Automated detection of depression from brain structural magnetic resonance imaging (sMRI) scans

 Automated sMRI-based depression detection system is developed whose components include acquisition and preprocessing, feature extraction, feature selection, and classification. The core focus of the research is on the establishment of a new feature selection algorithm that quantifies the most relevant brain volumetric feature for depression detection at an individual level

The application of voxel-based methods to magnetic resonance imaging in the study of psychiatric disorder.

While there are a number of psychiatric disorders as classified by the major international coding systems, however, the application of modem neuroimaging methods has only been utilised on a limited basis with some disorders receiving more research attention than others. Consequently, psychiatric phenotypes that have been relatively understudied are investigated further in this thesis. These disorders correspond to psychiatric disorder in: 22ql 1 deletion syndrome, temporal lobe epilepsy, antisocial personality disorder and Asperger syndrome. Subjects with each of these diagnoses were recruited and then compared to healthy matched controls using the application of novel whole-brain voxel-based analyses to their magnetic resonance imaging data whereby white matter integrity and/or brain tissue volume was assessed in each experimental study of this thesis. In Study 1, young people with 22ql 1 deletion syndrome were found to have significant differences in both white matter microstructure and volume. Additionally, there was preliminary evidence that within 22ql 1 deletion syndrome, some regional differences in fractional anisotropy were associated with allelic variation in COMT and with schizotypy. In Study 2, while significant grey and white matter volume deficits were found in temporal lobe epilepsy with comorbid psychosis, these abnormalities encompassed not only the medial temporal lobe structures but also extended to lateral temporal and extratemporal regions whereby some of the deficits also overlapped with those found in schizophrenia. In Study 3, reduced fractional anisotropy was found in antisocial personality disorder and psychopathy in tracts of interhemispheric, posterior brain and frontal lobe networks. Additionally, fractional anisotropy deficits in the frontal lobe demonstrated a significant negative correlation with psychopathy measures. Finally, in Study 4, adults with Asperger syndrome were specifically recruited and found to not only demonstrate impairments in white matter microstructural integrity in regions relevant to social skills and behaviour but also in more widespread white matter networks

Strukturální podklady kognitivního deficitu v zobrazování magnetické rezonance.

Předkládaná dizertační práce se ve své hlavní části zabývá možnostmi detekce strukturálních a difuzních změn v MR zobrazení u pacientů s kognitivním deficitem. V širším kontextu je nejprve zmíněn podklad klinických změn a nálezů při neurozobrazení u pacientů s demencí, a to se zvláštním zaměřením na Alzheimerovu chorobu (ACh) a její diferenciální diagnostiku. Druhá část práce obsahuje čtyři experimentální studie v rámci našeho výzkumu. Hlavním cílem prvních dvou studií bylo získání strukturální a mikrostrukturální informace o neurodegenerativních procesech charakteristických pro ACh - na globální i regionální úrovni. Pro tento účel bylo použito několik komplementárních přístupů se zaměřením především na evaluaci šedé, a následně i bílé hmoty mozku. V následujících částech jsme se zaměřili na popis kontextu mikrostrukturálních změn bílé hmoty u normotenzního hydrocefalu (NPH) a charakteristických vzorců dezintegrace bílé hmoty u epilepsií temporálního laloku (TLE). Nejdůležitějším závěrem, který lze vyvodit z našich studií je, že strukturální a difuzní zobrazování se ukázalo jako užitečné při identifikaci regionálně specifické a disproporcionální ztráty objemu mozku a mikrostruktury u některých patologických procesů, které jsou základem kognitivního zhoršení. Použití několika různých morfometrických...Structural and diffusion imaging patterns that can be evaluated using MRI in patients with cognitive deficits are the central theme of the proposed work. First, the clinical and neuroimaging background of dementias has been reviewed in a broader context, with a special focus on Alzheimer's disease (AD) and differential diagnoses. The second part of this thesis contains four consecutive experimental studies. The primary objective of the first two studies was to obtain structural and microstructural information on the neurodegenerative processes characteristic for AD on global and regional levels. For this purpose, several complementary approaches were used and the focus was shifted from grey to white matter (GM/WM). The following two studies focused on the differential context of WM microstructural alterations in normal pressure hydrocephalus (NPH) and distinctive patterns of WM disintegrity in temporal lobe epilepsy (TLE). The most important conclusion of our studies is that structural and diffusion imaging proved to be useful in identifying regionally specific and disproportionate loss of brain volume and microstructure in several pathological processes underlying cognitive deterioration. The use of distinctive morphometric methods yielded complementary information on AD-related atrophy patterns,...Department of Neurosurgery and Neurooncology First Faculty of Medicine and Central Military HospitalNeurochirurgická a neuroonkologická klinika 1. LF UK a ÚVN1. lékařská fakultaFirst Faculty of Medicin

