ArticleFrontiers in bioengineering and biotechnology2022
Probabilistic planning for ligament-balanced TKA-Identification of critical ligament properties.
Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Ultrasound can assess soft tissue laxity in osteoarthritic knees and after total knee arthroplasty.Journal of experimental orthopaedics · 2025Article
- Instantaneous Generation of Subject-Specific Finite Element Models of the Hip Capsule.Bioengineering (Basel, Switzerland) · 2023Article
- Pre-Planning the Surgical Target for Optimal Implant Positioning in Robotic-Assisted Total Knee Arthroplasty.Bioengineering (Basel, Switzerland) · 2023Article
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Total knee arthroplasty (TKA) failures are often attributed to unbalanced knee ligament loading. The current study aims to develop a probabilistic planning process to optimize implant component positioning that achieves a ligament-balanced TKA. This planning process accounts for both subject-specific uncertainty, in terms of ligament material properties and attachment sites, and surgical precision related to the TKA process typically used in clinical practice. The consequent uncertainty in the implant position parameters is quantified by means of a surrogate model in combination with a Monte Carlo simulation. The samples for the Monte Carlo simulation are generated through Bayesian parameter estimation on the native knee model in such a way that each sample is physiologically relevant. In this way, a subject-specific uncertainty is accounted for. A sensitivity analysis, using the delta-moment-independent sensitivity measure, is performed to identify the most critical ligament parameters. The designed process is capable of estimating the precision with which the targeted ligament-balanced TKA can be realized and converting this into a success probability. This study shows that without additional subject-specific information (e.g., knee kinematic measurements), a global success probability of only 12% is estimated. Furthermore, accurate measurement of reference strains and attachment sites critically improves the success probability of the pre-operative planning process. To allow more precise planning, more accurate identification of these ligament properties is required. This study underlines the relevance of investigating
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