Subject-specific modelling of total knee arthroplasty

Background

Personalised bone geometries are essential in orthopaedics for planning surgeries. Subject specific model of total knee arthroplasty (TKA) patients is necessary for understanding soft tissue mechanics after TKA surgery, investigating the cause and designing of revision surgery.

Goal

The goal of this project is to investigate how change of soft tissue parameters affects passive laxity and functional movement of post TKA knee.

Method

We derive the personalized subject specific skeleton model from CT images from a TKA patient in CAMS-Knee dataset. Ligaments and muscles are added to build the multibody model.
Ligament stiffnesses are then randomly adjusted using Monte Calo method. Thousands of personalized subject specific models are created to simulate passive laxity to check the knee’s degree of motion and simulate functional activities to investigate ligaments’ stretch and muscles’ reaction.