Newborns and preterm infants at term equivalent age: A semi-quantitative assessment of cerebral maturity

Quantitative Magnetic Resonance Imaging for Neurodevelopmental Outcome Prediction in Neonates Born Extremely Premature-An Exploratory Study

PURPOSE

Neonates born at < 28 weeks of gestation are at risk for neurodevelopmental delay. The aim of this study was to identify quantitative MR-based metrics for the prediction of neurodevelopmental outcomes in extremely preterm neonates.

METHODS

T1-/T2-relaxation times (T1R/T2R), ADC, and fractional anisotropy (FA) of the left/right posterior limb of the internal capsule (PLIC) and the brainstem were determined at term-equivalent ages in a sample of extremely preterm infants (n = 33). Scores for cognitive, language, and motor outcomes were collected at one year corrected-age. Pearson's correlation analyses detected relationships between quantitative measures and outcome data. Stepwise regression procedures identified imaging metrics to estimate neurodevelopmental outcomes.

RESULTS

Cognitive outcomes correlated significantly with T2R (r = 0.412; p = 0.017) and ADC (r = -0.401; p = 0.021) (medulla oblongata). Furthermore, there were significant correlations between motor outcomes and T1R (pontine tegmentum (r = 0.346; p = 0.049), midbrain (r = 0.415; p = 0.016), right PLIC (r = 0.513; p = 0.002), and left PLIC (r = 0.504; p = 0.003)); T2R (right PLIC (r = 0.405; p = 0.019)); ADC (medulla oblongata (r = -0.408; p = 0.018) and pontine tegmentum (r = -0.414; p = 0.017)); and FA (pontine tegmentum (r = -0.352; p = 0.045)). T2R/ADC (medulla oblongata) (cognitive outcomes (R2 = 0.296; p = 0.037)) and T1R (right PLIC)/ADC (medulla oblongata) (motor outcomes (R2 = 0.405; p = 0.009)) revealed predictive potential for neurodevelopmental outcomes.

CONCLUSION

There are relationships between relaxometry‑/DTI-based metrics determined by neuroimaging near term and neurodevelopmental outcomes collected at one year of age. Both modalities bear prognostic potential for the prediction of cognitive and motor outcomes. Thus, quantitative MRI at term-equivalent ages represents a promising approach with which to estimate neurologic development in extremely preterm infants.

Neurodevelopmental outcome in preterm infants with intraventricular hemorrhages: the potential of quantitative brainstem MRI

OBJECTIVES

This retrospective study aimed to identify quantitative magnetic resonance imaging markers in the brainstem of preterm neonates with intraventricular hemorrhages. It delves into the intricate associations between quantitative brainstem magnetic resonance imaging metrics and neurodevelopmental outcomes in preterm infants with intraventricular hemorrhage, aiming to elucidate potential relationships and their clinical implications.

MATERIALS AND METHODS

Neuroimaging was performed on preterm neonates with intraventricular hemorrhage using a multi-dynamic multi-echo sequence to determine T1 relaxation time, T2 relaxation time, and proton density in specific brainstem regions. Neonatal outcome scores were collected using the Bayley Scales of Infant and Toddler Development. Statistical analysis aimed to explore potential correlations between magnetic resonance imaging metrics and neurodevelopmental outcomes.

RESULTS

Sixty preterm neonates (mean gestational age at birth 26.26 ± 2.69 wk; n = 24 [40%] females) were included. The T2 relaxation time of the midbrain exhibited significant positive correlations with cognitive (r = 0.538, P < 0.0001, Pearson's correlation), motor (r = 0.530, P < 0.0001), and language (r = 0.449, P = 0.0008) composite scores at 1 yr of age.

CONCLUSION

Quantitative magnetic resonance imaging can provide valuable insights into neurodevelopmental outcomes after intraventricular hemorrhage, potentially aiding in identifying at-risk neonates. Multi-dynamic multi-echo sequence sequences hold promise as an adjunct to conventional sequences, enhancing the sensitivity of neonatal magnetic resonance neuroimaging and supporting clinical decision-making for these vulnerable patients.

