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Radiomics and dosiomics for predicting radiation-induced hypothyroidism and guiding intensity-modulated radiotherapy

Authors :
Shan-Shan Yang
Qing-He Peng
Ai-Qian Wu
Bao-Yu Zhang
Zhi-Qiao Liu
En-Ni Chen
Fang-Yun Xie
Pu-Yun OuYang
Chun-Yan Chen
Source :
iScience, Vol 26, Iss 12, Pp 108394- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Summary: To guide individualized intensity-modulated radiotherapy (IMRT), we developed and prospectively validated a multiview radiomics risk model for predicting radiation-induced hypothyroidism in patients with nasopharyngeal carcinoma. And simulated radiotherapy plans with same dose-volume-histogram (DVH) but different dose distributions were redesigned to explore the clinical application of the multiview radiomics risk model. The radiomics and dosiomics were built based on selected radiomics and dosiomics features from planning computed tomography and dose distribution, respectively. The multiview radiomics risk model that integrated radiomics, dosiomics, DVH parameters, and clinical factors had better performance than traditional normal tissue complication probability models. And multiview radiomics risk model could identify differences of patient hypothyroidism-free survival that cannot be stratified by traditional models. Besides, two redesigned simulated plans further verified the clinical application and advantage of the multiview radiomics risk model. The multiview radiomics risk model was a promising method to predict radiation-induced hypothyroidism and guide individualized IMRT.

Details

Language :
English
ISSN :
25890042
Volume :
26
Issue :
12
Database :
Directory of Open Access Journals
Journal :
iScience
Publication Type :
Academic Journal
Accession number :
edsdoj.b8a515f9867437297299b22b6f25006
Document Type :
article
Full Text :
https://doi.org/10.1016/j.isci.2023.108394