Novel Elastography-Inspired Approach to Angiographic Visualization in Optical Coherence Tomography

Abstract

In this paper, we present a new approach to contrast-agent-free angiographic visualization in optical coherence tomography (OCT). The proposed approach has much in common with imaging of local interframe strains in OCT-based elastography and utilizes the fact that the interframe motion of blood particles leads to discontinuity of strains within the vessel cross section. By this reasoning, we call this approach “elastography-inspired”. Here, we first elucidate the essence and main features of the elastography-inspired approach using numerical simulation of OCT data. The simulations allow one to introduce both moving scatterers imitating blood flow in vessels as well as various masking motions imitating natural motions of living “solid” tissue surrounding the vessels. Second, using real OCT signals, we present comparative results of angiographic processing using the proposed elastography-inspired approach and a realization of OCA based on high-pass filtering of temporal variability of a series of OCT B-scans. The two methods can use the same initial dataset and the high-pass filtering OCA has already been routinely applied in both animal experiments and on patients. The new elastography-inspired method has a similar computational efficiency, and it is intrinsically able to compensate spatially-inhomogeneous masking tissue motions and demonstrates high robustness with respect to motion artefacts. Thus, the new approach looks very promising for enabling wider application of OCA in both laboratory studies on animals and, most importantly, for wider clinical applications on patients.

Real-Time Nondestructive Viscosity Measurement of Soft Tissue Based on Viscoelastic Response Optical Coherence Elastography

“…They then used the method to evaluate the nonlinear properties of breast tissue and the Young's modulus to improve the accuracy of tumor diagnosis [6]. Zykov et al [7] proposed an OCE method to detect vascular networks. These methods are static-prone methods, that is, they are more suitable for measuring static elastic properties of the tissue.…”