Data-driven normative values based on generative manifold learning for quantitative MRI.

In medicine, abnormalities in quantitative metrics such as the volume reduction of one brain region of an individual versus a control group are often provided as deviations from so-called normal values. These normative reference values are traditionally calculated based on the quantitative values from a control group, which can be adjusted for relevant clinical co-variables, such as age or sex. However, these average normative values do not take into account the globality of the available quantitative information.

Fault roughness controls injection-induced seismicity.

Surface roughness ubiquitously prevails in natural faults across various length scales. Despite extensive studies highlighting the important role of fault geometry in the dynamics of tectonic earthquakes, whether and how fault roughness affects fluid-induced seismicity remains elusive. Here, we investigate the effects of fault geometry and stress heterogeneity on fluid-induced fault slip and associated seismicity characteristics using laboratory experiments and numerical modeling.

Individualised profiling of white matter organisation in moderate-to-severe traumatic brain injury patients.

Background And Purpose: Approximately 65% of moderate-to-severe traumatic brain injury (m-sTBI) patients present with poor long-term behavioural outcomes, which can significantly impair activities of daily living. Numerous diffusion-weighted MRI studies have linked these poor outcomes to decreased white matter integrity of several commissural tracts, association fibres and projection fibres in the brain. However, most studies have focused on group-based analyses, which are unable to deal with the substantial between-patient heterogeneity in m-sTBI.

SARS-CoV-2 Transmission in Belgian French-Speaking Primary Schools: An Epidemiological Pilot Study.

Schools have been a point of attention during the pandemic, and their closure one of the mitigating measures taken. A better understanding of the dynamics of the transmission of SARS-CoV-2 in elementary education is essential to advise decisionmakers. We conducted an uncontrolled non-interventional prospective study in Belgian French-speaking schools to describe the role of attending asymptomatic children and school staff in the spread of COVID-19 and to estimate the transmission to others.

Leveraging manifold learning techniques to explore white matter anomalies: An application of the TractLearn pipeline in epilepsy.

An accurate description of brain white matter anatomy in vivo remains a challenge. However, technical progress allows us to analyze structural variations in an increasingly sophisticated way. Current methods of processing diffusion MRI data now make it possible to correct some limiting biases.

The use of digital dermoscopy in the surveillance of melanocytic skin lesions: A real-life retrospective study comparing university hospital and private practices.

Background: Few studies have evaluated the role of digital dermoscopy (DD) in the surveillance of pigmented lesions in real-life practice.

Patients And Methods: Patients followed with DD by 4 hospital dermatologists (group 1) and 4 private dermatologists (group 2) were retrospectively included if they had had at least 2 DD examinations for a minimum of 4 pigmented lesions. Their characteristics, risk factors, history of excision of benign nevi and melanomas prior to and during the DD follow-up, and characteristics of detected melanomas, were recorded.

COVID-19 mortality, excess mortality, deaths per million and infection fatality ratio, Belgium, 9 March 2020 to 28 June 2020.

BackgroundCOVID-19 mortality, excess mortality, deaths per million population (DPM), infection fatality ratio (IFR) and case fatality ratio (CFR) are reported and compared for many countries globally. These measures may appear objective, however, they should be interpreted with caution.AimWe examined reported COVID-19-related mortality in Belgium from 9 March 2020 to 28 June 2020, placing it against the background of excess mortality and compared the DPM and IFR between countries and within subgroups.

Running biomechanical alterations during a 40-km mountain race.

Background: The purpose of this study was to analyze running biomechanical alterations according to different slopes (flat, uphill and downhill) and distance, during a 40-km mountain trail running race.

Methods: Throughout the race, eight runners were equipped with Runscribe inertial units placed on each running shoe. Measurements included spatiotemporal parameters (contact time, step frequency, stride length, running speed), kinetic (impact peak and braking force) and kinematic data (foot pronation velocity and foot pronation excursion).

HEMO life® improves renal function independent of cold ischemia time in kidney recipients: A comparison with a large multicenter prospective cohort study.

Background: M101 is an extracellular hemoglobin isolated from a marine lugworm and is present in the medical device HEMO life®. The clinical investigation OXYOP was a paired kidney analysis (n = 60) designed to evaluate the safety and performance of HEMO life® used as an additive to preservation solution in renal transplantation. The secondary efficacy endpoints showed less delayed graft function (DGF) and better renal function in the HEMO life® group but due to the study design cold ischemia time (CIT) was longer in the contralateral kidneys.

Establishing an ad hoc COVID-19 mortality surveillance during the first epidemic wave in Belgium, 1 March to 21 June 2020.

BackgroundCOVID-19-related mortality in Belgium has drawn attention for two reasons: its high level, and a good completeness in reporting of deaths. An ad hoc surveillance was established to register COVID-19 death numbers in hospitals, long-term care facilities (LTCF) and the community. Belgium adopted broad inclusion criteria for the COVID-19 death notifications, also including possible cases, resulting in a robust correlation between COVID-19 and all-cause mortality.

