Brain network analyses of diffusion tensor imaging for brain aging

The approach of graph-based diffusion tensor imaging (DTI) networks has been used to explore the complicated structural connectivity of brain aging. In this study, the changes of DTI networks of brain aging were quantitatively and qualitatively investigated by comparing the characteristics of brain...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Song Xu, Xufeng Yao, Liting Han, Yuting Lv, Xixi Bu, Gan Huang, Yifeng Fan, Tonggang Yu, Gang Huang
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	brain aging diffusion tensor imaging (dti) network characteristics white matter (wm) critical nodes Biotechnology TP248.13-248.65 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/cc7eeb42fce647c681b103a1e2c0ce54
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:cc7eeb42fce647c681b103a1e2c0ce54
record_format	dspace
spelling	oai:doaj.org-article:cc7eeb42fce647c681b103a1e2c0ce542021-11-11T00:56:10ZBrain network analyses of diffusion tensor imaging for brain aging10.3934/mbe.20213031551-0018https://doaj.org/article/cc7eeb42fce647c681b103a1e2c0ce542021-07-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021303?viewType=HTMLhttps://doaj.org/toc/1551-0018The approach of graph-based diffusion tensor imaging (DTI) networks has been used to explore the complicated structural connectivity of brain aging. In this study, the changes of DTI networks of brain aging were quantitatively and qualitatively investigated by comparing the characteristics of brain network. A cohort of 60 volunteers was enrolled and equally divided into young adults (YA) and older adults (OA) groups. The network characteristics of critical nodes, path length (L<sub>p</sub>), clustering coefficient (C<sub>p</sub>), global efficiency (E<sub>global</sub>), local efficiency (E<sub>local</sub>), strength (S<sub>p</sub>), and small world attribute (σ) were employed to evaluate the DTI networks at the levels of whole brain, bilateral hemispheres and critical brain regions. The correlations between each network characteristic and age were predicted, respectively. Our findings suggested that the DTI networks produced significant changes in network configurations at the critical nodes and node edges for the YA and OA groups. The analysis of whole brains network revealed that L<sub>p</sub>, C<sub>p</sub> increased (<italic>p</italic> < 0.05, positive correlation), E<sub>global</sub>, E<sub>local</sub>, S<sub>p</sub> decreased (<italic>p</italic> < 0.05, negative correlation), and σ unchanged (<italic>p</italic> ≥ 0.05, non-correlation) between the YA and OA groups. The analyses of bilateral hemispheres and brain regions showed similar results as that of the whole-brain analysis. Therefore the proposed scheme of DTI networks could be used to evaluate the WM changes of brain aging, and the network characteristics of critical nodes exhibited valuable indications for WM degeneration.Song XuXufeng YaoLiting HanYuting LvXixi BuGan HuangYifeng FanTonggang YuGang HuangAIMS Pressarticlebrain agingdiffusion tensor imaging (dti)network characteristicswhite matter (wm)critical nodesBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 5, Pp 6066-6078 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	brain aging diffusion tensor imaging (dti) network characteristics white matter (wm) critical nodes Biotechnology TP248.13-248.65 Mathematics QA1-939
spellingShingle	brain aging diffusion tensor imaging (dti) network characteristics white matter (wm) critical nodes Biotechnology TP248.13-248.65 Mathematics QA1-939 Song Xu Xufeng Yao Liting Han Yuting Lv Xixi Bu Gan Huang Yifeng Fan Tonggang Yu Gang Huang Brain network analyses of diffusion tensor imaging for brain aging
description	The approach of graph-based diffusion tensor imaging (DTI) networks has been used to explore the complicated structural connectivity of brain aging. In this study, the changes of DTI networks of brain aging were quantitatively and qualitatively investigated by comparing the characteristics of brain network. A cohort of 60 volunteers was enrolled and equally divided into young adults (YA) and older adults (OA) groups. The network characteristics of critical nodes, path length (L<sub>p</sub>), clustering coefficient (C<sub>p</sub>), global efficiency (E<sub>global</sub>), local efficiency (E<sub>local</sub>), strength (S<sub>p</sub>), and small world attribute (σ) were employed to evaluate the DTI networks at the levels of whole brain, bilateral hemispheres and critical brain regions. The correlations between each network characteristic and age were predicted, respectively. Our findings suggested that the DTI networks produced significant changes in network configurations at the critical nodes and node edges for the YA and OA groups. The analysis of whole brains network revealed that L<sub>p</sub>, C<sub>p</sub> increased (<italic>p</italic> < 0.05, positive correlation), E<sub>global</sub>, E<sub>local</sub>, S<sub>p</sub> decreased (<italic>p</italic> < 0.05, negative correlation), and σ unchanged (<italic>p</italic> ≥ 0.05, non-correlation) between the YA and OA groups. The analyses of bilateral hemispheres and brain regions showed similar results as that of the whole-brain analysis. Therefore the proposed scheme of DTI networks could be used to evaluate the WM changes of brain aging, and the network characteristics of critical nodes exhibited valuable indications for WM degeneration.
format	article
author	Song Xu Xufeng Yao Liting Han Yuting Lv Xixi Bu Gan Huang Yifeng Fan Tonggang Yu Gang Huang
author_facet	Song Xu Xufeng Yao Liting Han Yuting Lv Xixi Bu Gan Huang Yifeng Fan Tonggang Yu Gang Huang
author_sort	Song Xu
title	Brain network analyses of diffusion tensor imaging for brain aging
title_short	Brain network analyses of diffusion tensor imaging for brain aging
title_full	Brain network analyses of diffusion tensor imaging for brain aging
title_fullStr	Brain network analyses of diffusion tensor imaging for brain aging
title_full_unstemmed	Brain network analyses of diffusion tensor imaging for brain aging
title_sort	brain network analyses of diffusion tensor imaging for brain aging
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/cc7eeb42fce647c681b103a1e2c0ce54
work_keys_str_mv	AT songxu brainnetworkanalysesofdiffusiontensorimagingforbrainaging AT xufengyao brainnetworkanalysesofdiffusiontensorimagingforbrainaging AT litinghan brainnetworkanalysesofdiffusiontensorimagingforbrainaging AT yutinglv brainnetworkanalysesofdiffusiontensorimagingforbrainaging AT xixibu brainnetworkanalysesofdiffusiontensorimagingforbrainaging AT ganhuang brainnetworkanalysesofdiffusiontensorimagingforbrainaging AT yifengfan brainnetworkanalysesofdiffusiontensorimagingforbrainaging AT tonggangyu brainnetworkanalysesofdiffusiontensorimagingforbrainaging AT ganghuang brainnetworkanalysesofdiffusiontensorimagingforbrainaging
_version_	1718439629292568576

Brain network analyses of diffusion tensor imaging for brain aging

Ejemplares similares