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Open AccessArticle

Full-Field Optical Coherence Tomography as a Diagnosis Tool: Recent Progress with Multimodal Imaging

1
Institut Langevin, ESPCI Paris, PSL Research University, 1 rue Jussieu, Paris 75005, France
2
LLTech SAS, Pépinière Paris Santé Cochin 29 rue du Faubourg Saint Jacques, Paris 75014, France
*
Author to whom correspondence should be addressed.
Academic Editor: Michael Pircher
Appl. Sci. 2017, 7(3), 236; https://doi.org/10.3390/app7030236
Received: 20 January 2017 / Revised: 20 February 2017 / Accepted: 21 February 2017 / Published: 2 March 2017
(This article belongs to the Special Issue Development and Application of Optical Coherence Tomography (OCT))
Full-field optical coherence tomography (FF-OCT) is a variant of OCT that is able to register 2D en face views of scattering samples at a given depth. Thanks to its superior resolution, it can quickly reveal information similar to histology without the need to physically section the sample. Sensitivity and specificity levels of diagnosis performed with FF-OCT are 80% to 95% of the equivalent histological diagnosis performances and could therefore benefit from improvement. Therefore, multimodal systems have been designed to increase the diagnostic performance of FF-OCT. In this paper, we will discuss which contrasts can be measured with such multimodal systems in the context of ex vivo biological tissue examination. We will particularly emphasize three multimodal combinations to measure the tissue mechanics, dynamics, and molecular content respectively. View Full-Text
Keywords: full-field optical coherence tomography; multimodality; biomechanics; mechanical properties; dynamics; cellular metabolism; fluorescence microscopy full-field optical coherence tomography; multimodality; biomechanics; mechanical properties; dynamics; cellular metabolism; fluorescence microscopy
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MDPI and ACS Style

Thouvenin, O.; Apelian, C.; Nahas, A.; Fink, M.; Boccara, C. Full-Field Optical Coherence Tomography as a Diagnosis Tool: Recent Progress with Multimodal Imaging. Appl. Sci. 2017, 7, 236.

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