Placental Pathology Contributes to Impaired Volumetric Brain Development in Neonates With Congenital Heart Disease.

BACKGROUND: Neonates with congenital heart disease are at risk for impaired brain development in utero, predisposing children to postnatal brain injury and adverse long-term neurodevelopmental outcomes. Given the vital role of the placenta in fetal growth, we assessed the incidence of placental pathology in fetal congenital heart disease and explored its association with total and regional brain volumes, gyrification, and brain injury after birth. METHODS AND RESULTS: Placentas from 96 term singleton pregnancies with severe fetal congenital heart disease were prospectively analyzed for macroscopic and microscopic pathology. We applied a placental pathology severity score to relate placental abnormalities to neurological outcome. Postnatal, presurgical magnetic resonance imaging was used to analyze brain volumes, gyrification, and brain injuries. Placental analyses revealed the following abnormalities: maternal vascular malperfusion lesions in 46%, nucleated red blood cells in 37%, chronic inflammatory lesions in 35%, delayed maturation in 30%, and placental weight below the 10th percentile in 28%. Severity of placental pathology was negatively correlated with cortical gray matter, deep gray matter, brainstem, cerebellar, and total brain volumes (r=-0.25 to -0.31, all P<0.05). When correcting for postmenstrual age at magnetic resonance imaging in linear regression, this association remained significant for cortical gray matter, cerebellar, and total brain volume (adjusted R2=0.25-0.47, all P<0.05). CONCLUSIONS: Placental pathology occurs frequently in neonates with severe congenital heart disease and may contribute to impaired brain development, indicated by the association between placental pathology severity and reductions in postnatal cortical, cerebellar, and total brain volumes.

Detailed statistical analysis plan for ALBINO: effect of Allopurinol in addition to hypothermia for hypoxic-ischemic Brain Injury on Neurocognitive Outcome - a blinded randomized placebo-controlled parallel group multicenter trial for superiority (phase III).

BACKGROUND: Despite therapeutic hypothermia (TH) and neonatal intensive care, 45-50% of children affected by moderate-to-severe neonatal hypoxic-ischemic encephalopathy (HIE) die or suffer from long-term neurodevelopmental impairment. Additional neuroprotective therapies are sought, besides TH, to further improve the outcome of affected infants. Allopurinol - a xanthine oxidase inhibitor - reduced the production of oxygen radicals and subsequent brain damage in pre-clinical and preliminary human studies of cerebral ischemia and reperfusion, if administered before or early after the insult. This ALBINO trial aims to evaluate the efficacy and safety of allopurinol administered immediately after birth to (near-)term infants with early signs of HIE. METHODS/DESIGN: The ALBINO trial is an investigator-initiated, randomized, placebo-controlled, double-blinded, multi-national parallel group comparison for superiority investigating the effect of allopurinol in (near-)term infants with neonatal HIE. Primary endpoint is long-term outcome determined as survival with neurodevelopmental impairment versus death versus non-impaired survival at 2 years. RESULTS: The primary analysis with three mutually exclusive responses (healthy, death, composite outcome for impairment) will be on the intention-to-treat (ITT) population by a generalized logits model according to Bishop, Fienberg, Holland (Bishop YF, Discrete Multivariate Analysis: Therory and Practice, 1975) and ."will be stratified for the two treatment groups. DISCUSSION: The statistical analysis for the ALBINO study was defined in detail in the study protocol and implemented in this statistical analysis plan published prior to any data analysis. This is in accordance with the Declaration of Helsinki and the International Conference on Harmonization Good Clinical Practice guidelines. TRIAL REGISTRATION: ClinicalTrials.gov NCT03162653. Registered on 22 May 2017.

Detecting Asymmetry of Upper Limb Activity with Accelerometry in Infants at Risk for Unilateral Spastic Cerebral Palsy.

