40 research outputs found
Volumétrie des ventricules latéraux chez le nouveau-né par segmentation automatique d’échographies 3D
Les nouvelles sondes échographiques d’ultrason (US) permettent d’acquérir des volumes de
manière quasi instantanée et ce sans balayage. En comparaison avec les sondes deux dimensions
(2D), ceci permet de diminuer le temps d’acquisition tout en ayant une qualité d’image
similaire et potentiellement une meilleure confiance dans l’interprétation ou le diagnostic.
L’évaluation ou le suivi du développement du cerveau et de la taille des ventricules est nécessaire
pour plusieurs situations où le nouveau-né y est vulnérable comme dans des cas de
naissances prématurées, d’hémorragie intraventriculaire (HIV), ou d’interventions chirurgicales.
De plus, au niveau psychologique, une dilatation importante des ventricules latéraux
est associée à divers troubles neurologiques ou retard de développement cognitif. Au niveau
physique, une dilatation est associée à un développement altéré de la matière blanche et un
volume anormal de matière grise corticale. Réaliser un suivi de la dilatation des ventricules
latéraux peut donc permettre de déterminer si le nouveau-né est à risque d’avoir des effets
négatifs sur son développement cognitif ou encore, pour les cas plus graves, si une intervention
chirurgicale est nécessaire.
Si une anormalité est trouvée en examen standard 2D US, une acquisition par imagerie par
résonnance magnétique (IRM) peut être prescrite pour un examen approfondi. Cependant,
l’IRM est difficile à utiliser pour imager le cerveau des nouveau-nés en raison de la contrainte
d’immobilisation qui se traduit souvent par l’utilisation d’un sédatif. Donc une alternative
pour suivre le développement du cerveau est d’utiliser une sonde matricielle avec une acquisition
à travers la fontanelle qui est encore ouverte chez le nouveau-né de quelques mois. De
plus, cette alternative permettrait de réaliser des analyses volumiques avec une méthode plus
accessible et moins coûteuse que l’IRM. L’hypothèse du projet est que les images ultrasons
acquises dans les premiers mois de vie du nouveau-né peuvent servir à évaluer le développement
du cerveau et des ventricules latéraux en raison de la possibilité de réaliser des analyses
volumiques quantitatives sur les volumes des ventricules latéraux et du cerveau. L’objectif
du projet est donc de valider les volumes extraits des images tridimensionnelles (3D) US avec
ceux de référence en IRM et de développer une méthodologie pour extraire automatiquement
le volume du cerveau et des ventricules latéraux.
Dans un premier temps, les ventricules latéraux sont segmentés manuellement sur les images
IRM et 3D US acquises pour une première cohorte de patients. De plus, une méthode géométrique
est développée afin d’estimer le volume du cerveau qui n’est pas inclus complètement
par le faisceau d’acquisition. Cette méthode utilise un ellipsoïde pour modéliser la forme du
cerveau où le volume peut donc être calculé avec les 3 semi-axes. Cette estimation du volume
du cerveau est comparée à la mesure de circonférence de la tête, mesure pratiquée en
clinique pour suivre le développement du cerveau, mais qui comporte plusieurs limitations.
De plus, le ratio volumique ventricule-cerveau peut être calculé, ce qui permet d’évaluer la
dilatation relative des ventricules par rapport au cerveau. Une Ă©tude comparative avec des
tests statistiques est réalisée afin de valider les volumes extraits des images échographiques
avec ceux de l’IRM qui représentent la vérité terrain. Les résultats démontrent qu’il n’y a
aucune différence statistiquement significative entre les volumes extraits des images 3D US
et des images IRM et qu’il y a une corrélation presque parfaite pour les ventricules latéraux
(r=0.999) et une excellente corrélation pour le volume du cerveau (r=0.988). Ces analyses
peuvent être réalisées sur les nouveau-nés jusqu’à l’âge d’environ 8 mois, âge où la fontanelle
antérieure commence à se fermer empêchant les ondes acoustiques de passer.
Dans un deuxième temps, le volume du cerveau est extrait automatiquement de l’image 3D
US en isolant le cerveau du crâne et en appliquant la méthode géométrique développée. De
plus, les ventricules latéraux ont été segmentés automatiquement sur 13 patients. Un recalage
multi-atlas est d’abord réalisé avec des images IRM. Comme le recalage est multimodal, la
différence des principes physiques des deux modalités d’imagerie le rend plus complexe et
c’est pourquoi une métrique spécialement conçue pour le recalage US-IRM, la LC2 (Linear
Correlation of Linear Combination) est utilisée. Les recalages sont suivis par une sélection des
meilleures images et une fusion. Cependant, la LC2 ne permet pas de sélectionner automatiquement
les meilleurs recalages entre différents atlas ou images IRM. Cette sélection est alors
réalisée avec un terme de pondération de régions combiné à la LC2. La région ventriculaire
est composée de deux sous-régions, la cavité de fluide qui est hypoéchogène et la choroïde
plexus qui est hyperéchogène. Ce terme de pondération définit un poids pour chaque voxel
de la région ventriculaire projetée, selon l’intensité et la position de ce voxel sur l’image échographique.
