Hypertensive Disorders of Pregnancy and Risk of Early Brain Abnormalities on MRI at Term among Infants Born at ≤32 Weeks' Gestational Age.

OBJECTIVE: To evaluate the proximal effects of hypertensive disorders of pregnancy (HDP) on a validated measure of brain abnormalities in infants born at ≤32 weeks' gestational age (GA) using magnetic resonance imaging (MRI) at term-equivalent age. STUDY DESIGN: In a multisite prospective cohort study, 395 infants born at ≤32 weeks' GA, underwent 3T MRI scan between 39 through 44 weeks' postmenstrual age. A single neuroradiologist, blinded to clinical history, evaluated the standardized Kidokoro global brain abnormality score as the primary outcome. We classified infants as HDP-exposed by maternal diagnosis of chronic hypertension, gestational hypertension, preeclampsia, or eclampsia. Linear regression analysis identified the independent effects of HDP on infant brain abnormalities, adjusting for histologic chorioamnionitis, maternal smoking, antenatal steroids, magnesium sulfate, and infant sex. Mediation analyses quantified the indirect effect of HDP mediated via impaired intrauterine growth and prematurity and remaining direct effects on brain abnormalities. RESULTS: 170/395 infants (43%) were HDP-exposed. Adjusted multivariable analyses revealed HDP-exposed infants had 27% (95% CI 5-53%) higher brain abnormality scores than those without HDP exposure (p=0.02), primarily driven by increased white matter injury/abnormality scores (p=0.01). Mediation analyses showed HDP-induced impaired intrauterine growth significantly (p=0.02) contributed to brain abnormality scores (22% of the total effect). CONCLUSIONS: Maternal hypertension independently increased the risk for early brain injury and/or maturational delays in infants born at ≤32 weeks' GA with an indirect effect of 22% resulting from impaired intrauterine growth. Enhanced prevention/treatment of maternal hypertension may mitigate the risk of infant brain abnormalities and potential neurodevelopmental impairments.

Association of enlarged extra-axial spaces and subdural hemorrhage in preterm infants at term-equivalent age.

To determine the incidence of enlarged extra-axial space (EES) and its association with subdural hemorrhage (SDH) in a regional cohort of preterm infants. As part of a prospective cohort study of 395 preterm infants, brain magnetic resonance imaging (MRI) was collected on each infant at term-equivalent age. Six preterm infants showed evidence of SDH. We reviewed the MRIs to identify the incidence of EES in these 6 infants and the cohort broadly. We then completed a retrospective chart review of the 6 infants to identify any concerns for non-accidental trauma (NAT) since the MRI was obtained. The incidence of SDH in the cohort was 1.6%. The incidence of EES was 48.1% including all 6 infants with SDH. The incidence of SDH in infants with EES was 3.2%. The retrospective chart review of the 6 infants did not yield any evidence of NAT. The incidence of EES and SDH in our cohort was significantly higher than similar cohorts of term infants, demonstrating an increased risk in preterm infants. The incidence of SDH in infants with EES was greater than in the total cohort, suggesting that it is a risk factor for asymptomatic SDH in preterm infants.

Corpus Callosum Abnormalities at Term-Equivalent Age Are Associated with Language Development at 2 Years' Corrected Age in Infants Born Very Preterm.

We studied the effect of microstructural abnormalities in the corpus callosum on language development in 348 infants born very prematurely. We discovered that the fractional anisotropy of the corpus callosum anterior midbody was a significant predictor of standardized language scores at 2 years, independent of clinical and social risk factors.

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 systematic review of automated methods to perform white matter tract segmentation.

