Diagnosis of oral cancer by light-induced autofluorescence spectroscopy using double excitation wavelengths

A cancer diagnostic algorithm, light-induced autofluorescence spectroscopy using double excitation wavelengths, was employed for distinguishing between cancerous and normal oral mucosa. For emission spectra at the shorter excitation wavelengths (280, 290, and 300 nm), the ratio between the area under 325–335 nm and the area under 465–475 nm was calculated. In the same way, for emission spectra at the longer excitation wavelengths (320, 330, and 340 nm), the ratio between the area under 375–385 nm and the area under 465–475 nm was calculated. Receiver operating characteristic curves were used to evaluate the performance of algorithms using single and the double (by combining shorter and longer) excitation wavelengths. The results showed that better performance, up to sensitivity 81.25%, specificity 93.75%, and positive predictive value 92.86%, could be achieved by using the double excitation wavelengths. The present study can be useful as a basis for further investigation on in vivo autofluorescence measurement and analysis using double excitation wavelength.