Measurement of a multi-layered tear film phantom using optical coherence tomography and statistical decision theory

To extend our understanding of tear film dynamics for the management of dry eye disease, we propose a method to optically sense the tear film and estimate simultaneously the thicknesses of the lipid and aqueous layers. The proposed method, SDT-OCT, combines ultra-high axial resolution optical coherence tomography (OCT) and a robust estimator based on statistical decision theory (SDT) to achieve thickness measurements at the nanometer scale. Unlike conventional Fourier-domain OCT where peak detection of layers occurs in Fourier space, in SDT-OCT thickness is estimated using statistical decision theory directly on the raw spectra acquired with the OCT system. In this paper, we demonstrate in simulation that a customized OCT system tailored to ~1 µm axial point spread function (FWHM) in the corneal tissue, combined with the maximum-likelihood estimator, can estimate thicknesses of the nanometer-scale lipid and micron-scale aqueous layers of the tear film, simultaneously, with nanometer precision. This capability was validated in experiments using a physical phantom that consists of two layers of optical coatings that mimic the lipid and aqueous layers of the tear film.