A review of probabilistic analysis in orthopaedic biomechanics

Abstract

Probabilistic analysis methods are being increasingly applied in the orthopaedics and biomechanics literature to account for uncertainty and variability in subject geometries, properties of various structures, kinematics and joint loading, as well as uncertainty in implant alignment. As a complement to experiments, finite element modelling, and statistical analysis, probabilistic analysis provides a method of characterizing the potential impact of variability in parameters on performance. This paper presents an overview of probabilistic analysis and a review of biomechanics literature utilizing probabilistic methods in structural reliability, kinematics, joint mechanics, musculoskeletal modelling, and patient-specific representations. The aim of this review paper is to demonstrate the wide range of applications of probabilistic methods and to aid researchers and clinicians in better understanding probabilistic analyses.

The Influence of Component Alignment and Ligament Properties on Tibiofemoral Contact Forces in Total Knee Replacement

“…Finally, our sensitivity metrics from the Monte Carlo analysis are first-order correlation coefficients, which inherently do not account for nonlinearities or characterize interactions between the ligaments. The number of simulations can easily be scaled up using high throughput computing platforms, allowing for more advanced sensitivity analyses [78,86] that consider parametric interactions.…”

Is My Model Good Enough? Best Practices for Verification and Validation of Musculoskeletal Models and Simulations of Movement

“…Several approaches to sensitivity analysis are available, from simple to complex [19]. The direct approach is a differential analysis, which determines the analytic relationship between inputs and outputs [20].…”

Multiscale cartilage biomechanics: technical challenges in realizing a high-throughput modelling and simulation workflow

“…A high-throughput modelling and simulation framework seeks to provide the ability to represent such variations and conduct individualized analysis to assess this multiscale mechanical system under various loading conditions, which can be used for understanding trauma risk, for evaluating the protective performance of interventions, and for diagnosis and prognosis through the use of biomechanical markers. Likewise, parametric analysis supported by large-scale unsupervised simulations can allow probabilistic studies (for population analysis or for uncertainty estimation) [20], inverse analysis (for estimation of patient-specific mechanical properties) [21] and virtual prototyping (to design new therapeutic, surgical or rehabilitative management strategies) [22]. While the use of modelling and simulation for explorations of cartilage and chondrocyte mechanics is appealing, routine investigations are hampered by many technical challenges associated with the need to accommodate the nonlinear, multiscale and multiphasic biomechanical nature of this tissue [1].…”

“…These analyses can be conducted in conjunction to evaluate the changes in multiscale load sharing path as model parameters at all scales are perturbed simultaneously (third use case). All these use cases can lead into probabilistic analysis [20], i.e. for assessment of population variations, sensitivity studies and uncertainty quantification.…”