Background: This study evaluated whether fluorescence lifetime imaging (FLIm), coupled with standard diagnostic workups, could enhance primary lesion detection in patients with p16+ head and neck squamous cell carcinoma of the unknown primary (HNSCCUP).
Methods: FLIm was integrated into transoral robotic surgery to acquire optical data on six HNSCCUP patients' oropharyngeal tissues. An additional 55-patient FLIm dataset, comprising conventional primary tumors, trained a machine learning classifier; the output predicted the presence and location of HNSCCUP for the six patients. Validation was performed using histopathology.
Results: Among the six HNSCCUP patients, p16+ occult primary was surgically identified in three patients, whereas three patients ultimately had no identifiable primary site in the oropharynx. FLIm correctly detected HNSCCUP in all three patients (ROC-AUC: 0.90 ± 0.06), and correctly predicted benign oropharyngeal tissue for the remaining three patients. The mean sensitivity was 95% ± 3.5%, and specificity 89% ± 12.7%.
Conclusions: FLIm may be a useful diagnostic adjunct for detecting HNSCCUP.
Keywords: cancer delineation; endogenous autofluorescence; fluorescence lifetime imaging (FLIm); intraoperative surgical guidance; machine learning in oncology applications; occult primary tumor; oropharyngeal cancer of unknown primary origin; p16+ squamous cell carcinoma; transoral robotic surgery.
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