gms | German Medical Science

German Congress of Orthopaedics and Traumatology (DKOU 2016)

25.10. - 28.10.2016, Berlin

Spatial And Temporal Fracture Prediction In The Femur During Compression Using Acoustic Emission Analysis

Meeting Abstract

  • presenting/speaker Peter Föhr - Technische Universität München, Klinikum rechts der Isar, Klinik für Orthopädie und Sportorthopädie, München, Germany
  • Robin Groschup - Technische Universität München, Centrum Baustoffe und Materialprüfung, Lehrstuhl für Zerstörungsfreie Prüfung, München, Germany
  • Hannes Eigner - Technische Universität München, Klinikum rechts der Isar, Klinik für Orthopädie und Sportorthopädie, München, Germany
  • Fabian Malm - Technische Universität München, Centrum Baustoffe und Materialprüfung, Lehrstuhl für Zerstörungsfreie Prüfung, München, Germany
  • Manuel Raith - Technische Universität München, Centrum Baustoffe und Materialprüfung, Lehrstuhl für Zerstörungsfreie Prüfung, München, Germany
  • Constantin von Deimling - Technische Universität München, Klinikum rechts der Isar, Klinik für Orthopädie und Sportorthopädie, München, Germany
  • Rainer Burgkart - Technische Universität München, Klinikum rechts der Isar, Klinik für Orthopädie und Sportorthopädie, München, Germany
  • Christian U. Große - Technische Universität München, Centrum Baustoffe und Materialprüfung, Lehrstuhl für Zerstörungsfreie Prüfung, München, Germany

Deutscher Kongress für Orthopädie und Unfallchirurgie (DKOU 2016). Berlin, 25.-28.10.2016. Düsseldorf: German Medical Science GMS Publishing House; 2016. DocGR21-428

doi: 10.3205/16dkou482, urn:nbn:de:0183-16dkou4821

Published: October 10, 2016

© 2016 Föhr et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.


Outline

Text

Objectives: Osteoporosis is associated with a gradual loss of bone mineral density (BMD). The BMD loss leads to an increased risk of bone fractures, particularly at the femoral neck. In this study, non-destructive acoustic emission analysis (AEA) has been explored to determine the early spatial and temporal events during mechanical loading. The study was conducted to determine if localization methods based on signal transit time is applicable to bone. It is expected that such methods are limited for bone due to its complex anisotropic structure. However correlations between external forces and AE-parameters like magnitude and frequency content could be identified, as well as the individual patients fracture risk could be estimated.

Methods: Experiments were conducted on equine femora (n=7). Damaged samples were excluded via computed tomography scans. Bones were physiologically aligned in a uniaxial test system (Wolpert TZZ-707) and loaded at a rate of 5 mm/min until total failure or a force limit of 50 kN occurred. Longitudinal ultrasonic sensors (Panametrics V103-RB) were glued directly to the cortical shell to measure the AE induced by fracture initiation and propagation. The temporal count rate of the AE-events was measured at eight sensor locations, two on the shaft area and six on the proximal meta- and epiphysis, and was then compared to the force-time-graphs. Prior to the analysis of the main study, the experimental set up was validated using two additional femora.

Results and Conclusion: Data on the compression characteristics showed considerable scattering with partially ductile and brittle behavior. Two characteristic data points divided the measurement graphs into three subsections: linear, plastic-elastic and destructive. Data analysis of the AE-events at the data points demonstrated that in the initial phase of loading the AE arises mainly from the distal femur. Prior to bone failure the AE arose predominantly from the femoral neck, consistent with the location of the final fracture. The two sensors located closest to the fracture showed a statistically significant higher amount of detected events as the remaining six sensors (One-way ANOVA followed by Tukey's test, p<0.05, Figure 1 [Fig. 1]). In conclusion, analysis and statistical evaluation of the AE-events is suited to deal with the bone material challenges. Thus the spatial and temporal damage phases can safely be identified. In future, utilizing AEA for risk estimation of osteoporotic induced hip fractures will enable a more effective diagnosis, prophylaxis and treatment for the affected patients.