Validating subject-specific knee models from in vivo measurements.

Area of Science:

• Orthopaedics and Biomechanics
• Computational Modeling
• Medical Device Development

Background:

• Computational models in orthopaedics are sensitive to modeling decisions, yet input data influence is often overlooked.
• Accurate calibration of knee models requires in vivo (in a living organism) data, which is challenging to obtain non-invasively.
• Personalized modeling and digital twins necessitate validated subject-specific computational models.

Purpose of the Study:

• To demonstrate that subject-specific computational knee models calibrated with in vivo measurements achieve accuracy comparable to those calibrated with in vitro (in a controlled environment) measurements.
• To support the development of subject-specific computational models for the living knee.

Main Methods:

• Two cadaveric knee specimens were imaged using CT and surface scans.
• Knee laxity measurements were performed using a custom in vivo knee laxity apparatus (KLA) and a robotic knee simulator (RKS).
• Computational models were calibrated using laxity data from either the KLA or the RKS, and their performance was compared through simulated activities.

Main Results:

• Models calibrated with in vivo KLA data showed comparable performance to models calibrated with in vitro RKS data.
• Predicted differences in anterior-posterior laxity were less than 2.5 mm, and pivot shift simulations differed by less than 2.6°.
• Differences in predicted ligament loads and calibrated material properties were observed, indicating a need to incorporate ligament load in calibration.

Conclusions:

• Current in vivo knee laxity measurement methods are sufficient for calibrating computational models with accuracy comparable to in vitro techniques.
• The described workflows may form a basis for subject-specific modeling of the living knee.
• Publicly available data and tools support further research in this area.