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Prediction of out-of-field recurrence after chemoradiotherapy for cervical cancer using a combination model of clinical parameters and magnetic resonance imaging radiomics: a multi-institutional study of the Japanese Radiation Oncology Study Group
https://repo.qst.go.jp/records/85033
https://repo.qst.go.jp/records/85033b90889a2-3910-473f-a1c4-599a1977d531
Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2021-12-10 | |||||
タイトル | ||||||
タイトル | Prediction of out-of-field recurrence after chemoradiotherapy for cervical cancer using a combination model of clinical parameters and magnetic resonance imaging radiomics: a multi-institutional study of the Japanese Radiation Oncology Study Group | |||||
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 | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
Ikushima, Hitoshi
× Ikushima, Hitoshi× Haga, Akihiro× Ando, Ken× Kato, Shingo× Kaneyasu, Yuko× Uno, Takashi× Okonogi, Noriyuki× Yoshida, Kenji× Ariga, Takuro× Isohashi, Fumiaki× Harima, Yoko× Kanemoto, Ayae× Ii, Noriko× Wakatsuki, Masaru× Ohno, Tatsuya× Ken, Ando× Shingo, Kato× Takashi, Uno× Noriyuki, Okonogi× Kenji, Yoshida× Takuro, Ariga× Masaru, Wakatsuki× Tatsuya, Ohno |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | We retrospectively assessed whether magnetic resonance imaging (MRI) radiomics combined with clinical parameters can improve the predictability of out-of-field recurrence (OFR) of cervical cancer after chemoradiotherapy. The data set was collected from 204 patients with stage IIB (FIGO: International Federation of Gynecology and Obstetrics 2008) cervical cancer who underwent chemoradiotherapy at 14 Japanese institutes. Of these, 180 patients were finally included for analysis. OFR-free survival was calculated using the Kaplan-Meier method, and the statistical significance of clinicopathological parameters for the OFR-free survival was evaluated using the log-rank test and Cox proportional-hazards model. Prediction of OFR from the analysis of diffusion-weighted images (DWI) and T2-weighted images of pretreatment MRI was done using the least absolute shrinkage and selection operator (LASSO) model for engineering image feature extraction. The accuracy of prediction was evaluated by 5-fold cross-validation of the receiver operating characteristic (ROC) analysis. Para-aortic lymph node metastasis (p = 0.003) was a significant prognostic factor in univariate and multivariate analyses. ROC analysis showed an area under the curve (AUC) of 0.709 in predicting OFR using the pretreatment status of para-aortic lymph node metastasis, 0.667 using the LASSO model for DWIs and 0.602 using T2 weighted images. The AUC improved to 0.734 upon combining the pretreatment status of para-aortic lymph node metastasis with that from the LASSO model for DWIs. Combining MRI radiomics with clinical parameters improved the accuracy of predicting OFR after chemoradiotherapy for locally advanced cervical cancer. | |||||
書誌情報 |
Journal of radiation research 巻 63, 号 1, p. 98-106, 発行日 2021-12 |
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出版者 | ||||||
出版者 | Oxford University Press | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0449-3060 | |||||
PubMed番号 | ||||||
識別子タイプ | PMID | |||||
関連識別子 | 34865079 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1093/jrr/rrab104 | |||||
関連サイト | ||||||
識別子タイプ | URI | |||||
関連識別子 | https://academic.oup.com/jrr/article/63/1/98/6448467?login=true |