Differences in the diagnostic value between fiberoptic and high definition laryngoscopy for the characterisation of pharyngeal and laryngeal lesions: A multi‐observer paired analysis of videos

Scholman, Constanze; Westra, Jantine L.; Zwakenberg, Manon A.; Dikkers, Frederik G.; Halmos, György B.; Wedman, Jan; Wachters, Jan E.; Laan, Bernard F. A. M. van der; Plaat, Boudewijn E. C.

doi:10.1111/coa.13476

Cited by 12 publications

(24 citation statements)

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“…The higher detection rate with HDL of squamous cell carcinoma is in line with our previous study and is of great importance for a patient presenting with a malignant lesion of the glottis [ 7 , 10 ]. Early detection of malignancy has an essential impact on the prognosis of the patient [ 2 ].…”

Section: Discussionsupporting

confidence: 87%

“…In FOL, 25% of the observers judged the normal glottis inaccurately as hyperkeratosis and in HDL this was 6.6%. The superiority of HDL to detect a normal glottis is an improvement since it was not shown in our previous study [ 7 ]. An explanation could be the large number of observations.…”

Section: Discussionmentioning

confidence: 77%

“…An explanation could be the large number of observations. For evaluation of a normal glottis with both endoscopes, we reached an amount of more than 200 observations versus 18 observations in the previous study [ 7 ]. In this way, we were able to manifest slight differences into significant ones.…”

Section: Discussionmentioning

confidence: 81%

“…However, the quality of the images obtained with FOL might make it hard to distinguish a malignant from a benign lesion and minor epithelial changes could be overlooked [5]. HDL, which was developed after the introduction of digital chip-on tip endoscopy in 1983, shows a superior image quality and has the potential to improve diagnostics of laryngeal lesions [6,7]. In a previous study, we found that HDL is superior to FOL in detecting mucosal abnormalities and enhanced the level of diagnostic accuracy [7].…”

Section: Introductionmentioning

confidence: 99%

“…HDL, which was developed after the introduction of digital chip-on tip endoscopy in 1983, shows a superior image quality and has the potential to improve diagnostics of laryngeal lesions [6,7]. In a previous study, we found that HDL is superior to FOL in detecting mucosal abnormalities and enhanced the level of diagnostic accuracy [7]. In that study, observers with at least 5 years of clinical experience in the field of laryngology and/or Head and Neck oncology examined pharyngeal and laryngeal videos recorded by both FOL and HDL.…”

Section: Introductionmentioning

confidence: 99%

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High-definition videolaryngoscopy is superior to fiberoptic laryngoscopy: a 111 multi-observer study

Scholman

Westra

Zwakenberg

et al. 2021

Eur Arch Otorhinolaryngol

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Purpose This study aims to analyse differences in fiberoptic laryngoscopy (FOL) versus high definition laryngoscopy (HDL) by examining videolaryngoscopy images by a large group of observers with different levels of clinical expertise in ear, nose and throat (ENT) medicine. Methods This study is a 111 observer paired analysis of laryngoscopy videos during an interactive presentation. During a National Meeting of the Dutch Society of ENT/Head and Neck Surgery, observers assessed both FOL and HDL videos of nine cases with additional clinical information. Observers included 41 ENT consultants (36.9%), 34 ENT residents (30.6%), 22 researchers with Head and Neck interest (19.8%) and 14 with unspecified clinical expertise (12.6%). For both laryngoscopic techniques, sensitivity, specificity, positive and negative predictive value and diagnostic accuracy were determined for identifying a normal glottis, hyperkeratosis, radiotherapy adverse effects and squamous cell carcinoma. The sensitivities for FOL and HDL were analysed with regard to the different levels of clinical expertise. Results The overall sensitivity for correctly identifying the specific histological entity was higher in HDL (FOL 61% vs HDL 66.3%, p < 0.05). HDL was superior to FOL in identifying a normal glottis (FOL 68.1% vs HDL 91.6%, p < 0.01) and squamous cell carcinoma (FOL 70.86% vs HDL 79.41%, p = 0.02). Residents and researchers with Head and Neck interest diagnosed laryngeal lesions more correctly with HDL (p < 0.05). Conclusions In a large population of observers with different levels of clinical expertise, HDL is superior to FOL in identifying laryngeal lesions.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 77%