Morphological and clinical correlations in different forms of dystonia

Distonija predstavlja heterogeno oboljenje, kako po pitanju fenotipskog ispoljavanja, tako i po pitanju etiologije. Pored dobro poznatih motornih karakteristika (akciono pojačanje, fenomeni prelivanja i mirror pokreta, itd), nedavno su prepoznati i različiti nemotorni simptomi, uključujući psihijatrijske smetnje. Iako su rezultati neurovizuelizacionih studija kontradiktorni, u različitim formama distonije su pokazane promene u bazalnim ganglijama (BG), senzorimotornom korteksu i cerebelumu, kao i u cerebelotalamokortikalnim putevima. Najnoviji stavovi ukazuju na to da distonija predstavlja „bolest mreže“ i da može nastati usled disfunkcije ili poremećene komunikacije između bilo kojih tačaka u mreži. Ciljevi: Osnovni ciljevi studije su: 1) Ispitivanje obrasca fenotipskog ispoljavanja i karakteristika kliničkog toka u različitim formama distonije (fokalne-FokD, genetski definisane-GenD i funkcionalne distonije-FunkD); 2) Analiza psihijatrijske osnove, tj. psihijatrijskih komorbiditeta i procena profila ličnosti kod obolelih od funkcionalne distonije u poređenju sa obolelima od „organske distonije“; 3) Ispitivanje specifičnosti obrasca morfoloških i funkcionalnih promena u različitim formama fokalne distonije; 4) Ispitivanje strukturnih promena u genetskim formama distonije; 5) Ispitivanje morfoloških i funkcionalnih izmena u funkcionalnoj distoniji. Metode: U studiju je uključeno 205 bolesnika sa dijagnozom distonije, od toga 116 FokD, 41 GenD, 48 FunkD, koji su dalje uključeni u različite modalitete ispitivanja. Prvo se pristupilo analizi fenotipskog ispoljavanja, u okviru kojeg je u grupi FunkD korišćena klaster analiza, kao i prospektivno praćenje za definisanje dva različita fenotipa. Zatim je rađeno ispitivanje psihijatrijskih komorbiditeta i profila ličnosti u grupi FunkD u poređenju sa „organskom“ (primarnom) distonijom PrimD (FokD i GenD bolesnici upareni po polu, uzrastu i distribuciji distonije) korišćenjem široke palete neuropsihijatrijskih upitnika, uz psihijatrijski pregled. Drugi deo studije se odnosio na neurovizuelizacione metode. U sve 3 grupe bolesnika i u grupi zdravih kontrola (ZK) (83 ispitanika) rađeno je magnetno rezonatno (MR) snimanje mozga i pri tome su dobijeni trodimenzionalni T1 snimci, difuzioni tenzorski (DT) snimci, i funkcionalna MR u mirovanju. Procenjena je debljina korteksa pomoću morfometrije zasnovane na površini, supkortikalni volumeni sive mase (SM), DT MR merenja bele mase (BM). Ispitana je funkcionalna MR u mirovanju korišćenjem slobodnog pristupa. Zatim je u grupi FunkD ispitano funkcionalno povezivanje određenih regiona od interesa koji čine deo emocionalno-kognitivne mreže i učestvuju u definisanju motornog fenotipa. Rezultati: Analiza fenotipa: Bolesnici sa fokalnim distonijama su ispoljili očekivane fenotipske karakteristike, dok su nosioci genetskih mutacije prezentovali značajnu fenotipsku heterogenost, čak i unutar porodica. U grupi FunkD definisana sa dva različita fenotipa. Jedan fenotip – fiksne distonije (FiksFunkD) karakteriše početak simptoma u sredini tridesetih godina života, izražen bol, rani fiksni, abnormalni položaj koji uglavnom zahvata ekstremitete, često udružen sa sindromom kompleksnog regionalnog bola, sa progresivnom deterioracijom simptoma. Drugi fenotip – mobilne distonije (MobFunkD) karakterišu statičke ili akcione intermitentne mišićne kontrakcije koje uzrokuju abnormalne položaje i pokrete, uglavnom, ali ne isključivo, sa kranijalnom i cervikalnom distribucijom, uz relapsno-remitentan klinički tok. Psihijatrijska osnova: Gotovo polovina bolesnika sa FunkD je lečena psihijatrijski pre pojave distoničnih simptoma, a najčešći psihijatrijski komorbiditet je depresivni poremećaj, kako pre početka pojave distoničkih fenomena, tako i tokom trajanja FunkD. U poređenju sa PrimD, kod bolesnika sa FunkD značajno češće je zabeležen precipitirajući stres, viši skorovi na skalama za procenu apatije, disocijativnih i somatoformnih fenomena, kao i prisustvo znaka La Belle Indifférence. Kao nezavisni prediktori FunkD izdvojili su se znak La Belle Indifférence, stres pre početka distonije i prethodno psihijatrijsko oboljenje. Bolesnici sa FunkD su imali nižu ekstroverziju i otvorenost ka iskustvu nego pacijenti sa PrimD...Dystonia is a heterogeneous disorder, both