Real-time imaging of nanobubble ultrasound contrast agent flow, extravasation, and diffusion through an extracellular matrix using a microfluidic model.
Michaela B CooleyWilliam J WulftangeDana WegierakUtku GorekeEric Chua AbenojarUmut A GurkanAgata A ExnerPublished in: Lab on a chip (2023)
Lipid shell-stabilized nanoparticles with a perfluorocarbon gas-core, or nanobubbles, have recently attracted attention as a new contrast agent for molecular ultrasound imaging and image-guided therapy. Due to their small size (∼275 nm diameter) and flexible shell, nanobubbles have been shown to extravasate through hyperpermeable vasculature ( e.g. , in tumors). However, little is known about the dynamics and depth of extravasation of intact, acoustically active nanobubbles. Accordingly, in this work, we developed a microfluidic chip with a lumen and extracellular matrix (ECM) and imaging method that allows real-time imaging and characterization of the extravasation process with high-frequency ultrasound. The microfluidic device has a lumen and is surrounded by an extracellular matrix with tunable porosity. The combination of ultrasound imaging and the microfluidic chip advantageously produces real-time images of the entire length and depth of the matrix. This captures the matrix heterogeneity, offering advantages over other imaging techniques with smaller fields of view. Results from this study show that nanobubbles diffuse through a 1.3 μm pore size (2 mg mL -1 ) collagen I matrix 25× faster with a penetration depth that was 0.19 mm deeper than a 3.7 μm (4 mg mL -1 ) matrix. In the 3.7 μm pore size matrix, nanobubbles diffused 92× faster than large nanobubbles (∼875 nm diameter). Decorrelation time analysis was successfully used to differentiate flowing and extra-luminally diffusing nanobubbles. In this work, we show for the first time that combination of an ultrasound-capable microfluidic chip and real-time imaging provided valuable insight into spatiotemporal nanoparticle movement through a heterogeneous extracellular matrix. This work could help accurately predict parameters ( e.g. , injection dosage) that improve translation of nanoparticles from in vitro to in vivo environments.
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