Development and validation of subject-specific pediatric multibody knee kinematic models with ligamentous constraints.

Computational knee models that replicate the joint motion are important tools to discern difficult-to-measure functional joint biomechanics. Numerous knee kinematic models of different complexity, with either generic or subject-specific anatomy, have been presented and used to predict three-dimensional tibiofemoral (TFJ) and patellofemoral (PFJ) joint kinematics of cadavers or healthy adults, but not pediatric populations. The aims of this study were: (i) to develop subject-specific TFJ and PFJ kinematic models, with TFJ models having either rigid or extensible ligament constraints, for eight healthy pediatric participants and (ii) to validate the estimated joint and ligament kinematics against in vivo kinematics measured from magnetic resonance imaging (MRI) at four TFJ flexion angles. Three different TFJ models were created from MRIs and used to solve the TFJ kinematics: (i) 5-rigid-link parallel mechanism with rigid surface contact and isometric anterior cruciate (ACL), posterior cruciate (PCL) and medial collateral (MCL) ligaments (ΔLnull), (ii) 6-link parallel mechanism with minimized ACL, PCL, MCL and lateral collateral ligament (LCL) length changes (ΔLmin) and (iii) 6-link parallel mechanism with prescribed ACL, PCL, MCL and LCL length variations (ΔLmatch). Each model's geometrical parameters were optimized using a Multiple Objective Particle Swarm algorithm. When compared to MRI-measured data, ΔLnull and ΔLmatch performed the best, with average root mean square errors below 6.93° and 4.23 mm for TFJ and PFJ angles and displacements, respectively, and below 2.01 mm for ligament lengths (<4.32% ligament strain). Therefore, within these error ranges, ΔLnull and ΔLmatch can be used to estimate three-dimensional pediatric TFJ, PFJ and ligament kinematics and can be incorporated into lower-limb models to estimate joint kinematics and kinetics during dynamic tasks.

[1]  Karl J. Friston,et al.  Statistical parametric mapping , 2013 .

[2]  X Gasparutto,et al.  Multi-body optimisation with deformable ligament constraints: influence of ligament geometry , 2012, Computer methods in biomechanics and biomedical engineering.

[3]  P. Sponseller,et al.  Ligamentous Laxity of the Knee During Childhood and Adolescence , 2008, Journal of pediatric orthopedics.

[4]  M. S. Andersen,et al.  Workflow assessing the effect of gait alterations on stresses in the medial tibial cartilage - combined musculoskeletal modelling and finite element analysis , 2017, Scientific Reports.

[5]  Tung-Wu Lu,et al.  In vivo three-dimensional kinematics of the normal knee during active extension under unloaded and loaded conditions using single-plane fluoroscopy. , 2008, Medical engineering & physics.

[6]  Nicola Sancisi,et al.  A novel 3D parallel mechanism for the passive motion simulation of the patella-femur-tibia complex , 2011 .

[7]  Nicola Sancisi,et al.  Validation of a multi-body optimization with knee kinematic models including ligament constraints. , 2015, Journal of biomechanics.

[8]  Dan K Ramsey,et al.  Effect of skin movement artifact on knee kinematics during gait and cutting motions measured in vivo. , 2005, Gait & posture.

[9]  A. Leardini,et al.  Patellar tracking during total knee arthroplasty: an in vitro feasibility study , 2007, Knee Surgery, Sports Traumatology, Arthroscopy.

[10]  A. Leardini,et al.  A new anatomically based protocol for gait analysis in children. , 2007, Gait & posture.

[11]  B. Koopman,et al.  A subject-specific musculoskeletal modeling framework to predict in vivo mechanics of total knee arthroplasty. , 2015, Journal of biomechanical engineering.

[12]  Angelo Cappello,et al.  Double calibration vs. global optimisation: performance and effectiveness for clinical application. , 2006, Gait & posture.

[13]  Aurelio Cappozzo,et al.  A soft tissue artefact model driven by proximal and distal joint kinematics. , 2014, Journal of biomechanics.

[14]  M. P. Baxter Assessment of Normal Pediatric Knee Ligament Laxity Using the Genucom , 1988, Journal of pediatric orthopedics.

[15]  A Leardini,et al.  Articular surface approximation in equivalent spatial parallel mechanism models of the human knee joint: An experiment-based assessment , 2010, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[16]  A. J. van den Bogert,et al.  Effect of skin movement on the analysis of skeletal knee joint motion during running. , 1997, Journal of biomechanics.

