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. 2020 Jan 8;15(1):e0227272.
doi: 10.1371/journal.pone.0227272. eCollection 2020.

Evaluation and Validation of 2D Biomechanical Models of the Knee for Radiograph-Based Preoperative Planning in Total Knee Arthroplasty

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Free PMC article

Evaluation and Validation of 2D Biomechanical Models of the Knee for Radiograph-Based Preoperative Planning in Total Knee Arthroplasty

Malte Asseln et al. PLoS One. .
Free PMC article

Abstract

Thorough preoperative planning in total knee arthroplasty is essential to reduce implant failure by proper implant sizing and alignment. The "gold standard" in conventional preoperative planning is based on anterior-posterior long-leg radiographs. However, the coronal component alignment is still an open discussion in literature, since studies have reported contradictory outcomes on survivorship, indicating that optimal individual alignment goals still need to be defined. Two-dimensional biomechanical models of the knee have the potential to predict joint forces and, therefore, objectify therapy planning. Previously published two-dimensional biomechanical models were evaluated and validated for the first time in this study by comparison of model predictions to corresponding in vivo measurements obtained from telemetric implants for a one- and two-leg stance. Model input parameters were acquired from weight-bearing anterior-posterior long-leg radiographs and statistical assumptions for patient-specific model adaptation. The overall time from initialization to load prediction was in the range of 7-8 minutes per patient for all models. However, no model could accurately predict the correct trend of knee joint forces over patients. Two dimensional biomechanical models of the knee have the potential to improve preoperative planning in total knee arthroplasty by providing additional individual biomechanical information to the surgeon. Although integration into the clinical workflow might be performed with acceptable costs, the models' accuracy is insufficient for the moment. Future work is needed for model optimization and more sophisticated modelling approaches.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1
(A) Maquet’s model. (B) Kettelkamp’s model. Minns’ model (modified) [25] in frontal view (C) and sagittal view (D). Joint forces (blue), external and body forces (red), soft-tissue and muscular forces (green). Abbreviations of the forces: (A) L = lateral muscular force; R = knee joint force; P = partial body weight; (B) P = lateral ligament force; Q = medial ligament force; F1 = lateral knee joint force; F2 = medial knee joint force; W = gravity force of the leg; R = ground reaction force; (C) PLL = lateral ligament force; PLM = medial ligament force; PFTL = lateral knee joint force; PFTM = medial knee joint force; PT = patellar ligament force; R = ground reaction force; (D) PT = patellar ligament force; PFT = knee joint force; PHAM = hamstring force; R = ground reaction force.
Fig 2
Fig 2. Parameter acquisition for patient-specific model adaptation (exemplary).
(A) Long-leg radiograph, (B) knee region, (C) hip region, and (D) ankle region. The nomenclature is presented in Table 3.
Fig 3
Fig 3. Rule-based protocol for the modelling process.
At least three test cycles were performed to reduce learning curve effects.
Fig 4
Fig 4. Exemplarily calculation of the average in vivo force in a one-leg stance.
Fig 5
Fig 5. Resultant knee joint forces calculated for nine patients, based on the mathematical models of Kettelkamp and Minns with corresponding average in vivo force measurements for a two-leg stance.
The error indicators demonstrate the minimum/maximum values. Forces in %BW.
Fig 6
Fig 6. Correlation and regression analysis between tibiofemoral angle and medial force ratio during static two-leg stance based on the models of Kettelkamp and Minns.
Fig 7
Fig 7. Calculated resultant knee joint forces based on the models of Maquet, Kettelkamp and Minns with corresponding in vivo forces for a one-leg stance.
The error indicators demonstrate the minimum/maximum values. Forces in %BW.

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Publication types

Grant support

This work was supported by Deutsche Forschungsgemeinschaft (Be 804/18, TR 1657/1-1) (http://www.dfg.de/en/index.jsp), Deutsche Arthrose-Hilfe e.V. (http://www.arthrose.de/), Federal Ministry of Education and Research (BMBF: OVERLOAD-PrevOP, 01EC1408A) and the OrthoLoadClub (https://orthoload.com/orthoload-club/).
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