Computational Simulation of Patellar Instability

Patellar Instability

Computational simulation will be performed to represent motion of knees with a dislocating kneecap. Common surgical treatment methods will be simulated and anatomical parameters commonly associated with the dislocation will be varied in order to characterize the most appropriate surgical approach as a function of knee anatomy.

The two most common stabilization procedures for patients with recurrent patellar instability are reconstruction of the medial patellofemoral ligament (MPFL) and medialization of the tibial tuberosity. MPFL reconstruction has been growing in popularity, due in large part to the technical demands of tibial tuberosity realignment and concerns related to bone healing across the osteotomy. In cases of severe trochlear dysplasia and/or a dramatically lateralized tibial tuberosity, an MPFL graft tensioned according to current standards may not provide sufficient resistance to limit lateral patellar tracking that causes continued instability. Increasing graft tension could overload medial patellofemoral cartilage. The proposed study is based on the hypothesis that the ability of MPFL reconstruction to effectively limit lateral patellar maltracking decreases as trochlear dysplasia and the lateral position of the tibial tuberosity increase. Computational dynamic simulation of knee function will be performed to establish anatomical standards for which tibial tuberosity medicalization is more likely than MPFL reconstruction to limit patellar maltracking without overloading patellofemoral cartilage. The first specific aim is to computationally replicate lateral patellar maltracking and pressure applied to cartilage during function for patients being treated for patellar instability. Multibody dynamics knee models representing patients being treated for recurrent patellar instability will be based on 3D reconstructions from MRI scans. The modeling technique treats the bones and cartilage surfaces as rigid bodies with Hertzian contact determining contact forces and guiding joint motion. Discrete element analysis techniques will be used to characterize contact pressure patterns based on overlap of cartilage surfaces. Models will be individually validated by comparing output to in vivo data. The source of the in vivo data will be computational reconstruction of in vivo function based on motions performed by the patients who provide the imaging data for model development. The second specific aim will be to computationally characterize the influence of surgical stabilization on knee function for individual patients. MPFL reconstruction and tibial tuberosity medialization, each with variations in surgical parameters, will be simulated. The actual surgical procedures performed on the patients will be simulated, with the influence on lateral tracking compared to in vivo results to validate the representation of the surgical procedures. The third specific aim will be to compare surgical options as a function of patellofemoral anatomy. Variations in patellar tracking and pressure applied to cartilage will be compared between MPFL reconstruction and tuberosity medialization. In addition, techniques to parametrically alter trochlear dysplasia and tuberosity lateralization within the models will be developed. Simulations will be performed while varying anatomy to set ranges over which each surgical option can limit patellar maltracking without elevating contact pressures. The modeling system will be available for future studies addressing additional surgical options and anatomical parameters related to patellar instability.

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