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Computational and Mathematical Methods in Medicine
Volume 2015, Article ID 162481, 7 pages
Research Article

Bone Mineral Density and Fracture Risk Assessment to Optimize Prosthesis Selection in Total Hip Replacement

1Institute for Biomedical and Neural Engineering, Háskólinn í Reykjavík, Menntavegur 1, 101 Reykjavík, Iceland
2Department of Rehabilitation, Landspítali, Norðurmýri, 101 Reykjavík, Iceland
3Orthopaedic Clinic, Landspitali Hospital, Norðurmýri, 101 Reykjavík, Iceland
4Medical Faculty, Háskóli Íslands, Sæmundargötu 2, 101 Reykjavík, Iceland
5Department of Science, Landspítali University Hospital, Norðurmýri, 101 Reykjavík, Iceland

Received 17 December 2014; Revised 3 March 2015; Accepted 5 March 2015

Academic Editor: Zhonghua Sun

Copyright © 2015 Þröstur Pétursson et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The variability in patient outcome and propensity for surgical complications in total hip replacement (THR) necessitates the development of a comprehensive, quantitative methodology for prescribing the optimal type of prosthetic stem: cemented or cementless. The objective of the research presented herein was to describe a novel approach to this problem as a first step towards creating a patient-specific, presurgical application for determining the optimal prosthesis procedure. Finite element analysis (FEA) and bone mineral density (BMD) calculations were performed with ten voluntary primary THR patients to estimate the status of their operative femurs before surgery. A compilation model of the press-fitting procedure was generated to define a fracture risk index (FRI) from incurred forces on the periprosthetic femoral head. Comparing these values to patient age, sex, and gender elicited a high degree of variability between patients grouped by implant procedure, reinforcing the notion that age and gender alone are poor indicators for prescribing prosthesis type. Additionally, correlating FRI and BMD measurements indicated that at least two of the ten patients may have received nonideal implants. This investigation highlights the utility of our model as a foundation for presurgical software applications to assist orthopedic surgeons with selecting THR prostheses.