Kirsi Palmu

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.

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.

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.

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.

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.

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.

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

BackgroundMedical professionals need to exercise particular caution when developing CT scanning protocols for children who require multiple CT studies, such as those with craniosynostosis.ObjectiveTo evaluate the utility of ultra-low-dose CT protocols with model-based iterative reconstruction techniques for craniosynostosis imaging.Materials and methodsWe 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.ResultsMean 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.ConclusionCraniosynostosis 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.

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.

Semiautomatic quantification of spiking in patients with continuous spikes and waves in sleep: sensitivity to settings and correspondence to visual assessment.

OBJECTIVE To define the optimal analysis protocol for semiautomatic quantification of spike index (SI) in continuous spikes and waves in sleep (CSWS). METHODS Ten overnight EEGs (nine patients) with abundant spiking were used to quantify SI with a previously published semiautomatic quantification based on spike detection with BESA software. We studied (i) dependency of SI on maximal interspike interval (maxISI) defining the continuous discharge, (ii) sensitivity of SI to variations in the spike search protocol, and (iii) stability of SI over time. Finally, the semiautomatic method was compared with the quantification based on visual scoring by two neurophysiologists. RESULTS MaxISI of 3s appeared to yield the best combination of sensitivity and stability in SI quantification. The SI of the first hour of sleep did not differ significantly from the SI of the whole night. Mean error of the semiautomatic method compared to visual scoring was only seven percentage units. CONCLUSIONS Semiautomatic quantification of SI functions well with maxISI of 3s, and the first hour of sleep represents the whole night SI with a clinically relevant accuracy. SIGNIFICANCE This method opens a possibility for objective quantification of near-continuous epileptiform spiking during sleep, and it supports the use of shorter epochs for quantitative assessment of CSWS.

P10-17 Measures of the spontaneous, intermittent activity in the early preterm EEG

Conclusions: According to our preliminary results, the proposed approach proved suitable to address the analysis of brain imaginative functions, allowing to discriminate different mental states without the limitations of an fMRI scanner, in the perspective to be used at the patient’s bedside. This methods can thus open the way to real-time Brain Computer Interface applications addressed to non responsive patients, as part of the objectives of the European Project DECODER. Acknowledgements: This work was supported by the European ICT Program FP7-ICT-2009 4 Grant Agreement 247919 DECODER. This paper only reflects the authors’ views and funding agencies are not liable for any use that may be made of the information contained herein.