Infinite Feature Selection on Shore-Based Biomarkers Reveals Connectivity Modulation after Stroke

Connectomics is gaining increasing interest in the scientific and clinical communities. It consists in deriving models of structural or functional brain connections based on some local measures. Here we focus on structural connectivity as detected by diffusion MRI. Connectivity matrices are derived from microstructural indices obtained by the 3D-SHORE. Typically, graphs are derived from connectivity matrices and used for inferring node properties that allow identifying those nodes that play a prominent role in the network. This information can then be used to detect network modulations induced by diseases. In this paper we take a complementary approach and focus on link as opposed to node properties. We hypothesize that network modulation can be better described by measuring the connectivity alteration directly in the form of modulation of the properties of white matter fiber bundles constituting the network communication backbone. The goal of this paper is to detect the paths that are most altered by the pathology by exploiting a feature selection paradigm. Temporal changes on connection weights are treated as features and those playing a leading role in a patient versus healthy controls classification task are detected by the Infinite Feature Selection (Inf-FS) method. Results show that connection paths with high discriminative power can be identified that are shared by the considered microstructural descriptors allowing a classification accuracy ranging between 83% and 89%

An introduction to model-independent diffusion magnetic resonance imaging.

ABSTRACT: q-Space-based techniques such as diffusion spectrum imaging, q-ball imaging, and their variations have been used extensively in research for their desired capability to delineate complex neuronal architectures such as multiple fiber crossings in each of the image voxels. The purpose of this article was to provide an introduction to the q-space formalism and the principles of basic q-space techniques together with the discussion on the advantages as well as challenges in translating these techniques into the clinical environment. A review of the currently used q-space-based protocols in clinical research is also provided

Long-Term Monitoring of Post-Stroke Plasticity After Transient Cerebral Ischemia in Mice Using In Vivo and Ex Vivo Diffusion Tensor MRI

We used a murine model of transient focal cerebral ischemia to study: 1) in vivo DTI long-term temporal evolution of the apparent diffusion coefficient (ADC) and diffusion fractional anisotropy (FA) at days 4, 10, 15 and 21 after stroke 2) ex vivo distribution of a plasticity-related protein (GAP-43) and its relationship with the ex vivo DTI characteristics of the striato-thalamic pathway (21 days)

Nanotecnologia na agricultura: prospecção dos indicadores de impactos ambientais e sociais.

Resumo: A Nanotecnologia está baseada na crescente capacidade da tecnologia moderna de manipular átomos e partículas em nanoescala, com aplicações em diversas áreas de atuação, desde a medicina, meio ambiente e agricultura. Apesar das nanotecnologias apresentarem propriedades físicas específicas, a avaliação dos impactos associados ao seu emprego e liberação no meio ambiente ainda não é uma prática corrente. Neste cenário, o presente trabalho propõe um estudo de caso sobre as nanopartículas na agricultura, através da formulação de indicadores de impacto a partir de levantamento da literatura científica

Método 'Impactos-Nanotec' para avaliação dos impactos ambientais: estudo de caso das nanotecnologias na agricultura.

Resumo: A Nanotecnologia está baseada na crescente capacidade da tecnologia moderna de manipular átomos e partículas em nanoescala, com aplicações em diversas áreas de atuação desde a medicina, meio ambiente e agricultura. Apesar das nanotecnologias apresentarem propriedades físicas específicas, a avaliação dos impactos associados ao seu emprego e liberação no meio ambiente ainda não é uma prática corrente. Neste cenário, o presente trabalho propõe o estudo de caso de nanopartículas na agricultura, através do levantamento de indicadores, utilizando uma metodologia empregada para estudo de transgênicos, adaptada para um novo software de avaliação de risco de nanoproduto

A New Approach for Deep Gray Matter Analysis Using Partial-Volume Estimation.

INTRODUCTION: The existence of partial volume effects in brain MR images makes it challenging to understand physio-pathological alterations underlying signal changes due to pathology across groups of healthy subjects and patients. In this study, we implement a new approach to disentangle gray and white matter alterations in the thalamus and the basal ganglia. The proposed method was applied to a cohort of early multiple sclerosis (MS) patients and healthy subjects to evaluate tissue-specific alterations related to diffuse inflammatory or neurodegenerative processes. METHOD: Forty-three relapsing-remitting MS patients and nineteen healthy controls underwent 3T MRI including: (i) fluid-attenuated inversion recovery, double inversion recovery, magnetization-prepared gradient echo for lesion count, and (ii) T1 relaxometry. We applied a partial volume estimation algorithm to T1 relaxometry maps to gray and white matter local concentrations as well as T1 values characteristic of gray and white matter in the thalamus and the basal ganglia. Statistical tests were performed to compare groups in terms of both global T1 values, tissue characteristic T1 values, and tissue concentrations. RESULTS: Significant increases in global T1 values were observed in the thalamus (p = 0.038) and the putamen (p = 0.026) in RRMS patients compared to HC. In the Thalamus, the T1 increase was associated with a significant increase in gray matter characteristic T1 (p = 0.0016) with no significant effect in white matter. CONCLUSION: The presented methodology provides additional information to standard MR signal averaging approaches that holds promise to identify the presence and nature of diffuse pathology in neuro-inflammatory and neurodegenerative diseases