Automated brain morphometric biomarkers from MRI at term predict motor development in very preterm infants

Thalamic volume in very preterm infants: associations with severe brain injury and neurodevelopmental outcome at two years

Introduction

Several studies demonstrate the relationship between preterm birth and a reduced thalamus volume at term-equivalent age. In contrast, this study aims to investigate the link between the thalamic growth trajectory during the early postnatal period and neurodevelopment at two years of age.

Methods

Thalamic volume was extracted from 84 early MRI scans at postmenstrual age of 32.33 (± 2.63) weeks and 93 term-equivalent age MRI scans at postmenstrual age of 42.05 (± 3.33) weeks of 116 very preterm infants (56% male) with gestational age at birth of 29.32 (± 2.28) weeks and a birth weight of 1158.92 (± 348.59) grams. Cognitive, motor, and language outcomes at two years of age were assessed with Bayley Scales of Infant and Toddler Development Third Edition. Bivariate analysis was used to describe the clinical variables according to neurodevelopmental outcomes and multilevel linear regression models were used to examine the impact of these variables on thalamic volume and its relationship with neurodevelopmental outcomes.

Results

The results suggest an association between severe brain injury and thalamic growth trajectory (β coef = -0.611; p < 0.001). Moreover, thalamic growth trajectory during early postnatal life was associated with the three subscale scores of the neurodevelopmental assessment (cognitive: β coef = 6.297; p = 0.004; motor: β coef = 7.283; p = 0.001; language: β coeficient = 9.053; p = 0.002).

Discussion

These findings highlight (i) the impact of severe brain injury on thalamic growth trajectory during early extrauterine life after preterm birth and (ii) the relationship of thalamic growth trajectory with cognitive, motor, and language outcomes.

The developmental phenotype of motor delay in extremely preterm infants following early-life respiratory adversity is influenced by brain dysmaturation in the parietal lobe

BACKGROUND

Research indicates that preterm infants requiring prolonged mechanical ventilation often exhibit suboptimal neurodevelopment at follow-up, coupled with altered brain development as detected by magnetic resonance imaging (MRI) at term-equivalent age (TEA). However, specific regions of brain dysmaturation and the subsequent neurodevelopmental phenotype following early-life adverse respiratory exposures remain unclear. Additionally, it is uncertain whether brain dysmaturation mediates neurodevelopmental outcomes after respiratory adversity. This study aims to investigate the relationship between early-life adverse respiratory exposures, brain dysmaturation at TEA, and the developmental phenotype observed during follow-up in extremely preterm infants.

METHODS

89 infants born < 29 weeks' gestation from 2019 to 2021 received MRI examinations at TEA for structural and lobe brain volumes, which were adjusted with sex-and-postmenstrual-age expected volumes for volume residuals. Assisted ventilation patterns in the first 8 postnatal weeks were analyzed using kmlShape analyses. Patterns for motor, cognition, and language development were evaluated from corrected age 6 to 12 months using Bayley Scales of Infant Development, third edition. Mediation effects of brain volumes between early-life respiratory exposures and neurodevelopmental phenotypes were adjusted for sex, gestational age, maternal education, and severe brain injury.

RESULTS

Two distinct respiratory trajectories with varying severity were identified: improving (n = 35, 39%) and delayed improvement (n = 54, 61%). Compared with the improving group, the delayed improvement group exhibited selectively reduced brain volume residuals in the parietal lobe (mean - 4.9 cm3, 95% confidence interval - 9.4 to - 0.3) at TEA and lower motor composite scores (- 8.7, - 14.2 to - 3.1) at corrected age 12 months. The association between delayed respiratory improvement and inferior motor performance (total effect - 8.7, - 14.8 to - 3.3) was partially mediated through reduced parietal lobe volume (natural indirect effect - 1.8, - 4.9 to - 0.01), suggesting a mediating effect of 20%.

CONCLUSIONS

Early-life adverse respiratory exposure is specifically linked to the parietal lobe dysmaturation and neurodevelopmental phenotype of motor delay at follow-up. Dysmaturation of the parietal lobe serves as a mediator in the connection between respiratory adversity and compromised motor development. Optimizing respiratory critical care may emerge as a potential avenue to mitigate the consequences of altered brain growth and motor developmental delay in this extremely preterm population.

