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

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.

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').

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 POINTS: • The structural connectivity analysis quantifies white-matter networks within the brain • In callosal agenesis there is reduced global and increased local connectivity • In callosal agenesis, alternative decussating pathways are used for interhemispheric connectivity.