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

Ali, Azhar A.; Clary, Chadd W.; Smoger, Lowell M.; Dennis, Douglas A.; Fitzpatrick, Clare K.; Rullkoetter, Paul J.; Laz, Peter J.

doi:10.1007/s10237-020-01295-7

Cited by 7 publications

(9 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Orthopedic surgeons attempt to optimize the dynamic behavior of the knee joint by a correct intraoperative alignment of the patellar component. Interindividual morphological joint variation [23][24][25][26] is known to influence knee joint dynamics [27] and functionality of TKRs [26,28]. Furthermore, the difference in patellar component designs and the size of the patellar component are factors that influence the PF dynamics [28,37,38].…”

Section: Discussionmentioning

confidence: 99%

“…Despite improvements in surgical instruments and techniques, many of the causes of revisions and patient dissatisfaction are directly related to implant component malalignment [6,18,21,22]. The morphology of the knee joint differs between both genders and different ethnicities [23][24][25][26]. These differences cannot only affect the implant component size selection but also the trochlear groove geometry, as well as the positioning of the patellar component between patients.…”

Section: Introductionmentioning

confidence: 99%

“…These differences cannot only affect the implant component size selection but also the trochlear groove geometry, as well as the positioning of the patellar component between patients. Likewise, interindividual morphological joint variation is known to influence knee joint dynamics [27] and functionality of TKRs [26,28]. In this regard, Chen et al [29] showed that the internal rotation of the femoral component and the varus malpositioning of the tibial component led to unfavorable postoperative loading conditions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Musculoskeletal Multibody Simulation Analysis on the Impact of Patellar Component Design and Positioning on Joint Dynamics after Unconstrained Total Knee Arthroplasty

Kebbach

Darowski

Krueger³

et al. 2020

Materials

View full text Add to dashboard Cite

Patellofemoral (PF) disorders are considered a major clinical complication after total knee replacement (TKR). Malpositioning and design of the patellar component impacts knee joint dynamics, implant fixation and wear propagation. However, only a limited number of studies have addressed the biomechanical impact of the patellar component on PF dynamics and their results have been discussed controversially. To address these issues, we implemented a musculoskeletal multibody simulation (MMBS) study for the systematical analysis of the patellar component’s thickness and positioning on PF contact forces and kinematics during dynamic squat motion with virtually implanted unconstrained cruciate-retaining (CR)-TKR. The patellar button thickness clearly increased the contact forces in the PF joint (up to 27%). Similarly, the PF contact forces were affected by superior–inferior positioning (up to 16%) and mediolateral positioning (up to 8%) of the patellar button. PF kinematics was mostly affected by the mediolateral positioning and the thickness of the patellar component. A medialization of 3 mm caused a lateral patellar shift by up to 2.7 mm and lateral patellar tilt by up to 1.6°. However, deviations in the rotational positioning of the patellar button had minor effects on PF dynamics. Aiming at an optimal intraoperative patellar component alignment, the orthopedic surgeon should pay close attention to the patellar component thickness in combination with its mediolateral and superior–inferior positioning on the retropatellar surface. Our generated MMBS model provides systematic and reproducible insight into the effects of patellar component positioning and design on PF dynamics and has the potential to serve as a preoperative analysis tool.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Musculoskeletal Multibody Simulation Analysis on the Impact of Patellar Component Design and Positioning on Joint Dynamics after Unconstrained Total Knee Arthroplasty

Kebbach

Darowski

Krueger³

et al. 2020

Materials

View full text Add to dashboard Cite

show abstract

“…• Computational efficient method for assessing the influence of surgical variability on primary stability of a contemporary femoral stem in a cohort of subjects (Al-Dirini et al 2019) • Impact of alignment and kinematic variation on resistive movement and dislocation propensity for THA with lipped and neutral liners (Huff et al 2020) • Computational framework for population -based evaluation of TKR -implanted patellofemoral joint mechanics (Ali et al 2020) Design and Assessment of Patient-Specific Interventions:…”

Section: ) • Rapid Muscle Volume Prediction Using Anthropometricmentioning

confidence: 99%

“…Surgical variation in acetabular cup position was incorporated by adjusting inclination and anteversion angles, and the model produced evidence of surgical options which might enhance dislocation resistance. Finally, a third paper (Ali et al 2020) presents a pipeline to support the robust design of new implant systems. The computational efficiency of population analyses is particularly important in early design cycle evaluation, where many concepts are considered.…”

Section: Editorialmentioning

confidence: 99%

Population based approaches to computational musculoskeletal modelling

Fernandez

Dickinson

Hunter

2020

Biomech Model Mechanobiol

View full text Add to dashboard Cite

In Silico Clinical Trials in the Orthopedic Device Industry: From Fantasy to Reality?

et al. 2021

View full text Add to dashboard Cite

The orthopedic device industry relies heavily on clinical evaluation to confirm the safety, performance, and clinical benefits of its implants. Limited sample size often prevents these studies from capturing the full spectrum of patient variability and real-life implant use. The device industry is accustomed to simulating benchtop tests with numerical methods and recent developments now enable virtual “in silico clinical trials” (ISCT). In this article, we describe how the advancement of computer modeling has naturally led to ISCT; outline the potential benefits of ISCT to patients, healthcare systems, manufacturers, and regulators; and identify how hurdles associated with ISCT may be overcome. In particular, we highlight a process for defining the relevant patient risks to address with ISCT, the utility of a versatile software pipeline, the necessity to ensure model credibility, and the goal of limiting regulatory uncertainty. By complementing—not replacing—traditional clinical trials with computational evidence, ISCT provides a viable technical and regulatory strategy for characterizing the full spectrum of patients, clinical conditions, and configurations that are embodied in contemporary orthopedic implant systems.

show abstract

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

Cited by 7 publications

References 37 publications

Musculoskeletal Multibody Simulation Analysis on the Impact of Patellar Component Design and Positioning on Joint Dynamics after Unconstrained Total Knee Arthroplasty

Musculoskeletal Multibody Simulation Analysis on the Impact of Patellar Component Design and Positioning on Joint Dynamics after Unconstrained Total Knee Arthroplasty

Population based approaches to computational musculoskeletal modelling

In Silico Clinical Trials in the Orthopedic Device Industry: From Fantasy to Reality?

Contact Info

Product

Resources

About