Defining a baseline identification of artifacts in confocal laser endomicroscopy in head and neck cancer imaging

Abstract

PurposeProbe-based confocal laser endomicroscopy (pCLE) allows imaging of the laryngeal mucosa in a thousand-fold magnification. However, the existence of multiple nondiagnostic frames might hinder the performance of automated systems, especially in post-processing and analysis algorithms. This study aims to investigate the feasibility of building a baseline for the identification of diagnostic frames and to evaluate the influence of sequence information in this task. Materials and methodsWe included eight patients with squamous cell carcinoma (SCC) and planned total laryngectomy between October 2020 and February 2021. One hundred frames were randomly selected out of 21,272 pCLE frames of the tumor and healthy mucosa during surgery. Three experts were asked to classify these frames into diagnostic and nondiagnostic ones with different subtypes under two settings, i.e., isolated frames or short video sequences. Inter-rater and intra-rater consistency were analyzed with Cohen's kappa coefficients. ResultsAmong all raters, regarding the classification of diagnostic frames, an average agreement of κ = 0.79 has been achieved. The overall consistency for the subtypes of nondiagnostic frames is κ = 0.75 and κ = 0.57, respectively. ConclusionsThe high level of consistency regarding the identification of diagnostic frames shows the reliability of the classification results and builds the foundation for future automatic algorithms.