Predictive prosthetic socket design: part 1—population-based evaluation of transtibial prosthetic sockets by FEA-driven surrogate modelling

Abstract

It has been proposed that finite element analysis can complement clinical decision making for the appropriate design and manufacture of prosthetic sockets for amputees. However, clinical translation has not been achieved, in part due to lengthy solver times and the complexity involved in model development. In this study, a parametric model was created, informed by variation in (i) population-driven residuum shape morphology, (ii) soft tissue compliance and (iii) prosthetic socket design. A Kriging surrogate model was fitted to the response of the analyses across the design space enabling prediction for new residual limb morphologies and socket designs. It was predicted that morphological variability and prosthetic socket design had a substantial effect on socket-limb interfacial pressure and shear conditions as well as sub-dermal soft tissue strains. These relationships were investigated with a higher resolution of anatomical, surgical and design variability than previously reported, with a reduction in computational expense of six orders of magnitude. This enabled real-time predictions (1.6 ms) with error vs the analytical solutions of < 4 kPa in pressure at residuum tip, and < 3% in soft tissue strain. As such, this framework represents a substantial step towards implementation of finite element analysis in the prosthetics clinic.

Developing an Analogue Residual Limb for Comparative DVC Analysis of Transtibial Prosthetic Socket Designs

“…In the subsequent case study evaluation, the majority of the residual limb's region of interest experienced estimated strain up to 10% for both axial and shear strains, which corresponded to the strain range for which the analogue material's stiffness was designed. This is corroborated by finite element analyses, which give typical mean strain estimates of 3-15% for both principal tension, compression, and maximal shear, and strain peaks of 30-75% [15,17,38]. The estimated strain distribution lies below estimated thresholds for skeletal muscle damage from engineered tissue and rat models [39,40].…”

“…Researchers have presented tools to assess the mechanical conditions at the skin-socket interface using sensors [11,12] and the use of finite element (FE) analysis to predict these conditions to inform socket design was first proposed in the 1980s [13,14]. Recent work has established highly computationally efficient implementations, with a view to facilitate translation into the clinic [15]. Previously, it has only been possible to validate an FE model's surface stress predictions [16], but it is recognised that soft tissue injury is a product of tissue shear strains in the superficial and in deeper tissues, particularly around bony prominences [17].…”

Is a simplified Finite Element model of the gluteus region able to capture the mechanical response of the internal soft tissues under compression?

“…However, to our knowledge and to date, no correlation has been done between shear moduli obtained by Shear Wave Elastography and mechanical properties from classic ex vivo mechanical testing methods. The development of surrogate models that allow equivalent predictions to single FEA solutions, across a broad population with sufficiently reduced computational expense for clinical use (Steer et al, 2019) is a promising alternative that will be explored in future work. Third, the strain damage thresholds (above 75% and above 45%) reported in the literature for tissue injury (motivated by the work of (Ceelen et al, 2008;Loerakker et al, 2011) come from animal models and should be considered with some caution since they might not be relevant for humans.…”

Key considerations for finite element modelling of the residuum-prosthetic socket interface

“…High-quality input data from experimental studies, in addition to good practice in model development, is necessary for reliable FE modelling. Many studies have already sought to characterise patient anatomy [34], gait analysis [35], soft tissue material models [13] and interface properties [24]. More recently, a framework has been presented to incorporate this population variability, to enhance this evidence base whilst maintaining low requirements of computational resources, FE training and experience [34].…”

“…Many studies have already sought to characterise patient anatomy [34], gait analysis [35], soft tissue material models [13] and interface properties [24]. More recently, a framework has been presented to incorporate this population variability, to enhance this evidence base whilst maintaining low requirements of computational resources, FE training and experience [34]. Such methods have applications for lower limb prosthetics to move away from single-case research studies, and move towards clinical application enabling prosthetists to access rapid, comparative predictions of a wide range of socket designs.…”