AIMS: To examine whether accelerometry can quantitate asymmetry of upper limb activity in infants aged 3-12 months at risk for developing unilateral spastic cerebral palsy (USCP). METHOD: A prospective study was performed in 50 infants with unilateral perinatal brain injury at high risk of developing USCP. Triaxial accelerometers were worn on the ipsilateral and contralesional upper limb during the Hand Assessment for Infants (HAI). Infants were grouped in three age intervals (3-5 months, 5-7.5 months and 7.5 until 12 months). Each age interval group was divided in a group with and without asymmetrical hand function based on HAI cutoff values suggestive of USCP. RESULTS: In a total of 82 assessments, the asymmetry index for mean upper limb activity was higher in infants with asymmetrical hand function compared to infants with symmetrical hand function in all three age groups (ranging from 41 to 51% versus - 2-6%, p < 0.01), while the total activity of both upper limbs did not differ. CONCLUSIONS: Upper limb accelerometry can identify asymmetrical hand function in the upper limbs in infants with unilateral perinatal brain injury from 3 months onwards and is complementary to the Hand Assessment for Infants.

Perioperative Brain Injury in Relation to Early Neurodevelopment Among Children with Severe Congenital Heart Disease: Results from a European Collaboration.

OBJECTIVE: To examine the relationship between perioperative brain injury and neurodevelopment during early childhood in patients with severe congenital heart disease (CHD). STUDY DESIGN: One hundred and seventy children with CHD and born at term who required cardiopulmonary bypass surgery in the first 6 weeks after birth were recruited from 3 European centers and underwent preoperative and postoperative brain MRIs. Uniform description of imaging findings was performed and an overall brain injury score was created, based on the sum of the worst preoperative or postoperative brain injury subscores. Motor and cognitive outcomes were assessed with the Bayley Scales of Infant and Toddler Development Third Edition at 12 to 30 months of age. The relationship between brain injury score and clinical outcome was assessed using multiple linear regression analysis, adjusting for CHD severity, length of hospital stay (LOS), socioeconomic status (SES), and age at follow-up. RESULTS: Neither the overall brain injury score nor any of the brain injury subscores correlated with motor or cognitive outcome. The number of preoperative white matter lesions was significantly associated with gross motor outcome after correction for multiple testing (P = .013, ß = -0.50). SES was independently associated with cognitive outcome (P < .001, ß = 0.26), and LOS with motor outcome (P < .001, ß = -0.35). CONCLUSION: Preoperative white matter lesions appear to be the most predictive MRI marker for adverse early childhood gross motor outcome in this large European cohort of infants with severe CHD. LOS as a marker of disease severity, and SES influence outcome and future intervention trials need to address these risk factors.

Effect of Systemic Hydrocortisone on Brain Abnormalities and Regional Brain Volumes in Ventilator-dependent Infants Born Preterm: Substudy of the SToP-BPD Study.

OBJECTIVE: To evaluate whether a high cumulative dose of systemic hydrocortisone affects brain development compared with placebo when initiated between 7 and 14 days after birth in ventilated infants born preterm. STUDY DESIGN: A double-blind, placebo-controlled, randomized trial was conducted in 16 neonatal intensive care units among infants born at <30 weeks of gestation or with a birth weight of <1250 g who were ventilator-dependent in the second week after birth. Three centers performed MRI at term-equivalent age. Brain injury was assessed on MRI using the Kidokoro scoring system and compared between the 2 treatment groups. Both total and regional brain volumes were calculated using an automatic segmentation method and compared using multivariable regression analysis adjusted for baseline variables. RESULTS: From the 3 centers, 78 infants participated in the study and 59 had acceptable MRI scans (hydrocortisone group, n = 31; placebo group, n = 28). Analyses of the median global brain abnormality score of the Kidokoro score showed no difference between the hydrocortisone and placebo groups (median, 7; IQR, 5-9 vs median, 8, IQR, 4-10, respectively; P = .92). In 39 infants, brain tissue volumes were measured, showing no differences in the adjusted mean total brain tissue volumes, at 352 ± 32 mL in the hydrocortisone group and 364 ± 51 mL in the placebo group (P = .80). CONCLUSIONS: Systemic hydrocortisone started in the second week after birth in ventilator-dependent infants born very preterm was not found to be associated with significant differences in brain development compared with placebo treatment. TRIAL REGISTRATION: The SToP-BPD study was registered with the Netherlands Trial Register (NTR2768; registered on 17 February 2011; https://www.trialregister.nl/trial/2640) and the European Union Clinical Trials Register (EudraCT, 2010-023777-19; registered on 2 November 2010; https://www.clinicaltrialsregister.eu/ctr-search/trial/2010-023777-19/NL).

