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MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma
Chemotherapy remains controversial for stage II nasopharyngeal carcinoma because of its considerable prognostic heterogeneity. We aimed to develop an MRI-based deep learning model for predicting distant metastasis and assessing chemotherapy efficacy in stage II nasopharyngeal carcinoma. This multice...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291473/ https://www.ncbi.nlm.nih.gov/pubmed/37378335 http://dx.doi.org/10.1016/j.isci.2023.106932 |
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author | Hu, Yu-Jun Zhang, Lin Xiao, You-Ping Lu, Tian-Zhu Guo, Qiao-Juan Lin, Shao-Jun Liu, Lan Chen, Yun-Bin Huang, Zi-Lu Liu, Ya Su, Yong Liu, Li-Zhi Gong, Xiao-Chang Pan, Jian-Ji Li, Jin-Gao Xia, Yun-Fei |
author_facet | Hu, Yu-Jun Zhang, Lin Xiao, You-Ping Lu, Tian-Zhu Guo, Qiao-Juan Lin, Shao-Jun Liu, Lan Chen, Yun-Bin Huang, Zi-Lu Liu, Ya Su, Yong Liu, Li-Zhi Gong, Xiao-Chang Pan, Jian-Ji Li, Jin-Gao Xia, Yun-Fei |
author_sort | Hu, Yu-Jun |
collection | PubMed |
description | Chemotherapy remains controversial for stage II nasopharyngeal carcinoma because of its considerable prognostic heterogeneity. We aimed to develop an MRI-based deep learning model for predicting distant metastasis and assessing chemotherapy efficacy in stage II nasopharyngeal carcinoma. This multicenter retrospective study enrolled 1072 patients from three Chinese centers for training (Center 1, n = 575) and external validation (Centers 2 and 3, n = 497). The deep learning model significantly predicted the risk of distant metastases for stage II nasopharyngeal carcinoma and was validated in the external validation cohort. In addition, the deep learning model outperformed the clinical and radiomics models in terms of predictive performance. Furthermore, the deep learning model facilitates the identification of high-risk patients who could benefit from chemotherapy, providing useful additional information for individualized treatment decisions. |
format | Online Article Text |
id | pubmed-10291473 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-102914732023-06-27 MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma Hu, Yu-Jun Zhang, Lin Xiao, You-Ping Lu, Tian-Zhu Guo, Qiao-Juan Lin, Shao-Jun Liu, Lan Chen, Yun-Bin Huang, Zi-Lu Liu, Ya Su, Yong Liu, Li-Zhi Gong, Xiao-Chang Pan, Jian-Ji Li, Jin-Gao Xia, Yun-Fei iScience Article Chemotherapy remains controversial for stage II nasopharyngeal carcinoma because of its considerable prognostic heterogeneity. We aimed to develop an MRI-based deep learning model for predicting distant metastasis and assessing chemotherapy efficacy in stage II nasopharyngeal carcinoma. This multicenter retrospective study enrolled 1072 patients from three Chinese centers for training (Center 1, n = 575) and external validation (Centers 2 and 3, n = 497). The deep learning model significantly predicted the risk of distant metastases for stage II nasopharyngeal carcinoma and was validated in the external validation cohort. In addition, the deep learning model outperformed the clinical and radiomics models in terms of predictive performance. Furthermore, the deep learning model facilitates the identification of high-risk patients who could benefit from chemotherapy, providing useful additional information for individualized treatment decisions. Elsevier 2023-05-19 /pmc/articles/PMC10291473/ /pubmed/37378335 http://dx.doi.org/10.1016/j.isci.2023.106932 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Hu, Yu-Jun Zhang, Lin Xiao, You-Ping Lu, Tian-Zhu Guo, Qiao-Juan Lin, Shao-Jun Liu, Lan Chen, Yun-Bin Huang, Zi-Lu Liu, Ya Su, Yong Liu, Li-Zhi Gong, Xiao-Chang Pan, Jian-Ji Li, Jin-Gao Xia, Yun-Fei MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma |
title | MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma |
title_full | MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma |
title_fullStr | MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma |
title_full_unstemmed | MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma |
title_short | MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma |
title_sort | mri-based deep learning model predicts distant metastasis and chemotherapy benefit in stage ii nasopharyngeal carcinoma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10291473/ https://www.ncbi.nlm.nih.gov/pubmed/37378335 http://dx.doi.org/10.1016/j.isci.2023.106932 |
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