In the last few decades, the survival rates of preterm babies and full-term babies
with severe diseases have increased due to advances in perinatal care. Understandably
however, higher survival rates have not been accompanied by an overall reduction of
morbidity, so that limitation of long-term neurodevelopmental abnormalities remains
a major challenge of early care (Plaisier et al., 2014). The possibility to better
predict the outcome of newborns at neurodevelopmental risk is essential to inform
early intervention, to allow best allocation of resources, and to minimize long-term
consequences. Unfortunately, clinicians continue to possess limited ability to predict
neurodevelopmental outcomes, mainly relying, in most settings, on early findings at
cranial ultrasound (cUS).
Recent studies (Smyser et al., 2012) have proven the power of magnetic resonance imaging
(MRI) superior to other neuroimaging modalities, including cUS, in detecting cerebral
injury. Neonatal MRI provides non-invasive, high-resolution images in less than 1 h;
scans are performed without sedation eliminating the risk and the costs associated
to it and are not associated to radiation exposure, as for computerized tomography
(CT). The application of MRI in the neonatal population is rapidly increasing, making
MRI one of the key diagnostic tools for the assessment of early brain development
and injury.
In specific clinical groups, such as for example very preterm infants, cerebral MRI
should become part of standard clinical care and should be systematically performed
at term equivalent age (TEA). Accurate assessment of cortical folding at TEA provides
an important marker for structural brain growth and maturation. Myelination of the
posterior limb of the internal capsule (PLIC) at around 36–38 weeks gestation, identifiable
on T1 but also on T2-weighted images, is another important maturational hallmark,
since its presence and symmetry are very powerful in predicting motor outcome. MR
imaging is superior to cUS also in detecting diffuse white matter (WM) injury. Indeed,
although cystic periventricular leukomalacia is seen less often, diffuse non-cystic
types of WM injury, including punctate WM lesions and diffuse excessive high signal
intensity, are most frequent and are considered the leading cause of disturbed brain
growth, connectivity, and functionality. The predictive power of conventional MRI
in this domain remains relatively low, as it is not sensitive enough to analyze changes
in microstructure; however, it is greatly enhanced by the use of advanced MR techniques
targeting the WM, such as diffusion tensor imaging (DTI), that can help analyzing
brain growth in extremely preterm babies in the absence of evident WM abnormalities
(Ramenghi et al., 2009).
Diffusion tensor imaging (DTI) is a relatively new MR modality that assesses water
diffusion in biological tissues at microstructural level. The diffusion tensor describes
an ellipsoid in space characterized by the diffusion eigenvalues (λ1,λ2,λ3) in the
three orthogonal directions and their corresponding eigenvectors. In brain WM, axial
diffusivity (λ1) is oriented along the direction of the main tracts and radial diffusivity
(λ2 and λ3) is oriented perpendicular to these tracts. Average diffusivity (D
av) reflects the mean of these eigenvalues and it is an indicator of brain maturation
and/or injury. D
av decreases with increasing age probably for decreasing water content and increasing
complexity of WM structures with myelination. Fractional anisotropy (FA) reflects
the variance of the eigenvalues, ranging from 0 (isotropic diffusion) to 1 (anisotropic).
The diffusion is mainly anisotropic because the water molecules preferentially move
in the direction of fascicles of axons (Adams et al., 2010). In the white and gray
matter, there is similar water content but different D
av value probably because the WM is less restrictive to water motion. Brain water
content decreases with increasing gestational age and this mostly increases the WM
anisotropy values. This increase has also been attributed to changes in WM structure
associated with histologic maturation, and it takes place at different rates in different
brain areas [the main areas analyzed are in commissural tracts, the corpus callosum
(CC), and in projection tracts, the corticospinal tracts (CSTs)]. Developmental changes
in anisotropy of cerebral cortex reflect changes in its microstructure, such as the
arborization of basal dendrites of cortical neurons, the innervation of the cortical
plate by thalamocortical and cortico-cortical fibers, all processes which are important
basis of later functional connectivity (Huppi and Dubois, 2006). Because there are
strongly preferred directions of diffusion, it is possible to create color maps of
neonatal brain with diffusion tensor post-processing techniques. The color maps are
based on major orientation with red representing right–left, green representing antero–posterior,
and blue representing superior–inferior anatomical directions (De Bruïne et al., 2013)
(Figure 1).
Figure 1
Color anisotropy maps.
Preterm birth can cause white matter injuries (WMIs) and consequently can cause change
in FA and diffusivity. Decreased FA in the CC of preterm babies scanned at TEA is
rather common and implies less efficient transmission between the hemispheres and
may lead to language problems and cognitive dysfunctions. Regions with increased FA
in a preterm baby may be attributed to a loss or to an impairment of WM instead of
improved WM maturation (Li et al., 2014). Disorders of motor function can be tested
in clinical practice with DTI. In children with congenital hemiparesis, there are
different diffusion characteristics of CSTs compared to healthy one. There is an increasing
FA asymmetry and a decrease in FA value in the affected pyramidal tract.
A recent extension of DTI is tractography, which is a powerful tool that offers the
possibility of non-invasive identification of specific WM pathways and connections
in the brain. The general principle is to connect adjacent image voxels following
water diffusion. Directional coherence of the fibers in a pathway is used to determine
the presence or absence of connectivity between two regions of the brain. Tracking
of the fiber-trajectories is terminated when they turn of too much degrees between
two successive voxels. The main regions of interest include the CSTs, the CC, and
optic radiations (OR). The primary goal should be to understand the normal relationship
between structural and functional networks of these structures but there are few data
in preterm babies (Brown et al., 2014). Preterm birth correlates with reduced connectivity,
and it is very difficult to establish normal value for all gestational ages. Maturation
does not occur simultaneously in the brain infact, for example, connectivity increases
earlier in the occipital lobe and then in the frontal area. The postnatal age and
WMI are additional confounding factors of diffusion metrics (Pannek et al., 2014).
Nevertheless, the primary difference between DTI and conventional imaging is the capability
of DTI to often detect injury earlier. This could anticipate the diagnosis of brain
damage and might offer advantages in the future for deciding early intervention or
administration of neuroprotective agents. Further studies will be needed to confirm
whether these new techniques may predict neurodevelopmental outcome and whether they
are equally applicable to all the pathways of the central nervous system.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial
or financial relationships that could be construed as a potential conflict of interest.