Early development of structural networks and the impact of prematurity on brain connectivity.
Preterm infants are at high risk of neurodevelopmental impairment, which may be due to altered development of brain connectivity. We aimed to (i) assess structural brain development from 25 to 45 weeks gestational age (GA) using graph theoretical approaches and (ii) test the hypothesis that preterm birth results in altered white matter network topology. Sixty-five infants underwent MRI between 25+3and 45+6weeks GA. Structural networks were constructed using constrained spherical deconvolution tractography and were weighted by measures of white matter microstructure (fractional anisotropy, neurite density and orientation dispersion index). We observed regional differences in brain maturation, with connections to and from deep grey matter showing most rapid developmental changes during this period. Intra-frontal, frontal to cingulate, frontal to caudate and inter-hemispheric connections matured more slowly. We demonstrated a core of key connections that was not affected by GA at birth. However, local connectivity involving thalamus, cerebellum, superior frontal lobe, cingulate gyrus and short range cortico-cortical connections was related to the degree of prematurity and contributed to altered global topology of the structural brain network. The relative preservation of core connections at the expense of local connections may support more effective use of impaired white matter reserve following preterm birth.
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom.
Dafnis
D
Batalle
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom.
Emer J
EJ
Hughes
Department of Computer Science & Centre for Medical Image Computing, University College London, United Kingdom.
Hui
H
Zhang
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom.
J-Donald
JD
Tournier
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom.
Nora
N
Tusor
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom.
Paul
P
Aljabar
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom.
Luqman
L
Wali
Department of Computer Science & Centre for Medical Image Computing, University College London, United Kingdom.
Daniel C
DC
Alexander
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom.
Joseph V
JV
Hajnal
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom.
Chiara
C
Nosarti
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom. Electronic address: ad.edwards@kcl.ac.uk.
A David
AD
Edwards
Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College London, SE1 7EH London, United Kingdom.
Serena J
SJ
Counsell
D001921:Brain / Q000254:growth & development*; D056324:Diffusion Tensor Imaging / Q000379:methods; D005260:Female; D005865:Gestational Age; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007231:Infant, Newborn; D007234:Infant, Premature / Q000254:growth & development*; D008279:Magnetic Resonance Imaging; D008297:Male; D009434:Neural Pathways / Q000254:growth & development*
Brain mapping; Diffusion MRI; Graph theory; NODDI; Newborn