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Artificial intelligence-based diagnosis of the depth of laryngopharyngeal cancer

https://hiroshima.repo.nii.ac.jp/records/2006351
https://hiroshima.repo.nii.ac.jp/records/2006351
e212115b-68eb-4bd0-b2be-4c7eb8ee2fc0
名前 / ファイル ライセンス アクション
ANL_51_417.pdf ANL_51_417.pdf (4.1 MB)
Item type デフォルトアイテムタイプ_(フル)(1)
公開日 2024-12-25
タイトル
タイトル Artificial intelligence-based diagnosis of the depth of laryngopharyngeal cancer
言語 en
作成者 Yumii, Kohei

× Yumii, Kohei

en Yumii, Kohei

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Ueda, Tsutomu

× Ueda, Tsutomu

en Ueda, Tsutomu

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Kawahara, Daisuke

× Kawahara, Daisuke

en Kawahara, Daisuke

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Chikuie, Nobuyuki

× Chikuie, Nobuyuki

en Chikuie, Nobuyuki

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Taruya, Takayuki

× Taruya, Takayuki

en Taruya, Takayuki

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Hamamoto, Takao

× Hamamoto, Takao

en Hamamoto, Takao

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Takeno, Sachio

× Takeno, Sachio

en Takeno, Sachio

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アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利情報
言語 en
権利情報 © 2023. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
権利情報
言語 en
権利情報 This is not the published version. Please cite only the published version.
権利情報
言語 ja
権利情報 この論文は出版社版ではありません。引用の際には出版社版をご確認、ご利用ください。
主題
言語 en
主題Scheme Other
主題 Artificial intelligence (AI)
主題
言語 en
主題Scheme Other
主題 Head and neck cancer
主題
言語 en
主題Scheme Other
主題 Transoral surgery
主題
言語 en
主題Scheme Other
主題 Diagnosis of depth
主題
言語 en
主題Scheme Other
主題 Radiomics
主題
言語 en
主題Scheme Other
主題 Deep learning
内容記述
内容記述 Objective Transoral surgery (TOS) is a widely used treatment for laryngopharyngeal cancer. There are some difficult cases of setting the extent of resection in TOS, particularly in setting the vertical margins. However, positive vertical margins require additional treatment. Further, excessive resection should be avoided as it increases the risk of bleeding as a postoperative complication and may lead to decreased quality of life, such as dysphagia. Considering these issues, determining the extent of resection in TOS is an important consideration. In this study, we investigated the possibility of accurately diagnosing the depth of laryngopharyngeal cancer using radiomics, an image analysis method based on artificial intelligence (AI). Methods We included esophagogastroduodenoscopic images of 95 lesions that were pathologically diagnosed as squamous cell carcinoma (SCC) and treated with transoral surgery at our institution between August 2009 and April 2020. Of the 95 lesions, 54 were SCC in situ, and 41 were SCC. Radiomics analysis was performed on 95 upper gastrointestinal endoscopic NBI images of these lesions to evaluate their diagnostic performance for the presence of subepithelial invasion. The lesions in the endoscopic images were manually delineated, and the accuracy, sensitivity, specificity, and area under the curve (AUC) were evaluated from the features obtained using least absolute shrinkage and selection operator analysis. In addition, the results were compared with the depth predictions made by skilled endoscopists. Results In the Radiomics study, the average cross-validation was 0.833. The mean AUC for cross-validation calculated from the receiver operating characteristic curve was 0.868. These results were equivalent to those of the diagnosis made by a skilled endoscopist. Conclusion The diagnosis of laryngopharyngeal cancer depth using radiomics analysis has potential clinical applications. We plan to use it in actual surgery in the future and prospectively study whether it can be used for diagnosis.
言語 en
出版者
出版者 Elsevier
言語 en
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
出版タイプ
出版タイプ AM
出版タイプResource http://purl.org/coar/version/c_ab4af688f83e57aa
関連情報
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1016/j.anl.2023.09.001
助成情報
助成機関名 日本学術振興会
言語 ja
研究課題番号URI https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-20K09713/
研究課題番号 20K09713
研究課題名 頭頸部癌における人工知能を用いた内視鏡と経口超音波による超高精度診断モデルの開発
言語 ja
助成情報
助成機関名 Japan Society for the Promotion of Science
言語 en
研究課題名 Development of an ultra-high-precision diagnostic model using endoscopy and oral ultrasound with artificial intelligence in head and neck cancer.
言語 en
開始ページ
開始ページ 417
書誌情報 en : Auris Nasus Larynx

巻 51, 号 2, p. 417-424, 発行日 2023-10-12
旧ID 55901
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