17 research outputs found

    ASAP (Automatic Software for ASL Processing): A toolbox for processing Arterial Spin Labeling images

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    The method of Arterial Spin Labeling (ASL) has experienced a significant rise in its application to functional imaging, since it is the only technique capable of measuring blood perfusion in a truly non-invasive manner. Currently, there are no commercial packages for processing ASL data and there is no recognised standard for normalising ASL data to a common frame of reference. This work describes a new Automated Software for ASL Processing (ASAP) that can automatically process several ASL datasets. ASAP includes functions for all stages of image pre-processing: quantification, skull-stripping, co-registration, partial volume correction and normalization. To assess the applicability and validity of the toolbox, this work shows its application in the study of hypoperfusion in a sample of healthy subjects at risk of progressing to Alzheimer's Disease. ASAP requires limited user intervention, minimising the possibility of random and systematic errors, and produces cerebral blood flow maps that are ready for statistical group analysis. The software is easy to operate and results in excellent quality of spatial normalisation. The results found in this evaluation study are consistent with previous studies that find decreased perfusionComment: 10 pages, 8 figures, 3 table

    Application for Decision-Making on Mild Cognitive Impairments

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    Presented at the 4th XoveTIC Conference, A Coruña, Spain, 7–8 October 2021.[Abstract] Life expectancy in Western countries is increasing. The fact that humans are living longer lives presents new challenges to people’s quality of life. Some of the problems that most affect older people are the problems associated with cognitive impairment. The development of a tool that helps psychologists to carry out different types of tests is the main objective of this work. To this end, an interdisciplinary group of psychologists and engineers have joined forces to create a tool that generates a series of standardised metrics to guide clinicians and help them make decisions about a patient’s cognitive impairment

    Effect of water T2 shortening in the quantification of in-vitro proton MR spectroscopy

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    Short communication[Abstract] PURPOSE. This work studies the relationship between in-vitro Proton Magnetic Resonance Spectroscopy metabolite quantification and water T2 decay. MATERIALS AND METHODS. An in-vitro correspondence is established between the iron accumulation and the shortening of water T2 relaxation times using seven spherical phantoms, 6 of them were doped with an increasing concentration of iron metal nanoparticles solution. This is later proposed as a source of error during the LCModel metabolite quantification of either absolute concentrations or ratios. RESULTS. The Pearson's correlation coefficient between water T2 values against absolute metabolite concentrations was on average [r] = 0.97 and on average [r] = 0.85 for metabolite ratios. CONCLUSION. These results suggest that the shortening of T2 values should be taken into account when performing metabolite quantification. Also, the need of demonstrated similar results in in-vivo studies, since the presence of iron deposits or other factors affecting the water T2 decay measurements could explain part of the inter-subject variability in the metabolite concentration and ratio quantification

    The partial volume effect in the quantification of 1H magnetic resonance spectroscopy in Alzheimer's disease and aging

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    [Abstract] 1H-MRS variability increases due to normal aging and also as a result of atrophy in grey and white matter caused by neurodegeneration. In this work, an automatic process was developed to integrate data from spectra and high-resolution anatomical images to quantify metabolites, taking into account tissue partial volumes within the voxel of interest avoiding additional spectra acquisitions required for partial volume correction. To evaluate this method, we use a cohort of 135 subjects (47 male and 88 female, aged between 57 and 99 years) classified into 4 groups: 38 healthy participants, 20 amnesic mild cognitive impairment patients, 22 multi-domain mild cognitive impairment patients, and 55 Alzheimer's disease patients. Our findings suggest that knowing the voxel composition of white and grey matter and cerebrospinal fluid is necessary to avoid partial volume variations in a single-voxel study and to decrease part of the variability found in metabolites quantification, particularly in those studies involving elder patients and neurodegenerative diseases. The proposed method facilitates the use of 1H-MRS techniques in statistical studies in Alzheimer's disease, because it provides more accurate quantitative measurements, reduces the inter-subject variability, and improves statistical results when performing group comparisons

    A data mining approach for classification of orthostatic and essential tremor based on MRI‐derived brain volume and cortical thickness

