Novel diffuse white matter abnormality biomarker at term-equivalent age enhances prediction of long-term motor development in very preterm children

The Quartile Levels of Thyroid-stimulating Hormone at Newborn Screening Stratified Risks of Neurodevelopmental Impairment in Extremely Preterm Infants: A Population Cohort Study

BACKGROUND

To evaluate whether thyroid-stimulating hormone (TSH) measured during newborn screening (NBS) at birth and at discharge can be surrogate markers for neurodevelopmental impairment (NDI) in extremely preterm infants.

METHODS

The population cohort enrolled infants born <29 weeks' gestation in 2008-2020 in southern Taiwan. Infants with a maternal history of thyroid disorders and infants who required thyroxine supplementation during hospitalization were excluded. TSH levels measured during NBS at birth and at term-equivalent age (TEA)/discharge were respectively categorized into the lowest quartile, the interquartile range, and the highest quartile, which were correlated to NDI outcomes.

RESULTS

Among 392 patients with paired TSH data, 358 (91%) were prospectively followed until a corrected age of 24 months. At birth, infants with lowest-quartile TSH had higher NDI risks (odds ratio [OR] 2.3; 95% confidence interval [CI], 1.3-4.1, P = 0.004) compared to infants with interquartile-range TSH. Conversely, by TEA/discharge, infants with highest-quartile TSH had increased NDI (OR 1.9; 95% CI, 1.0-3.4, P = 0.03). By paired TSH categories, infants persistently in the lowest TSH quartile (48%; aOR 4.4; 95% CI, 1.4-14.5, P = 0.01) and those with a shift from interquartile range to the highest quartile (32%; aOR 2.7; 95% CI, 1.0-7.4, P = 0.046) had increased NDI risks compared with the reference with consistent interquartile-range TSH.

CONCLUSION

Extremely preterm infants persistently in the lowest-quartile TSH level at birth and at discharge had the highest NDI risk. TSH quartile levels measured during NBS may serve as a population surrogate biomarker for assessing NDI risks in infants born extremely preterm.

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.

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.

Prenatal tobacco smoke exposure and risk of brain abnormalities on magnetic resonance imaging at term in infants born very preterm

BACKGROUND

Prenatal tobacco smoke exposure and preterm birth are associated with abnormal brain and neurodevelopmental outcomes in infants. Studies that can disentangle indirect mediating effects from direct effects of prenatal tobacco smoke exposure on sensitive early brain magnetic resonance imaging biomarkers in very preterm infants are needed.

OBJECTIVE

This study aimed to determine whether prenatal tobacco smoke exposure in preterm infants posed any direct effects on magnetic resonance imaging-determined global brain abnormality score and secondary measures of brain abnormalities after removing any indirect mediating effects of preterm birth on neurostructural outcomes.

STUDY DESIGN

We examined brain magnetic resonance imaging findings collected at 39 to 44 weeks postmenstrual age from a prospective cohort of 395 infants born very preterm (gestational age of ≤32 weeks). The primary outcome was global brain abnormality score, and the secondary outcomes were global efficiency of structural connectome, diffuse white matter abnormality volume, total brain tissue volume, total gray and white matter volumes, and cerebellar volume. Maternal reports of smoking during pregnancy were obtained. We performed multivariable linear regression analyses to examine the association between prenatal tobacco smoke exposure and our magnetic resonance imaging outcomes, controlling for prospectively collected confounders. Moreover, we performed a mediation analysis to estimate the direct effects of prenatal tobacco smoke exposure on brain abnormalities and any indirect effects through preterm birth.

RESULTS

Overall, 12.6% of infants had prenatal tobacco smoke exposure. Infants with prenatal tobacco smoke exposure had a higher median global brain abnormality score than nonexposed infants (7 [interquartile range, 0-41] vs 5 [interquartile range, 0-34]; P≤.001); the findings remained significant (P<.001) after controlling for antenatal confounders. Global efficiency (P<.001), diffuse white matter volume (P=.037), and total brain tissue volume (P=.047) were significantly different between TSE groups in multivariable analyses. On mediation analysis, preterm birth mediated between 0% and 29% of the indirect effect of prenatal tobacco smoke exposure on several measures of brain abnormality outcomes. Thus, prenatal tobacco smoke exposure had a direct adverse effect between 71% and 100% on brain injury or abnormal development.