Extremely Preterm Infants with a Near-total Absence of Cerebellum: Usefulness of Quantitative Magnetic Resonance in Predicting the Motor Outcome

This study aims to evaluate in extremely premature infants the severity of brain structural injury causing total absence or near-total absence of cerebellar hemispheres by using MRI visual and volumetric scoring systems. It also aims to assess the role of the score systems in predicting motor outcome. We developed qualitative and quantitative MRI scoring systems to grade the overall brain damage severity in 16 infants with total absence or near-total absence of cerebellar hemispheres. The qualitative scoring system assessed the severity of macrostructural abnormalities of cerebellum, brainstem, supratentorial gray and white matters, ventricles while the quantitative scoring system weighted the loss of brain tissue volumes, and gross motor function classification system (GMFCS) was used to assess motor function at 1- and 5-year follow-ups.Positive correlations between both MRI scores and GMFCS scales were detected at follow-ups (p > 0.05), but only the volumetric score could identify those infants developing higher levels of motor impairment.Brain volumetric MRI offers an unbiassed assessment of prenatal brain damage. The quantitative scoring system, performed at term equivalent age, can be a helpful tool for predicting the long-term motor outcome in extremely preterm infants with a near-total absence of cerebellum.

Brain development in newborns and infants after ECMO

BACKGROUND

Extracorporeal membrane oxygenation (ECMO) not only significantly improves survival rates in severely ill neonates but also is associated with long-term neurodevelopmental issues. To systematically review the available literature on the neurodevelopmental outcomes of neonates and infants who have undergone ECMO treatment, with a focus on motor deficits, cognitive impairments, sensory impairments, and developmental delays. This review aims to understand the incidence, prevalence, and risk factors for these problems and to explore current nursing care and management strategies.

DATA SOURCES

A comprehensive literature search was performed across PubMed, EMBASE, and Web of Science using a wide array of keywords and phrases pertaining to ECMO, neonates, infants, and various facets of neurodevelopment. The initial screening involved reviewing titles and abstracts to exclude irrelevant articles, followed by a full-text assessment of potentially relevant literature. The quality of each study was evaluated based on its research methodology and statistical analysis. Moreover, citation searches were conducted to identify potentially overlooked studies. Although the focus was primarily on neonatal ECMO, studies involving children and adults were also included due to the limited availability of neonate-specific literature.

RESULTS

About 50% of neonates post-ECMO treatment exhibit varying degrees of brain injury, particularly in the frontal and temporoparietal white matter regions, often accompanied by neurological complications. Seizures occur in 18%-23% of neonates within the first 24 hours, and bleeding events occur in 27%-60% of ECMO procedures, with up to 33% potentially experiencing ischemic strokes. Although some studies suggest that ECMO may negatively impact hearing and visual development, other studies have found no significant differences; hence, the influence of ECMO remains unclear. In terms of cognitive, language, and intellectual development, ECMO treatment may be associated with potential developmental delays, including lower composite scores in cognitive and motor functions, as well as potential language and learning difficulties. These studies emphasize the importance of early detection and intervention of potential developmental issues in ECMO survivors, possibly necessitating the implementation of a multidisciplinary follow-up plan that includes regular neuromotor and psychological evaluations. Overall, further multicenter, large-sample, long-term follow-up studies are needed to determine the impact of ECMO on these developmental aspects.

CONCLUSIONS

The impact of ECMO on an infant's nervous system still requires further investigation with larger sample sizes for validation. Fine-tuned management, comprehensive nursing care, appropriate patient selection, proactive monitoring, nutritional support, and early rehabilitation may potentially contribute to improving the long-term outcomes for these infants.