in terms of phenotypic manifestation and etiology. In addition to well-known motor characteristics (action reinforcement, overflow phenomena, mirror movements, etc.), non-motor symptoms, including psychiatric disorders, have recently been recognized recently. Although the results of neuroimaging studies are conflicting, changes in basal ganglia (BG), sensorimotor cortex and cerebellum, as well as cerebello-thalamo-cortical pathways have been shown in various forms of dystonia. The new model indicates that dystonia is a "disorder of network" that can occur due to dysfunction of one node or more nodes, or disturbed communication between them. Objecitves: The main objectives of our study are: 1) to examine the pattern of phenotypic expression and clinical course in various forms of dystonia (focal dystonia-FocD, genetically defined dystonia- GenD and functional dystonia-FuncD); 2) to analyse the psychiatric background, i.e. psychiatric comorbidity and personality profile in patients with FuncD compared to those with "organic” dystonia; 3) to investigate the specificity of the pattern of morphological and functional brain changes in different forms of focal dystonia; 4) to investigate morphological changes in hereditary dystonia; 5) to investigate morphological and functional brain changes in functional dystonia Methods: The study included 205 patients diagnosed with dystonia (116 FocD, 41 GenD, 48 FuncD) who were further involved in different modalities of examination. First, the analysis of phenotypic expression was done. Cluster analysis and follow-up study were used for definition of two different phenotypes of FuncD. Then, psychiatric comorbidity and personality profile in FuncD group were compared with "organic" primary dystonia PrimD (FocD and GenD patients matched by sex, age and distribution of dystonia) using a number of neuropsychiatric questionnaires, and psychiatric interview. The second part of the study concerned neuroimaging methods. Three different groups of patients and the group of healthy controls (HC) underwent three-dimensional T1-weighed, diffusion tensor (DT) MRI, and resting-state functional MRI (RS-fMRI). We assessed cortical thickness with surface-based morphometry, subcortical volumes using region of interest, and DT MRI and RS fMRI using a free model approach. Further, in the FuncD group, the functional connectivity of certain regions of interest that form the emotional-cognitive network and are involved in the definition of motor phenotype were examined using “seed”-based approach. Results: Phenotype analysis: Patients with focal dystonia exhibited the expected phenotypic characteristics, while genetic mutation carriers presented significant phenotypic heterogeneity, even within families. Two different phenotypes were defined in the FuncD group. One phenotype –fixed dystonia (FixFuncD) was characterized by the onset of symptoms in the middle of the thirties, prominent pain, early fixed, abnormal posture that mainly involves extremities, often associated with a complex regional pain syndrome, with progressive deterioration of symptoms. Another phenotype – mobile dystonia (MobFuncD) was characterized by static or action intermittent muscular contractions that cause abnormal postures and movements, mainly but not exclusively, with cranial and cervical distribution, with relapse-remitting clinical course. Psychiatric background: Almost half of patients with FuncD had been treated psychiatrically prior to dystonia onset. The most common psychiatric comorbidity was a depressive disorder, both before the onset of dystonia and actually. Precipitating stress, higher scores on the apathy, dissociative and somatoform scales, and the presence of the La Belle Indifférence sign were significantly more frequent in patients with FuncD in comparison with PrimD. La Belle Indifférence sign, stress before the onset of dystonia and previous psychiatric disorder were independent predictors of FuncD. Patients with FuncD had lower extroversion and openness to experience than patients with PrimD Structural and functional characteristics of focal dystonia: Findings characteristic for task nonspecific dystonia (TNSD) were focal cortical changes (atrophy of the right inferior frontal gyrus) and reduced resting-state functional connectivity within the left frontoparietal network..

