Assessment of a fictitious domain method for patient-specific biomechanical modelling of press-fit orthopaedic implantation

• Published in: Computer methods in biomechanics and biomedical engineering Vol. 15; no. 5; pp. 501 - 516
• Main Authors: Kallivokas, L. F., Na, S.-W., Ghattas, O., Jaramaz, B.
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis Group 01.05.2012
• Subjects: Adult; Arthroplasty, Replacement, Hip - methods; Arthroplasty, Replacement, Hip - statistics & numerical data; Biomechanical Phenomena; Computer Simulation; CT- or MRI-scan; Elastic Modulus; fictitious domain method; Finite Element Analysis; Hip Prosthesis - statistics & numerical data; Humans; Imaging, Three-Dimensional; linear elasticity; medical imaging; Models, Anatomic; Models, Biological; press-fit implant; regular and geometry-conforming finite element methods; Surgery, Computer-Assisted - methods; Surgery, Computer-Assisted - statistics & numerical data; Tomography, X-Ray Computed
• ISSN: 1025-5842; 1476-8259
• DOI: 10.1080/10255842.2010.545822

In this article, we discuss an application of a fictitious domain method to the numerical simulation of the mechanical process induced by press-fitting cementless femoral implants in total hip replacement surgeries. Here, the primary goal is to demonstrate the feasibility of the method and its advantages over competing numerical methods for a wide range of applications for which the primary input originates from computed tomography-, magnetic resonance imaging- or other regular-grid medical imaging data. For this class of problems, the fictitious domain method is a natural choice, because it avoids the segmentation, surface reconstruction and meshing phases required by unstructured geometry-conforming simulation methods. We consider the implantation of a press-fit femoral artificial prosthesis as a prototype problem for sketching the application path of the methodology. Of concern is the assessment of the robustness and speed of the methodology, for both factors are critical if one were to consider patient-specific modelling. To this end, we report numerical results that exhibit optimal convergence rates and thus shed a favourable light on the approach.