[Effects of antenatal corticosteroid therapy in pregnant women on the brain development of preterm infants as assessed by amplitude-integrated electroencephalography]

OBJECTIVES

To investigate the effects of antenatal corticosteroid (ACS) therapy in pregnant women on the brain development of preterm infants using amplitude-integrated electroencephalography (aEEG).

METHODS

A retrospective analysis was conducted on 211 preterm infants with a gestational age of 28 to 34+6 weeks. The infants were divided into an ACS group (131 cases) and a control group (80 cases) based on whether antenatal dexamethasone was given for promoting fetal lung maturity. The first aEEG monitoring (referred to as aEEG1) was performed within 24 hours after birth, and the second aEEG monitoring (referred to as aEEG2) was performed between 5 to 7 days after birth. The aEEG results were compared between the two groups.

RESULTS

In preterm infants with a gestational age of 28 to 31+6 weeks, the ACS group showed a more mature periodic pattern and higher lower amplitude boundary in aEEG1 compared to the control group (P<0.05). In preterm infants with a gestational age of 32 to 33+6 weeks and 34 to 34+6 weeks, the ACS group showed a higher proportion of continuous patterns, more mature periodic patterns and higher Burdjalov scores in aEEG1 (P<0.05). And the ACS group exhibited a higher proportion of continuous patterns, more mature periodic patterns, higher lower amplitude boundaries, narrower bandwidths, and higher Burdjalov scores in aEEG2 (P<0.05).

CONCLUSIONS

ACS-treated preterm infants have more mature aEEG patterns compared to those not treated with ACS, suggesting a beneficial effect of ACS on the brain development of preterm infants.

Machine Learning-Derived Active Sleep as an Early Predictor of White Matter Development in Preterm Infants

White matter dysmaturation is commonly seen in preterm infants admitted to the neonatal intensive care unit (NICU). Animal research has shown that active sleep is essential for early brain plasticity. This study aimed to determine the potential of active sleep as an early predictor for subsequent white matter development in preterm infants. Using heart and respiratory rates routinely monitored in the NICU, we developed a machine learning-based automated sleep stage classifier in a cohort of 25 preterm infants (12 females). The automated classifier was subsequently applied to a study cohort of 58 preterm infants (31 females) to extract active sleep percentage over 5-7 consecutive days during 29-32 weeks of postmenstrual age. Each of the 58 infants underwent high-quality T2-weighted magnetic resonance brain imaging at term-equivalent age, which was used to measure the total white matter volume. The association between active sleep percentage and white matter volume was examined using a multiple linear regression model adjusted for potential confounders. Using the automated classifier with a superior sleep classification performance [mean area under the receiver operating characteristic curve (AUROC) = 0.87, 95% CI 0.83-0.92], we found that a higher active sleep percentage during the preterm period was significantly associated with an increased white matter volume at term-equivalent age [β = 0.31, 95% CI 0.09-0.53, false discovery rate (FDR)-adjusted p-value = 0.021]. Our results extend the positive association between active sleep and early brain development found in animal research to human preterm infants and emphasize the potential benefit of sleep preservation in the NICU setting.

Development and validation of a predictive model for fetal cerebral maturation using ultrasound for fetuses with normal growth and fetal growth restriction

Background

Investigation of fetal cerebral maturation (FCM) is necessary and important to provide crucial prognostic information for normal and high-risk fetuses. The study aimed to develop a valid and quantitative predictive model for assessing FCM using ultrasound and validate the model for fetuses with normal and restricted growth.

