Fracture risk predictions based on statistical shape and density modeling of the proximal femur
Journal of Bone and Mineral Research,  Clinical Article

Bredbenner TL, et al. – Increased risk of skeletal fractures due to bone mass loss is a major public health problem resulting in significant morbidity and mortality, particularly in the case of hip fractures. Current clinical methods based on two–dimensional measures of bone mineral density (areal BMD or aBMD) are often unable to identify individuals at risk of fracture. Statistical shape and density modeling (SSDM) identifies subtle changes in combinations of structural bone traits (e.g., geometric and BMD distribution traits) that appear to indicate fracture risk. Investigation of important structural differences in the proximal femur between fracture and no–fracture cases may lead to improved prediction of those at risk for future hip fracture.

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