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Connectome-based prediction of brain age in Rolandic epilepsy: a protocol for a multicenter cross-sectional study
BACKGROUND: Rolandic epilepsy (RE) is a common pediatric idiopathic partial epilepsy syndrome. Children with RE display varying degrees of cognitive impairment. In epilepsy, age-related neuroanatomic and cognitive changes differ greatly from those observed in the healthy brain, and may be defined as...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8039653/ https://www.ncbi.nlm.nih.gov/pubmed/33850908 http://dx.doi.org/10.21037/atm-21-574 |
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author | Wang, Fuqin Yin, Yu Yang, Yang Liang, Ting Huang, Tingting He, Cheng Hu, Jie Zhang, Jingjing Yang, Yanli Xing, Qianlu Zhang, Tijiang Liu, Heng |
author_facet | Wang, Fuqin Yin, Yu Yang, Yang Liang, Ting Huang, Tingting He, Cheng Hu, Jie Zhang, Jingjing Yang, Yanli Xing, Qianlu Zhang, Tijiang Liu, Heng |
author_sort | Wang, Fuqin |
collection | PubMed |
description | BACKGROUND: Rolandic epilepsy (RE) is a common pediatric idiopathic partial epilepsy syndrome. Children with RE display varying degrees of cognitive impairment. In epilepsy, age-related neuroanatomic and cognitive changes differ greatly from those observed in the healthy brain, and may be defined as accelerated brain aging. Connectome-based predictive modeling (CPM) is a recently developed machine learning approach that uses whole-brain connectivity measured with neuroimaging data (“neural fingerprints”) to predict brain-behavior relationships. The aim of the study will be to develop and validate a CPM for predicting brain age in patients with RE. METHODS: A multicenter, cross-sectional study will be conducted in 5 Chinese hospitals. A total of 100 RE patients (including 50 patients receiving anti-epileptic drugs and 50 drug-naïve patients) and 100 healthy children will be recruited to undergo a neuropsychological test using the Wechsler Intelligence Scale. Magnetic resonance images will also be collected. CPM will be applied to predict the brain age of children with RE based on brain functional connectivity. DISCUSSION: The findings of the study will facilitate our understanding of developmental changes in the brain in children with RE and could also be an important milestone in the journey toward developing effective early interventions for this disorder. TRIAL REGISTRATION: The study has been registered with Chinese Clinical Trial Registry (ChiCTR2000032984). |
format | Online Article Text |
id | pubmed-8039653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-80396532021-04-12 Connectome-based prediction of brain age in Rolandic epilepsy: a protocol for a multicenter cross-sectional study Wang, Fuqin Yin, Yu Yang, Yang Liang, Ting Huang, Tingting He, Cheng Hu, Jie Zhang, Jingjing Yang, Yanli Xing, Qianlu Zhang, Tijiang Liu, Heng Ann Transl Med Study Protocol BACKGROUND: Rolandic epilepsy (RE) is a common pediatric idiopathic partial epilepsy syndrome. Children with RE display varying degrees of cognitive impairment. In epilepsy, age-related neuroanatomic and cognitive changes differ greatly from those observed in the healthy brain, and may be defined as accelerated brain aging. Connectome-based predictive modeling (CPM) is a recently developed machine learning approach that uses whole-brain connectivity measured with neuroimaging data (“neural fingerprints”) to predict brain-behavior relationships. The aim of the study will be to develop and validate a CPM for predicting brain age in patients with RE. METHODS: A multicenter, cross-sectional study will be conducted in 5 Chinese hospitals. A total of 100 RE patients (including 50 patients receiving anti-epileptic drugs and 50 drug-naïve patients) and 100 healthy children will be recruited to undergo a neuropsychological test using the Wechsler Intelligence Scale. Magnetic resonance images will also be collected. CPM will be applied to predict the brain age of children with RE based on brain functional connectivity. DISCUSSION: The findings of the study will facilitate our understanding of developmental changes in the brain in children with RE and could also be an important milestone in the journey toward developing effective early interventions for this disorder. TRIAL REGISTRATION: The study has been registered with Chinese Clinical Trial Registry (ChiCTR2000032984). AME Publishing Company 2021-03 /pmc/articles/PMC8039653/ /pubmed/33850908 http://dx.doi.org/10.21037/atm-21-574 Text en 2021 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Study Protocol Wang, Fuqin Yin, Yu Yang, Yang Liang, Ting Huang, Tingting He, Cheng Hu, Jie Zhang, Jingjing Yang, Yanli Xing, Qianlu Zhang, Tijiang Liu, Heng Connectome-based prediction of brain age in Rolandic epilepsy: a protocol for a multicenter cross-sectional study |
title | Connectome-based prediction of brain age in Rolandic epilepsy: a protocol for a multicenter cross-sectional study |
title_full | Connectome-based prediction of brain age in Rolandic epilepsy: a protocol for a multicenter cross-sectional study |
title_fullStr | Connectome-based prediction of brain age in Rolandic epilepsy: a protocol for a multicenter cross-sectional study |
title_full_unstemmed | Connectome-based prediction of brain age in Rolandic epilepsy: a protocol for a multicenter cross-sectional study |
title_short | Connectome-based prediction of brain age in Rolandic epilepsy: a protocol for a multicenter cross-sectional study |
title_sort | connectome-based prediction of brain age in rolandic epilepsy: a protocol for a multicenter cross-sectional study |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8039653/ https://www.ncbi.nlm.nih.gov/pubmed/33850908 http://dx.doi.org/10.21037/atm-21-574 |
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