Cartilage damage in femoroacetabular impingement (FAI): preliminary results on comparison of standard diagnostic vs delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC)

OBJECTIVES: To study the three-dimensional (3D) T1 patterns in different types of femoroacetabular impingement (FAI) by utilizing delayed gadolinium-enhanced magnetic resonance imaging (MRI) of cartilage (dGEMRIC) and subsequent 3D T1 mapping. We used standard grading of OA by Tonnis grade on standard radiographs and morphological grading of cartilage in MRI for comparative analysis. METHODS: dGEMRIC was obtained from ten asymptomatic young-adult volunteers and 26 symptomatic FAI patients. MRI included the routine hip protocol and a dual-flip angle (FA) 3D gradient echo (GRE) sequence utilizing inline T1 measurement. Cartilage was morphologically classified from the radial images based on the extent of degeneration as: no degeneration, degeneration zone measuring <0.75 cm from the rim, >0.75 cm, or total loss. T1 findings were evaluated and correlated. RESULTS: All FAI types revealed remarkably lower T1 mean values in comparison to asymptomatic volunteers in all regions of interest. Distribution of the T1 dGEMRIC values was in accordance with the specific FAI damage pattern. In cam-types (n=6) there was a significant drop (P<0.05) of T1 in the anterior to superior location. In pincer-types (n=7), there was a generalized circumferential decrease noted. High inter-observer (intra-observer) reliability was noted for T1 assessment using intra-class correlation (ICC):intra-class coefficient=0.89 (0.95). CONCLUSIONS: We conclude that a pattern of zonal T1 variation does seem to exist that is unique for different sub-groups of FAI. The FA GRE approach to perform 3D T1 mapping has a promising role for further studies of standard MRI and dGEMRIC in the hip joint.

Virtopsy: forensic traumatology of the subcutaneous fatty tissue; multislice computed tomography (MSCT) and magnetic resonance imaging (MRI) as diagnostic tools

Traumatic lesions of the subcutaneous fatty tissue provide important clues for forensic reconstruction. The interpretation of these patterns requires a precise description and recording of the position and extent of each lesion. During conventional autopsy, this evaluation is performed by dissecting the skin and subcutaneous tissues in successive layers. In this way, depending on the force and type of impact (right angle or tangent), several morphologically distinct stages of fatty tissue damage can be differentiated: perilobular hemorrhage (I), contusion (II), or disintegration (III) of the fat lobuli, and disintegration with development of a subcutaneous cavity (IV). In examples of virtopsy cases showing blunt trauma to the skin and fatty tissue, we analyzed whether these lesions can also be recorded and classified using multislice computed tomography (MSCT) and magnetic resonance imaging (MRI). MSCT has proven to be a valuable screening method to detect the lesions, but MRI is necessary in order to properly differentiate and classify the grade of damage. These noninvasive radiological diagnostic tools can be further developed to play an important role in forensic examinations, in particular when it comes to evaluating living trauma victims.

Commissioning an Anthropomorphic Spine and Lung Phantom for Remote Dose Verification of Institutions Participating in RTOG 0631

The RPC developed a new phantom to ensure comparable and consistent radiation administration in spinal radiosurgery clinical trials. This study assessed the phantom’s dosimetric and anatomic utility. The ‘spine phantom’ is a water filled thorax with anatomy encountered in spinal radiosurgery: target volume, vertebral column, spinal canal, esophagus, heart, and lungs. The dose to the target volume was measured with axial and sagittal planes of radiochromic film and thermoluminescent dosimeters (TLD). The dose distributions were measured with the radiochromic film calibrated to the absolute dose measured by the TLD. Four irradiations were administered: a four angle box plan, a seven angle conformal plan, a seven angle IMRT plan, and a nine angle IMRT plan (denoted as IMRT plan #1 and plan #2, respectively). In each plan, at least 95% of the defined tumor volume received 8 Gy. For each irradiation the planned and administered dose distributions were registered via pinpricks, and compared using point dose measurements, dose profiles, isodose distributions, and gamma analyses. Based on previous experience at the RPC, a gamma analysis was considering passing if greater than 95% of pixels passed the criteria of 5% dose difference and 3 mm distance-to-agreement. Each irradiation showed acceptable agreement in the qualitative assessments and exceeded the 95% passing rate at the 5% / 3 mm criteria, except IMRT plan #1, which was determined to have been poorly localized during treatment administration. The measured and planned dose distributions demonstrated acceptable agreement at the 5% / 3 mm criteria, and the spine phantom was determined to be a useful tool for the remote assessment of an institution’s treatment planning and dose delivery regimen.

