Structural network analysis of brain development in young preterm neonates Colin J. Brown a, ⁎, Steven P. Miller b , Brian G. Booth a , Shawn Andrews a , Vann Chau b , Kenneth J. Poskitt c , Ghassan Hamarneh a a Medical Image Analysis Lab, Simon Fraser University, Burnaby, BC, Canada b Department of Paediatrics, The Hospital for Sick Children and the University of Toronto, Toronto, ON, Canada c BC Children's Hospital, Vancouver, BC, Canada abstract article info Article history: Accepted 20 July 2014 Available online 27 July 2014 Keywords: Preterm Brain development Structural connectome Network measures Neonates Tractography Preterm infants develop differently than those born at term and are at higher risk of brain pathology. Thus, an understanding of their development is of particular importance. Diffusion tensor imaging (DTI) of preterm infants offers a window into brain development at a very early age, an age at which that development is not yet fully understood. Recent works have used DTI to analyze structural connectome of the brain scans using network analysis. These studies have shown that, even from infancy, the brain exhibits small-world properties. Here we examine a cohort of 47 normal preterm neonates (i.e., without brain injury and with normal neurodevelopment at 18 months of age) scanned between 27 and 45 weeks post-menstrual age to further the understanding of how the structural connectome develops. We use full-brain tractography to find white matter tracts between the 90 cortical and sub-cortical regions defined in the University of North Carolina Chapel Hill neonatal atlas. We then analyze the resulting connectomes and explore the differences between weighting edges by tract count versus fractional anisotropy. We observe that the brain networks in preterm infants, much like infants born at term, show high efficiency and clustering measures across a range of network scales. Further, the development of many individual region-pair connections, particularly in the frontal and occipital lobes, is significantly correlated with age. Finally, we observe that the preterm infant connectome remains highly efficient yet becomes more clustered across this age range, leading to a significant increase in its small-world structure. © 2014 Elsevier Inc. All rights reserved. Introduction The early configuration and development of the brain's structural network is not yet well understood. In vivo analysis of white matter connections typically requires a diffusion magnetic resonance (dMR) image of the brain which, for in utero subjects, presents significant challenges (Jiang et al., 2007). Preterm neonatal subjects provide an opportunity to study the early connectome without the difficulties associated with in utero imaging. Understanding the connectomes of these infants is doubly important due to the risk factors associated with preterm birth, including white matter injury and abnormal neurodevelopment (Dudink et al., 2008). Here, we examine a normative cohort of preterm neonatal infants scanned between 27 and 45 weeks post-menstrual age (PMA) and identify consistent topological and developmental trends in their structural brain networks. Our goal is to develop a better understanding of early brain configuration and growth which will enable future studies to better characterize abnormal development and injury. Previous works have examined white matter development in young infants. Many early studies focused on voxel-wise measures of fraction- al anisotropy (FA) and mean diffusivity (MD) (Bonifacio et al., 2010; Hüppi et al., 1998; Neil et al., 1998). These works discussed the effects of myelination and reduction in brain water over time on increasing FA and decreasing MD (Dudink et al., 2008; Gao et al., 2009a). Many other studies have looked at functional network develop- ment in young infants (Fransson et al., 2007, 2011; Gao et al., 2009b; Wang et al., 2008). Fransson et al., in particular, examined the resting-state functional network architecture of very young preterm infants (25 weeks mean gestational age) and found that only half of the number of resting-state sub-networks found in healthy adults were present at the preterm stage (Fransson et al., 2007). Recently, van der Heuvel et al. found that functional networks in preterm infants agreed well with the underlying anatomical structure (van den Heuvel et al., 2014). In general, the relationship between functional networks and structural networks is complex NeuroImage 101 (2014) 667–680 ⁎ Corresponding author at: 9971 Applied Sciences Building (ASB), School of Computing Science, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada. E-mail address: cjbrown@sfu.ca (C.J. Brown). http://dx.doi.org/10.1016/j.neuroimage.2014.07.030 1053-8119/© 2014 Elsevier Inc. All rights reserved. Contents lists available at ScienceDirect NeuroImage journal homepage: www.elsevier.com/locate/ynimg