Linear intensity normalization of DaTSCAN images using Mean Square Error and a model-based clustering approach.

The analysis of 3D SPECT brain images requires several pre-processing steps such as intensity normalization and brain feature extraction. In this sense, a new method for intensity normalization of I-ioflupane-SPECT (DaTSCAN) brain images based on minimization of the Mean Square Error (MSE) between the Gaussian Mixture Model (GMM)-based extracted features from each subject image and a template in the so-defined non-specific region is derived. Our approach to feature extraction consists of using the set of parameters that define the template features, such as weights, covariance matrices and mean vectors to model the remaining images by reducing, consequently their dimensionality.

Projecting MRI brain images for the detection of Alzheimer's Disease.

Recent advances in the process of diagnosis of neurodegenerative diseases, such as Alzheimer's Disease, rely on the use of molecular imaging that allow the interpretation of different metabolic biomarkers in the brain. However these procedures are considered of invasive nature, as they involve the injection of radioactive markers. On the other hand, Magnetic Resonance Imaging (MRI) is perhaps the most widely used and less invasive medical imaging technique, although its ability to detect Alzheimer's Disease has revealed limited.

Affine registration of [123I]FP-CIT SPECT brain images.

In this work, we perform a comparison between the spatial normalization of [123I]FP-CIT SPECT brain images when a FP-CIT SPECT and a MRI template are used. A 12-parameters affine registration model is calculated by the optimization of a sum of squares cost function. When the images are registered to a FP-CIT template, the intersubject variation is found to be lower than when the MRI template is used, specially in the striatum, which is the most relevant part of the brain in FP-CIT SPECT brain images.

Gated Sensor Fusion: A way to Improve the Precision of Ambulatory Human Body Motion Estimation.

Human body motion is usually variable in terms of intensity and, therefore, any Inertial Measurement Unit attached to a subject will measure both low and high angular rate and accelerations. This can be a problem for the accuracy of orientation estimation algorithms based on adaptive filters such as the Kalman filter, since both the variances of the process noise and the measurement noise are set at the beginning of the algorithm and remain constant during its execution. Setting fixed noise parameters burdens the adaptation capability of the filter if the intensity of the motion changes rapidly.

Statistical significance in the selection of the regions of interest for Parkinson brain image processing.

This paper presents the analysis of the statistical significance in the selection of the ROI for the discriminant analysis of brain images to identify Parkinson patients or subjects without any pathology. The particular features and brain functional patterns of the Parkinson's disease cause that there are regions that conveniently reveal the presence of the pathology, in this case mainly the striatum region. The selection of the brain mask makes incidence in two main aspects: the selection of the region of interest (striatum and surrounding area) for the analysis, but also the selection of the region without significance, which is the reference area for the intensity normalization, previous to the analysis.

Multimodal image data fusion for Alzheimer's Disease diagnosis by sparse representation.

Alzheimer's Diasese (AD) diagnosis can be carried out by analysing functional or structural changes in the brain. Functional changes associated to neurological disorders can be figured out by positron emission tomography (PET) as it allows to study the activation of certain areas of the brain during specific task development. On the other hand, neurological disorders can also be discovered by analysing structural changes in the brain which are usually assessed by Magnetic Resonance Imaging (MRI).

Consensus document on the management of renal disease in HIV-infected patients.

Objective: To update the 2010 recommendations on the evaluation and management of renal disease in HIV-infected patients.

Methods: This document was approved by a panel of experts from the AIDS Working Group (GESIDA) of the Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC), the Spanish Society of Nephrology (S.E.

Executive summary of the consensus document on the management of renal disease in HIV-infected patients.

The aim of this article is to update the 2010 recommendations on the evaluation and management of renal disease in HIV-infected patients. Renal function should be monitored in all HIV-infected patients. The basic renal work-up should include measurements of serum creatinine, estimated glomerular filtration rate by CKD-EPI, urine protein-to-creatinine ratio, and urinary sediment.

Real time QRS detection based on M-ary likelihood ratio test on the DFT coefficients.

