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Disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy

Purpose: Thyroid-associated ophthalmopathy (TAO) is an autoimmune disease that affects the orbit and is the most prevalent extra-thyroidal complication of Graves’ disease. Previous neuroimaging studies have focused on abnormal static regional activity and functional connectivity in patients with TAO...

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Autores principales: Wen, Zhi, Kang, Yan, Zhang, Yu, Yang, Huaguang, Zhao, Yilin, Huang, Xin, Xie, Baojun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213541/
https://www.ncbi.nlm.nih.gov/pubmed/37250893
http://dx.doi.org/10.3389/fcell.2023.1174688
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author Wen, Zhi
Kang, Yan
Zhang, Yu
Yang, Huaguang
Zhao, Yilin
Huang, Xin
Xie, Baojun
author_facet Wen, Zhi
Kang, Yan
Zhang, Yu
Yang, Huaguang
Zhao, Yilin
Huang, Xin
Xie, Baojun
author_sort Wen, Zhi
collection PubMed
description Purpose: Thyroid-associated ophthalmopathy (TAO) is an autoimmune disease that affects the orbit and is the most prevalent extra-thyroidal complication of Graves’ disease. Previous neuroimaging studies have focused on abnormal static regional activity and functional connectivity in patients with TAO. However, the characteristics of local brain activity over time are poorly understood. This study aimed to investigate alterations in the dynamic amplitude of low-frequency fluctuation (dALFF) in patients with active TAO and to distinguish patients with TAO from healthy controls (HCs) using a support vector machine (SVM) classifier. Methods: A total of 21 patients with TAO and 21 HCs underwent resting-state functional magnetic resonance imaging scans. dALFFs were calculated in conjunction with sliding window approaches to assess dynamic regional brain activity and to compare the groups. Then, we used SVM, a machine learning algorithm, to determine whether dALFF maps may be used as diagnostic indicators for TAO. Results: Compared with HCs, patients with active TAO showed decreased dALFF in the right calcarine, lingual gyrus, superior parietal lobule, and precuneus. The SVM model showed an accuracy of 45.24%–47.62% and area under the curve of 0.35–0.44 in distinguishing TAO from HCs. No correlation was found between clinical variables and regional dALFF. Conclusion: Patients with active TAO showed altered dALFF in the visual cortex and the ventral and dorsal visual pathways, providing further details on the pathogenesis of TAO.
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spelling pubmed-102135412023-05-27 Disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy Wen, Zhi Kang, Yan Zhang, Yu Yang, Huaguang Zhao, Yilin Huang, Xin Xie, Baojun Front Cell Dev Biol Cell and Developmental Biology Purpose: Thyroid-associated ophthalmopathy (TAO) is an autoimmune disease that affects the orbit and is the most prevalent extra-thyroidal complication of Graves’ disease. Previous neuroimaging studies have focused on abnormal static regional activity and functional connectivity in patients with TAO. However, the characteristics of local brain activity over time are poorly understood. This study aimed to investigate alterations in the dynamic amplitude of low-frequency fluctuation (dALFF) in patients with active TAO and to distinguish patients with TAO from healthy controls (HCs) using a support vector machine (SVM) classifier. Methods: A total of 21 patients with TAO and 21 HCs underwent resting-state functional magnetic resonance imaging scans. dALFFs were calculated in conjunction with sliding window approaches to assess dynamic regional brain activity and to compare the groups. Then, we used SVM, a machine learning algorithm, to determine whether dALFF maps may be used as diagnostic indicators for TAO. Results: Compared with HCs, patients with active TAO showed decreased dALFF in the right calcarine, lingual gyrus, superior parietal lobule, and precuneus. The SVM model showed an accuracy of 45.24%–47.62% and area under the curve of 0.35–0.44 in distinguishing TAO from HCs. No correlation was found between clinical variables and regional dALFF. Conclusion: Patients with active TAO showed altered dALFF in the visual cortex and the ventral and dorsal visual pathways, providing further details on the pathogenesis of TAO. Frontiers Media S.A. 2023-05-12 /pmc/articles/PMC10213541/ /pubmed/37250893 http://dx.doi.org/10.3389/fcell.2023.1174688 Text en Copyright © 2023 Wen, Kang, Zhang, Yang, Zhao, Huang and Xie. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cell and Developmental Biology
Wen, Zhi
Kang, Yan
Zhang, Yu
Yang, Huaguang
Zhao, Yilin
Huang, Xin
Xie, Baojun
Disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy
title Disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy
title_full Disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy
title_fullStr Disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy
title_full_unstemmed Disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy
title_short Disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy
title_sort disrupted dynamic amplitude of low-frequency fluctuations in patients with active thyroid-associated ophthalmopathy
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213541/
https://www.ncbi.nlm.nih.gov/pubmed/37250893
http://dx.doi.org/10.3389/fcell.2023.1174688
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