Early extra-uterine exposure alters regional cerebellar growth in infants born preterm

Preterm Birth Alters the Regional Development and Structural Covariance of Cerebellum at Term-Equivalent Age

Preterm birth is associated with increased risk for a spectrum of neurodevelopmental disabilities. The cerebellum is implicated in a wide range of cognitive functions extending beyond sensorimotor control and plays an increasingly recognized role in brain development. Morphometric studies based on volume analyses have revealed impaired cerebellar development in preterm infants. However, the structural covariance between the cerebellum and cerebral cortex has not been studied during the neonatal period, and the extent to which structural covariance is affected by preterm birth remains unknown. In this study, using the structural MR images of 52 preterm infants scanned at term-equivalent age and 312 full-term controls from the Developing Human Connectome Project, we compared volumetric growth, local cerebellum shape development and cerebello-cerebral structural covariance between the two groups. We found that although there was no significant difference in the overall volume measurements between preterm and full-term infants, the shape measurements were different. Compared with the control infants, preterm infants had significantly larger thickness in the vermis and lower thickness in the lateral portions of the bilateral cerebral hemispheres. The structural covariance between the cerebellum and frontal and parietal lobes was significantly greater in preterm infants than in full-term controls. The findings in this study suggested that cerebellar development and cerebello-cerebral structural covariance may be affected by premature birth.

Systemic postnatal corticosteroids and magnetic resonance imaging measurements of corpus callosum and cerebellum of extremely preterm infants

AIM

To compare the size of the corpus callosum (CC) and cerebellum on magnetic resonance imaging (MRI) brain scans conducted at term equivalent age (TEA) in extremely preterm infants who received systemic postnatal corticosteroids (PCS) to extremely preterm infants who did not receive systemic PCS and determine the dose-dependent effects on these outcomes.

METHODS

Single-centre retrospective cohort study including extremely preterm infants (born < 26 weeks' gestation) who had MRI brain scans at TEA. CC and cerebellar measurements were evaluated by two radiologists who were blinded to steroid use and their independent measurements were averaged. Comparative analyses were conducted between exposed (to systemic PCS) and non-exposed groups.

RESULTS

Eighty-three extremely preterm infants with mean (SD) 24.9 (0.91) weeks' gestational age, 721.8 (156) g birthweight were included; 38 with systemic PCS exposure and 45 without exposure. After adjustment for birthweight and other significant neonatal morbidities, there was no significant difference noted in corpus callosum length (CCL) between unexposed and exposed groups (adjusted mean (SE) 39.5 (0.57) mm vs. 38.5 (0.62) mm; P = 0.29). Similarly, the ratios of CCL/fronto-occipital diameter (FOD) and CCL/biparietal diameter (BPD) were not significantly different between the groups (CCL/FOD (0.40 (0.01) vs. 0.41 (0.01); P = 0.70) and CCL/BPD (0.51 (0.01) vs. 0.52 (0.01); P = 0.62)). Finally, no significant differences in cerebellar measurements, such as vermian height (adjusted mean (SE) 24.0 (0.46) mm vs. 23.5 (0.51 mm); P = 0.47) and transcerebellar diameter (adjusted mean (SE) 49.3 (0.74) mm vs. 4.78 (0.82) mm; P = 0.22) were found. No dose-dependent effects of systemic PCS on CC and cerebellar measurements were identified.

CONCLUSIONS

Systemic PCS use in extremely preterm infants was not associated with a change in the CC and cerebellar measurements on MRI brain scan at TEA.

Semi-automatic segmentation of the fetal brain from magnetic resonance imaging

Background

Volumetric measurements of fetal brain maturation in the third trimester of pregnancy are key predictors of developmental outcomes. Improved understanding of fetal brain development trajectories may aid in identifying and clinically managing at-risk fetuses. Currently, fetal brain structures in magnetic resonance images (MRI) are often manually segmented, which requires both time and expertise. To facilitate the targeting and measurement of brain structures in the fetus, we compared the results of five segmentation methods applied to fetal brain MRI data to gold-standard manual tracings.

Methods

Adult women with singleton pregnancies (n = 21), of whom five were scanned twice, approximately 3 weeks apart, were recruited [26 total datasets, median gestational age (GA) = 34.8, IQR = 30.9-36.6]. T2-weighted single-shot fast spin echo images of the fetal brain were acquired on 1.5T and 3T MRI scanners. Images were first combined into a single 3D anatomical volume. Next, a trained tracer manually segmented the thalamus, cerebellum, and total cerebral volumes. The manual segmentations were compared with five automatic methods of segmentation available within Advanced Normalization Tools (ANTs) and FMRIB's Linear Image Registration Tool (FLIRT) toolboxes. The manual and automatic labels were compared using Dice similarity coefficients (DSCs). The DSC values were compared using Friedman's test for repeated measures.

Results

Comparing cerebellum and thalamus masks against the manually segmented masks, the median DSC values for ANTs and FLIRT were 0.72 [interquartile range (IQR) = 0.6-0.8] and 0.54 (IQR = 0.4-0.6), respectively. A Friedman's test indicated that the ANTs registration methods, primarily nonlinear methods, performed better than FLIRT (p < 0.001).

Conclusion

Deformable registration methods provided the most accurate results relative to manual segmentation. Overall, this semi-automatic subcortical segmentation method provides reliable performance to segment subcortical volumes in fetal MR images. This method reduces the costs of manual segmentation, facilitating the measurement of typical and atypical fetal brain development.