This paper shows an adaptive statistical test for QRS detection of electrocardiography (ECG) signals. The method is based on a M-ary generalized likelihood ratio test (LRT) defined over a multiple observation window in the Fourier domain. The motivations for proposing another detection algorithm based on maximum a posteriori (MAP) estimation are found in the high complexity of the signal model proposed in previous approaches which i) makes them computationally unfeasible or not intended for real time applications such as intensive care monitoring and (ii) in which the parameter selection conditions the overall performance.

[Executive summary of the recommendations on the evaluation and management of renal disease in human immunodeficiency virus-infected patients].

The aim of this article is to update the 2010 recommendations on the evaluation and management of renal disease in human immunodeficiency virus (HIV)-infected patients. Renal function should be monitored in all HIV-infected patients. The basic renal work-up should include measurements of serum creatinine, estimated glomerular filtration rate by CKD-EPI, urine protein-to-creatinine ratio, and urinary sediment.

[Consensus document for the detection and management of chronic kidney disease].

Chronic kidney disease (CKD) is an important global health problem, involving to 10% of the Spanish population, promoting high morbidity and mortality for the patient and an elevate consumption of the total health resources for the National Health System. This is a summary of an executive consensus document of ten scientific societies involved in the care of the renal patient, that actualizes the consensus document published in 2007. The central extended document can be consulted in the web page of each society.

[Consensus document for the detection and management of chronic kidney disease].

Chronic kidney disease (CKD) is an important global health problem, involving to 10% of the Spanish population, promoting high morbidity and mortality for the patient and an elevate consumption of the total health resources for the National Health System. This is a summary of an executive consensus document of ten scientific societies involved in the care of the renal patient, that actualizes the consensus document published in 2007. The central extended document can be consulted in the web page of each society.

[Consensus document for the detection and management of chronic kidney disease].

Chronic kidney disease (CKD) is an important global health problem, involving to 10% of the Spanish population, promoting high morbidity and mortality for the patient and an elevate consumption of the total health resources for the National Health System. This is a summary of an executive consensus document of ten scientific societies involved in the care of the renal patient, that actualizes the consensus document published in 2007. The central extended document can be consulted in the web page of each society.

Identifying endophenotypes of autism: a multivariate approach.

The existence of an endophenotype of autism spectrum condition (ASC) has been recently suggested by several commentators. It can be estimated by finding differences between controls and people with ASC that are also present when comparing controls and the unaffected siblings of ASC individuals. In this work, we used a multivariate methodology applied on magnetic resonance images to look for such differences.

Diabetic kidney disease: from physiology to therapeutics.

Diabetic kidney disease (DKD) defines the functional, structural and clinical abnormalities of the kidneys that are caused by diabetes. This complication has become the single most frequent cause of end-stage renal disease. The pathophysiology of DKD comprises the interaction of both genetic and environmental determinants that trigger a complex network of pathophysiological events, which leads to the damage of the glomerular filtration barrier, a highly specialized structure formed by the fenestrated endothelium, the glomerular basement membrane and the epithelial podocytes, that permits a highly selective ultrafiltration of the blood plasma.

Spanish Society of Nephrology document on KDIGO guidelines for the assessment and treatment of chronic kidney disease.

The new Kidney Disease: Improving Global Outcomes (KDIGO) international guidelines on chronic kidney disease (CKD) and the management of blood pressure (BP) in CKD patients are an update of the corresponding 2002 and 2004 KDOQI (Kidney Disease Outcomes Quality Initiative) guidelines. The documents aim to provide updated guidelines on the assessment, management and treatment of patients with CKD. The first guidelines retain the 2002 definition of CKD but present an improved prognosis classification.

Automatic ROI selection in structural brain MRI using SOM 3D projection.

