Disrupted structural connectivity of fronto-deep gray matter pathways in progressive supranuclear palsy.
Graph theory
Progressive supranuclear palsy
Structural connectivity
Tractography
Journal
NeuroImage. Clinical
ISSN: 2213-1582
Titre abrégé: Neuroimage Clin
Pays: Netherlands
ID NLM: 101597070
Informations de publication
Date de publication:
2019
2019
Historique:
received:
12
03
2019
revised:
09
06
2019
accepted:
13
06
2019
pubmed:
24
6
2019
medline:
7
8
2020
entrez:
24
6
2019
Statut:
ppublish
Résumé
Structural connectivity is a promising methodology to detect patterns of neural network dysfunction in neurodegenerative diseases. This approach has not been tested in progressive supranuclear palsy (PSP). The aim of this study is reconstructing the structural connectome to characterize and detect the pathways of degeneration in PSP patients compared with healthy controls and their correlation with clinical features. The second objective is to assess the potential of structural connectivity measures to distinguish between PSP patients and healthy controls at the single-subject level. Twenty healthy controls and 19 PSP patients underwent diffusion-weighted MRI with a 3T scanner. Structural connectivity, represented by number of streamlines, was derived from probabilistic tractography. Global and local network metrics were calculated based on graph theory. Reduced numbers of streamlines were predominantly found in connections between frontal areas and deep gray matter (DGM) structures in PSP compared with controls. Significant changes in structural connectivity correlated with clinical features in PSP patients. An abnormal small-world architecture was detected in the subnetwork comprising the frontal lobe and DGM structures in PSP patients. The classification procedure achieved an overall accuracy of 82.23% with 94.74% sensitivity and 70% specificity. Our findings suggest that modelling the brain as a structural connectome is a useful method to detect changes in the organization and topology of white matter tracts in PSP patients. Secondly, measures of structural connectivity have the potential to correctly discriminate between PSP patients and healthy controls.
Sections du résumé
BACKGROUND
Structural connectivity is a promising methodology to detect patterns of neural network dysfunction in neurodegenerative diseases. This approach has not been tested in progressive supranuclear palsy (PSP).
OBJECTIVES
The aim of this study is reconstructing the structural connectome to characterize and detect the pathways of degeneration in PSP patients compared with healthy controls and their correlation with clinical features. The second objective is to assess the potential of structural connectivity measures to distinguish between PSP patients and healthy controls at the single-subject level.
METHODS
Twenty healthy controls and 19 PSP patients underwent diffusion-weighted MRI with a 3T scanner. Structural connectivity, represented by number of streamlines, was derived from probabilistic tractography. Global and local network metrics were calculated based on graph theory.
RESULTS
Reduced numbers of streamlines were predominantly found in connections between frontal areas and deep gray matter (DGM) structures in PSP compared with controls. Significant changes in structural connectivity correlated with clinical features in PSP patients. An abnormal small-world architecture was detected in the subnetwork comprising the frontal lobe and DGM structures in PSP patients. The classification procedure achieved an overall accuracy of 82.23% with 94.74% sensitivity and 70% specificity.
CONCLUSION
Our findings suggest that modelling the brain as a structural connectome is a useful method to detect changes in the organization and topology of white matter tracts in PSP patients. Secondly, measures of structural connectivity have the potential to correctly discriminate between PSP patients and healthy controls.
Identifiants
pubmed: 31229940
pii: S2213-1582(19)30249-9
doi: 10.1016/j.nicl.2019.101899
pmc: PMC6593210
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
101899Informations de copyright
