Brain tissue microstructural and free-water composition 13 years after very preterm birth

Assessing neonatal brain glymphatic system development using diffusion tensor imaging along the perivascular space and choroid plexus volume

PURPOSE

Neonatal brain development constitutes a critical period of structural and functional maturation underpinning sensory, motor, and cognitive capacities. The glymphatic system-a cerebral waste clearance network-remains poorly understood in neonates. We investigated non-invasive magnetic resonance imaging (MRI) biomarkers of glymphatic system and their developmental correlates in neonates.

METHODS

In 117 neonates undergoing high-resolution T1-weighted and diffusion MRI, we quantified two glymphatic metrics: (1) diffusion tensor imaging along the perivascular space (DTI-ALPS) index, reflecting perivascular fluid dynamics; (2) choroid plexus (CP) volume, a cerebrospinal fluid (CSF) production marker. Associations with postmenstrual age (PMA) at MRI scan, gestational age (GA), birth weight (BW), and sex were analyzed using covariate-adjusted models.

RESULTS

Preterm neonates displayed significantly reduced DTI-ALPS indices versus term neonates (total index: 1.01 vs. 1.05, P = 0.002), with reductions persisting after adjustment (P < 0.05). CP volumes showed right-dominant pre-adjustment differences (preterm: 0.33 vs. term: 0.39, P = 0.039) that attenuated post-adjustment (P = 0.348). DTI-ALPS indices demonstrated transient correlations with PMA/GA/BW in unadjusted analyses (P < 0.05), whereas CP volumes maintained robust PMA associations post-adjustment in all neonates (P = 0.037) and term subgroup (P = 0.013). No significant effects of sex on both metrics were observed.

CONCLUSION

Our findings reveal prematurity-associated delays in glymphatic maturation, rather than biological sex. The persistent PMA-CP volume relationship suggests developmental regulation of CSF production, while attenuated DTI-ALPS correlations highlight covariate-mediated effects. These glymphatic metrics show potential for monitoring neurodevelopmental trajectories, though longitudinal validation is required to establish their clinical utility in neonatal care.

CLINICAL TRIAL NUMBER

Not applicable.

Widespread Associations between Behavioral Metrics and Brain Microstructure in ASD Suggest Age Mediates Subtypes of ASD

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and repetitive behaviors. Our lab has previously found that g-ratio, the proportion of axon width to myelin diameter, and axonal conduction velocity, which is associated with the capacity of an axon to carry information, are both decreased in ASD individuals. By associating these differences with performance on cognitive and behavioral tests, this study aims to first associate a broad array of behavioral metrics with neuroimaging markers of ASD, and to explore the prevalence of ASD subtypes using a neuroimaging driven perspective. Analyzing 273 participants (148 with ASD) ages 8 to 17 through an NIH-sponsored Autism Centers of Excellence network (MH100028), we observe widespread associations between behavioral and cognitive evaluations of autism and between behavioral and microstructural metrics, alongside different directional correlations between different behavioral metrics. Stronger associations with individual subcategories from each test rather than summary scores suggest that different neuronal profiles may be masked by composite test scores. Machine learning cluster analyses applied to neuroimaging data reinforce the association between neuroimaging and behavioral metrics and suggest that age-related maturation of brain metrics may drive changes in ASD behavior. This suggests that if ASD can be definitively subtyped, these subtypes may show different behavioral trajectories across the developmental period. Clustering identified a pattern of restrictive and repetitive behavior in some participants and a second group that was defined by high sensory sensitivity and language performance.

Children born very preterm experience altered cortical expansion over the first decade of life

The brain develops rapidly from the final trimester of gestation through childhood, with cortical surface area expanding greatly in the first decade of life. However, it is unclear exactly where and how cortical surface area changes after birth, or how prematurity affects these developmental trajectories. Fifty-two very preterm (gestational age at birth = 26 ± 1.6 weeks) and 41 full-term (gestational age at birth = 39 ± 1.2 weeks) infants were scanned using structural magnetic resonance imaging at term-equivalent age and again at 9/10 years of age. Individual cortical surface reconstructions were extracted for each scan. Infant and 9/10 cortical surfaces were aligned using anatomically constrained Multimodal Surface Matching (aMSM), a technique that allows calculation of local expansion gradients across the cortical surface for each individual subject. At the neonatal time point, very preterm infants had significantly smaller surface area than their full-term peers (P < 0.001), but at the age 9/10-year time point, very preterm and full-term children had comparable surface area (P > 0.05). Across all subjects, cortical expansion by age 9/10 years was most pronounced in frontal, temporal, and supramarginal/inferior parietal junction areas, which are key association cortices (P Spin < 0.001). Very preterm children showed greater cortical surface area expansion between term-equivalent age and age 9/10 compared to their full-term peers in the medial and lateral frontal areas, precuneus, and middle temporal/banks of the superior sulcus junction (P < 0.05). Furthermore, within the very preterm group, expansion was highly variable within the orbitofrontal cortex and posterior regions of the brain. By mapping these patterns across the cortex, we identify differences in association cortices that are known to be important for executive functioning, emotion processing, and social cognition. Additional longitudinal work will be needed to understand if increased expansion in very preterm children is adaptive, or if differences persist into adulthood.

Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a new approach to calculating axonal conduction velocity termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel formulation for calculating aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Conduction Velocity, G-ratio, and Extracellular Water as Microstructural Characteristics of Autism Spectrum Disorder

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a novel metric termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel neuroimaging metric, aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Fiber-Specific Measures of White Matter Microstructure and Macrostructure Are Associated With Internalizing and Externalizing Symptoms in Children Born Very Preterm and Full-term

BACKGROUND

Tensor-based investigations suggest that delayed or disrupted white matter development may relate to adverse behavioral outcomes in individuals born very preterm (VP); however, metrics derived from such models lack specificity. Here, we applied a fixel-based analysis framework to examine white matter microstructural and macrostructural correlates of concurrent internalizing and externalizing problems in VP and full-term (FT) children at 7 and 13 years.

METHODS

Diffusion imaging data were collected in a longitudinal cohort of VP and FT individuals (130 VP and 29 FT at 7 years, 125 VP and 44 FT at 13 years). Fixel-based measures of fiber density, fiber-bundle cross-section, and fiber density and cross-section were extracted from 21 white matter tracts previously implicated in psychopathology. Internalizing and externalizing symptoms were assessed using the Strengths and Difficulties Questionnaire parent report at 7 and 13 years.

RESULTS

At age 7 years, widespread reductions in fiber-bundle cross-section and fiber density and cross-section and tract-specific reductions in fiber density were related to more internalizing and externalizing symptoms irrespective of birth group. At age 13 years, fixel-based measures were not related to internalizing symptoms, while tract-specific reductions in fiber density, fiber-bundle cross-section, and fiber density and cross-section measures were related to more externalizing symptoms in the FT group only.

CONCLUSIONS

Age-specific neurobiological markers of internalizing and externalizing problems identified in this study extend previous tensor-based findings to inform pathophysiological models of behavior problems and provide the foundation for investigations into novel preventative and therapeutic interventions to mitigate risk in VP and other high-risk infant populations.

SynBOLD-DisCo: Synthetic BOLD images for distortion correction of fMRI without additional calibration scans

The blood oxygen level dependent (BOLD) signal from functional magnetic resonance imaging (fMRI) is a noninvasive technique that has been widely used in research to study brain function. However, fMRI suffers from susceptibility-induced off resonance fields which may cause geometric distortions and mismatches with anatomical images. State-of-the-art correction methods require acquiring reverse phase encoded images or additional field maps to enable distortion correction. However, not all imaging protocols include these additional scans and thus cannot take advantage of these susceptibility correction capabilities. As such, in this study we aim to enable state-of-the-art distortion correction with FSL's topup algorithm of historical and/or limited fMRI data that include only a structural image and single phase encoded fMRI. To do this, we use 3D U-net models to synthesize undistorted fMRI BOLD contrast images from the structural image and use this undistorted synthetic image as an anatomical target for distortion correction with topup. We evaluate the efficacy of this approach, named SynBOLD-DisCo (synthetic BOLD images for distortion correction), and show that BOLD images corrected using our approach are geometrically more similar to structural images than the distorted BOLD data and are practically equivalent to state-of-the-art correction methods which require reverse phase encoded data. Future directions include additional validation studies, integration with other preprocessing operations, retraining with broader pathologies, and investigating the effects of spin echo versus gradient echo images for training and distortion correction. In summary, we demonstrate SynBOLD-DisCo corrects distortion of fMRI when reverse phase encoding scans or field maps are not available.

Aberrant claustrum structure in preterm-born neonates: an MRI study

The human claustrum is a gray matter structure in the white matter between insula and striatum. Previous analysis found altered claustrum microstructure in very preterm-born adults associated with lower cognitive performance. As the claustrum development is related to hypoxia-ischemia sensitive transient cell populations being at-risk in premature birth, we hypothesized that claustrum structure is already altered in preterm-born neonates. We studied anatomical and diffusion-weighted MRIs of 83 preterm- and 83 term-born neonates at term-equivalent age. Additionally, claustrum development was analyzed both in a spectrum of 377 term-born neonates and longitudinally in 53 preterm-born subjects. Data was provided by the developing Human Connectome Project. Claustrum development showed increasing volume, increasing fractional anisotropy (FA), and decreasing mean diffusivity (MD) around term both across term- and preterm-born neonates. Relative to term-born ones, preterm-born neonates had (i) increased absolute and relative claustrum volumes, both indicating increased cellular and/or extracellular matter and being in contrast to other subcortical gray matter regions of decreased volumes such as thalamus; (ii) lower claustrum FA and higher claustrum MD, pointing at increased extracellular matrix and impaired axonal integrity; and (iii) aberrant covariance between claustrum FA and MD, respectively, and that of distributed gray matter regions, hinting at relatively altered claustrum microstructure. Results together demonstrate specifically aberrant claustrum structure in preterm-born neonates, suggesting altered claustrum development in prematurity, potentially relevant for later cognitive performance.