CONCLUSION

Our study has identified multiple adverse effects of prenatal tobacco smoke exposure on sensitive and objective measures of neonatal brain injury and abnormal development; most cases seemed to be a direct effect of prenatal tobacco smoke exposure on fetal brain development. The results underscored the significant adverse neurostructural effects of prenatal tobacco smoke exposure to tobacco smoke pollutants.

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.

MRI based radiomics enhances prediction of neurodevelopmental outcome in very preterm neonates

To predict adverse neurodevelopmental outcome of very preterm neonates. A total of 166 preterm neonates born between 24–32 weeks’ gestation underwent brain MRI early in life. Radiomics features were extracted from T1- and T2- weighted images. Motor, cognitive, and language outcomes were assessed at a corrected age of 18 and 33 months and 4.5 years. Elastic Net was implemented to select the clinical and radiomic features that best predicted outcome. The area under the receiver operating characteristic (AUROC) curve was used to determine the predictive ability of each feature set. Clinical variables predicted cognitive outcome at 18 months with AUROC 0.76 and motor outcome at 4.5 years with AUROC 0.78. T1-radiomics features showed better prediction than T2-radiomics on the total motor outcome at 18 months and gross motor outcome at 33 months (AUROC: 0.81 vs 0.66 and 0.77 vs 0.7). T2-radiomics features were superior in two 4.5-year motor outcomes (AUROC: 0.78 vs 0.64 and 0.8 vs 0.57). Combining clinical parameters and radiomics features improved model performance in motor outcome at 4.5 years (AUROC: 0.84 vs 0.8). Radiomic features outperformed clinical variables for the prediction of adverse motor outcomes. Adding clinical variables to the radiomics model enhanced predictive performance.

Magnetic resonance spectroscopy brain metabolites at term and 3-year neurodevelopmental outcomes in very preterm infants

BACKGROUND

Noninvasive advanced neuroimaging and neurochemical assessment can identify subtle abnormalities and predict neurodevelopmental impairments. Our objective was to quantify white matter metabolite levels and evaluate their relationship with neurodevelopmental outcomes at age 3 years.

METHODS

Our study evaluated a longitudinal prospective cohort of very premature infants (<32 weeks gestational age) with single-voxel proton magnetic resonance spectroscopy from the centrum semiovale performed at term-equivalent age and standardized cognitive, verbal, and motor assessments at 3 years corrected age. We separately examined metabolite ratios in the left and right centrum semiovale. We also conducted an exploratory interaction analysis for high/low socioeconomic status (SES) to evaluate the relationship between metabolites and neurodevelopmental outcomes, after adjusting for confounders.

RESULTS

We found significant relationships between choline/creatine levels in the left and right centrum semiovale and motor development scores. Exploratory interaction analyses revealed that, for infants with low SES, there was a negative association between choline/creatine in the left centrum semiovale and motor assessment scores at age 3 years.

CONCLUSIONS

Brain metabolites from the centrum semiovale at term-equivalent age were associated with motor outcomes for very preterm infants at 3 years corrected age. This effect may be most pronounced for infants with low SES.

IMPACT

Motor development at 3 years corrected age for very preterm infants is inversely associated with choline neurochemistry within the centrum semiovale on magnetic resonance spectroscopy at term-equivalent age, especially in infants with low socioeconomic status. No prior studies have studied metabolites in the centrum semiovale to predict neurodevelopmental outcomes at 3 years corrected age based on high/low socioeconomic status. For very preterm infants with lower socioeconomic status, higher choline-to-creatine ratio in central white matter is associated with worse neurodevelopmental outcomes.

