MRI at term equivalent age for predicting long-term neurodevelopmental outcome in preterm infants - a cohort study

Early brain microstructural development among preterm infants requiring caesarean section versus those delivered vaginally

It is known that the rate of caesarean section (C-section) has been increasing among preterm births. However, the relationship between C-section and long-term neurological outcomes is unclear. In this study, we utilized diffusion tensor imaging (DTI) to characterize the association of delivery method with brain white matter (WM) microstructural integrity in preterm infants. We retrospectively analyzed the DTI scans and health records of preterm infants without neuroimaging abnormality on pre-discharge term-equivalent MRI. We applied both voxel-wise and tract-based analyses to evaluate the association between delivery method and DTI metrics across WM tracts while controlling for numerous covariates. We included 68 preterm infants in this study (23 delivered vaginally, 45 delivered via C-section). Voxel-wise and tract-based analyses revealed significantly lower fractional anisotropy values and significantly higher diffusivity values across major WM tracts in preterm infants delivered via C-section when compared to those delivered vaginally. These results may be partially, but not entirely, mediated by lower birth weight among infants delivered by C-section. Nevertheless, these infants may be at risk for delayed neurodevelopment and could benefit from close neurological follow up for early intervention and mitigation of adverse long-term outcomes.

Impact of postnatal weight gain on brain white matter maturation in very preterm infants

BACKGROUND AND PURPOSE

Very preterm infants (VPIs, <32 weeks gestational age at birth) are prone to long-term neurological deficits. While the effects of birth weight and postnatal growth on VPIs' neurological outcome are well established, the neurobiological mechanism behind these associations remains elusive. In this study, we utilized diffusion tensor imaging (DTI) to characterize how birth weight and postnatal weight gain influence VPIs' white matter (WM) maturation.

METHODS

We included VPIs with complete birth and postnatal weight data in their health record, and DTI scan as part of their predischarge Magnetic Resonance Imaging (MRI). We conducted voxel-wise general linear model and tract-based regression analyses to explore the impact of birth weight and postnatal weight gain on WM maturation.

RESULTS

We included 91 VPIs in our analysis. After controlling for gestational age at birth and time between birth and scan, higher birth weight Z-scores were associated with DTI markers of more mature WM tracts, most prominently in the corpus callosum and sagittal striatum. The postnatal weight Z-score changes over the first 4 weeks of life were also associated with increased maturity in these WM tracts, when controlling for gestational age at birth, birth weight Z-score, and time between birth and scan.

CONCLUSIONS

In VPIs, birth weight and post-natal weight gain are associated with markers of brain WM maturation, particularly in the corpus callosum, which can be captured on discharge MRI. These neuroimaging metrics can serve as potential biomarkers for the early effects of nutritional interventions on VPIs' brain development.

Effect of a NICU to Home Physical Therapy Intervention on White Matter Trajectories, Motor Skills, and Problem-Solving Skills of Infants Born Very Preterm: A Case Series

Infants born very preterm (VPT; ≤29 weeks of gestation) are at high risk of developmental disabilities and abnormalities in neural white matter characteristics. Early physical therapy interventions such as Supporting Play Exploration and Early Development Intervention (SPEEDI2) are associated with improvements in developmental outcomes. Six VPT infants were enrolled in a randomised clinical trial of SPEEDI2 during the transition from the neonatal intensive care unit to home over four time points. Magnetic resonance imaging scans and fixel-based analysis were performed, and fibre density (FD), fibre cross-section (FC), and fibre density and cross-section values (FDC) were computed. Changes in white matter microstructure and macrostructure were positively correlated with cognitive, motor, and motor-based problem solving over time on developmental assessments. In all infants, the greatest increase in FD, FC, and FDC occurred between Visit 1 and 2 (mean chronological age: 2.68-6.22 months), suggesting that this is a potential window of time to optimally support adaptive development. Results warrant further studies with larger groups to formally compare the impact of intervention and disparity on neurodevelopmental outcomes in infants born VPT.

