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A biomechanical assessment of modular and monoblock revision hip implants using FE analysis and strain gage measurements

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journal contribution
posted on 21.05.2021, 17:36 authored by Habiba Bougherara, Rad Zdero, Suraj Shah, Milan Niric, Marcello Papini, Paul Zalzal, Emil H. Schemitsch
Background: The bone loss associated with revision surgery or pathology has been the impetus for developing modular revision total hip prostheses. Few studies have assessed these modular implants quantitatively from a mechanical standpoint.
Methods: Three-dimensional finite element (FE) models were developed to mimic a hip implant alone (Construct A) and a hip implant-femur configuration (Construct B). Bonded contact was assumed for all interfaces to simulate long-term bony on growth and stability. The hip implants modeled were a Modular stem having two interlocking parts (Zimmer Modular Revision Hip System, Zimmer, Warsaw, IN, USA) and a Monoblock stem made from a single piece of material (Stryker Restoration HA Hip System, Stryker, Mahwah, NJ, USA). Axial loads of 700 and 2000 N were applied to Construct A and 2000 N to Construct B models. Stiffness, strain, and stress were computed. Mechanical tests using axial loads were used for Construct A to validate the FE model. Strain gages were placed along the medial and lateral side of the hip implants at 8 locations to measure axial strain distribution.
Results: There was approximately a 3% average difference between FE and experimental strains for Construct A at all locations for the Modular implant and in the proximal region for the Monoblock implant. FE results for Construct B showed that both implants carried the majority (Modular, 76%; Monoblock, 66%) of the 2000 N load relative to the femur. FE analysis and experiments demonstrated that the Modular implant was 3 to 4.5 times mechanically stiffer than the Monoblock due primarily to geometric differences.
Conclusions: This study provides mechanical characteristics of revision hip implants at sub-clinical axial loads as an initial predictor of potential failure.

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