A 4D imaging approach to monitor bone remodeling

Age-related diseases, such as age-related bone loss and osteoporosis, are a major challenge in our aging society. Therefore healthy aging is one major objective in current regenerative medicine. However, to approach this goal a detailed knowledge of the physiological processes of all organs is required. Bone is a constantly (re)modeling organ, dynamic processes repeatedly modify its micro-structure throughout life. In these processes, existing bone material is removed and replaced by newly formed new bone packages. Besides this ability to restructure bone has the potential to adapt its mass and micro-structure to changes in its mechanical environment, to maintain its load-bearing efficiency and consequently to avoid mechanical failure. Osteoporosis, the most common bone disease is to date only poorly understood and therefore of great interest in biomedical research. It is assumed, that this disease is caused by a loss of mechano-responsiveness of the bone, which results in failing restructuring processes. In the first part of the presented work a closer analysis of the initial situation revealed, that due to the dynamic characteristics of the bone restructuring processes, a method has to include the kinetics of these processes into the evaluation of bone (re)modeling. Based on this approach, the state of the art of quantifying dynamic processes in bone is analyzed. The results of this analysis show, that to date no automated methods are in use, that allow for a combined direct spatio-temporal investigation of bone (re)modeling events as well as sequences, enabling the monitoring of dynamic bone restructuring over time. Thus, a concept for including the spatio-temporal character of bone (re)modeling into the analysis of bone health has to be developed and applied to more precisely answer specific biological bone research questions. Automated 3D methods have a great potential to improve the basic knowledge of the body and the diagnosis of patho-physiological conditions in the individual in the near future. Therefore, within the scope of this dissertation, contributions were made to the advancement of knowledge of dynamic bone (re)modeling using this technique. The development, design, validation and first applications of a tomography-based medical image processing method and tool for enhanced visualization and quantification of patho-physiological dynamic structural processes in bone is presented, representing a step in the direction of a holistic, automated analysis of bone and providing new insights into dynamic micro-structural processes. In the second part of the work a method for a 4D (3D spatial, 1D temporal) analysis of bone (re)modeling is developed. In basic biological research animal models are commonly used to mimic human patho-physiologies and to test new therapies. At the Julius Wolff Institute bone processes are investigated in mouse models. As the bone (re)modeling in a mouse model of bone adaptation was intended to be the first application of the developed method, a detailed investigation of the expected characteristics of this application set the basis for the development specifications. The main objective was to develop techniques for extraction, quantification and visualization of relevant information from 4D data sets.Therefore, within this thesis a framework has developed, including registration, segmentation, feature extraction, tracking and analysis methods, enabling an in depth evaluation of dynamic changes in bone structure. Using this method, longitudinal microCT data sets of bone acquired in experimental bone biology can be evaluated such that bone formation and resorption processes, as well as the overall (re)modeling sequences can be detected, displayed and morphologically quantified. In the third part the developed method and tool were validated and applied to answer specific biological research questions. The validation revealed, that the methods produce reliable results, which are comparable or improved to previous manual histomorphometric techniques, therefore allowing statistically significant biological findings to be obtained far earlier, thus, allowing to reduce sample numbers in animal experiments. Application of the developed method in several studies enabled the evaluation of quantitative (re)modeling differences on different bone surfaces. Linking these information of formation and resorption processes of all bone surfaces, the trabecular, the endocortical and the periosteal, enabled a detailed 3D time-dependent analysis of the structural dynamics and thereby allowing, for the first time, a precise quantification of the whole balances of bone restructuring. In addition, the procesess of aging and bone adaptation could be displayed by analyzing young, adult and elderly mice subjected to physiological and additional controlled tibia loading. It could be shown that loading has a much stronger effect on formation than on resorption of bone, and more specifically this greater effect is due to an increase of the formation surface with mechanical stimulation. This is the only effect of loading which is conserved with age. As a next step, effects of pharmacological treatment or absence of certain genes on bone (re)modeling could be studied. In conclusion, the application of the method could not only show direct causes of trabecular and cortical bone loss and thinning with aging, but also provided first direct evidence on the underlying failing mechanisms. Taken together, within this dissertation it could be shown that it is possible to extract spatial as well as temporal information of dynamic bone restructuring processes using computational image analysis methods that are integrated in an existing experimental imaging setup using a commercially available microCT device. This constitutes a new approach to establish a more complete analysis of bone (re)modeling in experimental biology and provides the basis for an early risk detection and intervention of bone loss in human patients.