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Label free detection of pre-cancerous cells in vivo with a/LCI (Conference Presentation)
Author(s): Adam Wax
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Paper Abstract

Detection of pre-cancerous (dysplastic) tissues in the clinic remains an ongoing challenge. Current methods often rely on systematic biopsies with no visual cues to guide the physician to areas likely to harbor dysplasia. We have developed novel spectroscopic techniques for assessing cell structure and diagnosing disease based on combining interferometry with light scattering. Angle-resolved low coherence interferometry (a/LCI) combines the depth gating of coherence imaging, as used in optical coherence tomography, with the high resolution structural information that can be obtained with light scattering spectroscopy. The a/LCI approach has been validated with in vitro measurements of phantoms and in vitro cells to recover sub-cellular structure with sub-wavelength accuracy and precision. Discrimination of pre-cancerous tissue states was initially demonstrated using animal models and ex vivo human tissues, by using light scattering and interferometry to measure the size of cell nuclei in selected tissue layers. We will discuss various light scattering models used in a/LCI, including Mie theory, T-matrix, and analysis methods based on wavelet transforms and machine learning, as they relate to their application to this clinical problem. To implement a/LCI for detection of pre-cancerous tissues in patients, we have developed a clinical a/LCI system, including a portable optical engine, and an endoscope compatible fiber probe for in vivo measurements. The capabilities of a/LCI will be shown with results from clinical studies to detect precancerous cells in both the esophagus and cervix during routine clinical examination. Further directions to enhance clinical utility and ergonomic ease of use will also be discussed.

Paper Details

Date Published: 4 March 2019
Proc. SPIE 10890, Label-free Biomedical Imaging and Sensing (LBIS) 2019, 1089014 (4 March 2019); doi: 10.1117/12.2507063
Show Author Affiliations
Adam Wax, Duke Univ. (United States)

Published in SPIE Proceedings Vol. 10890:
Label-free Biomedical Imaging and Sensing (LBIS) 2019
Natan T. Shaked; Oliver Hayden, Editor(s)

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