Nicole Morando
Identification of statistical critical area of proximal femur when a lateral fall happens.
Rel. Lorenzo Peroni. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2021
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Abstract
Osteoporotic hip fracture is considered a worldwide health problem in the elderly population, with a negative social and economic impact characterized by an increase of hospital cost and a worsening of quality of life. Diagnostic tools widely used for assessment of osteoporosis include Dual-energy X-ray absorptiometry (DXA), Quantitative Computed Tomography (QCT), FRAX. Although DXA is the gold standard for osteoporosis diagnose, it is not enough reliable for fracture prediction. For this reason, the Finite Element (FE) model rises as a complementary tool to tackle the fracture prediction. In this sense, the evaluation of critical fracture regions on FE model, is often based on visual identification of mapped field introducing under/over estimation of the local nature of fracture event.
The present thesis provides an innovative rigorous methodology applied on FE proximal femur models generated from DXA images, to identify statistically significant difference between fracture and non-fracture group through the application of Random Field Theory (RFT) and its topological extension of statistical process based on Statistical Parametric Map (SPM)
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