Par la suite, deux algorithmes de fusion sont utilisés dans le projet, soit Majority
Voting (MV) et STAPLE. Finalement, le résultat de la fusion est transformé en maillage et
une déformation du maillage par minimisation d’énergie est implémentée pour finaliser la
segmentation. Les résultats de segmentation démontrent une amélioration des résultats avec
le terme de pondération par régions, la fusion, et le maillage déformable. Les résultats de segmentation
finaux permettent d’avoir une précision adéquate en volume (DICE : 70.8%±3.6)
et un faible écart des surfaces (Mean Absolute Distance : 0.88mm ± 0.20). Quant aux volumes
du cerveau extraits automatiquement, ils ont une erreur absolue moyenne de 7.73% et
une très bonne corrélation (r=0.942 ) comparativement à 3.12% et une excellente corrélation
(r=0.988) lorsqu’ils sont extrait manuellement. De plus, les volumes des ventricules latéraux
sont Ă©galement extraits des segmentations (9.84% erreur absolue moyenne et r=0.848), ce qui
permet de calculer le ratio volumique ventricule-cerveau automatiquement.
Les travaux présentés dans ce mémoire ouvrent de nouvelles perspectives sur l’évaluation du
développement du cerveau chez les nouveau-nés. Nos résultats démontrent qu’il est possible
d’évaluer le volume du cerveau et des ventricules latéraux avec les nouvelles sondes matricielles
d’échographies, ce qui pourrait augmenter l’accessibilité et la facilité des évaluations et
des suivis réalisés en clinique. De plus, cela permet de calculer le ratio volumique ventriculecerveau
afin d’évaluer la sévérité de la dilatation des ventricules relativement à la taille du
cerveau.----------ABSTRACT
New matrix-array ultrasound (US) probes allow neuroradiologists to acquire volumetric images
almost instantly with no sweep of the region of interest. Compared to traditional 2D
protocols, 3D US imaging decreases acquisition time without reducing image quality and
could increase interpretation capabilities. Monitoring of the brain and lateral ventricles development
is necessary especially in cases of premature birth, intraventricular hemorrhage
(IVH) and surgical interventions. Significant ventricular dilatation is associated with some
neurological disorders as well as lower scores on the Bayley scale of infant development and
in some circumstances lower intelligence quotient (IQ). Furthermore, it is also associated
with altered white matter development and abnormal volume of cortical gray matter. By
monitoring the patients’ lateral ventricular dilatation, it is possible to determine if this is a
risk factor for their cognitive development or if a surgical intervention is necessary in serious
situations.
If an abnormality is found with standard 2D US examinations, an MRI can be prescribed for a
thorough examination. MRI is challenging with newborns due to immobilization issues, which
requires most of the time sedation of the newborn. An alternative is to use recent matrix-array
probes instead to perform non-invasive brain imaging through the fontanel. This will allow
to perform volumetric analysis with an imaging method more accessible and less expensive
than MRI. The project hypothesis is that it is possible to evaluate brain and ventricular
development with the 3D US images and accomplish a series of quantitative volumetric
measurements. The objective of this project is to validate the volumetric measurement of
the 3D US images with the reference MRI and to develop a method to automatically extract
the brain volume and segment the lateral ventricles in 3D US. The lateral ventricles volume
is important to assess the progression of the dilatation before and after surgical interventions
and to assess the severity of the dilatation.
First, MRI and 3D US images are acquired for an initial cohort of 12 patients and the lateral
ventricles are segmented manually in both imaging modalities. A geometric method is also
developed in order to estimate the brain volume which is not fully captured by the limited
US probe beam. This method uses an ellipsoid to model the brain shape where its volume is
calculated with the 3 ellipsoid semi-axes. This brain volume estimation is compared to the
head circumference (HC) which is a widely used method in clinical practice to follow brain
development, although there are limitations associated with this approach. Ventricular-brain
volume ratio is also calculated to assess the severity of the ventricular dilatation relatively to
the brain size. A comparative study and statistical analysis are then undertaken to validate
volumes obtained from 3D US images with those from MRI. Results show no statistically
significant differences between the extracted MRI and 3D US volumes. Lateral ventricles
have a near perfect correlation (r=0.999) and there is an excellent correlation for the brain
volume (r=0.988). The difference in volume ratios was 6.0 ± 4.8% compared to MRI. Those
analysis are possible on newborns and infants until they are approximately 8 months old,
which is the age where the fontanelle starts to close, reducing the acoustic waves propagation.
