Positive surgical margins in head and neck cancers (HNC) are associated with poor survival. Standard frozen section analysis for intraoperative assessment of margins is limited by processing time and sampling error. Optical imaging technologies may address these limitations. We identified the following techniques in a literature search of optical imaging modalities for the detection of head and neck tumor margins: autofluorescence imaging, dynamic optical contrast imaging, optical coherence tomography, narrow band imaging, hyperspectral imaging, Raman spectroscopy, near-infrared fluorescence imaging, confocal laser endomicroscopy, and high-resolution microendoscopy. Penetration depths range from surface level to 6mm, image acquisition times range from real-time to several minutes, and 3/9 require exogenous contrast agents. Reported sensitivity and specificity range from 71-100% and 43-100%, respectively. Each reviewed modality lends unique strengths such as fast image acquisition times, wide field of view, high native contrast, or seamless integration with existing endoscopes. However, none have yet to replace palpation and frozen section analysis in the operating room.
Dynamic optical contrast imaging (DOCI) is an imaging method utilizing fluorescence lifetime that our team has developed for identification of margins in head & neck mucosal malignancies. In this paper we demonstrate the first utilization of DOCI in cutaneous melanoma. We utilized both a 530/30nm band pass filter, as well as a 400nm long pass filter to capture the autofluorescence of tissue fluorophores, after excitation with a 365nm wide field LED light source. Imaging was captured, processed via an established protocol in MatLab, and regions of interest were compared to corresponding histopathology. Patients with biopsy confirmed cutaneous melanoma who were undergoing surgical removal of their malignancy were recruited for in-vivo pre-operative DOCI imaging, intraoperative imaging, then ex-vivo imaging of the tumor after removal. Patients free of disease with benign moles were also recruited for in-vivo DOCI imaging to serve as controls. 11 patients with melanoma and 10 controls were included. DOCI distinguishes between melanoma vs. normal surrounding skin (sensitivity=94% specificity=88%, AUC=0.921) as well as benign nevi vs. melanoma (sensitivity=100% and specificity=80%, AUC=0.953), posing benefit opportunities for both melanoma diagnostics as well as margin determination.
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