Predicting 2-year neurodevelopmental outcomes in preterm infants using multimodal structural brain magnetic resonance imaging with local connectivity

The neurodevelopmental outcomes of preterm infants can be stratified based on the level of prematurity. We explored brain structural networks in extremely preterm (EP; < 28 weeks of gestation) and very-to-late (V-LP; ≥ 28 and < 37 weeks of gestation) preterm infants at term-equivalent age to predict 2-year neurodevelopmental outcomes. Using MRI and diffusion MRI on 62 EP and 131 V-LP infants, we built a multimodal feature set for volumetric and structural network analysis. We employed linear and nonlinear machine learning models to predict the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III) scores, assessing predictive accuracy and feature importance. Our findings revealed that models incorporating local connectivity features demonstrated high predictive performance for BSID-III subsets in preterm infants. Specifically, for cognitive scores in preterm (variance explained, 17%) and V-LP infants (variance explained, 17%), and for motor scores in EP infants (variance explained, 15%), models with local connectivity features outperformed others. Additionally, a model using only local connectivity features effectively predicted language scores in preterm infants (variance explained, 15%). This study underscores the value of multimodal feature sets, particularly local connectivity, in predicting neurodevelopmental outcomes, highlighting the utility of machine learning in understanding microstructural changes and their implications for early intervention.

Structural connectivity at term equivalent age and language in preterm children at 2 years corrected

We previously reported interhemispheric structural hyperconnectivity bypassing the corpus callosum in children born extremely preterm (<28 weeks) versus term children. This increased connectivity was positively associated with language performance at 4-6 years of age in our prior work. In the present study, we aim to investigate whether this extracallosal connectivity develops in extremely preterm infants at term equivalent age by leveraging a prospective cohort study of 350 very and extremely preterm infants followed longitudinally in the Cincinnati Infant Neurodevelopment Early Prediction Study. For this secondary analysis, we included only children born extremely preterm and without significant brain injury (n = 95). We use higher-order diffusion modelling to assess the degree to which extracallosal pathways are present in extremely preterm infants and predictive of later language scores at 22-26 months corrected age. We compare results obtained from two higher-order diffusion models: generalized q-sampling imaging and constrained spherical deconvolution. Advanced MRI was obtained at term equivalent age (39-44 weeks post-menstrual age). For structural connectometry analysis, we assessed the level of correlation between white matter connectivity at the whole-brain level at term equivalent age and language scores at 2 years corrected age, controlling for post-menstrual age, sex, brain abnormality score and social risk. For our constrained spherical deconvolution analyses, we performed connectivity-based fixel enhancement, using probabilistic tractography to inform statistical testing of the hypothesis that fibre metrics at term equivalent age relate to language scores at 2 years corrected age after adjusting for covariates. Ninety-five infants were extremely preterm with no significant brain injury. Of these, 53 had complete neurodevelopmental and imaging data sets that passed quality control. In the connectometry analyses adjusted for covariates and multiple comparisons (P < 0.05), the following tracks were inversely correlated with language: bilateral cerebellar white matter and middle cerebellar peduncles, bilateral corticospinal tracks, posterior commissure and the posterior inferior fronto-occipital fasciculus. No tracks from the constrained spherical deconvolution/connectivity-based fixel enhancement analyses remained significant after correction for multiple comparisons. Our findings provide critical information about the ontogeny of structural brain networks supporting language in extremely preterm children. Greater connectivity in more posterior tracks that include the cerebellum and connections to the regions of the temporal lobes at term equivalent age appears to be disadvantageous for language development.

Prenatal Opioid Exposure and Risk for Adverse Brain and Motor Outcomes in Infants Born Premature

OBJECTIVE

To compare brain magnetic resonance imaging (MRI) biomarkers and neurodevelopmental test scores in infants born preterm with and without prenatal opioid exposure (POE).

STUDY DESIGN

We examined 395 preterm infants (≤32 weeks gestational age) who had term-equivalent brain MRIs, composite scores from the Bayley Scales of Infant and Toddler Development-III at 2 years corrected age, and POE data. MRI parameters included total/regional brain volumes and severe punctate white matter lesions (PWMLs). We conducted bivariable analysis and multivariable logistic regression analyses.

