Computational Methods to Predict the Robustness of Cementless Total Hip Replacements

Lead Research Organisation: University of Southampton
Department Name: Faculty of Engineering & the Environment

Abstract

When a person undergoes hip replacement surgery, there are many factors that can affect how long it will last, many of which are not immediately apparent to the patient. Within each patient, the properties of bone can vary considerably; this difference in bone quality may be even more apparent between patients, particularly if one patient is more active than another, is heavier, or even if their diets are different. Other factors to consider are the geometries of the bone and implant, the quality of the surrounding tissues, the trauma associated with surgery and how well aligned the implant is, the last two of which are related to the surgical technique. Traditionally, experimental investigations into the performance of hip replacements have been limited to analysing one situation per experiment (e.g. one alignment and one bone). The results of these investigations can really only provide a good qualitative indicator as the biological environment can not be adequately simulated in the laboratory. Add to this, the huge number of experiments that would be required to simulate all possible scenarios (combinations of alignment, geometries, bone quality etc.) and experimental investigations soon become unfeasible. In order to address this shortcoming, computational methods have been developed that are capable of simulating an experimental test in a much shorter time. However, to date, most of these investigations again describe only one situation and many computational models are required to fully describe the effect of variations in only a single parameter. The proposed research program therefore, will deliver new computational tools that can account for variations in parameters such as the properties of bone, the loading conditions and the surgical technique simultaneously and efficiently, in a single analysis. It is anticipated that the immediate benefits of this research will include the development of models capable of determining which current implant designs are more forgiving of variations in misalignment and bone geometry, and are therefore likely to perform well regardless of the patient. In the medium term, these analyses should enable the surgeon to make an informed decision when selecting the most appropriate implant for his/her patient. In the longer term, it is believed that the research will help prosthesis manufacturers to arrive at new designs with improved performance and longevity, to the benefit of the manufacturer, the health provider, and of course, the patient.

Publications

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Bah M (2011) Effects of implant positioning in cementless total hip replacements in Computer Methods in Biomechanics and Biomedical Engineering

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Bah MT (2009) Effect of geometrical uncertainty on cemented hip implant structural integrity. in Journal of biomechanical engineering

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Laz PJ (2010) A review of probabilistic analysis in orthopaedic biomechanics. in Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine

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Shi J (2014) Sensitivity analysis of a cemented hip stem to implant position and cement mantle thickness. in Computer methods in biomechanics and biomedical engineering

 
Description A novel computational framework combining CAD and finite element (FE) computational modelling, a mesh morphing technique, design of experiments, contact analysis and Bayesian surrogate modelling has been developed.



The mesh morphing technique is developed to automate the FE model generation process for various femur-implant configurations to circumvent the manual steps of CAD modelling and remeshing procedures. In this way, implants can be rapdily 'virtually' implanted into any bone and thei
Exploitation Route The findings of this research are being directly delivered to clinicians to advise in pre-operative planning. By simulating the performance of the hip implant in a range of bones computationally, it is possible to determine what factors influence its performance. In the present study, the way the surgeon positions the implant was found to be important, and this information, has been disseminated to clinciancs at conferences and through direct contact at the University Hospitals Trust. The codes
Sectors Healthcare

 
Description The findings of this research have been used by orthopaedic companies and research organisations in the development of more robust orthopaedic implants. Using the methodologies developed, implants that are more tolerant of uncertainty in patient characteristics (size, weight, activity level, bone quality) can be proposed.
First Year Of Impact 2009
Sector Healthcare,Manufacturing, including Industrial Biotechology
Impact Types Societal,Economic

 
Description CETIM
Amount £190,713 (GBP)
Organisation Cetim 
Sector Private
Country France
Start 11/2012 
End 04/2014
 
Description EPSRC
Amount £466,444 (GBP)
Funding ID EP/K034847/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 11/2013 
End 10/2016
 
Description EPSRC
Amount £57,484 (GBP)
Funding ID KTS Q/07/10/004 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2010 
End 10/2011
 
Description TSB Towards Zero Prototyping
Amount £244,000 (GBP)
Funding ID 101881 
Organisation TSB Bank plc 
Sector Private
Country United Kingdom
Start 10/2014 
End 09/2016
 
Title Statistical modelling tool 
Description We have developed a modelling environment that enables the response of the surrounding environment (bone, tissues) to the presence of an implant. It also enables the effect of surgical technique to be considered, allowing designers to create more reliable, robust implants. 
Type Of Material Model of mechanisms or symptoms - in vitro 
Provided To Others? No  
Impact Supported a successful grant application. Used in the development of a new knee implant by a major orthopaedic company. 
 
