961 resultados para Nuclear magnetic resonance.
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The aim of this study was to determine the capability of ceMRI based signal intensity (SI) mapping to predict appropriate ICD therapies after PVTSA.
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El daño cerebral adquirido (DCA) es un problema social y sanitario grave, de magnitud creciente y de una gran complejidad diagnóstica y terapéutica. Su elevada incidencia, junto con el aumento de la supervivencia de los pacientes, una vez superada la fase aguda, lo convierten también en un problema de alta prevalencia. En concreto, según la Organización Mundial de la Salud (OMS) el DCA estará entre las 10 causas más comunes de discapacidad en el año 2020. La neurorrehabilitación permite mejorar el déficit tanto cognitivo como funcional y aumentar la autonomÃa de las personas con DCA. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma donde se puedan diseñar tratamientos que sean intensivos, personalizados, monitorizados y basados en la evidencia. Ya que son estas cuatro caracterÃsticas las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de sÃntomas y signos de la alteración cognitiva que faciliten la orientación terapéutica. Actualmente, los tratamientos de neurorrehabilitación se diseñan en base a los resultados obtenidos en una baterÃa de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La lÃnea de investigación en la que se enmarca este trabajo de investigación pretende diseñar y desarrollar un perfil cognitivo basado no sólo en el resultado obtenido en esa baterÃa de test, sino también en información teórica que engloba tanto estructuras anatómicas como relaciones funcionales e información anatómica obtenida de los estudios de imagen. De esta forma, el perfil cognitivo utilizado para diseñar los tratamientos integra información personalizada y basada en la evidencia. Las técnicas de neuroimagen representan una herramienta fundamental en la identificación de lesiones para la generación de estos perfiles cognitivos. La aproximación clásica utilizada en la identificación de lesiones consiste en delinear manualmente regiones anatómicas cerebrales. Esta aproximación presenta diversos problemas relacionados con inconsistencias de criterio entre distintos clÃnicos, reproducibilidad y tiempo. Por tanto, la automatización de este procedimiento es fundamental para asegurar una extracción objetiva de información. La delineación automática de regiones anatómicas se realiza mediante el registro tanto contra atlas como contra otros estudios de imagen de distintos sujetos. Sin embargo, los cambios patológicos asociados al DCA están siempre asociados a anormalidades de intensidad y/o cambios en la localización de las estructuras. Este hecho provoca que los algoritmos de registro tradicionales basados en intensidad no funcionen correctamente y requieran la intervención del clÃnico para seleccionar ciertos puntos (que en esta tesis hemos denominado puntos singulares). Además estos algoritmos tampoco permiten que se produzcan deformaciones grandes deslocalizadas. Hecho que también puede ocurrir ante la presencia de lesiones provocadas por un accidente cerebrovascular (ACV) o un traumatismo craneoencefálico (TCE). Esta tesis se centra en el diseño, desarrollo e implementación de una metodologÃa para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodologÃa se divide en cuatro etapas: pre-procesado, identificación de puntos singulares, registro y detección de lesiones. Los trabajos y resultados alcanzados en esta tesis son los siguientes: Pre-procesado. En esta primera etapa el objetivo es homogeneizar todos los datos de entrada con el objetivo de poder extraer conclusiones válidas de los resultados obtenidos. Esta etapa, por tanto, tiene un gran impacto en los resultados finales. Se compone de tres operaciones: eliminación del cráneo, normalización en intensidad y normalización espacial. Identificación de puntos singulares. El objetivo de esta etapa es automatizar la identificación de puntos anatómicos (puntos singulares). Esta etapa equivale a la identificación manual de puntos anatómicos por parte del clÃnico, permitiendo: identificar un mayor número de puntos lo que se traduce en mayor información; eliminar el factor asociado a la variabilidad inter-sujeto, por tanto, los resultados son reproducibles y objetivos; y elimina el tiempo invertido en el marcado manual de puntos. Este trabajo de investigación propone un algoritmo de identificación de puntos singulares (descriptor) basado en una solución multi-detector y que contiene información multi-paramétrica: espacial y asociada a la intensidad. Este algoritmo ha sido contrastado con otros algoritmos similares encontrados en el estado del arte. Registro. En esta etapa se pretenden poner en concordancia espacial dos estudios de imagen de sujetos/pacientes distintos. El algoritmo propuesto en este trabajo de investigación