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.

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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.

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