ArticleAnnals of biomedical engineering2021
Multimodal Loading Environment Predicts Bioresorbable Vascular Scaffolds' Durability.
Article in Annals of biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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7 authors.
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Abstract
Bioresorbable vascular scaffolds were considered the fourth generation of endovascular implants deemed to revolutionize cardiovascular interventions. Yet, unexpected high risk of scaffold thrombosis and post-procedural myocardial infractions quenched the early enthusiasm and highlighted the gap between benchtop predictions and clinical observations. To better understand scaffold behavior in the mechanical environment of vessels, animal, and benchtop tests with multimodal loading environment were conducted using industrial standard scaffolds. Finite element analysis was also performed to study the relationship among structural failure, scaffold design, and load types. We identified that applying the combination of bending, axial compression, and torsion better reflects incidence observed in-vivo, far more than tranditional single mode loads. Predication of fracture locations is also more accurate when at least bending and axial compression are applied during benchtop tests (>60% fractures at connected peak). These structural failures may be initiated by implantation-induced microstructural damages and worsened by cyclic loads from the beating heart. Ignoring the multi-modal loading environment in benchtop fatigue tests and computational platforms can lead to undetected potential design defects, calling for redefining consensus evaluation strategies for scaffold performance. With the robust evaluation strategy presented herein, which exploits the results of in-vivo, in-vitro and in-silico investigations, we may be able to compare alternative designs of prototypes at the early stages of device development and optimize the performance of endovascular implants according to patients-specific vessel dynamics and lesion configurations in the future.
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