3D Analysis of the Proximal Femur Compared to 2D Analysis for Hip Fracture Risk Prediction in a Clinical Population
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Due to the adverse impacts of hip fractures on patients' lives, it is crucial to enhance the identification of people at high risk through accessible clinical techniques. Reconstructing the 3D geometry and BMD distribution of the proximal femur could be beneficial in enhancing hip fracture risk predictions; however, it is associated with a high computational burden. It is also not clear whether it provides a better performance than 2D model analysis. Therefore, the purpose of this study was to compare the 2D and 3D model reconstruction's ability to predict hip fracture risk in a clinical population of patients. The DXA scans and CT scans of 16 cadaveric femurs were used to create training sets for the 2D and 3D model reconstruction based on statistical shape and appearance modeling. Subsequently, these methods were used to predict the risk of sustaining a hip fracture in a clinical population of 150 subjects (50 fractured, and 100 non-fractured) that were monitored for five years in the Canadian Multicentre Osteoporosis Study. 3D model reconstruction was able to improve the identification of patients who sustained a hip fracture more accurately than the standard clinical practice (by 40%). Also, the predictions from the 2D statistical model didn't differ significantly from the 3D ones (p > 0.76). These results indicated that to enhance hip fracture risk prediction in clinical practice implementing 2D statistical modeling has comparable performance with lower associated computational load.
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