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 [ß = 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.

Cranial MRI beyond the Neonatal Period and Neurodevelopmental Outcomes in Neonatal Encephalopathy Due to Perinatal Asphyxia: A Systematic Review.

BACKGROUND: Magnetic resonance imaging (MRI) including diffusion-weighted imaging within seven days after birth is widely used to obtain prognostic information in neonatal encephalopathy (NE) following perinatal asphyxia. Later MRI could be useful for infants without a neonatal MRI or in the case of clinical concerns during follow-up. Therefore, this review evaluates the association between cranial MRI beyond the neonatal period and neurodevelopmental outcomes following NE. METHODS: A systematic literature search was performed using PubMed and Embase on cranial MRI between 2 and 24 months after birth and neurodevelopmental outcomes following NE due to perinatal asphyxia. Two independent researchers performed the study selection and risk of bias analysis. Results were separately described for MRI before and after 18 months. RESULTS: Twelve studies were included (high-quality n = 2, moderate-quality n = 6, low-quality n = 4). All reported on MRI at 2-18 months: seven studies demonstrated a significant association between the pattern and/or severity of injury and overall neurodevelopmental outcomes and three showed a significant association with motor outcome. There were insufficient data on non-motor outcomes and the association between MRI at 18-24 months and neurodevelopmental outcomes. CONCLUSIONS: Cranial MRI performed between 2 and 18 months after birth is associated with neurodevelopmental outcomes in NE following perinatal asphyxia. However, more data on the association with non-motor outcomes are needed.

Early qualitative and quantitative amplitude-integrated electroencephalogram and raw electroencephalogram for predicting long-term neurodevelopmental outcomes in extremely preterm infants in the Netherlands: a 10-year cohort study.

BACKGROUND: Extremely preterm infants (<28 weeks of gestation) are at great risk of long-term neurodevelopmental impairments. Early amplitude-integrated electroencephalogram (aEEG) accompanied by raw EEG traces (aEEG-EEG) has potential for predicting subsequent outcomes in preterm infants. We aimed to determine whether and which qualitative and quantitative aEEG-EEG features obtained within the first postnatal days predict neurodevelopmental outcomes in extremely preterm infants. METHODS: This study retrospectively analysed a cohort of extremely preterm infants (born before 28 weeks and 0 days of gestation) who underwent continuous two-channel aEEG-EEG monitoring during their first 3 postnatal days at Wilhelmina Children's Hospital, Utrecht, the Netherlands, between June 1, 2008, and Sept 30, 2018. Only infants who did not have genetic or metabolic diseases or major congenital malformations were eligible for inclusion. Features were extracted from preprocessed aEEG-EEG signals, comprising qualitative parameters grouped in three types (background pattern, sleep-wake cycling, and seizure activity) and quantitative metrics grouped in four categories (spectral content, amplitude, connectivity, and discontinuity). Machine learning-based regression and classification models were used to evaluate the predictive value of the extracted aEEG-EEG features for 13 outcomes, including cognitive, motor, and behavioural problem outcomes, at 2-3 years and 5-7 years. Potential confounders (gestational age at birth, maternal education, illness severity, morphine cumulative dose, the presence of severe brain injury, and the administration of antiseizure, sedative, or anaesthetic medications) were controlled for in all prediction analyses. FINDINGS: 369 infants were included and an extensive set of 339 aEEG-EEG features was extracted, comprising nine qualitative parameters and 330 quantitative metrics. The machine learning-based regression models showed significant but relatively weak predictive performance (ranging from r=0·13 to r=0·23) for nine of 13 outcomes. However, the machine learning-based classifiers exhibited acceptable performance in identifying infants with intellectual impairments from those with optimal outcomes at age 5-7 years, achieving balanced accuracies of 0·77 (95% CI 0·62-0·90; p=0·0020) for full-scale intelligence quotient score and 0·81 (0·65-0·96; p=0·0010) for verbal intelligence quotient score. Both classifiers maintained identical performance when solely using quantitative features, achieving balanced accuracies of 0·77 (95% CI 0·63-0·91; p=0·0030) for full-scale intelligence quotient score and 0·81 (0·65-0·96; p=0·0010) for verbal intelligence quotient score. INTERPRETATION: These findings highlight the potential benefits of using early postnatal aEEG-EEG features to automatically recognise extremely preterm infants with poor outcomes, facilitating the development of an interpretable prognostic tool that aids in decision making and therapy planning. FUNDING: European Commission Horizon 2020.

