{"created":"2025-01-06T04:45:22.414220+00:00","id":2000373,"links":{},"metadata":{"_buckets":{"deposit":"d57a8c27-553f-48df-8d06-a3a94303bb21"},"_deposit":{"created_by":86,"id":"2000373","owner":"86","owners":[86],"pid":{"revision_id":0,"type":"depid","value":"2000373"},"status":"published"},"_oai":{"id":"oai:yamanashi.repo.nii.ac.jp:02000373","sets":["205:1734940925896:1736137967974:1736138060534"]},"author_link":["25168","17898","19056","18956","18089","13008"],"control_number":"2000373","item_30001_access_rights4":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_30001_bibliographic_information17":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2024-07-12","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"7","bibliographicVolumeNumber":"25","bibliographic_titles":[{"bibliographic_title":"Journal of 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Hikaru","creatorNameLang":"en"}],"familyNames":[{"familyName":"根本","familyNameLang":"ja"},{"familyName":"ネモト","familyNameLang":"ja-Kana"},{"familyName":"Nemoto","familyNameLang":"en"}],"givenNames":[{"givenName":"光","givenNameLang":"ja"},{"givenName":"ヒカル","givenNameLang":"ja-Kana"},{"givenName":"Hikaru","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"25168","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"80970441","nameIdentifierScheme":"e-Rad_Researcher","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/search/?kw=80970441"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"13501","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"山梨大学","affiliationNameLang":"ja"},{"affiliationName":"University of Yamanashi","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"齋藤, 正英","creatorNameLang":"ja"},{"creatorName":"サイトウ, マサヒデ","creatorNameLang":"ja-Kana"},{"creatorName":"Saitoh, Masahide","creatorNameLang":"en"}],"familyNames":[{"familyName":"齋藤","familyNameLang":"ja"},{"familyName":"サイトウ","familyNameLang":"ja-Kana"},{"familyName":"Saitoh","familyNameLang":"en"}],"givenNames":[{"givenName":"正英","givenNameLang":"ja"},{"givenName":"マサヒデ","givenNameLang":"ja-Kana"},{"givenName":"Masahide","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"17898","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"80790427","nameIdentifierScheme":"e-Rad_Researcher","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/search/?kw=80790427"}]},{"creatorNames":[{"creatorName":"Satoh, Yoko","creatorNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"13501","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"山梨大学","affiliationNameLang":"ja"},{"affiliationName":"University of Yamanashi","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"小宮山, 貴史","creatorNameLang":"ja"},{"creatorName":"コミヤマ, タカフミ","creatorNameLang":"ja-Kana"},{"creatorName":"Komiyama, Takafumi","creatorNameLang":"en"}],"familyNames":[{"familyName":"小宮山","familyNameLang":"ja"},{"familyName":"コミヤマ","familyNameLang":"ja-Kana"},{"familyName":"Komiyama","familyNameLang":"en"}],"givenNames":[{"givenName":"貴史","givenNameLang":"ja"},{"givenName":"タカフミ","givenNameLang":"ja-Kana"},{"givenName":"Takafumi","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"19056","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"40324206","nameIdentifierScheme":"e-Rad_Researcher","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/search/?kw=40324206"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"13501","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"山梨大学","affiliationNameLang":"ja"},{"affiliationName":"University of Yamanashi","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"萬利乃, 寛","creatorNameLang":"ja"},{"creatorName":"マリノ, カン","creatorNameLang":"ja-Kana"},{"creatorName":"Marino, Kan","creatorNameLang":"en"}],"familyNames":[{"familyName":"萬利乃","familyNameLang":"ja"},{"familyName":"マリノ","familyNameLang":"ja-Kana"},{"familyName":"Marino","familyNameLang":"en"}],"givenNames":[{"givenName":"寛","givenNameLang":"ja"},{"givenName":"カン","givenNameLang":"ja-Kana"},{"givenName":"Kan","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"18956","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"70372505","nameIdentifierScheme":"e-Rad_Researcher","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/search/?kw=70372505"}]},{"creatorNames":[{"creatorName":"Aoki, Shinichi","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Suzuki, Hidekazu","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Sano, Naoki","creatorNameLang":"en"}],"familyNames":[{"familyName":"Sano","familyNameLang":"en"}],"givenNames":[{"givenName":"Naoki","givenNameLang":"en"}]},{"creatorNames":[{"creatorName":"Nonaka, Hotaka,","creatorNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"13501","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"山梨大学","affiliationNameLang":"ja"},{"affiliationName":"University of Yamanashi","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"渡邊, 裕陽","creatorNameLang":"ja"},{"creatorName":"ワタナベ, ヒロアキ","creatorNameLang":"ja-Kana"},{"creatorName":"Watanabe, Hiroaki","creatorNameLang":"en"}],"familyNames":[{"familyName":"渡邊","familyNameLang":"ja"},{"familyName":"ワタナベ","familyNameLang":"ja-Kana"},{"familyName":"Watanabe","familyNameLang":"en"}],"givenNames":[{"givenName":"裕陽","givenNameLang":"ja"},{"givenName":"ヒロアキ","givenNameLang":"ja-Kana"},{"givenName":"Hiroaki","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"18089","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Funayama, Satoshi","creatorNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"13501","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"山梨大学","affiliationNameLang":"ja"},{"affiliationName":"University