Anatomie du tractus cortico-spinal en tractographie : évaluation d'une méthode déterministe

Introduction : Si la substance grise a été largement étudiée en IRM fonctionnelle (IRMf), l'étude in vivo des tractus de substance blanche est plus récente. L'IRM en tenseur de diffusion permet désormais d'étudier son anatomie grâce à la tractographie. Notre objectif était l'étude du tractus cortico-spinal (TCS) en tenseur de diffusion et en tractographie chez des sujets sains. Matériel et méthodes : La population concernait 15 volontaires sains droitiers. Une IRM 3T anatomique T1 a permis la détermination des régions d'intérêts (ROI) au niveau du mésencéphale. L'IRMf a été analysée par le logiciel SPM5 afin d'obtenir une carte d'activation représentant l'activation motrice de la main au niveau du cortex moteur. L'IRM de diffusion a servi à reconstruire un tenseur (matrice 3x3) en chaque voxel de l'image. Après recalage des 3 séquences, nous avons effectué une tractographie du TCS par une méthode déterministe utilisant l'algorithme (Mori et al). Les tractographies ont été réalisées entre les deux ROI de chaque côté. Résultat : Cette méthode donne une représentation anatomique du TSC méconnaissent la partie ventro-latérale de la ROI fonctionnelle. Cette partie correspond aux croisements de fibres des autres faisceaux de fibres blanches traversant la région. Conclusion : La limite principale du tenseur se situe au niveau des croisements des fibres, car il ne représente correctement qu'une seule direction de diffusion. Cela ne permet pas actuellement de retrouver l'anatomie des faisceaux de fibres telle que nous la connaissons pas les dissections. Les méthodes déterministes mono-directionnelles ne sont pas suffisantes notamment dans le contexte de la chirurgie guidée par l'image. Elles doivent être enrichies de méthodes multidirectionnelles en utilisant des algorithmes plus complexes

Image guidance in neurosurgical procedures, the "Visages" point of view.

This paper gives an overview of the evolution of clinical neuroinformatics in the domain of neurosurgery. It shows how image guided neurosurgery (IGNS) is evolving according to the integration of new imaging modalities before, during and after the surgical procedure and how this acts as the premise of the Operative Room of the future. These different issues, as addressed by the VisAGeS INRIA/INSERM U746 research team (http://www.irisa.fr/visages), are presented and discussed in order to exhibit the benefits of an integrated work between physicians (radiologists, neurologists and neurosurgeons) and computer scientists to give adequate answers toward a more effective use of images in IGNS

Mixed-Model Noise Removal in 3D MRI via Rotation-and-Scale Invariant Non-Local Means

Mixed noise is a major issue influencing quantitative analysis in different forms of magnetic resonance image (MRI), such as T1 and diffusion image like DWI and DTI. Using different filters sequentially to remove mixed noise will severely deteriorate such medical images. We present a novel algorithm called rotation-and-scale invariant nonlocal means filter (RSNLM) to simultaneously remove mixed noise from different kinds of three-dimensional (3D) MRI images. First, we design a new similarity weights, including rank-ordered absolute difference (ROAD), coming from a trilateral filter (TriF) that is obtained to detect the mixed and high-level noise. Then, we present a shape view to consider the MRI data as a 3D operator, with which the similarity between the patches is calculated with the rigid transformation. The translation, rotation and scale have no influence on the similarity. Finally, the adaptive parameter estimation method of ROAD is illustrated, and the effective proof that validates the proposed algorithm is presented. Experiments using synthetic data with impulse noise, Rician noise, and the real MRI data confirm that the proposed method yields superior performance compared with current state-of-the-art methods

Danos genéticos e exposição a pesticidas em trabalhadores agrícolas do Vale San Quintin, Baixa California, México