Section: Discussionmentioning

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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High-definition videolaryngoscopy is superior to fiberoptic laryngoscopy: a 111 multi-observer study

Scholman

Westra

Zwakenberg

et al. 2021

Eur Arch Otorhinolaryngol

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Deep Learning Applied to White Light and Narrow Band Imaging Videolaryngoscopy: Toward Real‐Time Laryngeal Cancer Detection

et al. 2021

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Objectives: To assess a new application of artificial intelligence for real-time detection of laryngeal squamous cell carcinoma (LSCC) in both white light (WL) and narrow-band imaging (NBI) videolaryngoscopies based on the You-Only-Look-Once (YOLO) deep learning convolutional neural network (CNN).Study Design: Experimental study with retrospective data. Methods: Recorded videos of LSCC were retrospectively collected from in-office transnasal videoendoscopies and intraoperative rigid endoscopies. LSCC videoframes were extracted for training, validation, and testing of various YOLO models. Different techniques were used to enhance the image analysis: contrast limited adaptive histogram equalization, data augmentation techniques, and test time augmentation (TTA). The best-performing model was used to assess the automatic detection of LSCC in six videolaryngoscopies.Results: Two hundred and nineteen patients were retrospectively enrolled. A total of 624 LSCC videoframes were extracted. The YOLO models were trained after random distribution of images into a training set (82.6%), validation set (8.2%), and testing set (9.2%). Among the various models, the ensemble algorithm (YOLOv5s with YOLOv5m-TTA) achieved the best LSCC detection results, with performance metrics in par with the results reported by other state-of-the-art detection models: 0.66 Precision (positive predicted value), 0.62 Recall (sensitivity), and 0.63 mean Average Precision at 0.5 intersection over union. Tests on the six videolaryngoscopies demonstrated an average computation time per videoframe of 0.026 seconds. Three demonstration videos are provided.Conclusion: This study identified a suitable CNN model for LSCC detection in WL and NBI videolaryngoscopies. Detection performances are highly promising. The limited complexity and quick computational times for LSCC detection make this model ideal for real-time processing.

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Edge Enhancement Optimization in Flexible Endoscopic Images to the Perception of Ear, Nose and Throat Professionals

Geleijnse,

Veder,

Hakkesteegt

et al. 2023

The Laryngoscope

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ObjectivesDigital endoscopes are connected to a video processor that applies various operations to process the image. One of those operations is edge enhancement that sharpens the image. The purpose of this study was to (1) quantify the level of edge enhancement, (2) measure the effect on sharpness and image noise, and (3) study the influence of edge enhancement on image quality perceived by ENT professionals.MethodsThree digital flexible endoscopic systems were included. The level of edge enhancement and the influence on sharpness and noise were measured in vitro, while systematically varying the levels of edge enhancement. In vivo images were captured at identical levels of one healthy larynx. Each series of in vivo images was presented to 39 ENT professionals according to a forced pairwise comparison test, to select the image with the best image quality for diagnostic purposes. The numbers of votes were converted to a psychometric scale of just noticeable differences (JND) according to the Thurstone V model.ResultsThe maximum level of edge enhancement varied per endoscopic system and ranged from 0.8 to 1.2. Edge enhancement increased sharpness and noise. Images with edge enhancement were unanimously preferred to images without edge enhancement. The quality difference with respect to zero edge enhancement reaches an optimum at levels between 0.7 and 0.9.ConclusionEdge enhancement has a major impact on sharpness, noise, and the resulting perceived image quality. We conclude that ENT professionals benefit from this video processing and should verify if their equipment is optimally configured.Level of EvidenceN/A Laryngoscope, 2023

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Differences in the diagnostic value between fiberoptic and high definition laryngoscopy for the characterisation of pharyngeal and laryngeal lesions: A multi‐observer paired analysis of videos

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 12 publications

References 24 publications

High-definition videolaryngoscopy is superior to fiberoptic laryngoscopy: a 111 multi-observer study

High-definition videolaryngoscopy is superior to fiberoptic laryngoscopy: a 111 multi-observer study

Deep Learning Applied to White Light and Narrow Band Imaging Videolaryngoscopy: Toward Real‐Time Laryngeal Cancer Detection

Edge Enhancement Optimization in Flexible Endoscopic Images to the Perception of Ear, Nose and Throat Professionals

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