Imaging the body with diffuse optical tomography

TLDR

Diffuse optical tomography (DOT) uses near‑infrared light to probe tissue, exploiting the weak absorption of water and hemoglobin to create a spectral window that enables localization of absorption and scattering, and is currently applied to breast tumor detection and brain imaging. The paper aims to introduce the fundamental concept of DOT and review the historical development of optical medical imaging techniques that led to its current form. The authors describe DOT’s operational principles, including tissue optical properties, imaging modes, and the challenges of forward and inverse problem modeling, with a focus on signal‑processing approaches. They conclude by presenting specific results that illustrate the present state of DOT research.

Abstract

Diffuse optical tomography (DOT) is an ongoing medical imaging modality in which tissue is illuminated by near-infrared light from an array of sources, the multiply-scattered light which emerges is observed with an array of detectors, and then a model of the propagation physics is used to infer the localized optical properties of the illuminated tissue. The three primary absorbers at these wavelengths, water and both oxygenated and deoxygenated hemoglobin, all have relatively weak absorption. This fortuitous fact provides a spectral window through which we can attempt to localize absorption (primarily by the two forms of hemoglobin) and scattering in the tissue. The most important current applications of DOT are detecting tumors in the breast and imaging the brain. We introduce the basic idea of DOT and review the history of optical methods in medicine as relevant to the development of DOT. We then detail the concept of DOT, including a review of the tissue's optical properties, modes of operation for DOT, and the challenges which the development of DOT must overcome. The basics of modelling the DOT forward problem and some critical issues among the numerous implementations that have been investigated for the DOT inverse problem, with an emphasis on signal processing. We summarize with some specific results as examples of the current state of DOT research.