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

Pan Z, Breininger K, Aubreville M, Stelzle F, Maier A, Oetter N, Mantsopoulos K, Iro H, Goncalves M, Sievert M (2023)

Publication Type: Journal article

Publication year: 2023

Journal

American Journal of Otolaryngology WB Saunders

Book Volume: 44

Article Number: 103779

Journal Issue: 2

DOI: 10.1016/j.amjoto.2022.103779

Abstract

Purpose: Probe-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 methods: We 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. Results: Among 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. Conclusions: The 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.

Authors with CRIS profile

Zhaoya Pan Lehrstuhl für Informatik 5 (Mustererkennung) Katharina Breininger Juniorprofessur für Artificial Intelligence in Medical Imaging Florian Stelzle Department of Oral and Cranio-Maxillofacial Surgery Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung) Nicolai Oetter Department of Oral and Cranio-Maxillofacial Surgery Konstantinos Mantsopoulos Department of Otorhinolaryngology – Head and Neck Surgery Heinrich Iro Lehrstuhl für Hals-, Nasen- und Ohrenheilkunde Matti Sievert Department of Otorhinolaryngology – Head and Neck Surgery

Involved external institutions

Universitätsklinikum Aachen (UKA) DE Germany (DE) Technische Hochschule Ingolstadt DE Germany (DE)

How to cite

APA:

Pan, Z., Breininger, K., Aubreville, M., Stelzle, F., Maier, A., Oetter, N.,... Sievert, M. (2023). Defining a baseline identification of artifacts in confocal laser endomicroscopy in head and neck cancer imaging. American Journal of Otolaryngology, 44(2). https://dx.doi.org/10.1016/j.amjoto.2022.103779

MLA:

Pan, Zhaoya, et al. "Defining a baseline identification of artifacts in confocal laser endomicroscopy in head and neck cancer imaging." American Journal of Otolaryngology 44.2 (2023).

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