Subtle alterations in stromal tissue structures and organizations within the extracellular matrix (ECM) have been observed in several types of tissue abnormalities, including early skin cancer and wounds. Current microscopic imaging methods often lack the ability to accurately determine the extent of malignancy over a large area, due to their limited field of view. In this research we focus on the development of simple mesoscopic (i.e. between microscopic and macroscopic) biomedical imaging device for non-invasive assessment of ECM alterations over a large, heterogeneous area. In our technology development, a telecentric lens, commonly used in machine vision systems but rarely used in biomedical imaging, serves as a key platform to visualize alterations in tissue microenvironments in a label-free manner over a clinically relevant area. In general, telecentric imaging represents a simple, alternative method for reducing unwanted scattering or diffuse light caused by the highly anisotropic scattering properties of biological tissue. In particular, under telecentric imaging the light intensity backscattered from biological tissue is mainly sensitive to the scattering anisotropy factor, possibly associated with the ECM. We demonstrate the inherent advantages of combining telecentric lens systems with hyperspectral imaging for providing optical information of tissue scattering in biological tissue of murine models, as well as light absorption of hemoglobin in blood vessel tissue phantoms. Thus, we envision that telecentric imaging could potentially serve for simple site-specific, tissue-based assessment of stromal alterations over a clinically relevant field of view in a label-free manner, for studying diseases associated with disruption of homeostasis in ECM.
Michelle A. Visbal Onufrak, Raymond L. Konger, and Young L. Kim, "Large area, label-free imaging of extracellular matrix using telecentricity," Proc. SPIE 10060, Optical Biopsy XV: Toward Real-Time Spectroscopic Imaging and Diagnosis, 1006010 (Presented at SPIE BiOS: February 01, 2017; Published: 17 February 2017); https://doi.org/10.1117/12.2253388.
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