Association of ECG abnormalities and incident heart failure events

Background: With the aging of the population, the heart failure (HF) incidence and prevalence trends are expected to significantly worsen unless concentrated prevention efforts are undertaken. ECG abnormalities are common in the elderly but data are limited for their association with HF risk. Objective: To assess whether baseline ECG abnormalities or dynamic changes are associated with an increased risk of HF. Method: A prospective cohort study of 2915 participants aged 70 to 79 years without a preexisting HF followed for a median period of 11.4 (IQR 7.0-11.7) years from the Health Aging and Body Composition study. The Minnesota Code was used to define major and minor ECG abnormalities at baseline and at 4-year. Main outcome measure was adjudicated incident HF events. Using Cox models, the (1) the association between ECG abnormalities and incident HF and (2) incremental value of adding ECG to the Health ABC HF Risk Score, was assessed. Results: At baseline, 380 participants (13.0%) had minor and 620 (21.3%) had major ECG abnormalities. During follow-up, 485 (16.6%) participants developed incident HF. After adjusting for the eight clinical variables in the Health ABC HF Risk Score, the hazard ratio (HR) was 1.27 (95% confidence interval [CI] 0.96-1.68) for minor and 1.99 (CI 1.61-2.44) for major ECG abnormalities (P for trend <0.001) compared to no ECG abnormalities. The association did not change according to presence of baseline CHD. At 4-year, 263 participants developed new and 549 had persistent abnormalities and both were associated with increased HF risk (HR = 1.94, CI 1.38-2.72 for new and HR=2.35, CI 1.82-3.02 for persistent compared to no ECG abnormalities). Baseline ECG correctly reclassified 10.6% of overall participants across the categories of the Health ABC HF Risk Score. Conclusion: Among older adults, baseline ECG abnormalities and changes in them over time are common; both are associated with an increased risk of HF. Whether ECG should be incorporated in routine screening of older adults should be evaluated in randomized controlled trials.

Assessing the associations between mental disorders, cardiovascular risk factors, and cardiovascular disease : the CoLaus/PsyCoLaus study

Background: Cardio-vascular diseases (CVD), their well established risk factors (CVRF) and mental disorders are common and co-occur more frequently than would be expected by chance. However, the pathogenic mechanisms and course determinants of both CVD and mental disorders have only been partially identified.Methods/Design: Comprehensive follow-up of CVRF and CVD with a psychiatric exam in all subjects who participated in the baseline cross-sectional CoLaus study (2003-2006) (n=6'738) which also included a comprehensive genetic assessment. The somatic investigation will include a shortened questionnaire on CVRF, CV events and new CVD since baseline and measurements of the same clinical and biological variables as at baseline. In addition, pro-inflammatory markers, persistent pain and sleep patterns and disorders will be assessed. In the case of a new CV event, detailed information will be abstracted from medical records. Similarly, data on the cause of death will be collected from the Swiss National Death Registry. The comprehensive psychiatric investigation of the CoLaus/PsyCoLaus study will use contemporary epidemiological methods including semi-structured diagnostic interviews, experienced clinical interviewers, standardized diagnostic criteria including threshold according to DSM-IV and sub-threshold syndromes and supplementary information on risk and protective factors for disorders. In addition, screening for objective cognitive impairment will be performed in participants older than 65 years.Discussion: The combined CoLaus/PsyCoLaus sample provides a unique opportunity to obtain prospective data on the interplay between CVRF/CVD and mental disorders, overcoming limitations of previous research by bringing together a comprehensive investigation of both CVRF and mental disorders as well as a large number of biological variables and a genome-wide genetic assessment in participants recruited from the general population.

Prevalence and impact of cannabis use disorders in adolescents with early onset first episode psychosis.

BACKGROUND: Previous studies on the impact of cannabis use disorders (CU) on outcome in psychosis were predominantly based on non representative samples, often have not controlled for confounders and rarely focused on adolescent patients. Thus, the aims of the present study were to assess: (i) prevalence of CU; (ii) baseline and pretreatment differences between CU and those without CU (NCU); (iii) the impact of baseline and course of CU on 18-month outcomes in a representative cohort of adolescents with early onset first episode psychosis (EOP). METHODS: The sample comprised 99 adolescents (age 14 to 18) with EOP (onset age 14 to 17), admitted to the Early Psychosis Prevention and Intervention Centre in Australia. Data were collected from medical files using a standardized questionnaire. RESULTS: Prevalence of lifetime CU was 65.7%, of current CU at baseline 53.5%, and of persistent CU throughout treatment 26.3%. Baseline CU compared to NCU had significantly higher illness-severity, lower psychosocial functioning, less insight, lower premorbid functioning and longer duration of untreated psychosis. Compared to all other groups, only persistent CU was linked to worse outcomes and more service disengagement. Effect sizes were medium controlling for relevant confounders. Medication non-adherence did not explain the association between persistent CU and worse outcome. CONCLUSIONS: Baseline CU was associated with worse baseline characteristics, but only persistent CU was linked with worse outcome. About half of those with baseline CU reduced cannabis during treatment. For these, effectively treating the psychotic disorder may already be beneficial. However, future research is necessary on the reasons for persistent CU in EOP and its treatment.