Methods

This was a multicenter prospective observational study. Fetuses with normal growth recruited from a university teaching hospital (Center 1) and a municipal maternal unit (Center 2) were included in the training set and external validation set 1, respectively. The 124 growth-restricted fetuses enrolled in Center 1 were included in validation set 2. FCM was used to describe the gestational age (GA) in this study. The model was developed based on the sum of fetal cranial parameters (total fetal cranial parameters), including head circumference (HC) and depths of the insula (INS) and sylvian fissure (SF), parieto-occipital fissure (POF), and calcarine fissure (CF). A regression model, constructed based on total fetal cranial parameters and predicted GA, was established using the training set and validated using external validation set 1 and validation set 2.

Results

The intra- and interobserver intraclass correlation coefficients for HC, and depths of the INS and SF, POF, and CF were >0.90. An exponential regression equation was used to predict FCM: predicted GA of FCM (weeks) =11.16 × exp (0.003 × total fetal cranial parameters) (P<0.001; adjusted R2=0.973), standard error of estimate, 0.67 weeks. The standard error of the predicted GA of FCM from the model was ±4.7 days. In the validation set 1, the mean standard error of the developed prediction model for FCM was 0.97 weeks. The predictive model showed that FCM was significantly delayed in validation set 2 (2.10±1.31 weeks, P<0.001), considering the GA per the last menstrual period.

Conclusions

The predictive performance of the FCM model developed in this study was excellent, and the novel model may be a valuable investigative tool during clinical implementation.

Neurodevelopmental patterns of early postnatal white matter maturation represent distinct underlying microstructure and histology

Cerebral white matter undergoes a rapid and complex maturation during the early postnatal period. Prior magnetic resonance imaging (MRI) studies of early postnatal development have often been limited by small sample size, single-modality imaging, and univariate analytics. Here, we applied nonnegative matrix factorization, an unsupervised multivariate pattern analysis technique, to T2w/T1w signal ratio maps from the Developing Human Connectome Project (n = 342 newborns) revealing patterns of coordinated white matter maturation. These patterns showed divergent age-related maturational trajectories, which were replicated in another independent cohort (n = 239). Furthermore, we showed that T2w/T1w signal variations in these maturational patterns are explained by differential contributions of white matter microstructural indices derived from diffusion-weighted MRI. Finally, we demonstrated how white matter maturation patterns relate to distinct histological features by comparing our findings with postmortem late fetal/early postnatal brain tissue staining. Together, these results delineate concise and effective representation of early postnatal white matter reorganization.

Early arterial pressure monitoring and term-equivalent age MRI findings in very preterm infants

INTRODUCTION

Variability of arterial blood pressure (ABP) has been associated with intraventricular hemorrhage in very preterm neonates (VPT) and may predict other brain lesions assessed at term-equivalent of age (TEA).

METHODS

This was a prospective single-center study including VPT with early invasive continuous ABP monitoring and assessed at TEA using brain magnetic resonance imaging (TEA-MRI). The association between early mean ABP (MABP) and TEA-MRI findings was modeled by multivariate logistic regression analysis using covariates selected by the LASSO method.

RESULTS

Among 99 VPT, the LASSO procedure selected consecutive periods of lowest MABP of 30 min on day 1 (d1) and 10 min on day 2 (d2) as the most relevant durations to predict TEA-MRI findings (OR [95% CI], 1.11 [1.02-1.23], p = 0.03 and 1.13 [1.01-1.27], p = 0.03, respectively). ROC curve analysis showed optimal thresholds at 30.25 mmHg on d1 and 33.25 mmHg on d2. This significant association persisted after adjustment with covariates including birthweight, gestational age, sex, and inotrope exposure. Final models selected by LASSO included the decile of the birthweight and lowest MABP for 30 min on d1 and 10 min on d2, for which the areas under the ROC curve were 74% and 75%, respectively.

CONCLUSION

Early continuous ABP monitoring may predict brain TEA-MRI findings in VPT.

IMPACT

Early arterial blood pressure monitoring may contribute to predicting brain damage upon MRI at term-equivalent of age for infants born very preterm. Careful blood pressure continuous monitoring in very preterm infants may identify infants at risk of long-term brain damage. Umbilical artery catheterization provides the best option for continuously monitoring arterial blood pressure in very preterm infants.