Neonatal motor functional connectivity and motor outcomes at age two years in very preterm children with and without high-grade brain injury

Preterm-born children have high rates of motor impairments, but mechanisms for early identification remain limited. We hypothesized that neonatal motor system functional connectivity (FC) would relate to motor outcomes at age two years; currently, this relationship is not yet well-described in very preterm (VPT; born <32 weeks' gestation) infants with and without brain injury. We recruited 107 VPT infants - including 55 with brain injury (grade III-IV intraventricular hemorrhage, cystic periventricular leukomalacia, post-hemorrhagic hydrocephalus) - and collected FC data at/near term-equivalent age (35-45 weeks postmenstrual age). Correlation coefficients were used to calculate the FC between bilateral motor and visual cortices and thalami. At two years corrected-age, motor outcomes were assessed with the Bayley Scales of Infant and Toddler Development, 3rd edition. Multiple imputation was used to estimate missing data, and regression models related FC measures to motor outcomes. Within the brain-injured group only, interhemispheric motor cortex FC was positively related to gross motor outcomes. Thalamocortical and visual FC were not related to motor scores. This suggests neonatal alterations in motor system FC may provide prognostic information about impairments in children with brain injury.

Proof of Concept of a Gamified DEvelopmental Assessment on an E-Platform (DEEP) Tool to Measure Cognitive Development in Rural Indian Preschool Children

Over 250 million children in developing countries are at risk of not achieving their developmental potential, and unlikely to receive timely interventions because existing developmental assessments that help identify children who are faltering are prohibitive for use in low resource contexts. To bridge this “detection gap,” we developed a tablet-based, gamified cognitive assessment tool named DEvelopmental assessment on an E-Platform (DEEP), which is feasible for delivery by non-specialists in rural Indian households and acceptable to all end-users. Here we provide proof-of-concept of using a supervised machine learning (ML) approach benchmarked to the Bayley’s Scale of Infant and Toddler Development, 3rd Edition (BSID-III) cognitive scale, to predict a child’s cognitive development using metrics derived from gameplay on DEEP. Two-hundred children aged 34–40 months recruited from rural Haryana, India were concurrently assessed using DEEP and BSID-III. Seventy percent of the sample was used for training the ML algorithms using a 10-fold cross validation approach and ensemble modeling, while 30% was assigned to the “test” dataset to evaluate the algorithm’s accuracy on novel data. Of the 522 features that computationally described children’s performance on DEEP, 31 features which together represented all nine games of DEEP were selected in the final model. The predicted DEEP scores were in good agreement (ICC [2,1] > 0.6) and positively correlated (Pearson’s r = 0.67) with BSID-cognitive scores, and model performance metrics were highly comparable between the training and test datasets. Importantly, the mean absolute prediction error was less than three points (<10% error) on a possible range of 31 points on the BSID-cognitive scale in both the training and test datasets. Leveraging the power of ML which allows iterative improvements as more diverse data become available for training, DEEP, pending further validation, holds promise to serve as an acceptable and feasible cognitive assessment tool to bridge the detection gap and support optimum child development.

Synthetic MRI of Preterm Infants at Term-Equivalent Age: Evaluation of Diagnostic Image Quality and Automated Brain Volume Segmentation

BACKGROUND AND PURPOSE

Neonatal MR imaging brain volume measurements can be used as biomarkers for long-term neurodevelopmental outcome, but quantitative volumetric MR imaging data are not usually available during routine radiologic evaluation. In the current study, the feasibility of automated quantitative brain volumetry and image reconstruction via synthetic MR imaging in very preterm infants was investigated.

MATERIALS AND METHODS

Conventional and synthetic T1WIs and T2WIs from 111 very preterm infants were acquired at term-equivalent age. Overall image quality and artifacts of the conventional and synthetic images were rated on a 4-point scale. Legibility of anatomic structures and lesion conspicuity were assessed on a binary scale. Synthetic MR volumetry was compared with that generated via MANTiS, which is a neonatal tissue segmentation toolbox based on T2WI.