está basado en descriptores y su principal objetivo es el cálculo de un campo vectorial que permita introducir deformaciones deslocalizadas en la imagen (en distintas regiones de la imagen) y tan grandes como indique el vector de deformación asociado. El algoritmo propuesto ha sido comparado con otros algoritmos de registro utilizados en aplicaciones de neuroimagen que se utilizan con estudios de sujetos control. Los resultados obtenidos son prometedores y representan un nuevo contexto para la identificación automática de estructuras. Identificación de lesiones. En esta última etapa se identifican aquellas estructuras cuyas caracterÃsticas asociadas a la localización espacial y al área o volumen han sido modificadas con respecto a una situación de normalidad. Para ello se realiza un estudio estadÃstico del atlas que se vaya a utilizar y se establecen los parámetros estadÃsticos de normalidad asociados a la localización y al área. En función de las estructuras delineadas en el atlas, se podrán identificar más o menos estructuras anatómicas, siendo nuestra metodologÃa independiente del atlas seleccionado. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la identificación automática de lesiones utilizando estudios de imagen médica estructural, concretamente estudios de resonancia magnética. Basándose en estos cimientos, se han abrir nuevos campos de investigación que contribuyan a la mejora en la detección de lesiones. ABSTRACT Brain injury constitutes a serious social and health problem of increasing magnitude and of great diagnostic and therapeutic complexity. Its high incidence and survival rate, after the initial critical phases, makes it a prevalent problem that needs to be addressed. In particular, according to the World Health Organization (WHO), brain injury will be among the 10 most common causes of disability by 2020. Neurorehabilitation improves both cognitive and functional deficits and increases the autonomy of brain injury patients. The incorporation of new technologies to the neurorehabilitation tries to reach a new paradigm focused on designing intensive, personalized, monitored and evidence-based treatments. Since these four characteristics ensure the effectivity of treatments. Contrary to most medical disciplines, it is not possible to link symptoms and cognitive disorder syndromes, to assist the therapist. Currently, neurorehabilitation treatments are planned considering the results obtained from a neuropsychological assessment battery, which evaluates the functional impairment of each cognitive function (memory, attention, executive functions, etc.). The research line, on which this PhD falls under, aims to design and develop a cognitive profile based not only on the results obtained in the assessment battery, but also on theoretical information that includes both anatomical structures and functional relationships and anatomical information obtained from medical imaging studies, such as magnetic resonance. Therefore, the cognitive profile used to design these treatments integrates information personalized and evidence-based. Neuroimaging techniques represent an essential tool to identify lesions and generate this type of cognitive dysfunctional profiles. Manual delineation of brain anatomical regions is the classical approach to identify brain anatomical regions. Manual approaches present several problems related to inconsistencies across different clinicians, time and repeatability. Automated delineation is done by registering brains to one another or to a template. However, when imaging studies contain lesions, there are several intensity abnormalities and location alterations that reduce the performance of most of the registration algorithms based on intensity parameters. Thus, specialists may have to manually interact with imaging studies to select landmarks (called singular points in this PhD) or identify regions of interest. These two solutions have the same inconvenient than manual approaches, mentioned before. Moreover, these registration algorithms do not allow large and distributed deformations. This type of deformations may also appear when a stroke or a traumatic brain injury (TBI) occur. This PhD is focused on the design, development and implementation of a new methodology to automatically identify lesions in anatomical structures. This methodology integrates algorithms whose main objective is to generate objective and reproducible results. It is divided into four stages: pre-processing, singular points identification, registration and lesion detection. Pre-processing stage. In this first stage, the aim is to standardize all input data in order to be able to draw valid conclusions from the results. Therefore, this stage has a direct impact on the final results. It consists of three steps: skull-stripping, spatial and intensity normalization. Singular points identification. This stage aims to automatize the identification of anatomical