Effects of neurodevelopmental risk factors on brainstem maturation in premature infants

BACKGROUND

Interpeak latencies (IPL), as measured by the auditory brainstem-evoked responses (ABR) test, represent the conduction time, and therefore the maturation of the brainstem auditory pathway. We aimed to study the effect of various risk factors for the neurodevelopmental delay on the conduction time in the auditory pathway among normal hearing premature infants, at term postmenstrual age (PMA).

METHODS

Retrospective analysis of 239 premature infants (gestational age 32.5 ± 2.1 weeks, birth weight 1827 ± 483 g). Interpeak latencies, demographic data, and risk factors were recorded.

RESULTS

Sex, PMA at ABR test, being small for gestational age (SGA), intraventricular hemorrhage (IVH) or periventricular leukomalacia (PVL), and days of invasive ventilation were found to significantly affect the IPL's in the auditory pathway in a univariate analysis. Multivariable regression analysis revealed that male sex and less advanced PMA at the examination were independent factors associated with prolonged IPL's, while bronchopulmonary dysplasia, IVH or PVL and being SGA shortened the IPL's. Non-invasive mechanical ventilation, did not affect the caudal part of the auditory pathway, despite its high noise level.

CONCLUSIONS

Among various risk factors for the neurodevelopmental delay, male sex was associated with delayed, while IVH or PVL, BPD and SGA could be associated with accelerated auditory brainstem maturation.

IMPACT

Auditory brainstem-evoked response (ABR) test, among normal hearing infants, can serve as a clinical tool to assess brainstem auditory maturation. Different neurodevelopmental risk factors could have different effects on the maturity of the auditory pathway. Male sex is significantly associated with prolonged interpeak latencies (IPL) among preterm and term infants, while intraventricular hemorrhage or periventricular leukomalacia, bronchopulmonary dysplasia, and being small for gestation age may be associated with shortened IPL The corrected age at ABR testing is of significance, among preterm and term infants.

Association of Cerebral Blood Flow and Brain Tissue Relaxation Time With Neurodevelopmental Outcomes of Preterm Neonates: Multidelay Arterial Spin Labeling and Synthetic MRI Study

OBJECTIVES

Both cerebral blood flow (CBF) and brain tissue relaxation times are known to reflect maturation in the neonatal brain. However, we do not yet know if these factors are associated with neurodevelopmental outcomes. The objective of this study was to acquire CBF and relaxation time in preterm neonates, using multidelay arterial spin labeling and synthetic magnetic resonance imaging (MRI), and show their association with later neurodevelopmental outcomes.

MATERIALS AND METHODS

In this prospective study, preterm neonates were recruited, and multidelay arterial spin labeling and synthetic MRI were performed between September 2017 and December 2018. These neonates underwent the Bayley Scales of Infant Development test at 18 months of age, and both cognitive and motor outcome scores were measured. Transit time-corrected CBF and T1 and T2 relaxation time values were measured for different brain regions. The measured values were correlated with gestational age (GA) at birth and corrected GA at the MRI scan. Simple and multiple linear regression analyses were performed for the measured values and neurodevelopmental outcome scores.

RESULTS

Forty-nine neonates (median [interquartile range] GA, 30 [2] weeks, 209 [17] days; 28 boys) underwent MRI scans at or near term-equivalent age (median [interquartile range] corrected GA, 37 [2] weeks, 258 [14] days). Transit time-corrected CBF (coefficient, 0.31-0.59) and relaxation time (coefficient, -0.39 to -0.86) values showed significant correlation with corrected GA but not with GA. After controlling for GA, the frontal white matter CBF in preterm neonates showed a negative relationship with cognitive outcome scores (β = -0.97; P = 0.029). Frontal white matter T1 relaxation times showed a positive relationship with cognitive outcome scores (β = 0.03; P = 0.025) after controlling for GA.

