Analysis of Trabecular Bone Microstructure Using Contour Tree Connectivity

: Aydogan DB, Moritz N, Aro HT, Hyttinen J

: Mori K., Sakuma I., Sato Y., Barillot C., Navab N.

: International Conference on Medical Image Computing and Computer-Assisted Intervention

Publisher: SPRINGER-VERLAG BERLIN

: Nagoya, Japan

: 2013

: Lecture Notes in Computer Science

: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013

: Lecture Notes in Computer Science

: 8150

: 428

: 435

: 978-3-642-40762-8

: 978-3-642-40763-5

: 0302-9743

DOI: https://doi.org/10.1007/978-3-642-40763-5_53

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 mu CT 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 mu CT. The results based on our dataset show that CTC is the 3rd best predictive feature of ultimate bone strength after bone volume fraction and degree of anisotropy.