Osteoporosis is a skeletal disease of reduced bone mass, degraded micro--architecture and increased fragility. Distal radius (Colles') fractures occur earlier in lifetime than other osteoporotic fractures. Efficient non-invasive assessment of fracture risk in the distal radius may therefore help to identify patients at risk early in time, indicate the need for treatment and prevent them from sustaining the predicted fragility fracture. The current gold standard clinical tool for this purpose is densitometry (DXA), predictive capability of which was however shown to be limited as bone mass is not the single contributor to bone strength. The emergence of High Resolution peripheral Quantitative Computed Tomography (HR-pQCT) allows for in vivo assessment of detailed reconstructions of the trabecular microstructure and the cortical shell in the peripheral skeleton. HR-pQCT-based anatomy-specific finite element (FE) modeling may succeed to DXA in predicting fracture risk in the distal radius.
Following an introductory chapter, the studies presented in this Thesis examine if the currently available HR-pQCT-based FE approaches (1) provide adequate predictions of ex vivo Colles' fracture load and (2) are applicable in the in vivo case.
The first study applies the recently developed smooth-surface-based homogenized continuum FE (hFE) approach on the distal radius, validate it with experimental Colles' fracture tests and raises numerous research questions which are then addressed in the following studies.
The second study introduces an alternative, grayscale image-based approach (SSOD) for assessment of structural anisotropy (fabric) in trabecular bone, aiming to circumvent the need of image segmentation, which is the main weakness of the current methods (e.g. MIL).
The third study evaluates how precisely HR-pQCT imaging is able to predict input parameters of the homogenization approach used in the hFE models, volume fraction and fabric, and identifies calibration laws for both of these quantities to match their gold standard (uCT) equivalents.
The fourth study shows that HR-pQCT-based hFE modeling incorporating the determined improvements is able to precisely predict experimental fracture load of distal radius sections and have comparable accuracy but lower computational needs than the uFE approach.
Finally, the fifth study demonstrates that the FE models of distal radius sections sized according to the in vivo HR-pQCT protocol are excellent predictors of the in vitro Colles' fracture load obtained in the first study and perform better in this sense than densitometry or morphological analysis. Moreover, distal shift of the standard HR-pQCT region of analysis is shown to increase the power of the prediction.
The herein accomplished research work provides better understanding of the biomechanics of Colles' fractures. Furthermore, the results suggest that the patient-specific HR-pQCT-based FE simulation represent an improved tool for in vivo fracture risk prediction, which will provide more precise identification of individuals at risk than the currently available DXA-based approach.