Development and clinical impact assessment of a machine-learning model for early prediction of late-onset sepsis.

BACKGROUND AND AIM: Preterm infants are prone to neonatal infections such as late-onset sepsis (LOS). The consequences of LOS can be severe and potentially life-threatening. Unfortunately, LOS often presents with unspecific symptoms, and early screening laboratory tests have limited diagnostic value and are often late. This study aimed to build a predictive algorithm to aid doctors in the early detection of LOS in very preterm infants. METHODS: In a retrospective cohort study, all consecutively admitted preterm infants (GA ≤ 32 weeks) from 2008 until 2019 were included. They were classified as LOS or control according to blood culture results, currently the gold standard. To generate features, routine and continuously measured oxygen saturation and heart rate data with a minute-by-minute sampling rate were extracted from electronic medical records. Care was taken not to include variables indicative of existing LOS suspicion. The timing of a positive blood culture served as a proxy for LOS-onset. An equivalent timestamp was generated in gestational-age-matched control patients without a positive blood culture. Three machine learning (ML) techniques (generalized additive models, logistic regression, and XGBoost) were used to build a classification algorithm. To simulate the performance of the algorithm in clinical practice, a simulation using multiple alarm thresholds was performed on hourly predictions for the total hospitalization period. RESULTS: 292 infants with LOS were matched to 1497 controls. The median gestational age before matching was 28.1 and 30.3 weeks, respectively. Evaluation of the overall discriminative power of the LR algorithm yielded an AUC of 0.73 (p < 0.05) at the moment of clinical suspicion (t = 0). In the longitudinal simulation, our algorithm detects LOS in at least 47% of the patients before clinical suspicion without exceeding the alarm fatigue threshold of 3 alarms per day. Furthermore, medical experts evaluated the algorithm as clinically relevant regarding the feature contributions in the model explanations. CONCLUSIONS: An ML algorithm was trained for the early detection of LOS. Performance was evaluated on both prediction horizons and in a clinical impact simulation. To the best of our knowledge, our assessment of clinical impact with a retrospective simulation on longitudinal data is the most extensive in the literature on LOS prediction to date. The clinically relevant algorithm, based on routinely collected data, can potentially accelerate clinical decisions in the early detection of LOS, even with limited inputs.

The influence of nutrition on white matter development in preterm infants: a scoping review.

