The radial dynamics and acoustic emissions of phase-shift droplets are impacted by mechanical properties of tissue-mimicking hydrogels.

Acoustic droplet vaporization (ADV) offers a dynamic approach for generating bubbles on demand, presenting new possibilities in biomedical applications. Although ADV has been investigated in various biomedical applications, its potential in tissue characterization remains unexplored. Here, we investigated the effects of surrounding media on the radial dynamics and acoustic emissions of ADV bubbles using theoretical and experimental methodologies. For theoretical studies, bubble dynamics were combined with the Kelvin-Voigt material constitutive model, accounting for viscoelasticity of the media. The radial dynamics and acoustic emissions of the ADV-bubbles were recorded via ultra-high-speed microscopy and passive cavitation detection, respectively. Perfluoropentane phase-shift droplets were embedded in tissue-mimicking hydrogels of varying fibrin concentrations, representing different elastic moduli. Radial dynamics and the acoustic emissions, both temporal and spectral, of the ADV-bubbles depended significantly on fibrin elastic modulus. For example, an increase in fibrin elastic modulus from ≈0.2 kPa to ≈6 kPa reduced the maximum expansion radius of the ADV-bubbles by 50%. A similar increase in the elastic modulus significantly impacted both linear (e.g., fundamental) and nonlinear (e.g., subharmonic) acoustic responses of the ADV-bubbles, by up to 10 dB. The sensitivity of ADV to the surrounding media was dependent on acoustic parameters such as driving pressure and the droplets concentration. Further analysis of the acoustic emissions revealed distinct ADV signal characteristics, which were significantly influenced by the surrounding media.

Ultra-high-speed dynamics of acoustic droplet vaporization in soft biomaterials: Effects of viscoelasticity, frequency, and bulk boiling point.

Phase-shift droplets are a highly adaptable platform for biomedical applications of ultrasound. The spatiotemporal response of phase-shift droplets to focused ultrasound above a certain pressure threshold, termed acoustic droplet vaporization (ADV), is influenced by intrinsic features (e.g., bulk boiling point) and extrinsic factors (e.g., driving frequency and surrounding media). A deep understanding of ADV dynamics is critical to ensure the robustness and repeatability of an ADV-assisted application. Here, we integrated ultra-high-speed imaging, at 10 million frames per second, and confocal microscopy for a full-scale (i.e., from nanoseconds to seconds) characterization of ADV. Experiments were conducted in fibrin-based hydrogels to mimic soft tissue environments. Effects of fibrin concentration (0.2 to 8 % (w/v)), excitation frequency (1, 2.5, and 9.4 MHz), and perfluorocarbon core (perfluoropentane, perfluorohexane, and perfluorooctane) on ADV dynamics were studied. Several fundamental parameters related to ADV dynamics, such as expansion ratio, expansion velocity, collapse radius, collapse time, radius of secondary rebound, resting radius, and equilibrium radius of the generated bubbles were extracted from the radius vs time curves. Diffusion-driven ADV-bubble growth was fit to a modified Epstein-Plesset equation, adding a material stress term, to estimate the growth rate. Our results indicated that ADV dynamics were significantly impacted by fibrin concentration, frequency, and perfluorocarbon liquid core. This is the first study to combine ultra-high-speed and confocal microscopy techniques to provide insights into ADV bubble dynamics in tissue-mimicking hydrogels.

Real-time spatiotemporal characterization of mechanics and sonoporation of acoustic droplet vaporization in acoustically responsive scaffolds.

Phase-shift droplets provide a flexible and dynamic platform for therapeutic and diagnostic applications of ultrasound. The spatiotemporal response of phase-shift droplets to focused ultrasound, via the mechanism termed acoustic droplet vaporization (ADV), can generate a range of bioeffects. Although ADV has been used widely in theranostic applications, ADV-induced bioeffects are understudied. Here, we integrated ultra-high-speed microscopy, confocal microscopy, and focused ultrasound for real-time visualization of ADV-induced mechanics and sonoporation in fibrin-based, tissue-mimicking hydrogels. Three monodispersed phase-shift droplets-containing perfluoropentane (PFP), perfluorohexane (PFH), or perfluorooctane (PFO)-with an average radius of ∼6 µm were studied. Fibroblasts and tracer particles, co-encapsulated within the hydrogel, were used to quantify sonoporation and mechanics resulting from ADV, respectively. The maximum radial expansion, expansion velocity, induced strain, and displacement of tracer particles were significantly higher in fibrin gels containing PFP droplets compared to PFH or PFO. Additionally, cell membrane permeabilization significantly depended on the distance between the droplet and cell (d), decreasing rapidly with increasing d. Significant membrane permeabilization occurred when d was smaller than the maximum radius of expansion. Both ultra-high-speed and confocal images indicate a hyper-local region of influence by an ADV bubble, which correlated inversely with the bulk boiling point of the phase-shift droplets. The findings provide insight into developing optimal approaches for therapeutic applications of ADV.

Ogden material calibration via magnetic resonance cartography, parameter sensitivity and variational system identification.

Contemporary material characterization techniques that leverage deformation fields and the weak form of the equilibrium equations face challenges in the numerical solution procedure of the inverse characterization problem. As material models and descriptions differ, so too must the approaches for identifying parameters and their corresponding mechanisms. The widely used Ogden material model can be comprised of a chosen number of terms of the same mathematical form, which presents challenges of parsimonious representation, interpretability and stability. Robust techniques for system identification of any material model are important to assess and improve experimental design, in addition to their centrality to forward computations. Using fully three-dimensional displacement fields acquired in silicone elastomers with our recently developed magnetic resonance cartography (MR-u) technique on the order of greater than [Formula: see text], we leverage partial differential equation-constrained optimization as the basis of variational system identification of our material parameters. We incorporate the statistical F-test to maintain parsimony of representation. Using a new, local deformation decomposition locally into mixtures of biaxial and uniaxial tensile states, we evaluate experiments based on an analytical sensitivity metric and discuss the implications for experimental design. This article is part of the theme issue 'The Ogden model of rubber mechanics: Fifty years of impact on nonlinear elasticity'.