points (singular points). It involves the manual identification of anatomical points by the clinician. This automatic identification allows to identify a greater number of points which results in more information; to remove the factor associated to inter-subject variability and thus, the results are reproducible and objective; and to eliminate the time spent on manual marking. This PhD proposed an algorithm to automatically identify singular points (descriptor) based on a multi-detector approach. This algorithm contains multi-parametric (spatial and intensity) information. This algorithm has been compared with other similar algorithms found on the state of the art. Registration. The goal of this stage is to put in spatial correspondence two imaging studies of different subjects/patients. The algorithm proposed in this PhD is based on descriptors. Its main objective is to compute a vector field to introduce distributed deformations (changes in different imaging regions), as large as the deformation vector indicates. The proposed algorithm has been compared with other registration algorithms used on different neuroimaging applications which are used with control subjects. The obtained results are promising and they represent a new context for the automatic identification of anatomical structures. Lesion identification. This final stage aims to identify those anatomical structures whose characteristics associated to spatial location and area or volume has been modified with respect to a normal state. A statistical study of the atlas to be used is performed to establish which are the statistical parameters associated to the normal state. The anatomical structures that may be identified depend on the selected anatomical structures identified on the atlas. The proposed methodology is independent from the selected atlas. Overall, this PhD corroborates the investigated research hypotheses regarding the automatic identification of lesions based on structural medical imaging studies (resonance magnetic studies). Based on these foundations, new research fields to improve the automatic identification of lesions in brain injury can be proposed.
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We have developed a proton magnetic resonance spectroscopy method that selectively can sample cortical gray matter and adjacent white matter in the frontal lobe. We have used this approach to study a group of patients (n = 7) infected with HIV and clinical manifestations of the AIDS dementia complex (ADC), a group of patients (n = 8) infected with HIV without any indications of ADC, and seven controls. The patients without ADC had a statistically significant increase in the ratio of myo-inositol to creatine in white matter compared with normal controls. In contrast, the group of patients with ADC had almost normal levels of myo-inositol to creatine in both gray matter and white matter and showed a statistically significant decrease in the N-acetylaspartate to creatine ratio in gray matter compared with either the normal controls or the patients without ADC. Patterns of spectral abnormalities correlated with neuropsychological measures of frontal lobe dysfunction, suggesting that the evaluation of frontal lobe metabolism by magnetic resonance spectroscopy can play a role in the early detection of ADC, in determining its progression, and in assessing responses to therapeutic interventions.
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Magnetic resonance microscopy (MRM) theoretically provides the spatial resolution and signal-to-noise ratio needed to resolve neuritic plaques, the neuropathological hallmark of Alzheimer’s disease (AD). Two previously unexplored MR contrast parameters, T2* and diffusion, are tested for plaque-specific contrast to noise. Autopsy specimens from nondemented controls (n = 3) and patients with AD (n = 5) were used. Three-dimensional T2* and diffusion MR images with voxel sizes ranging from 3 × 10−3 mm3 to 5.9 × 10−5 mm3 were acquired. After imaging, specimens were cut and stained with a microwave king silver stain to demonstrate neuritic plaques. From controls, the alveus, fimbria, pyramidal cell layer, hippocampal sulcus, and granule cell layer were detected by either T2* or diffusion contrast. These structures were used as landmarks when correlating MRMs with histological sections. At a voxel resolution of 5.9 × 10−5 mm3, neuritic plaques could be detected by T2*. The neuritic plaques emerged as black, spherical elements on T2* MRMs and could be distinguished from vessels only in cross-section when presented in three dimension. Here we provide MR images of neuritic plaques in vitro. The MRM results reported provide a new direction for applying this technology in vivo. Clearly, the ability to detect and follow the early progression of amyloid-positive brain lesions will greatly aid and simplify the many possibilities to intervene pharmacologically in AD.