Various studies have shown the ability of pesticides to induce genetic damage (GD) that can cause health effects. In the present work, a genotoxicological study was conducted monitoring residents from the agricultural region of the San Quintin Valley (SQV), Baja California, Mexico. The objective was to determine if occupational and environmental exposure to pesticides in the region of the SQV is a factor in GD, and to find out if women are more vulnerable to this effect. A questionnaire was administered to 88 residents of the SQV to establish inclusion and exclusion criteria for the study; of these, 40 agreed to participate (25 occupationally exposed to pesticides and 15 environmentally exposed to them), with similar numbers of men and women. All participants signed an informed consent form. The micronuclei technique (MN) was used, which blocks cytokinesis in peripheral blood samples, to evaluate GD by counting the number of MN and Chromatin Bridges in 1000 bi-nucleated cells (BNC). The results of this measure of genetic damage were then correlated with the degree of occupational pesticide exposure of the participants. Environmentally exposed men had less GD than women with MN means of 8.1± (1.83) and 13.1(±1.7) respectively, whereas occupational exposure affected both sexes, men with a mean of MN equal to 15.9 (± 2.9), and women with 18.12 (± 1.7). Based on our results, it can be concluded that occupational exposure to pesticides is a factor in GD, with women showing greater vulnerability than men. The time of exposure at work was shown to be directly related to the increased number of MN.Diferentes estudios muestran la capacidad de los plaguicidas para inducir daño genético (DG) con diversos efectos en la salud. En el presente trabajo se estudia la genotoxicidad en residentes del valle agrícola de San Quintín, Baja California, México (VSQ). El objetivo fue determinar si la exposición laboral y ambiental a plaguicidas en la región del VSQ es un factor de DG y explorar si las mujeres son más vulnerables a dicho efecto. Se aplicó un cuestionario a 88 residentes del VSQ para determinar los factores de inclusión y exclusión del estudio, 40 aceptaron participar, 25 expuestos ocupacionalmente a plaguicidas y 15 ambientalmente expuestos, con similar número de hombres y mujeres. Todos los participantes firmaron un consentimiento informado. Se utilizó la técnica de micronúcleos (MN) por bloqueo de la citocinesis en sangre periférica para evaluar el DG con la frecuencia de MN y Puentes de Cromatina en 1000 células binucleadas (CBN); se exploró la correlación del DG con el tiempo de exposición ocupacional a plaguicidas. Los hombres ambientalmente expuestos tuvieron menos DG que las mujeres con medias de MN de 8,1 (±1,83) y 13,1 (±1,7) respectivamente; en cambio, la exposición laboral afectó a los dos sexos: los hombres tuvieron una media de MN igual a 15,9 (±2,9) y en las mujeres fue 18,1 (±1,7). Se concluye que la exposición laboral a plaguicidas es un factor de DG, las mujeres mostraron mayor vulnerabilidad al DG. El tiempo de exposición laboral se relaciona directamente con el aumento del número de MN.Diferentes estudos mostram a capacidade que os pesticidas possuem para induzir dano genético (DG) com diversos efeitos na saúde. Neste trabalho estudou-se a genotoxicidade em residentes do vale agrícola de San Quintin, Baixa Califórnia, México (VSQ), cujo objetivo foi determinar se a exposição ocupacional e ambiental a pesticidas nesta região é um fator DG e explorar se as mulheres são mais vulneráveis a este efeito. Aplicou-se um questionário a 88 moradores do VSQ para determinar os fatores de inclusão e exclusão no estudo, 40 concordaram em participar dos quais 25 com exposição ocupacional e 15 com exposição ambiental, com um número idêntico de homens e mulheres. Todos os participantes assinaram um termo de consentimento informado. Foi utilizada a técnica de micronúcleos (MN) por bloqueio da citocinese em amostras de sangue periférico para avaliar o DG com a frequência de MN e Pontes de Cromatina em 1000 células binucleadas (CBN); explorou-se a correlação do DG com o tempo de exposição ocupacional a pesticidas. Os homens ambientalmente expostos tiveram menos DG do que as mulheres com médias de MN de 8,1 ± (1,83) y 13,1 (±1,7) respetivamente; por outro lado, a exposição ocupacional afetou os dois sexos: os homens tiveram uma média de MN igual 15,9 (± 2,9) e nas mulheres foi de 18,1 (± 1,7). Concluiu-se que a exposição ocupacional a pesticidas é um facto de DG e as mulheres apresentam maior vulnerabilidade a DG. O tempo de exposição ocupacional está diretamente relacionado com o aumento do número de MN

MRI noise estimation and denoising using non-local PCA

NOTICE: this is the author’s version of a work that was accepted for publication in Medical Image AnalysisChanges resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Medical Image Analysis, [Volume 22, Issue 1, May 2015, Pages 35–47] DOI 10.1016/j.media.2015.01.004This paper proposes a novel method for MRI denoising that exploits both the sparseness and self-similarity properties of the MR images. The proposed method is a two-stage approach that first filters the noisy image using a non local PCA thresholding strategy by automatically estimating the local noise level present in the image and second uses this filtered image as a guide image within a rotationally invariant non-local means filter. The proposed method internally estimates the amount of local noise presents in the images that enables applying it automatically to images with spatially varying noise levels and also corrects the Rician noise induced bias locally. The proposed approach has been compared with related state-of-the-art methods showing competitive results in all the studied cases.We are grateful to Dr. Matteo Mangioni and Dr. Alessandro Foi for their help on running their BM4D method in our comparisons. We want also to thank Dr. Luis Marti-Bonmati and Dr. Angel Alberich-Bayarri from Quiron Hospital of Valencia for providing the real clinical data used in this paper. This study has been carried out with financial support from the French State, managed by the French National Research Agency (ANR) in the frame of the Investments for the future Programme IdEx Bordeaux (ANR-10-IDEX-03-02), Cluster of excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57).Manjón Herrera, JV.; Coupé, P.; Buades, A. (2015). MRI noise estimation and denoising using non-local PCA. Medical Image Analysis. 22(1):35-47. doi:10.1016/j.media.2015.01.004S354722

Denoising for improved parametric MRI of the kidney: protocol for nonlocal means filtering

In order to tackle the challenges caused by the variability in estimated MRI parameters (e.g., T(2)* and T(2)) due to low SNR a number of strategies can be followed. One approach is postprocessing of the acquired data with a filter. The basic idea is that MR images possess a local spatial structure that is characterized by equal, or at least similar, noise-free signal values in vicinities of a location. Then, local averaging of the signal reduces the noise component of the signal. In contrast, nonlocal means filtering defines the weights for averaging not only within the local vicinity, bur it compares the image intensities between all voxels to define "nonlocal" weights. Furthermore, it generally compares not only single-voxel intensities but small spatial patches of the data to better account for extended similar patterns. Here we describe how to use an open source NLM filter tool to denoise 2D MR image series of the kidney used for parametric mapping of the relaxation times T(2)* and T(2).This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers

Diffusion Weighted Image Denoising using overcomplete Local PCA

Diffusion Weighted Images (DWI) normally shows a low Signal to Noise Ratio (SNR) due to the presence of noise from the measurement process that complicates and biases the estimation of quantitative diffusion parameters. In this paper, a new denoising methodology is proposed that takes into consideration the multicomponent nature of multi-directional DWI datasets such as those employed in diffusion imaging. This new filter reduces random noise in multicomponent DWI by locally shrinking less significant Principal Components using an overcomplete approach. The proposed method is compared with state-of-the-art methods using synthetic and real clinical MR images, showing improved performance in terms of denoising quality and estimation of diffusion parameters.This work has been supported by the Spanish grant TIN2011-26727 from Ministerio de Ciencia e Innovacion. 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