RESULTS

The mean ± SD gestational age was 29.3 ± 2.5 weeks; 35 (8.9%) had POE and 20 (5.1%) had severe PWML. Compared with unexposed infants, those with POE exhibited higher rates of severe PWML (17.1% vs 3.9%, respectively; P = .002); findings remained significant with an OR of 4.16 (95% CI, 1.26-13.68) after adjusting for confounders. On mediation analysis, the significant relationship between POE and severe PWML was not indirectly mediated through preterm birth/gestational age (OR, 0.93; 95% CI, 0.78-1.10), thus suggesting the association was largely driven by a direct adverse effect of POE on white matter. In multivariable analyses, POE was associated with a significantly lower score by -6.2 (95% CI, -11.8 to -0.6) points on the Bayley Scales of Infant and Toddler Development-III Motor subscale compared with unexposed infants.

CONCLUSIONS

POE was associated with severe PWML; this outcome may be a direct effect of POE rather than being mediated by premature birth. POE was also associated with worse motor development. Continued follow-up to understand the long-term effects of POE is warranted.

Neuroinflammation, blood-brain barrier dysfunction, hippocampal atrophy and delayed neurodevelopment: Contributions for a rat model of congenital Zika syndrome

The congenital Zika syndrome (CZS) has been characterized as a set of several brain changes, such as reduced brain volume and subcortical calcifications, in addition to cognitive deficits. Microcephaly is one of the possible complications found in newborns exposed to Zika virus (ZIKV) during pregnancy, although it is an impacting clinical sign. This study aimed to investigate the consequences of a model of congenital ZIKV infection by evaluating the histopathology, blood-brain barrier, and neuroinflammation in pup rats 24 h after birth, and neurodevelopment of the offspring. Pregnant rats were inoculated subcutaneously with ZIKV-BR at the dose 1 × 107 plaque-forming unit (PFU mL-1) of ZIKV isolated in Brazil (ZIKV-BR) on gestational day 18 (G18). A set of pups, 24 h after birth, was euthanized. The brain was collected and later evaluated for the histopathology of brain structures through histological analysis. Additionally, analyses of the blood-brain barrier were conducted using western blotting, and neuroinflammation was assessed using ELISA. Another set of animals was evaluated on postnatal days 3, 6, 9, and 12 for neurodevelopment by observing the developmental milestones. Our results revealed hippocampal atrophy in ZIKV animals, in addition to changes in the blood-brain barrier structure and pro-inflammatory cytokines expression increase. Regarding neurodevelopment, a delay in important reflexes during the neonatal period in ZIKV animals was observed. These findings advance the understanding of the pathophysiology of CZS and contribute to enhancing the rat model of CZS.

MRI Assessment of the Relationship Between Cortical Morphological Features and Hemiparetic Motor-Related Outcomes in Chronic Subcortical Stroke Patients

BACKGROUND

It is unclear which cortical regions are specific to or commonly associated with the impairments of the upper/lower limbs and the activities of daily life (ADL) in stroke patients.

PURPOSE

To investigate the relationships between MRI-assessed surface-based morphometry (SBM) features and motor function as well as ADL in participants with chronic stroke.

STUDY TYPE

Prospective.

SUBJECTS

Thirty-five participants with subcortical stroke more than 3 months from the first-onset (age: 56.44 ± 9.56 years; 32 male).

FIELD STRENGTH/SEQUENCE

T₁ -weighted images, 3.0 T, three-dimensional fast field-echo sequence.

ASSESSMENT

FreeSurfer (6.0) was used to parcellate each hemisphere into 34 regions based on the Desikan-Killiany atlas and to extract the surface area, volume, thickness, and curvature. The motor function and ADL were assessed by the Fugl-Meyer Assessment for the Upper/Lower Extremity (FMA-UE/FMA-LE) and the Chinese version of the Modified Barthel Index (MBI-C), respectively.

STATISTICAL TESTS

A linear mixed-effect model was applied to evaluate the relationship between the morphological features and the FMA-UE, FMA-LE, and MBI-C. A false discovery rate corrected P value < 0.05 was considered statistically significant.

RESULTS

Correlations between the size of stroke lesion and MRI measurements did not pass the FDR correction (adjusted P > 0.05). SBM features in motor-related and high-order cognitive cortical regions showed significant correlations with FMA-UE and FMA-LE, respectively. Moreover, the thickness in the prefrontal cortex significantly positively correlated, while the surface area in the right supramarginal gyrus significantly negatively correlated, with both FMA-UE, FMA-LE, and MBI-C. The thickness in the left frontal lobe significantly positively correlated with both FMA-UE and MBI-C.