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Functional MRI revealed differences between children with Attention Deficit Hyperactivity Disorder (ADHD) and healthy controls in their frontal–striatal function and its modulation by methylphenidate during response inhibition. Children performed two go/no-go tasks with and without drug. ADHD children had impaired inhibitory control on both tasks. Off-drug frontal–striatal activation during response inhibition differed between ADHD and healthy children: ADHD children had greater frontal activation on one task and reduced striatal activation on the other task. Drug effects differed between ADHD and healthy children: The drug improved response inhibition in both groups on one task and only in ADHD children on the other task. The drug modulated brain activation during response inhibition on only one task: It increased frontal activation to an equal extent in both groups. In contrast, it increased striatal activation in ADHD children but reduced it in healthy children. These results suggest that ADHD is characterized by atypical frontal–striatal function and that methylphenidate affects striatal activation differently in ADHD than in healthy children.
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Changes in metabolism and local circulation occur in the spinal cord during peripheral noxious stimulation. Evidence is presented that this stimulation also causes signal intensity alterations in functional magnetic resonance images of the spinal cord during formalin-induced pain. These results indicate the potential of functional magnetic resonance imaging in assessing noninvasively the extent and intensity of spinal cord excitation in this well characterized pain model. Therefore, the aim of this study was to establish functional magnetic resonance imaging as a noninvasive method to characterize temporal changes in the spinal cord after a single injection of 50 μl of formalin subcutaneously into the hindpaw of the anesthetized rat. This challenge produced a biphasic licking activity in the freely moving conscious animal. Images of the spinal cord were acquired within 2 min, enabling monitoring of the site and the temporal evolution of the signal changes during the development of formalin-induced hyperalgesia without the need of any surgical procedure. The time course of changes in the spinal cord functional image in the isoflurane-anesthetized animal was similar to that obtained from behavioral experiments. Also, comparable physiological data, control experiments, and the inhibition of a response through application of the local anesthetic agent lidocaine indicate that the signal changes observed after formalin injection were specifically related to excitability changes in the relevant segments of the lumbar spinal cord. This approach could be useful to characterize different models of pain and hyperalgesia and, more importantly, to evaluate effects of analgesic drugs.
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Demyelination is a common pathological finding in human neurological diseases and frequently persists as a result of failure of endogenous repair. Transplanted oligodendrocytes and their precursor cells can (re)myelinate axons, raising the possibility of therapeutic intervention. The migratory capacity of transplanted cells is of key importance in determining the extent of (re)myelination and can, at present, be evaluated only by using invasive and irreversible procedures. We have exploited the transferrin receptor as an efficient intracellular delivery device for magnetic nanoparticles, and transplanted tagged oligodendrocyte progenitor cells into the spinal cord of myelin-deficient rats. Cell migration could be easily detected by using three-dimensional magnetic resonance microscopy, with a close correlation between the areas of contrast enhancement and the achieved extent of myelination. The present results demonstrate that magnetic resonance tracking of transplanted oligodendrocyte progenitors is feasible; this technique has the potential to be easily extended to other neurotransplantation studies involving different precursor cell types.
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Functional neuroimaging studies in human subjects using positron emission tomography or functional magnetic resonance imaging (fMRI) are typically conducted by collecting data over extended time periods that contain many similar trials of a task. Here methods for acquiring fMRI data from single trials of a cognitive task are reported. In experiment one, whole brain fMRI was used to reliably detect single-trial responses in a prefrontal region within single subjects. In experiment two, higher temporal sampling of a more limited spatial field was used to measure temporal offsets between regions. Activation maps produced solely from the single-trial data were comparable to those produced from blocked runs. These findings suggest that single-trial paradigms will be able to exploit the high temporal resolution of fMRI. Such paradigms will provide experimental flexibility and time-resolved data for individual brain regions on a trial-by-trial basis.
