An openly available wearable, a diaper cover, monitors infant's respiration and position during rest and sleep.

AIM: To describe and test the accuracy of respiratory rate assessment in long-term surveillance using an open-source infant wearable, NAPping PAnts (NAPPA). METHODS: We recorded 24 infants aged 1-9 months using our newly developed infant wearable that is a diaper cover with an integrated programmable electronics with accelerometer and gyroscope sensors. The sensor collects child's respiration rate (RR), activity and body posture in 30-s epochs, to be downloaded afterwards into a mobile phone application. An automated RR quality measure was also implemented using autocorrelation function, and the accuracy of RR estimate was compared with a reference obtained from the simultaneously recorded capnography signal that was part of polysomnography recordings. RESULTS: Altogether 88 h 27 min of data were recorded, and 4147 epochs (39% of all data) were accepted after quality detection. The median of patient wise mean absolute errors in RR estimates was 1.5 breaths per minute (interquartile range 1.1-2.6 bpm), and the Blandt-Altman analysis indicated an RR bias of 0.0 bpm with the 95% limits of agreement of -5.7-5.7 bpm. CONCLUSION: Long-term monitoring of RR and posture can be done with reasonable accuracy in out-of-hospital settings using NAPPA, an openly available infant wearable.

Altered N100-potential associates with working memory impairment in Parkinson's disease.

The diagnosis of cognitive impairment and dementia often occurring with Parkinson's disease (PD) is still based on the clinical picture and neuropsychological examination. Ancillary methods to detect cognitive decline in these patients are, therefore, needed. Alterations in the latencies and amplitudes of evoked response potential (ERP) components N100 and P200 have been described in PD. Due to limited number of studies their relation to cognitive deficits in PD remains obscure. The present study was designed to examine if alterations in the N100- and P200-potentials associate with neuropsychological impairment in PD. EEG-ERP was conducted to 18 PD patients and 24 healthy controls. The patients underwent a thorough neuropsychological evaluation. The controls were screened for cognitive impairment with Consortium to Establish Alzheimer's disease (CERAD)-testing and a normal result were required to be included in the study. The N100-latency was prolonged in the patients compared to the controls (p = 0.05). In the patients, the N100 latency correlated significantly with a visual working memory task (p = 0.01). Also N100 latency was prolonged and N100 amplitude habituation diminished in the patients achieving poorly in this task. We conclude that prolonged N100-latency and diminished amplitude habituation associate with visual working memory impairment in PD.

Early Brain Activity Relates to Subsequent Brain Growth in Premature Infants.

Recent experimental studies have shown that early brain activity is crucial for neuronal survival and the development of brain networks; however, it has been challenging to assess its role in the developing human brain. We employed serial quantitative magnetic resonance imaging to measure the rate of growth in circumscribed brain tissues from preterm to term age, and compared it with measures of electroencephalographic (EEG) activity during the first postnatal days by 2 different methods. EEG metrics of functional activity were computed: EEG signal peak-to-peak amplitude and the occurrence of developmentally important spontaneous activity transients (SATs). We found that an increased brain activity in the first postnatal days correlates with a faster growth of brain structures during subsequent months until term age. Total brain volume, and in particular subcortical gray matter volume, grew faster in babies with less cortical electrical quiescence and with more SAT events. The present findings are compatible with the idea that (1) early cortical network activity is important for brain growth, and that (2) objective measures may be devised to follow early human brain activity in a biologically reasoned way in future research as well as during intensive care treatment.

Limiting CT radiation dose in children with craniosynostosis: phantom study using model-based iterative reconstruction.

