ESMAC best paper 2016A methodological framework for detecting ulcers’ risk in diabetic foot subjects by combining gait analysis, a new musculoskeletal foot model and a foot finite element model
Introduction
A sensorimotor polyneuropathy is a long-term diabetic complication. The main consequences are plantar ulcers and lower limb amputations which is a major cause of morbidity and mortality [1]. The prevalence of diabetic sensorimotor polyneuropathy in diabetic patients is 25% after 10 years of disease, and it is often associated with peripheral artery disease. Diabetic foot ulcers are commonly due to repetitive stress over an area that is subject to high vertical or shear stress in patients with peripheral neuropathy and peripheral artery disease. Several preventive approaches have been proposed [1] including clinical and biomechanical interventions [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13]. Biomechanical analysis has been carried out using experimental and computational methods, via Finite Element models (FEMs) or Musculoskeletal models (MSMs). Despite the advances in prevention methodologies, there is an increasing number of diabetic foot subjects and lower extremity amputations [1].
Experimental studies report that diabetic neuropathy significantly reduces walking ability and causes alterations of foot posture and function [2], [3], [4], [5], [6], [7], [8]. Limited foot flexibility and a restrained forward progression of body weight during the stance phase of gait were observed [2], [3], [4]. As a consequence, balance is impaired and the risk of falls increased [2], [5], [8]. An inadequate foot rollover associated with a smaller ankle range of motion modifies the plantar pressure (PP) distribution inducing higher PP concentration and a higher risk for ulcer formation at specific foot areas [2], [3], [5], [6]. Diabetes also accelerates age-related decreases in muscle mass [4] contributing to electromyographic abnormalities in the lower limb muscles [6], [7]. Recently, strengthening, stretching and functional training programmes are being combined with the use of insoles to reduce the stress of the plantar tissue [5].
Current literature shows that ulceration seems to be caused by repetitive and/or excessive mechanical loading on the surface of the insensitive skin, which leads to tissue damage. Clinical studies have indicated that prediction of ulcer risk level can be substantially improved when static and dynamic PP measurements are performed [2], [3], [4], [5], [8]. However, it should be mentioned that while experimental techniques can only assess loading at the foot–ground interface, reliable numerical models can provide insight on internal stresses and strains tolerated by the plantar and even deeper foot tissue [9], [10], [11], [12], [13], [14]. Different foot FEMs have been developed that account for critical aspects of the diabetic foot [9], [10], [11], [12], [13], [14]. The model developed by Gefen et al. (2003) [11] revealed significant tension stress concentrations, known as von Mises stresses, in the plantar pad of the simulated diabetic forefoot, as high as four times the normal maximum stress under the first metatarsal head and almost eight times under the second metatarsal head. The increased internal stresses at the plantar soft tissue suggest that injury onset in diabetic feet is in the deeper tissue layers rather than on the plantar foot surface. Thus, there is a need for further investigation of the aetiopathogenesis of diabetic foot through FEM.
Furthermore, while PP can be directly measured through PP sensors, there is not an experimental gold standard available for internal stress measurements. Therefore the comparison between FEM derived PP, and experimentally measured PP, is used as the standard validation method [13].
The majority of foot FEMs rely on the use of a simplified or partial foot shape, linear material properties and non subject-specific boundary conditions. When limiting these assumptions by using a subject specific 3D FEM combined with subject specific gait analysis data [13], the authors validated their model through direct comparison with the experimentally measured peak PP acquired during gait on the same subject, reaching an error of 18% and 36% respectively in the healthy and diabetic subjects’ simulated PP.
The use of MSMs has proliferated in the biomechanics community thanks to its ability to evaluate muscle and joint contact forces during gait [15], [16], [17], [18]. However, we are unaware of FEM studies evaluating the influence of muscle forces on the PP distribution during gait. Given the recent focus on muscle retraining exercises as part of rehabilitation programmes [5], such insights may be invaluable in defining targeted training programmes in neuropathic subjects.
The aim of this study was to develop a methodology for improving the prediction of internal stresses and strain on the foot through a 3D FEM based on subject specific gait analysis data combined with MSM derived intrinsic and extrinsic foot muscle forces. The feasibility of the pipeline was verified using the integrated motion capture data of one healthy subject. The model was validated through direct comparison between the simulated PP distribution and the coinciding experimentally measured ones. Finally, the role of the foot muscles on the internal stress distribution was evaluated by comparing estimates of foot models with different levels of complexity and muscle detail.
Section snippets
Methods
The framework follows three consecutive steps (Fig. 1): 1) Integrated 3D motion capture. 2) Calculation of muscle forces using MSMs and 3) Calculation of PP and stresses in soft tissues and bones using FEMs.
Subject specific data from one healthy subject (female, age 31 years, BMI 20.1 kg/m2) was used through the whole modelling procedure. The subject gave written informed consent. The protocol was approved by the local Ethic Committee of the University Clinic of Padova [13].
Results
Results of peak PP and Von Mises were reported in Fig. 4, Fig. 5 for the four different boundary conditions. In order to verify the accuracy of each simulated condition, the experimentally measured PP was compared with the simulated one (Fig. 4).
The highest experimental PP was revealed at LR on the hindfoot (504.4KPa), and SM1 and SM3 provided the best estimate with an error of 5.3% and 10.8% respectively.
At IC, the peak PP measured at the hindfoot (204.8KPa) was well approximated by all
Discussion
The goal of the present study was to develop a methodology to improve the prediction of internal stresses and strain on the foot for future diabetic foot prevention purposes whilst investigating the effect of different modelling techniques on internal stress estimation. The validity of the application of the different model parameters related to foot model complexity as well as the inclusion of intrinsic muscle forces was assessed through direct comparison between simulated and experimentally
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These authors have contributed equally to this work.