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 |
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タイトル |
Artificial intelligence-based diagnosis of the depth of laryngopharyngeal cancer |
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言語 |
en |
作成者 |
Yumii, Kohei
Ueda, Tsutomu
Kawahara, Daisuke
Chikuie, Nobuyuki
Taruya, Takayuki
Hamamoto, Takao
Takeno, Sachio
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アクセス権 |
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アクセス権 |
open access |
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アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
権利情報 |
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言語 |
en |
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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 |
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言語 |
en |
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権利情報 |
This is not the published version. Please cite only the published version. |
権利情報 |
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言語 |
ja |
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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 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
Artificial intelligence (AI) |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
Head and neck cancer |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
Transoral surgery |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
Diagnosis of depth |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
Radiomics |
主題 |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
Deep learning |
内容記述 |
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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. |
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言語 |
en |
出版者 |
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出版者 |
Elsevier |
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言語 |
en |
言語 |
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言語 |
eng |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
出版タイプ |
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出版タイプ |
AM |
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出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
関連情報 |
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関連タイプ |
isVersionOf |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1016/j.anl.2023.09.001 |
助成情報 |
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助成機関名 |
日本学術振興会 |
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言語 |
ja |
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研究課題番号URI |
https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-20K09713/ |
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研究課題番号 |
20K09713 |
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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 |
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言語 |
ja |
助成情報 |
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助成機関名 |
Japan Society for the Promotion of Science |
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言語 |
en |
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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. |
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言語 |
en |
開始ページ |
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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
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旧ID |
55901 |