Automated detection and classification of brain injury lesions on structural magnetic resonance imaging

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 autonomía 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 características las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de síntomas 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 batería de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La línea 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 batería 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 clínicos, 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 clínico 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 metodología para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodología 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 clínico, 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 características 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 estadístico del atlas que se vaya a utilizar y se establecen los parámetros estadísticos 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 metodología 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.

Structure and function in rhodopsin: Topology of the C-terminal polypeptide chain in relation to the cytoplasmic loops*

Cysteine mutagenesis and site-directed spin labeling in the C-terminal region of rhodopsin have been used to probe the local structure and proximity of that region to the cytoplasmic loops. Each of the native amino acids in the sequence T335–T340 was replaced with Cys, one at a time. The sulfhydryl groups of all mutants reacted rapidly with the sulfhydryl reagent 4,4′-dithiodipyridine, which indicated a high degree of solvent accessibility. Furthermore, to probe the proximity relationships, a series of double Cys mutants was constructed. One Cys in all sets was at position 338 and the other was at a position in the sequence S240–V250 in the EF interhelical loop, at position 65 in the AB interhelical loop, or at position 140 in the CD interhelical loop. In the dark state, no significant disulfide formation was observed between C338 and C65 or C140 under the conditions used, whereas a relatively rapid disulfide formation was observed between C338 and C242 or C245. Spin labels in the double Cys mutants showed the strongest magnetic interactions between the nitroxides attached to C338 and C245 or C246. Light activation of the double mutant T242C/S338C resulted in slower disulfide formation, whereas interactions between nitroxides at C338 and C245 or C246 decreased. These results suggest the proximity of the C-terminal residue C338 to residues located on the outer face of a cytoplasmic helical extension of the F helix with an apparent increase of distance upon photoactivation.

Field and laboratory performance evaluation of a field-blended rubber asphalt.

ALICE is one of four major experiments of particle accelerator LHC installed in the European laboratory CERN. The management committee of the LHC accelerator has just approved a program update for this experiment. Among the upgrades planned for the coming years of the ALICE experiment is to improve the resolution and tracking efficiency maintaining the excellent particles identification ability, and to increase the read-out event rate to 100 KHz. In order to achieve this, it is necessary to update the Time Projection Chamber detector (TPC) and Muon tracking (MCH) detector modifying the read-out electronics, which is not suitable for this migration. To overcome this limitation the design, fabrication and experimental test of new ASIC named SAMPA has been proposed . This ASIC will support both positive and negative polarities, with 32 channels per chip and continuous data readout with smaller power consumption than the previous versions. This work aims to design, fabrication and experimental test of a readout front-end in 130nm CMOS technology with configurable polarity (positive/negative), peaking time and sensitivity. The new SAMPA ASIC can be used in both chambers (TPC and MCH). The proposed front-end is composed of a Charge Sensitive Amplifier (CSA) and a Semi-Gaussian shaper. In order to obtain an ASIC integrating 32 channels per chip, the design of the proposed front-end requires small area and low power consumption, but at the same time requires low noise. In this sense, a new Noise and PSRR (Power Supply Rejection Ratio) improvement technique for the CSA design without power and area impact is proposed in this work. The analysis and equations of the proposed circuit are presented which were verified by electrical simulations and experimental test of a produced chip with 5 channels of the designed front-end. The measured equivalent noise charge was <550e for 30mV/fC of sensitivity at a input capacitance of 18.5pF. The total core area of the front-end was 2300?m × 150?m, and the measured total power consumption was 9.1mW per channel.

Noncollinear magnetic phases and edge states in graphene quantum Hall bars

Application of a perpendicular magnetic field to charge neutral graphene is expected to result in a variety of broken symmetry phases, including antiferromagnetic, canted, and ferromagnetic. All these phases open a gap in bulk but have very different edge states and noncollinear spin order, recently confirmed experimentally. Here we provide an integrated description of both edge and bulk for the various magnetic phases of graphene Hall bars making use of a noncollinear mean field Hubbard model. Our calculations show that, at the edges, the three types of magnetic order are either enhanced (zigzag) or suppressed (armchair). Interestingly, we find that preformed local moments in zigzag edges interact with the quantum spin Hall like edge states of the ferromagnetic phase and can induce backscattering.

