Hip fracture has been identified as a major worldwide health problem among the elderly population. A fast, accurate and effective evaluation of hip fracture risk is essential for accurate health care planning and selecting a proper treatment. Therefore, the high applicability and the universal availability are required for assessing a technique. The objective of this study was to develop a two-dimensional subject-specific beam model, which is easy to be adopted into a clinical environment to assess hip fracture risk. First, the equivalence between CTXA (computed tomography X-ray absorptiometry) and QCT (quantitative computed tomography) derived femur cross-section stiffness was studied. Then, the CTXA-based femur cross-section stiffness was used in the beam model to calculate the hip fracture risk index (FRI) during sideways fall and single-leg stance loading configuration. Finally, the test of discrimination between PPI (proton-pump inhibitor) users and non-PPI users based on cross-sectional stiffness, BMD (bone mineral density) and FRI was conducted to demonstrate if PPI use is associated with the presence of osteoporosis or accelerated BMD loss. Strong correlation is found between CTXA and QCT derived femur cross-section stiffness, which indicates that QCT can be replaced by CTXA in assessing femur bone quality. Therefore, DXA can be a replacement of QCT to calculate femur cross-sectional properties due to the equivalence between CTXA and DXA derived mechanical properties. It is also demonstrated that the cross-sectional stiffness, BMD, and FRI cannot discriminate the PPI users from non-PPI users, which means that there is no difference between PPI users and non-PPI users in cross-sectional stiffness, BMD, and FRI. This may suggested that PPI use is not associated with the presence of osteoporosis or accelerated BMD loss. The proposed beam model can be easily adopted into clinic to predict hip fracture risk, and this beam model derived FRI can be used in some clinical verification. Yet its accuracy of discriminate fracture will be investigated in a future study. / May 2017

Accurate assessment of hip fracture risk is very important to prevent hip fracture and to monitor the effect of a treatment. A subject-specific QCT-based finite element model was constructed to assess hip fracture risk at the critical locations of femur during the single-leg stance and the sideways fall. The aim of this study was to improve the prediction of hip fracture risk by introducing a more proper failure criterion to more accurately describe bone failure mechanism. Hip fracture risk index was defined using the strain energy criterion, which is able to integrally consider information such as stresses, strains and material properties in bone failure. It was found that the femoral neck and the intertrochanteric region have higher fracture risk than other part of the femur, probably owing to the larger content of cancellous bone in these regions. The study results also suggested that women are more prone to hip fracture than men. The effects of different parameters such as age, body height, weight, and BMI on hip fracture risk were also investigated in this study. The findings in this study have a good agreement with those clinical observations reported in the literature. The main contributions from this study include: (1) introducing an algorithm for hip fracture risk assessment at the critical locations of femur using the strain energy criterion and QCT-based finite element modeling, (2) theoretically more reasonable definition of hip fracture risk index based on the strain energy criterion, and (3) a semi-automatic finite element analysis and automatic calculation of hip fracture risk index at the critical locations of femur using in-house developed computer codes. The proposed hip fracture risk index based on the strain energy criterion will be a promising tool for more accurate assessment of hip fracture risk. However, experimental validation should be conducted before its clinical applications. / October 2015

Hip fractures in older adults have severe effects on patients’ morbidity as well as mortality, so it is crucial to avoid this injury through the early identification of patients at high risk. Currently, the diagnosis of osteoporosis and consequently hip fracture risk is done through the measurement of bone mineral density by a dual-energy X-ray absorptiometry (DXA) scan. However, studies show that this method is not accurate enough, and a high percentage of patients who sustain a hip fracture had non-osteoporotic DXA scans less than a year before the incidence. In this research, to enhance the hip fracture risk prediction, the effect of a femur’s geometry and bone mineral density distribution was considered in the hip fracture risk estimation. This was done through 2D and 3D statistical shape and appearance modeling of the proximal femur using standard clinical DXA scans. To assess the proposed techniques, destructive mechanical tests were performed on 16 isolated cadaveric femurs. Also, through collaboration with the Canadian Osteoporosis Study (CaMos), the proposed statistical techniques to predict the hip fracture risk were evaluated in a clinical population as well. The results of this study showed that new techniques can enhance hip fracture risk estimation; in the clinical study, 2D and 3D statistical modeling were able to improve identifying patients at high risk by 40% and 44% over the clinical standard method. Also, the percentage of correct predictions using 2D statistical models did not differ significantly from the 3D predictions. Therefore, by applying these techniques in clinical practice it could be possible to identify patients at high risk of sustaining a hip fracture more accurately and eventually reduce the incidence of hip fractures and the pain and social and economic burden that comes with it. / Thesis / Doctor of Philosophy (PhD) / Diagnosis of osteoporosis and consequently hip fracture risk is based on the measurement of bone mineral density in clinical imaging called DXA scanning. However, studies have shown that this method is not sufficient in identifying all patients at high risk of sustaining a hip fracture. The purpose of this work was to incorporate the geometry and bone mineral density distribution of the proximal femur in hip fracture risk prediction through image processing of DXA scans. Two algorithms of 2D and 3D statistical shape and appearance modeling were implemented and evaluated in a cadaveric study (comparing the predicted fracture load to measured ones) as well as a clinical study (comparing the fracture predictions to the fracture history of patients). The results indicated that new techniques can enhance hip fracture risk estimation compared to the clinical standard method, and hence the devastating injury can be prevented through applying protective measures.

Dual Energy X-ray Absorptiometry (DXA)-based finite element (FE) modelling has emerged as a potential tool for better assessment of osteoporotic hip fracture risk. Automation of this complex and computationally-intense procedure is the prime requirement for its clinical applicability. The aim of this study was to develop a fully automatic DXA-based finite element tool and assess its discrimination ability and short-term repeatability. The proximal femur was automatically segmented from clinical hip DXA scan and the subject-specific FE model was constructed for simulating sideways fall. Hip fracture risk indices (HFRIs) were calculated using two ways (along a femur cross-section and over a region of interest, ROI). Hip fracture discriminability increased when moved from femur cross-section based to ROI based HFRI calculation. A significant increase in hip fracture discriminability from baseline femoral neck and total hip bone mineral density (BMD) was achieved with ROI based HFRIs. Promising short-term repeatability was observed for HFRIs (coefficient of variation, CV, 3~3.5%). After removing representative poor cases, CVs were less than 3%. These preliminary results establish the potential of the proposed automatic tool for hip fracture risk assessment and justify large-scale clinical evaluation of its ability to predict incident hip fractures. / February 2017

Hip fracture has been identified as one of the main health problems in the elderly. To improve the accuracy in assessing subject-specific hip fracture risk, this study proposed normalized cortical bone thickness (NCBT) estimated from patient’s hip DXA as an alternative predictor of hip fracture risk. Hip fracture risk index (HFRI) derived from DXA-based finite element model was utilized as a baseline for evaluating the effectiveness of NCBT in predicting hip fracture risk. It was found that NCBT at the lateral side of the narrowest femoral neck had the strongest correlation with femoral neck HFRI among the six locations of the proximal femur. This study suggests that it is possible to use NCBT as a surrogate for a quick evaluation of hip fracture risk. Yet its clinical performances such as sensitivity to therapy effectiveness and the ability to discriminate clinical fracture cases will be investigated in a future study.