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Enhancement of Prediction for Hip Fractures Using Stochastic Assessment of Bone Mineral Density Distribution From DXA Images

[+] Author Affiliations
Xuanliang Neil Dong, Timothy Lowe, Joyce Ballard

The University of Texas at Tyler, Tyler, TX

Patricia Cussen, David Di Paolo

The University of Texas Health Science Center at Tyler, Tyler, TX

Paper No. SBC2013-14227, pp. V01AT08A002; 2 pages
  • ASME 2013 Summer Bioengineering Conference
  • Volume 1A: Abdominal Aortic Aneurysms; Active and Reactive Soft Matter; Atherosclerosis; BioFluid Mechanics; Education; Biotransport Phenomena; Bone, Joint and Spine Mechanics; Brain Injury; Cardiac Mechanics; Cardiovascular Devices, Fluids and Imaging; Cartilage and Disc Mechanics; Cell and Tissue Engineering; Cerebral Aneurysms; Computational Biofluid Dynamics; Device Design, Human Dynamics, and Rehabilitation; Drug Delivery and Disease Treatment; Engineered Cellular Environments
  • Sunriver, Oregon, USA, June 26–29, 2013
  • Conference Sponsors: Bioengineering Division
  • ISBN: 978-0-7918-5560-7
  • Copyright © 2013 by ASME


Hip fractures are among the most common types of osteoporotic fractures that affect one in three women and one in six men over the age of 50 [1]. It is well known that loss of bone mass, quantified by bone mineral density using Dual-energy X-ray Absorptiometry (DXA), is associated with the increasing risk of bone fractures. However, bone mineral density (BMD) alone cannot fully explain changes in fracture risks [2, 3]. In particular, BMD is not able to predict fracture risks for women with osteopenia, in which a BMD T-score is between −1.0 and −2.5. This suggests additional factors (i.e., bone quality) should be considered in predicting fracture risks [4].

Copyright © 2013 by ASME
Topics: Density , Bone , Hip fractures



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