Patellofemoral Knee Pain: An Experimental and Computational Analysis
Development and Validation of a Kinematically-Driven Computational Model of the Patellofemoral Joint
Osteoarthritis (OA) of the patellofemoral joint affects about 25% of the population, and yet despite its high prevalence, the etiology of patellofemoral OA remains poorly understood. Patellofemoral pain (PFP) at a young age is recognized as an early indicator for the development of OA. It has been proposed that PFP can develop due to increased articular contact pressures resulting from maltracking of the patella. Current methods for measuring patellofemoral joint stress in vivo are limited and require the use of computational models. Therefore, the objective of this study is to develop a validated computational knee model driven by knee joint kinematics and assess the models ability to discriminate different knee states using subject-specific kinematics data in vivo.
In Vitro Data Collection
An in vitro study was performed to develop and validate specimen-specific discrete element models (DEMs) for future advancements and use in vivo. Three cadaveric knees were imaged for anatomical geometry to be used as input for models, dissected, and then experimentally tested in quasi-static loading positions with physiological muscle loads applied to the quadriceps tendons. Positional displacements were digitized for each bone using a FaroArm digitizing system and joint kinematics were calculated at each position to be used as input data to drive the computational models. Pressure maps were recorded for the tibiofemoral and patellofemoral joints using TekScan® pressure sensors as validation for model output.
A discrete element modeling (DEM) approach is currently being utilized for computational analysis of in vitro data collected. Inputs to the computational model require: 1) specimen-specific geometry collected using highly-accurate MR imaging methods, 2) knee joint kinematics collected experimentally, and 3) material properties of knee joint cartilage. Validation will be performed by comparing in vitro contact pressures with those estimated by the computational model. Preliminary data has demonstrated good agreement between the model and experimental results.
In Vivo Model Implementation
Collaborations with Dr. Scott Tashman and the Department of Orthopaedic Surgery have resulted in the collection of highly accurate knee joint kinematics from patients with and without patellofemoral OA. By combining these subject-specific knee joint kinematics and validated computational models, it will be possible to examine the effect of patellofemoral joint motion on articular joint contact pressure. In the future, these models could be utilized to examine the effect of rehabilitation treatments for patients with patellofemoral joint dysfunction and assist clinicians in creating a subject-specific treatment plan to help manage pain for these patients.