Physiological underpinnings of healthy brain ageing

Changes in cerebral perfusion or metabolism can occur as a result of healthy ageing, and in conditions of impaired ageing such as mild cognitive impairment (MCI) or Alzheimer’s disease (AD). Overarchingly, this thesis aimed to explore physiological magnetic resonance imaging (MRI) measures to study both cerebral perfusion and metabolism in the healthy ageing brain. Specifically, arterial spin labelling (ASL) and functional magnetic resonance spectroscopy (1H-fMRS) were employed in the elucidation of healthy ageing. Investigation of cerebral functionality is clinically important, enabling understanding of healthy ageing and disease pathology beyond that provided by structural measures. Given the necessity for tightly-regulated tissue perfusion in the delivery of oxygen to the brain, assessment of brain perfusion can enable elucidation of related brain health. Firstly, this thesis focused on changes in brain perfusion within a cross-sectional retrospective cohort of healthy subjects. This study aimed to assess the utility of univariate and multivariate pattern analysis (MVPA) techniques, and determine whether spatial coefficient of variation (sCoV) measures – which provide a method for inferring spatial heterogeneity of blood flow from single post-label delay (PLD) ASL data – are more significantly associated with age than standard perfusion metrics (ml/100g/min values). The impact of data processing steps on quantification of perfusion was initially assessed. Particularly, the influence of partial volume effect (PVE) correction and how this affected quantification of cerebral perfusion was of interest. The relationship between measures of cerebral perfusion – in regions of interest, vascular territories, and grey matter – and age were assessed, before grey matter (GM) spatial covariance patterns were identified, with MVPA hypothesised to elucidate more subtle age-related change than univariate, voxel-wise methodology. The executive control network (ECN) was the only network exhibiting a significant decline in perfusion with age, after controlling for relevant covariates. Interestingly, whilst the PCA approach resulted in a pattern of both positive and negative associations with age across cerebral GM, the surviving clusters in voxel-wise approaches were deemed spurious. Five-fold cross validation of PCA findings was used to assess whether the resultant spatial covariance patterns were able to predict subject age. This prediction was successful, with related r2 values of between 0.5316 and 0.7297 (p < 0.001 for all), however validation of these findings in an unseen dataset is required. The utility of the sCoV metric was also compared with standard tissue perfusion values, finding that sCoV may be more closely associated with ageing than ml/100g/min in certain regions. Particularly, a significant increase in whole GM sCoV with age was notable, given the absence of significant changes in perfusion with age in the same region. Additionally, a MVPA approach was used to establish the complex unknown relationship between cerebral perfusion and the Montreal Cognitive Assessment (MoCA), before graph visualisation was used to further understand the regional relatedness of the spatial covariance pattern. PCA resulted in a model which provided a moderate explanation of the aforementioned relationship, but this may be improved by inclusion of additional covariates in subsequent work, such as those pertaining to genetic status, such as apolipoprotein E (APOE). This study also replicates an FDG PET cognitive resilience signature in an ASL cohort for the first time, with a trend towards declining perfusion with age found (p = .08). Lastly, as ageing is associated with metabolic failure in the brain, which is often investigated using methodology which employs ionising radiation, the final study was motivated to investigate possible metabolic markers of brain ageing which can be measured using MRI. Metabolic-functional coupling can be studied using functional stimulation, and functional magnetic resonance spectroscopy (fMRS) is perfectly poised to elucidate certain metabolic behaviour. Given the close relationship between glucose (Glc) – the key fuel for cerebral functionality – and lactate (Lac) metabolism, an optimised long echo time (TE) semi-localized by adiabatic selective refocusing (semi-LASER) sequence (TE=144ms) with optimised J-modulation selection at 7T was employed to assess the effects of age on the dynamic behaviour of Lac, and determine its absolute concentrations throughout the time course, whilst a visual stimulation paradigm was viewed. Successful quantification of metabolite concentrations – including Lac, tCr and tNAA – was achieved in both the young and old cohorts, and their Lac peaks clearly visually identifiable throughout the time course. A significant increase in Lac concentration was observed between rest and stimulation, but not stimulation and recovery, in the young cohort. No significant Lac time course changes were identified in the full old cohort. This thesis concluded by summarising and contextualising the key findings herein, and discussion of possible directions for further associated research. The findings of this thesis broaden the field of knowledge around healthy ageing, and therefore may contribute to subsequent translation efforts for both clinical diagnostics and treatment approaches