This paper presents a method for selecting Regions of Interest (ROI) in brain Magnetic Resonance Imaging (MRI) for diagnostic purposes, using statistical learning and vector quantization techniques. The proposed method models the distribution of GM and WM tissues grouping the voxels belonging to each tissue in ROIs associated to a specific neurological disorder. Tissue distribution of normal and abnormal images is modelled by a Self-Organizing map (SOM), generating a set of representative prototypes, and the receptive field (RF) of each SOM prototype defines a ROI.

Consensus document for the detection and management of chronic kidney disease.

Chronic kidney disease (CKD) is a major public health problem that, in its different stages, may affect up to 10% of the Spanish population and results in high morbidity and mortality, as well as high consumption of National Health System resources. Ten scientific societies involved in the management of kidney patients agreed to update the 2007 CKD consensus document. The current version is an abridged edition of the detailed general document, which can be consulted on the webpages of each signatory society.

Regions of interest computed by SVM wrapped method for Alzheimer's disease examination from segmented MRI.

Accurate identification of the most relevant brain regions linked to Alzheimer's disease (AD) is crucial in order to improve diagnosis techniques and to better understand this neurodegenerative process. For this purpose, statistical classification is suitable. In this work, a novel method based on support vector machine recursive feature elimination (SVM-RFE) is proposed to be applied on segmented brain MRI for detecting the most discriminant AD regions of interest (ROIs).

[Consensus document on treatment of type 2 diabetes in patients with chronic kidney disease].

Chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM) are highly prevalent chronic diseases that represent a significant public health problem and require multidisciplinary management. T2DM is the main cause of CKD in our setting and it is also a major comorbidity of non-diabetic nephropathy. Patients with diabetes and renal failure represent a special risk group as they have higher morbidity and mortality and are at a higher risk of hypoglycaemia than diabetic individuals with normal renal function.

Combining PET images and neuropsychological test data for automatic diagnosis of Alzheimer's disease.

In recent years, several approaches to develop computer aided diagnosis (CAD) systems for dementia have been proposed. Some of these systems analyze neurological brain images by means of machine learning algorithms in order to find the patterns that characterize the disorder, and a few combine several imaging modalities to improve the diagnostic accuracy. However, they usually do not use neuropsychological testing data in that analysis.

Parametrization of textural patterns in 123I-ioflupane imaging for the automatic detection of Parkinsonism.

Purpose: A novel approach to a computer aided diagnosis system for the Parkinson's disease is proposed. This tool is intended as a supporting tool for physicians, based on fully automated methods that lead to the classification of (123)I-ioflupane SPECT images.

Methods: (123)I-ioflupane images from three different databases are used to train the system.

[Treatment of type 2 diabetes mellitus in patients with chronic kidney disease. Grupo de Trabajo para el Documento de Consenso sobre el tratamiento de la diabetes tipo 2 en el paciente con enfermedad renal crónica].

Chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM) are highly prevalent chronic diseases, which represent an important public health problem and require a multidisciplinary management. T2DM is the main cause of CKD and it also causes a significant comorbidity with regard to non-diabetic nephropathy. Patients with diabetes and kidney disease represent a special risk group as they have higher morbi-mortality as well as higher risk of hypoglycemia than diabetic individuals with a normal kidney function.

Conservative care in Europe--nephrologists' experience with the decision not to start renal replacement therapy.

Background: For some patients with end-stage renal disease (ESRD), providing conservative care until death may be an acceptable alternative for renal replacement therapy (RRT). We aimed to estimate the occurrence of conservative care in Europe and evaluated opinions about which factors nephrologists consider important in their decision not to offer RRT.

Methods: With a web-based survey sent to nephrologists in 11 European countries, we inquired how often RRT was not started in 2009 and how specific factors would influence the nephrologists' decision to provide conservative care.

Automatic determination of validity of input data used in ellipsoid fitting MARG calibration algorithms.

Ellipsoid fitting algorithms are widely used to calibrate Magnetic Angular Rate and Gravity (MARG) sensors. These algorithms are based on the minimization of an error function that optimizes the parameters of a mathematical sensor model that is subsequently applied to calibrate the raw data. The convergence of this kind of algorithms to a correct solution is very sensitive to input data.