Mechanisms of pressure-diuresis and pressure-natriuresis in Dahl salt-resistant and Dahl salt-sensitive rats

<p>Abstract</p> <p>Background</p> <p>Data on blood flow regulation, renal filtration, and urine output in salt-sensitive Dahl S rats fed on high-salt (hypertensive) and low-salt (prehypertensive) diets and salt-resistant Dahl R rats fed on high-salt diets were analyzed using a mathematical model of renal blood flow regulation, glomerular filtration, and solute transport in a nephron.</p> <p>Results</p> <p>The mechanism of pressure-diuresis and pressure-natriuresis that emerges from simulation of the integrated systems is that relatively small increases in glomerular filtration that follow from increases in renal arterial pressure cause relatively large increases in urine and sodium output. Furthermore, analysis reveals the minimal differences between the experimental cases necessary to explain the observed data. It is determined that differences in renal afferent and efferent arterial resistances are able to explain all of the qualitative differences in observed flows, filtration rates, and glomerular pressure as well as the differences in the pressure-natriuresis and pressure-diuresis relationships in the three groups. The model is able to satisfactorily explain data from all three groups without varying parameters associated with glomerular filtration or solute transport in the nephron component of the model.</p> <p>Conclusions</p> <p>Thus the differences between the experimental groups are explained solely in terms of difference in blood flow regulation. This finding is consistent with the hypothesis that, if a shift in the pressure-natriuresis relationship is the primary cause of elevated arterial pressure in the Dahl S rat, then alternation in how renal afferent and efferent arterial resistances are regulated represents the primary cause of chronic hypertension in the Dahl S rat.</p

Modèle de transport de molécules dans le foie (application à l'IRM dynamique)

L'analyse d'images est une méthode non invasive utilisée dans la définition du diagnostic des lésions du foie. En complément de l analyse visuelle effectuée par les radiologues, certaines méthodes quantitatives, telles que l'analyse de texture peuvent donner des résultats encourageants dans la caractérisation des tumeurs. Nous proposons de coupler un modèle bi-niveau du foie, prenant en compte des paramètres physiologiques et pathologiques, avec un modèle d'acquisition d'IRM, dans le but de comprendre certaines relations entre les caractéristiques de l'image et le développement tumoral. Un modèle pharmacocinétique basé physiologie (PBPK) distribué axialement et adapté au foie, permet de simuler la distribution de molécules d agents de contraste spécifiques au foie. Il est couplé à un modèle macroscopique de l organe et de sa vascularisation. Ce modèle multi-échelle permet la simulation de modifications d'ordre pathologique liées au développement du carcinome hépatocellulaire, et la simulation des images IRM correspondantes.Image analysis is a noninvasive technique used to define the diagnosis of liver lesions. In addition to the visual inspection brought by radiologists, some quantitative methods such as texture analysis can also give encouraging results regarding tumor characterization. We propose to couple a bi-level model of the liver, which takes into account some physiological and pathological parameters, with the simulation of dynamic MRI acquisition, in order to understand some relations between image characteristics and the tumor development. A new axially-distributed Physiologically-Based PharmacoKinetic (PBPK) model, adapted to the liver, enables the simulation of the distribution of liver-specific contrast agents. This model is coupled with a macroscopic model of the liver and of its vascularisation. The multiscale model allows for i) simulations of pathological modifications related to the development of the hepatocellular carcinoma, and ii) simulations of corresponding MR images.RENNES1-BU Sciences Philo (352382102) / SudocSudocFranceF

Multiscale model of liver DCE-MRI towards a better understanding of tumor complexity.

International audienceThe use of quantitative imaging for the characterization of hepatic tumors in magnetic resonance imaging (MRI) can improve the diagnosis and therefore the treatment of these life-threatening tumors. However, image parameters remain difficult to interpret because they result from a mixture of complex processes related to pathophysiology and to acquisition. These processes occur at variable spatial and temporal scales. We propose a multiscale model of liver dynamic contrast-enhanced (DCE) MRI in order to better understand the tumor complexity in images. Our design couples a model of the organ (tissue and vasculature) with a model of the image acquisition. At the macroscopic scale, vascular trees take a prominent place. Regarding the formation of MRI images, we propose a distributed model of parenchymal biodistribution of extracellular contrast agents. Model parameters can be adapted to simulate the tumor development. The sensitivity of the multiscale model of liver DCE-MRI was studied through observations of the influence of two physiological parameters involved in carcinogenesis (arterial flow and capillary permeability) on its outputs (MRI images at arterial and portal phases). Finally, images were simulated for a set of parameters corresponding to the five stages of hepatocarcinogenesis (from regenerative nodules to poorly differentiated HepatoCellular Carcinoma)

Le singe marmouset comme modèle humain : Effet du vieillissement sur l'hémodynamique cérébrale.

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Diffeomorphic registration with self-adaptive spatial regularization for the segmentation of non-human primate brains

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On Single-Image Super-Resolution in 3D Brain Magnetic Resonance Imaging

International audienceThe objective of this work is to apply 3D super resolution (SR) techniques to brain magnetic resonance (MR) image restoration. Two 3D SR methods are considered following different trends: one recently proposed tensor-based approach and one inverse problem algorithm based on total variation and low rank regularization. The evaluation of their effectiveness is assessed through the segmentation of brain compartments: gray matter, white matter and cerebrospinal fluid. The two algorithms are qualitatively and quantitatively evaluated on simulated images with ground truth available and on experimental data. The originality of this work is to consider the SR methods as an initial step towards the final segmentation task. The results show the ability of both methods to overcome the loss of spatial resolution and to facilitate the segmentation of brain structures with improved accuracy compared to native low-resolution MR images. Both algorithms achieved almost equivalent results with a highly reduced computational time cost for the tensor-based approach

Variation pattern of the imprints of the middle meningeal vessels in extant human endocasts

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IRM de flux chez le singe marmouset. Traitement d'images pour la modélisation des écoulements et des interactions fluides-structures dans le cerveau

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