Development of an Image-Based Biomechanical Model for Assessment of Hip Fracture Risk

Author(s):  
Masoud Nasiri Sarvi ◽  
Yunhua Luo

Low-trauma hip fracture, usually caused by fall from standing height, has become a main source of morbidity and mortality for the elderly. Factors affecting hip fracture include sex, race, age, body weight, height, body mass distribution, etc., and thus, hip fracture risk in fall differs widely from subject to subject. It is therefore necessary to develop a subject-specific biomechanical model to predict hip fracture risk. The objective of this study is to develop a two-level, image-based, subject-specific biomechanical model consisting of a whole-body dynamics model and a proximal-femur finite element (FE) model for more accurately assessing the risk of hip fracture in lateral falls. Required information for constructing the model is extracted from a whole-body and a hip DXA (Dual Energy Xray Absorptiometry) image of the subject. The proposed model considers all parameters subject-specifically, which will provide a fast, accurate, and non-expensive method for predicting hip fracture risk.

Author(s):  
Masoud Nasiri Sarvi ◽  
Yunhua Luo

Low-trauma hip fracture, usually caused by fall from standing height, has become a main source of morbidity and mortality among the elderly. However, the hip fracture risk is subject-dependent as it is related to the subject’s anthropometric parameters, the kinematic/kinetic variables in fall, and the hip anatomy. A compound fracture risk indicator is proposed in this study to define the correlation between the hip fracture risk and subject’s parameters such as anthropometric parameters, bone mineral density (BMD), height of body mass center (HMC), and hip soft tissue thickness (STT). In this study, a two-level, subject-specific biomechanical model composed of a whole-body dynamics model and a proximal femur finite element model was used to predict the hip fracture risk for 80 subjects. The required information was obtained from the subject’s whole body and hip DXA (dual energy X-ray absorptiometry) images. Then, multivariate nonlinear least-square fits of power functions were used to investigate the effect of parameters on hip fracture risk. Results indicated that although BMD is the dominant parameter affecting the hip fracture risk, other parameters such as hip soft tissue thickness and anthropometric parameters also have considerable effects. This finding suggests that the hip fracture risk cannot be accurately predicted by the currently available single factor predictors as they do not consider all multifactorial parameters. However, the proposed function can properly predict the risk of hip fracture in the absence of any computational simulation and biomechanical model. It also quantifies the effect of musculoskeletal-, and organ-level parameters on hip fracture risk and demonstrates which individual is more likely to experience hip fracture.


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