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Postnatal growth restriction and deficits in fat-free mass are associated with impaired neurodevelopment. The optimal body composition to support normal brain growth and development remains unclear. This study investigated the association between body composition and brain size in preterm infants. We included 118 infants born <28 weeks of gestation between 2017-2021, who underwent body composition (fat-free mass (FFM) and fat mass (FM)) and cerebral magnetic resonance imaging to quantify brain size (cerebral biparietal diameter (cBPD), bone biparietal diameter (bBPD), interhemispheric distance (IHD), transverse cerebellar diameter (tCD)) at term-equivalent age. FFM Z-Score significantly correlated with higher cBPD Z-Score (rs = 0.69; p < 0.001), bBPD Z-Score (rs = 0.48; p < 0.001) and tCD Z-Score (rs = 0.30; p = 0.002); FM Z-Score significantly correlated with lower brain size (cBPD Z-Score (rs = -0.32; p < 0.001) and bBPD Z-Score (rs = -0.42; p < 0.001). In contrast weight (rs = 0.08), length (rs = -0.01) and head circumference Z-Score (rs = 0.14) did not. Linear regression model adjusted for important neonatal variables revealed that FFM Z-Score was independently and significantly associated with higher cBPD Z-Score (median 0.50, 95% CI: 0.59, 0.43; p < 0.001) and bBPD Z-Score (median 0.31, 95% CI: 0.42, 0.19; p < 0.001); FM Z-Score was independently and significantly associated with lower cBPD Z-Score (median -0.27, 95% CI: -0.42, -0.11; p < 0.001) and bBPD Z-Score (median -0.32, 95% CI: -0.45, -0.18; p < 0.001). Higher FFM Z-Score and lower FM Z-scores were significantly associated with larger brain size at term-equivalent age. These results indicate that early body composition might be a useful tool to evaluate and eventually optimize brain growth and neurodevelopment.

Purpose: The purpose of this study was to assess the diagnostic accuracy of T1-weighted and T2-weighted contrasts generated by the MR data postprocessing software SyMRI (Synthetic MR AB, Linköping, Sweden) for neonatal brain imaging., Methods: In this study 36 cases of neonatal MRI were retrospectively collected, which included T1-weighted and T2-weighted sequences as well as multi-dynamic multi-echo (MDME) sequences. Of the 36 neonates 32 were included in this study and 4 neuroradiologists independently assessed neonatal brain examinations on the basis of conventional and SyMRI-generated T1-weighted and T2-weighted contrasts, in order to determine the presence or absence of lesions. The sensitivity and specificity of both methods were calculated and compared., Results: Compared to conventionally acquired T1 and T2-weighted images, SyMRI-generated contrasts showed a lower sensitivity but a higher specificity (SyMRI sensitivity 0.88, confidence interval (CI): 0.72-0.95; specificity 1, CI: 0.89-1/conventional MRI: sensitivity: 0.94, CI: 0.80-0.98; specificity: 0.94, CI: 0.80-0.98)., Conclusion: The T1-weighted and T2-weighted images generated by SyMRI showed a diagnostic accuracy comparable to that of conventionally acquired contrasts. In addition to semiquantitative imaging data, SyMRI provides diagnostic images and leads to a more efficient use of available imaging time in neonatal brain MRI.