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

Noninvasive Urinary Metabolomic Profiling Identifies Diagnostic and Prognostic Markers in Lung Cancer

Lung cancer remains the most common cause of cancer deaths worldwide, yet there is currently a lack of diagnostic noninvasive biomarkers that could guide treatment decisions. Small molecules (<1,500 Da) were measured in urine collected from 469 patients with lung cancer and 536 population controls using unbiased liquid chromatography/mass spectrometry. Clinical putative diagnostic and prognostic biomarkers were validated by quantitation and normalized to creatinine levels at two different time points and further confirmed in an independent sample set, which comprises 80 cases and 78 population controls, with similar demographic and clinical characteristics when compared with the training set. Creatine riboside (IUPAC name: 2-{2-[(2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)-oxolan-2-yl]-1-methylcarbamimidamido}acetic acid), a novel molecule identified in this study, and N-acetylneuraminic acid (NANA) were each significantly (P < 0.00001) elevated in non-small cell lung cancer and associated with worse prognosis [HR = 1.81 (P = 0.0002), and 1.54 (P = 0.025), respectively]. Creatine riboside was the strongest classifier of lung cancer status in all and stage I-II cases, important for early detection, and also associated with worse prognosis in stage I-II lung cancer (HR = 1.71, P = 0.048). All measurements were highly reproducible with intraclass correlation coefficients ranging from 0.82 to 0.99. Both metabolites were significantly (P < 0.03) enriched in tumor tissue compared with adjacent nontumor tissue (N = 48), thus revealing their direct association with tumor metabolism. Creatine riboside and NANA may be robust urinary clinical metabolomic markers that are elevated in tumor tissue and associated with early lung cancer diagnosis and worse prognosis.

Lung Volume Reduction in Pulmonary Emphysema from the Radiologist's Perspective

Pulmonary emphysema causes decrease in lung function due to irreversible dilatation of intrapulmonary air spaces, which is linked to high morbidity and mortality. Lung volume reduction (LVR) is an invasive therapeutical option for pulmonary emphysema in order to improve ventilation mechanics. LVR can be carried out by lung resection surgery or different minimally invasive endoscopical procedures. All LVR-options require mandatory preinterventional evaluation to detect hyperinflated dysfunctional lung areas as target structures for treatment. Quantitative computed tomography can determine the volume percentage of emphysematous lung and its topographical distribution based on the lung's radiodensity. Modern techniques allow for lobebased quantification that facilitates treatment planning. Clinical tests still play the most important role in post-interventional therapy monitoring, but CT is crucial in the detection of postoperative complications and foreshadows the method's high potential in sophisticated experimental studies. Within the last ten years, LVR with endobronchial valves has become an extensively researched minimally-invasive treatment option. However, this therapy is considerably complicated by the frequent occurrence of functional interlobar shunts. The presence of "collateral ventilation" has to be ruled out prior to valve implantations, as the presence of these extraanatomical connections between different lobes may jeopardize the success of therapy. Recent experimental studies evaluated the automatic detection of incomplete lobar fissures from CT scans, because they are considered to be a predictor for the existence of shunts. To date, these methods are yet to show acceptable results. KEY POINTS Today, surgical and various minimal invasive methods of lung volume reduction are in use. Radiological and nuclear medical examinations are helpful in the evaluation of an appropriate lung area. Imaging can detect periinterventional complications. Reduction of lung volume has not yet been conclusively proven to be effective and is a therapeutical option with little scientific evidence.

