Point Shear Wave Elastography by ElastPQ for Fibrosis Screening in Patients with NAFLD: A Prospective, Multicenter Comparison to Vibration-Controlled Elastography.

Background: Since nonalcoholic fatty liver disease (NAFLD) has become the leading cause of liver disease in the Western world, clinicians need reliable noninvasive tools for the identification of NAFLD-associated fibrosis. Limited evidence on the performance of the novel shear wave elastography technique Elast-PQ (EPQ) in NAFLD is available.

Method: In this prospective, European multinational study we assessed the diagnostic accuracy of EPQ using vibration-controlled transient elastography (VCTE) as a reference standard.

Magnitude dependent discordance in liver stiffness measurements using elastography point quantification with transient elastography as the reference test.

Objectives: To investigate diagnostic performance of point shear wave elastography by elastography point quantification (ElastPQ) for non-invasive assessment of liver fibrosis in patients with chronic liver diseases (CLD).

Methods: Liver stiffness measurement (LSM) by transient elastography (TE) and ElastPQ was performed in patients with CLD and healthy volunteers. The stage of liver fibrosis was defined by TE which served as the reference.

Ultrasound Grade of Liver Steatosis Is Independently Associated with the Risk of Metabolic Syndrome.

The aim of the study was to explore (a) prevalence and grade of nonalcoholic fatty liver (NAFL) among outpatients referred for abdominal ultrasound (US) examination and (b) relationship between the presence and severity of liver steatosis and metabolic syndrome (MS). This was a retrospective analysis of patients without history of liver disease examined by abdominal US in the University hospital setting. US was used to detect and semiquantitatively grade (0-3) liver steatosis.

Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study.

Background: To improve the objective assessment of continuous video-EEG (cEEG) monitoring of neonatal brain function, the aim was to relate automated derived amplitude and duration parameters of the suppressed periods in the EEG background (dynamic Interburst Interval= dIBIs) after neonatal hypoxic-ischemic encephalopathy (HIE) to favourable or adverse neurodevelopmental outcome.

Methods: Nineteen neonates (gestational age 36-41 weeks) with HIE underwent therapeutic hypothermia and had cEEG-monitoring. EEGs were retrospectively analyzed with a previously developed algorithm to detect the dynamic Interburst Intervals.

Non-invasive diagnosis of portal hypertension in cirrhosis using ultrasound based elastography.

Liver stiffness measurement (LSM) by ultrasound-based elastography may be used to non-invasively discriminate between the stages of liver fibrosis, rule out cirrhosis and follow its evolution, including the prediction of the presence of oesophageal varices. The same is possible in order to diagnose clinically significant portal hypertension, referring primarilyto transient elastography and LSM values ≥20-25 kPa. The same approach may be used to reliably rule out the presence ofoesophageal varices (LSM <20 kPa + platelets >150x109/L).

Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database.

Objective: To assess interrater agreement based on majority voting in visual scoring of neonatal seizures.

Methods: An online platform was designed based on a multicentre seizure EEG-database. Consensus decision based on 'majority voting' and interrater agreement was estimated using Fleiss' Kappa.

Data-driven metric representing the maturation of preterm EEG.

Essential information about early brain maturation can be retrieved from the preterm human electroencephalogram (EEG). This study proposes a new set of quantitative features that correlate with early maturation. We exploit the known early trend in EEG content from intermittent to continuous activity, which changes the line length content of the EEG.

Improving Reliability of Monitoring Background EEG Dynamics in Asphyxiated Infants.

The goal of this study is to develop an automated algorithm to quantify background electroencephalography (EEG) dynamics in term neonates with hypoxic ischemic encephalopathy. The recorded EEG signal is adaptively segmented and the segments with low amplitudes are detected. Next, depending on the spatial distribution of the low-amplitude segments, the first part of the algorithm detects (dynamic) interburst intervals (dIBIs) and performs well on the relatively artifact-free EEG periods and well-defined burst-suppression EEG periods.

Objective differentiation of neonatal EEG background grades using detrended fluctuation analysis.

A quantitative and objective assessment of background electroencephalograph (EEG) in sick neonates remains an everyday clinical challenge. We studied whether long range temporal correlations quantified by detrended fluctuation analysis (DFA) could be used in the neonatal EEG to distinguish different grades of abnormality in the background EEG activity. Long-term EEG records of 34 neonates were collected after perinatal asphyxia, and their background was scored in 1 h epochs (8 h in each neonate) as mild, moderate or severe.

Interhemispheric synchrony in the neonatal EEG revisited: activation synchrony index as a promising classifier.

A key feature of normal neonatal EEG at term age is interhemispheric synchrony (IHS), which refers to the temporal co-incidence of bursting across hemispheres during trace alternant EEG activity. The assessment of IHS in both clinical and scientific work relies on visual, qualitative EEG assessment without clearly quantifiable definitions. A quantitative measure, activation synchrony index (ASI), was recently shown to perform well as compared to visual assessments.

Holistic approach for automated background EEG assessment in asphyxiated full-term infants.

Objective: To develop an automated algorithm to quantify background EEG abnormalities in full-term neonates with hypoxic ischemic encephalopathy.

Approach: The algorithm classifies 1 h of continuous neonatal EEG (cEEG) into a mild, moderate or severe background abnormality grade. These classes are well established in the literature and a clinical neurophysiologist labeled 272 1 h cEEG epochs selected from 34 neonates.

Line length as a robust method to detect high-activity events: automated burst detection in premature EEG recordings.

Objective: EEG is a valuable tool for evaluation of brain maturation in preterm babies. Preterm EEG constitutes of high voltage burst activities and more suppressed episodes, called interburst intervals (IBIs). Evolution of background characteristics provides information on brain maturation and helps in prediction of neurological outcome.

Heart rate variability in newborns with hypoxic brain injury.

In neonatal intensive care units, there is a need for continuous monitoring of sick newborns with perinatal hypoxic ischemic brain injury (HIE). We assessed the utility of heart rate variability (HRV) in newborns with acute HIE undergoing simultaneous continuous EEG (cEEG) and ECG monitoring. HIE was classified using clinical criteria as well as visual grading of cEEG.

Multi-structural signal recovery for biomedical compressive sensing.

Compressive sensing has shown significant promise in biomedical fields. It reconstructs a signal from sub-Nyquist random linear measurements. Classical methods only exploit the sparsity in one domain.

Multi-sparse signal recovery for compressive sensing.

Signal recovery is one of the key techniques of compressive sensing (CS). It reconstructs the original signal from the linear sub-Nyquist measurements. Classical methods exploit the sparsity in one domain to formulate the L0 norm optimization.

Automated EEG inter-burst interval detection in neonates with mild to moderate postasphyxial encephalopathy.

EEG inter-burst interval (IBI) and its evolution is a robust parameter for grading hypoxic encephalopathy and prognostication in newborns with perinatal asphyxia. We present a reliable algorithm for the automatic detection of IBIs. This automated approach is based on adaptive segmentation of EEG, classification of segments and use of temporal profiles to describe the global distribution of EEG activity.

Independent component analysis as a preprocessing step for data compression of neonatal EEG.

We propose a novel approach for compressive sampling of the neonatal electro-encefalogram (EEG) data. The method assumes that the set of EEG data is generated by linearly mixing a fewer number of source signals. Another assumption is that the sources are nearly-sparse in Gabor dictionary.