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Metabolic Brain Network Analysis With (18)F-FDG PET in a Rat Model of Neuropathic Pain
Neuropathic pain has been found to be related to profound reorganization in the function and structure of the brain. We previously demonstrated changes in local brain activity and functional/metabolic connectivity among selected brain regions by using neuroimaging methods. The present study further...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8284720/ https://www.ncbi.nlm.nih.gov/pubmed/34276529 http://dx.doi.org/10.3389/fneur.2021.566119 |
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author | Huo, Bei-Bei Zheng, Mou-Xiong Hua, Xu-Yun Shen, Jun Wu, Jia-Jia Xu, Jian-Guang |
author_facet | Huo, Bei-Bei Zheng, Mou-Xiong Hua, Xu-Yun Shen, Jun Wu, Jia-Jia Xu, Jian-Guang |
author_sort | Huo, Bei-Bei |
collection | PubMed |
description | Neuropathic pain has been found to be related to profound reorganization in the function and structure of the brain. We previously demonstrated changes in local brain activity and functional/metabolic connectivity among selected brain regions by using neuroimaging methods. The present study further investigated large-scale metabolic brain network changes in 32 Sprague–Dawley rats with right brachial plexus avulsion injury (BPAI). Graph theory was applied in the analysis of 2-deoxy-2-[18F] fluoro-D-glucose ((18)F-FDG) PET images. Inter-subject metabolic networks were constructed by calculating correlation coefficients. Global and nodal network properties were calculated and comparisons between pre- and post-BPAI (7 days) status were conducted. The global network properties (including global efficiency, local efficiency and small-world index) and nodal betweenness centrality did not significantly change for all selected sparsity thresholds following BPAI (p > 0.05). As for nodal network properties, both nodal degree and nodal efficiency measures significantly increased in the left caudate putamen, left medial prefrontal cortex, and right caudate putamen (p < 0.001). The right entorhinal cortex showed a different nodal degree (p < 0.05) but not nodal efficiency. These four regions were selected for seed-based metabolic connectivity analysis. Strengthened connectivity was found among these seeds and distributed brain regions including sensorimotor area, cognitive area, and limbic system, etc. (p < 0.05). Our results indicated that the brain had the resilience to compensate for BPAI-induced neuropathic pain. However, the importance of bilateral caudate putamen, left medial prefrontal cortex, and right entorhinal cortex in the network was strengthened, as well as most of their connections with distributed brain regions. |
format | Online Article Text |
id | pubmed-8284720 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82847202021-07-17 Metabolic Brain Network Analysis With (18)F-FDG PET in a Rat Model of Neuropathic Pain Huo, Bei-Bei Zheng, Mou-Xiong Hua, Xu-Yun Shen, Jun Wu, Jia-Jia Xu, Jian-Guang Front Neurol Neurology Neuropathic pain has been found to be related to profound reorganization in the function and structure of the brain. We previously demonstrated changes in local brain activity and functional/metabolic connectivity among selected brain regions by using neuroimaging methods. The present study further investigated large-scale metabolic brain network changes in 32 Sprague–Dawley rats with right brachial plexus avulsion injury (BPAI). Graph theory was applied in the analysis of 2-deoxy-2-[18F] fluoro-D-glucose ((18)F-FDG) PET images. Inter-subject metabolic networks were constructed by calculating correlation coefficients. Global and nodal network properties were calculated and comparisons between pre- and post-BPAI (7 days) status were conducted. The global network properties (including global efficiency, local efficiency and small-world index) and nodal betweenness centrality did not significantly change for all selected sparsity thresholds following BPAI (p > 0.05). As for nodal network properties, both nodal degree and nodal efficiency measures significantly increased in the left caudate putamen, left medial prefrontal cortex, and right caudate putamen (p < 0.001). The right entorhinal cortex showed a different nodal degree (p < 0.05) but not nodal efficiency. These four regions were selected for seed-based metabolic connectivity analysis. Strengthened connectivity was found among these seeds and distributed brain regions including sensorimotor area, cognitive area, and limbic system, etc. (p < 0.05). Our results indicated that the brain had the resilience to compensate for BPAI-induced neuropathic pain. However, the importance of bilateral caudate putamen, left medial prefrontal cortex, and right entorhinal cortex in the network was strengthened, as well as most of their connections with distributed brain regions. Frontiers Media S.A. 2021-07-02 /pmc/articles/PMC8284720/ /pubmed/34276529 http://dx.doi.org/10.3389/fneur.2021.566119 Text en Copyright © 2021 Huo, Zheng, Hua, Shen, Wu and Xu. 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 | Neurology Huo, Bei-Bei Zheng, Mou-Xiong Hua, Xu-Yun Shen, Jun Wu, Jia-Jia Xu, Jian-Guang Metabolic Brain Network Analysis With (18)F-FDG PET in a Rat Model of Neuropathic Pain |
title | Metabolic Brain Network Analysis With (18)F-FDG PET in a Rat Model of Neuropathic Pain |
title_full | Metabolic Brain Network Analysis With (18)F-FDG PET in a Rat Model of Neuropathic Pain |
title_fullStr | Metabolic Brain Network Analysis With (18)F-FDG PET in a Rat Model of Neuropathic Pain |
title_full_unstemmed | Metabolic Brain Network Analysis With (18)F-FDG PET in a Rat Model of Neuropathic Pain |
title_short | Metabolic Brain Network Analysis With (18)F-FDG PET in a Rat Model of Neuropathic Pain |
title_sort | metabolic brain network analysis with (18)f-fdg pet in a rat model of neuropathic pain |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8284720/ https://www.ncbi.nlm.nih.gov/pubmed/34276529 http://dx.doi.org/10.3389/fneur.2021.566119 |
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