Optical coherence angiography (OCA) enables visualisation of three-dimensional micro-vasculature from optical coherence tomography data volumes. Typically, various statistical methods are used to discriminate static tissue from blood flow within vessels. In this paper, we introduce a new method that relies upon the beating heart frequency to isolate blood vessels from the surrounding tissue. Vascular blood flow is assumed to be more strongly modulated by the heart-beat compared to surrounding tissue and therefore short-time Fourier transform of sequential measurements can discriminate the two. Furthermore, it is demonstrated that adjacent B-Scans within an OCT data volume can provide the required sampling frequency. As such, the technique can be considered to be a spatially mapped variation of photoplethysmography (PPG), whereby each image voxel operates as a PPG detector. This principle is demonstrated using both a model system and in vivo for monitoring the vascular changes effected by traumatic brain injury in mice. In vivo measurements were acquired at an A-Scan rate of 10kHz to form a 500x500x512 (lateral x lateral x axial) pixel volume, enabling sequential sampling of the mouse heart rate in an expected range of 300-600 bpm. One of the advantages of this new OCA processing method is that it can be used in conjunction with existing algorithms as an additional filter for signal to noise enhancement.
Karl Alvarez, Jordi Lopez-Tremoleda, Rob Donnan, Adina T. Michael-Titus, and Peter H. Tomlins, "Heart rate sensitive optical coherence angiography," Proc. SPIE 10493, Dynamics and Fluctuations in Biomedical Photonics XV, 104930G (Presented at SPIE BiOS: January 29, 2018; Published: 13 February 2018); https://doi.org/10.1117/12.2317602.
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