In vivo autofluorescence imaging of early cancers in the human tracheobronchial tree with a spectrally optimized system.

The changes in the autofluorescence characteristics of the bronchial tissue is of crucial interest as a cancer diagnostic tool. Evidence exists that this native fluorescence or autofluorescence of bronchial tissues changes when they turn dysplastic and to carcinoma in situ. There is good agreement that the lesions display a decrease of autofluorescence in the green region of the spectrum under illumination with violet-light, and a relative increase in the red region of the spectrum is often reported. Imaging devices rely on this principle to detect early cancerous lesions in the bronchi. Based on a spectroscopic study, an industrial imaging prototype is developed to detect early cancerous lesions in collaboration with the firm Richard Wolf Endoskope GmbH, Germany. A preliminary clinical trial involving 20 patients with this spectrally optimized system shows that the autofluorescence can help to detect most lesions that would otherwise have remained invisible to an experienced endoscopist under white light illumination. A systematic off line analysis of the autofluorescence images pointed out that real-time decisional functions can be defined to reduce the number of false positive results. Using this method, a positive predictive value (PPV) of 75% is reached using autofluorescence only. Moreover, a PPV of 100% is obtained, when combining the white light (WL) mode and the autofluorescence (AF) mode, at the applied conditions. Furthermore, the sensitivity is estimated to be twice higher in the AF mode than in WL mode.