Assessing polypharmacy in the older population: Comparison of a self-reported and prescription based method.

Purpose: To explore differences in the prevalence and determinants of polypharmacy in the older general population in Belgium between self-reported and prescription based estimates and assess the relative merits of each data source.

Methods: Data were used from participants aged ≥65 years of the Belgian national health survey 2013 (n = 1950). Detailed information was asked on the use of medicines in the past 24 h and linked with prescription data from the Belgian compulsory health insurance (BCHI).

Minimal model for the onset of slip pulses in frictional rupture.

We present a minimal one-dimensional continuum model for the transition from cracklike to pulselike propagation of frictional rupture. In its nondimensional form, the model depends on only two free parameters: the nondimensional prestress and an elasticity ratio that accounts for the finite height of the system. The model predicts stable slip pulse solutions for slip boundary conditions, and unstable slip pulse solutions for stress boundary conditions.

TractLearn: A geodesic learning framework for quantitative analysis of brain bundles.

Deep learning-based convolutional neural networks have recently proved their efficiency in providing fast segmentation of major brain fascicles structures, based on diffusion-weighted imaging. The quantitative analysis of brain fascicles then relies on metrics either coming from the tractography process itself or from each voxel along the bundle. Statistical detection of abnormal voxels in the context of disease usually relies on univariate and multivariate statistics models, such as the General Linear Model (GLM).

A covariate-constraint method to map brain feature space into lower dimensional manifolds.

Human brain connectome studies aim to both explore healthy brains, and extract and analyze relevant features associated with pathologies of interest. Usually this consists of modeling the brain connectome as a graph and using graph metrics as features. A fine brain description requires graph metrics computation at the node level.

All-cause mortality supports the COVID-19 mortality in Belgium and comparison with major fatal events of the last century.

Background: The COVID-19 mortality rate in Belgium has been ranked among the highest in the world. To assess the appropriateness of the country's COVID-19 mortality surveillance, that includes long-term care facilities deaths and deaths in possible cases, the number of COVID-19 deaths was compared with the number of deaths from all-cause mortality. Mortality during the COVID-19 pandemic was also compared with historical mortality rates from the last century including those of the Spanish influenza pandemic.

Validity of self-reported mammography uptake in the Belgian health interview survey: selection and reporting bias.

Background: The validity of self-reported mammography uptake is often questioned. We assessed the related selection and reporting biases among women aged 50-69 years in the Belgian Health Interview Survey (BHIS) using reimbursement data for mammography stemming from the Belgian Compulsory Health Insurance organizations (BCHI).

Methods: Individual BHIS 2013 data (n = 1040) were linked to BCHI data 2010-13 (BHIS-BCHI sample).

Birth weight is associated with adolescent brain development: A multimodal imaging study in monozygotic twins.

Previous research has shown that the prenatal environment, commonly indexed by birth weight (BW), is a predictor of morphological brain development. We previously showed in monozygotic (MZ) twins associations between BW and brain morphology that were independent of genetics. In the present study, we employed a longitudinal MZ twin design to investigate whether variations in prenatal environment (as indexed by discordance in BW) are associated with resting-state functional connectivity (rs-FC) and with structural connectivity.

Variability and reproducibility in deep learning for medical image segmentation.

Medical image segmentation is an important tool for current clinical applications. It is the backbone of numerous clinical diagnosis methods, oncological treatments and computer-integrated surgeries. A new class of machine learning algorithm, deep learning algorithms, outperforms the results of classical segmentation in terms of accuracy.

Artificial intelligence to predict clinical disability in patients with multiple sclerosis using FLAIR MRI.

Purpose: The purpose of this study was to create an algorithm that combines multiple machine-learning techniques to predict the expanded disability status scale (EDSS) score of patients with multiple sclerosis at two years solely based on age, sex and fluid attenuated inversion recovery (FLAIR) MRI data.

Materials And Methods: Our algorithm combined several complementary predictors: a pure deep learning predictor based on a convolutional neural network (CNN) that learns from the images, as well as classical machine-learning predictors based on random forest regressors and manifold learning trained using the location of lesion load with respect to white matter tracts. The aggregation of the predictors was done through a weighted average taking into account prediction errors for different EDSS ranges.

Spatial distribution and differences of stroke occurrence in the Rhone department of France (STROKE 69 cohort).

In France, 110,000 patients are admitted to hospital per year for stroke. Even though the relationship between stroke and risk factors such as low socio-economic status is well known, research in the spatial distribution (SD) of stroke as a contributing risk factor is less documented. Understanding the geographic differences of the disease may improve stroke prevention.

Real Time 3D Observations of Portland Cement Carbonation at CO Storage Conditions.

Depleted oil reservoirs are considered a viable solution to the global challenge of CO storage. A key concern is whether the wells can be suitably sealed with cement to hinder the escape of CO. Under reservoir conditions, CO is in its supercritical state, and the high pressures and temperatures involved make real-time microscopic observations of cement degradation experimentally challenging.