Different patterns of cortical maturation before and after 38 weeks gestational age demonstrated by diffusion MRI in vivo

Abstract

Human cortical development during the third trimester is characterised by macro-and microstructural changes which are reflected in alterations in diffusion MRI (dMRI) measures, with significant decreases in cortical mean diffusivity (MD) and fractional anisotropy (FA). This has been interpreted as reflecting increased cellular density and dendritic arborisation. However, the fall in FA stops abruptly at 38 weeks post-menstrual age (PMA), and then tends to plateau, while MD continues to fall, suggesting a more complex picture and raising the hypothesis that after this age development is dominated by continuing increase in neural and organelle density rather than alterations in the geometry of dendritic trees. To test this, we used neurite orientation dispersion and density imaging (NODDI), acquiring multi-shell, high angular resolution dMRI and measures of cortical volume and mean curvature in 99 preterm infants scanned between 25 and 47 weeks PMA. We predicted that increased neurite and organelle density would be reflected in increases in neurite density index (NDI), while a relatively unchanging geometrical structure would be associated with constant orientation dispersion index (ODI). As dendritic arborisation is likely to be one of the drivers of gyrification, we also predicted that measures of cortical volume and curvature would correlate with ODI and show slower growth after 38 weeks.We observed a decrease of MD throughout the period, while cortical FA decreased from 25 to 38 weeks PMA and then increased. ODI increased up to 38 weeks and then plateaued, while NDI rose after 38 weeks. The evolution of ODI correlated with cortical volume and curvature. Regional analysis of cortical microstructure revealed a heterogenous pattern with increases in FA and NDI after 38 weeks confined to primary motor and sensory regions. These results support the interpretation that cortical development between 25 and 38 weeks PMA shows a predominant increase in dendritic arborisation and neurite growth, while between 38 and 47 weeks PMA it is dominated by increasing cellular and organelle density.

Development of Microstructural and Morphological Cortical Profiles in the Neonatal Brain

“…Typical measure of cortical anatomy, thickness and area, as well as a good measure of relative T1w contrast, myelin content, showed strong increases with age . Age however showed little significant association with curvature, in agreement with previous reports showing relatively little change in MC compared to other surface measures in the first months following birth (Batalle et al 2019;Li et al 2015), suggesting that cortical folding remains relatively static in this period. Though no single individual measure mirrored the clustering solution achieved by combining all measures, the four diffusion metrics had the better correspondence ( Figure 6a), but were apparently less important to the clustering solution ( Figure 6b).…”

“…When examining each morphometric measure in isolation, developmental trajectories with clear anatomical structure were found across the PMA range examined replicating prior work (Batalle et al, 2019;Dean et al, 2017). Typical measure of cortical anatomy, thickness and area, as well as a good measure of relative T1w contrast, myelin content, showed strong increases with age .…”

“…Cortical diffusion metrics show complex maturational changes before and after the period considered as term birth. Ball et al (2013) and Batalle et al (2019) have shown that MD decreases linearly with PMA, while FA decreases rapidly until week 38 PMA, but then begins to slowly increase. This might explain why at the PMA range examined here (37-44 weeks) we observed both negative and positive associations between FA and PMA.…”

“…A tensor model for diffusion data was fitted using a single shell (b=1000), and fractional anisotropy (FA) and mean diffusivity (MD) maps were generated using MRtrix3 (Tournier et al, 2019). Neurite density index (NDI) and orientation dispersion index (ODI) maps were calculated using the NODDI toolbox (Zhang et al, 2012) as previously applied in the neonatal brain (Batalle et al, 2019). Diffusion maps were registered onto individual T2w images using FSL's epi_reg (FLIRT) (https://fsl.fmrib.ox.ac.uk), and then projected onto cortical surface using Connectome Workbench in order to sample imaging features with the same spatial representation.…”

Neonatal morphometric similarity mapping for predicting brain age and characterizing neuroanatomic variation associated with preterm birth

“…Preterm birth is closely associated with increased risk of neurodevelopmental, cognitive and psychiatric impairment that extends across the life course (Nosarti et al, 2012; Anderson, 2014; Mathewson et al, 2017; Van Lieshout et al, 2018). Structural and diffusion MRI (sMRI and dMRI) support the conceptualisation of atypical brain growth after preterm birth as a process characterised by micro-structural alteration of connective pathways due to impaired myelination and neuronal dysmaturation (Boardman et al, 2006; Anjari et al, 2007; Counsell et al, 2008; Ball et al, 2013; Back and Miller, 2014; Van Den Heuvel et al, 2015; Eaton-Rosen et al, 2015; Thompson et al, 2016; Batalle et al, 2017; Telford et al, 2017; Batalle et al, 2018); and the ensuing ‘dysconnectivity phenotype’ could form the basis for long term functional impairment (Boardman et al, 2010; Caldinelli et al, 2017; Keunen et al, 2017; Cao et al, 2017; Batalle et al, 2018b). However, there has not been a unified approach that incorporates all available information from sMRI and dMRI to study brain maturation in the perinatal period so the set of image features that best capture brain maturation, and support image classification, are unknown.…”