Extracallosal Structural Connectivity Is Positively Associated With Language Performance in Well-Performing Children Born Extremely Preterm

Children born extremely preterm (<28 weeks gestation) are at risk for language delay or disorders. Decreased structural connectivity in preterm children has been associated with poor language outcome. Previously, we used multimodal imaging techniques to demonstrate that increased functional connectivity during a stories listening task was positively associated with language scores for preterm children. This functional connectivity was supported by extracallosal structural hyperconnectivity when compared to term-born children. Here, we attempt to validate this finding in a distinct cohort of well-performing extremely preterm children (EPT, n = 16) vs. term comparisons (TC, n = 28) and also compare this to structural connectivity in a group of extremely preterm children with a history of language delay or disorder (EPT-HLD, n = 8). All participants are 4-6 years of age. We perform q-space diffeomorphic reconstruction and functionally-constrained structural connectometry (based on fMRI activation), including a novel extension enabling between-groups comparisons with non-parametric ANOVA. There were no significant differences between groups in age, sex, race, ethnicity, parental education, family income, or language scores. For EPT, tracks positively associated with language scores included the bilateral posterior inferior fronto-occipital fasciculi and bilateral cerebellar peduncles and additional cerebellar white matter. Quantitative anisotropy in these pathways accounted for 55% of the variance in standardized language scores for the EPT group specifically. Future work will expand this cohort and follow longitudinally to investigate the impact of environmental factors on developing language networks and resiliency in the preterm brain.

Development of the pupillary light reflex from 9 to 24 months: association with common autism spectrum disorder (ASD) genetic liability and 3-year ASD diagnosis

BACKGROUND

Although autism spectrum disorder (ASD) is heritable, the mechanisms through which genes contribute to symptom emergence remain unclear. Investigating candidate intermediate phenotypes such as the pupillary light reflex (PLR) prospectively from early in development could bridge genotype and behavioural phenotype.

METHODS

Using eye tracking, we longitudinally measured the PLR at 9, 14 and 24 months in a sample of infants (N = 264) enriched for a family history of ASD; 27 infants received an ASD diagnosis at 3 years. We examined the 9- to 24-month developmental trajectories of PLR constriction latency (onset; ms) and amplitude (%) and explored their relation to categorical 3-year ASD outcome, polygenic liability for ASD and dimensional 3-year social affect (SA) and repetitive/restrictive behaviour (RRB) traits. Polygenic scores for ASD (PGS_ASD ) were calculated for 190 infants.

RESULTS

While infants showed a decrease in latency between 9 and 14 months, higher PGS_ASD was associated with a smaller decrease in latency in the first year (β = -.16, 95% CI = -0.31, -0.002); infants with later ASD showed a significantly steeper decrease in latency (a putative 'catch-up') between 14 and 24 months relative to those with other outcomes (typical: β = .54, 95% CI = 0.08, 0.99; other: β = .53, 95% CI = 0.02, 1.04). Latency development did not associate with later dimensional variation in ASD-related traits. In contrast, change in amplitude was not related to categorical ASD or genetics, but decreasing 9- to 14-month amplitude was associated with higher SA (β = .08, 95% CI = 0.01, 0.14) and RRB (β = .05, 95% CI = 0.004, 0.11) traits.

CONCLUSIONS

These findings corroborate PLR development as possible intermediate phenotypes being linked to both genetic liability and phenotypic outcomes. Future work should incorporate alternative measures (e.g. functionally informed structural and genetic measures) to test whether distinct neural mechanisms underpin PLR alterations.

Neurodevelopmental outcome of preterm very low birth weight infants admitted to an Italian tertiary center over an 11-year period

