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Microscale quantification of cilia-driven fluid flow is an emerging area in medical physiology, including pulmonary and central nervous system physiology. Cilia-driven fluid flow is most completely described by a three-dimensional, three-component (3D3C) vector field. Here, we generate 3D3C velocimetry measurements by synthesizing higher dimensional data from lower dimensional measurements obtained using two separate optical coherence tomography (OCT)-based approaches: digital particle image velocimetry (DPIV) and dynamic light scattering (DLS)-OCT. Building on previous work, we first demonstrate directional DLS-OCT for 1D2C velocimetry measurements in the sub-1 mm/s regime (sub-2.5 inch/minute regime) of cilia-driven fluid flow in Xenopus epithelium, an important animal model of the ciliated respiratory tract. We then extend our analysis toward 3D3C measurements in Xenopus using both DLS-OCT and DPIV. We demonstrate the use of DPIV-based approaches towards flow imaging of Xenopus cerebrospinal fluid and mouse trachea, two other important ciliary systems. Both of these flows typically fall in the sub-100 μm/s regime (sub-0.25 inch/minute regime). Lastly, we develop a framework for optimizing the signal-to-noise ratio of 3D3C flow velocity measurements synthesized from 2D2C measures in non-orthogonal planes. In all, 3D3C OCT-based velocimetry has the potential to comprehensively characterize the flow performance of biological ciliated surfaces.
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