A new locus for congenital cataract, microcornea, microphthalmia, and atypical iris coloboma maps to chromosome 2.

OBJECTIVE: To report a novel phenotype of autosomal dominant atypical congenital cataract associated with variable expression of microcornea, microphthalmia, and iris coloboma linked to chromosome 2. Molecular analysis of this phenotype may improve our understanding of anterior segment development. DESIGN: Observational case study, genome linkage analysis, and gene mutation screening. PARTICIPANTS: Three families, 1 Egyptian and 2 Belgians, with a total of 31 affected were studied. METHODS: Twenty-one affected subjects and 9 first-degree relatives underwent complete ophthalmic examination. In the Egyptian family, exclusion of PAX6, CRYAA, and MAF genes was demonstrated by haplotype analysis using microsatellite markers on chromosomes 11, 16, and 21. Genome-wide linkage analysis was then performed using 385 microsatellite markers on this family. In the 2 Belgian families, the PAX6 gene was screened for mutations by direct sequencing of all exons. MAIN OUTCOME MEASURES: Phenotype description, genome-wide linkage of the phenotype, linkage to the PAX6, CRYAA, and MAF genes, and mutation detection in the PAX6 gene. RESULTS: Affected members of the 3 families had bilateral congenital cataracts inherited in an autosomal dominant pattern. A novel form of hexagonal nuclear cataract with cortical riders was expressed. Among affected subjects with available data, 95% had microcornea, 39% had microphthalmia, and 38% had iris coloboma. Seventy-five percent of the colobomata were atypical, showing a nasal superior location in 56%. A positive lod score of 4.86 was obtained at theta = 0 for D2S2309 on chromosome 2, a 4.9-Mb common haplotype flanked by D2S2309 and D2S2358 was obtained in the Egyptian family, and linkage to the PAX6, CRYAA, or MAF gene was excluded. In the 2 Belgian families, sequencing of the junctions and all coding exons of PAX6 did not reveal any molecular change. CONCLUSIONS: We describe a novel phenotype that includes the combination of a novel form of congenital hexagonal cataract, with variably expressed microcornea, microphthalmia, and atypical iris coloboma, not caused by PAX6 and mapping to chromosome 2. FINANCIAL DISCLOSURE(S): The authors have no proprietary or commercial interest in any materials discussed in this article.

Machine learning for spatial environmental data. Theory, applications and software

The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.

Copy number variants, diseases and gene expression.

Copy number variation (CNV) has recently gained considerable interest as a source of genetic variation likely to play a role in phenotypic diversity and evolution. Much effort has been put into the identification and mapping of regions that vary in copy number among seemingly normal individuals in humans and a number of model organisms, using bioinformatics or hybridization-based methods. These have allowed uncovering associations between copy number changes and complex diseases in whole-genome association studies, as well as identify new genomic disorders. At the genome-wide scale, however, the functional impact of CNV remains poorly studied. Here we review the current catalogs of CNVs, their association with diseases and how they link genotype and phenotype. We describe initial evidence which revealed that genes in CNV regions are expressed at lower and more variable levels than genes mapping elsewhere, and also that CNV not only affects the expression of genes varying in copy number, but also have a global influence on the transcriptome. Further studies are warranted for complete cataloguing and fine mapping of CNVs, as well as to elucidate the different mechanisms by which they influence gene expression.