White matter tract segmentation is a pivotal research area that leverages diffusion-weighted magnetic resonance imaging (dMRI) for the identification and mapping of individual white matter tracts and their trajectories. This study aims to provide a comprehensive systematic literature review on automated methods for white matter tract segmentation in brain dMRI scans. Articles on PubMed, ScienceDirect [NeuroImage, NeuroImage (Clinical), Medical Image Analysis], Scopus and IEEEXplore databases and Conference proceedings of Medical Imaging Computing and Computer Assisted Intervention Society (MICCAI) and International Symposium on Biomedical Imaging (ISBI), were searched in the range from January 2013 until September 2023. This systematic search and review identified 619 articles. Adhering to the specified search criteria using the query, "white matter tract segmentation OR fiber tract identification OR fiber bundle segmentation OR tractography dissection OR white matter parcellation OR tract segmentation," 59 published studies were selected. Among these, 27% employed direct voxel-based methods, 25% applied streamline-based clustering methods, 20% used streamline-based classification methods, 14% implemented atlas-based methods, and 14% utilized hybrid approaches. The paper delves into the research gaps and challenges associated with each of these categories. Additionally, this review paper illuminates the most frequently utilized public datasets for tract segmentation along with their specific characteristics. Furthermore, it presents evaluation strategies and their key attributes. The review concludes with a detailed discussion of the challenges and future directions in this field.

Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome.

Very preterm (VPT) infants (born at less than 32 weeks gestational age) are at high risk for various adverse neurodevelopmental deficits. Unfortunately, most of these deficits cannot be accurately diagnosed until the age of 2-5 years old. Given the benefits of early interventions, accurate diagnosis and prediction soon after birth are urgently needed for VPT infants. Previous studies have applied deep learning models to learn the brain structural connectome (SC) to predict neurodevelopmental deficits in the preterm population. However, none of these models are specifically designed for graph-structured data, and thus may potentially miss certain topological information conveyed in the brain SC. In this study, we aim to develop deep learning models to learn the SC acquired at term-equivalent age for early prediction of neurodevelopmental deficits at 2 years corrected age in VPT infants. We directly treated the brain SC as a graph, and applied graph convolutional network (GCN) models to capture complex topological information of the SC. In addition, we applied the supervised contrastive learning (SCL) technique to mitigate the effects of the data scarcity problem, and enable robust training of GCN models. We hypothesize that SCL will enhance GCN models for early prediction of neurodevelopmental deficits in VPT infants using the SC. We used a regional prospective cohort of ∼280 VPT infants who underwent MRI examinations at term-equivalent age from the Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS). These VPT infants completed neurodevelopmental assessment at 2 years corrected age to evaluate cognition, language, and motor skills. Using the SCL technique, the GCN model achieved mean areas under the receiver operating characteristic curve (AUCs) in the range of 0.72∼0.75 for predicting three neurodevelopmental deficits, outperforming several competing models. Our results support our hypothesis that the SCL technique is able to enhance the GCN model in our prediction tasks.

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.

Prenatal tobacco smoke exposure and risk for cognitive delays in infants born very premature.

Prenatal tobacco smoke exposure (TSE) and prematurity are independent risk factors for abnormal neurodevelopment. The objectives were to compare differences in Bayley-III cognitive, language, and motor scores at 2 years corrected age (CA) in 395 infants born very preterm (≤ 32 weeks gestation) with and without prenatal TSE. We performed multivariable linear regression analyses to examine associations between prenatal TSE and neurodevelopmental outcomes and a mediation analysis to estimate direct effects of prenatal TSE on outcomes and indirect effects through preterm birth. In total, 50 (12.6%) infants had prenatal TSE. Infants with prenatal TSE had lower mean [95% CI] Cognitive score (82.8 [78.6, 87.1]) vs. nonexposed infants (91.7 [90.1, 93.4]). In children with and without prenatal TSE, there were significant differences in mean [95% CI] Language scores (81.7 [76.0, 87.4] vs. 92.4 [90.2, 94.6], respectively) and mean [95% CI] Motor scores (86.5 [82.2, 90.7] vs. 93.4 [91.8, 95.0], respectively); scores remained significant after controlling for confounders. Preterm birth indirectly mediated 9.0% of the total effect of prenatal TSE on Cognitive score (P = NS). However, 91% of the remaining total effect was significant and attributable to TSE's direct harmful effects on cognitive development (ß = - 5.17 [95% CI - 9.97, - 0.38]). The significant association is largely due to TSE's direct effect on cognitive development and not primarily due to TSE's indirect effect on preterm birth.

