347 research outputs found

    Towards a homogenization of the long-term surface solar global radiation series over Europe

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    Póster elaborado para la European Geosciences Union General Assembly, celebrada en Viena del 3 al 8 de abril de 2011This research was supported by the Spanish Ministry of Science and Innovation project NUCLIERSOL (CGL2010- 18546). The first author was granted by a postdoctoral position funded by the government of Catalonia (2009 BP-A 00035)

    Imaging techniques in Veterinary Medicine. Part I: Radiography and Ultrasonography

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    In Veterinary Medicine all the Imaging techniques are used and described but, due to organizational, managerial and, mostly, economical reasons, Radiography and Ultrasonography are the most used. Veterinary Radiology teaching has a relatively small number of educational credits in the degree courses but, nowday, educational opportunities are remarkably increased thanks to a number of post-degree courses and masters, organized both by the universities and private veterinary associations. The relevance of Diagnostic Imaging is particularly true in Veterinary Medicine, in which Radiology could be considered “indispensable” for diagnosis, prognosis and follow up. Furthermore, it should not be forgotten that the diagnostic image represents a “document” and, has a relevant role in legal medical debats. In this first part, Radiography and Ultrasonography are described

    differential diagnosis of benign and malignant vertebral compression fractures using conventional and advanced mri techniques

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    Atraumatic vertebral compression fractures (VCFs) are commonly encountered in clinical practice and often represent a diagnostic challenge. MRI plays a major role in the differential diagnosis of benign and malignant VCFs, due to its high contrast resolution and the possibility to obtain quantitative and functional data with the employment of advanced sequences. Computer-aided diagnosis systems are also applied on MRI images for this purpose, showing promising results. In this setting, aim of this pictorial review is to elucidate the role of MRI in the differential diagnosis of VCFs with a specific focus on advanced and post-processing imaging techniques

    Analysis of the human interaction with a wearable lower-limb exoskeleton

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    The design of a wearable robotic exoskeleton needs to consider the interaction, either physical or cognitive, between the human user and the robotic device. This paper presents a method to analyse the interaction between the human user and a unilateral, wearable lower-limb exoskeleton. The lower-limb exoskeleton function was to compensate for muscle weakness around the knee joint. It is shown that the cognitive interaction is bidirectional; on the one hand, the robot gathered information from the sensors in order to detect human actions, such as the gait phases, but the subjects also modified their gait patterns to obtain the desired responses from the exoskeleton. The results of the two-phase evaluation of learning with healthy subjects and experiments with a patient case are presented, regarding the analysis of the interaction, assessed in terms of kinematics, kinetics and/or muscle recruitment. Human-driven response of the exoskeleton after training revealed the improvements in the use of the device, while particular modifications of motion patterns were observed in healthy subjects. Also, endurance (mechanical) tests provided criteria to perform experiments with one post-polio patient. The results with the post-polio patient demonstrate the feasibility of providing gait compensation by means of the presented wearable exoskeleton, designed with a testing procedure that involves the human users to assess the human-robot interaction

    Oncologic Imaging and Radiomics: A Walkthrough Review of Methodological Challenges

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    Imaging plays a crucial role in the management of oncologic patients, from the initial diagnosis to staging and treatment response monitoring. Recently, it has been suggested that its importance could be further increased by accessing a new layer of previously hidden quantitative data at the pixel level. Using a multi-step process, radiomics extracts potential biomarkers from medical images that could power decision support tools. Despite the growing interest and rising number of research articles being published, radiomics is still far from fulfilling its promise of guiding oncologic imaging toward personalized medicine. This is, at least partly, due to the heterogeneous methodological quality in radiomic research, caused by the complexity of the analysis pipelines. In this review, we aim to disentangle this complexity with a stepwise approach. Specifically, we focus on challenges to face during image preprocessing and segmentation, how to handle imbalanced classes and avoid information leaks, as well as strategies for the proper validation of findings

    Intracranial extension of orbital inflammatory pseudotumor: a case report and literature review

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    Background: Orbital inflammatory pseudotumor is a rare inflammatory condition of unknown cause that may extend intracranially, usually as a dural-based infiltrate. Here we report the first case of orbital pseudotumor presenting with intra-axial Magnetic Resonance Imaging (MRI) changes. Case presentation: A 57-year-old white female, with a 3-month history of headache and right palpebral edema, presented with marked right temporal lobe edema with ominous MRI appearance, and ipsilateral alterations of orbital and periorbital structures. Following steroid therapy, both intracranial and orbital involvement dramatically improved. Conclusion: Orbital inflammatory pseudotumor with chronic inflammation may infrequently present with intracranial involvement, mimicking more aggressive diseases, even showing intra-axial enhancement after i.v. contrast administration in brain MRI. Awareness of this possibility may help neurologists to choose the appropriate therapeutic approach

    Updating and extending the “dimming” and “brightening” over Spain

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    Póster elaborado para la European Geosciences Union General Assembly, celebrada en Viena del 3 al 8 de abril de 2011Ministerio de Ciencia e Innovación. Proyecto NUCLIERSOL (CGL2010- 18546

    Atorvastatin combined to interferon to verify the efficacy (ACTIVE) in relapsing-remitting active multiple sclerosis patients: a longitudinal controlled trial of combination therapy.