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    [Abstract] Objective - Orthostatic tremor (OT) is an extremely rare, misdiagnosed, and underdiagnosed disorder affecting adults in midlife. There is debate as to whether it is a different condition or a variant of essential tremor (ET), or even, if both conditions coexist. Our objective was to use data mining classification methods, using magnetic resonance imaging (MRI)‐derived brain volume and cortical thickness data, to identify morphometric measures that help to discriminate OT patients from those with ET. Methods - MRI‐derived brain volume and cortical thickness were obtained from 14 OT patients and 15 age‐, sex‐, and education‐matched ET patients. Feature selection and machine learning methods were subsequently applied. Results - Four MRI features alone distinguished the two, OT from ET, with 100% diagnostic accuracy. More specifically, left thalamus proper volume (normalized by the total intracranial volume), right superior parietal volume, right superior parietal thickness, and right inferior parietal roughness (i.e., the standard deviation of cortical thickness) were shown to play a key role in OT and ET characterization. Finally, the left caudal anterior cingulate thickness and the left caudal middle frontal roughness allowed us to separate with 100% diagnostic accuracy subgroups of OT patients (primary and those with mild parkinsonian signs). Conclusions - A data mining approach applied to MRI‐derived brain volume and cortical thickness data may differentiate between these two types of tremor with an accuracy of 100%. Our results suggest that OT and ET are distinct conditions.National Institutes of Health (United States); #R01, NS39422National Institutes of Health (United States), #R01, NS094607National Institutes of Health (United States); #R01, NS085136National Institutes of Health (United States); #R01, NS073872National Institutes of Health (United States); #R01, NS085136National Institutes of Health (United States); #R01, NS088257European Commission; ICT‐2011‐287739Ministerio de Economía y Competitividad; RTC‐2015‐3967‐1Agencia Española de Investigación de la Salud; FIS PI12/01602Agencia Española de Investigación de la Salud; FIS PI16/00451Madrid Robotics Digital Innovation Hub; S2018/NMT‐433

    Classification of mild cognitive impairment and Alzheimer’s Disease with machine-learning techniques using 1H Magnetic Resonance Spectroscopy data

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    [Abstract] Several magnetic resonance techniques have been proposed as non-invasive imaging biomarkers for the evaluation of disease progression and early diagnosis of Alzheimer’s Disease (AD). This work is the first application of the Proton Magnetic Resonance Spectroscopy 1H-MRS data and machine-learning techniques to the classification of AD. A gender-matched cohort of 260 subjects aged between 57 and 99 years from the Alzheimer’s Disease Research Unit, of the Fundación CIEN-Fundación Reina Sofía has been used. A single-layer perceptron was found for AD prediction with only two spectroscopic voxel volumes (Tvol and CSFvol) in the left hippocampus, with an AUROC value of 0.866 (with TPR 0.812 and FPR 0.204) in a filter feature selection approach. These results suggest that knowing the composition of white and grey matter and cerebrospinal fluid of the spectroscopic voxel is essential in a 1H-MRS study to improve the accuracy of the quantifications and classifications, particularly in those studies involving elder patients and neurodegenerative diseases.Instituto de Salud Carlos III; PI13/0028

    Diffusion tensor imaging in orthostatic tremor: a tract‐based spatial statistics study

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    [Abstract] Objective The pathogenesis of orthostatic tremor (OT) is unknown. We investigated OT‐related white matter changes and their correlations with scores from a neuropsychological testing battery. Methods Diffusion tensor imaging measures were compared between 14 OT patients and 14 age‐ and education‐matched healthy controls, using whole‐brain tract‐based spatial statistics analysis. Correlations between altered diffusion metrics and cognitive performance in OT group were assessed. Results In all cognitive domains (attention, executive function, visuospatial ability, verbal memory, visual memory, and language), OT patients’ cognitive performance was significantly worse than that of healthy controls. OT patients demonstrated altered diffusivity metrics not only in the posterior lobe of the cerebellum (left cerebellar lobule VI) and in its efferent cerebellar fibers (left superior cerebellar peduncle), but also in medial lemniscus bilaterally (pontine tegmentum), anterior limb of the internal capsule bilaterally, right posterior limb of the internal capsule, left anterior corona radiata, right insula, and the splenium of corpus callosum. No relationship was found between diffusion measures and disease duration in OT patients. Diffusion white matter changes, mainly those located in right anterior limb of the internal capsule, were correlated with poor performance on tests of executive function, visuospatial ability, verbal memory, and visual memory in OT patients. Interpretation White matter changes were preferentially located in the cerebellum, its efferent pathways, as well as in the pontine tegmentum and key components of the frontal–thalamic–cerebellar circuit. Further work needs to be done to understand the evolution of these white matter changes and their functional consequences.National Institutes of Health; R01 NS39422National Institutes of Health; R01 NS094607National Institutes of Health; R01 NS085136National Institutes of Health; R01 NS073872National Institutes of Health; R01 NS088257European Commission. Grant Number: ICT‐2011‐287739Ministerio de Ecnomía y Competitividad; RTC‐2015‐3967‐1Spanish Health Research Agency; FIS PI12/01602Spanish Health Research Agency; FIS PI16/00451Ministerio de Ecnomía y Competitividad; DPI‐2015‐68664‐C4‐1‐