RESULTS

Image quality was good or excellent for most conventional and synthetic images. The 2 methods did not differ significantly regarding image quality or diagnostic performance for focal and cystic WM lesions. Dice similarity coefficients had excellent overlap for intracranial volume (97.3%) and brain parenchymal volume (94.3%), and moderate overlap for CSF (75.6%). Bland-Altman plots demonstrated a small systematic bias in all cases (1.7%-5.9%) CONCLUSIONS: Synthetic T1WI and T2WI sequences may complement or replace conventional images in neonatal imaging, and robust synthetic volumetric results are accessible from a clinical workstation in less than 1 minute. Via the above-described methods, volume assessments could be routinely used in daily clinical practice.

Brain 3D-echographic early predictors of neuro-behavioral disorders in infants: a prospective observational study

Background: Prematurity, low birth weight (LBW), very low birth weight (VLBW), and intrauterine growth restriction (IUGR) are risk factors of long-term poor neuro-development outcomes and associate with reduction of regional brain volumes.Objective: To evaluate the possible role of 3D ultrasound sonography (3DUS) regional brain volumes, measured at 30-40 days of postnatal period, as early predictors of long-term risk of neuro-behavioral disorders.Methods: A highly selected population, which included: full-term, preterm, IUGR, and preterm-IUGR born individuals, was followed longitudinally from 30 to 40 days of postnatal period to the second year of life. The population was mostly composed of bichorionic twins to ensure a, theoretically, major intracategory homogeneity. Preterm and IUGR subjects were characterized by a gestational age (GA) and birth weight (BW)>32 weeks and >1500 g, respectively, whereas the full-term neonates were of 37 weeks GA. At enrollment, the assessment of the volumetric measurements was performed using the 3DUS. The evaluation of neuro-development was performed at 2 years using the Griffiths Mental Development Scales.Results: The 3DUS measurements of whole brain, thalamus, frontal cortex, and cerebellum volumes, assessed at 30-40 days of postnatal period, were significantly reduced in infants characterized by negative outcome. In addition, the respective areas of the ROC curves, made by comparing values of normal and abnormal neuro-development groups, were indicative of a strong diagnostic accuracy.Conclusion: Data found suggest that the 3DUS regional brain volumes may assume a significant role as early indicators of neonates at major risk of neuro-behavioral disorders in later life. Further and larger studies in this direction are needed to validate this significant perspective.

Are Simple Magnetic Resonance Imaging Biomarkers Predictive of Neurodevelopmental Outcome at Two Years in Very Preterm Infants?

BACKGROUND

Preterm infants are at increased risk of neurodevelopmental impairment due to the vulnerability of the immature brain. Early risk stratification is necessary for predicting outcome in the period of highest neuroplasticity. Several biomarkers in magnetic resonance imaging (MRI) at term equivalent age (TEA) have therefore been suggested.

OBJECTIVE

To assess the predictive value of simple brain metrics and the total abnormality score (TAS) - a modified score for brain injury and growth - in relation to neurodevelopmental outcome of very preterm infants in MRI at TEA.

METHODS

Single-centre cohort study including preterm infants with gestational age (GA) ≤32 weeks and birth weight ≤1,500 g. Biparietal width (BPW), interhemispheric distance, transcerebellar diameter (TCD) and TAS were assessed. To detect subtle haemorrhages, additional susceptibility-weighted imaging (SWI) was used in addition to conventional MRI to evaluate its clinical relevance. Neurodevelopment was tested by the Mental and Psychomotor Developmental Index (MDI/PDI) of the Bayley Scales of Infant Development II at a corrected age of 24 months.

RESULTS

One hundred twenty-nine children with median GA of 28.1 weeks and median birth weight of 980 g were included. BPW significantly correlated with PDI (p= 0.01, R2 = 0.06) and TCD with MDI (p < 0.01, R2 = 0.05) and PDI (p < 0.01, R2 = 0.06) but explained variances were low. TAS was not predictive of neurodevelopmental outcome. By using SWI, additional 4 cases of low grade haemorrhages were identified compared to conventional sequences. In one case this additional information was clinically relevant (MDI/PDI below average).

CONCLUSION

Simple brain metrics and TAS did not reliably predict neurodevelopmental outcome in a cohort with low prevalence of high grade brain injury. The additional value of SWI is yet to be determined in larger cohorts. The combination of imaging and functional biomarkers may be advisable for the prediction of neurodevelopmental outcome.