Assessment of cortical thickening in total hip replacement patients
Lead Research Organisation:
University of Leeds
Department Name: Mechanical Engineering
Abstract
Total hip replacement (THR) is a successful operation but the number of devices requiring revision is continuing to rise. The aging population, growing cohorts of more active and more obese patients, are all increasing the demands on devices: they need to last for longer and withstand higher loads than ever before. Changes in the bone ('distal cortical thickening') are often observed on x-rays of THR patients prior to revision, but there has been little characterisation of these changes, how they relate to the choice of implant or to the outcomes for the patient.
The aim of this study is to develop methods to characterise and quantify distal cortical thickening objectively using automated image-processing methods, and assess if and how it relates to subsequent stem loosening.
The main objectives are: [1] To develop methods to characterise and quantify cortical thickening from x-ray evidence. [2] To validate the methods and define their accuracy by comparison with (a) manual methods used by clinical professionals, and (b) 3D CT/MRI imaging of the same patients/cadaveric specimens. [3] To apply the methods to larger datasets, provided by our collaborators at Musgrave Park Hospital, Belfast and other sources accessed through our industry partnership, and assess the progression of changes over time and the relationship to patient outcome. [4] To extend the methods of analysis using statistical shape modelling and finite element analysis to examine the biomechanical effects of different femoral fit scenarios, for both primary and revision stems.
This work fits to EPSRC HealthTech Grand Challenges on Optimising Treatment (evidence based decision making) and Frontiers of Physical Intervention (improving success rates of implants), as well as EPSRC Delivery Plan priorities of training industry relevant PhDs and enhancing future digital technologies. It has been co-developed with our industry partner and is driven by both industry and clinical need. The work will provide new evidence of the underpinning mechanisms of bone remodelling and quantify its effects. It will provide evidence for surgical recommendations on device selection for different patients and may provide a route to monitor at-risk cases more objectively.
The aim of this study is to develop methods to characterise and quantify distal cortical thickening objectively using automated image-processing methods, and assess if and how it relates to subsequent stem loosening.
The main objectives are: [1] To develop methods to characterise and quantify cortical thickening from x-ray evidence. [2] To validate the methods and define their accuracy by comparison with (a) manual methods used by clinical professionals, and (b) 3D CT/MRI imaging of the same patients/cadaveric specimens. [3] To apply the methods to larger datasets, provided by our collaborators at Musgrave Park Hospital, Belfast and other sources accessed through our industry partnership, and assess the progression of changes over time and the relationship to patient outcome. [4] To extend the methods of analysis using statistical shape modelling and finite element analysis to examine the biomechanical effects of different femoral fit scenarios, for both primary and revision stems.
This work fits to EPSRC HealthTech Grand Challenges on Optimising Treatment (evidence based decision making) and Frontiers of Physical Intervention (improving success rates of implants), as well as EPSRC Delivery Plan priorities of training industry relevant PhDs and enhancing future digital technologies. It has been co-developed with our industry partner and is driven by both industry and clinical need. The work will provide new evidence of the underpinning mechanisms of bone remodelling and quantify its effects. It will provide evidence for surgical recommendations on device selection for different patients and may provide a route to monitor at-risk cases more objectively.
People |
ORCID iD |
| Callum Keighley (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/W524372/1 | 30/09/2022 | 29/09/2028 | |||
| 2744952 | Studentship | EP/W524372/1 | 30/09/2022 | 30/03/2026 | Callum Keighley |