Abstract
Millions of people worldwide suffer from fragility fractures, which cause significant morbidity, financial costs and even mortality. The gold standard to quantify structural properties of trabecular bone is based on the morphometric parameters obtained from μCT images of clinical bone biopsy specimens. The currently used image processing approaches are not able to fully explain the variation in bone strength. In this study, we introduce the contour tree connectivity (CTC) as a novel morphometric parameter to study trabecular bone quality. With CTC, we calculate a new connectivity measure for trabecular bone by using contour tree representation of binary images and algebraic graph theory. To test our approach, we use trabecular bone biopsies obtained from 55 female patients. We study the correlation of CTC with biomechanical test results as well as other morphometric parameters obtained from μCT. The results based on our dataset show that CTC is the 3rdbest predictive feature of ultimate bone strength after bone volume fraction and degree of anisotropy.
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Dogu Baran Aydogan
Group leader, Academy Research Fellow
I am interested in computational neuroimaging, connectivity of the brain and brain stimulation