Structural connectivity analysis reveals abnormal brain connections in agenesis of the corpus callosum in children

Avner Meoded, Rohan Katipally, Thangamadhan Bosemani, Thierry A.G.M. Huisman, Andrea Poretti

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Results: Ten patients (six males, mean age 6.5 years, SD 4.5 years) and ten controls (mean age 5.9 years, SD 4.7 years) were included. In patients, topology analysis revealed higher clustering coefficient and transitivity and lower small world index and assortativity compared to controls. The bilateral insula were identified as hubs in patients, whereas the cerebellum was detected as a hub only in controls. Three sub-networks of increased connectivity were identified in patients.

Conclusions: We found reduced global and increased local connectivity in children with AgCC compared to controls. Neural plasticity in AgCC may attempt to increase the interhemispheric connectivity through alternative decussating pathways other than the corpus callosum.

Key

Methods: Structural connectivity analysis including topology analysis and network-based-statistics was applied in children with AgCC and age-matched controls. Probabilistic-tractography and brain segmentation into 108 regions were performed. For controls, structural connectivity has been analyzed after excluding the callosal connections (‘virtual callosotomy’).

Objectives: Structural connectivity analysis is an ideal tool to study connections in brain malformations. We aimed to characterize the topological network measures and study sub-networks in children with agenesis of the corpus callosum (AgCC). We hypothesized a more segregated structural network in children with AgCC.

Original languageEnglish (US)
Pages (from-to)1471-1478
Number of pages8
JournalEuropean radiology
Volume25
Issue number5
DOIs
StatePublished - May 1 2015

Keywords

  • Agenesis
  • Children
  • Corpus callosum
  • Diffusion tensor imaging
  • Structural connectivity

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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