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In-vivo Testing of Oral Mucosal Lesions with an In-house Developed Portable Imaging Device and Comparison with Spectroscopy Results

Overview
Journal J Fluoresc
Specialties Biophysics
Chemistry
Date 2023 Jan 26
PMID 36701084
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Abstract

Progression of oral mucosal lesions is generally marked by changes in the concentration of the intrinsic fluorophores such as collagen, nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD) and porphyrin present in the human oral tissue. In this study, we have probed the changes in FAD and porphyrin by exciting with 405 nm laser light on different sites (tongue, buccal mucosa, lip etc.) of the oral cavity. Testing has been done by an in-house developed fluorescence-based portable imaging device on oral squamous cell carcinoma (OSCC) patients, dysplastic patients and control (normal) group. Fluorescence images recorded from OSCC and dysplastic patients have displayed an enhancement in the red band (porphyrin) as compared to those from the normal volunteers. Porphyrin to FAD intensity ratio (I/I), referred to red to green ratio (I/I) has been taken as the diagnostic marker for classification among the groups. Receiver operating characteristic (ROC) analysis applied on I/I is able to discriminate OSCC to normal, dysplasia to normal and OSCC to dysplasia with sensitivities of 100%, 81%, 92% and specificities of 100%, 93% and 92% respectively. Fluorescence imaging probe can capture a large area of oral lesions in a single scan and hence would be useful for initial scanning. On comparison with spectroscopy studies performed by our group, it is found that combining both spectroscopy and imaging as a device may be effective for the early detection of oral lesions. This clinical study was registered on the date 13/10/2017 in the clinical trials registry-India (CTRI) with registration number CTRI/2017/10/010102.

Citing Articles

Human Saliva as a Substitute Diagnostic Medium for the Detection of Oral Lesions Using the Stokes Shift Spectroscopy: Discrimination among the Groups by Multivariate Analysis Methods.

Kumar P, Pradhan A Asian Pac J Cancer Prev. 2023; 24(11):3757-3763.

PMID: 38019233 PMC: 10772759. DOI: 10.31557/APJCP.2023.24.11.3757.

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