195 research outputs found

    Frequency offset corrected inversion (FOCI) pulses for use in localized spectroscopy

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    Gradient localized spectroscopy techniques suffer from a well documented spatial localization error caused by the difference in chemical shifts between resonances. This results in the acquisition of spectra from partially overlapping spatial regions of the sample, with each resonance representing a different region. The image-selected in vivo spectroscopy technique uses hyperbolic secant inversion pulses, where the main limitation in reducing this error is in the RF power available for application of the selective RF pulse. This spatial localization error may be dramatically reduced by increasing, and temporally shaping, the gradient pulse during slice-selective spin inversion. The performance of these RF pulses have been experimentally verified

    Reconstruction of multi-generation pedigrees involving numerous old apple cultivars thanks to whole-genome SNP data

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    A number of European apple cultivars are old, some of them dating back to the Renaissance, Middle Ages or even earlier. Many other cultivars have been developed during subsequent times. In order to decipher the relationships that link some of these old cultivars, whole-genome SNP data (~ 250K) for over 1400 genotypes were analyzed to infer first-degree relationships and reconstruct pedigrees. We used simple exclusion tests based on a count of Mendelian error to identify up to a thousand potential parent-offspring duos, including 295 complete parent-offspring trios and a hundred duos that could be oriented. grand-parents for some missing parents could also be inferred. Combining all this information allowed us to reconstruct pedigrees (up to 6 generations) highlighting the central role of major founders such as ‘Reinette Franche’, ‘Margil’, and ‘Alexander’. Haplotypes were deduced from genotypic data and pedigrees, and used to measure haplotype sharing between supposedly unrelated cultivars, allowing investigating further links between them.To our knowledge, such a large analysis to reconstruct multigeneration pedigrees involving (very) old cultivars selected over such time has never before been performed in perennial fruit species

    Clinical impairment in premanifest and early Huntington's disease is associated with regionally specific atrophy.

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    TRACK-HD is a multicentre longitudinal observational study investigating the use of clinical assessments and 3-Tesla magnetic resonance imaging as potential biomarkers for future therapeutic trials in Huntington's disease (HD). The cross-sectional data from this large well-characterized dataset provide the opportunity to improve our knowledge of how the underlying neuropathology of HD may contribute to the clinical manifestations of the disease across the spectrum of premanifest (PreHD) and early HD. Two hundred and thirty nine gene-positive subjects (120 PreHD and 119 early HD) from the TRACK-HD study were included. Using voxel-based morphometry (VBM), grey and white matter volumes were correlated with performance in four domains: quantitative motor (tongue force, metronome tapping, and gait); oculomotor [anti-saccade error rate (ASE)]; cognition (negative emotion recognition, spot the change and the University of Pennsylvania smell identification test) and neuropsychiatric measures (apathy, affect and irritability). After adjusting for estimated disease severity, regionally specific associations between structural loss and task performance were found (familywise error corrected, P < 0.05); impairment in tongue force, metronome tapping and ASE were all associated with striatal loss. Additionally, tongue force deficits and ASE were associated with volume reduction in the occipital lobe. Impaired recognition of negative emotions was associated with volumetric reductions in the precuneus and cuneus. Our study reveals specific associations between atrophy and decline in a range of clinical modalities, demonstrating the utility of VBM correlation analysis for investigating these relationships in HD

    Quantifying the area-at-risk of myocardial infarction in-vivo using arterial spin labeling cardiac magnetic resonance

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    © The Author(s) 2017.T2-weighted cardiovascular magnetic resonance (T2-CMR) of myocardial edema can quantify the area-at-risk (AAR) following acute myocardial infarction (AMI), and has been used to assess myocardial salvage by new cardioprotective therapies. However, some of these therapies may reduce edema, leading to an underestimation of the AAR by T2-CMR. Here, we investigated arterial spin labeling (ASL) perfusion CMR as a novel approach to quantify the AAR following AMI. Adult B6sv129-mice were subjected to in vivo left coronary artery ligation for 30 minutes followed by 72 hours reperfusion. T2-mapping was used to quantify the edema-based AAR (% of left ventricle) following ischemic preconditioning (IPC) or cyclosporin-A (CsA) treatment. In control animals, the AAR by T2-mapping corresponded to that delineated by histology. As expected, both IPC and CsA reduced MI size. However, IPC, but not CsA, also reduced myocardial edema leading to an underestimation of the AAR by T2-mapping. In contrast, regions of reduced myocardial perfusion delineated by cardiac ASL were able to delineate the AAR when compared to both T2-mapping and histology in control animals, and were not affected by either IPC or CsA. Therefore, ASL perfusion CMR may be an alternative method for quantifying the AAR following AMI, which unlike T2-mapping, is not affected by IPC