BACKGROUND: Medical professionals need to exercise particular caution when developing CT scanning protocols for children who require multiple CT studies, such as those with craniosynostosis. OBJECTIVE: To evaluate the utility of ultra-low-dose CT protocols with model-based iterative reconstruction techniques for craniosynostosis imaging. MATERIALS AND METHODS: We scanned two pediatric anthropomorphic phantoms with a 64-slice CT scanner using different low-dose protocols for craniosynostosis. We measured organ doses in the head region with metal-oxide-semiconductor field-effect transistor (MOSFET) dosimeters. Numerical simulations served to estimate organ and effective doses. We objectively and subjectively evaluated the quality of images produced by adaptive statistical iterative reconstruction (ASiR) 30%, ASiR 50% and Veo (all by GE Healthcare, Waukesha, WI). Image noise and contrast were determined for different tissues. RESULTS: Mean organ dose with the newborn phantom was decreased up to 83% compared to the routine protocol when using ultra-low-dose scanning settings. Similarly, for the 5-year phantom the greatest radiation dose reduction was 88%. The numerical simulations supported the findings with MOSFET measurements. The image quality remained adequate with Veo reconstruction, even at the lowest dose level. CONCLUSION: Craniosynostosis CT with model-based iterative reconstruction could be performed with a 20-µSv effective dose, corresponding to the radiation exposure of plain skull radiography, without compromising required image quality.

Effect of patient centering on patient dose and image noise in chest CT.

OBJECTIVE: The objective of our study was to evaluate the effect of vertical centering on dose and image noise in chest MDCT of different-sized patients using anthropomorphic phantoms and retrospectively studying examinations of clinical patients. MATERIALS AND METHODS: Three different anthropomorphic phantoms were scanned using different vertical centering (offset ± 6 cm) and were assessed with radiation dose-monitoring software. The effect of vertical positioning on the radiation dose was studied using the volume CT dose index, dose-length product, and size-specific dose estimates for different-sized phantoms. Image noise was determined from CT number histograms. Vertical positioning for chest CT examinations of 112 patients ranging from neonates to adults were retrospectively assessed. RESULTS: Radiation doses were highest when using the posteroanterior scout image for automatic exposure control (AEC) and when phantoms were set in the lowest table position, and radiation doses were lowest when phantoms were set in the uppermost table position. For the adult phantom, relative doses increased by 38% in the lowest table position and decreased by 23% in the highest table position. Similarly, doses for pediatric 5-year-old and newborn phantoms were 21% and 12% higher in the lowest table position and 12% and 8% lower in the highest table position, respectively. The effect decreased when a lateral scout image was used for AEC. The relative noise was lowest when the phantoms were properly centered and increased with vertical offset. In clinical patients, we observed offset with a median value varying from 25 to 35 mm below the isocenter. CONCLUSION: Regardless of patient size, most patients in this study were positioned too low, which negatively affected both patient dose and image noise. Miscentering was more pronounced in smaller pediatric patients.

Effect of vertical positioning on organ dose, image noise and contrast in pediatric chest CT--phantom study.

BACKGROUND: CT optimization has a special importance in children. Smaller body size accentuates the importance of patient positioning affecting both radiation dose and image quality. OBJECTIVE: To determine the effect of vertical positioning on organ dose, image noise and contrast in pediatric chest CT examination. MATERIALS AND METHODS: Chest scans of a pediatric 5-year anthropomorphic phantom were performed in different vertical positions (-6 cm to +5.4 cm) with a 64-slice CT scanner. Organ doses were measured with metal-oxide-semiconductor field-effect transistor (MOSFET) dosimeters. Image noise and contrast were determined from the CT number histograms corresponding to different tissues. RESULTS: Significant changes in organ doses resulting from vertical positioning were observed, especially in radiosensitive anterior organs. The breast dose increased up to 16% and the thyroid dose up to 24% in lower positions. The noise was increased up to 45% relative to the centre position in the highest and lowest vertical positions, with a particular increase observed on the anterior and posterior sides, respectively. Off-centering also affected measured image contrast. CONCLUSION: Vertical off-centering markedly affects organ doses and measured image-quality parameters in pediatric chest CT examination. Special attention should be given to correct patient centering when preparing patients for CT scans, especially when imaging children.

Phase synchrony in the early preterm EEG: development of methods for estimating synchrony in both oscillations and events.