CONCLUSIONS

Higher CBF values and lower T1 relaxation times in frontal white matter were associated with poorer cognitive outcomes. As quantitative neuroimaging markers, CBF and relaxation times may help predict neurodevelopmental outcomes in preterm neonates.

Development and validation of Auto-Neo-electroencephalography (EEG) to estimate brain age and predict report conclusion for electroencephalography monitoring data in neonatal intensive care units

Background

Electroencephalography (EEG) monitoring is widely used in neonatal intensive care units (NICUs). However, conventional EEG report generation processes are time-consuming and labor-intensive. Therefore, an automatic, objective, and comprehensive pipeline for brain age estimation and EEG report conclusion prediction is urgently needed to assist clinician’s decision-making.

Methods

We recruited patients who underwent EEG monitoring from the NICU at Children’s Hospital of Fudan University from Jan. 2016 to Mar. 2018. A total of 1,851 subjects were enrolled, including the patient’s conceptional age (CA) and the clinical EEG report conclusion (normal, slightly abnormal, moderately abnormal, or severely abnormal). A total of 1,591 subjects were used to generate predictive models and 260 were used as the validation dataset. We developed Auto-Neo-EEG (an automatic prediction system to assist clinical neonatal EEG report generation), including signal feature extraction, supervised machine learning realized by gradient boosted models, to estimate brain age and predict EEG report conclusion.

Results

The predicted results from the validation dataset were compared with the clinical observations to assess the performance. In the independent validation dataset, the model could achieve accordance 0.904 on estimating brain age for neonates with normal clinical EEG report conclusion, and differences between the predicted and observed brain age were strongly related with EEG report conclusion abnormality. Further, as for the EEG report conclusion prediction, the model could achieve area under the curve (AUC) of 0.984 for severely abnormal situations, and 0.857 for moderately abnormal ones.

Conclusions

The Auto-Neo-EEG has the high accuracy of estimating brain age and EEG report conclusion, which can potentially greatly accelerate the EEG report generation processes assist in clinical decision making.

Super-resolution reconstruction of T2-weighted thick-slice neonatal brain MRI scans

Background and Purpose

Super‐resolutionreconstruction (SRR) can be used to reconstruct 3‐dimensional (3D) high‐resolution (HR) volume from several 2‐dimensional (2D) low‐resolution (LR) stacks of MRI slices. The purpose is to compare lengthy 2D T2‐weighted HR image acquisition of neonatal subjects with 3D SRR from several LR stacks in terms of image quality for clinical and morphometric assessments.

Methods

LR brain images were acquired from neonatal subjects to reconstruct isotropic 3D HR volumes by using SRR algorithm. Quality assessments were done by an experienced pediatric radiologist using scoring criteria adapted to newborn anatomical landmarks. The Wilcoxon signed‐rank test was used to compare scoring results between HR and SRR images. For quantitative assessments, morphology‐based segmentation was performed on both HR and SRR images and Dice coefficients between the results were computed. Additionally, simple linear regression was performed to compare the tissue volumes.

Results

No statistical difference was found between HR and SRR structural scores using Wilcoxon signed‐rank test (p = .63, Z = .48). Regarding segmentation results, R² values for the volumes of gray matter, white matter, cerebrospinal fluid, basal ganglia, cerebellum, and total brain volume including brain stem ranged between .95 and .99. Dice coefficients between the segmented regions from HR and SRR ranged between .83 ± .04 and .96 ± .01.

Conclusion

Qualitative and quantitative assessments showed that 3D SRR of several LR images produces images that are of comparable quality to standard 2D HR image acquisition for healthy neonatal imaging without loss of anatomical details with similar edge definition allowing the detection of fine anatomical structures and permitting comparable morphometric measurement.