Textual autocorrelation : formalism and illustrations

Abstract Textual autocorrelation is a broad and pervasive concept, referring to the similarity between nearby textual units: lexical repetitions along consecutive sentences, semantic association between neighbouring lexemes, persistence of discourse types (narrative, descriptive, dialogal...) and so on. Textual autocorrelation can also be negative, as illustrated by alternating phonological or morpho-syntactic categories, or the succession of word lengths. This contribution proposes a general Markov formalism for textual navigation, and inspired by spatial statistics. The formalism can express well-known constructs in textual data analysis, such as term-document matrices, references and hyperlinks navigation, (web) information retrieval, and in particular textual autocorrelation, as measured by Moran's I relatively to the exchange matrix associated to neighbourhoods of various possible types. Four case studies (word lengths alternation, lexical repulsion, parts of speech autocorrelation, and semantic autocorrelation) illustrate the theory. In particular, one observes a short-range repulsion between nouns together with a short-range attraction between verbs, both at the lexical and semantic levels. Résumé: Le concept d'autocorrélation textuelle, fort vaste, réfère à la similarité entre unités textuelles voisines: répétitions lexicales entre phrases successives, association sémantique entre lexèmes voisins, persistance du type de discours (narratif, descriptif, dialogal...) et ainsi de suite. L'autocorrélation textuelle peut être également négative, comme l'illustrent l'alternance entre les catégories phonologiques ou morpho-syntaxiques, ou la succession des longueurs de mots. Cette contribution propose un formalisme markovien général pour la navigation textuelle, inspiré par la statistique spatiale. Le formalisme est capable d'exprimer des constructions bien connues en analyse des données textuelles, telles que les matrices termes-documents, les références et la navigation par hyperliens, la recherche documentaire sur internet, et, en particulier, l'autocorélation textuelle, telle que mesurée par le I de Moran relatif à une matrice d'échange associée à des voisinages de différents types possibles. Quatre cas d'étude illustrent la théorie: alternance des longueurs de mots, répulsion lexicale, autocorrélation des catégories morpho-syntaxiques et autocorrélation sémantique. On observe en particulier une répulsion à courte portée entre les noms, ainsi qu'une attraction à courte portée entre les verbes, tant au niveau lexical que sémantique.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Interest rates mapping

The present study deals with the analysis and mapping of Swiss franc interest rates. Interest rates depend on time and maturity, defining term structure of the interest rate curves (IRC). In the present study IRC are considered in a two-dimensional feature space - time and maturity. Exploratory data analysis includes a variety of tools widely used in econophysics and geostatistics. Geostatistical models and machine learning algorithms (multilayer perceptron and Support Vector Machines) were applied to produce interest rate maps. IR maps can be used for the visualisation and pattern perception purposes, to develop and to explore economical hypotheses, to produce dynamic asset-liability simulations and for financial risk assessments. The feasibility of an application of interest rates mapping approach for the IRC forecasting is considered as well. (C) 2008 Elsevier B.V. All rights reserved.

Persistent left superior vena cava in cardiac congenital surgery.

Persistent left superior vena cava (LSVC) is a relatively frequent finding in congenital cardiac malformation. The scope of the study was to analyze the timing of diagnosis of persistent LSVC, the timing of diagnosis of associated anomalies of the coronary sinus, and the global impact on morbidity and mortality of persistent LSVC in children with congenital heart disease after cardiac surgery. Retrospective analysis of a cohort of children after cardiac surgery on bypass for congenital heart disease. Three hundred seventy-one patients were included in the study, and their median age was 2.75 years (IQR 0.65-6.63). Forty-seven children had persistent LSVC (12.7 %), and persistent LSVC was identified on echocardiography before surgery in 39 patients (83 %). In three patients (6.4 %) with persistent LSVC, significant inflow obstruction of the left ventricle developed after surgery leading to low output syndrome or secondary pulmonary hypertension. In eight patients (17 %), persistent LSVC was associated with a partially or completely unroofed coronary sinus and in two cases (4 %) with coronary sinus ostial atresia. Duration of mechanical ventilation was significantly shorter in the control group (1.2 vs. 3.0 days, p = 0.04), whereas length of stay in intensive care did not differ. Mortality was also significantly lower in the control group (2.5 vs. 10.6 %, p = 0.004). The results of study show that persistent LSVC in association with congenital cardiac malformation increases the risk of mortality in children with cardiac surgery on cardiopulmonary bypass. Recognition of a persistent LSVC and its associated anomalies is mandatory to avoid complications during or after cardiac surgery.

Infection and chronic allograft dysfunction.

With the advent of more potent immunosuppressive regimens, the incidence of acute rejection following renal transplantation has declined sharply in recent years. In spite of this, long-term graft outcomes remain suboptimal because of relentless attrition by cumulated insults to the allograft. As acute rejection rates have declined, other causes of graft injury and loss have recently emerged. Among these, infectious diseases remain a persistent threat and can be associated with allograft dysfunction. This group includes nephropathy due to polyoma (BK) virus infection, cytomegalovirus disease, and bacterial infection (the latter most commonly arising from the urinary tract). Rarer infectious causes of chronic allograft dysfunction include cryoglobulinemia associated with hepatitis C, Epstein-Barr virus-associated posttransplant lymphoproliferative disease, and direct cytotoxicity from adenoviral infection or parvovirus B19.

