Quantifying the interactions and effects of joint function, pathology and pain in end-stage OA to understand why Total Knee Replacement (TKR) outcomes vary

Start date: July 2017/October 2017

This is an interdisciplinary project between the Schools of Engineering, Psychology, Healthcare and Cardiff and Vale Orthopaedic Centre.

Outline

Despite a 20% dissatisfaction rate, TKR patients are generally treated as a homogenous group. Multifactorial data is required to improve diagnosis of OA and stratify patients in order to predict outcomes and better target therapeutic and surgical interventions. The Centre enables multiple protocol studies on the same subject.

Our studies differ from existing patient-based stratification studies for OA:

1.we exploit novel decision making tools (Principal Component Analysis/uncertain reasoning) linking biology, biomechanical and clinical data to discover which factor combinations predict poor outcomes, why, and how this can be remedied by targeting treatments
2.we combine multifactorial data for each patient, pre-to-post intervention. These will lead to patient stratification, effective targeting of management.

Approach

Biomechanics will be measured for Activities of Daily Living (ADL), and quantified for patients (pre- and post-TKR) and for healthy volunteers. These subjects will also be assessed pre- and post-TKR, using joint imaging combined with motion capture.

Analysis

ADL biomechanics, patients reported scores, physiotherapy and patient history, pre-surgery MRI to define OA markers, X-ray, post-surgery low-dose CT to quantify implant alignment (if available), and combined motion analysis, fluoroscopy and image registration, EMG and forceplate data. Long leg X-rays will define knee obliquity/leg alignment. TKR CAD models acquired with industry for image registration/fluoroscopy, will define implant kinematics.

Outputs

Biomechanical changes will be assessed (Visual3D). Knee translations/rotations and contact locations quantified using image registration/fluoroscopy. Muscle activations (EMG), marker and forceplate data will drive joint loading models (OpenSIM).

This will provide gait, stair ascent/descent, sit-to-stand/stand-to-sit data for the Cardiff Classifier to identify whether biomechanical indicators of recovery are evident pre-surgery, and to quantify knee obliquity/mechanical axes/implant orientation pre-to-post-TKR.

TKR patient stratification will be based on biomechanics, biological, pain, clinical and psychosocial data for late-stage knee OA patients.

Interdisciplinary aspects

This is an interdisciplinary project between the Schools of Engineering, Psychology, Healthcare and Cardiff and Vale Orthopaedic Centre. The project gives us an opportunity to link biomarkers from joint tissue and clinical outcome measures to longitudinal changes in patient biomechanics.

Discipline hopping

Opportunities exist to work across academic disciplines such as Biomedical Sciences, Engineering and in Physiotherapy, Orthopaedics, Rheumatology settings.

The successful applicant will join an international team of researchers in a Center of Excellence for Arthritis Research and have access to state-of–the art technology to address research questions and long-standing expertise in research translation.

For further information, please see: http://www.cardiff.ac.uk/arthritis-biomechanics-bioengineering-centre/study-opportunities/phd-studentships