Mathematics abilities associated with adaptive functioning in preschool children born preterm.

It is well known that infants born very preterm (VPT) often demonstrate deficits in mathematical abilities in early childhood which are associated with poorer academic outcomes. Mathematic skills are also critical for other areas of functioning. However, it is not known whether mathematics skills are associated with adaptive functioning in children born preterm. Infants born at ≤31 weeks gestation and full term were recruited at birth and followed over time. At the 36-month corrected age assessment, children were administered the Early Number Concepts subtest of the Differential Abilities Scale, Second Edition, and caregivers completed the Adaptive Behavior Assessment System, Third Edition. After controlling for age, sex, cognitive abilities, and caregiver education, performance on the mathematics measure was uniquely and positively associated with adaptive behavior for preschool children in the VPT group only. Exploratory analyses revealed this association to be specifically related to the Practical and Social composites. Knowledge of concepts of number and quantity were associated with better adaptive functioning, particularly for behaviors related to functioning at home and in the community and play/social functioning, for children born VPT. Although replication is warranted, it would appear that mathematical skills may be an important early intervention target for children born VPT.

Feasibility and acceptability of an online parenting intervention to address behaviour problems in moderately to extremely preterm pre-school and school-age children.

BACKGROUND: Preterm birth is associated with adverse mental health outcomes, including internalizing problems, social difficulties and inattention. Interventions are needed beyond infancy and toddlerhood to support children and their families. We examined the feasibility and acceptability of the I-InTERACT Preterm pilot study, an online parenting intervention for preterm children ages 3-8. METHOD: Families participated in a weekly intervention comprised of seven sessions with online modules followed by videoconference coaching sessions with a therapist. Following completion of the study, caregivers completed a survey to assess their satisfaction and were asked to participate in a voluntary semi-structured interview to provide feedback. We anticipated greater than a 50% participation rate (enrollment feasibility) and 75% completion rate (adherence feasibility). We also hypothesized that at least 80% of participants would be satisfied with the intervention (acceptability). RESULTS: Nineteen of 32 families (59%) enrolled in the study, suggesting adequate enrollment feasibility. Feasibility of programme completion (adherence) was lower than anticipated (59%). Regarding satisfaction, all caregivers agreed that the programme's information was relevant to them and their family. Nearly all participants (92%) indicated that they had a better understanding of the effects of preterm birth on behaviour, that they enjoyed the programme, that it met their expectations and that they recommend the programme to others. In qualitative interviews, caregivers expressed satisfaction with the content, skills they learned, and receiving direct coaching. Caregivers suggested improvements to increase intervention feasibility and skill implementation, including offering biweekly sessions and more hands-on coaching. CONCLUSION: Our largely satisfactory acceptability rates suggest the value of and need for a parenting intervention for children born preterm past the initial period of early development. Future directions include modifying the intervention in response to caregiver feedback to improve recruitment, engagement and adherence.

Corpus callosum abnormalities at term-equivalent age are associated with language development at two years corrected age in infants born very preterm.

We studied the impact of microstructural abnormalities in the corpus callosum on language development in 348 infants born very prematurely. We discovered that the fractional anisotropy of the corpus callosum anterior midbody was a significant predictor of standardized language scores at two years, independent of clinical and social risk factors.

Language Outcomes of Children Born Very Preterm in Relation to Early Maternal Depression and Anxiety.

