Abstract
Tibial and femoral component malalignment is poorly tolerated in uni- and bi-compartmental knee replacement. Poor outcomes may still occur while using navigation or robotic-assisted bone preparation, which currently require surgeon assessment to establish a preoperative plan for implant placement. Choosing where to place partial knee replacement components is a challenging task that depends on complicated interactions between patient variability and implant design.
We developed a patient-customizable knee model that can assist surgeons by providing a quantitative measure of knee laxity. In order to build upon previous knee modeling efforts and to demonstrate the technique, three-dimensional femur and tibia bone and articular cartilage geometries were obtained from the OpenKnee finite element repository (https://simtk.org/home/openknee). Generic, patient-customizable transversely isotropic, fibril-reinforced cruciate and collateral ligament models, which allow for bone-to-ligament, cartilage-to-ligament, ligament-to-ligament interaction, were substituted into the model (Figure 1). This reduces the dependency on expensive and time-consuming MRI segmentation required to recreate soft-tissue geometries. Ligament pre-tensioning and insertion and origin sites (approximated as elliptical regions fit to the bone surface) can be tuned to match a patient's passive knee kinematics.
The model was run through a series of simulated passive flexion paths. At each degree of flexion, combinations of anterior-posterior and medial-lateral forces as well as internal-external and varus/valgus moments were applied and the resulting joint kinematics were recorded. These results represent the passive envelope of knee motion, which is used to characterize knee laxity. An optimization framework was developed to iteratively tune the cruciate ligament model to match a virtual set of passive loading conditions.
A majority of preoperative planning techniques only monitor geometric targets such as flexion and extension gaps, limb alignment, restoration of the joint line, and tibial component slope. Patient-customized knee models can be tuned to quantify post-operative knee laxity and identify the range of tolerable alignment of partial knee replacement components. Future work will employ in-vitro testing to validate the capability of the model to identify patient-specific cruciate ligament parameters.
