Finite Element Analysis for Pre-Clinical Testing of Custom-Made Knee Implants for Complex Reconstruction Surgery

Transfer of patients' tibiofemoral kinematics and loads to a six-degree-of-freedom (6-DOF) joint simulator under consideration of virtual ligaments

Preclinical testing of total knee replacements (TKR) is crucial for evaluating new implant designs. Dynamic experimental testing focus mostly on level walking and squats, failing to represent a full range of daily activities. Moreover, the contribution of the ligament apparatus is often simplified. Therefore, this study transferred five daily activity load cases-level walking, downhill walking, stair descent, squat, and sit-to-stand-onto a six-degree-of-freedom (6-DOF) joint simulator with a cruciate-retaining bicondylar TKR and a virtual ligament apparatus. Forces and kinematics were based on telemetric data from an ultra-congruent TKR. The resulting kinematics, kinetics, and tibiofemoral contact surfaces were evaluated. Additionally, variations of the virtual ligament apparatus on the joint simulator, e.g. resection of the posterior cruciate ligament (PCL), have been used to assess its influence on the resulting joint dynamics. Results showed that tibiofemoral contact area was more influenced by dynamics than kinematics. Virtual PCL resection shifted the tibia posteriorly (up to 3 mm) and increased abduction (up to 0.5°). Different results were seen across all load cases. The exceptions are the squat and sit-to-stand load cases with similar patterns. Thus, cruciate-retaining TKR can be tested using telemetric data from ultra-congruent TKR, aiding in comprehensive evaluations.

Finite element analysis and its application in Orthopaedics: A narrative review

Orthopedic surgery and traumatology necessitate cost-effective approaches that can be replicated across multiple venues. Finite Element (FE) simulation models have evolved as a solution, allowing for consistent investigations into biomechanical systems. Finite Element Analysis (FEA), which began in the 1950s aviation industry, has since expanded into orthopedics. Its progress, fueled by improved computing, has a significant impact on orthopedic surgery, helping to understand biomechanics and post-implantation responses. The use of FEA has increased in recent decades, demonstrating its critical importance in modern orthopedic research. Methodologies for FEA include both generic and patient-specific approaches, each customized to individual needs. FEA goes through three stages: preprocessing, solution, and postprocessing, all of which require exact material property assignment and boundary conditions. Pathophysiology, orthopedic biomechanics, implant design, fracture fixation, bracing, and preoperative planning are all applications of FEA, which has revolutionized surgical methods. However, FEA has drawbacks such as oversimplification, processing needs, and validation issues. Future FEA advances aim to improve model accuracy, add active muscle simulation, and standardize procedures, resulting in significant advancements in orthopedic research and treatment planning.

Developing and Validating a Model of Humeral Stem Primary Stability, Intended for In Silico Clinical Trials

In silico clinical trials (ISCT) can contribute to demonstrating a device's performance via credible computational models applied on virtual cohorts. Our purpose was to establish the credibility of a model for assessing the risk of humeral stem loosening in total shoulder arthroplasty, based on a twofold validation scheme involving both benchtop and clinical validation activities, for ISCT applications. A finite element model computing bone-implant micromotion (benchtop model) was quantitatively compared to a bone foam micromotion test (benchtop comparator) to ensure that the physics of the system was captured correctly. The model was expanded to a population-based approach (clinical model) and qualitatively evaluated based on its ability to replicate findings from a published clinical study (clinical comparator), namely that grit-blasted stems are at a significantly higher risk of loosening than porous-coated stems, to ensure that clinical performance of the stem can be predicted appropriately. Model form sensitivities pertaining to surgical variation and implant design were evaluated. The model replicated benchtop micromotion measurements (52.1 ± 4.3 µm), without a significant impact of the press-fit ("Press-fit": 54.0 ± 8.5 µm, "No press-fit": 56.0 ± 12.0 µm). Applied to a virtual population, the grit-blasted stems (227 ± 78µm) experienced significantly larger micromotions than porous-coated stems (162 ± 69µm), in accordance with the findings of the clinical comparator. This work provides a concrete example for evaluating the credibility of an ISCT study. By validating the modeling approach against both benchtop and clinical data, model credibility is established for an ISCT application aiming to enrich clinical data in a regulatory submission.