Consensus ou fusion de segmentation pour quelques applications de détection ou de classification en imagerie

Récemment, des vraies mesures de distances, au sens d’un certain critère (et possédant de bonnes propriétés asymptotiques) ont été introduites entre des résultats de partitionnement (clustering) de donnés, quelquefois indexées spatialement comme le sont les images segmentées. À partir de ces métriques, le principe de segmentation moyenne (ou consensus) a été proposée en traitement d’images, comme étant la solution d’un problème d’optimisation et une façon simple et efficace d’améliorer le résultat final de segmentation ou de classification obtenues en moyennant (ou fusionnant) différentes segmentations de la même scène estimée grossièrement à partir de plusieurs algorithmes de segmentation simples (ou identiques mais utilisant différents paramètres internes). Ce principe qui peut se concevoir comme un débruitage de données d’abstraction élevée, s’est avéré récemment une alternative efficace et très parallélisable, comparativement aux méthodes utilisant des modèles de segmentation toujours plus complexes et plus coûteux en temps de calcul. Le principe de distance entre segmentations et de moyennage ou fusion de segmentations peut être exploité, directement ou facilement adapté, par tous les algorithmes ou les méthodes utilisées en imagerie numérique où les données peuvent en fait se substituer à des images segmentées. Cette thèse a pour but de démontrer cette assertion et de présenter différentes applications originales dans des domaines comme la visualisation et l’indexation dans les grandes bases d’images au sens du contenu segmenté de chaque image, et non plus au sens habituel de la couleur et de la texture, le traitement d’images pour améliorer sensiblement et facilement la performance des méthodes de détection du mouvement dans une séquence d’images ou finalement en analyse et classification d’images médicales avec une application permettant la détection automatique et la quantification de la maladie d’Alzheimer à partir d’images par résonance magnétique du cerveau.Recently, some true metrics in a criterion sense (with good asymptotic properties) were introduced between data partitions (or clusterings) even for data spatially ordered such as image segmentations. From these metrics, the notion of average clustering (or consensus segmentation) was then proposed in image processing as the solution of an optimization problem and a simple and effective way to improve the final result of segmentation or classification obtained by averaging (or fusing) different segmentations of the same scene which are roughly estimated from several simple segmentation models (or obtained with the same model but with different internal parameters). This principle, which can be conceived as a denoising of high abstraction data, has recently proved to be an effective and very parallelizable alternative, compared to methods using ever more complex and time-consuming segmentation models. The principle of distance between segmentations, and averaging of segmentations, in a criterion sense, can be exploited, directly or easily adapted, by all the algorithms or methods used in digital imaging where data can in fact be substituted to segmented images. This thesis proposal aims at demonstrating this assertion and to present different original applications in various fields in digital imagery such as the visualization and the indexation in the image databases, in the sense of the segmented contents of each image, and no longer in the common color and texture sense, or in image processing in order to sensibly and easily improve the detection of movement in the image sequence or finally in analysis and classification in medical imaging with an application allowing the automatic detection and quantification of Alzheimer’s disease

