Abstract
The attenuation coefficient of biological tissue could serve as an indicator of structural and functional changes related to the onset or progression of disease. Optical coherence tomography (OCT) provides cross-sectional images of tissue up to a depth of a few millimeters, based on the local backscatter properties. Monte Carlo (MC) simulations are ideally suited to investigate and improve OCT attenuation coefficient extraction in confounding cases of (low-order) multiple scattering and inclusions such as blood vessels. However, current MC methods are time-consuming due to the OCT detection configuration rejecting many of the backscattered photons. In this work, we present two MC OCT detection models, a conventional photon detection model and a hybrid particle-wave detection model based on spherical waves from a photon's last scatter position, and compare their simulation efficiency by comparing the SNR of the resulting depth profiles for equal conditions and number of simulated photons. We find a three orders of magnitude increase in the simulation efficiency for the hybrid particle-wave model compared to the conventional photon detection model. Both models show excellent agreement with single-scatter theory for weakly scattering samples. Additionally, we use the hybrid particle-wave model to simulate experimentally measured samples with 0.1 mm(-1) ≤µ (s) ≤ ~4.5 mm(-1). The resulting simulated depth profiles show excellent agreement with the experimental depth profiles, even in those cases where the single-scatter theory model fails to describe the experimental depth profiles accurately.