Regional growth and atlasing of the developing human brain

Antonios Makropoulos,Paul Aljabar,Robert Wright,Britta Hüning,Nazakat Merchant,Tomoki Arichi,Nora Tusor,Joseph V Hajnal,A David Edwards,Serena J Counsell,Daniel Rueckert

doi:10.1016/j.neuroimage.2015.10.047

Antonios Makropoulos, Paul Aljabar + Show 9 more

Open Access

https://doi.org/10.1016/j.neuroimage.2015.10.047

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Abstract

Detailed morphometric analysis of the neonatal brain is required to characterise brain development and define neuroimaging biomarkers related to impaired brain growth. Accurate automatic segmentation of neonatal brain MRI is a prerequisite to analyse large datasets. We have previously presented an accurate and robust automatic segmentation technique for parcellating the neonatal brain into multiple cortical and subcortical regions. In this study, we further extend our segmentation method to detect cortical sulci and provide a detailed delineation of the cortical ribbon. These detailed segmentations are used to build a 4-dimensional spatio-temporal structural atlas of the brain for 82 cortical and subcortical structures throughout this developmental period. We employ the algorithm to segment an extensive database of 420 MR images of the developing brain, from 27 to 45weeks post-menstrual age at imaging. Regional volumetric and cortical surface measurements are derived and used to investigate brain growth and development during this critical period and to assess the impact of immaturity at birth. Whole brain volume, the absolute volume of all structures studied, cortical curvature and cortical surface area increased with increasing age at scan. Relative volumes of cortical grey matter, cerebellum and cerebrospinal fluid increased with age at scan, while relative volumes of white matter, ventricles, brainstem and basal ganglia and thalami decreased. Preterm infants at term had smaller whole brain volumes, reduced regional white matter and cortical and subcortical grey matter volumes, and reduced cortical surface area compared with term born controls, while ventricular volume was greater in the preterm group. Increasing prematurity at birth was associated with a reduction in total and regional white matter, cortical and subcortical grey matter volume, an increase in ventricular volume, and reduced cortical surface area.

Highlights

The incidence of preterm birth continues to rise, with an estimated 14.9 million infants delivered worldwide each year (Blencowe et al, 2012)
We studied 338 infants (298 preterm infants and 40 healthy term born infants) who were born at a median gestational age (GA) of 30 (23+2–42) weeks. 49 preterm infants had chronic lung disease (CLD), 49 patent ductus arteriosus (PDA) and 32 culture positive sepsis. 66 preterm infants were scanned on 2 occasions and 8 on 3 occasions, resulting in 420 magnetic resonance (MR) imaging data-sets
Most of the structures have a significant linear correlation of their relative volumes to age at scan. These correlations were positive for relative volume of the CGM, cerebrospinal fluid (CSF), cerebellum and corpus callosum and negative for relative volume of the ventricles, the majority of WM regions and the basal ganglia and thalami

Summary

Introduction

The incidence of preterm birth continues to rise, with an estimated 14.9 million infants (representing 11.1% of all births) delivered worldwide each year (Blencowe et al, 2012). Insights into impaired neurodevelopment in these vulnerable infants have been gained from magnetic resonance (MR) imaging studies assessing brain development during the period between preterm birth and the normal time of birth. Previous studies in preterm infants have demonstrated reduced brain volume (Peterson et al, 2003; Inder et al, 2005; Thompson et al, 2007; Ball et al, 2012) and decreased cortical surface area (Ajayi-Obe et al, 2000; Kapellou et al, 2006), which are related to subsequent adverse neurodevelopmental outcome (Kapellou et al, 2006; Rathbone et al, 2011). Sample sizes have usually been small, over a limited age range and detailed regional brain growth has not been studied (Hüppi et al, 1998; Murphy et al, 2001; Peterson et al, 2003; Inder et al, 2005; Prastawa et al, 2005; Mewes et al, 2006; Nishida et al, 2006; Zacharia et al, 2006; Gilmore et al, 2007; Song et al, 2007; Thompson et al, 2007; Xue et al, 2007; Anbeek et al, 2008; Dubois et al, 2008a,b; Pienaar et al, 2008; Rodriguez-Carranza et al, 2008; Yu et al, 2010; Cardoso et al, 2013; Wang et al, 2012; Moeskops et al, 2013, 2015)

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