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Subcortical nuclei in the thalamus, which play an important role in many functions of the human brain, provide challenging targets for functional mapping with neuroimaging techniques because of their small sizes and deep locations. In this study, we explore the capability of high-resolution functional magnetic resonance imaging at 4 Tesla for mapping the retinotopic organization in the lateral geniculate nucleus (LGN). Our results show that the hemifield visual stimulation only activates LGN in the contralateral hemisphere, and the lower-field and upper-field visual stimulations activate the superior and inferior portion of LGN, respectively. These results reveal a similar retinotopic organization between the human and nonhuman primate LGN and between LGN and the primary visual cortex. We conclude that high-resolution functional magnetic resonance imaging is capable of functional mapping of suborganizations in small nuclei together with cortical activation. This will have an impact for studying the thalamocortical networks in the human brain.
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Two different attentional networks have been associated with visuospatial attention and conflict resolution. In most situations either one of the two networks is active or both are increased in activity together. By using functional magnetic resonance imaging and a flanker task, we show conditions in which one network (anterior attention system) is increased in activity whereas the other (visuospatial attention system) is reduced, showing that attentional conflict and selection are separate aspects of attention. Further, we distinguish between neural systems involved in different forms of conflict. Specifically, we dissociate patterns of activity in the basal ganglia and insula cortex during simple violations in expectancies (i.e., sudden changes in the frequency of an event) from patterns of activity in the anterior attention system specifically correlated with response conflict as evidenced by longer response latencies and more errors. These data provide a systems-level approach in understanding integrated attentional networks.
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Accurate and automated methods for measuring the thickness of human cerebral cortex could provide powerful tools for diagnosing and studying a variety of neurodegenerative and psychiatric disorders. Manual methods for estimating cortical thickness from neuroimaging data are labor intensive, requiring several days of effort by a trained anatomist. Furthermore, the highly folded nature of the cortex is problematic for manual techniques, frequently resulting in measurement errors in regions in which the cortical surface is not perpendicular to any of the cardinal axes. As a consequence, it has been impractical to obtain accurate thickness estimates for the entire cortex in individual subjects, or group statistics for patient or control populations. Here, we present an automated method for accurately measuring the thickness of the cerebral cortex across the entire brain and for generating cross-subject statistics in a coordinate system based on cortical anatomy. The intersubject standard deviation of the thickness measures is shown to be less than 0.5 mm, implying the ability to detect focal atrophy in small populations or even individual subjects. The reliability and accuracy of this new method are assessed by within-subject test–retest studies, as well as by comparison of cross-subject regional thickness measures with published values.
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Laser-polarized gases (3He and 129Xe) are currently being used in magnetic resonance imaging as strong signal sources that can be safely introduced into the lung. Recently, researchers have been investigating other tissues using 129Xe. These studies use xenon dissolved in a carrier such as lipid vesicles or blood. Since helium is much less soluble than xenon in these materials, 3He has been used exclusively for imaging air spaces. However, considering that the signal of 3He is more than 10 times greater than that of 129Xe for presently attainable polarization levels, this work has focused on generating a method to introduce 3He into the vascular system. We addressed the low solubility issue by producing suspensions of 3He microbubbles. Here, we provide the first vascular images obtained with laser-polarized 3He. The potential increase in signal and absence of background should allow this technique to produce high-resolution angiographic images. In addition, quantitative measurements of blood flow velocity and tissue perfusion will be feasible.
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Considerable evidence exists to support the hypothesis that the hippocampus and related medial temporal lobe structures are crucial for the encoding and storage of information in long-term memory. Few human imaging studies, however, have successfully shown signal intensity changes in these areas during encoding or retrieval. Using functional magnetic resonance imaging (fMRI), we studied normal human subjects while they performed a novel picture encoding task. High-speed echo-planar imaging techniques evaluated fMRI signal changes throughout the brain. During the encoding of novel pictures, statistically significant increases in fMRI signal were observed bilaterally in the posterior hippocampal formation and parahippocampal gyrus and in the lingual and fusiform gyri. To our knowledge, this experiment is the first fMRI study to show robust signal changes in the human hippocampal region. It also provides evidence that the encoding of novel, complex pictures depends upon an interaction between ventral cortical regions, specialized for object vision, and the hippocampal formation and parahippocampal gyrus, specialized for long-term memory.