White matter (WM) injury is the most common type of brain injury in preterm infants and is associated with impaired neurodevelopmental outcome (NDO). Currently, there are no treatments for WM injury, but optimal nutrition during early preterm life may support WM development. The main aim of this scoping review was to assess the influence of early postnatal nutrition on WM development in preterm infants. Searches were performed in PubMed, EMBASE, and COCHRANE on September 2022. Inclusion criteria were assessment of preterm infants, nutritional intake before 1 month corrected age, and WM outcome. Methods were congruent with the PRISMA-ScR checklist. Thirty-two articles were included. Negative associations were found between longer parenteral feeding duration and WM development, although likely confounded by illness. Positive associations between macronutrient, energy, and human milk intake and WM development were common, especially when fed enterally. Results on fatty acid and glutamine supplementation remained inconclusive. Significant associations were most often detected at the microstructural level using diffusion magnetic resonance imaging. Optimizing postnatal nutrition can positively influence WM development and subsequent NDO in preterm infants, but more controlled intervention studies using quantitative neuroimaging are needed. IMPACT: White matter brain injury is common in preterm infants and associated with impaired neurodevelopmental outcome. Optimizing postnatal nutrition can positively influence white matter development and subsequent neurodevelopmental outcome in preterm infants. More studies are needed, using quantitative neuroimaging techniques and interventional designs controlling for confounders, to define optimal nutritional intakes in preterm infants.

Brain injury and long-term outcome after neonatal surgery for non-cardiac congenital anomalies.

BACKGROUND: There is growing evidence that neonatal surgery for non-cardiac congenital anomalies (NCCAs) in the neonatal period adversely affects long-term neurodevelopmental outcome. However, less is known about acquired brain injury after surgery for NCCA and abnormal brain maturation leading to these impairments. METHODS: A systematic search was performed in PubMed, Embase, and The Cochrane Library on May 6, 2022 on brain injury and maturation abnormalities seen on magnetic resonance imaging (MRI) and its associations with neurodevelopment in neonates undergoing NCCA surgery the first month postpartum. Rayyan was used for article screening and ROBINS-I for risk of bias assessment. Data on the studies, infants, surgery, MRI, and outcome were extracted. RESULTS: Three eligible studies were included, reporting 197 infants. Brain injury was found in n = 120 (50%) patients after NCCA surgery. Sixty (30%) were diagnosed with white matter injury. Cortical folding was delayed in the majority of cases. Brain injury and delayed brain maturation was associated with a decrease in neurodevelopmental outcome at 2 years of age. CONCLUSIONS: Surgery for NCCA was associated with high risk of brain injury and delay in maturation leading to delay in neurocognitive and motor development. However, more research is recommended for strong conclusions in this group of patients. IMPACT: Brain injury was found in 50% of neonates who underwent NCCA surgery. NCCA surgery is associated with a delay in cortical folding. There is an important research gap regarding perioperative brain injury and NCCA surgery.

Additional Value of 3-Month Cranial Magnetic Resonance Imaging in Infants with Neonatal Encephalopathy following Perinatal Asphyxia.

OBJECTIVE: To assess the evolution of neonatal brain injury noted on magnetic resonance imaging (MRI), develop a score to assess brain injury on 3-month MRI, and determine the association of 3-month MRI with neurodevelopmental outcome in neonatal encephalopathy (NE) following perinatal asphyxia. METHODS: This was a retrospective, single-center study including 63 infants with perinatal asphyxia and NE (n = 28 cooled) with cranial MRI <2 weeks and 2-4 months after birth. Both scans were assessed using biometrics, a validated injury score for neonatal MRI, and a new score for 3-month MRI, with a white matter (WM), deep gray matter (DGM), and cerebellum subscore. The evolution of brain lesions was assessed, and both scans were related to 18- to 24-month composite outcome. Adverse outcome included cerebral palsy, neurodevelopmental delay, hearing/visual impairment, and epilepsy. RESULTS: Neonatal DGM injury generally evolved into DGM atrophy and focal signal abnormalities, and WM/watershed injury evolved into WM and/or cortical atrophy. Although the neonatal total and DGM scores were associated with composite adverse outcomes, the 3-month DGM score (OR 1.5, 95% CI 1.2-2.0) and WM score (OR 1.1, 95% CI 1.0-1.3) also were associated with composite adverse outcomes (occurring in n = 23). The 3-month multivariable model (including the DGM and WM subscores) had higher positive (0.88 vs 0.83) but lower negative predictive value (0.83 vs 0.84) than neonatal MRI. Inter-rater agreement for the total, WM, and DGM 3-month score was 0.93, 0.86, and 0.59. CONCLUSIONS: In particular, DGM abnormalities on 3-month MRI, preceded by DGM abnormalities on the neonatal MRI, were associated with 18- to 24-month outcome, indicating the utility of 3-month MRI for treatment evaluation in neuroprotective trials. However, the clinical usefulness of 3-month MRI seems limited compared with neonatal MRI.

