Effect of Scatterering on Coherent Anti-Stokes Raman Scattering (CARS) signals

TL;DR

This paper presents a computational framework to analyze how scattering in turbid media distorts CARS signals, revealing factors affecting signal integrity and proposing methods to minimize distortions.

Contribution

The study introduces a combined HF-WEFS and dipole approximation approach to quantify scattering effects on CARS signals in turbid samples.

Findings

Distortions arise from focal field attenuation and phase changes.

High numerical aperture condensers reduce CARS signal attenuation.

Polarization-based CARS imaging is less affected by scattering.

Abstract

We develop a computational framework to examine the factors responsible for scattering-induced distortions of coherent anti-Stokes Raman scattering (CARS) signals in turbid samples. We apply the Huygens-Fresnel Wave-based Electric Field Superposition (HF-WEFS) method combined with the radiating dipole approximation to compute the effects of scattering-induced distortions of focal excitation fields on the far-field CARS signal. We analyze the effect of spherical scatterers, placed in the vicinity of the focal volume, on the CARS signal emitted by different objects (2{\mu}m diameter solid sphere, 2{\mu}m diameter myelin cylinder and 2{\mu}m diameter myelin tube). We find that distortions in the CARS signals arise not only from attenuation of the focal field but also from scattering-induced changes in the spatial phase that modifies the angular distribution of the CARS emission. Our simulations further show that CARS signal attenuation can be minimized by using a high numerical aperture condenser. Moreover, unlike the CARS intensity image, CARS images formed by taking the ratio of CARS signals obtained using x- and y-polarized input fields is relatively insensitive to the effects of spherical scatterers. Our computational framework provide a mechanistic approach to characterizing scattering-induced distortions in coherent imaging of turbid media and may inspire bottom-up approaches for adaptive optical methods for image correction.