    Environmental Sustainability in Information Technologies Governance

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    [Abstract] In the present day, many risk factors affect the continuity of a business. However, this situation produces a conducive atmosphere to approach alternatives that relieve this situation for organizations. Within these alternatives, environmental sustainability (ES) and information technologies governance (IT governance or ITG) stand out. Both alternatives allow organizations to address intrinsically common issues such as strategic alignment, generation of value, mechanisms for performance improvement, risk management and resource management. This article focuses on the fusion of both alternatives, determining to what extent current ITG models consider ES issues. With this purpose, the strategy followed was firstly to identify the relevant factors of ES present in the main approaches of the domain (ISO14001, GRI G4, EMAS, SGE21 and ISO26000). As a result, we identified 27 activities and 103 sub-activities of ES. Next, as the second main objective, we determined which of those factors are present in the main current ITG approaches (COBIT5, ISO38500 and WEILL & ROSS). Finally, we concluded through a quantitative study that COBIT5 is the most sustainable (i.e., the one that incorporates more ES issues) ITG approach

    Diffusion tensor imaging in orthostatic tremor: a tract-based spatial statistics study.

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    Objective: The pathogenesis of orthostatic tremor (OT) is unknown. We investigated OT-related white matter changes and their correlations with scores from a neuropsychological testing battery. Methods: Diffusion tensor imaging measures were compared between 14 OT patients and 14 age- and educationmatched healthy controls, using whole-brain tract-based spatial statistics analysis. Correlations between altered diffusion metrics and cognitive performance in OT group were assessed. Results: In all cognitive domains (attention, executive function, visuospatial ability, verbal memory, visual memory, and language), OT patients’ cognitive performance was significantly worse than that of healthy controls. OT patients demonstrated altered diffusivity metrics not only in the posterior lobe of the cerebellum (left cerebellar lobule VI) and in its efferent cerebellar fibers (left superior cerebellar peduncle), but also in medial lemniscus bilaterally (pontine tegmentum), anterior limb of the internal capsule bilaterally, right posterior limb of the internal capsule, left anterior corona radiata, right insula, and the splenium of corpus callosum. No relationship was found between diffusion measures and disease duration in OT patients. Diffusion white matter changes, mainly those located in right anterior limb of the internal capsule, were correlated with poor performance on tests of executive function, visuospatial ability, verbal memory, and visual memory in OT patients. Interpretation: White matter changes were preferentially located in the cerebellum, its efferent pathways, as well as in the pontine tegmentum and key components of the frontal–thalamic–cerebellar circuit. Further work needs to be done to understand the evolution of these white matter changes and their functional consequences.post-print404 K

    In vivo neurometabolic profiling in orthostatic tremor

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    The pathogenesis of orthostatic tremor (OT) remains unclear, although some evidence points to dysfunction in the brainstem or cerebellum. We used single voxel proton magnetic resonance spectroscopy (1H-MRS) (3 T) to investigate whether neurochemical changes underlie abnormal cerebellar or cortical function in OT. Fourteen OT patients and 14 healthy controls underwent 1H-MRS studies with voxels placed in midparietal gray matter and cerebellum (vermis and central white matter). Spectral analysis was analyzed using the software package LCModel (version 6.3). The absolute metabolite concentrations and ratios of total N-acetylaspartate + N-acetylaspartyl glutamate (NAA), choline-containing compounds, myoinositol, and glutamate + glutamine to creatine were calculated. In midparietal gray matter spectra, we found a significant decrease in the absolute concentration of NAA in OT patients versus healthy controls (7.76 ± 0.25 vs 8.11 ± 0.45, P = 0.017). A similar decrease in NAA was seen in the cerebellar vermis (7.33 ± 0.61 vs 8.55 ± 1.54, P = 0.014) and cerebellar white matter (8.54 ± 0.79 vs 9.95 ± 1.57, P = 0.010). No differences in the other metabolites or their ratios were observed. Reductions in both cerebral cortical and cerebellar NAA suggest that there is neuronal damage or loss in OT, raising the intriguing question as to whether OT is a neurodegenerative disease. Along with clinical history and electrophysio0logical examination, 1H-MRS could serve as a useful diagnostic aid for OT
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