Gradient mapping of multi-timescale optical coherence tomography angiography signals for enhancing signal-to-noise ratio of flow detection

• Published in: Journal of Biomechanical Science and Engineering 2023, Vol.18(2), pp.23-00035-23-00035
• Main Author: NAKAMICHI, Yu
• Format: Article
• Language: English
• Subjects: Angiography; Blood flow; Broadband; Computation; Flow velocity; Imaging techniques; Interferometry; Low coherence interferometry; Mapping; Medical imaging; Microvasculature; Ophthalmology; Optical Coherence Tomography; Optical coherence tomography (OCT); Optical coherence tomography angiography (OCTA); Optical communication; Separation; Signal to noise ratio; Time series; Tissues; Tomography; Velocity
• ISSN: 1880-9863; 1880-9863
• DOI: 10.1299/jbse.23-00035

Optical coherence tomography (OCT) is a three-dimensional imaging technique based on low coherence interferometry of near-infrared broadband light and has been applied to medical diagnoses, such as structural diagnosis of the retina in ophthalmology. For several decades, functional variations of OCT have been also developed. OCT angiography (OCTA) is one of the functional variations of OCT and can visualize blood flows (microvasculature) in biological tissues by analyzing the time-series of OCT signals. Recently, several studies suggested the possibility that OCTA can not only visualize blood flows but also detect the blood flow velocity quantitatively, where the blood flow velocity is estimated by analyzing OCTA signals computed with multiple time separations from the time-series of OCT signals measured at a short time interval. OCTA signals computed with short time separations, however, reduce its contrast between dynamic tissues (blood flows) and other static tissues, resulting in the decrease of signal-to-noise (SN) ratio of the flow detection. This study proposed a novel method to enhance the SN ratio of the flow detection from such OCTA signals computed with short time separations, by means of mapping the gradient of OCTA signals against the time separations. In the experiments, a flow phantom and human skins were employed to compare SN ratios among OCTA with a long time separation (standard OCTA), OCTA with a short time separation, and the proposed method. The results showed that the proposed methods can detect flow signals with a high SN ratio equivalent to that of the standard OCTA and, therefore, suggested that quantitative detection of the flow velocity with OCTA will be possible with a high SN ratio of flow detection.