Secondly, the brain and lateral ventricles volumes are automatically extracted from the 3D
US images. The brain volume is estimated with the same ellipsoid method after it has been
aligned and stripped from the skull. The lateral ventricles were segmented on 13 patients
using a multi-atlas registration pipeline with MRI images. Since this is a multimodal registration,
a highly specific metric is used to register the MRI with the US images, the LC2 metric
(Linear Correlation of Linear Combination). Then, the best registrations are selected for a
label fusion but the LC2 alone doesn’t allow to automatically select the best registrations
between several MRI images. An area weighting term is combined with the LC2 in order to
improve the affine registration and to compare the registration results between several MRI
images. The area weighting term assigns a weight to each voxel of the projected venricular
area based on the position and intensity of the voxel on the US image. Indeed, the ventricular
areas are divided in two areas, the fluid cavities which are hypoechoic and the plexus choroĂŻd
which is hyperechoic. These regions are used in the calculation of the weighting term. Two
algorithms are tested for the label fusion, Majority Voting (MV) and STAPLE. Furthermore,
the mesh is refined using deformable mesh model with an energy minimization process.
The segmentation results are encouraging (DICE: 70.8±3.6, Mean Absolute Distance: 0.88±
0.20) and the extracted volumes have no statistically significant differences with the manual
segmentations. The brain volumes have a mean absolute error with MRI volumes of 7.73%
and a good correlation (r=0.942) when automatically segmented. As a comparison, the
error was of 3.12% and the correlation excellent (r=0.988) with the manual measurements.
In addition, the automatically extracted lateral ventricles volumes have a good correlation
(r=0.848) with the manual segmentations and a mean absolute error of 9.84%.
The methodology and results presented in this thesis show new perspectives and tools to help
evaluate the infants’ brain development. This project demonstrates the potential of using
new matrix-array US probes to assess brain and lateral ventricular volumes in newborns and
infants which could be useful to facilitate monitoring of the lateral ventricles dilatation used
for the macrocephaly diagnosis. Furthermore, it is possible to calculate the ventricular-brain
volume ratio to assess the dilatation severity relatively to the brain volume
Honeycombs with structured core for enhanced damping
Honeycomb sandwich panels, formed by bonding a core of honeycomb between two thin face sheets, are in wide use in aerospace, automotive and marine applications due to their well-known excellent density-specific properties. There are many technological methods of damping vibrations, including the use of inherently lossy materials such as viscoelastic materials, viscous and friction damping and smart materials such as piezoelectrics. Some have been applied to damping of vibrations, in particular to sandwich panel and honeycomb structures, including viscoelastic inserts in the cell voids. Complete filling of the cell with foam, viscoelastic or particulate fillers have all been demonstrated to improve damping loss in honeycombs. However, the use of an additional damping material inside the core of a sandwich panel increases its mass, which is often deleterious and may also lead to a significant change in dynamic properties. The work presented in this thesis explores the competing demands of vibration damping and minimum additional mass in the case of secondary inserts in honeycomb-like structures.
The problem was tackled by initially characterising the main local deformation mechanism of a unit cell within a sandwich panel subjected to vibration. Out-of-plane bending deformation of the honeycomb unit cell was shown to be the predominant mode of deformation for most of the honeycomb cells within a sandwich panel. The out-of-plane bending deformation of the honeycomb cells results in relatively high in-plane deformation of the cells close to the skins of the sandwich panels. It was also highlighted that the magnitude and loading of the honeycomb unit cell are dependent on its location within the honeycomb or sandwich panel and the mode shape of the panel.
An optimisation study was carried out on diverse honeycomb unit cell geometries to find locations at which the relative displacement between the honeycomb cell walls of the void is maximal under in-plane loadings. These locations were shown to be dependant of the nature of the loading, i.e. in-plane tension/compression or in-plane shear loading of the honeycomb unit cell and the unit cell geometry.
Analytical expressions and finite element analyses were used to investigate the partial filling of the honeycomb unit cell with a damping material, in this case a viscoelastic elastomer, in the target locations identified previously where the relative displacement between the honeycomb cell walls is maximal. Damping inserts in the form of ligaments partially filling the honeycomb cell void have shown to increase the density-specific loss modulus by 26% compared to cells completely filled with damping material for in-plane tension/compression loading.