Long-term effects of neonatal hypoglycemia on brain growth and psychomotor development in small-for-gestational-age preterm infants.

OBJECTIVE: To investigate the effects of neonatal hypoglycemia on physical growth and neurocognitive function.Study design: A systematic detection of hypoglycemia (<2.6 mmol/L or 47 mg/dL) was carried out in 85 small-for-gestational-age preterm neonates. Prospective serial evaluations of physical growth and psychomotor development were performed. Retrospectively, infants were grouped according to their glycemic status. RESULTS: The incidence of hypoglycemia was 72.9%. Infants with repeated episodes of hypoglycemia had significantly reduced head circumferences and lower scores in specific psychometric tests at 3.5 years of age. Hypoglycemia also caused reduced head circumferences at 18 months and lower psychometric scores at 5 years of age. Infants with moderate recurrent hypoglycemia had lower scores at 3.5 and 5 years of age compared with the group of infants who had 1 single severe hypoglycemic episode. CONCLUSION: Recurrent episodes of hypoglycemia were strongly correlated with persistent neurodevelopmental and physical growth deficits until 5 years of age. Recurrent hypoglycemia also was a more predictable factor for long-term effects than the severity of a single hypoglycemic episode. Therefore repetitive blood glucose monitoring and rapid treatment even for mild hypoglycemia are recommended for small-for-gestational-age infants in the neonatal period.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Presence of Leishmania RNA Virus 1 in Leishmania guyanensis Increases the Risk of First-Line Treatment Failure and Symptomatic Relapse.

Treatment failure and symptomatic relapse are major concerns in American tegumentary leishmaniasis (TL). Such complications are seen frequently in Leishmania guyanensis infections, in which patients respond variously to first-line antileishmanials and are more prone to develop chronic cutaneous leishmaniasis. The factors underlying this pathology, however, are unknown. Recently, we reported that a double-stranded RNA virus, Leishmania RNA virus 1 (LRV1), nested within L. guyanensis parasites is able to exacerbate experimental murine leishmaniasis by inducing a hyperinflammatory response. This report investigates the prevalence of LRV1 in human L. guyanensis infection and its effect on treatment efficacy, as well as its correlation to symptomatic relapses after the completion of first-line treatment. In our cohort of 75 patients with a diagnosis of primary localized American TL, the prevalence of LRV1-positive L. guyanensis infection was elevated to 58%. All patients infected with LRV1-negative L. guyanensis were cured after 1 dose (22 of 31 [71%]) or 2 doses (31 of 31 [100%]) of pentamidine. In contrast, 12 of 44 LRV1-positive patients (27%) presented with persistent infection and symptomatic relapse that required extended therapy and the use of second-line drugs. Finally, LRV1 presence was associated with a significant increase in levels of intra-lesional inflammatory markers. In conclusion, LRV1 status in L. guyanensis infection is significantly predictive (P = .0009) of first-line treatment failure and symptomatic relapse and has the potential to guide therapeutic choices in American TL.

Combining T2-preparation with spectral and spatial selectivity for improved coronary MRA