Contributions to Ensemble Classifiers with Image Analysis Applications

134 p.Ésta tesis tiene dos aspectos fundamentales, por un lado, la propuesta denuevas arquitecturas de clasificadores y, por otro, su aplicación a el análisis deimagen.Desde el punto de vista de proponer nuevas arquitecturas de clasificaciónla tesis tiene dos contribucciones principales. En primer lugar la propuestade un innovador ensemble de clasificadores basado en arquitecturas aleatorias,como pueden ser las Extreme Learning Machines (ELM), Random Forest (RF) yRotation Forest, llamado Hybrid Extreme Rotation Forest (HERF) y su mejoraAnticipative HERF (AHERF) que conlleva una selección del modelo basada enel rendimiento de predicción para cada conjunto de datos específico. Ademásde lo anterior, proveemos una prueba formal tanto del AHERF, como de laconvergencia de los ensembles de regresores ELMs que mejoran la usabilidad yreproducibilidad de los resultados.En la vertiente de aplicación hemos estado trabajando con dos tipos de imágenes:imágenes hiperespectrales de remote sensing, e imágenes médicas tanto depatologías específicas de venas de sangre como de imágenes para el diagnósticode Alzheimer. En todos los casos los ensembles de clasificadores han sido la herramientacomún además de estrategias especificas de aprendizaje activo basadasen dichos ensembles de clasificadores. En el caso concreto de la segmentaciónde vasos sanguíneos nos hemos enfrentado con problemas, uno relacionado conlos trombos del Aneurismas de Aorta Abdominal en imágenes 3D de tomografíacomputerizada y el otro la segmentación de venas sangineas en la retina. Losresultados en ambos casos en términos de rendimiento en clasificación y ahorrode tiempo en la segmentación humana nos permiten recomendar esos enfoquespara la práctica clínica.Chapter 1Background y contribuccionesDado el espacio limitado para realizar el resumen de la tesis hemos decididoincluir un resumen general con los puntos más importantes, una pequeña introducciónque pudiera servir como background para entender los conceptos básicosde cada uno de los temas que hemos tocado y un listado con las contribuccionesmás importantes.1.1 Ensembles de clasificadoresLa idea de los ensembles de clasificadores fue propuesta por Hansen y Salamon[4] en el contexto del aprendizaje de las redes neuronales artificiales. Sutrabajo mostró que un ensemble de redes neuronales con un esquema de consensogrupal podía mejorar el resultado obtenido con una única red neuronal.Los ensembles de clasificadores buscan obtener unos resultados de clasificaciónmejores combinando clasificadores débiles y diversos [8, 9]. La propuesta inicialde ensemble contenía una colección homogena de clasificadores individuales. ElRandom Forest es un claro ejemplo de ello, puesto que combina la salida de unacolección de árboles de decisión realizando una votación por mayoría [2, 3], yse construye utilizando una técnica de remuestreo sobre el conjunto de datos ycon selección aleatoria de variables.2CHAPTER 1. BACKGROUND Y CONTRIBUCCIONES 31.2 Aprendizaje activoLa construcción de un clasificador supervisado consiste en el aprendizaje de unaasignación de funciones de datos en un conjunto de clases dado un conjunto deentrenamiento etiquetado. En muchas situaciones de la vida real la obtenciónde las etiquetas del conjunto de entrenamiento es costosa, lenta y propensa aerrores. Esto hace que la construcción del conjunto de entrenamiento sea unatarea engorrosa y requiera un análisis manual exaustivo de la imagen. Esto se realizanormalmente mediante una inspección visual de las imágenes y realizandoun etiquetado píxel a píxel. En consecuencia el conjunto de entrenamiento esaltamente redundante y hace que la fase de entrenamiento del modelo sea muylenta. Además los píxeles ruidosos pueden interferir en las estadísticas de cadaclase lo que puede dar lugar a errores de clasificación y/o overfitting. Por tantoes deseable que un conjunto de entrenamiento sea construido de una manera inteligente,lo que significa que debe representar correctamente los límites de clasemediante el muestreo de píxeles discriminantes. La generalización es la habilidadde etiquetar correctamente datos que no se han visto previamente y quepor tanto son nuevos para el modelo. El aprendizaje activo intenta aprovecharla interacción con un usuario para proporcionar las etiquetas de las muestrasdel conjunto de entrenamiento con el objetivo de obtener la clasificación másprecisa utilizando el conjunto de entrenamiento más pequeño posible.1.3 AlzheimerLa enfermedad de Alzheimer es una de las causas más