Unaddressed maternal psychological distress within the first year postpartum is known to have numerous negative consequences on the child's developmental outcomes, including language acquisition. This study examined the relationship between early maternal psychosocial factors and the language outcomes of children born very preterm (VPT; ≤32 weeks gestational age). It used data from the Cincinnati Infant Neurodevelopment Early Prediction Study, an ongoing National-Institutes-of-Health-funded prospective, multicenter cohort investigation of VPT infants. A total of 243 (125 boys; 118 girls) children born VPT (M = 29.03 weeks of gestation; SD = 2.47) and their corresponding 207 mothers (34 with multiple infants) were included in this study. We did not find an association between maternal depression or anxiety and Bayley-III (M = 92.3, SD = 18.9) language scores. Additionally, maternal grit and self-efficacy did not modify the relationship between depression and anxiety and language scores. A higher level of maternal education and infant female sex were significantly associated with higher language scores. While preterm birth typically results in higher rates of depression and anxiety for parents, the findings suggest that maternal depression, anxiety, and grit and the self-efficacy of the mothers in this sample did not relate to the language development of their children, independent of maternal education and infant female sex.

Correlation of NICU anthropometry in extremely preterm infants with brain development and language scores at early school age.

Growth in preterm infants in the neonatal intensive care unit (NICU) is associated with increased global and regional brain volumes at term, and increased postnatal linear growth is associated with higher language scores at age 2. It is unknown whether these relationships persist to school age or if an association between growth and cortical metrics exists. Using regression analyses, we investigated relationships between the growth of 42 children born extremely preterm (< 28 weeks gestation) from their NICU hospitalization, standardized neurodevelopmental/language assessments at 2 and 4-6 years, and multiple neuroimaging biomarkers obtained from T1-weighted images at 4-6 years. We found length at birth and 36 weeks post-menstrual age had positive associations with language scores at 2 years in multivariable linear regression. No growth metric correlated with 4-6 year assessments. Weight and head circumference at 36 weeks post-menstrual age positively correlated with total brain volume and negatively with global cortical thickness at 4-6 years of age. Head circumference relationships remained significant after adjusting for age, sex, and socioeconomic status. Right temporal cortical thickness was related to receptive language at 4-6 years in the multivariable model. Results suggest growth in the NICU may have lasting effects on brain development in extremely preterm children.

Parenting Interventions Targeting Behavior for Children Born Preterm or Low Birth Weight: A Systematic Review.

OBJECTIVE: To systematically review and summarize the outcomes of parenting interventions designed to improve child and/or parenting behavior for children born preterm and/or low birth weight (LBW). METHODS: We conducted systematic searches of Embase, Scopus, PubMed, PsycInfo, and CINAHL in September 2021. We identified articles published at any time that describe the outcomes of parenting interventions targeting the child and/or parenting behavior of children born preterm/LBW and their caregivers. Two independent raters assessed the risk of bias using the Revised Cochrane Risk-of-Bias Tool. RESULTS: Eight hundred sixteen titles and abstracts were screened, followed by 71 full-text articles, resulting in 24 eligible articles reporting on nine interventions with 1,676 participants. Eligible articles had an adequate risk of bias ratings. Sample characteristics, intervention components, and intervention effects were tabulated and described narratively by the intervention type. Preventative and treatment programs demonstrated positive intervention effects on externalizing behavior, parenting stress, and parenting behaviors, with mixed effects on internalizing behavior and emotion regulation. The few studies with longitudinal follow-up found little evidence of effects beyond 6 months postintervention. CONCLUSION: Behavior problems in children born preterm/LBW may be modifiable, and interventions targeting parenting behavior are promising. However, existing interventions may not produce long-lasting changes and are not designed for children older than four. Existing treatment programs may require adaptation for the neurocognitive, medical, and family needs of children born preterm/LBW (e.g., processing speed deficits, post-traumatic stress). Interventions that account for theories of sustained change may promote long-term effectiveness and the developmental tailoring of parenting skills.

A novel collaborative self-supervised learning method for radiomic data.

