Phase-resolved Doppler optical coherence tomography has been used to image blood flow dynamics in various tissues using both time-domain and spectral-domain optical coherence tomography techniques. In this manuscript, we present phase-resolved Doppler imaging with a high-speed optical frequency domain imaging system. We demonstrate that by correcting for spurious timing-induced phase errors, excellent flow sensitivity can be achieved, limited only by the imaging signal-to-noise ratio. Conventional and Doppler images showing flow in an Intralipid phantom and in human skin are presented. Additionally, we demonstrate the ability of phase-resolved OFDI to measure high flow rates without the deleterious effects of fringe washout.

Directin vivoimaging of lymph flow is key to understanding lymphatic system function in normal and disease states. Optical microscopy techniques provide the resolution required for these measurements, but existing optical techniques for measuring lymph flow require complex protocols and provide limited temporal resolution. Here, we describe a Doppler optical coherence tomography platform that allows direct, label-free quantification of lymph velocity and volumetric flow rates. We overcome the challenge of very low scattering by employing a Doppler algorithm that operates on low signal-to-noise measurements. We show that this technique can measure lymph velocity at sufficiently high temporal resolution to resolve the dynamic pulsatile flow in collecting lymphatic vessels.

© 2006 Optical Society of America

Decorrelation noise limits the ability of phase-resolved Doppler optical coherence tomography systems to detect smaller vessels exhibiting slower flow velocities, which limits the utility of the technique in many clinical and biological settings. An understanding of the statistical properties of decorrelation noise can aid in the optimal design of these systems and guide the development of noise mitigating strategies. In this work, the statistical properties of decorrelation noise are derived from the underlying statistics of the coherent imaging system and validated through comparison with empirical results and Monte Carlo modeling. Expressions for the noise distribution and the noise variance as a function of relevant imaging system parameters are given, and the implications of these results on both system and algorithm design are discussed.