Fluorescence spectroscopy for throat cancer detection using human saliva

Pavan Kumar; Ashutosh Singh; Mohammad Zaffar; Asima Pradhan

doi:10.1117/12.2289897

21 February 2018 Fluorescence spectroscopy for throat cancer detection using human saliva

Pavan Kumar, Ashutosh Singh, Mohammad Zaffar, Asima Pradhan

Proceedings Volume 10489, Optical Biopsy XVI: Toward Real-Time Spectroscopic Imaging and Diagnosis; 104891B (2018) https://doi.org/10.1117/12.2289897
Event: SPIE BiOS, 2018, San Francisco, California, United States

Abstract

Throat precancer detection using fluorescence from human saliva is reported here. It may be noted that accessing the throat for investigation is cumbersome and use of saliva as a diagnostic medium may ease the process. The study has been conducted on three groups of patients: oral squamous cell carcinoma (OSCC), dysplasia, and normal (control). An in-house developed compact set-up has been used for fluorescence measurements. The compact system consist of a 375 nm laser diode, collimating lens, long pass filter, fibers, and cuvette holder. Major and minor bands of flavin adenine dinucleotide (FAD) and porphyrin are observed in the spectra. A receiver operating characteristic (ROC) analysis has been used to evaluate the diagnostic performance. Area under the spectra has been chosen for discrimination among the groups and is able to differentiate OSCC to normal, dysplasia to normal, and OSCC to dysplasia with sensitivities 100% (48/48), 92% (32/35), 77% (37/48), and specificities 96% (50/52), 96% (50/52), 89% (31/35) with the accuracy of 98%, 94% and 82% respectively. Sensitivity and specificity, when differentiating OSCC to normal and dysplasia to normal, are significantly large, which indicates that human saliva may be an excellent diagnostic medium for early detection of throat cancer.

Citation Download Citation

Pavan Kumar, Ashutosh Singh, Mohammad Zaffar, and Asima Pradhan "Fluorescence spectroscopy for throat cancer detection using human saliva", Proc. SPIE 10489, Optical Biopsy XVI: Toward Real-Time Spectroscopic Imaging and Diagnosis, 104891B (21 February 2018); https://doi.org/10.1117/12.2289897

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