Effect of Cyclic Topology on Charge-Transfer Properties of Organic Molecular Semiconductors: The Case of Cycloparaphenylene Molecules

We have studied the role played by cyclic topology on charge-transfer properties of recently synthesized π -conjugated molecules, namely the set of [n]cycloparaphenylene compounds, with n the number of phenylene rings forming the curved nanoring. We estimate the charge-transfer rates for holes and electrons migration within the array of molecules in their crystalline state. The theoretical calculations suggest that increasing the size of the system would help to obtain higher hole and electron charge-transfer rates and that these materials might show an ambipolar behavior in real samples, independently of the different mode of packing followed by the [6]cycloparaphenylene and [12]cycloparaphenylene cases studied.

(Table 1) Magnetic viscosity coefficient, VRM and NRM of DSDP Hole 6-57

THE magnetic properties of the basalts which form layer 2 of the oceanic lithosphere are important because of their relevance to the hypothesis (Vine and Matthews, 1963, doi:10.1038/199947a0) of seafloor spreading. Most studies of these magnetic properties have been carried out on basalts obtained from dredge hauls taken predominantly from ocean ridge systems and fracture zones. These constitute special areas of the oceanic crust where the sediment cover is negligible. It is of interest to compare the magnetic properties of the dredged basalts with samples recovered from holes drilled through the overlying sediments into the basaltic layer at places distant from ridge axes. Samples obtained from the abandoned Mohole project and, more recently, from the Deep Sea Drilling Project (DSDP) possessed magnetic properties similar to those of dredged basalts (Cox and Doell, 1962, doi:10.1029/JZ067i010p03997; Lowrie et al., 1973, doi:10.1016/0012-821X(73)90198-2). Here I describe highly unstable magnetic characteristics found in basalts from DSDP hole 57.

(Table 1) Magnetic properties and Curie temperatures of basalts from DSDP Leg 65 holes

During DSDP Leg 65, we achieved significant basement penetration at three sites (482, 483, and 485) in the mouth of the Gulf of California (Lewis and Robinson, 1983, doi:10.2973/dsdp.proc.65.1983). Since these holes were all drilled into extremely young crust near the crest of the East Pacific Rise, the rocks we recovered present an unusual opportunity to study the magnetic properties of submarine basalts before alteration has become pervasive. To take advantage of this opportunity and to complement the paleomagnetic studies conducted on these basalts by Day (1983, doi:10.2973/dsdp.proc.65.138.1983), we have studied, in the same samples, the following properties: saturation magnetization (Js); intensity and stability of isothermal remanent magnetization (IRM); hysteresis parameters, such as the coercive force (Hc), the remanent coercive force (HRC), and the ratio of saturation remanence (JRS) to saturation magnetization; susceptibility (x); and Curie temperature (Tc). In this chapter we will discuss the results of these studies in conjunction with the opaque mineralogy of the samples.

Magnetic Devices and Techniques for the Study of Viscoelasticity of Biomaterials and Myocardial Forces

Thesis (Ph.D.)--University of Washington, 2016-06

A novel phantom and method for comprehensive 3-dimensional measurement and correction of geometric distortion in magnetic resonance imaging

A phantom that can be used for mapping geometric distortion in magnetic resonance imaging (MRI) is described. This phantom provides an array of densely distributed control points in three-dimensional (3D) space. These points form the basis of a comprehensive measurement method to correct for geometric distortion in MR images arising principally from gradient field non-linearity and magnet field inhomogeneity. The phantom was designed based on the concept that a point in space can be defined using three orthogonal planes. This novel design approach allows for as many control points as desired. Employing this novel design, a highly accurate method has been developed that enables the positions of the control points to be measured to sub-voxel accuracy. The phantom described in this paper was constructed to fit into a body coil of a MRI scanner, (external dimensions of the phantom were: 310 mm x 310 mm x 310 mm), and it contained 10,830 control points. With this phantom, the mean errors in the measured coordinates of the control points were on the order of 0.1 mm or less, which were less than one tenth of the voxel's dimensions of the phantom image. The calculated three-dimensional distortion map, i.e., the differences between the image positions and true positions of the control points, can then be used to compensate for geometric distortion for a full image restoration. It is anticipated that this novel method will have an impact on the applicability of MRI in both clinical and research settings. especially in areas where geometric accuracy is highly required, such as in MR neuro-imaging. (C) 2004 Elsevier Inc. All rights reserved.