Objectives: To determine the accuracy of, and agreement among, EEG and aEEG readers' estimation of maturity and a novel computational measure of functional brain age (FBA) in preterm infants., Methods: Seven experts estimated the postmenstrual ages (PMA) in a cohort of recordings from preterm infants using cloud-based review software. The FBA was calculated using a machine learning-based algorithm. Error analysis was used to determine the accuracy of PMA assessments and intraclass correlation (ICC) was used to assess agreement between experts., Results: EEG recordings from a PMA range 25 to 38 weeks were successfully interpreted. In 179 recordings from 62 infants interpreted by all human readers, there was moderate agreement between experts (aEEG ICC = 0.724; 95%CI:0.658-0.781 and EEG ICC = 0.517; 95%CI:0.311-0.664). In 149 recordings from 61 infants interpreted by all human readers and the FBA algorithm, random and systematic errors in visual interpretation of PMA were significantly higher than the computational FBA estimate. Tracking of maturation in individual infants showed stable FBA trajectories, but the trajectories of the experts' PMA estimate were more likely to be obscured by random errors. The accuracy of visual interpretation of PMA estimation was compromised by neurodevelopmental outcome for both aEEG and EEG review., Interpretation: Visual assessment of infant maturity is possible from the EEG or aEEG, with an average of human experts providing the highest accuracy. Tracking PMA of individual infants was hampered by errors in experts' estimates. FBA provided the most accurate maturity assessment and has potential as a biomarker of early outcome., (© 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Objective: A major challenge in the care of preterm infants is the early identification of compromised neurological development. While several measures are routinely used to track anatomical growth, there is a striking lack of reliable and objective tools for tracking maturation of early brain function; a cornerstone of lifelong neurological health. We present a cot-side method for measuring the functional maturity of the newborn brain based on routinely available neurological monitoring with electroencephalography (EEG)., Methods: We used a dataset of 177 EEG recordings from 65 preterm infants to train a multivariable prediction of functional brain age (FBA) from EEG. The FBA was validated on an independent set of 99 EEG recordings from 42 preterm infants. The difference between FBA and postmenstrual age (PMA) was evaluated as a predictor for neurodevelopmental outcome., Results: The FBA correlated strongly with the PMA of an infant, with a median prediction error of less than 1 week. Moreover, individual babies follow well-defined individual trajectories. The accuracy of the FBA applied to the validation set was statistically equivalent to the training set accuracy. In a subgroup of infants with repeated EEG recordings, a persistently negative predicted age difference was associated with poor neurodevelopmental outcome., Interpretation: The FBA enables the tracking of functional neurodevelopment in preterm infants. This establishes proof of principle for growth charts for brain function, a new tool to assist clinical management and identify infants who will benefit most from early intervention., (© 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Objectives: The software "SyMRI" generates different MR contrasts and characterizes tissue properties based on a single acquisition of a multi-dynamic multi-echo (MDME)-FLAIR sequence. The aim of this study was to assess the applicability of "SyMRI" in the assessment of myelination in preterm and term-born neonates. Furthermore, "SyMRI" was compared with conventional MRI., Methods: A total of 30 preterm and term-born neonates were examined at term-equivalent age using a standardized MRI protocol. MDME sequence (acquisition time, 5 min, 24 s)-based post-processing was performed using "SyMRI". Myelination was assessed by scoring seven brain regions on quantitative T1-/T2-maps, generated by "SyMRI" and on standard T1-/T2-weighted images, acquired separately. Analysis of covariance (ANCOVA) (covariate, gestational age (GA) at MRI (GAMRI)) was used for group comparison., Results: In 25/30 patients (83.3%) (18 preterm and seven term-born neonates), "SyMRI" acquisitions were successfully performed. "SyMRI"-based myelination scores were significantly lower in preterm compared with term-born neonates (ANCOVA: T1: F(1, 22) = 7.420, p = 0.012; T2: F(1, 22) = 5.658, p = 0.026). "SyMRI"-based myelination scores positively correlated with GAMRI (T1: r = 0.662, n = 25, p ≤ 0.001; T2: r = 0.676, n = 25, p ≤ 0.001). The myelination scores based on standard MRI did not correlate with the GAMRI. No significant differences between preterm and term-born neonates were detectable., Conclusions: "SyMRI" is a highly promising MR technique for neonatal brain imaging. "SyMRI" is superior to conventional MR sequences in the visual detection of delayed myelination in preterm neonates., Key Points: • By providing multiple MR contrasts, "SyMRI" is a time-saving method in neonatal brain imaging. • Differences concerning the myelination in term-born and preterm infants are visually detectable on T1-/T2-weighted maps generated by "SyMRI". • "SyMRI" allows a faster and more sensitive assessment of myelination compared with standard MR sequences.