Effects of a Multicomponent Lipid Emulsion on Brain Volumes in Extremely Low Birth Weight Infants.

OBJECTIVE: During the early weeks of life optimization of nutrition in extremely preterm infants presents a critical opportunity to attenuate the adverse neurological consequences of prematurity and potentially improve neurodevelopmental outcome. We hypothesized that the use of multicomponent lipid emulsion (MLE) in parenteral nutrition (PN) would be related to larger volume of the cerebellum on brain magnetic resonance at term of equivalent age (TEA) in extremely low birth weight (ELBW) infants. STUDY DESIGN: We analyzed the brain magnetic resonance imaging (MRI) at TEA of a cohort of preterm infants with gestational age ≤28 weeks and/or birth weight <1,000 g randomly assigned in our previous trial to receive an MLE or soybean-based lipid emulsion (SLE). The primary outcome of the study was the cerebellar volume (CeV), valued on MRI acquired at TEA. Secondary outcomes included total brain volume (TBV), supratentorial volume, brainstem volume, and CeV corrected for TBV evaluated on MRI acquired at TEA. RESULTS: MRIs at TEA of 34 infants were then analyzed: 17 in the MLE group and 17 in the SLE group. The postmenstrual age (PMA) at which MRIs were performed were comparable between the two study groups. The CeV as well as the PMA-corrected CeV were significantly higher in the MLE group than in the SLE group. No difference was found among the other brain volumes considered. CONCLUSION: Our results suggest that the use of MLE in PN could promote CeV growth in ELBW infants, valued with MRI at TEA. KEY POINTS: · Optimization of nutrition in extremely low birthweight infants.. · Use of multicomponent lipid emulsions in parenteral nutrition.. · Larger cerebellar volume with use of multicomponent lipid emulsion..

Brain segmentation in patients with perinatal arterial ischemic stroke.

BACKGROUND: Perinatal arterial ischemic stroke (PAIS) is associated with adverse neurological outcomes. Quantification of ischemic lesions and consequent brain development in newborn infants relies on labor-intensive manual assessment of brain tissues and ischemic lesions. Hence, we propose an automatic method utilizing convolutional neural networks (CNNs) to segment brain tissues and ischemic lesions in MRI scans of infants suffering from PAIS. MATERIALS AND METHODS: This single-center retrospective study included 115 patients with PAIS that underwent MRI after the stroke onset (baseline) and after three months (follow-up). Nine baseline and 12 follow-up MRI scans were manually annotated to provide reference segmentations (white matter, gray matter, basal ganglia and thalami, brainstem, ventricles, extra-ventricular cerebrospinal fluid, and cerebellum, and additionally on the baseline scans the ischemic lesions). Two CNNs were trained to perform automatic segmentation on the baseline and follow-up MRIs, respectively. Automatic segmentations were quantitatively evaluated using the Dice coefficient (DC) and the mean surface distance (MSD). Volumetric agreement between segmentations that were manually and automatically obtained was computed. Moreover, the scan quality and automatic segmentations were qualitatively evaluated in a larger set of MRIs without manual annotation by two experts. In addition, the scan quality was qualitatively evaluated in these scans to establish its impact on the automatic segmentation performance. RESULTS: Automatic brain tissue segmentation led to a DC and MSD between 0.78-0.92 and 0.18-1.08 mm for baseline, and between 0.88-0.95 and 0.10-0.58 mm for follow-up scans, respectively. For the ischemic lesions at baseline the DC and MSD were between 0.72-0.86 and 1.23-2.18 mm, respectively. Volumetric measurements indicated limited oversegmentation of the extra-ventricular cerebrospinal fluid in both the follow-up and baseline scans, oversegmentation of the ischemic lesions in the left hemisphere, and undersegmentation of the ischemic lesions in the right hemisphere. In scans without imaging artifacts, brain tissue segmentation was graded as excellent in more than 85% and 91% of cases, respectively for the baseline and follow-up scans. For the ischemic lesions at baseline, this was in 61% of cases. CONCLUSIONS: Automatic segmentation of brain tissue and ischemic lesions in MRI scans of patients with PAIS is feasible. The method may allow evaluation of the brain development and efficacy of treatment in large datasets.

