Rapid diagnosis and intraoperative margin assessment of human lung cancer with fluorescence lifetime imaging microscopy.
BBA Clin
; 8: 7-13, 2017 Dec.
Article
em En
| MEDLINE
| ID: mdl-28567338
ABSTRACT
A method of rapidly differentiating lung tumor from healthy tissue is extraordinarily needed for both the diagnosis and the intraoperative margin assessment. We assessed the ability of fluorescence lifetime imaging microscopy (FLIM) for differentiating human lung cancer and normal tissues with the autofluorescence, and also elucidated the mechanism in tissue studies and cell studies. A 15-patient testing group was used to compare FLIM results with traditional histopathology diagnosis. Based on the endogenous fluorescence lifetimes of the testing group, a criterion line was proposed to distinguish normal and cancerous tissues. Then by blinded examined 41 sections from the validation group of other 16 patients, the sensitivity and specificity of FLIM were determined. The cellular metabolism was studied with specific perturbations of oxidative phosphorylation and glycolysis in cell studies. The fluorescence lifetime of cancerous lung tissues is consistently lower than normal tissues, and this is due to the both decrease of reduced nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) lifetimes. A criterion line of lifetime at 1920 ps can be given for differentiating human lung cancer and normal tissues.The sensitivity and specificity of FLIM for lung cancer diagnosis were determined as 92.9% and 92.3%. These findings suggest that NADH and FAD can be used to rapidly diagnose lung cancer. FLIM is a rapid, accurate and highly sensitive technique in the judgment during lung cancer surgery and it can be potential in earlier cancer detection.
Autofluorescence; BEAS-2B, human bronchial epithelial cells; Cancer metabolism; FAD, flavin adenine dinucleotide; FLIM, fluorescence lifetime imaging microscopy; HE, haematoxylin and eosin; Lifetime; Lung tissues; NADH, reduced nicotinamide adenine dinucleotide; Rapid and sensitive diagnosis; TCSPC, time-correlated single photon counting
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2017
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Article