of Yamanashi","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"大西, 洋","creatorNameLang":"ja"},{"creatorName":"オオニシ, ヒロシ","creatorNameLang":"ja-Kana"},{"creatorName":"Onishi, Hiroshi","creatorNameLang":"en"}],"familyNames":[{"familyName":"大西","familyNameLang":"ja"},{"familyName":"オオニシ","familyNameLang":"ja-Kana"},{"familyName":"Onishi","familyNameLang":"en"}],"givenNames":[{"givenName":"洋","givenNameLang":"ja"},{"givenName":"ヒロシ","givenNameLang":"ja-Kana"},{"givenName":"Hiroshi","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"13008","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"30213804","nameIdentifierScheme":"e-Rad_Researcher","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/search/?kw=30213804"}]}]},"item_30001_description8":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"Purpose: Predicting recurrence following stereotactic body radiotherapy (SBRT) for non-small cell lung cancer provides important information for the feasibility of the individualized radiotherapy and allows to select the appropriate treatment strategy based on the risk of recurrence. In this study, we evaluated the performance of both machine learning models using positron emission tomography (PET) and computed tomography (CT) radiomic features for predicting recurrence after SBRT. \nMethods: Planning CT and PET images of 82 non-small cell lung cancer patients who performed SBRT at our hospital were used. First, tumors were delineated on each CT and PET of each patient, and 111 unique radiomic features were extracted, respectively. Next, the 10 features were selected using three different feature selection algorithms, respectively. Recurrence prediction models based on the selected features and four different machine learning algorithms were developed, respectively. Finally, we compared the predictive performance of each model for each recurrence pattern using the mean area under the curve (AUC) calculated following the 0.632+ bootstrap method.\nResults: The highest performance for local recurrence, regional lymph node metastasis, and distant metastasis were observed in models using Support vector machine with PET features (mean AUC = 0.646), Naive Bayes with PET features (mean AUC = 0.611), and Support vector machine with CT features (mean AUC = 0.645), respectively.\nConclusions: We comprehensively evaluated the performance of prediction model developed for recurrence following SBRT. The model in this study would provide information to predict the recurrence pattern and assist in making treatment strategies.","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_30001_file22":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2025-01-07"}],"displaytype":"detail","filename":"Journal of Applied Clinical Medical Physics25_7_e14322.pdf","filesize":[{"value":"1.6 MB"}],"format":"application/pdf","licensetype":"license_0","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://yamanashi.repo.nii.ac.jp/record/2000373/files/Journal of Applied Clinical Medical Physics25_7_e14322.pdf"},"version_id":"fd946161-aeb4-4b98-bc50-49410155f18e"}]},"item_30001_language10":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_30001_publisher9":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Wiley","subitem_publisher_language":"en"},{"subitem_publisher":"The American Association of Physicists in Medicine","subitem_publisher_language":"en"}]},"item_30001_relation14":{"attribute_name":"関連情報","attribute_value_mlt":[{"subitem_relation_type":"isIdenticalTo","subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.1002/acm2.14322","subitem_relation_type_select":"DOI"}}]},"item_30001_resource_type11":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_30001_rights5":{"attribute_name":"権利情報","attribute_value_mlt":[{"subitem_rights":"Creative Commons Attribution 4.0 International (CC BY 4.0)","subitem_rights_language":"en","subitem_rights_resource":"https://creativecommons.org/licenses/by/4.0/"},{"subitem_rights":"© 2024 The Authors","subitem_rights_language":"en"}]},"item_30001_source_identifier16":{"attribute_name":"収録物識別子","attribute_value_mlt":[{"subitem_source_identifier":"1526-9914","subitem_source_identifier_type":"PISSN"},{"subitem_source_identifier":"1526-9914","subitem_source_identifier_type":"EISSN"}]},"item_30001_subject7":{"attribute_name":"主題","attribute_value_mlt":[{"subitem_subject":"lung cancer","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"machine learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"PET imaging","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"radiomics","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"SBRT","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_30001_title0":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study","subitem_title_language":"en"}]},"item_30001_version_type12":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_title":"Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study","item_type_id":"40035","owner":"86","path":["1736138060534"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2025-01-06"},"publish_date":"2025-01-06","publish_status":"0","recid":"2000373","relation_version_is_last":true,"title":["Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study"],"weko_creator_id":"86","weko_shared_id":-1},"updated":"2025-02-06T07:33:33.878030+00:00"}