Preterm very low birth weight infants (VLBWi) are known to be at greater risk of adverse neurodevelopmental outcome. Identifying early factors associated with outcome is essential in order to refer patients for early intervention. Few studies have investigated neurodevelopmental outcome in Italian VLBWi. The aim of our longitudinal study is to describe neurodevelopmental outcome at 24 months of corrected age in an eleven-year cohort of 502 Italian preterm VLBWi and to identify associations with outcome. At 24 months, Griffiths’ Mental Developmental Scales were administered. Neurodevelopmental outcome was classified as: normal, minor sequelae (minor neurological signs, General Quotient between 76 and 87), major sequelae (cerebral palsy; General Quotient ≤ 75; severe sensory impairment). 75.3% showed a normal outcome, 13.9% minor sequelae and 10.8% major sequelae (3.8% cerebral palsy). Male gender, bronchopulmonary dysplasia, abnormal neonatal neurological assessment and severe brain ultrasound abnormalities were independently associated with poor outcome on multivariate ordered logistic regression. Rates of major sequelae are in line with international studies, as is the prevalence of developmental delay over cerebral palsy. Analysis of perinatal complications and the combination of close cUS monitoring and neurological assessment are still essential for early identification of infants with adverse outcome.

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.

Diffuse white matter abnormality in very preterm infants at term reflects reduced brain network efficiency

•

Most preterm infants exhibit regions of high signal intensity on T2 MRI at term.

•

Debate remains as to whether this signal (DWMA) is pathological.

•

We quantified DWMA and used graph theory to measure brain network efficiency.

•

Whole-brain and regional network efficiency at term decreased with greater DWMA.

•

DWMA in very preterm infants is associated with reduced brain efficiency at term.

Between 50 and 80% of very preterm infants (<32 weeks gestational age) exhibit increased white matter signal intensity on T2-weighted MRI at term-equivalent age, known as diffuse white matter abnormality (DWMA). A few studies have linked DWMA with microstructural abnormalities, but the exact relationship remains poorly understood. We related DWMA extent to graph theory measures of network efficiency at term in a representative cohort of 343 very preterm infants. We performed anatomic and diffusion MRI at term and quantified DWMA volume with our novel, semi-automated algorithm. From diffusion-weighted structural connectomes, we calculated the graph theory metrics local efficiency and clustering coefficient, which measure the ability of groups of nodes to perform specialized processing, and global efficiency, which assesses the ability of brain regions to efficiently combine information. We computed partial correlations between these measures and DWMA volume, adjusted for confounders. Increasing DWMA volume was associated with decreased global efficiency of the entire very preterm brain and decreased local efficiency and clustering coefficient in a variety of regions supporting cognitive, linguistic, and motor function. We show that DWMA is associated with widespread decreased brain network efficiency, suggesting that it is pathologic and likely has adverse developmental consequences.

Perinatal Risk and Protective Factors in the Development of Diffuse White Matter Abnormality on Term-Equivalent Age Magnetic Resonance Imaging in Infants Born Very Preterm

OBJECTIVE

To identify perinatal clinical diseases and treatments that are associated with the development of objectively diagnosed diffuse white matter abnormality (DWMA) on structural magnetic resonance imaging (MRI) at term-equivalent age in infants born very preterm.

STUDY DESIGN

A prospective cohort of 392 infants born very preterm (≤32 weeks of gestational age) was enrolled from 5 level III/IV neonatal intensive care units between September 2016 and November 2019. MRIs of the brain were collected at 39 to 45 weeks of postmenstrual age to evaluate DWMA volume. A predefined list of pertinent maternal characteristics, pregnancy/delivery data, and neonatal intensive care unit data were collected for enrolled patients to identify antecedents of objectively diagnosed DWMA.

RESULTS

Of the 392 infants in the cohort, 377 (96%) had high-quality MRI data. Their mean (SD) gestational age was 29.3 (2.5) weeks. In multivariable linear regression analyses, pneumothorax (P = .027), severe bronchopulmonary dysplasia (BPD) (P = .009), severe retinopathy of prematurity (P < .001), and male sex (P = .041) were associated with increasing volume of DWMA. The following factors were associated with decreased risk of DWMA: postnatal dexamethasone therapy for severe BPD (P = .004), duration of caffeine therapy for severe BPD (P = .009), and exclusive maternal milk diet at neonatal intensive care unit discharge (P = .049).

CONCLUSIONS

Severe retinopathy of prematurity and BPD exhibited the strongest adverse association with development of DWMA. We also identified treatments and nutritional factors that appear protective against the development of DWMA that also have implications for the clinical care of infants born very preterm.