Head and neck cancers are the 16th most prevalent globally, and survival relies on early detection. Widefield autofluorescence (WFAF) shows potential for identifying neoplastic sites but lacks specificity. We investigate multispectral WFAF imaging to identify spectral features from endogenous biomarkers in native and neoplastic oral mucosa, using a DMBA-treated hamster buccal pouch model, with the aim to increase specificity. Spatially resolved spectra revealed variations between nonneoplastic and neoplastic areas. Analyses will compare spectral features in benign, dysplastic, and carcinoma sites from preclinical animal model and human tissues. Refinements in the red/green WFAF approach, by analyzing spectral features, are considered.
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