The primary standard of care for Head and Neck (H&N) cancer patients is the complete surgical removal of cancer. Tissue classifiers based of autofluorescence lifetime imaging (FLIm) parameters have shown potential to differentiate healthy from cancer tissue in H&N patients and thus enhance the accuracy of this procedure. Here we report how collective autofluorescence trends (100-patient cohort, oral/oropharyngeal cancer) driving healthy vs. tumor contrast depend on anatomical location, patient medical history (e.g. tobacco use) and surgical context (in vivo vs. ex vivo). Accounting for such biological variables may further improve the accuracy of FLIm-guided H&N cancer surgery.
Oral cavity and oropharyngeal cancers are leading pathologies, representing 3% of all new cancer cases in the United States. Adequate intraoperative marginal clearance of these malignancies is essential for long-term survival; however, presently available techniques limit precise instantaneous tumor margin characterization. Herein, we report the clinical validation of a fiber-based fluorescence lifetime imaging device for real-time intraoperative tumor delineation. Results from 72 human patients are reported (autofluorescence trends, ROC-AUC), including diverse cancer histologies, anatomic sites (e.g. tongue, tonsil, etc.), and patient medical histories. Emphasis is placed on results governing the detection of unknown primary tumors from 4 patients, as well as data from 5 patients presenting with residual carcinoma.
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