Cone-Beam Computed Tomography as a Prediction Tool for Osteoporosis in Postmenopausal Women

Osteoporosis is a disease of the skeletal system which is characterised by decreased bone density and microarchitectural damage, resulting in decreased bone strength and a significantly increased risk of bone fracture. According to the WHO, osteoporosis is the second most common pathology after cardiovascular disease. Osteoporotic fractures often lead to disability with a significant deterioration in quality of life or can even be a cause of death. Therefore, early diagnosis of osteoporosis and the initiation of prevention or treatment becomes important. However, the most widely used method of diagnosing osteoporosis today is Dual-energy X-ray absorptiometry (DXA). It is not available to the general public and cannot be used as a screening method. As postmenopausal patients often visit the dentist, it has been hypothesised that dental radiographs could be used to determine the risk of osteoporosis. Therefore, the first purpose of this interdisciplinary project is to develop a method for osteoporosis risk detection in postmenopausal women by assessing qualitative changes in mandibular cortical and trabecular bone on CBCT scans and to create a comprehensive deep learning prototype model for osteoporosis risk detection. And second purpose of this project is to assess the impact of osteoporosis in postmenopausal women on TMJ bone structures ( density, volume, surface structure of mandibular condyle). A total of 250 patients are expected to be enrolled in this study.