The computer-aided disease diagnosis from radiomic data is important in many medical applications. However, developing such a technique relies on labeling radiological images, which is a time-consuming, labor-intensive, and expensive process. In this work, we present the first novel collaborative self-supervised learning method to solve the challenge of insufficient labeled radiomic data, whose characteristics are different from text and image data. To achieve this, we present two collaborative pretext tasks that explore the latent pathological or biological relationships between regions of interest and the similarity and dissimilarity of information between subjects. Our method collaboratively learns the robust latent feature representations from radiomic data in a self-supervised manner to reduce human annotation efforts, which benefits the disease diagnosis. We compared our proposed method with other state-of-the-art self-supervised learning methods on a simulation study and two independent datasets. Extensive experimental results demonstrated that our method outperforms other self-supervised learning methods on both classification and regression tasks. With further refinement, our method will have the potential advantage in automatic disease diagnosis with large-scale unlabeled data available.

Dynamic weighted hypergraph convolutional network for brain functional connectome analysis.

The hypergraph structure has been utilized to characterize the brain functional connectome (FC) by capturing the high order relationships among multiple brain regions of interest (ROIs) compared with a simple graph. Accordingly, hypergraph neural network (HGNN) models have emerged and provided efficient tools for hypergraph embedding learning. However, most existing HGNN models can only be applied to pre-constructed hypergraphs with a static structure during model training, which might not be a sufficient representation of the complex brain networks. In this study, we propose a dynamic weighted hypergraph convolutional network (dwHGCN) framework to consider a dynamic hypergraph with learnable hyperedge weights. Specifically, we generate hyperedges based on sparse representation and calculate the hyper similarity as node features. The hypergraph and node features are fed into a neural network model, where the hyperedge weights are updated adaptively during training. The dwHGCN facilitates the learning of brain FC features by assigning larger weights to hyperedges with higher discriminative power. The weighting strategy also improves the interpretability of the model by identifying the highly active interactions among ROIs shared by a common hyperedge. We validate the performance of the proposed model on two classification tasks with three paradigms functional magnetic resonance imaging (fMRI) data from Philadelphia Neurodevelopmental Cohort. Experimental results demonstrate the superiority of our proposed method over existing hypergraph neural networks. We believe our model can be applied to other applications in neuroimaging for its strength in representation learning and interpretation.

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.

Neuroimaging of brain connectivity related to reading outcomes in children born preterm: A critical narrative review.

Premature children are at high risk for delays in language and reading, which can lead to poor school achievement. Neuroimaging studies have assessed structural and functional connectivity by diffusion MRI, functional MRI, and magnetoencephalography, in order to better define the "reading network" in children born preterm. Findings point to differences in structural and functional connectivity compared to children born at term. It is not entirely clear whether this discrepancy is due to delayed development or alternative mechanisms for reading, which may have developed to compensate for brain injury in the perinatal period. This narrative review critically appraises the existing literature evaluating the neural basis of reading in preterm children, summarizes the current findings, and suggests future directions in the field.

Early surgery in very preterm infants is associated with brain abnormalities on term MRI: a propensity score analysis.

OBJECTIVE: To investigate the association between exposure to surgery under general anesthesia and brain abnormalities and neurodevelopmental outcomes in very preterm infants. STUDY DESIGN: This prospective observational study includes 392 infants born at or below 32 weeks' gestational age. Participants completed brain MRI at term-equivalent age and Bayley-III assessment at 2 years corrected age. We evaluated the independent effects of surgery on brain MRI abnormalities and neurodevelopmental outcomes after propensity score matching. RESULTS: All infants completed brain MRI, and 341 (87%) completed neurodevelopmental testing. Forty-five received surgery. Surgery was associated with worse MRI abnormalities (p < 0.0001) but with none of the developmental outcomes after propensity score matching. The global brain abnormality score was associated with the Bayley Cognitive (p = 0.005) and Motor (p = 0.028) composite scores. CONCLUSIONS: Very preterm infants exposed to surgery under general anesthesia were at higher risk of brain abnormalities on MRI at term.