Targeting Microglial Disturbances to Protect the Brain From Neurodevelopmental Disorders Associated With Prematurity

Microglial activation during critical phases of brain development can result in short- and long-term consequences for neurological and psychiatric health. Several studies in humans and rodents have shown that microglial activation, leading to a transition from the homeostatic state toward a proinflammatory phenotype, has adverse effects on the developing brain and neurodevelopmental disorders. Targeting proinflammatory microglia may be an effective strategy for protecting the brain and attenuating neurodevelopmental disorders induced by inflammation. In this review we focus on the role of inflammation and the activation of immature microglia (pre-microglia) soon after birth in prematurity-associated neurodevelopmental disorders, and the specific features of pre-microglia during development. We also highlight the relevance of immunomodulatory strategies for regulating activated microglia in a rodent model of perinatal brain injury. An original neuroprotective approach involving a nanoparticle-based therapy and targeting microglia, with the aim of improving myelination and protecting the developing brain, is also addressed.

Developmental score of the infant brain: characterizing diffusion MRI in term- and preterm-born infants

Large-scale longitudinal neuroimaging studies of the infant brain allow us to map the spatiotemporal development of the brain in its early phase. While the postmenstrual age (PMA) is commonly used as a time index to analyze longitudinal MRI data, the nonlinear relationship between PMA and MRI data imposes challenges for downstream analyses. We propose a mathematical model that provides a Developmental Score (DevS) as a data-driven time index to characterize the brain development based on MRI features. 319 diffusion tensor imaging (DTI) datasets were collected from 87 term-born and 66 preterm-born infants at multiple visits, which were automatically segmented based on the JHU neonatal atlas. The mean diffusivity (MD) and fractional anisotropy (FA) in 126 brain parcels were used in the model to derive DevS. We demonstrate that transforming the time index from PMA to DevS improves the linearity of the longitudinal changes in MD and FA in both gray and white matter structures. More importantly, regional developmental differences in DTI metrics between preterm- and term-born infants were identified more clearly using DevS, e.g. 79 structures showed significantly different regression patterns in MD between preterm- and term-born infants, compared to only 27 structures that showed group differences using PMA as the index. Therefore, the DevS model facilitates linear analyses of DTI metrics in the infant brain, and provides a useful tool to characterize altered brain development due to preterm-birth.

Altered local cerebellar and brainstem development in preterm infants

BACKGROUND

Premature birth is associated with high prevalence of neurodevelopmental impairments in surviving infants. The putative role of cerebellar and brainstem dysfunction remains poorly understood, particularly in the absence of overt structural injury.

METHOD

We compared in-utero versus ex-utero global, regional and local cerebellar and brainstem development in healthy fetuses (n ​= ​38) and prematurely born infants without evidence of structural brain injury on conventional MRI studies (n ​= ​74) that were performed at two time points: the first corresponding to the third trimester, either in utero or ex utero in the early postnatal period following preterm birth (30-40 weeks of gestation; 38 control fetuses; 52 premature infants) and the second at term equivalent age (37-46 weeks; 38 control infants; 58 premature infants). We compared 1) volumetric growth of 7 regions in the cerebellum (left and right hemispheres, left and right dentate nuclei, and the anterior, neo, and posterior vermis); 2) volumetric growth of 3 brainstem regions (midbrain, pons, and medulla); and 3) shape development in the cerebellum and brainstem using spherical harmonic description between the two groups.

RESULTS

Both premature and control groups showed regional cerebellar differences in growth rates, with the left and right cerebellar hemispheres showing faster growth compared to the vermis. In the brainstem, the pons grew faster than the midbrain and medulla in both prematurely born infants and controls. Using shape analyses, premature infants had smaller left and right cerebellar hemispheres but larger regional vermis and paravermis compared to in-utero control fetuses. For the brainstem, premature infants showed impaired growth of the superior surface of the midbrain, anterior surface of the pons, and inferior aspects of the medulla compared to the control fetuses. At term-equivalent age, premature infants had smaller cerebellar hemispheres bilaterally, extending to the superior aspect of the left cerebellar hemisphere, and larger anterior vermis and posteroinferior cerebellar lobes than healthy newborns. For the brainstem, large differences between premature infants and healthy newborns were found in the anterior surface of the pons.

CONCLUSION

This study analyzed both volumetric growth and shape development of the cerebellum and brainstem in premature infants compared to healthy fetuses using longitudinal MRI measurements. The findings in the present study suggested that preterm birth may alter global, regional and local development of the cerebellum and brainstem even in the absence of structural brain injury evident on conventional MRI.

Modelling brain development to detect white matter injury in term and preterm born neonates

Premature birth occurs during a period of rapid brain growth. In this context, interpreting clinical neuroimaging can be complicated by the typical changes in brain contrast, size and gyrification occurring in the background to any pathology. To model and describe this evolving background in brain shape and contrast, we used a Bayesian regression technique, Gaussian process regression, adapted to multiple correlated outputs. Using MRI, we simultaneously estimated brain tissue intensity on T1- and T2-weighted scans as well as local tissue shape in a large cohort of 408 neonates scanned cross-sectionally across the perinatal period. The resulting model provided a continuous estimate of brain shape and intensity, appropriate to age at scan, degree of prematurity and sex. Next, we investigated the clinical utility of this model to detect focal white matter injury. In individual neonates, we calculated deviations of a neonate's observed MRI from that predicted by the model to detect punctate white matter lesions with very good accuracy (area under the curve > 0.95). To investigate longitudinal consistency of the model, we calculated model deviations in 46 neonates who were scanned on a second occasion. These infants' voxelwise deviations from the model could be used to identify them from the other 408 images in 83% (T2-weighted) and 76% (T1-weighted) of cases, indicating an anatomical fingerprint. Our approach provides accurate estimates of non-linear changes in brain tissue intensity and shape with clear potential for radiological use.