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Appl. Sci. 2017, 7(1), 32; doi:10.3390/app7010032

Autofluorescence Imaging and Spectroscopy of Human Lung Cancer

1
Department of Optical Science and Engineering, Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Green Photoelectron Platform, Fudan University, 220 Handan Road, Shanghai 200433, China
2
Department of Respiratory Diseases, Huashan North Hospital, 108 Luxiang Road, Baoshan District, Shanghai 201907, China
3
Department of Pathology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai 200040, China
4
School of Arts and Sciences, MCPHS University, Boston, MA 02115, USA
5
Department of Respiratory Diseases, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai 200040, China
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Academic Editor: Richard Leach
Received: 16 November 2016 / Revised: 23 December 2016 / Accepted: 23 December 2016 / Published: 28 December 2016
(This article belongs to the Special Issue Dimensional Micro and Nanometrology)
View Full-Text   |   Download PDF [3403 KB, uploaded 28 December 2016]   |  

Abstract

Lung cancer is one of the most common cancers, with high mortality rate worldwide. Autofluorescence imaging and spectroscopy is a non-invasive, label-free, real-time technique for cancer detection. In this study, lung tissue sections excised from patients were detected by laser scan confocal microscopy and spectroscopy. The autofluorescence images demonstrated the cellular morphology and tissue structure, as well as the pathology of stained images. Based on the spectra study, it was found that the majority of the patients showed discriminating fluorescence in tumor tissues from normal tissues. Therefore, autofluorescence imaging and spectroscopy may be a potential method for aiding the diagnosis of lung cancer. View Full-Text
Keywords: autofluorescence; spectroscopy; confocal imaging; lung cancer detection; metabolism autofluorescence; spectroscopy; confocal imaging; lung cancer detection; metabolism
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Wang, M.; Long, F.; Tang, F.; Jing, Y.; Wang, X.; Yao, L.; Ma, J.; Fei, Y.; Chen, L.; Wang, G.; Mi, L. Autofluorescence Imaging and Spectroscopy of Human Lung Cancer. Appl. Sci. 2017, 7, 32.

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