| Item type |
文献 / Documents(1) |
| 公開日 |
2023-03-27 |
| アクセス権 |
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アクセス権 |
open access |
| 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 |
|
資源タイプ |
journal article |
| 出版社版DOI |
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|
関連識別子 |
https://doi.org/10.1093/jrr/rrab104 |
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関連名称 |
10.1093/jrr/rrab104 |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 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 |
| タイトル別表記 |
|
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その他のタイトル |
Prediction of recurrence after chemoradiotherapy |
| 著者 |
生島, 仁史
芳賀, 昭弘
アンドウ, ケン
カトウ, シンゴ
カネヤス, ユウコ
ウノ, タカシ
オコノギ, ノリユキ
ヨシダ, ケンジ
アリガ, タクロウ
イソハシ, フミアキ
ハリマ, ヨウコ
カネモト, アヤエ
イイ, ノリコ
ワカツキ, マサル
オオノ, タツヤ
|
| 抄録 |
|
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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. |
| キーワード |
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|
主題 |
cervical cancer |
| キーワード |
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|
主題 |
chemoradiotherapy |
| キーワード |
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|
主題 |
MRI |
| キーワード |
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|
主題 |
out-of-field recurrence (OFR) |
| キーワード |
|
|
主題 |
prediction |
| キーワード |
|
|
主題 |
radiomics |
| 書誌情報 |
en : Journal of Radiation Research
巻 63,
号 1,
p. 98-106,
発行日 2021-12-03
|
| 収録物ID |
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収録物識別子タイプ |
ISSN |
|
収録物識別子 |
13499157 |
| 収録物ID |
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|
収録物識別子タイプ |
NCID |
|
収録物識別子 |
AA00705792 |
| 出版者 |
|
|
出版者 |
Oxford University Press |
| 出版者 |
|
|
出版者 |
The Japanese Radiation Research Society |
| 出版者 |
|
|
出版者 |
Japanese Society for Radiation Oncology |
| 権利情報 |
|
|
権利情報 |
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
| EID |
|
|
識別子 |
383378 |
| 言語 |
|
|
言語 |
eng |
jrr_63_1_98.pdf (799 KB)
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