Recent studies on optical coherence tomography imaging of biological tissues

Abstract

Use of optical techniques for biomedical imaging is a topic of considerable current interest. This is motivated by the potential of optical techniques to provide micrometer-scale resolution imaging without the need for ionizing radiation and associated risks. Optical coherence tomography (OCT) can provide non-invasive cross-sectional images of biological tissues in real time with spatial resolutions down to few micrometers. Recent advances in OCT enable rapid image acquisition speeds and 3D volumetric information. There have been increasing applications of 3D-OCT for imaging of biological microstructures such as human retina, human skin and other developmental model systems. The depth of OCT imaging is limited by scattering of the medium that destroys the coherence of the probe beam. Thus while for non-scattering ocular structures, OCT can be used to image the entire structure, imaging of highly scattering tissues like skin is usually limited to a few mm. By taking OCT images for two orthogonal linear polarizations of the scattered light we can get information about the birefringent properties of the tissue. This helps monitor changes in the morphology of the birefringent constituents (collagen, tendon etc) of the tissue. Such Polarisation Senstive OCT (PSOCT) systems have also been developed and are being used for monitoring changes that take place in malignancy or in wounds. Work on the development and utilization of OCT & PSOCT systems for biological tissue imaging is being actively pursued at RRCAT, Indore. The OCT Proceedings of 2010 International Conference on Systems in Medicine and Biology 16–18 December 2010, IIT Kharagpur, India systems have been used for real time, in vivo & in vitro imaging of micro-structures of biological tissues and animal model systems with resolutions of ∼10–20 µm. Even though cytological differences cannot be monitored, the characteristic morphological features (texture) in OCT images can be used to discriminate and classify different tissue types using automated algorithms. In this talk I shall provide an overview of some of these developments and describe a few representative applications carried out in our laboratory.