in silico EVAR outcome with respect to EVAR complication likelihoods (eg, endoleaks and SG migration). Based on a large literature study, in this contribution, 20 mechanical and geometrical parameters (eg, SG drag force and SG fixation force) are defined to evaluate the quality of the in silico EVAR outcome. For a cohort of n = 146 realizations of parameterized vessel and SG geometries, the in silico EVAR results are studied with respect to these mechanical and geometrical parameters. All degrees of SG oversizing in the range between 5% and 40% are investigated continuously by a computationally efficient parameter continuation approach. The in silico investigations have shown that the mechanical and geometrical parameters are able to indicate candidates at high risk of postinterventional complications. Hence, this study provides the basis for the development of a simulation‐based metric to assess the potential success of EVAR based on engineering parameters.