2 resultados para Montenegro skin test

em CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal


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Digital thermal imaging has been employed in medicine for over 50 years. However, its use has been focused on vascular, musculoskeletal and neurological conditions, while other potential applications,such as obstetrics, have been much less explored. This paper presents a study conducted during 2011 at the Hospital of Braga on a group of healthy pregnant women in the last third of gestation. The analysis focused on characterizing typical pregnant women steady temperature profiles in specific defined regions of interest (ROI), and determining if the thermal symmetry values for late pregnant healthy women are in line with the values for non-pregnant healthy women. A temperature distribution pattern was found in the defined ROI. The obtained thermal symmetry value had a maximum of 0.370.2 1C, and there was no evidence for the influence of age (p40.05) in the observed group. The influence of the BMI requires further investigation since one ROI (P2 right) presented a p¼0.059, close to the threshold of statistical evidence in the influence of BMI. The study group presented symmetry values in line with non-pregnant reference values, but the profiles in temperature distribution are different. Assumptions can therefore now be used with higher confidence when assessing abnormalities in specific pathologic states during pregnancy using the defined ROI. This work represents a first contribution towards establishing guidelines for future research in this specific field of study.

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Pectus excavatum is the most common congenital deformity of the anterior chest wall, in which several ribs and the sternum grow abnormally. Nowadays, the surgical correction is carried out in children and adults through Nuss technic. This technic has been shown to be safe with major drivers as cosmesis and the prevention of psychological problems and social stress. Nowadays, no application is known to predict the cosmetic outcome of the pectus excavatum surgical correction. Such tool could be used to help the surgeon and the patient in the moment of deciding the need for surgery correction. This work is a first step to predict postsurgical outcome in pectus excavatum surgery correction. Facing this goal, it was firstly determined a point cloud of the skin surface along the thoracic wall using Computed Tomography (before surgical correction) and the Polhemus FastSCAN (after the surgical correction). Then, a surface mesh was reconstructed from the two point clouds using a Radial Basis Function algorithm for further affine registration between the meshes. After registration, one studied the surgical correction influence area (SCIA) of the thoracic wall. This SCIA was used to train, test and validate artificial neural networks in order to predict the surgical outcome of pectus excavatum correction and to determine the degree of convergence of SCIA in different patients. Often, ANN did not converge to a satisfactory solution (each patient had its own deformity characteristics), thus invalidating the creation of a mathematical model capable of estimating, with satisfactory results, the postsurgical outcome