Age-specific gray and white matter DTI atlas for human brain at 33, 36 and 39 postmenstrual weeks

Abstract

During the 3rd trimester, dramatic structural changes take place in the human brain, underlying the neural circuit formation. The survival rate of premature infants has increased significantly in recent years. The large morphological differences of the preterm brain at 33 or 36 postmenstrual weeks (PMW) from the brain at 40PMW (full term) make it necessary to establish age-specific atlases for preterm brains. In this study, with high quality (1.5 × 1.5 × 1.6 mm imaging resolution) diffusion tensor imaging (DTI) data obtained from 84 healthy preterm and term-born neonates, we established age-specific preterm and term-born brain templates and atlases at 33, 36 and 39PMW. Age-specific DTI templates include a single-subject template, a population-averaged template with linear transformation and a population-averaged template with nonlinear transformation. Each of the age-specific DTI atlases includes comprehensive labeling of 126 major gray matter (GM) and white matter (WM) structures, specifically 52 cerebral cortical structures, 40 cerebral WM structures, 22 brainstem and cerebellar structures and 12 subcortical GM structures. From 33 to 39 PMW, dramatic morphological changes of delineated individual neural structures such as ganglionic eminence and uncinate fasciculus were revealed. The evaluation based on measurements of Dice ratio and L1 error suggested reliable and reproducible automated labels from the age-matched atlases compared to labels from manual delineation. Applying these atlases to automatically and effectively delineate microstructural changes of major WM tracts during the 3rd trimester was demonstrated. The established age-specific DTI templates and atlases of 33, 36 and 39 PMW brains may be used for not only understanding normal functional and structural maturational processes but also detecting biomarkers of neural disorders in the preterm brains.

Structural network maturation of the preterm human brain

“…These dMRI studies have demonstrated, for example, that limbic WM fibers appear earlier while the association WM fibers constituting major cortico-cortical connectivity appear later. By the start of the 3 rd trimester, except arcuate fasciculus, all major WM fibers can be identified with dMRI (Feng et al, 2016). The asynchronous and heterogeneous maturation of WM across regions in the 3 rd trimester has also been suggested by other neuroimaging studies (e.g.…”

Structural network maturation of the preterm human brain

“…Consistent with histological atlases (Bayer and Altman 2004), these dMRI findings have demonstrated that limbic WM fibers appear earlier while the association WM fibers constituting major cortico-cortical connectivity appear later. By the start of the 3 rd trimester, except the arcuate fasciculus, all other major WM fibers can be identified with dMRI (Feng et al, 2016). Asynchronous and heterogeneous maturation of WM across regions in the 3rd trimester has also been suggested by other neuroimaging studies (e.g.…”

White matter extension of the Melbourne Children's Regional Infant Brain atlas: M‐CRIB‐WM

“…Considering there are equivalent JHU atlases available for younger third trimester time points (Feng et al, ) and older time points (Mori et al, ; Oishi et al, ), our neonatal WM atlas also has the benefit of facilitating longitudinal analyses of neuroimaging metrics from equivalent WM regions. Together with the large range of complementary multi‐parametric neuroimaging tools and techniques available, the combined M‐CRIB and M‐CRIB‐WM atlases will enable detailed structural and microstructural measures to be obtained in an accurate and age‐specific way for major cortical and subcortical regions of the neonatal brain, and now additionally for all major WM tracts and regions.…”

“…During the neonatal period, MRI images have relatively low spatial resolution due to small brain size and have different tissue contrast compared with older children and adults due to partial myelination and dynamic tissue properties in neonates (Heemskerk et al, ). Over the last decade, increasing efforts in the neonatal brain imaging field have led to development of several neonatal parcellated atlases (Alexander et al, ; Alexander et al, ; Blesa et al, ; de Macedo Rodrigues et al, ; Feng et al, ; Gousias et al, ; Kuklisova‐Murgasova et al, ; Makropoulos et al, ; Oishi et al, ; Shi et al, ; Shi et al, ). These atlases differ in image modality and quality, parcellation technique, and parcellation schemes.…”