DATA CONCLUSION

This study's findings suggest that different hemiparetic motor-related outcomes in participants with subcortical stroke which suffered a corticospinal tract-related injury show specific, but also share common, associations with several cortical regions.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

A Semi-Supervised Graph Convolutional Network for Early Prediction of Motor Abnormalities in Very Preterm Infants

Approximately 32-42% of very preterm infants develop minor motor abnormalities. Earlier diagnosis soon after birth is urgently needed because the first two years of life represent a critical window of opportunity for early neuroplasticity in infants. In this study, we developed a semi-supervised graph convolutional network (GCN) model that is able to simultaneously learn the neuroimaging features of subjects and consider the pairwise similarity between them. The semi-supervised GCN model also allows us to combine labeled data with additional unlabeled data to facilitate model training. We conducted our experiments on a multisite regional cohort of 224 preterm infants (119 labeled subjects and 105 unlabeled subjects) who were born at 32 weeks or earlier from the Cincinnati Infant Neurodevelopment Early Prediction Study. A weighted loss function was applied to mitigate the impact of an imbalanced positive:negative (~1:2) subject ratio in our cohort. With only labeled data, our GCN model achieved an accuracy of 66.4% and an AUC of 0.67 in the early prediction of motor abnormalities, outperforming prior supervised learning models. By taking advantage of additional unlabeled data, the GCN model had significantly better accuracy (68.0%, p = 0.016) and a higher AUC (0.69, p = 0.029). This pilot work suggests that the semi-supervised GCN model can be utilized to aid early prediction of neurodevelopmental deficits in preterm infants.

Early brain morphometrics from neonatal MRI predict motor and cognitive outcomes at 2-years corrected age in very preterm infants

Infants born very preterm face a range of neurodevelopmental challenges in cognitive, language, behavioural and/or motor domains. Early accurate identification of those at risk of adverse neurodevelopmental outcomes, through clinical assessment and Magnetic Resonance Imaging (MRI), enables prognostication of outcomes and the initiation of targeted early interventions. This study utilises a prospective cohort of 181 infants born <31 weeks gestation, who had 3T MRIs acquired at 29-35 weeks postmenstrual age and a comprehensive neurodevelopmental evaluation at 2 years corrected age (CA). Cognitive, language and motor outcomes were assessed using the Bayley Scales of Infant and Toddler Development - Third Edition and functional motor outcomes using the Neuro-sensory Motor Developmental Assessment. By leveraging advanced structural MRI pre-processing steps to standardise the data, and the state-of-the-art developing Human Connectome Pipeline, early MRI biomarkers of neurodevelopmental outcomes were identified. Using Least Absolute Shrinkage and Selection Operator (LASSO) regression, significant associations between brain structure on early MRIs with 2-year outcomes were obtained (r = 0.51 and 0.48 for motor and cognitive outcomes respectively) on an independent 25% of the data. Additionally, important brain biomarkers from early MRIs were identified, including cortical grey matter volumes, as well as cortical thickness and sulcal depth across the entire cortex. Adverse outcome on the Bayley-III motor and cognitive composite scores were accurately predicted, with an Area Under the Curve of 0.86 for both scores. These associations between 2-year outcomes and patient prognosis and early neonatal MRI measures demonstrate the utility of imaging prior to term equivalent age for providing earlier commencement of targeted interventions for infants born preterm.

