OCT-based three-dimensional, three vector component imaging of cilia-driven fluid flow for developmental biology (Conference Presentation)

Abstract

One critical barrier to the robust study of cilia-driven fluid flow in developmental biology is a lack of methods for acquiring three-dimensional (3D) images of three vector component (3C) measurements of flow velocities. A 3D3C map of cilia-driven fluid flow quantifies the flow speed along three axes (e.g. three Cartesian vector components v_x, v_y, v_z) at each point in 3D space. 3D3C quantification is important because cilia-driven fluid flow is not amenable to simplifying assumptions (e.g. parabolic flow profile. Such quantification may enable systematically detailed characterization of performance using shear force and power dissipation metrics derived from 3D3C flow velocity fields. We report our OCT-based results in developing methods for the 3D3C quantification of cilia-driven flow fields. First, we used custom scan protocols and reconstruction algorithms to synthesize 3D3C flow velocity fields from 2D2C fields generated using correlation-based methods (directional dynamic light scattering and digital particle image velocimetry). Xenopus results include flow driven by ciliated embryo skin and flow driven by ciliated ependymal cells in developing brain ventricles. Second, we developed a new approach to particle tracking velocimetry that generates 2D2.5C (2.5C: v_x,|v_y|,v_z) velocity fields from single-plane 2D image acquisitions. We demonstrated this particle streak velocimetry method in calibrated flow phantoms and in flow driven by ciliated Xenopus embryo skin. Additionally, we have preliminary results extending particle streak velocimetry to 3D3C in calibrated flow phantoms with ongoing work in Xenopus embryos.