Development of neuronal connections relies on proper neuronal activity, and it starts during the time when early preterm babies are treated in the neonatal intensive care units. While synchrony has been a key element in visual assessment of neonatal EEG signals, there has been no unambiguous definitions for synchrony, and no objective measures available for neonatal signals. Estimation of phase locking value (PLV) has been an established paradigm in adults, but many unique characteristics of the neonatal EEG have precluded its applicability in them. In the present paper, we developed the existing PLV-based methods further to be applicable for neonatal signals at two different temporal scales, oscillations and events, where the latter refers technically to quantitating phase synchrony (PS) between band-specific amplitude envelopes (bafPS). In addition, we present a measure for quantitation based on assessing cumulative proportion of time with statistically significant synchrony between the given signal pair. The paper uses real EEG examples and the prior neurobiological knowledge in the process of defining optimal parameters in each step of the procedure. Finally, we apply the method to a set of dense array EEG recordings from very early preterm babies, recorded at conceptional age of less than 30 weeks. By comparing PS and bafPS from babies without and with major cerebrovascular lesion, we show that the effects of brain lesions may be selective both in space and in frequency. These findings do by nature escape visual detection in the conventional EEG reading, however they have intriguing correlates in the current concept of how somatosensory networks are thought to develop and/or become disorganized in the early preterm babies.

Compound nerve conduction velocity- a reflection of proprioceptive afferents?

OBJECTIVE: To gather the required sample size to compare compound nerve conduction velocities (CV) to cutaneous sensory CVs and motor CVs to find out if there are statistically significant differences between these nerve fibre populations. METHODS: We report age, height, and temperature standardized CVs for cutaneous sensory, motor, and compound nerve fibres measured by electroneuromyography (ENMG) for 109 median nerves in 74 people from different age groups with no known neuropathy (age 50.4, median 49, range 21-87). RESULTS: In the region of the forearm, mean CVs were 63.6m/s (CI=62.6-64.7) for compound nerve fibres, 61.3m/s (CI=60.1-62.5) for cutaneous sensory fibres, and 56.3m/s (CI=55.1-57.6) for motor fibres (for all p<0.001). Age explained most of the variation of CVs (Pearson's coefficients -0.394, -0,538, and -0.443, respectively, for all p

Measuring brain activity cycling (BAC) in long term EEG monitoring of preterm babies.

Measuring fluctuation of vigilance states in early preterm infants undergoing long term intensive care holds promise for monitoring their neurological well-being. There is currently, however, neither objective nor quantitative methods available for this purpose in a research or clinical environment. The aim of this proof-of-concept study was, therefore, to develop quantitative measures of the fluctuation in vigilance states or brain activity cycling (BAC) in early preterm infants. The proposed measures of BAC were summary statistics computed on a frequency domain representation of the proportional duration of spontaneous activity transients (SAT%) calculated from electroencephalograph (EEG) recordings. Eighteen combinations of three statistics and six frequency domain representations were compared to a visual interpretation of cycling in the SAT% signal. Three high performing measures (band energy/periodogram: R = 0.809, relative band energy/nonstationary frequency marginal: R = 0.711, g-statistic/nonstationary frequency marginal: R = 0.638) were then compared to a grading of sleep wake cycling based on the visual interpretation of the amplitude-integrated EEG trend. These measures of BAC are conceptually straightforward, correlate well with the visual scores of BAC and sleep wake cycling, are robust enough to cope with the technically compromised monitoring data available in intensive care units, and are recommended for further validation in prospective studies.

Sleep wake cycling in early preterm infants: comparison of polysomnographic recordings with a novel EEG-based index.