Magnetic properties and Spin dynamics in magnetic Molecular Rings

Molecular nanomagnets are spin clusters whose topology and magnetic interactions can be modulated at the level of the chemical synthesis. They are formed by a small number of transition metal ions coupled by the Heisenberg's exchange interactions. Each cluster is magnetically isolated from its neighbors by organic ligands, making each unit not interacting with the others. Therefore, we can investigate the magnetic properties of an isolated molecular nanomagnet by bulk measurements. The present thesis has been mostly devoted to the experimental investigation of the magnetic properties and spin dynamics of different classes of antiferromagnetic (AF) molecular rings. This study has been exploiting various techniques of investigations, such as Nuclear Magnetic Resonance (NMR), muon spin relaxation (muSR) and SQUiD magnetometry. We investigate the magnetic properties and the phonon-induced relaxation dynamics of the first regular Cr9 antiferromagnetic (AF) ring, which represents a prototype frustrated AF ring. The magnetically-open AF rings like Cr8Cd are model systems for the study of the microscopic magnetic behaviour of finite AF Heisenberg chains. In this type of system the different magnetic behaviour depends length and on the parity of the chain (odd or even). In order to study the local spin densities on the Cr sites, the Cr-NMR spectra was collected at low temperature. The experimental result confirm the theoretical predictions for the spin configuration. Finally, the study of Dy6, the first rare-earth based ring that has been ever synthesized, has been performed by AC-SQuID and muSR measurements. We found that the dynamics is characterized by more than one characteristic correlation time, whose values depend strongly on the applied field.

The influence of age on the pattern and flash visual evoked field

We have investigated the effect of ageing on the visual system using the relatively new technique of magentoencephalography (MEG). This technique measures the magnetic signals produced by the visual system using a SQUID magnetometer. The magnetic visual evoked field (VEF) was measured over the occipital cortex to pattern and flash stimuli in 86 normal subjects aged 15 - 86 years. Factors that influenced subject defocussing or defixating the stimulus or selective attention were controlled as far as possible. The latency of the major positive component to the pattern reversal stimulus (P100M) increased with age particularly after the age of 55 years while the amplitude of the P100M decreased over the life span. The latency of the major flash component (P2M) increased much more slowly with age, while its amplitude decreased in only a proportion of elderly subjects. Changes in the P100M with age may reflect senile changes in the eye and optic nerve, e.g. senile miosis or degenerative changes in the retina. The P2M may be more susceptible to senile changes in the retina. The data suggest that the spatial frequency channels deteriorate more rapidly with age than the luminance channels and that MEG may be an effective method of studying ageing in the visual system.

Topography of the visual evoked magnetic response and hemispherical specialization

The visual evoked magnetic response CIIm component to a pattern onset stimulus presented half field produced a consistent scalp topography in 15 normal subjects. The major response was seen over the contralateral hemisphere, suggesting a dipole with current flowing away from the medial surface of the brain. Full field responses were more unpredictable. The reponses of five subjects were studied to the onset of a full, left half and right half checkerboard stimuli of 38 x 27 min arc checks appearing for 200 ms. In two subjects the full field CIIm topography was consistent with that of the mathematical summation of their relevant half field distribution. The remaining subjects had unpredictable full field topographies, showing little or no relationship to their half or summated half fields. In each of these subjects, a distribution matching that of the summated half field CIIm distribution appears at an earlier latency than that of the predominant full field waveform peak. By examining the topography of the full and half field responses at 5 ms intervals along the waveform for one such subject, the CIIm topography of the right hemisphere develops 10 ms before that of the left hemisphere, and is replaced by the following CIIIm component 20 ms earlier. Hence, the large peak seen in full field results from a combination of the CIIm component of the left hemisphere plus that of the CIIIm from the right. The earlier peak results from the CIIm generated in both hemispheres, at a latency where both show similar amplitudes. As the relative amplitudes of these two peaks alter with check and field size, topographic studies would be required for accurate CIIm identification. In addition. the CIIm-CIIIm complex lasts for 80 ms in the right hemisphere and 135 ms in the left, suggesting hemispherical apecialization in the visual processing of the pattern onset response.