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Stability of graph theoretical measures in structural brain networks in Alzheimer's disease

Martensson, G. (författare)
Karolinska Institutet
Pereira, J. B. (författare)
Karolinska Institutet
Mecocci, P. (författare)
visa fler...
Vellas, B. (författare)
Tsolaki, M. (författare)
Kloszewska, I. (författare)
Soininen, H. (författare)
Lovestone, S. (författare)
Simmons, A. (författare)
Volpe, Giovanni, 1979 (författare)
Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
Westman, E. (författare)
Karolinska Institutet
visa färre...
 (creator_code:org_t)
2018-08-02
2018
Engelska.
Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Graph analysis has become a popular approach to study structural brain networks in neurodegenerative disorders such as Alzheimer's disease (AD). However, reported results across similar studies are often not consistent. In this paper we investigated the stability of the graph analysis measures clustering, path length, global efficiency and transitivity in a cohort of AD (N = 293) and control subjects (N = 293). More specifically, we studied the effect that group size and composition, choice of neuroanatomical atlas, and choice of cortical measure (thickness or volume) have on binary and weighted network properties and relate them to the magnitude of the differences between groups of AD and control subjects. Our results showed that specific group composition heavily influenced the network properties, particularly for groups with less than 150 subjects. Weighted measures generally required fewer subjects to stabilize and all assessed measures showed robust significant differences, consistent across atlases and cortical measures. However, all these measures were driven by the average correlation strength, which implies a limitation of capturing more complex features in weighted networks. In binary graphs, significant differences were only found in the global efficiency and transitivity measures when using cortical thickness measures to define edges. The findings were consistent across the two atlases, but no differences were found when using cortical volumes. Our findings merits future investigations of weighted brain networks and suggest that cortical thickness measures should be preferred in future AD studies if using binary networks. Further, studying cortical networks in small cohorts should be complemented by analyzing smaller, subsampled groups to reduce the risk that findings are spurious.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Neurosciences (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Medicinsk bioteknologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Medical Biotechnology (hsv//eng)

Nyckelord

mild cognitive impairment
human cerebral-cortex
cortical thickness
mri
connectivity
organization
classification
segmentation
framework
severity
Science & Technology - Other Topics

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