Perceiving object dangerousness: an escape from pain?

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Deep Boosted Regression for MR to CT Synthesis

Attenuation correction is an essential requirement of positron emission tomography (PET) image reconstruction to allow for accurate quantification. However, attenuation correction is particularly challenging for PET-MRI as neither PET nor magnetic resonance imaging (MRI) can directly image tissue attenuation properties. MRI-based computed tomography (CT) synthesis has been proposed as an alternative to physics based and segmentation-based approaches that assign a population-based tissue density value in order to generate an attenuation map. We propose a novel deep fully convolutional neural network that generates synthetic CTs in a recursive manner by gradually reducing the residuals of the previous network, increasing the overall accuracy and generalisability, while keeping the number of trainable parameters within reasonable limits. The model is trained on a database of 20 pre-acquired MRI/CT pairs and a four-fold random bootstrapped validation with a 80:20 split is performed. Quantitative results show that the proposed framework outperforms a state-of-the-art atlas-based approach decreasing the Mean Absolute Error (MAE) from 131HU to 68HU for the synthetic CTs and reducing the PET reconstruction error from 14.3% to 7.2%.Comment: Accepted at SASHIMI201

Integrated Nitrogen CAtchment model (INCA) applied to a tropical catchment in the Atlantic Forest, São Paulo, Brazil

International audienceStream-water flows and in-stream nitrate and ammonium concentrations in a small (36.7 ha) Atlantic Forest catchment were simulated using the Integrated Nitrogen in CAtchments (INCA) model version 1.9.4. The catchment, at Cunha, is in the Serra do Mar State Park, SE Brazil and is nearly pristine because the nearest major conurbations, São Paulo and Rio, are some 450 km distant. However, intensive farming may increase nitrogen (N) deposition and there are growing pressures for urbanisation. The mean-monthly discharges and NO3-N concentration dynamics were simulated adequately for the calibration and validation periods with (simulated) loss rates of 6.55 kg.ha?1 yr?1 for NO3-N and 3.85 kg.ha?1 yr?1 for NH4-N. To investigate the effects of elevated levels of N deposition in the future, various scenarios for atmospheric deposition were simulated; the highest value corresponded to that in a highly polluted area of Atlantic Forest in Sao Paulo City. It was found that doubling the atmospheric deposition generated a 25% increase in the N leaching rate, while at levels approaching the highly polluted São Paulo deposition rate, five times higher than the current rate, leaching increased by 240%, which would create highly eutrophic conditions, detrimental to downstream water quality. The results indicate that the INCA model can be useful for estimating N concentration and fluxes for different atmospheric deposition rates and hydrological conditions

Changes in electrophysiological static and dynamic human brain functional architecture from childhood to late adulthood

Published: 04 November 2020This magnetoencephalography study aimed at characterizing age-related changes in resting-state functional brain organization from mid-childhood to late adulthood. We investigated neuromagnetic brain activity at rest in 105 participants divided into three age groups: children (6–9 years), young adults (18–34 years) and healthy elders (53–78 years). The effects of age on static resting-state functional brain integration were assessed using band-limited power envelope correlation, whereas those on transient functional brain dynamics were disclosed using hidden Markov modeling of power envelope activity. Brain development from childhood to adulthood came with (1) a strengthening of functional integration within and between resting-state networks and (2) an increased temporal stability of transient (100–300 ms lifetime) and recurrent states of network activation or deactivation mainly encompassing lateral or medial associative neocortical areas. Healthy aging was characterized by decreased static resting-state functional integration and dynamic stability within the primary visual network. These results based on electrophysiological measurements free of neurovascular biases suggest that functional brain integration mainly evolves during brain development, with limited changes in healthy aging. These novel electrophysiological insights into human brain functional architecture across the lifespan pave the way for future clinical studies investigating how brain disorders affect brain development or healthy aging.This study was supported by the Action de Recherche Concertée Consolidation (ARCC, “Characterizing the spatio-temporal dynamics and the electrophysiological bases of resting state networks”, ULB, Brussels, Belgium), the Fonds Erasme (Research Convention “Les Voies du Savoir”,Brussels, Belgium) and the Fonds de la Recherche Scientifique (Research Convention: T.0109.13, FRS-FNRS, Brussels, Belgium). Nicolas Coquelet has been supported by the ARCC, by the Fonds Erasme (Research Convention “Les Voies du Savoir”, Brussels, Belgium) and is supported by the FRS-FNRS (Research Convention: Excellence of Science EOS “MEMODYN”). Alison Mary is Postdoctoral Researcher at the FRS-FNRS. Maxime Niesen and Marc Vander Ghinst have been supported by the Fonds Erasme. Mariagrazia Ranzini is supported by the Marie Sklodowska-Curie European Union’s Horizon 2020 research and innovation program (Research Grant: 839394). Mathieu Bourguignon is supported by the program Attract of Innoviris (Research Grant 2015-BB2B-10, Brussels, Belgium), the Marie Sklodowska-Curie Action of the European Commission (Research Grant: 743562) and by the Spanish Ministery of Economy and Competitiveness (Research Grant: PSI2016-77175-P). Xavier De Tiège is Postdoctorate Clinical Master Specialist at the FRS-FNRS. The MEG project at the CUB Hôpital Erasme is financially supported by the Fonds Erasme