    Reliability of dynamic contrast-enhanced magnetic resonance imaging data in primary brain tumours: a comparison of Tofts and shutter speed models

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    Purpose To investigate the robustness of pharmacokinetic modelling of DCE-MRI brain tumour data and to ascertain reliable perfusion parameters through a model selection process and a stability test. Methods DCE-MRI data of 14 patients with primary brain tumours were analysed using the Tofts model (TM), the extended Tofts model (ETM), the shutter speed model (SSM) and the extended shutter speed model (ESSM). A no-effect model (NEM) was implemented to assess overfitting of data by the other models. For each lesion, the Akaike Information Criteria (AIC) was used to build a 3D model selection map. The variability of each pharmacokinetic parameter extracted from this map was assessed with a noise propagation procedure, resulting in voxel-wise distributions of the coefficient of variation (CV). Results The model selection map over all patients showed NEM had the best fit in 35.5% of voxels, followed by ETM (32%), TM (28.2%), SSM (4.3%) and ESSM (<0.1%). In analysing the reliability of Ktrans, when considering regions with a CV<20%, ≈25% of voxels were found to be stable across all patients. The remaining 75% of voxels were considered unreliable. Conclusions The majority of studies quantifying DCE-MRI data in brain tumours only consider a single model and whole-tumour statistics for the output parameters. Appropriate model selection, considering tissue biology and its effects on blood brain barrier permeability and exchange conditions, together with an analysis on the reliability and stability of the calculated parameters, is critical in processing robust brain tumour DCE-MRI data

    Optimized EPI for fMRI studies of the orbitofrontal cortex: compensation of susceptibility-induced gradients in the readout direction

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    Object Most functional magnetic resonance imaging (fMRI) studies record the blood oxygen leveldependent (BOLD) signal using gradient-echo echo-planar imaging (GE EPI). EPI can suffer from substantial BOLD sensitivity loss caused by magnetic field inhomogeneities. Here, BOLD sensitivity losses due to susceptibility- induced gradients in the readout (RO) direction are characterized and a compensation approach is developed

    SSR-Based Analysis of Genetic Diversity and Structure of Sweet Cherry (Prunus avium L.) from 19 Countries in Europe

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    Sweet cherry (Prunus avium L.) is a temperate fruit species whose production might be highly impacted by climate change in the near future. Diversity of plant material could be an option to mitigate these climate risks by enabling producers to have new cultivars well adapted to new environmental conditions. In this study, subsets of sweet cherry collections of 19 European countries were genotyped using 14 SSR. The objectives of this study were (i) to assess genetic diversity parameters, (ii) to estimate the levels of population structure, and (iii) to identify germplasm redundancies. A total of 314 accessions, including landraces, early selections, and modern cultivars, were monitored, and 220 unique SSR genotypes were identified. All 14 loci were confirmed to be polymorphic, and a total of 137 alleles were detected with a mean of 9.8 alleles per locus. The average number of alleles (N = 9.8), PIC value (0.658), observed heterozygosity (Ho = 0.71), and expected heterozygosity (He = 0.70) were higher in this study compared to values reported so far. Four ancestral populations were detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA), and two of them (K1 and K4) could be attributed to the geographical origin of the accessions. A N-J tree grouped the 220 sweet cherry accessions within three main clusters and six subgroups. Accessions belonging to the four STRUCTURE populations roughly clustered together. Clustering confirmed known genealogical data for several accessions. The large genetic diversity of the collection was demonstrated, in particular within the landrace pool, justifying the efforts made over decades for their conservation. New sources of diversity will allow producers to face challenges, such as climate change and the need to develop more sustainable production systems
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