Standardisation of an AI-based vocal fold assessment tool on a recurrent respiratory papillomatosis model.

Mikolaj Buchwald, Piotr Nogal, Jan Nowak, Szymon Kupinski, Wojciech Andrzejewski, Juliusz Pukacki, Joanna Jackowska, Hanna Klimza, Cezary Mazurek, Alberto Paderno, Cesare Piazza, Małgorzata Wierzbicka
{"title":"Standardisation of an AI-based vocal fold assessment tool on a recurrent respiratory papillomatosis model.","authors":"Mikolaj Buchwald, Piotr Nogal, Jan Nowak, Szymon Kupinski, Wojciech Andrzejewski, Juliusz Pukacki, Joanna Jackowska, Hanna Klimza, Cezary Mazurek, Alberto Paderno, Cesare Piazza, Małgorzata Wierzbicka","doi":"10.14639/0392-100X-N2896","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The assessment of extension of papilloma growth in recurrent respiratory papillomatosis (RRP) on vocal folds can be performed quantitatively utilising artificial intelligence (AI).</p><p><strong>Methods: </strong>This study evaluated the efficacy of an AI-based annotation system, Glottis Coverage - Artificial Intelligence and Deep learning (GC-AID) in 4 patients to assess affected mucosa in white light (WL) and narrow band imaging modalities as a case-study for future applications.</p><p><strong>Results: </strong>In healthy larynges, the mean difference between areas of the right and left vocal folds was minimal (2.6%). For patient # 4, following treatment, RRP coverage in WL decreased from 69.5% to 42.6%. A similar improvement was observed for patient # 1, while no significant benefits were noted for patients # 2 and # 3.</p><p><strong>Conclusions: </strong>The extent of RRP was precisely measured with GC-AID before and after treatment. Obtaining objective, quantitative results was possible with frame extraction and annotation using the system described herein.</p>","PeriodicalId":520544,"journal":{"name":"Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale","volume":"45 4","pages":"244-251"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12456245/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14639/0392-100X-N2896","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: The assessment of extension of papilloma growth in recurrent respiratory papillomatosis (RRP) on vocal folds can be performed quantitatively utilising artificial intelligence (AI).

Methods: This study evaluated the efficacy of an AI-based annotation system, Glottis Coverage - Artificial Intelligence and Deep learning (GC-AID) in 4 patients to assess affected mucosa in white light (WL) and narrow band imaging modalities as a case-study for future applications.

Results: In healthy larynges, the mean difference between areas of the right and left vocal folds was minimal (2.6%). For patient # 4, following treatment, RRP coverage in WL decreased from 69.5% to 42.6%. A similar improvement was observed for patient # 1, while no significant benefits were noted for patients # 2 and # 3.

Conclusions: The extent of RRP was precisely measured with GC-AID before and after treatment. Obtaining objective, quantitative results was possible with frame extraction and annotation using the system described herein.

Abstract Image

Abstract Image

Abstract Image

基于人工智能的复发性呼吸道乳头状瘤模型声带评估工具的标准化。
目的:利用人工智能(AI)对声带复发性呼吸道乳头状瘤病(RRP)的乳头状瘤生长范围进行定量评估。方法:本研究评估了基于人工智能的声门覆盖-人工智能和深度学习(GC-AID)注释系统在白光和窄带成像模式下评估4例患者受影响粘膜的疗效,作为未来应用的案例研究。结果:在健康喉部,左右声带区域的平均差异很小(2.6%)。对于4号患者,在治疗后,WL的RRP覆盖率从69.5%下降到42.6%。患者1号也有类似的改善,而患者2号和患者3号没有明显的改善。结论:GC-AID能准确测定治疗前后的RRP程度。使用本文描述的系统进行帧提取和注释,可以获得客观、定量的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信