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MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma

Authors :
Yu-Jun Hu
Lin Zhang
You-Ping Xiao
Tian-Zhu Lu
Qiao-Juan Guo
Shao-Jun Lin
Lan Liu
Yun-Bin Chen
Zi-Lu Huang
Ya Liu
Yong Su
Li-Zhi Liu
Xiao-Chang Gong
Jian-Ji Pan
Jin-Gao Li
Yun-Fei Xia
Source :
iScience, Vol 26, Iss 6, Pp 106932- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Summary: 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.

Details

Language :
English
ISSN :
25890042
Volume :
26
Issue :
6
Database :
Directory of Open Access Journals
Journal :
iScience
Publication Type :
Academic Journal
Accession number :
edsdoj.490622e260074dbe84646266b2c2d068
Document Type :
article
Full Text :
https://doi.org/10.1016/j.isci.2023.106932