Abstract Oral squamous cell carcinoma (OSCC) is one of the most common malignancies worldwide, and new protocols for routine and early detection are required. Raman spectroscopy is an optical based method that can provide sensitive and non‐invasive real time detailed information on the biochemical content of a sample like saliva, through the unique vibrations of its constituent molecules and this is sensitive to changes associated with disease. A comprehensive systematic review of the available scientific literature related to Raman spectroscopy of human saliva for diagnosis of OSCC was performed. The 785 nm laser line was most applied wavelength along with principal components analysis associated with linear discriminant analysis. The main salivary components possibly associated with the presence of OSCC were proteins and lipids. Measurement in the liquid physical state, and with no addition of nanoparticles for signal enhancement, seemed to best conserve the salivary integrity. However, in terms of sampling protocols, no differentiation was generally made between stimulated and non‐stimulated saliva. Raman spectroscopy of saliva holds a promising future for clinical applications such as early detection of OSCC. However, more systematic analyses are still required for a better elucidation regarding sampling procedure, storage and degradation.

This photo illustrates the da Vinci SP robot performing an intraoperative fluorescence lifetime image scan of a patient undergoing oral cancer resection. The scan creates an augmented overlay with a color scale based on fluorescence lifetime. The difference in lifetime between healthy tissue and cancer generates contrast, thus enabling demarcation of the cancer area. Further details can be found in the article by Brent W. Weyers, Mark Marsden, Tianchen Sun, Julien Bec, Arnaud F. Bewley, Regina F. Gandour-Edwards, Michael G. Moore, D. Gregory Farwell, Laura Marcu (e201900017).

This study evaluates the potential for fluorescence lifetime imaging (FLIm) to enhance intraoperative decisionmaking during robotic-assisted surgery of oropharyngeal cancer. Using a custom built FLIm instrument integrated with the da Vinci robotic surgical platform, we first demonstrate that cancer in epithelial tissue diagnosed by histopathology can be differentiated from surrounding healthy epithelial tissue imaged in vivo prior to cancer resection and ex vivo on the excised specimen. Second, we study the fluorescence properties of tissue imaged in vivo at surgical resection margins (tumor bed). Fluorescence lifetimes and spectral intensity ratios were calculated for three spectral channels, producing a set of six FLIm parameters. Current results from 10 patients undergoing TORS procedures demonstrate that healthy epithelium can be resolved from cancer (P < .001) for at least one FLIm parameter. We also showed that a multiparameter linear discriminant analysis approach provides superior discrimination to individual FLIm parameters for tissue imaged both in vivo and ex vivo. Overall, this study highlights the potential for FLIm to be developed into a diagnostic tool for clinical cancer applications of the oropharynx. This technique could help to circumvent the issues posed by the lack of tactile feedback associated with robotic surgical platforms to better enable cancer delineation.