Abstract
Severe predictions have been made regarding osteoporotic fracture incidence for the next years, with major economic and social impacts in a worldwide greying society. However, the performance of the currently adopted gold standard for fracture risk prediction, the areal Bone Mineral Density (aBMD), remains moderate. To overcome current limitations, the construction of statistical models of the proximal femur, based on three-dimensional shape and intensity (a hallmark of bone density), is here proposed for predicting hip fracture in a Caucasian postmenopausal cohort. Partial Least Square (PLS)-based statistical models of the shape, intensity and their combination were developed, and the corresponding modes and components were identified. Logistic regression models using the first two shape, intensity and shape-intensity PLS components were implemented and tested within a 10-fold cross-validation procedure as predictors of hip fracture. It emerged that (1) intensity components were superior to shape components in stratifying patients according to their fracture status, and that (2) a combination of intensity and shape improved patients risk stratification. The area under the ROC curve was 0.64, 0.85 and 0.92 for the models based on shape, intensity and shape-intensity combination respectively, against a 0.72 value for the aBMD standard approach. Based on these findings, the presented methodology turns out to be promising in tackling the need for an enhanced fracture risk assessment.
Highlights
Osteoporosis is a metabolic disease very common in older adults, entailing bone mass reduction and microarchitectural deterioration eventually leading to bone fracture.[38]
The Statistical Intensity Model (SIM) model was less compact than the Statistical Shape Model (SSM): 67 modes were needed to account for at least 90% variation in the Bone Mineral Density (BMD) distribution, the first four modes accounting for the 37% of it (Fig. 3)
The whole femur bone mass variation represents the main feature of the first Shape-Intensity Model (SSIM) mode (Fig. 4) which, simultaneously accounting for both intensity and shape, captures variations in the cross-sections, consistent with the protective role that an increased cross-sectional moment of inertia is known to play on cortical stability.[26]
Summary
Osteoporosis is a metabolic disease very common in older adults, entailing bone mass reduction and microarchitectural deterioration eventually leading to bone fracture.[38]. 9 million fragility fractures were estimated to occur in 2000, including 1.6 million hip fractures,[22] with predictions suggesting this number will increase 3 to 4-fold by 2050.12,18 Osteoporotic fractures are a burden for the public health, costing 37 billion euros in EU and 16 billion dollars in USA.[7,19] Among others, hip fractures represent one of the most common and serious osteoporosis-related fractures, causing severe morbidity and mortality.[20,33] Hip fracture incidence increases exponentially with age, mainly due to progressive loss of bone mass, and structural and material deterioration of trabecular and cortical bone, combined with other non-skeletal factors.[8] Considering the adverse impact of hip fracture on patients’ life, the identification of individuals at high risk is pivotal, since it is the gateway to fracture prevention. According to the World Health Organisation (WHO) it is the areal Bone Mineral Density (aBMD), measured through Dual X-rays Absorptiometry (DXA) at the proximal femur or lumbar spine, that currently supports the diagnosis of osteoporosis and the indication for treatment.[11,23,24,25] aBMD is a surrogate marker of bone strength able to, at best, partially capture the influence that factors such as bone
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