Morphine exposure and neurodevelopmental outcome in infants born extremely preterm.

AIM: To investigate the association between morphine exposure in the neonatal period and neurodevelopment at 2 and 5 years of age while controlling for potential confounders. METHOD: We performed a retrospective, single-centre cohort study on 106 infants (60 males, 46 females; mean gestational age 26 weeks [SD 1]) born extremely preterm (gestational age < 28 weeks). Morphine administration was expressed as cumulative dose (mg/kg) until term-equivalent age. Neurodevelopmental outcome was assessed at 2 years with the Bayley Scales of Infant and Toddler Development, Third Edition, Dutch version and at 5 years with the Wechsler Preschool and Primary Scale of Intelligence, Third Edition, Dutch version. Multiple linear regression analysis was used to assess the association between morphine exposure and outcome. RESULTS: Sixty-four out of 106 (60.4%) infants included in the study received morphine. Morphine exposure was not associated with poorer motor, cognitive, and language subscores of the Bayley Scales of Infant and Toddler Development, Third Edition, Dutch version at 2 years. Morphine exposure was associated with lower Full-Scale IQ scores (p = 0.008, B = -9.3, 95% confidence interval [CI] = -15.6 to -3.1) and Performance IQ scores (p = 0.005, B = -17.5, 95% CI = -27.9 to -7) at 5 years of age. INTERPRETATION: Morphine exposure in infants born preterm is associated with poorer Full-Scale IQ and Performance IQ at 5 years. Individualized morphine administration is advised in infants born extremely preterm.

Exploring the emergence of morphological asymmetries around the brain's Sylvian fissure: a longitudinal study of shape variability in preterm infants.

Brain folding patterns vary within the human species, but some folding properties are common across individuals, including the Sylvian fissure's inter-hemispheric asymmetry. Contrarily to the other brain folds (sulci), the Sylvian fissure develops through the process of opercularization, with the frontal, parietal, and temporal lobes growing over the insular lobe. Its asymmetry may be related to the leftward functional lateralization for language processing, but the time course of these asymmetries' development is still poorly understood. In this study, we investigated refined shape features of the Sylvian fissure and their longitudinal development in 71 infants born extremely preterm (mean gestational age at birth: 26.5 weeks) and imaged once before and once at term-equivalent age (TEA). We additionally assessed asymmetrical sulcal patterns at TEA in the perisylvian and inferior frontal regions, neighbor to the Sylvian fissure. While reproducing renowned strong asymmetries in the Sylvian fissure, we captured an early encoding of its main asymmetrical shape features, and we observed global asymmetrical shape features representative of a more pronounced opercularization in the left hemisphere, contrasting with the previously reported right hemisphere advance in sulcation around birth. This added novel insights about the processes governing early-life brain folding mechanisms, potentially linked to the development of language-related capacities.

From computer to bedside, involving neonatologists in artificial intelligence models for neonatal medicine.

In recent years, data have become the main driver of medical innovation. With increased availability and decreased price of storage and computing power, the potential for improvement in care is enormous. Many data-driven explorations have started. However, the actual implementation of artificial intelligence in healthcare remains scarce. We describe essential elements during a computer-to-bedside process in a data science project that support the crucial role of the neonatologist. IMPACT: There is a great potential for data science in neonatal medicine. Multidisciplinary teams form the foundation of a data science project. Domain experts will need to play a pivotal role. We need an open learning environment.