Mechanisms of apoptosis in bleomycin-induced lung injury: Implications for pulmonary fibrosis

Chronic inflammation leading to pulmonary fibrosis develops in response to environmental pollutants, radiotherapy, or certain cancer chemotherapeutic agents. Studies have shown that several cell types accumulate during the inflammatory process, but little information is known about what actually triggers and stimulates persistent inflammation culminating in fibrosis. As a first step in defining the events that precipitate inflammation in the lung, the biological mechanism(s) mediating apoptosis and cellular targets must be identified. The purpose of this study was to determine the molecular mechanism(s) of bleomycin-induced apoptosis in the lung using mice deficient in genes that we hypothesized to play a key role in apoptosis. Intratracheal administration of bleomycin led to caspase-mediated DNA fragmentation characteristic of apoptosis. The effects of bleomycin were associated with translocation of p53 from the cytosol to the nucleus only in alveolar macrophages that had been exposed to the drug in vivo, suggesting that the lung microenvironment regulated p53 activation. Experiments with a thiol antioxidant (N-acetylcysteine) in vivo and nitric oxide donors in vitro confirmed that reactive oxygen species were required for p53 activation. A specific role for NO was demonstrated in experiments with iNOS−/− macrophages, which failed to demonstrate nuclear p53 localization after in vivo bleomycin exposure. Strikingly, rates of bleomycin-induced apoptosis were at least two-fold higher in iNOS−/− and p53−/− C57BL/6 mice compared to wild-type controls. Laser Scanning Cytometry (LSC) analysis revealed that bleomycin exposure resulted in a 2-fold induction in Fas and FasL expression in wild-type mice but not iNOS−/− or p53−/− mice. Experiments using gld mice confirmed that the Fas/FasL pathway was the primary mechanism of bleomycin-induced apoptosis in the lung. LSC-mediated analysis indicated that bleomycin exposure resulted in a 2-fold induction in Bax expression in iNOS−/− and P53−/− mice but not wild-type mice. Furthermore, LSC analysis revealed that bleomycin exposure induced a 3-fold increase in thrombospondin expression in wild-type mice. However, thrombospondin was not expressed in either the iNOS−/− or p53−/− mice, implicating a thrombospondin-mediated apoptotic cell clearance mechanism in the lung. Together, these results demonstrate that iNOS and p53 positively regulate apoptosis via the Fas/FasL pathway and mediate a novel apoptosis-suppressing pathway in the lung. ^

Targeting dysregulated nuclear proteins androgen receptor and enhancer of zeste homolog 2: Clinical implication and mechanism underline

Cancer is the most devastating disease that has tremendous impacts on public health. Many efforts have been devoted to fighting cancer through either translational or basic researches for years. Nowadays, it emerges the importance to converge these two research directions and complement to each other for battling with cancer. Thus, our study aims at both translational and basic research directions. The first goal of our study is focus on translational research to search for new agents targeting prevention and therapy of advanced prostate cancer. Hormone refractory prostate cancer is incurable and lethal. Androgen receptor (AR) mediates androgen's effect not only on the tumor initiation but also plays the major role in the relapse transition of prostate cancer. Here we demonstrate that emodin, a natural compound, can directly target AR to suppress prostate cancer cell growth in vitro and prolong the survival of C3(1)/SV40 transgenic mice in vivo. Emodin treatment resulted in repressing androgen-dependent transactivation of AR by inhibiting AR nuclear translocation. Emodin decreased the association of AR and heat shock protein 90 and increased the association of AR and MDM2, which in turn, induces AR degradation through a proteasome-mediated pathway in a ligand independent manner. Our work indicates a new mechanism for the emodin-mediated anticancer effect and justifies further investigation of emodin as a therapeutic and preventive agent for prostate cancer. The second goal of our study is try to elucidate the fundamental tumor biology of cancer progression then provide the rationale to develop more efficient therapeutic strategy. Enhancer of zeste homologue 2 (EZH2) plays an important role in many biological processes through its intrinsic methyltransferase activity to trimethylate lysine 27 in histone H3. Although overexpression of EZH2 has been shown to be involved in cancer progression, the detailed mechanisms are elusive. Here, we show that Akt phosphorylates EZH2 at serine 21 and suppresses its methyltransferase activity by impeding the binding to its substrate histone H3, resulting in a decrease of lysine 27 trimethylation and derepression of silenced genes, thus promotes cell proliferation and tumorigenicity. Our results also show that histone methylation is not permanent but regulated in a dynamic manner and that the Akt signaling pathway is involved in the regulation of this epigenetic modification through phosphorylation of EZH2, thus contributing to oncogenic processes. ^