Title Data analysis 
Description Using statistical analysis techniques, we have been able to create a population of thousands of possible femur and tibia geometries that enable us to assess how implants are likely to perform in a widely varying patient population. 
Type Of Material Data analysis technique 
Provided To Others? No  
Impact We have used the model to support research with orthopaedic companies interested in developing new implants 
 
Title Statistical modelling 
Description A collection of CT scans has been converted into a database of computational models that describe the variation in bone geometry and density across a population of over 100 patients 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact We have extended the database to produce thousands of possible patient bone geometries and densities using statistical modelling based on the original dataset 
 
Title Virtual patient software 
Description We are developing the models we have created further to allow rapid screening of potential implant designs to be undertaken in a population of 'virtual patients'. In this way, new designs can be assessed in a rapid and efficient manner - poor designs can be immediately eliminated rather than undergo extensive animal and clinical testing. The effect of surgical technique can be assessed in a similar 'virtual' environment. 
Type Of Material Computer model/algorithm 
Provided To Others? No  
Impact Research is on-going and surgeons are evaluating the potential for this software. 
 
Description CETIM 
Organisation Cetim
Country France 
Sector Private 
PI Contribution Knowledge transfer - assist in the development of a new hip implant design for CETIM
Collaborator Contribution Access to databases, company personnel, materials
Impact Preliminary development of a hip implant design
Start Year 2011
 
Description Collaborative work with Simpleware Ltd 
Organisation Simpleware Ltd
Country United Kingdom 
Sector Private 
PI Contribution The codes developed during the research were exploited by Simpleware Ltd, a software company who specialise in computational modelling. They subsequently sponsored a KTS grant carried out by the lead researcher on the EPSRC grant. The codes developed will be inroporated into a future software release. The knowledge transfer secondment has enabled the two groups to exchange ideas and modelling approaches, which has helped guide further research in the field of probabilistic appraoches in biomechanics. As a result of this, we have successfully established a relationship with CETIM France and are about to embark on a further research prgramme with them.
Impact Software development for the Simpleware modelling environment, Conference publication
Start Year 2010
 
Description Depuy International Ltd 
Organisation Depuy International
Country United Kingdom 
Sector Private 
PI Contribution Knowledge transfer - pre-clinical assessment techniques for their orthopaedic implants
Collaborator Contribution • Involvement and expertise of company employees • Access to design and clinical data • Materials, components and software support
Impact Development of statistically based methodology for performance prediction of orthopaedic implants. PhD sponsorship and journal papers.
 
Description Finsbury Orthopaedics Ltd 
Organisation DePuy Synthes
Country United States 
Sector Private 
PI Contribution Knowledge transfer
Collaborator Contribution • Involvement and expertise of company employees • Access to design and clinical data • Materials, components and software support
Impact Development of statistically based methodology fro performance prediction of orthopaedic implants
 
Title Virtual Patient Software 
Description The techniques investigated in the project helped support the creation of a software that assesses the performance of orthopaedic implants by automatically implanting and analysing a number of critical metrics. 
Type Of Technology Software 
Year Produced 2017 
Impact Presentation of technology to a major orthopaedic company in February 2017. Company considering adopting technology for new projects. 
 
Description Smallpeice 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? Yes
Geographic Reach National
Primary Audience Schools
Results and Impact Demonstration on how statistical analysis can be used to delineate behaviour of a population based on their walking characteristics

Increased interest in biomedical engineering from A level students, much improved application numbers in mechanical engineering (not explicitly down to this activity, but students on course tended to come to Southampton)
Year(s) Of Engagement Activity 2011,2012,2013,2014