Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.

<h4>Background</h4>Linked color imaging (LCI) has been shown to be effective in multiple randomized controlled trials for enhanced colorectal polyp detection. Recently, artificial intelligence (AI) with deep learning through convolutional neural networks has dramatically improved and is...

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Autores principales:	Helmut Neumann, Andreas Kreft, Visvakanth Sivanathan, Fareed Rahman, Peter R Galle
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c470c78a03ae41ffa3c196ce397201ce
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spelling	oai:doaj.org-article:c470c78a03ae41ffa3c196ce397201ce2021-12-02T20:17:34ZEvaluation of novel LCI CAD EYE system for real time detection of colon polyps.1932-620310.1371/journal.pone.0255955https://doaj.org/article/c470c78a03ae41ffa3c196ce397201ce2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0255955https://doaj.org/toc/1932-6203<h4>Background</h4>Linked color imaging (LCI) has been shown to be effective in multiple randomized controlled trials for enhanced colorectal polyp detection. Recently, artificial intelligence (AI) with deep learning through convolutional neural networks has dramatically improved and is increasingly recognized as a promising new technique for enhancing colorectal polyp detection.<h4>Aim</h4>This study aims to evaluate a newly developed computer-aided detection (CAD) system in combination with LCI for colorectal polyp detection.<h4>Methods</h4>First, a convolutional neural network was trained for colorectal polyp detection in combination with the LCI technique using a dataset of anonymized endoscopy videos. For validation, 240 polyps within fully recorded endoscopy videos in LCI mode, covering the entire spectrum of adenomatous histology, were used. Sensitivity (true-positive rate per lesion) and false-positive frames in a full procedure were assessed.<h4>Results</h4>The new CAD system used in LCI mode could process at least 60 frames per second, allowing for real-time video analysis. Sensitivity (true-positive rate per lesion) was 100%, with no lesion being missed. The calculated false-positive frame rate was 0.001%. Among the 240 polyps, 34 were sessile serrated lesions. The detection rate for sessile serrated lesions with the CAD system used in LCI mode was 100%.<h4>Conclusions</h4>The new CAD system used in LCI mode achieved a 100% sensitivity per lesion and a negligible false-positive frame rate. Note that the new CAD system used in LCI mode also specifically allowed for detection of serrated lesions in all cases. Accordingly, the AI algorithm introduced here for the first time has the potential to dramatically improve the quality of colonoscopy.Helmut NeumannAndreas KreftVisvakanth SivanathanFareed RahmanPeter R GallePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0255955 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Helmut Neumann Andreas Kreft Visvakanth Sivanathan Fareed Rahman Peter R Galle Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.
description	<h4>Background</h4>Linked color imaging (LCI) has been shown to be effective in multiple randomized controlled trials for enhanced colorectal polyp detection. Recently, artificial intelligence (AI) with deep learning through convolutional neural networks has dramatically improved and is increasingly recognized as a promising new technique for enhancing colorectal polyp detection.<h4>Aim</h4>This study aims to evaluate a newly developed computer-aided detection (CAD) system in combination with LCI for colorectal polyp detection.<h4>Methods</h4>First, a convolutional neural network was trained for colorectal polyp detection in combination with the LCI technique using a dataset of anonymized endoscopy videos. For validation, 240 polyps within fully recorded endoscopy videos in LCI mode, covering the entire spectrum of adenomatous histology, were used. Sensitivity (true-positive rate per lesion) and false-positive frames in a full procedure were assessed.<h4>Results</h4>The new CAD system used in LCI mode could process at least 60 frames per second, allowing for real-time video analysis. Sensitivity (true-positive rate per lesion) was 100%, with no lesion being missed. The calculated false-positive frame rate was 0.001%. Among the 240 polyps, 34 were sessile serrated lesions. The detection rate for sessile serrated lesions with the CAD system used in LCI mode was 100%.<h4>Conclusions</h4>The new CAD system used in LCI mode achieved a 100% sensitivity per lesion and a negligible false-positive frame rate. Note that the new CAD system used in LCI mode also specifically allowed for detection of serrated lesions in all cases. Accordingly, the AI algorithm introduced here for the first time has the potential to dramatically improve the quality of colonoscopy.
format	article
author	Helmut Neumann Andreas Kreft Visvakanth Sivanathan Fareed Rahman Peter R Galle
author_facet	Helmut Neumann Andreas Kreft Visvakanth Sivanathan Fareed Rahman Peter R Galle
author_sort	Helmut Neumann
title	Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.
title_short	Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.
title_full	Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.
title_fullStr	Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.
title_full_unstemmed	Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.
title_sort	evaluation of novel lci cad eye system for real time detection of colon polyps.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/c470c78a03ae41ffa3c196ce397201ce
work_keys_str_mv	AT helmutneumann evaluationofnovellcicadeyesystemforrealtimedetectionofcolonpolyps AT andreaskreft evaluationofnovellcicadeyesystemforrealtimedetectionofcolonpolyps AT visvakanthsivanathan evaluationofnovellcicadeyesystemforrealtimedetectionofcolonpolyps AT fareedrahman evaluationofnovellcicadeyesystemforrealtimedetectionofcolonpolyps AT peterrgalle evaluationofnovellcicadeyesystemforrealtimedetectionofcolonpolyps
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Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.

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