A tract-specific approach to assessing white matter in preterm infants

Diliana Pecheva,Paul Yushkevich,Dafnis Batalle,Emer Hughes,Paul Aljabar,Julia Wurie,Joseph V Hajnal,A David Edwards,Daniel C Alexander,Serena J Counsell,Hui Zhang

doi:10.1016/j.neuroimage.2017.04.057

Diliana Pecheva, Paul Yushkevich + Show 9 more

Open Access

https://doi.org/10.1016/j.neuroimage.2017.04.057

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Abstract

Diffusion-weighted imaging (DWI) is becoming an increasingly important tool for studying brain development. DWI analyses relying on manually-drawn regions of interest and tractography using manually-placed waypoints are considered to provide the most accurate characterisation of the underlying brain structure. However, these methods are labour-intensive and become impractical for studies with large cohorts and numerous white matter (WM) tracts. Tract-specific analysis (TSA) is an alternative WM analysis method applicable to large-scale studies that offers potential benefits. TSA produces a skeleton representation of WM tracts and projects the group's diffusion data onto the skeleton for statistical analysis. In this work we evaluate the performance of TSA in analysing preterm infant data against results obtained from native space tractography and tract-based spatial statistics. We evaluate TSA's registration accuracy of WM tracts and assess the agreement between native space data and template space data projected onto WM skeletons, in 12 tracts across 48 preterm neonates. We show that TSA registration provides better WM tract alignment than a previous protocol optimised for neonatal spatial normalisation, and that TSA projects FA values that match well with values derived from native space tractography. We apply TSA for the first time to a preterm neonatal population to study the effects of age at scan on WM tracts around term equivalent age. We demonstrate the effects of age at scan on DTI metrics in commissural, projection and association fibres. We demonstrate the potential of TSA for WM analysis and its suitability for infant studies involving multiple tracts.

Highlights

Diffusion-weighted magnetic resonance imaging is increasingly being used to study brain development and injury in infants
In this work we evaluate the performance of Tract-specific analysis (TSA) in analysing preterm infant data against results obtained from native space tractography and tract-based spatial statistics
We show that TSA registration provides better white matter (WM) tract alignment than a previous protocol optimised for neonatal spatial normalisation, and that TSA projects FA values that match well with values derived from native space tractography

Summary

Introduction

Diffusion-weighted magnetic resonance imaging (dMRI) is increasingly being used to study brain development and injury in infants. Using metrics derived from diffusion tensor imaging (DTI) (Basser et al, 1994) we have gained valuable insights into the effects of maturation and injury on white matter (WM) in healthy and patient infant populations. DTI analyses of WM have been used to assess quantitatively microstructural changes during normal development in infancy (Dubois et al, 2006; Gao et al, 2009) and through childhood to adulthood (Lebel et al, 2008); provide in vivo quantification of the spatio-temporal pattern of WM maturation (Dubois et al, 2008); assess differences in cerebral WM between term and preterm infants (Anjari et al, 2007; Huppi et al, 1998; Rose et al, 2008); and correlate DTI metrics with early developmental outcome in preterm infants (Counsell et al, 2008; van Kooij et al, 2012). Establishing correspondence between subjects’ WM tracts can be problematic due to inter-subject variability in anatomy and DTI characteristics, which can result in differences in tractography or segmentation. Correspondence can be achieved by sampling at equivalent levels along tracts (Groeschel et al, 2014; Verde et al, 2014) or parameterising WM tracts by arc length, essentially reducing entire

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