Transcriptional regulation of lung tumor suppressor GPRC5A in malignant and normal cells

Chronic exposure of the airways to cigarette smoke induces inflammatory response and genomic instability that play important roles in lung cancer development. Nuclear factor kappa B (NF-κB), the major intracellular mediator of inflammatory signals, is frequently activated in preneoplastic and malignant lung lesions. ^ Previously, we had shown that a lung tumor suppressor GPRC5A is frequently repressed in human non-small cell lung cancers (NSCLC) cells and lung tumor specimens. Recently, other groups have shown that human GPRC5A transcript levels are higher in bronchial samples of former than of current smokers. These results suggested that smoking represses GPRC5A expression and thus promotes the occurrence of lung cancer. We hypothesized that cigarette smoking or associated inflammatory response repressed GPRC5A expression through NF-κB signaling. ^ To determine the effect of inflammation, we examined GPRC5A protein expression in several lung cell lines following by TNF-α treatment. TNF-α significantly suppressed GPRC5A expression in normal small airway epithelial cells (SAEC) as well as in Calu-1 cells. Real-time PCR analysis indicated that TNF-α inhibits GPRC5A expression at the transcriptional level. NF-κB, the major downstream effectors of TNF-α signaling, mediates TNF-α-induced repression of GPRC5A because over-expression of NF-κB suppressed GPRC5A. To determine the region in the GPRC5A promoter through which NF-κB acts, we examined the ability of TNF-α to inhibit a series of reporter constructs with different deletions of GPRC5A promoter. The luciferase assay showed that the potential NF-κB binding sites containing region are irresponsible for TNF-α-induced suppression. Further analysis using constructs with different deletions in p65 revealed that NF-κB-mediated repression of GPRC5A is transcription-independent. Co-immunoprecipitation assays revealed that NF-κB could form a complex with RAR/RXR heterodimer. Moreover, the inhibitory effect of NF-κB has been found to be proportional to NF-κB/RAR ratio in luciferase assay. Finally, Chromatin IP demonstrated that NF-κB/p65 bound to GPRC5A promoter as well as RAR/RXR and suppressed transcription. Taken together, we propose that inflammation-induced NF-κB activation disrupts the RA signaling and suppresses GPRC5A expression and thus contributes to the oncogenesis of lung cancer. Our studies shed new light on the pathogenesis of lung cancer and potentially provide novel interventions for preventing and treating this disease. ^

HR Nuclear Magnetic Resonance Spectroscopy for Authentication of Olive Oil Quality

The present work is a preliminary study to settle the optimum experimental conditions and data processing for accomplishing the strategies established by the Action Plan for the EU olive oil sector. The objectives of the work were: a) to monitor the evolution of extra virgin olive oil exposed to indirect solar light in transparent glass bottles during four months; b) to identify spectral differences between edible and lampant virgin olive oil by applying high resolution Nuclear Magnetic Resonance (HR-NMR) Spectroscopy. Pr esent study could contribute to determine the date of minimum storage, their optimum conditions, and to properly characterize olive oil.

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.

A Cross-Polarization, Magic-Angle-Spinning, 13C-Nuclear-Magnetic-Resonance Study of Polysaccharides in Sugar Beet Cell Walls1

Solid-state nuclear magnetic resonance relaxation experiments were used to study the rigidity and spatial proximity of polymers in sugar beet (Beta vulgaris) cell walls. Proton T1ρ decay and cross-polarization patterns were consistent with the presence of rigid, crystalline cellulose microfibrils with a diameter of approximately 3 nm, mobile pectic galacturonans, and highly mobile arabinans. A direct-polarization, magic-angle-spinning spectrum recorded under conditions adapted to mobile polymers showed only the arabinans, which had a conformation similar to that of beet arabinans in solution. These cell walls contained very small amounts of hemicellulosic polymers such as xyloglucan, xylan, and mannan, and no arabinan or galacturonan fraction closely associated with cellulose microfibrils, as would be expected of hemicelluloses. Cellulose microfibrils in the beet cell walls were stable in the absence of any polysaccharide coating.