title: Analysis of trabecular bone microstructure using contour tree connectivity.
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 microCT 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 microCT. 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.
authors.affiliation: Department of Electronics and Communications Engineering, Tampere University of Technology, Tampere, Finland.
authors.forename: Dogu Baran
authors.initials: DB
authors.lastname: Aydogan
authors.affiliation: Orthopaedic Research Unit, Department of Orthopaedic Surgery and Traumatology, Turku University Hospital and University of Turku, Turku, Finland.
authors.forename: Niko
authors.initials: N
authors.lastname: Moritz
authors.affiliation: Orthopaedic Research Unit, Department of Orthopaedic Surgery and Traumatology, Turku University Hospital and University of Turku, Turku, Finland.
authors.forename: Hannu T
authors.initials: HT
authors.lastname: Aro
authors.affiliation: Department of Electronics and Communications Engineering, Tampere University of Technology, Tampere, Finland.
authors.forename: Jari
authors.initials: J
authors.lastname: Hyttinen
mesh_terms: D000465:Algorithms; D016880:Anisotropy; D001842:Bone and Bones / Q000166:cytology* / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D015207:Osteoarthritis, Hip / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*