Uncertainty-aware multi-resolution whole-body MR to CT synthesis

Synthesising computed tomography (CT) images from magnetic resonance images (MRI) plays an important role in the field of medical image analysis, both for quantification and diagnostic purposes. Especially for brain applications, convolutional neural networks (CNNs) have proven to be a valuable tool in this image translation task, achieving state-of-the-art results. Full body image synthesis, however, remains largely uncharted territory, bearing many challenges including a limited field of view and large image size, complex spatial context and anatomical differences between time-elapsing image acquisitions. We propose a novel multi-resolution cascade 3D network for end-to-end full-body MR to CT synthesis. We show that our method outperforms popular CNNs like U-Net in 2D and 3D. We further propose to include uncertainty in our network as a measure of safety and to account for intrinsic noise and misalignment in the data

A Multi-Channel Uncertainty-Aware Multi-Resolution Network for MR to CT Synthesis

Synthesising computed tomography (CT) images from magnetic resonance images (MRI) plays an important role in the field of medical image analysis, both for quantification and diagnostic purposes. Convolutional neural networks (CNNs) have achieved state-of-the-art results in image-to-image translation for brain applications. However, synthesising whole-body images remains largely uncharted territory, involving many challenges, including large image size and limited field of view, complex spatial context, and anatomical differences between images acquired at different times. We propose the use of an uncertainty-aware multi-channel multi-resolution 3D cascade network specifically aiming for whole-body MR to CT synthesis. The Mean Absolute Error on the synthetic CT generated with the MultiResunc network (73.90 HU) is compared to multiple baseline CNNs like 3D U-Net (92.89 HU), HighRes3DNet (89.05 HU) and deep boosted regression (77.58 HU) and shows superior synthesis performance. We ultimately exploit the extrapolation properties of the MultiRes networks on sub-regions of the body

Sequential occurrence of thrombotic thrombocytopenic purpura, essential thrombocythemia, and idiopathic thrombocytopenic purpura in a 42-year-old African-American woman: a case report and review of the literature

<p>Abstract</p> <p>Introduction</p> <p>Thrombotic thrombocytopenic purpura and idiopathic thrombocytopenic purpura are two well recognized syndromes that are characterized by low platelet counts. In contrast, essential thrombocythemia is a myeloproliferative disease characterized by abnormally high platelet numbers.</p> <p>The coexistence of thrombotic thrombocytopenic purpura and idiopathic thrombocytopenic purpura in a single patient has been reported in the literature on a few occasions. However, having essential thrombocythemia complicating the picture has never been reported before.</p> <p>Case presentation</p> <p>We present a case where thrombotic thrombocytopenic purpura, essential thrombocythemia, and idiopathic thrombocytopenic purpura were diagnosed in a 42-year-old African-American woman in the space of a few years; we are reporting this case with the aim of drawing attention to this undocumented occurrence, which remains under investigation.</p> <p>Conclusions</p> <p>As the three conditions have different natural histories and require different treatment modalities, it is important to recognize that these diseases may be seen sequentially. This case emphasizes the importance of reviewing peripheral blood smears for evaluation of thrombocytopenia and bone marrow aspirations for diagnosis of thrombocythemia in order to reach an accurate diagnosis and tailor therapy accordingly. Moreover, this case demonstrates the variability and complexity of platelet disorders. This occurrence of three different types of platelet disorders in one patient remains a pure observation on our part; regardless, this does raise the possibility of a common underlying, as yet undiscovered, pathophysiology that could explain the phenomenon.</p

White matter tract disconnection in Gerstmann's syndrome: Insights from a single case study

It has been suggested that Gerstmann's syndrome is the result of subcortical disconnection rather than emerging from damage of a multifunctional brain region within the parietal lobe. However, patterns of white matter tract disconnection following parietal damage have been barely investigated. This single case study allows characterising Gerstmann's syndrome in terms of disconnected networks. We report the case of a left parietal patient affected by Gerstmann's tetrad: agraphia, acalculia, left/right orientation problems, and finger agnosia. Lesion mapping, atlas-based estimation of probability of disconnection, and DTI-based tractography revealed that the lesion was mainly located in the superior parietal lobule, and it caused disruption of both intraparietal tracts passing through the inferior parietal lobule (e.g., tracts connecting the angular, supramarginal, postcentral gyri, and the superior parietal lobule) and fronto-parietal long tracts (e.g., the superior longitudinal fasciculus). The lesion site appears to be located more superiorly as compared to the cerebral regions shown active by other studies during tasks impaired in the syndrome, and it reached the subcortical area potentially critical in the emergence of the syndrome, as hypothesised in previous studies. Importantly, the reconstruction of tracts connecting regions within the parietal lobe indicates that this critical subcortical area is mainly crossed by white matter tracts connecting the angular gyrus and the superior parietal lobule. Taken together, these findings suggest that this case study might be considered as empirical evidence of Gerstmann's tetrad caused by disconnection of intraparietal white matter tracts