Alessandro Celauro
DXA-based statistical shape-intensity models for hip fracture prediction in post-menopausal women.
Rel. Cristina Bignardi, Alessandra Aldieri. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2022
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Abstract
Osteoporosis is a bone disease caused by an imbalance between bone deposition and resorption which affects bone microstructure and leads to a decreased bone mass. According to recent studies, over 200 million people worldwide have osteoporosis. There are approximately 9 million fractures worldwide per year due to osteoporosis, among which 1.6 million are hip fractures (75% of which affect women). Moreover, it is estimated that 1 in 3 females and 1 in 5 males over the age of 50 will have an osteoporotic fracture. Osteoporosis is particularly frequent in post-menopausal women for hormonal reasons. The current gold standard to diagnose osteoporosis is measuring the areal Bone Mineral Density (aBMD) through dual-energy X-ray absorptiometry (DXA); aBMD is then used to calculate the so-called T-score, an indicator based on the comparison between the screened subject’s BMD and the BMD of young females aged in the range of 20-29 years.
The World Health Organization (WHO) has chosen T-score as the ultimate parameter to discriminate osteoporotic subjects from non-osteoporotic ones; however, its performances in the fracture prediction field are limited: it is estimated that about one half of the subjects not classified as osteoporotic by the T-score did in fact fracture
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