importantes de discapacidaden personas mayores. Dado el envejecimiento poblacional que es una realidaden muchos países, con el aumento de la esperanza de vida y con el aumentodel número de personas mayores, el número de pacientes con demencia aumentarátambién. Debido a la importancia socioeconómica de la enfermedad enlos países occidentales existe un fuerte esfuerzo internacional focalizado en laenfermedad del Alzheimer. En las etapas tempranas de la enfermedad la atrofiacerebral suele ser sutil y está espacialmente distribuida por diferentes regionescerebrales que incluyen la corteza entorrinal, el hipocampo, las estructuras temporaleslateral e inferior, así como el cíngulo anterior y posterior. Son muchoslos esfuerzos de diseño de algoritmos computacionales tratando de encontrarbiomarcadores de imagen que puedan ser utilizados para el diagnóstico no invasivodel Alzheimer y otras enfermedades neurodegenerativas.CHAPTER 1. BACKGROUND Y CONTRIBUCCIONES 41.4 Segmentación de vasos sanguíneosLa segmentación de los vasos sanguíneos [1, 7, 6] es una de las herramientas computacionalesesenciales para la evaluación clínica de las enfermedades vasculares.Consiste en particionar un angiograma en dos regiones que no se superponen:la región vasculares y el fondo. Basándonos en los resultados de dicha particiónse pueden extraer, modelar, manipular, medir y visualizar las superficies vasculares.Éstas estructuras son muy útiles y juegan un rol muy imporntate en lostratamientos endovasculares de las enfermedades vasculares. Las enfermedadesvasculares son una de las principales fuentes de morbilidad y mortalidad en todoel mundo.Aneurisma de Aorta Abdominal El Aneurisma de Aorta Abdominal (AAA)es una dilatación local de la Aorta que ocurre entre las arterias renal e ilíaca. Eldebilitamiento de la pared de la aorta conduce a su deformación y la generaciónde un trombo. Generalmente, un AAA se diagnostica cuando el diámetro anterioposteriormínimo de la aorta alcanza los 3 centímetros [5]. La mayoría delos aneurismas aórticos son asintomáticos y sin complicaciones. Los aneurismasque causan los síntomas tienen un mayor riesgo de ruptura. El dolor abdominalo el dolor de espalda son las dos principales características clínicas que sugiereno bien la reciente expansión o fugas. Las complicaciones son a menudo cuestiónde vida o muerte y pueden ocurrir en un corto espacio de tiempo. Por lo tanto,el reto consiste en diagnosticar lo antes posible la aparición de los síntomas.Imágenes de Retina La evaluación de imágenes del fondo del ojo es una herramientade diagnóstico de la patología vascular y no vascular. Dicha inspecciónpuede revelar hipertensión, diabetes, arteriosclerosis, enfermedades cardiovascularese ictus. Los principales retos para la segmentación de vasos retinianos son:(1) la presencia de lesiones que se pueden interpretar de forma errónea comovasos sanguíneos; (2) bajo contraste alrededor de los vasos más delgados, (3)múltiples escalas de tamaño de los vasos.1.5 ContribucionesÉsta tesis tiene dos tipos de contribuciones. Contribuciones computacionales ycontribuciones orientadas a una aplicación o prácticas.CHAPTER 1. BACKGROUND Y CONTRIBUCCIONES 5Desde un punto de vista computacional las contribuciones han sido las siguientes:¿ Un nuevo esquema de aprendizaje activo usando Random Forest y el cálculode la incertidumbre que permite una segmentación de imágenes rápida,precisa e interactiva.¿ Hybrid Extreme Rotation Forest.¿ Adaptative Hybrid Extreme Rotation Forest.¿ Métodos de aprendizaje semisupervisados espectrales-espaciales.¿ Unmixing no lineal y reconstrucción utilizando ensembles de regresoresELM.Desde un punto de vista práctico:¿ Imágenes médicas¿ Aprendizaje activo combinado con HERF para la segmentación deimágenes de tomografía computerizada.¿ Mejorar el aprendizaje activo para segmentación de imágenes de tomografíacomputerizada con información de dominio.¿ Aprendizaje activo con el clasificador bootstrapped dendritic aplicadoa segmentación de imágenes médicas.¿ Meta-ensembles de clasificadores para detección de Alzheimer conimágenes de resonancia magnética.¿ Random Forest combinado con aprendizaje activo para segmentaciónde imágenes de retina.¿ Segmentación automática de grasa subcutanea y visceral utilizandoresonancia magnética.¿ Imágenes hiperespectrales¿ Unmixing no lineal y reconstrucción utilizando ensembles de regresoresELM.¿ Métodos de aprendizaje semisupervisados espectrales-espaciales concorrección espacial usando AHERF.¿ Método semisupervisado de clasificación utilizando ensembles de ELMsy con regularización espacial

