Probabilistic analysis of an uncemented total hip replacement

Dopico-González, Carolina; New, A.M.R.; Browne, Martin

doi:10.1016/j.medengphy.2009.01.002

Cited by 32 publications

(34 citation statements)

References 27 publications

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“…The variation of each parameter is now defined by a distribution, rather than by the fixed levels used in parametric and DOE studies. The most commonly used approach is the Monte Carlo analysis (Pal et al, 2008;Viceconti et al, 2006;Laz et al, 2006Laz et al, , 2007Strickland et al, 2010;Dopico-Gonzalez et al, 2009Prendergast et al, 2011;Galibarov et al, 2012), where the parameter space is randomly sampled. The Monte Carlo approach suffers from the curse of dimensionality, with the number of deterministic analyses needed increasing exponentially with the addition of more parameters.…”

Section: Design Of Computer Based Experimentsmentioning

confidence: 99%

“…The challenge in developing and implementing probabilistic techniques is automating the simulation process, particularly when aiming to generate hundreds or thousands of models to explore the effects implant alignment or patient to patient variability. Automated pipelines to generate implanted bone segments have been developed using; CAD based boolean operations followed by automated meshing (Taylor et al, 2013;Dopico-Gonzalez et al, 2009; meshed based boolean operations ; or mesh morphing (Bah et al, 2009). Early attempts to account for patient variability either manually modelled a small cohort of subjects (Radcliffe and Taylor, 2007;Perillo-Marcone et al, 2004;Lengsfeld et al, 2005) or scaled either the size (Viceconti et al, 2006) and/or the material properties (Viceconti et al, 2006;Wong et al, 2005) of a single femur.…”

Section: Design Of Computer Based Experimentsmentioning

confidence: 99%

See 1 more Smart Citation

Four decades of finite element analysis of orthopaedic devices: Where are we now and what are the opportunities?

Taylor

Prendergast

2015

Journal of Biomechanics

139

106

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a b s t r a c tFinite element has been used for more than four decades to study and evaluate the mechanical behaviour total joint replacements. In Huiskes seminal paper "Failed innovation in total hip replacement: diagnosis and proposals for a cure", finite element modelling was one of the potential cures to avoid poorly performing designs reaching the market place. The size and sophistication of models has increased significantly since that paper and a range of techniques are available from predicting the initial mechanical environment through to advanced adaptive simulations including bone adaptation, tissue differentiation, damage accumulation and wear. However, are we any closer to FE becoming an effective screening tool for new devices? This review contains a critical analysis of currently available finite element modelling techniques including (i) development of the basic model, the application of appropriate material properties, loading and boundary conditions, (ii) describing the initial mechanical environment of the bone-implant system, (iii) capturing the time dependent behaviour in adaptive simulations, (iv) the design and implementation of computer based experiments and (v) determining suitable performance metrics.The development of the underlying tools and techniques appears to have plateaued and further advances appear to be limited either by a lack of data to populate the models or the need to better understand the fundamentals of the mechanical and biological processes. There has been progress in the design of computer based experiments. Historically, FE has been used in a similar way to in vitro tests, by running only a limited set of analyses, typically of a single bone segment or joint under idealised conditions. The power of finite element is the ability to run multiple simulations and explore the performance of a device under a variety of conditions. There has been increasing usage of design of experiments, probabilistic techniques and more recently population based modelling to account for patient and surgical variability. In order to have effective screening methods, we need to continue to develop these approaches to examine the behaviour and performance of total joint replacements and benchmark them for devices with known clinical performance.Finite element will increasingly be used in the design, development and pre-clinical testing of total joint replacements. However, simulations must include holistic, closely corroborated, multi-domain analyses which account for real world variability.

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Section: Design Of Computer Based Experimentsmentioning

confidence: 99%

Section: Design Of Computer Based Experimentsmentioning

confidence: 99%

Four decades of finite element analysis of orthopaedic devices: Where are we now and what are the opportunities?

Taylor

Prendergast

2015

Journal of Biomechanics

139

106

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show abstract

“…Depending on the application, these studies also incorporate uncertainties related to geometry and loading conditions. However, some of these studies (Dopico-Gonzalez et al, 2009;Nicolella et al, 2006;Viceconti et al, 2006) apply a simplified homogeneous material which uses the same random variable everywhere to describe the Young's modulus and which is independent of r. In Laz et al (2007) and Taddei et al (2006) E2r relationship in form (1) is used, with a and b modeled as the Gaussian random variables based on the experimental results reported by Keller (1994). In this way, the standard errors for the estimation of the regression parameters are used as standard deviations, while the estimates for a and b are used as mean values.…”

Section: Introductionmentioning

confidence: 99%

“…A review of probabilistic methods and their application to bonemechanics can be found in Laz and Browne (2010), and several relating particularly to the human femur in Dopico-Gonzalez et al (2009), Laz et al (2007), Nicolella et al (2006), Taddei et al (2006), and Viceconti et al (2006). Depending on the application, these studies also incorporate uncertainties related to geometry and loading conditions.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the mechanical response of the femur with uncertain elastic properties

Wille

Rank

Yosibash

2012

Journal of Biomechanics

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“…Awareness of the need to account for such differences in the range of performance of different implants has led to a new wave of modelling approaches that attempt to include aspects of population variability when simulating implant behaviour, e.g. (Laz et al, 2006;Viceconti et al, 2006;Knight et al, 2007;Dopico-Gonzalez et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Computer simulating a clinical trial of a load-bearing implant: An example of an intramedullary prosthesis

Prendergast

Galibarov

Lowery

et al. 2011

Journal of the Mechanical Behavior of Biomedical Materials

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Probabilistic analysis of an uncemented total hip replacement

Cited by 32 publications

References 27 publications

Four decades of finite element analysis of orthopaedic devices: Where are we now and what are the opportunities?

Four decades of finite element analysis of orthopaedic devices: Where are we now and what are the opportunities?

Prediction of the mechanical response of the femur with uncertain elastic properties

Computer simulating a clinical trial of a load-bearing implant: An example of an intramedullary prosthesis

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