Técnicas de imagen : proceso de soporte

Publicado en la página web de la Consejería de Salud: www.juntadeandalucia.es/salud (Consejería de Salud / Profesionales / Nuestro Compromiso por la Calidad / Procesos de Soporte)

Executive functions profile in extreme eating/weight conditions: from anorexia nervosa to obesity.

BACKGROUND Extreme weight conditions (EWC) groups along a continuum may share some biological risk factors and intermediate neurocognitive phenotypes. A core cognitive trait in EWC appears to be executive dysfunction, with a focus on decision making, response inhibition and cognitive flexibility. Differences between individuals in these areas are likely to contribute to the differences in vulnerability to EWC. The aim of the study was to investigate whether there is a common pattern of executive dysfunction in EWC while comparing anorexia nervosa patients (AN), obese subjects (OB) and healthy eating/weight controls (HC). METHODS Thirty five AN patients, fifty two OB and one hundred thirty seven HC were compared using the Wisconsin Card Sorting Test (WCST); Stroop Color and Word Test (SCWT); and Iowa Gambling Task (IGT). All participants were female, aged between 18 and 60 years. RESULTS There was a significant difference in IGT score (F(1.79); p<.001), with AN and OB groups showing the poorest performance compared to HC. On the WCST, AN and OB made significantly more errors than controls (F(25.73); p<.001), and had significantly fewer correct responses (F(2.71); p<.001). Post hoc analysis revealed that the two clinical groups were not significantly different from each other. Finally, OB showed a significant reduced performance in the inhibition response measured with the Stroop test (F(5.11); p<.001) compared with both AN and HC. CONCLUSIONS These findings suggest that EWC subjects (namely AN and OB) have similar dysfunctional executive profile that may play a role in the development and maintenance of such disorders.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Evaluación del cartílago articular mediante técnicas de dignóstico por la imagen

This article briefly reviews the composition of the hyaline cartilage and its ultrastructure. Subsequently, we offer a brief review of the role of imaging techniques in the assessment of this pathology. These include the most useful pulse sequences for the morphological assessment of cartilaginous injuries using MRI, as well as how these injuries appear in the images, at pre and post-surgical intervals. Lastly, we mention the developments in MRI that allow us to close in on the biochemical assessment of normal and pathological cartilage.

Una declaración de amor a la ciencia en Andalucía

Boletín semanal para profesionales sanitarios de la Secretaría General de Calidad, Innovación y Salud Pública de la Consejería de Igualdad, Salud y Políticas Sociales