The form of the damping insert itself was then analysed for enhancement of the dissipation provided by the damping material. The shear lap joint (SLJ) damping insert placed in the location where the relative displacement between the honeycomb cell walls of the void is maximal under in-plane loadings was characterised with very significant damping improvements compared to honeycomb cells completely filled with viscoelastic material.
A case study of a cantilever honeycomb sandwich panel with embedded SLJ damping inserts demonstrated their efficiency in enhancing the loss factor of the structure for minimum added mass and marginal variation of the first modal frequency of the structure. Partial filling of the cells of the honeycomb core was shown to be the most efficient at increasing damping on a density basis.Rolls-Royce Pl
Multi-objective optimisation of viscoelastic damping inserts in honeycomb sandwich structures
PublishedArticleAccepted ManuscriptThe Double-Shear Lap Joint (DSLJ) is a novel damping insert sited internally within a structure which is particularly well suited for lightweight sandwich structures with internal voids, such as honeycomb core sandwich panels. In high performance lightweight structures, the insertion of relatively more dense dampers of any type may increase the total mass substantially and alter the mass distribution significantly. The objective herein was to determine the optimum location, number and orientation of DSLJ inserts within a typical sandwich panel, and thereby to assess the efficacy of two different optimisation approaches to this problem; a parametric optimisation and the Adaptive Indicator-Based Evolutionary Algorithm (IBEA). Both approaches were used to maximise the damping while minimising the additional mass of the damping inserts applied to the structure. Although the parametric approach was faster and easier to implement, the Adaptive IBEA identified significantly better configurations in many cases, especially where veering occurred, in one case improving modal loss factors more than fourfold vs the parametric method. Solutions were identified with large increases in modal loss factors but only small increases in mass vs the empty structure.This work was supported by the MEET project (Material for Energy Efficiency in Transport) in the context of the INTERREG IV-A France (Channel) England European cross-border co-operation programme, which is co-financed by the ERDF
Impact of brain overgrowth on sensorial learning processing during the first year of life
Macrocephaly is present in about 2–5% of the general population. It can be found as an isolated benign trait or as part of a syndromic condition. Brain overgrowth has been associated with neurodevelopmental disorders such as autism during the first year of life, however, evidence remains inconclusive. Furthermore, most of the studies have involved pathological or high-risk populations, but little is known about the effects of brain overgrowth on neurodevelopment in otherwise neurotypical infants. We investigated the impact of brain overgrowth on basic perceptual learning processes (repetition effects and change detection response) during the first year of life. We recorded high density electroencephalograms (EEG) in 116 full-term healthy infants aged between 3 and 11 months, 35 macrocephalic (14 girls) and 81 normocephalic (39 girls) classified according to the WHO head circumference norms. We used an adapted oddball paradigm, time-frequency analyses, and auditory event-related brain potentials (ERPs) to investigate differences between groups. We show that brain overgrowth has a significant impact on repetition effects and change detection response in the 10–20 Hz frequency band, and in N450 latency, suggesting that these correlates of sensorial learning processes are sensitive to brain overgrowth during the first year of life
DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France
We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon
The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases
The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article
MRS characterisation of a mountain hard rock aquifer: the Strengbach Catchment, Vosges Massif, France
International audienc
Impact of brain overgrowth on sensorial learning processing during the first year of life
Macrocephaly is present in about 2–5% of the general population. It can be found as an isolated benign trait or as part of a syndromic condition. Brain overgrowth has been associated with neurodevelopmental disorders such as autism during the first year of life, however, evidence remains inconclusive. Furthermore, most of the studies have involved pathological or high-risk populations, but little is known about the effects of brain overgrowth on neurodevelopment in otherwise neurotypical infants. We investigated the impact of brain overgrowth on basic perceptual learning processes (repetition effects and change detection response) during the first year of life. We recorded high density electroencephalograms (EEG) in 116 full-term healthy infants aged between 3 and 11 months, 35 macrocephalic (14 girls) and 81 normocephalic (39 girls) classified according to the WHO head circumference norms. We used an adapted oddball paradigm, time-frequency analyses, and auditory event-related brain potentials (ERPs) to investigate differences between groups. We show that brain overgrowth has a significant impact on repetition effects and change detection response in the 10–20 Hz frequency band, and in N450 latency, suggesting that these correlates of sensorial learning processes are sensitive to brain overgrowth during the first year of life