Multimodal Loading Environment Predicts Bioresorbable Vascular Scaffolds' Durability

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.

Characterizing viscoelastic mechanical properties of highly compliant polymers and biological tissues using impact indentation

Precise and accurate measurement of viscoelastic mechanical properties becomes increasingly challenging as sample stiffness decreases to elastic moduli <1 kPa, largely due to difficulties detecting initial contact with the compliant sample surface. This limitation is particularly relevant to characterization of biological soft tissues and compliant gels. Here, we employ impact indentation which, in contrast to shear rheology and conventional indentation, does not require contact detection a priori, and present a novel method to extract viscoelastic moduli and relaxation time constants directly from the impact response. We first validate our approach by using both impact indentation and shear rheology to characterize polydimethylsiloxane (PDMS) elastomers of stiffness ranging from 100 s of Pa to nearly 10 kPa. Assuming a linear viscoelastic constitutive model for the material, we find that the moduli and relaxation times obtained from fitting the impact response agree well with those obtained from fitting the rheological response. Next, we demonstrate our validated method on hydrated, biological soft tissues obtained from porcine brain, murine liver, and murine heart, and report the equilibrium shear moduli, instantaneous shear moduli, and relaxation time constants for each tissue. Together, our findings provide a new and straightforward approach capable of probing local mechanical properties of highly compliant viscoelastic materials with millimeter scale spatial resolution, mitigating complications involving contact detection or sample geometric constraints.

STATEMENT OF SIGNIFICANCE

Characterization and optimization of mechanical properties can be essential for the proper function of biomaterials in diverse applications. However, precise and accurate measurement of viscoelastic mechanical properties becomes increasingly difficult with increased compliance (particularly for elastic moduli <1 kPa), largely due to challenges detecting initial contact with the compliant sample surface and measuring response at short timescale or high frequency. By contrast, impact indentation has highly accurate contact detection and can be used to measure short timescale (glassy) response. Here, we demonstrate an experimental and analytical method that confers significant advantages over existing approaches to extract spatially resolved viscoelastic moduli and characteristic time constants of biological tissues (e.g., brain and heart) and engineered biomaterials.