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Abnormal Gray Matter Structural Networks in Idiopathic Normal Pressure Hydrocephalus

Authors :
Le-Kang Yin
Jia-Jun Zheng
Jia-Qi Tian
Xiao-Zhu Hao
Chan-Chan Li
Jian-Ding Ye
Yu-Xuan Zhang
Hong Yu
Yan-Mei Yang
Source :
Frontiers in Aging Neuroscience, Vol 10 (2018), Frontiers in Aging Neuroscience
Publication Year :
2018
Publisher :
Frontiers Media SA, 2018.

Abstract

Purpose: Idiopathic normal pressure hydrocephalus (iNPH) is known as a treatable form of dementia. Network analysis is emerging as a useful method to study neurological disorder diseases. No study has examined changes of structural brain networks of iNPH patients. We aimed to investigate alterations in the gray matter (GM) structural network of iNPH patients compared with normal elderly volunteers.Materials and Methods: Structural networks were reconstructed using covariance between regional GM volumes extracted from three-dimensional T1-weighted images of 29 possible iNPH patients and 30 demographically similar normal-control (NC) participants and compared with each other.Results: Global network modularity was significantly larger in the iNPH network (P < 0.05). Global network measures were not significantly different between the two networks (P > 0.05). Regional network analysis demonstrated eight nodes with significantly decreased betweenness located in the bilateral frontal, right temporal, right insula and right posterior cingulate regions, whereas only the left anterior cingulate was detected with significantly larger betweenness. The hubs of the iNPH network were mostly located in temporal areas and the limbic lobe, those of the NC network were mainly located in frontal areas.Conclusions: Network analysis was a promising method to study iNPH. Increased network modularity of the iNPH group was detected here, and modularity analysis should be paid much attention to explore the biomarker to select shunting-responsive patients.

Details

Language :
English
ISSN :
16634365
Volume :
10
Database :
OpenAIRE
Journal :
Frontiers in Aging Neuroscience
Accession number :
edsair.doi.dedup.....c93b329ab6c962c3072294befca8724c
Full Text :
https://doi.org/10.3389/fnagi.2018.00356