[¹⁸F]fluorination of biorelevant arylboronic acid pinacol ester scaffolds synthesized by convergence techniques

Aim: The development of small molecules through convergent multicomponent reactions (MCR) has been boosted during the last decade due to the ability to synthesize, virtually without any side-products, numerous small drug-like molecules with several degrees of structural diversity.(1) The association of positron emission tomography (PET) labeling techniques in line with the “one-pot” development of biologically active compounds has the potential to become relevant not only for the evaluation and characterization of those MCR products through molecular imaging, but also to increase the library of radiotracers available. Therefore, since the [18F]fluorination of arylboronic acid pinacol ester derivatives tolerates electron-poor and electro-rich arenes and various functional groups,(2) the main goal of this research work was to achieve the 18F-radiolabeling of several different molecules synthesized through MCR. Materials and Methods: [18F]Fluorination of boronic acid pinacol esters was first extensively optimized using a benzaldehyde derivative in relation to the ideal amount of Cu(II) catalyst and precursor to be used, as well as the reaction solvent. Radiochemical conversion (RCC) yields were assessed by TLC-SG. The optimized radiolabeling conditions were subsequently applied to several structurally different MCR scaffolds comprising biologically relevant pharmacophores (e.g. β-lactam, morpholine, tetrazole, oxazole) that were synthesized to specifically contain a boronic acid pinacol ester group. Results: Radiolabeling with fluorine-18 was achieved with volumes (800 μl) and activities (≤ 2 GBq) compatible with most radiochemistry techniques and modules. In summary, an increase in the quantities of precursor or Cu(II) catalyst lead to higher conversion yields. An optimal amount of precursor (0.06 mmol) and Cu(OTf)2(py)4 (0.04 mmol) was defined for further reactions, with DMA being a preferential solvent over DMF. RCC yields from 15% to 76%, depending on the scaffold, were reproducibly achieved. Interestingly, it was noticed that the structure of the scaffolds, beyond the arylboronic acid, exerts some influence in the final RCC, with electron-withdrawing groups in the para position apparently enhancing the radiolabeling yield. Conclusion: The developed method with high RCC and reproducibility has the potential to be applied in line with MCR and also has a possibility to be incorporated in a later stage of this convergent “one-pot” synthesis strategy. Further studies are currently ongoing to apply this radiolabeling concept to fluorine-containing approved drugs whose boronic acid pinacol ester precursors can be synthesized through MCR (e.g. atorvastatin)