Multi-Channel 4D Parametrized Atlas of Macro- and Microstructural Neonatal Brain Development

Structural (also known as anatomical) and diffusion MRI provide complimentary anatomical and microstructural characterization of early brain maturation. However, the existing models of the developing brain in time include only either structural or diffusion MRI channels. Furthermore, there is a lack of tools for combined analysis of structural and diffusion MRI in the same reference space. In this work, we propose a methodology to generate a multi-channel (MC) continuous spatio-temporal parametrized atlas of the brain development that combines multiple MRI-derived parameters in the same anatomical space during 37-44 weeks of postmenstrual age range. We co-align structural and diffusion MRI of 170 normal term subjects from the developing Human Connectomme Project using MC registration driven by both T2-weighted and orientation distribution functions channels and fit the Gompertz model to the signals and spatial transformations in time. The resulting atlas consists of 14 spatio-temporal microstructural indices and two parcellation maps delineating white matter tracts and neonatal transient structures. In order to demonstrate applicability of the atlas for quantitative region-specific studies, a comparison analysis of 140 term and 40 preterm subjects scanned at the term-equivalent age is performed using different MRI-derived microstructural indices in the atlas reference space for multiple white matter regions, including the transient compartments. The atlas and software will be available after publication of the article.

Transient structural MRI patterns correlate with the motor functions in preterm infants

AIM

To explore the relationships between transient structural brain patterns on MRI at preterm and at term-equivalent age (TEA) as a predictor of general movements (GMs) and motor development at 1-year corrected age (CA) in very preterm infants.

METHODS

In this prospective study, 30 very preterm infants (median = 28wks; 16 males) had structural magnetic resonance imaging (MRI) at preterm (median = 31wks + 6d) and at TEA (median = 40wks) and neuromotor assessments. The quality of GMs was assessed by Prechtl's general movements assessment and a detailed analysis of the motor repertoire was performed by calculating a motor optimality score (MOS), both at term age and at 3 months post-term. Motor development at 1-year CA was evaluated with the Infant Motor Profile (IMP). Associations between qualitative MRI findings and neuromotor scores were investigated.

RESULTS

Abnormal GMs and low motor performance at 1-year CA were associated with the poor visibility of transient structural pattern, that is with sagittal strata.

INTERPRETATION

Transient structural MRI pattern, sagittal strata, at preterm age is related to the quality of GMs and later motor development in preterm infants. This transient fetal brain compartment may be considered as a component of neurobiological basis for early neuromotor behavior, as expressed by GMs.

Automated brain MRI metrics in the EPIRMEX cohort of preterm newborns: Correlation with the neurodevelopmental outcome at 2 years

PURPOSE

The purpose of this study was to identify in the EPIRMEX cohort the correlations between MRI brain metrics, including diffuse excessive high signal intensities (DEHSI) obtained with an automated quantitative method and neurodevelopmental outcomes at 2 years.

MATERIALS AND METHODS

A total of 390 very preterm infants (gestational age at birth≤32 weeks) who underwent brain MRI at term equivalent age at 1.5T (n=338) or 3T (n=52) were prospectively included. Using a validated algorithm, automated metrics of the main brain surfaces (cortical and deep gray matter, white matter, cerebrospinal fluid) and DEHSI with three thresholds were obtained. Linear adjust regressions were performed to assess the correlation between brain metrics with the ages and stages questionnaire (ASQ) score at 2 years.

RESULTS

Basal ganglia and thalami, cortex and white matter surfaces positively and significantly correlated with the global ASQ score. For all ASQ sub-domains, basal ganglia and thalami surfaces significantly correlated with the scores. DEHSI was present in 289 premature newborns (74%) without any correlation with the ASQ score. Metrics of DEHSI were greater at 3T than at 1.5T.

CONCLUSION

Brain MRI metrics obtained in our multicentric cohort correlate with the neurodevelopmental outcome at 2 years of age. The quantitative detection of DEHSI is not predictive of adverse outcomes. Our automated algorithm might easily provide useful predictive information in daily practice.