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    A large body of evidence suggests that, besides their cholesterol-lowering effect, statins exert anti-inflammatory action. Consequently, statins may have therapeutic potential in immune-mediated disorders such as multiple sclerosis. Our objectives were to determine safety, tolerability and efficacy of low-dose atorvastatin plus high-dose interferon beta-1a in multiple sclerosis patients responding poorly to interferon beta-1a alone. Relapsing–remitting multiple sclerosis patients, aged 18–50 years, with contrast-enhanced lesions or relapses while on therapy with interferon beta-1a 44 mg (three times weekly) for 12 months, were randomized to combination therapy (interferon+atorvastatin 20mg per day; group A) or interferon alone (group B) for 24 months. Patients underwent blood analysis and clinical assessment with the Expanded Disability Status Scale every 3 months, and brain gadolinium-enhanced magnetic resonance imaging at screening, and 12 and 24 months thereafter. Primary outcome measure was contrast-enhanced lesion number. Secondary outcome measures were number of relapses, EDSS variation and safety laboratory data. Forty-five patients were randomized to group A (n 1⁄4 21) or B (n 1⁄4 24). At 24 months, group A had significantly fewer contrast-enhanced lesions versus baseline (p 1⁄4 0.007) and significantly fewer relapses versus the two pre-randomization years (p < 0.001). At survival analysis, the risk for a 1-point EDSS increase was slightly higher in group B than in group A (p 1⁄4 0.053). Low-dose atorvastatin may be beneficial, as add-on therapy, in poor responders to high-dose interferon beta-1a alone

    State of the art in abdominal MRI structured reporting: a review

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    In the management of several abdominal disorders, magnetic resonance imaging (MRI) has the potential to significantly improve patient's outcome due to its diagnostic accuracy leading to more appropriate treatment choice. However, its clinical value heavily relies on the quality and quantity of diagnostic information that radiologists manage to convey through their reports. To solve issues such as ambiguity and lack of comprehensiveness that can occur with conventional narrative reports, the adoption of structured reporting has been proposed. Using a checklist and standardized lexicon, structured reports are designed to increase clarity while assuring that all key imaging findings related to a specific disorder are included. Unfortunately, structured reports have their limitations too, such as risk of undue report simplification and poor template plasticity. Their adoption is also far from widespread, and probably the ideal balance between radiologist autonomy and report consistency of has yet to be found. In this article, we aimed to provide an overview of structured reporting proposals for abdominal MRI and of works assessing its value in comparison to conventional free-text reporting. While for several abdominal disorders there are structured templates that have been endorsed by scientific societies and their adoption might be beneficial, stronger evidence confirming their imperativeness and added value in terms of clinical practice is needed, especially regarding the improvement of patient outcome

    Meningioma MRI radiomics and machine learning: systematic review, quality score assessment, and meta-analysis

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    Purpose To systematically review and evaluate the methodological quality of studies using radiomics for diagnostic and predictive purposes in patients with intracranial meningioma. To perform a meta-analysis of machine learning studies for the prediction of intracranial meningioma grading from pre-operative brain MRI. Methods Articles published from the year 2000 on radiomics and machine learning applications in brain imaging of meningioma patients were included. Their methodological quality was assessed by three readers with the radiomics quality score, using the intra-class correlation coefficient (ICC) to evaluate inter-reader reproducibility. A meta-analysis of machine learning studies for the preoperative evaluation of meningioma grading was performed and their risk of bias was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool. Results In all, 23 studies were included in the systematic review, 8 of which were suitable for the meta-analysis. Total (possible range, −8 to 36) and percentage radiomics quality scores were respectively 6.96 ± 4.86 and 19 ± 13% with a moderate to good inter-reader reproducibility (ICC = 0.75, 95% confidence intervals, 95%CI = 0.54–0.88). The meta-analysis showed an overall AUC of 0.88 (95%CI = 0.84–0.93) with a standard error of 0.02. Conclusions Machine learning and radiomics have been proposed for multiple applications in the imaging of meningiomas, with promising results for preoperative lesion grading. However, future studies with adequate standardization and higher methodological quality are required prior to their introduction in clinical practice
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