Cardiovascular disease is the leading cause of death worldwide. Within this subset, coronary artery disease (CAD) is the most prevalent. Magnetic resonance angiography (MRA) is an emerging technique that provides a safe, non-invasive way of assessing CAD progression. To generate contrast between tissues, MR images are weighted according to the magnetic properties of those tissues. In cardiac MRI, T2 contrast, which is governed by the rate of transverse signal loss, is often created through the use of a T2-Preparation module. T2-Preparation, or T2-Prep, is a magnetization preparation scheme used to improve blood/myocardium contrast in cardiac MRI. T2-Prep methods generally use a non-selective +90°, 180°, 180°, -90° train of radiofrequency (RF) pulses (or variant thereof), to tip magnetization into the transverse plane, allow it to evolve, and then to restore it to the longitudinal plane. A key feature in this process is the combination of a +90° and -90° RF pulse. By changing either one of these, a mismatch occurs between signal excitation and restoration. This feature can be exploited to provide additional spectral or spatial selectivity. In this work, both of these possibilities are explored. The first - spectral selectivity - has been examined as a method of improving fat saturation in coronary MRA. The second - spatial selectivity - has been examined as a means of reducing imaging time by decreasing the field of view, and as a method of reducing artefacts originating from the tissues surrounding the heart. Two additional applications, parallel imaging and self-navigation, are also presented. This thesis is thus composed of four sections. The first, "A Fat Signal Suppression for Coronary MRA at 3T using a Water-Selective Adiabatic T2-Preparation Technique", was originally published in the journal Magnetic Resonance in Medicine (MRM) with co-authors Ruud B. van Heeswijk and Matthias Stuber. The second, "Combined T2-Preparation and 2D Pencil Beam Inner Volume Selection", again with co-authors Ruud van Heeswijk and Matthias Stuber, was also published in the journal MRM. The third, "A cylindrical, inner volume selecting 2D-T2-Prep improves GRAPPA-accelerated image quality in MRA of the right coronary artery", written with co-authors Jerome Yerly and Matthias Stuber, has been submitted to the "Journal of Cardiovascular Magnetic Resonance", and the fourth, "Combined respiratory self-navigation and 'pencil-beam' 2D-T2 -Prep for free-breathing, whole-heart coronary MRA", with co¬authors Jerome Chaptinel, Giulia Ginami, Gabriele Bonanno, Simone Coppo, Ruud van Heeswijk, Davide Piccini, and Matthias Stuber, is undergoing internal review prior to submission to the journal MRM. -- Les maladies cardiovasculaires sont la cause principale de décès dans le monde : parmi celles-ci, les maladies coronariennes sont les plus répandues. L'angiographie par résonance magnétique (ARM) est une technique émergente qui fournit une manière sûre, non invasive d'évaluer la progression de la coronaropathie. Pour obtenir un contraste entre les tissus, les images d'IRM sont pondérées en fonction des propriétés magnétiques de ces tissus. En IRM cardiaque, le contraste en T2, qui est lié à la décroissance du signal transversal, est souvent créé grâce à l'utilisàtion d'un module de préparation T2. La préparation T2, ou T2-Prep, est un système de préparation de l'aimantation qui est utilisé pour améliorer le contraste entre le sang et le myocarde lors d'une IRM cardiaque. Les méthodes de T2-Prep utilisent généralement une série non-sélective d'impulsions de radiofréquence (RF), typiquement [+ 90°, 180°, 180°, -90°] ou une variante, qui bascule l'aimantation dans le plan transversal, lui permet d'évoluer, puis la restaure dans le plan longitudinal. Un élément clé de ce processus est la combinaison des impulsions RF de +90° et -90°. En changeant l'une ou l'autre des impulsions, un décalage se produit entre l'excitation du signal et de la restauration. Cette fonction peut être exploitée pour fournir une sélectivité spectrale ou spatiale. Dans cette thèse, les deux possibilités sont explorées. La première - la sélectivité spectrale - a été examinée comme une méthode d'améliorer la saturation de la graisse dans l'IRM coronarienne. La deuxième - la sélectivité spatiale - a été étudiée comme un moyen de réduire le temps d'imagerie en diminuant le champ de vue, et comme une méthode de réduction des artefacts provenant des tissus entourant le coeur. Deux applications supplémentaires, l'imagerie parallèle et la self-navigation, sont également présentées. Cette thèse est ainsi composée de quatre sections. La première, "A Fat Signal Suppression for Coronary MRA at 3T using a Water-Selective Adiabatic T2-Preparation Technique", a été publiée dans la revue médicale Magnetic Resonance .in Medicine (MRM) avec les co-auteurs Ruud B. van Heeswijk et Matthias Stuber. La deuxième, Combined T2-Preparation and 2D Pencil Beam Inner Volume Selection", encore une fois avec les co-auteurs Ruud van Heeswijk et Matthias Stuber, a également été publiée dans le journal MRM. La troisième, "A cylindrical, inner volume selecting 2D-T2-Prep improves GRAPPA- accelerated image quality in MRA of the right coronary artery", écrite avec les co-auteurs Jérôme Yerly et Matthias Stuber, a été présentée au "Journal of Cardiovascular Magnetic Resonance", et la quatrième, "Combined respiratory self-navigation and 'pencil-beam' 2D-T2 -Prep for free-breathing, whole-heart coronary MRA", avec les co-auteurs Jérôme Chaptinel, Giulia Ginami, Gabriele Bonanno , Simone Coppo, Ruud van Heeswijk, Davide Piccini, et Matthias Stuber, subit un examen interne avant la soumission à la revue MRM.