OBJECTIVE: To document the occurrence of genuine sleep stages in the early preterm babies, and to develop an EEG-based index for following sleep wake cyclicity. METHODS: Twelve preterm babies were recruited from a study that assessed ventilator strategies. We used altogether 18 polysomnography recordings that were collected at mean conceptional age of 29.3 (25.9-32.7) weeks. Spontaneous activity transients (SAT) were detected automatically and their cumulative coverage in each 20s interval was computed from the EEG derivations C3-A2 and O2-A1. Mean SAT% values between sleep stages were compared. RESULTS: All babies exhibited all sleep stages, however the sleep was remarkably fragmentary in infants due to their respiratory issues. The EEG index, SAT% showed temporal behavior that strikingly well compared with the sleep stage fluctuations in the hypnogram. In the statistical analysis we found significant differences in all recordings between the deep (quiet) sleep and the REM sleep. CONCLUSION: Genuine sleep states exist in the early preterm babies, and changes in sleep stages are reflected in the EEG activity in a way that can be readily measured by assessing fluctuation of the automatically detected, EEG based index, the SAT%. SIGNIFICANCE: The findings open a possibility to construct automated analysis or monitoring of sleep wake cyclicity into brain monitors in neonatal intensive care unit.

Multimodal event-related potentials in occupational chronic solvent encephalopathy.

The aim of this study was to test a multimodal event-related potential (ERP) paradigm in chronic solvent encephalopathy (CSE) to develop a sensitive method for the clinical diagnostics to CSE. The study comprised 11 CSE patients and 13 healthy controls. We used three tasks: an auditory odd-ball (AUD), a visual detection (VIS), and a recognition memory (MEM) task. The auditory and visual stimuli were presented in single- and dual-task conditions. The auditory P300 amplitude in single-task condition was smaller in the patient group than in the control group at the parietal (Pz) but not at the frontal midline electrode location. The auditory P300 response in the dual task condition AUD+VIS was unrecognizable in 8 of 11 patients and in 1 of 13 controls and in the AUD+MEM condition in 10 of 11 patients and in 4 of 13 controls. In the AUD+MEM condition, the auditory P300 amplitude at Pz was smaller in the patient group than in the control group. Reaction time for auditory stimuli in both dual conditions as well as for visual stimuli in AUD+VIS condition were in the patient group prolonged. The ERP results indicate that CSE patients present with slowed performance speed and difficulties in allocation of attention. Based on ERP results, the disturbance in brain activity in CSE seems to affect posterior aspects of the frontoparietal continuity. The multimodal paradigm seems promising as a tool for the clinical diagnostics of CSE.

Detection of 'EEG bursts' in the early preterm EEG: visual vs. automated detection.

OBJECTIVE: To describe the characteristics of activity bursts in the early preterm EEG, to assess inter-rater agreement of burst detection by visual inspection, and to determine the performance of an automated burst detector that uses non-linear energy operator (NLEO). METHODS: EEG recordings from extremely preterm (n=12) and very preterm (n=6) infants were analysed. Three neurophysiologists independently marked bursts in the EEG, the characteristics of bursts were analyzed and inter-rater agreement determined. Unanimous detections were used as the gold standard in estimating the performance of an automated burst detector. In addition, some details of this automated detector were revised in an attempt to improve performance. RESULTS: Overall, inter-rater agreement was 86% for extremely preterm infants and 81% for very preterm infants. In visual markings, bursts had variable lengths (approximately 1-10s) and increased amplitudes (and power) throughout the frequency spectrum. Accuracy of the original detection algorithm was 87% and 79% and accuracy of the revised algorithm 93% and 87% for extremely preterm and very preterm babies, respectively. CONCLUSION: Visual detection of bursts from the early preterm EEG is comparable albeit not identical between raters. The original automated detector underestimates the amount of burst occurrence, but can be readily improved to yield results comparable to visual detection. Further clinical studies are warranted to assess the optimal descriptors of burst detection for monitoring and prognostication. SIGNIFICANCE: Validation of a burst detector offers an evidence-based platform for further development of brain monitors in very preterm babies.

Optimization of an NLEO-based algorithm for automated detection of spontaneous activity transients in early preterm EEG.

We propose here a simple algorithm for automated detection of spontaneous activity transients (SATs) in early preterm electroencephalography (EEG). The parameters of the algorithm were optimized by supervised learning using a gold standard created from visual classification data obtained from three human raters. The generalization performance of the algorithm was estimated by leave-one-out cross-validation. The mean sensitivity of the optimized algorithm was 97% (range 91-100%) and specificity 95% (76-100%). The optimized algorithm makes it possible to systematically study brain state fluctuations of preterm infants.