Computational framework for population-based evaluation of TKR-implanted patellofemoral joint mechanics.

Differences in patient anatomy are known to influence joint mechanics. Accordingly, intersubject anatomical variation is an important consideration when assessing the design of joint replacement implants. The objective of this study was to develop a computational workflow to perform population-based evaluations of total knee replacement implant mechanics considering variation in patient anatomy and to assess the potential for an efficient sampling strategy to support design phase screening analyses. The approach generated virtual subject anatomies using a statistical shape model of the knee and performed virtual implantation to size and align the implants. A finite-element analysis simulated a deep knee bend activity and predicted patellofemoral (PF) mechanics. The study predicted bounds of performance for kinematics and contact mechanics and investigated relationships between patient factors and outputs. For example, the patella was less flexed throughout the deep knee bend activity for patients with an alta patellar alignment. The results also showed the PF range of motions in AP and ML were generally larger with increasing femoral component size. Comparison of the 10-90% bounds between sampling strategies agreed reasonably, suggesting that Latin Hypercube sampling can be used for initial screening evaluations and followed up by more intensive Monte Carlo simulation for refined designs. The platform demonstrated a functional workflow to consider variation in joint anatomy to support robust implant design.

Statistical shape modeling predicts patellar bone geometry to enable stereo-radiographic kinematic tracking.

Complications in the patellofemoral (PF) joint of patients with total knee replacements include patellar subluxation and dislocation, and remain a cause for revision. Kinematic measurements to assess these complications and evaluate implant designs require the accuracy of dynamic stereo-radiographic systems with 3D-2D registration techniques. While tibiofemoral kinematics are typically derived by tracking metallic implants, PF kinematic measurements are difficult as the patellar implant is radiotransparent and a representation of the resected patella bone requires either pre-surgical imaging and precise implant placement or post-surgical imaging. Statistical shape models (SSMs), used to characterize anatomic variation, provide an alternative means to obtain the representation of the resected patella for use in kinematic tracking. Using a virtual platform of a stereo-radiographic system, the objectives of this study were to evaluate the ability of an SSM to predict subject-specific 3D implanted patellar geometries from simulated 2D image profiles, and to formulate an effective data collection methodology for PF kinematics by considering accuracy for a variety of patient pose scenarios. An SSM of the patella was developed for 50 subjects and a leave-one-out approach compared SSM-predicted and actual geometries; average 3D errors were 0.45±0.07mm (mean±standard deviation), which is comparable to the accuracy of traditional segmentation. Further, initial imaging of the patella in five unique stereo radiographic perspectives yielded the most accurate representation. The ability to predict the remaining patellar geometry of the implanted PF joint with radiographic images and SSM, instead of CT, can reduce radiation exposure and streamline in vivo kinematic evaluations.

Statistical modeling to characterize relationships between knee anatomy and kinematics.

The mechanics of the knee are complex and dependent on the shape of the articular surfaces and their relative alignment. Insight into how anatomy relates to kinematics can establish biomechanical norms, support the diagnosis and treatment of various pathologies (e.g., patellar maltracking) and inform implant design. Prior studies have used correlations to identify anatomical measures related to specific motions. The objective of this study was to describe relationships between knee anatomy and tibiofemoral (TF) and patellofemoral (PF) kinematics using a statistical shape and function modeling approach. A principal component (PC) analysis was performed on a 20-specimen dataset consisting of shape of the bone and cartilage for the femur, tibia and patella derived from imaging and six-degree-of-freedom TF and PF kinematics from cadaveric testing during a simulated squat. The PC modes characterized links between anatomy and kinematics; the first mode captured scaling and shape changes in the condylar radii and their influence on TF anterior-posterior translation, internal-external rotation, and the location of the femoral lowest point. Subsequent modes described relations in patella shape and alta/baja alignment impacting PF kinematics. The complex interactions described with the data-driven statistical approach provide insight into knee mechanics that is useful clinically and in implant design.

Effects of resection thickness on mechanics of resurfaced patellae.

Patellar resection thickness during total knee replacement (TKR) has been cited as a contributor to patellar fracture, anterior knee pain and quadriceps efficiency; however, optimal thickness required to minimize clinical complications remains unclear. The objectives of the current study were to determine how patellar resection thickness and bone quality impacts patellar bone strain, kinematics, and quadriceps efficiency. A series of specimen-specific finite element models of the knee joint with distributed patellar bone material properties were developed. Each specimen was virtually implanted with a TKR system. Each specimen was analyzed with patellar bone resected to thicknesses which varied from 9 to 14 mm. Simulations with reduced modulus bone were also performed. Each model perturbation was evaluated during a dynamic squat cycle, and bone strain, quadriceps force and six-degree-of-freedom kinematics were predicted. Highest peak bone strain was predicted in the thinnest patellae, indicating greatest risk of patellar fracture; highest median bone strain was predicted in the thickest patellae. Consistent differences in quadriceps efficiency were predicted; in early flexion the thickest patellae required the least quadriceps force. Greater sagittal plane tilt was observed for the thinnest patellae. Reduced modulus models (50% lower modulus) demonstrated an increase in peak bone strain of up to seven times the original modulus models. Understanding the complex interactions between patellar resection thickness, muscle requirements, kinematics, bone quality, and bone property distribution may aid in developing an understanding of which patients are most at risk from patellar fracture and anterior knee pain and how best to treat individuals to reduce potential complications.