Integrated contour detection and pose estimation for fluoroscopic analysis of knee implants

A novel method to accurately recreate in vivo loads and kinematics in computational models of the knee

Despite availability of in vivo knee loads and kinematics data, conventional load- and displacement-controlled configurations still can't accurately predict tibiofemoral loads from kinematics or vice versa. We propose a combined load- and displacement-control method for joint-level simulations of the knee to reliably reproduce in vivo contact mechanics. Prediction errors of the new approach were compared to those of conventional purely load- or displacement-controlled models using in vivo implant loads and kinematics for multiple subjects and activities (CAMS-Knee dataset). Our method reproduced both loads and kinematics more closely than conventional models and thus demonstrates clear advantages for investigating tibiofemoral contact or wear.

Modifications of femoral component design in multi-radius total knee arthroplasty lead to higher lateral posterior femoro-tibial translation

PURPOSE

As the aims of changes in total knee arthroplasty (TKA) designs are to reinstate more natural kinematics, the current study evaluated the in vivo kinematics in patients who underwent a cruciate retaining gradually changing femoral radius ("G-CURVE") against a cruciate retaining conventional changing femoral radius ("J-CURVE") geometry TKA design. The hypothesis of the study is that the G-CURVE design would allow a substantial increase in the femoral rollback compared to the J-CURVE design.

METHODS

Retrospective study design. Thirty patients were included (G-CURVE, n = 20; J-CURVE, n = 10). Single-plane fluoroscopic analysis and marker-based motion capture gait analysis was performed to analyse dynamic tibiofemoral motion during weight-bearing and unloaded activities at 24 month after index surgery.

RESULTS

The analysis of the medial and lateral points on the tibia plateau during the unloaded flexion-extension and the weight-bearing lunge activities revealed a significant difference in femoral rollback in G-CURVE TKA above 60° (p = 0.001) and 30° (p = 0.02) of knee flexion, respectively. Moreover, the lateral condyle of the G-CURVE showed a higher extent of femoral rollback while the lateral condyle of the J-CURVE rolled forward.

CONCLUSION

At 2 years post-operative, the G-CURVE TKA showed significant differences in femoro-tibial translation in comparison with the J-CURVE system, in vivo. The G-CURVE resulted in an increased lateral rollback and simultaneously in an elimination of the paradoxical medial roll-forward present in the J-CURVE design. Moreover, knee kinematics analysis showed significant differences between unloaded and weight-bearing conditions revealing the impact of load and muscle force. The analysis conducted in this study contributes to further understand the principal movement characteristics in widely used older designs in comparison with recently developed concepts to get a better overview on their potential benefits on in vivo kinematics.

LEVEL OF EVIDENCE

III.

Performance of local optimization in single-plane fluoroscopic analysis for total knee arthroplasty

Fluoroscopy-derived joint kinematics plays an important role in the evaluation of knee prostheses. Fluoroscopic analysis requires estimation of the 3D prosthesis pose from its 2D silhouette in the fluoroscopic image, by optimizing a dissimilarity measure. Currently, extensive user-interaction is needed, which makes analysis labor-intensive and operator-dependent. The aim of this study was to review five optimization methods for 3D pose estimation and to assess their performance in finding the correct solution. Two derivative-free optimizers (DHSAnn and IIPM) and three gradient-based optimizers (LevMar, DoNLP2 and IpOpt) were evaluated. For the latter three optimizers two different implementations were evaluated: one with a numerically approximated gradient and one with an analytically derived gradient for computational efficiency. On phantom data, all methods were able to find the 3D pose within 1mm and 1° in more than 85% of cases. IpOpt had the highest success-rate: 97%. On clinical data, the success rates were higher than 85% for the in-plane positions, but not for the rotations. IpOpt was the most expensive method and the application of an analytically derived gradients accelerated the gradient-based methods by a factor 3-4 without any differences in success rate. In conclusion, 85% of the frames can be analyzed automatically in clinical data and only 15% of the frames require manual supervision. The optimal success-rate on phantom data (97% with IpOpt) on phantom data indicates that even less supervision may become feasible.

Estimating total knee replacement joint load ratios from kinematics

Accurate prediction of loads acting at the joint in total knee replacement (TKR) patients is key to developing experimental or computational simulations which evaluate implant designs under physiological loading conditions. In vivo joint loads have been measured for a small number of telemetric TKR patients, but in order to assess device performance across the entire patient population, a larger patient cohort is necessary. This study investigates the accuracy of predicting joint loads from joint kinematics. Specifically, the objective of the study was to assess the accuracy of internal-external (I-E) and anterior-posterior (A-P) joint load predictions from I-E and A-P motions under a given compressive load, and to evaluate the repeatability of joint load ratios (I-E torque to compressive force (I-E:C), and A-P force to compressive force (A-P:C)) for a range of compressive loading profiles. A tibiofemoral finite element model was developed and used to simulate deep knee bend, chair-rise and step-up activities for five patients. Root-mean-square (RMS) differences in I-E:C and A-P:C load ratios between telemetric measurements and model predictions were less than 1.10e-3 Nm/N and 0.035 N/N for all activities. I-E:C and A-P:C load ratios were consistently reproduced regardless of the compressive force profile applied (RMS differences less than 0.53e-3 Nm/N and 0.010 N/N, respectively). When error in kinematic measurement was introduced to the model, joint load predictions were forgiving to kinematic measurement error when conformity between femoral and tibial components was low. The prevalence of kinematic data, in conjunction with the analysis presented here, facilitates determining the scope of A-P and I-E joint loading ratios experienced by the TKR population.