Abstract

Objective: Abnormalities in segregative and integrative properties of brain networks have been observed in multiple sclerosis (MS) and are related to clinical functioning. This study aims to investigate the micro-scale correlates of macro-scale network measures of segregation and integration in MS. Methods: Eight MS patients underwent post-mortem in situ whole-brain diffusion tensor (DT) imaging and subsequent brain dissection. Macro-scale structural network topology was derived from DT data using graph theory. Clustering coefficient and mean white matter (WM) fiber length were measures of nodal segregation and integration. Thirty-three tissue blocks were collected from five cortical brain regions. Using immunohistochemistry micro-scale tissue properties were evaluated, including, neuronal size, neuronal density, axonal density and total cell density. Nodal network properties and tissue properties were correlated. Results: A negative correlation between clustering coefficient and WM fiber length was found. Higher clustering coefficient was associated with smaller neuronal size and lower axonal density, and vice versa for fiber length. Higher whole-brain WM lesion load was associated with higher whole-brain clustering, shorter whole-brain fiber length, lower neuronal size and axonal density. Conclusion: Structural network properties on MRI associate with neuronal size and axonal density, suggesting that macro-scale network measures may grasp cortical neuroaxonal degeneration in MS.
LanguageEnglish
Pages212-222
JournalJournal of Neurology
Volume266
Issue number1
DOIs
Publication statusPublished - 25 Jan 2019

Cite this

@article{892562054a924cad91e974ddc9c73c50,
title = "Structural network topology relates to tissue properties in multiple sclerosis",
abstract = "Objective: Abnormalities in segregative and integrative properties of brain networks have been observed in multiple sclerosis (MS) and are related to clinical functioning. This study aims to investigate the micro-scale correlates of macro-scale network measures of segregation and integration in MS. Methods: Eight MS patients underwent post-mortem in situ whole-brain diffusion tensor (DT) imaging and subsequent brain dissection. Macro-scale structural network topology was derived from DT data using graph theory. Clustering coefficient and mean white matter (WM) fiber length were measures of nodal segregation and integration. Thirty-three tissue blocks were collected from five cortical brain regions. Using immunohistochemistry micro-scale tissue properties were evaluated, including, neuronal size, neuronal density, axonal density and total cell density. Nodal network properties and tissue properties were correlated. Results: A negative correlation between clustering coefficient and WM fiber length was found. Higher clustering coefficient was associated with smaller neuronal size and lower axonal density, and vice versa for fiber length. Higher whole-brain WM lesion load was associated with higher whole-brain clustering, shorter whole-brain fiber length, lower neuronal size and axonal density. Conclusion: Structural network properties on MRI associate with neuronal size and axonal density, suggesting that macro-scale network measures may grasp cortical neuroaxonal degeneration in MS.",
author = "Svenja Kiljan and Meijer, {Kim A.} and Steenwijk, {Martijn D.} and Pouwels, {Petra J. W.} and Schoonheim, {Menno M.} and Schenk, {Geert J.} and Geurts, {Jeroen J. G.} and Linda Douw",
year = "2019",
month = "1",
day = "25",
doi = "10.1007/s00415-018-9130-2",
language = "English",
volume = "266",
pages = "212--222",
journal = "Journal of Neurology",
issn = "0340-5354",
publisher = "D. Steinkopff-Verlag",
number = "1",

}

Structural network topology relates to tissue properties in multiple sclerosis. / Kiljan, Svenja; Meijer, Kim A.; Steenwijk, Martijn D.; Pouwels, Petra J. W.; Schoonheim, Menno M.; Schenk, Geert J.; Geurts, Jeroen J. G.; Douw, Linda.

In: Journal of Neurology, Vol. 266, No. 1, 25.01.2019, p. 212-222.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Structural network topology relates to tissue properties in multiple sclerosis

AU - Kiljan, Svenja

AU - Meijer, Kim A.

AU - Steenwijk, Martijn D.

AU - Pouwels, Petra J. W.

AU - Schoonheim, Menno M.

AU - Schenk, Geert J.

AU - Geurts, Jeroen J. G.

AU - Douw, Linda

PY - 2019/1/25

Y1 - 2019/1/25

N2 - Objective: Abnormalities in segregative and integrative properties of brain networks have been observed in multiple sclerosis (MS) and are related to clinical functioning. This study aims to investigate the micro-scale correlates of macro-scale network measures of segregation and integration in MS. Methods: Eight MS patients underwent post-mortem in situ whole-brain diffusion tensor (DT) imaging and subsequent brain dissection. Macro-scale structural network topology was derived from DT data using graph theory. Clustering coefficient and mean white matter (WM) fiber length were measures of nodal segregation and integration. Thirty-three tissue blocks were collected from five cortical brain regions. Using immunohistochemistry micro-scale tissue properties were evaluated, including, neuronal size, neuronal density, axonal density and total cell density. Nodal network properties and tissue properties were correlated. Results: A negative correlation between clustering coefficient and WM fiber length was found. Higher clustering coefficient was associated with smaller neuronal size and lower axonal density, and vice versa for fiber length. Higher whole-brain WM lesion load was associated with higher whole-brain clustering, shorter whole-brain fiber length, lower neuronal size and axonal density. Conclusion: Structural network properties on MRI associate with neuronal size and axonal density, suggesting that macro-scale network measures may grasp cortical neuroaxonal degeneration in MS.

AB - Objective: Abnormalities in segregative and integrative properties of brain networks have been observed in multiple sclerosis (MS) and are related to clinical functioning. This study aims to investigate the micro-scale correlates of macro-scale network measures of segregation and integration in MS. Methods: Eight MS patients underwent post-mortem in situ whole-brain diffusion tensor (DT) imaging and subsequent brain dissection. Macro-scale structural network topology was derived from DT data using graph theory. Clustering coefficient and mean white matter (WM) fiber length were measures of nodal segregation and integration. Thirty-three tissue blocks were collected from five cortical brain regions. Using immunohistochemistry micro-scale tissue properties were evaluated, including, neuronal size, neuronal density, axonal density and total cell density. Nodal network properties and tissue properties were correlated. Results: A negative correlation between clustering coefficient and WM fiber length was found. Higher clustering coefficient was associated with smaller neuronal size and lower axonal density, and vice versa for fiber length. Higher whole-brain WM lesion load was associated with higher whole-brain clustering, shorter whole-brain fiber length, lower neuronal size and axonal density. Conclusion: Structural network properties on MRI associate with neuronal size and axonal density, suggesting that macro-scale network measures may grasp cortical neuroaxonal degeneration in MS.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85056907551&origin=inward

UR - https://www.ncbi.nlm.nih.gov/pubmed/30467603

U2 - 10.1007/s00415-018-9130-2

DO - 10.1007/s00415-018-9130-2

M3 - Article

VL - 266

SP - 212

EP - 222

JO - Journal of Neurology

T2 - Journal of Neurology

JF - Journal of Neurology

SN - 0340-5354

IS - 1

ER -