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Abstract #0245

Graph Theory to Analyse Developmental Plasticity in Connectivity of Preterm Children

Elda Fischi-Gomez1, 2, Alessandra Griffa1, Alessandro Daducci1, Franois Lazeyras3, 4, Jean-Philippe Thiran1, 5, Petra S. Hppi2

1Ecole Polytechnique Federale de Lausanne (EPFL). Signal Processing Laboratory (LTS5), Lausanne, Switzerland; 2Division of Development and Growth. Department of Pediatrics. University of Geneva, Geneva, Switzerland; 3Center for Biomedical Imaging (CIBM), ,Lausanne and Geneva, Switzerland; 4Department of Radiology, University of Geneva and University Hospital of Geneva, Geneva, Switzerland; 5Department of Radiology of the University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland

We used DTI and network analysis to determine the impact of prematurity and prenatal growth restriction in neurostructural outcome of preterm born children at age 6 years-old. We construct individual brain network graphs derived from structural connectivity matrices, composed by an efficacy component (weighted by the mean FA value of the bundle connecting two cortical regions) and the density component (assumed to be constant within a group). Both groups, when compared to controls, show smaller efficiency (with an average path length's increase) and transitivity that may contribute to learning disabilities and behavior disorders linked to preterm infants at school age.