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MRI-based radiomics for pretreatment prediction of response to concurrent chemoradiotherapy in locally advanced cervical squamous cell cancer.

Authors :
Zhang, Xiaomiao
Zhang, Qi
Chen, Yan
Wang, Sicong
Zhang, Jieying
An, Jusheng
Xie, Lizhi
Yu, Xiaoduo
Zhao, Xinming
Source :
Abdominal Radiology; Jan2023, Vol. 48 Issue 1, p367-376, 10p
Publication Year :
2023

Abstract

Purpose: To investigate the value of magnetic resonance imaging (MRI)-based radiomics in predicting the treatment response to concurrent chemoradiotherapy (CCRT) in patients with locally advanced cervical squamous cell cancer (LACSC). Methods: In total, 198 patients (training: n = 138; testing: n = 60) with LACSC treated with CCRT between January 2014 and December 2019 were retrospectively enrolled in this study. Responses were evaluated by MRI and clinical data performed at one month after completion of CCRT according to RECIST standards, and patients were divided into the residual group and nonresidual group. Overall, 200 radiomics features were extracted from T2-weighted imaging and apparent diffusion coefficient maps. The radiomics score (Rad-score) was constructed with a feature selection strategy. Logistic regression analysis was used for multivariate analysis of radiomics features and clinical variables. The performance of all models was assessed using receiver operating characteristic curves. Results: Among the clinical variables, tumor grade and FIGO stage were independent risk factors, and the areas under the curve (AUCs) of the clinical model were 0.741 and 0.749 in the training and testing groups. The Rad-score, consisting of 4 radiomics features selected from 200 radiomics features, showed good predictive performance with an AUC of 0.819 in the training group and 0.776 in the testing group, which were higher than the clinical model, but the difference was not statistically significant. The combined model constructed with tumor grade, FIGO stage, and Rad-score achieved the best performance, with an AUC of 0.857 in the training group and 0.842 in the testing group, which were significantly higher than the clinical model. Conclusion: MRI-based radiomics features could be used as a noninvasive biomarker to improve the ability to predict the treatment response to CCRT in patients with LACSC. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2366004X
Volume :
48
Issue :
1
Database :
Complementary Index
Journal :
Abdominal Radiology
Publication Type :
Academic Journal
Accession number :
161360651
Full Text :
https://doi.org/10.1007/s00261-022-03665-4