Statistical analysis of motion contrast in optical coherence tomography angiography

TL;DR

This paper develops a mathematical model for motion contrast in optical coherence tomography angiography, explaining its origin and guiding improvements in system design and image analysis.

Contribution

It introduces a statistical framework based on random phasor sums to describe Angio-OCT signals and validates it with experiments, enhancing understanding of motion contrast mechanisms.

Findings

Mathematically derived distributions of Angio-OCT signals.

Validated model with phantom and animal experiments.

Insights into optimizing motion contrast and system parameters.

Abstract

Optical coherence tomography angiography (Angio-OCT), mainly based on the temporal dynamics of OCT scattering signals, has found a range of potential applications in clinical and scientific research. Based on the model of random phasor sums, temporal statistics of the complex-valued OCT signals are mathematically described. Statistical distributions of the amplitude differential and complex differential Angio-OCT signals are derived. The theories are validated through the flow phantom and live animal experiments. Using the model developed, the origin of the motion contrast in Angio-OCT is mathematically explained, and the implications in the improvement of motion contrast are further discussed, including threshold determination and its residual classification error, averaging method, and scanning protocol. The proposed mathematical model of Angio-OCT signals can aid in the optimal design of the system and associated algorithms.