Journal articles

The breakup of intravascular microbubbles and its impact on the endothelium

Encapsulated microbubbles (MBs) serve as endovascular agents in a wide range of medical ultrasound applications. The oscillatory response of these agents to ultrasonic excitation is determined by MB size, gas content, viscoelastic shell properties and geometrical constraints. The viscoelastic parameters of the MB capsule vary during an oscillation cycle and change irreversibly upon shell rupture. The latter results in marked stress changes on the endothelium of capillary blood vessels due to altered MB dynamics. Mechanical effects on microvessels are crucial for safety and efficacy in applications such as focused ultrasound-mediated blood–brain barrier (BBB) opening. Since direct in vivo quantification of vascular stresses is currently not achievable, computational modelling has established itself as an alternative. We have developed a novel computational framework combining fluid–structure coupling and interface tracking to model the nonlinear dynamics of an encapsulated MB in constrained environments. This framework is used to investigate the mechanical stresses at the endothelium resulting from MB shell rupture in three microvessel setups of increasing levels of geometric detail. All configurations predict substantial elevation of up to 150 % for peak wall shear stress upon MB breakup, whereas global peak transmural pressure levels remain unaltered. The presence of red blood cells causes confinement of pressure and shear gradients to the proximity of the MB, and the introduction of endothelial texture creates local modulations of shear stress levels. With regard to safety assessments, the mechanical impact of MB breakup is shown to be more important than taking into account individual red blood cells and endothelial texture. The latter two may prove to be relevant to the actual, complex process of BBB opening induced by MB oscillations.

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W. Wiedemair, Z. Tukovic, H. Jasak, D. Poulikakos, V. Kurtcuoglu, Biomechanics and Modeling in Mechanobiology, 16(2), 611 - 624 (2017). doi: 10.1007/s10237-016-0840-z