Diffuse excessive high signal intensity in the preterm brain on advanced MRI represents widespread neuropathology

Preterm brains commonly exhibit elevated signal intensity in the white matter on T2-weighted MRI at term-equivalent age. This signal, known as diffuse excessive high signal intensity (DEHSI) or diffuse white matter abnormality (DWMA) when quantitatively assessed, is associated with abnormal microstructure on diffusion tensor imaging. However, postmortem data are largely lacking and difficult to obtain, and the pathological significance of DEHSI remains in question. In a cohort of 202 infants born preterm at ≤32 weeks gestational age, we leveraged two newer diffusion MRI models - Constrained Spherical Deconvolution (CSD) and neurite orientation dispersion and density index (NODDI) - to better characterize the macro and microstructural properties of DWMA and inform the ongoing debate around the clinical significance of DWMA. With increasing DWMA volume, fiber density broadly decreased throughout the white matter and fiber cross-section decreased in the major sensorimotor tracts. Neurite orientation dispersion decreased in the centrum semiovale, corona radiata, and temporal lobe. These findings provide insight into DWMA's biological underpinnings and demonstrate that it is a serious pathology.

A novel Ontology-guided Attribute Partitioning ensemble learning model for early prediction of cognitive deficits using quantitative Structural MRI in very preterm infants

Structural magnetic resonance imaging studies have shown that brain anatomical abnormalities are associated with cognitive deficits in preterm infants. Brain maturation and geometric features can be used with machine learning models for predicting later neurodevelopmental deficits. However, traditional machine learning models would suffer from a large feature-to-instance ratio (i.e., a large number of features but a small number of instances/samples). Ensemble learning is a paradigm that strategically generates and integrates a library of machine learning classifiers and has been successfully used on a wide variety of predictive modeling problems to boost model performance. Attribute (i.e., feature) bagging method is the most commonly used feature partitioning scheme, which randomly and repeatedly draws feature subsets from the entire feature set. Although attribute bagging method can effectively reduce feature dimensionality to handle the large feature-to-instance ratio, it lacks consideration of domain knowledge and latent relationship among features. In this study, we proposed a novel Ontology-guided Attribute Partitioning (OAP) method to better draw feature subsets by considering the domain-specific relationship among features. With the better-partitioned feature subsets, we developed an ensemble learning framework, which is referred to as OAP-Ensemble Learning (OAP-EL). We applied the OAP-EL to predict cognitive deficits at 2 years of age using quantitative brain maturation and geometric features obtained at term equivalent age in very preterm infants. We demonstrated that the proposed OAP-EL approach significantly outperformed the peer ensemble learning and traditional machine learning approaches.

Altered Cerebral Curvature in Preterm Infants Is Associated with the Common Genetic Variation Related to Autism Spectrum Disorder and Lipid Metabolism

Preterm births are often associated with neurodevelopmental impairment. In the critical developmental period of the fetal brain, preterm birth disrupts cortical maturation. Notably, preterm birth leads to alterations in the fronto-striatal and temporal lobes and the limbic region. Recent advances in MRI acquisition and analysis methods have revealed an integrated approach to the genetic influence on brain structure. Based on imaging studies, we hypothesized that the altered cortical structure observed after preterm birth is associated with common genetic variations. We found that the presence of the minor allele at rs1042778 in OXTR was associated with reduced curvature in the right medial orbitofrontal gyrus (p < 0.001). The presence of the minor allele at rs174576 in FADS2 (p < 0.001) or rs740603 in COMT (p < 0.001) was related to reduced curvature in the left posterior cingulate gyrus. This study provides biological insight into altered cortical curvature at term-equivalent age, suggesting that the common genetic variations related to autism spectrum disorder (ASD) and lipid metabolism may mediate vulnerability to early cortical dysmaturation in preterm infants.

Association between brain structural network efficiency at term-equivalent age and early development of cerebral palsy in very preterm infants

