29 research outputs found
Focal cerebellar pathology in early relapsing-remitting multiple sclerosis patients: a MP2RAGE study at 3T and 7T MRI
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Structure of laponite-styrene precursor dispersions for production of advanced polymer-clay nanocomposites
No full textOne method for production of polymer-clay nanocomposites involves dispersal of surface-modified clay in a polymerisable monomeric solvent, followed by fast in situ polymerisation. In order to tailor the properties of the final material we aim to control the dispersion state of the clay in the precursor solvent. Here, we study dispersions of surface-modified Laponite, a synthetic clay, in styrene via large-scale Monte-Carlo simulations and experimentally, using small angle X-ray and static light scattering. By tuning the effective interaction between simulated laponite particles we are able to reproduce the experimental scattering intensity patterns for this system, with good accuracy over a wide range of length scales. However, this agreement could only be obtained by introducing a permanent electrostatic dipole moment into the plane of each Laponite particle, which we explain in terms of the distribution of substituted metal atoms within each Laponite particle. This suggests that Laponite dispersions, and perhaps other clay suspensions, should display some of the structural characteristics of dipolar fluids. Our simulated structures show aggregation regimes ranging from networks of long chains to dense clusters of Laponite particles, and we also obtain some intriguing ‘globular’ clusters, similar to capsids. We see no indication of any ‘house-of-cards’ structures. The simulation that most closely matches experimental results indicates that gel-like networks are obtained in Laponite dispersions, which however appear optically clear and non-sedimenting over extended periods of time. This suggests it could be difficult to obtain truly isotropic equilibrium dispersion as a starting point for synthesis of advanced polymer-clay nanocomposites with controlled structures
Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE
No full textThe presence of cortical lesions in multiple sclerosis patients has emerged as an important biomarker of the disease. They appear in the earliest stages of the illness and have been shown to correlate with the severity of clinical symptoms. However, cortical lesions are hardly visible in conventional magnetic resonance imaging (MRI) at 3T, and thus their automated detection has been so far little explored. In this study, we propose a fully-convolutional deep learning approach, based on the 3D U-Net, for the automated segmentation of cortical and white matter lesions at 3T. For this purpose, we consider a clinically plausible MRI setting consisting of two MRI contrasts only: one conventional T2-weighted sequence (FLAIR), and one specialized T1-weighted sequence (MP2RAGE). We include 90 patients from two different centers with a total of 728 and 3856 gray and white matter lesions, respectively. We show that two reference methods developed for white matter lesion segmentation are inadequate to detect small cortical lesions, whereas our proposed framework is able to achieve a detection rate of 76% for both cortical and white matter lesions with a false positive rate of 29% in comparison to manual segmentation. Further results suggest that our framework generalizes well for both types of lesion in subjects acquired in two hospitals with different scanners.LTS5This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution
Good and bad practices in pv plants
No full textThe PVCROPS project (PhotoVolta ic Cost r€duction, Reliability, Operational performance, Prediction and Simulation), cofinanced by European Commission in the frame of Seventh Framework Programme, has compiled in the “Good and bad practices: Manual to improve the quality and reduce the cost of PV systems” a collection of good and bad practices in actual PV plants . All the situations it collects represent the state-of-the-art of existing PV installations all around Europe. They show how the different parts of an installation can be implem ented properly or not. The aim of this manual is to represent a reference text which can help any PV actor (installers, electricians, maintenance operators, owners, etc.) not only to check and improve an already existing installation but will also, and mainly, avoid the previously known bad practices for the construction of a new PV installation. Thus, solving a priori the known errors, new PV installations will be more reliable, efficient and cost-effective and can recover the initial investment in a shorter time. The manual is going to be free available in the PVCROPS website in several languages
An ultra-high field study of cerebellar pathology in early relapsing-remitting multiple sclerosis using MP2RAGE
No full textThe aim of this study was to study focal cerebellar pathology in early stages of multiple sclerosis (MS) using ultra-high-field magnetization-prepared 2 inversion-contrast rapid gradient-echo (7T MP2RAGE).Twenty early-stage relapsing-remitting MS patients underwent an MP2RAGE acquisition at 7 T magnetic resonance imaging (MRI) (images acquired at 2 different resolutions: 0.58 × 0.58 × 0.58 mm, 7T_0.58, and 0.75 × 0.75 × 0.90 mm, 7T_0.75) and 3 T MRI (1.0 × 1.0 × 1.2 mm, 3T_1.0). Total cerebellar lesion load and volume and mean cerebellar lesion volume were compared across images using a Wilcoxon signed-rank test. Mean T1 relaxation times in lesions and normal-appearing tissue as well as contrast-to-noise ratio (CNR) measurements were also compared using a Wilcoxon signed-rank test. A multivariate analysis was applied to assess the contribution of MRI metrics to clinical performance in MS patients.Both 7T_0.58 and 7T_0.75 MP2RAGE showed significantly higher lesion load compared with 3T_1.0 MP2RAGE (P < 0.001). Plaques that were judged as leukocortical in 7T_0.75 and 3T_1.0 MP2RAGEs were instead identified as WM lesions in 7T_0.58 MP2RAGE. Cortical lesion CNR was significantly higher in MP2RAGEs at 7 T than at 3 T. Total lesion load as well as total and mean lesion volume obtained at both 7 T and 3 T MP2RAGE significantly predicted attention (P < 0.05, adjusted R = 0.5), verbal fluency (P < 0.01, adjusted R = 0.6), and motor performance (P = 0.01, adjusted R = 0.7).This study demonstrates the value of 7 T MP2RAGE to study the cerebellum in early MS patients. 7T_0.58 MP2RAGE provides a more accurate anatomical description of white and gray matter pathology compared with 7T_0.75 and 3T_1.0 MP2RAGE, likely due to the improved spatial resolution, lower partial volume effects, and higher CNR
Improving clinico-radiological correlation in multiple sclerosis with automated tract and topology annotations
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The Evolution of Cortical and Sub-cortical Lesion Size and Number Correlates with Changes in Cognition in Early-Stage Relapsing-Remitting Multiple Sclerosis Patients
No full textLesion load and activity in multiple sclerosis (MS) patients, as identified by conventional magnetic resonance imaging (MRI), correlate only moderately with patients clinical status and evolution. Cortical lesion number and volume measured with advanced MRI may provide better correlates to cognitive dysfunction and disability. In this work, we studied the clinical impact of advanced MRI metrics of cortical and subcortical lesion evolution in a cohort of early relapsing-remitting MS patients. The number and volume of lesions that “shrunk”, disappeared or remained stable over time were strong determinants of changes in cognition in our patients cohort
Partial volume-aware assessment of multiple sclerosis lesions
No full textWhite-matter lesion count and volume estimation are key to the diagnosis and monitoring of multiple sclerosis (MS). Automated MS lesion segmentation methods that have been proposed in the past 20 years reach their limits when applied to patients in early disease stages characterized by low lesion load and small lesions. We propose an algorithm to automatically assess MS lesion load (number and volume) while taking into account the mixing of healthy and lesional tissue in the image voxels due to partial volume effects. The proposed method works on 3D MPRAGE and 3D FLAIR images as obtained from current routine MS clinical protocols. The method was evaluated and compared with manual segmentation on a cohort of 39 early-stage MS patients with low disability, and showed higher Dice similarity coefficients (median DSC = 0.55) and higher detection rate (median DR = 61%) than two widely used methods (median DSC = 0.50, median DR < 45%) for automated MS lesion segmentation. We argue that this is due to the higher performance in segmentation of small lesions, which are inherently prone to partial volume effects