[17]  Vincenzo Parenti-Castelli,et al.  PARALLEL MECHANISMS APPLIED TO THE HUMAN KNEE PASSIVE MOTION SIMULATION , 2000 .

[18]  A. Jawad,et al.  Objective evaluation of knee laxity in children. , 2000, Journal of pediatric orthopedics.

[19]  Raphaël Dumas,et al.  Multibody Kinematics Optimization for the Estimation of Upper and Lower Limb Human Joint Kinematics: A Systematized Methodological Review. , 2018, Journal of biomechanical engineering.

[20]  Kevin B. Shelburne,et al.  Dependence of Muscle Moment Arms on In Vivo Three-Dimensional Kinematics of the Knee , 2017, Annals of Biomedical Engineering.

[21]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  D. Carpanen,et al.  Development and validation of a computational model of the knee joint for the evaluation of surgical treatments for osteoarthritis , 2014, Computer methods in biomechanics and biomedical engineering.

[23]  J. O'Connor,et al.  Ligaments and articular contact guide passive knee flexion. , 1998, Journal of biomechanics.

[24]  J. O'Connor,et al.  A constraint-based approach to modelling the mobility of the human knee joint. , 2003, Journal of biomechanics.

[25]  Jos Vanrenterghem,et al.  Vector field statistical analysis of kinematic and force trajectories. , 2013, Journal of biomechanics.

[26]  A Leardini,et al.  Position and orientation in space of bones during movement: anatomical frame definition and determination. , 1995, Clinical biomechanics.

[27]  Carlos A. Coello Coello,et al.  Handling multiple objectives with particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[28]  Scott L. Delp,et al.  Accuracy of Muscle Moment Arms Estimated from MRI-Based Musculoskeletal Models of the Lower Extremity , 2000 .

[29]  Timothy E Hewett,et al.  Finite element model of the knee for investigation of injury mechanisms: development and validation. , 2014, Journal of biomechanical engineering.

[30]  Michael Damsgaard,et al.  Do kinematic models reduce the effects of soft tissue artefacts in skin marker-based motion analysis? An in vivo study of knee kinematics. , 2010, Journal of biomechanics.

[31]  A Shirazi-Adl,et al.  Computational biodynamics of human knee joint in gait: from muscle forces to cartilage stresses. , 2012, Journal of biomechanics.

[32]  Carolyn Anglin,et al.  In vivo patellar kinematics during total knee arthroplasty , 2008, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[33]  W Skalli,et al.  Tibio-femoral joint constraints for bone pose estimation during movement using multi-body optimization. , 2011, Gait & posture.

[34]  Nicola Sancisi,et al.  A New Kinematic Model of the Passive Motion of the Knee Inclusive of the Patella , 2011 .

[35]  Jos Vanrenterghem,et al.  Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis. , 2015, Journal of biomechanics.

[36]  Yasin Y Dhaher,et al.  The effect of connective tissue material uncertainties on knee joint mechanics under isolated loading conditions. , 2010, Journal of biomechanics.

[37]  L Blankevoort,et al.  Recruitment of knee joint ligaments. , 1991, Journal of biomechanical engineering.

[38]  Nicola Sancisi,et al.  Feasibility of using MRIs to create subject-specific parallel-mechanism joint models. , 2017, Journal of biomechanics.

[39]  Laurence Chèze,et al.  A 3D lower limb musculoskeletal model for simultaneous estimation of musculo-tendon, joint contact, ligament and bone forces during gait. , 2014, Journal of biomechanics.

[40]  X. Gasparutto,et al.  A multi-body optimization framework with a knee kinematic model including articular contacts and ligaments , 2017 .

[41]  A Leardini,et al.  Geometrical changes of knee ligaments and patellar tendon during passive flexion. , 2012, Journal of biomechanics.

[42]  John J. O'Connor,et al.  A three-dimensional geometric model of the knee for the study of joint forces in gait , 1997 .

[43]  B. Forster,et al.  Patellofemoral and tibiofemoral alignment in a fully weight‐bearing upright MR: Implementation and repeatability , 2018, Journal of magnetic resonance imaging : JMRI.

[44]  Nicola Hagemeister,et al.  Soft tissue artifact compensation in knee kinematics by multi-body optimization: Performance of subject-specific knee joint models. , 2015, Journal of biomechanics.