A patient-specific wear prediction framework for an artificial knee joint with coupled musculoskeletal multibody-dynamics and finite element analysis

Abstract

A novel wear prediction framework was developed by coupling a patient-specific lower extremity musculoskeletal multibody dynamics model with the finite element contact mechanics and wear model of total knee replacement. The tibiofemoral contact forces and kinematics were influenced by articular surface wear, and in turn, the variations from the knee dynamics resulted in increases in the volumetric wear of 404.41 mm 3 after 30 million cycle simulation from 380.86 mm 3 from the traditional wear prediction using fixed load/motions. The developed patient-specific wear prediction framework provided a reliable virtual platform for investigating articular surface wear of total knee replacements.

Finite element analysis of polyethylene wear in total hip replacement: A literature review

“…Finite Element Analysis (FEA) of hip joint bearing wear, which was pioneered by Maxian et al [21][22][23] and adapted by a considerable number of researchers over the past two decades, allows more comprehensive algorithms to simulate the contact behavior, to gain understanding of the wear mechanics and provide initial screening of various parameters. More importantly, the numerical technique is also applicable to other types of joint replacements and has been employed on the wear prediction of knee [24][25][26][27][28][29][30][31], shoulder [32][33][34][35][36], ankle [37][38][39] and spine [40,41]. Nevertheless, the accuracy of FEA prediction depends on inputs from laboratory experiments and it is critical to validate the FEA model before it can provide guidance to testing and assist product development.…”

Editorial: Biotribology and Biotribocorrosion Properties of Implantable Biomaterials

“…Considering the above, to date, in-silico wear prediction models of artificial human implants attract the attentions of researchers to obtain complete tribological theoretical and numerical models useful for the in-silico testing (O'Brien et al, 2015;Mattei et al, 2016;Affatato et al, 2018), which could avoid the standard in-vitro time-consuming investigation procedures (simulators) and could contribute as tool for a more and more accurate tribological design of human prostheses. Obviously, the accurate wear prediction of artificial joints requires to develop detailed tribological models accounting for the complexity and the multiscale of wear phenomenon (Vakis et al, 2018) which requires scientific knowledge in many fields, such as contact mechanics (Popov, 2010), topographic contact surfaces characterization (Merola et al, 2016), new materials formulations (Affatato et al, 2015), stress-strain analysis and FEM/BEM simulations (Ruggiero et al, 2018;Ruggiero and D'Amato R, 2019), musculoskeletal multibody modeling (Zhang et al, 2017), unsteady synovial lubrication modeling (boundary/mixed, hydro-dynamic and EHD) (Ruggiero and Sicilia, 2020), tribo-corrosion (Tan et al, 2016), metal transfer phenomena (Affatato et al, 2017), biomaterials characterizations (Ruggiero et al, 2016), etc. Moreover, innovative biomaterials and manufacturing procedures (e.g., 3D printing), novel surface modification (coatings) constitute new and exciting research areas (Ten Kate et al, 2017).…”

An Approach to Developing Customized Total Knee Replacement Implants

“…TKR implant has traditionally been tested in knee wear simulator to determine its ability to resist wear. The computational models can be used to predict wear of implant as did by Zhang et al [ 33 ], and they created a patient-specific wear prediction framework for TKR implant combined musculoskeletal multibody dynamics and finite element analysis. An interesting research was carried out by Chen et al [ 34 ], and they created a full lower limb subject-specific musculoskeletal model that is scaled from a generic MSK model according to patient's CT images and gait dataset.…”