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Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging

OBJECTIVE: Detecting dysthyroid optic neuropathy (DON) in the early stages is vital for clinical decision-making. The aim of this study was to determine the feasibility of using an optic-nerve-based radiomics nomogram on water-fat imaging for detecting DON. METHODS: This study included 104 orbits (8...

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Autores principales: Wu, Hongyu, Luo, Ban, Zhao, Yali, Yuan, Gang, Wang, Qiuxia, Liu, Ping, Zhai, Linhan, Lv, Wenzhi, Zhang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9509517/
https://www.ncbi.nlm.nih.gov/pubmed/36153469
http://dx.doi.org/10.1186/s13244-022-01292-7
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author Wu, Hongyu
Luo, Ban
Zhao, Yali
Yuan, Gang
Wang, Qiuxia
Liu, Ping
Zhai, Linhan
Lv, Wenzhi
Zhang, Jing
author_facet Wu, Hongyu
Luo, Ban
Zhao, Yali
Yuan, Gang
Wang, Qiuxia
Liu, Ping
Zhai, Linhan
Lv, Wenzhi
Zhang, Jing
author_sort Wu, Hongyu
collection PubMed
description OBJECTIVE: Detecting dysthyroid optic neuropathy (DON) in the early stages is vital for clinical decision-making. The aim of this study was to determine the feasibility of using an optic-nerve-based radiomics nomogram on water-fat imaging for detecting DON. METHODS: This study included 104 orbits (83 in the training cohort) from 59 DON patients and 131 orbits (80 in the training cohort) from 69 thyroid-associated ophthalmopathy (TAO) without DON patients. Radiomic features were extracted from the optic-nerve T2-weighted water-fat images for each patient. Selected radiomics features were retrained to construct the radiomic signature model and calculate the radiomic score (Rad-score). The conventional MRI evaluation model was constructed based on apical crowding sign, optic-nerve stretching sign and muscle index. The radiomics nomogram model combining the Rad-score and conventional MRI evaluation factors was then developed. Predictive performance of the three models was assessed using ROC curves. RESULTS: Eight radiomics features from water-fat imaging were selected to build the radiomics signature. The radiomics nomogram (based on Rad-score, apical crowding sign and optic-nerve stretching sign) had superior diagnostic performance than did the conventional MRI evaluation model (AUC in the training set: 0.92 vs 0.80, the validation set:0.88 vs 0.75). Decision curve analysis confirmed the clinical usefulness of the radiomics nomogram. CONCLUSIONS: This optic-nerve-based radiomics nomogram showed better diagnostic performance than conventional MRI evaluation for differentiating DON from TAO without DON. The changes of the optic-nerve itself may deserve more consideration in the clinical decision-making process. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-022-01292-7.
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spelling pubmed-95095172022-10-20 Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging Wu, Hongyu Luo, Ban Zhao, Yali Yuan, Gang Wang, Qiuxia Liu, Ping Zhai, Linhan Lv, Wenzhi Zhang, Jing Insights Imaging Original Article OBJECTIVE: Detecting dysthyroid optic neuropathy (DON) in the early stages is vital for clinical decision-making. The aim of this study was to determine the feasibility of using an optic-nerve-based radiomics nomogram on water-fat imaging for detecting DON. METHODS: This study included 104 orbits (83 in the training cohort) from 59 DON patients and 131 orbits (80 in the training cohort) from 69 thyroid-associated ophthalmopathy (TAO) without DON patients. Radiomic features were extracted from the optic-nerve T2-weighted water-fat images for each patient. Selected radiomics features were retrained to construct the radiomic signature model and calculate the radiomic score (Rad-score). The conventional MRI evaluation model was constructed based on apical crowding sign, optic-nerve stretching sign and muscle index. The radiomics nomogram model combining the Rad-score and conventional MRI evaluation factors was then developed. Predictive performance of the three models was assessed using ROC curves. RESULTS: Eight radiomics features from water-fat imaging were selected to build the radiomics signature. The radiomics nomogram (based on Rad-score, apical crowding sign and optic-nerve stretching sign) had superior diagnostic performance than did the conventional MRI evaluation model (AUC in the training set: 0.92 vs 0.80, the validation set:0.88 vs 0.75). Decision curve analysis confirmed the clinical usefulness of the radiomics nomogram. CONCLUSIONS: This optic-nerve-based radiomics nomogram showed better diagnostic performance than conventional MRI evaluation for differentiating DON from TAO without DON. The changes of the optic-nerve itself may deserve more consideration in the clinical decision-making process. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-022-01292-7. Springer Vienna 2022-09-24 /pmc/articles/PMC9509517/ /pubmed/36153469 http://dx.doi.org/10.1186/s13244-022-01292-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Wu, Hongyu
Luo, Ban
Zhao, Yali
Yuan, Gang
Wang, Qiuxia
Liu, Ping
Zhai, Linhan
Lv, Wenzhi
Zhang, Jing
Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging
title Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging
title_full Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging
title_fullStr Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging
title_full_unstemmed Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging
title_short Radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging
title_sort radiomics analysis of the optic nerve for detecting dysthyroid optic neuropathy, based on water-fat imaging
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9509517/
https://www.ncbi.nlm.nih.gov/pubmed/36153469
http://dx.doi.org/10.1186/s13244-022-01292-7
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