New model for understanding the relationship between tissue composition and photothermal optical coherence tomography signals

Abstract

Photothermal optical coherence tomography (PT-OCT) is an extension of OCT that forms images based on both scattering and absorption of light. Conventional OCT measures the path length of elastically back-scattered light. Variation of the tissue’s local refractive index due to photothermal modulation results in a modulated OCT phase signal that relates to the absorption of light. Detailed understanding of the PT-OCT signal has the potential to provide insight into the chemical composition of tissue, and may pave a way to detecting and characterizing lipid-rich atherosclerotic plaques with intracoronary imaging in patients. Here, we investigated the dependence of the PT-OCT signal on concentration of a specific tissue component. We modeled the generated thermal wave field and the resulting PT-OCT signal as a function of concentration of this component using the bio-heat equation. We found that the significant parameters in determining the amplitude of the PT-OCT signals are the density, the absorption coefficient and the specific heat of the sample. All these parameters vary as a function of the sample composition, leading to a non-linear relation between PT-OCT signal and the concentration of the component of interest. Only in special cases, e.g. the oxygenation level of blood, when the absorption coefficient is the only varying parameter does a linear dependence arise. PT-OCT experiments on tissue-like samples, prepared by mixing mayonnaise (<80% lipid) and agar gel (<90% water) to mimic lipid-rich atherosclerotic plaques, confirmed the non-linear relation predicted by our model.