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.
Références
Dialogues Clin Neurosci. 2007;9(2):141-51
pubmed: 17726913
IEEE Trans Med Imaging. 2007 Apr;26(4):518-29
pubmed: 17427739
Neuroimage. 2010 Sep;52(3):1059-69
pubmed: 19819337
Neuroimage. 2002 Oct;17(2):825-41
pubmed: 12377157
Ann Appl Stat. 2012 Dec 27;6(4):1883-1905
pubmed: 24523851
Mov Disord. 2018 Apr;33(4):600-608
pubmed: 29473662
Cereb Cortex. 1994 Jul-Aug;4(4):344-60
pubmed: 7950308
Mov Disord. 2017 Jun;32(6):853-864
pubmed: 28467028
J Neurol Neurosurg Psychiatry. 2004 Feb;75(2):246-9
pubmed: 14742598
J Neurosci Methods. 2014 Jan 30;222:230-7
pubmed: 24286700
Neurology. 1996 Jul;47(1):1-9
pubmed: 8710059
Arch Neurol. 2011 Jun;68(6):753-60
pubmed: 21670399
Brain. 2007 Jun;130(Pt 6):1552-65
pubmed: 17405767
Am J Med Genet. 1997 Sep 19;74(5):507-14
pubmed: 9342202
J Neurol. 2014 May;261(5):913-24
pubmed: 24599641
Sci Rep. 2018 Aug 1;8(1):11562
pubmed: 30068926
J Magn Reson Imaging. 2010 Jul;32(1):69-75
pubmed: 20578012
PLoS One. 2013 Jul 15;8(7):e69237
pubmed: 23869237
PLoS One. 2014 Nov 18;9(11):e112638
pubmed: 25405990
Radiology. 2008 Jan;246(1):214-21
pubmed: 17991785
Neurology. 1996 Nov;47(5):1184-9
pubmed: 8909427
Brain. 2002 Apr;125(Pt 4):789-800
pubmed: 11912112
Neuroimage. 2009 Jan 1;44(1):83-98
pubmed: 18501637
AJNR Am J Neuroradiol. 2012 Dec;33(11):2123-8
pubmed: 22653326
IEEE Trans Med Imaging. 1998 Feb;17(1):87-97
pubmed: 9617910
Neurology. 1967 May;17(5):427-42
pubmed: 6067254
Mov Disord. 2014 Feb;29(2):266-9
pubmed: 24323617
Neuroimage. 2013 Oct 15;80:515-26
pubmed: 23623973
NMR Biomed. 2019 Apr;32(4):e3785
pubmed: 28945294
Magn Reson Med. 2012 Dec;68(6):1846-55
pubmed: 22334356
Neuroimage. 2010 Dec;53(4):1197-207
pubmed: 20600983
Curr Opin Neurobiol. 2013 Apr;23(2):162-71
pubmed: 23294553
Eur J Neurol. 2013 Mar;20(3):493-501
pubmed: 23061493
Neurology. 2000 Dec 12;55(11):1621-6
pubmed: 11113214
Eur Radiol. 2013 Jun;23(6):1459-66
pubmed: 23300042
AJNR Am J Neuroradiol. 2011 Dec;32(11):2087-92
pubmed: 21998102
Psychiatry Res. 2011 Nov 30;194(2):163-75
pubmed: 21899988
Neuroradiology. 2015 Nov;57(11):1079-91
pubmed: 26253801
Med Image Anal. 2001 Jun;5(2):143-56
pubmed: 11516708
Nat Rev Neurosci. 2009 Mar;10(3):186-98
pubmed: 19190637
Schizophr Res. 2012 Nov;141(2-3):109-18
pubmed: 22981811
Netw Neurosci. 2018 Oct 01;3(1):1-26
pubmed: 30793071
J Neurol Sci. 2015 Dec 15;359(1-2):367-72
pubmed: 26671144
Neuroimage. 2004 Oct;23(2):663-9
pubmed: 15488416
Arch Neurol. 1993 Aug;50(8):873-80
pubmed: 8352676
Neuroimage. 2006 Jul 15;31(4):1487-505
pubmed: 16624579
Proc Natl Acad Sci U S A. 2000 Sep 26;97(20):11050-5
pubmed: 10984517
Neuroimage. 2016 Nov 15;142:407-420
pubmed: 27364472
Neuroimage. 2007 Jan 1;34(1):144-55
pubmed: 17070705
Neuroimage. 2006 Jul 1;31(3):968-80
pubmed: 16530430
Parkinsonism Relat Disord. 2011 Sep;17(8):599-605
pubmed: 21665514
Lancet Neurol. 2017 Jul;16(7):552-563
pubmed: 28653647
Curr Neurol Neurosci Rep. 2018 Feb 17;18(3):12
pubmed: 29455271
Radiology. 2017 May;283(2):515-525
pubmed: 27924721
PLoS One. 2010 Nov 01;5(11):e13788
pubmed: 21072180
Mov Disord. 2016 Oct;31(10):1506-1517
pubmed: 27452874
Cereb Cortex. 2000 Feb;10(2):127-41
pubmed: 10667981
Neurol Neurochir Pol. 2015;49(6):421-31
pubmed: 26652877
Neuroimage Clin. 2019;22:101720
pubmed: 30785051
Hum Brain Mapp. 2018 Jun;39(6):2289-2302
pubmed: 29450940
PLoS Comput Biol. 2010 Nov 18;6(11):e1001006
pubmed: 21124954
Hum Brain Mapp. 2014 Sep;35(9):4620-34
pubmed: 24639411
Neuroradiology. 2012 Sep;54(9):947-55
pubmed: 22274571
Brain. 2005 Jun;128(Pt 6):1259-66
pubmed: 15843423
Dement Geriatr Cogn Disord. 2014;38(5-6):375-88
pubmed: 25195847
Ann Neurol. 2000 Jun;47(6):718-28
pubmed: 10852537
J Neurol Neurosurg Psychiatry. 2006 Apr;77(4):457-63
pubmed: 16306152
PLoS One. 2013 Jun 13;8(6):e66022
pubmed: 23785466
Trends Cogn Sci. 2013 Dec;17(12):683-96
pubmed: 24231140
PLoS Comput Biol. 2008 Jun 27;4(6):e1000100
pubmed: 18584043
J Neurosci. 2008 Apr 30;28(18):4756-66
pubmed: 18448652
Front Aging Neurosci. 2015 Apr 14;7:48
pubmed: 25926791
J Neurosci. 2010 Dec 15;30(50):16876-85
pubmed: 21159959