Objective: To assess whether parenteral nutrition for infants of extremely low birth weight using a mixed lipid emulsion that contains fish oil influences electrophysiological brain maturation., Study Design: The study is a prespecified secondary outcome analysis of a randomized controlled trial of 230 infants of extremely low birth weight receiving a mixed (soybean oil, medium-chain triglycerides, olive oil, and fish oil; intervention) or a soybean oil-based lipid emulsion (control). The study was conducted at a single-level IV neonatal care unit (Medical University Vienna; June 2012 to October 2015). Electrophysiological brain maturation (background activity, sleep-wake cycling, and brain maturational scores) was assessed biweekly by amplitude-integrated electroencephalography (birth to discharge)., Results: A total of 317 amplitude-integrated electroencephalography measurements (intervention: n = 165; control: n = 152) from 121 (intervention: n = 63; control: n = 58) of 230 infants of the core study were available for analysis. Demographic characteristics were not significantly different. By 28 weeks of postmenstrual age, infants receiving the intervention displayed significantly greater percentages of continuous background activity. Total maturational scores and individual scores for continuity, cycling, and bandwidth were significantly greater. Maximum maturational scores were reached 2 weeks earlier in the intervention group (36.4 weeks, 35.4-37.5) compared with the control group (38.4 weeks, 37.1-42.4) (median, IQR; P < .001)., Conclusions: Using a mixed parenteral lipid emulsion that contains fish oil, we found that electrophysiological brain maturation was accelerated in infants who were preterm., Trial Registration: ClinicalTrials.gov: NCT01585935., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Filter and peak detection algorithms implemented in amplitude-integrated electroencephalogram (aEEG) systems are not standardized. New aEEG systems are continuously enriching the market and clinicians are faced with different aEEG devices whose tracings may vary., Objectives: The aim of this work was to determine the role of different aEEG systems on quantitative measurements of the aEEG., Methods: In this observational study, a single-channel aEEG recording (Olympic CFM 6000) with corresponding EEG signal was obtained from 32 infants at a gestational age of 36-44 weeks. The signals were split into 334 episodes of 4 h. New aEEG tracings were generated using the NicoletOne Reader Software and aEEG emulations with varying filter profiles and peak detection settings. The aEEG amplitude margins and automated annotation of continuous normal voltage (CNV) were compared., Results: The output of the Olympic and the NicoletOne systems are very similar but not identical; the Spearman rank correlations of the aEEG amplitude margins exceeded 0.9 and the differences in the lower and upper amplitude margins were 1.55 μV (SD 1.47) and -2.12 μV (SD 1.44) on average (n = 309), respectively. The aEEG emulation showed that the differences between the output of the Olympic and the NicoletOne system could be primarily ascribed to the peak detection algorithm. The differences in output can affect automated analyses with agreement rates in CNV detection of 76% (n = 32, positive) and 92% (n = 32, negative) when comparing the Olympic to the NicoletOne outputs., Conclusions: Commercial aEEG systems have similar but not identical outputs. Care is advised when interpreting automated aEEG classifications across different devices., (© 2017 S. Karger AG, Basel.)

Background: Few data have been published on the combined use of amplitude-integrated electroencephalography (aEEG) and near-infrared spectroscopy (NIRS) for outcome prediction in neonates cooled for hypoxic-ischemic encephalopathy (HIE)., Objective: Our aim was to evaluate the predictive values and the most powerful predictive combinations of single aEEG and NIRS parameters and the respective cut-off values with regard to short-term outcomes in HIE II., Methods: aEEG and NIRS were prospectively studied at the Medical University of Vienna in the first 102 h of life with regard to magnetic resonance imaging (MRI). Thirty-two neonates diagnosed with HIE II treated with hypothermia were investigated. The measurement period was divided into 6-h epochs. According to MRI, 2 outcome groups were defined and predictive values of aEEG parameters, regional cerebral oxygen saturation (rScO2), and the additional value of both methods combined were studied. Receiver operating curves (ROC) were obtained and area under the curve (AUC) values were calculated. ROC were then used to detect the optimal cut-off points, sensitivity, specificity, positive predictive values, and negative predictive values., Results: At all time epochs, combined parameter scores were more predictive than single parameter scores. The highest AUC were observed between 18 and 60 h of cooling for the aEEG summation score (0.72-0.84) and for (background pattern + seizures) × rScO2 (0.79-0.85). At 42-60 h sensitivity was similar between those 2 scores (87.5-90.0%), but the addition of NIRS to aEEG led to an increase in specificity (from 52.4-59.1% to 72.7-90.5%)., Conclusions: In HIE II, aEEG and NIRS are important predictors of short-term outcome. The combination of both methods improves prognostication. The highest predictive abilities were observed between 18 and 60 h of cooling., (© 2017 S. Karger AG, Basel.)

Aim: The aim of this study was to measure the brain activity of preterm infants treated with caffeine citrate and doxapram for preterm apnoea, using amplitude-integrated electroencephalography (aEEG), to identify any adverse effects on cerebral function., Methods: We analysed the aEEG tracings of 13 preterm infants <30 weeks of gestation before, during and after doxapram treatment, with regard to background activity (percentages of continuous and discontinuous patterns), occurrence of sleep-wake cycling and appearance of electrographic seizure activity. They were also compared with 61 controls without doxapram treatment., Results: During doxapram treatment, aEEG tracings showed an increase in continuous background activity (19 ± 30% before treatment, 38 ± 35% during treatment) and a decrease in discontinuous patterns. In addition, they showed more frequent electrographic seizure activity (0% before treatment, 15 ± 37% during treatment) and less frequent sleep-wake cycling (92 ± 27% before treatment, 85 ± 37% during treatment) could be observed. These results were confirmed when compared to the control group., Conclusion: Doxapram treatment influences aEEG in preterm infants, showing higher percentages of continuous activity as well as more electrographic seizure activity and less sleep-wake cycling. It should, therefore, be used with caution in very preterm infants., (©2014 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.)