The Influence of Component Alignment and Ligament Properties on Tibiofemoral Contact Forces in Total Knee Replacement

Abstract

The study objective was to investigate the influence of coronal plane alignment and ligament properties on total knee replacement (TKR) contact loads during walking. We created a subject-specific knee model of an 83-year-old male who had an instrumented TKR. The knee model was incorporated into a lower extremity musculoskeletal model and included deformable contact, ligamentous structures, and six degrees-of-freedom (DOF) tibiofemoral and patellofemoral joints. A novel numerical optimization technique was used to simultaneously predict muscle forces, secondary knee kinematics, ligament forces, and joint contact pressures from standard gait analysis data collected on the subject. The nominal knee model predictions of medial, lateral, and total contact forces during gait agreed well with TKR measures, with root-mean-square (rms) errors of 0.23, 0.22, and 0.33 body weight (BW), respectively. Coronal plane component alignment did not affect total knee contact loads, but did alter the medial-lateral load distribution, with 4 deg varus and 4 deg valgus rotations in component alignment inducing þ17% and À23% changes in the first peak medial tibiofemoral contact forces, respectively. A Monte Carlo analysis showed that uncertainties in ligament stiffness and reference strains induce 60.2 BW uncertainty in tibiofemoral force estimates over the gait cycle. Ligament properties had substantial influence on the TKR load distributions, with the medial collateral ligament and iliotibial band (ITB) properties having the largest effects on medial and lateral compartment loading, respectively. The computational framework provides a viable approach for virtually designing TKR components, considering parametric uncertainty and predicting the effects of joint alignment and soft tissue balancing procedures on TKR function during movement.

Patients With Medial Knee Osteoarthritis Reduce Medial Knee Contact Forces by Altering Trunk Kinematics, Progression Speed, and Stepping Strategy During Stair Ascent and Descent: A Pilot Study

“…As dynamic validation, the calculated KCF were compared with instrumented implant data provided through the Grand Challenge Competition to Predict in vivo Knee Loads, a subject-specific data set that allows researchers to validate muscle and contact forces estimated in the knee. When comparing between the measured and calculated KCF, the joint contact load prediction errors (root-mean-square (rms) error = 0.33 BW) 36,38 were comparable to those (rms error = 0.26 BW) observed from a unique optimization approach, termed force-dependent kinematics, introduced by the 2014 "Grand Challenge" winner 39 , and slightly better than those that have been obtained using traditional optimization or forward dynamic simulations 40,41 . Calculated KCF were normalized to body weight (BW) and moments to the product of body weight and height (BW×Ht).…”

Alterations of musculoskeletal models for a more accurate estimation of lower limb joint contact forces during normal gait: A systematic review

“…Similarly, several alterations may thus have been omitted. This was for example the case for the study of Smith et al (Smith et al, 2016), studying modified styles of gait (i.e. smooth and bouncy), where a variant of the Arnold et al model (Arnold et al, 2010) was used in an inverse dynamics-based optimisation to evaluate the impact of alterations on knee alignment and knee ligament stiffness on tibiofemoral joint contact forces accuracy.…”

Development and validation of a subject-specific moving-axis tibiofemoral joint model using MRI and EOS imaging during a quasi-static lunge

“…Specifically, the kinematics will remain the same independent of external load, which for some applications may play a role. Complex multibody contact models (Guess et al, 2014;Marra et al, 2017Marra et al, , 2015Smith et al, 2017;Thelen et al, 2014) were established to avoid these limitations; these models are much more computationally expensive and therefore applied on smaller cohorts. Although large improvements were achieved by modeling the TF joint as a moving-axis, creating a linear relationship between EFC and FFC axes may not capture the entire trend.…”