The efficacy of ablative surgery for head and neck squamous cell carcinoma (HNSCC) depends critically on obtaining negative margins. While intraoperative "frozen section" analysis of margins is a valuable adjunct, it is expensive, time-consuming, and highly dependent on pathologist expertise. Optical imaging has potential to improve the accuracy of margins by identifying cancerous tissue in real time. Our aim was to determine the accuracy and inter-rater reliability of head and neck cancer specialists using high-resolution microendoscopic (HRME) images to discriminate between cancerous and benign mucosa.
Thirty-eight patients diagnosed with HNSCC were enrolled in this single-center study. HRME was used to image each specimen after application of proflavine, with concurrent standard histopathologic analysis. Images were evaluated for quality control, and a training set containing representative images of benign and neoplastic tissue was assembled. After viewing training images, seven head and neck cancer specialists with no prior HRME experience reviewed 37 test images and were asked to classify each.
The mean accuracy of all reviewers in correctly diagnosing neoplastic mucosa was 97 percent (95% Cl = 94–99%). The mean sensitivity and specificity were 98 percent (97–100%) and 92 percent (87–98%), respectively. The Fleiss kappa statistic for inter-rater reliability was 0.84 (0.77–0.91).
Medical professionals can be quickly trained to use HRME to discriminate between benign and neoplastic mucosa in the head and neck. With further development, the HRME shows promise as a method of real-time margin determination at the point of care.