Original Full Length ArticleAnalysis of strength and failure pattern of human proximal femur using quantitative computed tomography (QCT)-based finite element method
Graphical abstract
Introduction
Hip fractures cause significant numbers of disability and mortality worldwide. The incidence of these fractures varies globally, e.g., the city of Shiraz in Iran is reported to have the highest incidence of hip fractures in Asia [1]. Previous studies estimated that the worldwide number of hip fractures was 1.3 million in 1990 and predicted an increase between 7.3 and 21.3 million by 2050 [1], [2], [3]. Thus, many researchers have tried to devise new methods for noninvasive assessment of the hip fracture risk, among which the QCT-based finite element analysis (FEA) has been recognized as a very reliable tool [4], [5], [6], [7], [8], [9], [10], [11], [12]. However, there are some limitations that should be resolved before this method can be clinically feasible. One major problem is the high computational time and cost for implementation of nonlinear FEA which has been shown to have the required accuracy [4], [6], [7], [8], [9], [13]. A typical QCT-based nonlinear FEA of human proximal femur requires at least 8–10 h of runtime, even by implementing advanced computational techniques [4], [7], [9], [13]. On the other hand, the linear FE analyses are very much faster, quite easier to apply, and can provide comparable predictions of the failure location and pattern for the proximal femur and vertebra [13], [14]. However, they require further data processing schemes for predictions of the failure load that may give less accurate results in certain cases. For instance, Keyak et al. proposed a linear FEA method for the prediction of the failure load in the sideways fall and stance configurations and argued that failure of a certain number of contiguous non-surface elements can represent the failure of the whole proximal femur [15]. On the other hand, Nishiyama et al. defined a constant yield strain level and suggested that the failure of a constant percentage of elements would represent the failure of proximal femur in the sideways fall configuration [16]. Nevertheless, we believe that the percentage or the number of critical elements should naturally be different for various specimens and loading orientations. Moreover, our previous studies on human vertebrae and proximal femur have shown favorable results in the prediction of the failure patterns using a strain energy density measure within the framework of linear QCT-based FEA [13], [14]. Thus, this study was aimed at development and experimental verification of a new method for fast and accurate prediction of the failure strength of human proximal femur through specific assortments and usage of high strain energy elements of the linear QCT-based FEA results.
Section snippets
Sample preparation
Ten fresh-frozen human femora, from 9 cadavers (5 male, 4 female, average age: 34 ± 16), were used in this study (see Table 1) (specimens 9 and 10 were a contralateral pair from a single cadaver).
The initial treatment of the specimens included standard excision, freezing, and bagging procedures by the Iranian Tissue Bank (ITB). Moreover, the death causes announced by ITB were the three categories of coronary failure, cerebral death, and fatal trauma. Nevertheless, the plain radiographs of the
Failure patterns
Fig. 3 shows the predicted and experimental failure patterns for three specimens (numbers 4, 5, and 9) under different loading orientations (see Table 1). It should be noted that in this figure only the screened critical elements are shown for clarity. For the specimen 4, the initiation of a trochanteric local failure was distinguished. The occurrence of a similar failure pattern at the same location (in the form of a distinct crack) was clearly visible on the experimental specimen (see Fig. 3).
Discussion
Many investigations have been carried out on non-invasive assessment of the hip fracture risk using the QCT-based finite element analysis (FEA). The valuable advantages of this method are the ability of development of very accurate image-based 3D models of the femoral geometry, plus a pointwise description of BMD-based material properties. In general, the results have shown that nonlinear FEA can predict the femoral strength with very good accuracy. However, several researchers have faced
Acknowledgments
The authors wish to thank Dr. Mohsen Sadeghi for his continuous help during several stages of this work. The valuable help of Dr. Mahdavi and Dr. Khodadadi from the Iranian Tissue Bank (ITB, Tehran University of Medical Sciences) in providing Cadaveric samples is highly appreciated. The QCT scans were carried out using the facilities of the Noor Clinic with the help and support of Dr. Akhlaghpour. The valuable help of Mr. Kargar (Materials Laboratory of Tarbiat Modares University) with the
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