Very preterm infants (born at less than 32 weeks gestational age) are at high risk for serious motor impairments, including cerebral palsy (CP). The brain network changes that antecede the early development of CP in infants are not well characterized, and a better understanding may suggest new strategies for risk-stratification at term, which could lead to earlier access to therapies. Graph theoretical methods applied to diffusion MRI-derived brain connectomes may help quantify the organization and information transfer capacity of the preterm brain with greater nuance than overt structural or regional microstructural changes. Our aim was to shed light on the pathophysiology of early CP development, before the occurrence of early intervention therapies and other environmental confounders, to help identify the best early biomarkers of CP risk in VPT infants. In a cohort of 395 very preterm infants, we extracted cortical morphometrics and brain volumes from structural MRI and also applied graph theoretical methods to diffusion MRI connectomes, both acquired at term-equivalent age. Metrics from graph network analysis, especially global efficiency, strength values of the major sensorimotor tracts, and local efficiency of the motor nodes and novel non-motor regions were strongly inversely related to early CP diagnosis. These measures remained significantly associated with CP after correction for common risk factors of motor development, suggesting that metrics of brain network efficiency at term may be sensitive biomarkers for early CP detection. We demonstrate for the first time that in VPT infants, early CP diagnosis is anteceded by decreased brain network segregation in numerous nodes, including motor regions commonly-associated with CP and also novel regions that may partially explain the high rate of cognitive impairments concomitant with CP diagnosis. These advanced MRI biomarkers may help identify the highest risk infants by term-equivalent age, facilitating earlier interventions that are informed by early pathophysiological changes.

Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age

INTRODUCTION

The dynamic nature and complexity of the cellular events that take place during the last trimester of pregnancy make the developing cortex particularly vulnerable to perturbations. Abrupt interruption to normal gestation can lead to significant deviations to many of these processes, resulting in atypical trajectory of cortical maturation in preterm birth survivors.

METHODS

We sought to first map typical cortical micro- and macrostructure development using invivo MRI in a large sample of healthy term-born infants scanned after birth (n = 259). Then we offer a comprehensive characterization of the cortical consequences of preterm birth in 76 preterm infants scanned at term-equivalent age (37-44 weeks postmenstrual age). We describe the group-average atypicality, the heterogeneity across individual preterm infants, and relate individual deviations from normative development to age at birth and neurodevelopment at 18 months.

RESULTS

In the term-born neonatal brain, we observed heterogeneous and regionally specific associations between age at scan and measures of cortical morphology and microstructure, including rapid surface expansion, greater cortical thickness, lower cortical anisotropy and higher neurite orientation dispersion. By term-equivalent age, preterm infants had on average increased cortical tissue water content and reduced neurite density index in the posterior parts of the cortex, and greater cortical thickness anteriorly compared to term-born infants. While individual preterm infants were more likely to show extreme deviations (over 3.1 standard deviations) from normative cortical maturation compared to term-born infants, these extreme deviations were highly variable and showed very little spatial overlap between individuals. Measures of regional cortical development were associated with age at birth, but not with neurodevelopment at 18 months.

CONCLUSION

We showed that preterm birth alters cortical micro- and macrostructural maturation near the time of full-term birth. Deviations from normative development were highly variable between individual preterm infants.

Early micro- and macrostructure of sensorimotor tracts and development of cerebral palsy in high risk infants

Infants born very preterm (VPT) are at high risk of motor impairments such as cerebral palsy (CP), and diagnosis can take 2 years. Identifying in vivo determinants of CP could facilitate presymptomatic detection and targeted intervention. Our objectives were to derive micro‐ and macrostructural measures of sensorimotor white matter tract integrity from diffusion MRI at term‐equivalent age, and determine their association with early diagnosis of CP. We enrolled 263 VPT infants (≤32 weeks gestational age) as part of a large prospective cohort study. Diffusion and structural MRI were acquired at term. Following consensus guidelines, we defined early diagnosis of CP based on abnormal structural MRI at term and abnormal neuromotor exam at 3–4 months corrected age. Using Constrained Spherical Deconvolution, we derived a white matter fiber orientation distribution (fOD) for subjects, performed probabilistic whole‐brain tractography, and segmented nine sensorimotor tracts of interest. We used the recently developed fixel‐based (FB) analysis to compute fiber density (FD), fiber‐bundle cross‐section (FC), and combined fiber density and cross‐section (FDC) for each tract. Of 223 VPT infants with high‐quality diffusion MRI data, 14 (6.3%) received an early diagnosis of CP. The cohort's mean (SD) gestational age was 29.4 (2.4) weeks and postmenstrual age at MRI scan was 42.8 (1.3) weeks. FD, FC, and FDC for each sensorimotor tract were significantly associated with early CP diagnosis, with and without adjustment for confounders. Measures of sensorimotor tract integrity enhance our understanding of white matter changes that antecede and potentially contribute to the development of CP in VPT infants.