article
Análise estrutural utilizando MEF para avaliação da estrutura óssea da órbita
Fecha
2015Registro en:
2236-1103
10.18816/r-bits.v5i2.7255
Autor
Jesus, Gabriela Caires de
Guerra Neto, Custódio Leopoldino de Brito
Coutinho, Karilany Dantas
Resumen
Graves disease is an autoimmune disease caused by thyroid stimulant antibodies which increase the secretions of this gland. This pathological state can lead to Graves ophthalmopathy, in which extra ocular muscles and other orbital contents can be augmented, causing increased intra-orbital pressure. There are many tools for study of this pathology, such as finite element models of the soft tissues of the orbit, studies that
relate size of osteotomy, with the reduction of exophthalmos and volume of orbital contents. However, there are few studies examining how increasing orbital pressure due to increased volumes of intra-orbital soft tissue, increases the stresses on the bone structure. Faced with this problem, this paper proposed to perform a biomechanical analysis of bone structure of the orbit of a patient, via a finite element model, comparing
the displacements and stresses caused by physiological and pathological pressures. Thus, a finite element model was made from a CT image and a biomechanical analysis was performed yielding values of displacement and maximum stresses according to the applied pressures. From the analysis, total translation and maximum stress values for each model were obtained and it was observed an increase of 6.5 times of values of both stress and the translation for the model with the load applied simulating the pathology relative to the model without pathology. Because the pressures applied are low magnitude, results in displacements and stresses were of small magnitude, but there was indicative of stress concentrations in the lateral and medial walls of the orbit, suggesting that in case of decompression surgery is more appropriate to remove these regions while maintaining the most stable parts of the orbit. This study proved possible to make a model with specific patient data, providing personalized information