D-FOOTPRINT · Personalised insoles via additive manufacture for the prevention of plantar ulceration in diabetes

Personalised insoles via additive manufacture for the prevention of plantar ulceration in diabetes

Foot ulceration in patients with diabetes remains a highly prevalent, debilitating and expensive to treat problem. Recent recommendations by the International Working Group on the Diabetic Foot have suggested that therapeutic footwear including a custom insole should be the preferred intervention for those individuals who have been identified as “at risk” of developing a foot ulcer. However, current methods for the design and fabrication of custom insoles limit the potential to incorporate innovations that could increase the effectiveness of these devices, primarily due to the geometric restrictions inherent to the methods. The 24 month Marie Curie International Outgoing Fellowship project D-FOOTPRINT aimed to develop, evaluate and disseminate a novel prescription paradigm, focused on additive manufacturing (AM) and biomechanical modelling enabled design optimisation, for insoles aimed at preventing or treating plantar surface ulceration in the diabetic foot. From October 2013 to October 2014 I worked in the Computational, Robotics and Experiment Biomechanics laboratory at the University of Washington, Seattle. During this time I combined computer aided design, finite element modelling and additive manufacturing techniques to produce innovative personalised insoles optimised for forefoot pressure offloading, specifically targeted at patients with diabetic foot disease. These devices were prototyped using standard and additive manufacture techniques and I developed a highly novel integrated workflow that semi-automates their design and optimisation. In addition, I carried out a systematic review of work in this area, identifying previous research and evaluating techniques that could be implemented within the insole design workflow (Telfer et al., 2014a). I built on previous work from the laboratory to investigate how personalised but geometrically simplified computer simulations could be used to provide relevant information to inform insole design within clinically feasible time frames. These simulations were built using data acquired from easily accessible equipment, i.e. plantar pressure measurements, 3D surface scanning and ultrasound. A range of computation model designs were comprehensively investigated and I identified the key features that were required to produce comparable results to more geometrically complex simulations, and quantified differences in build and simulation run times for the models (Telfer et al., 2014b: Telfer et al., 2015). From October 2014 to October 2015 I worked in the Musculoskeletal Health research group at Glasgow Caledonian University, UK. During this time I successfully developed and carried out a clinical trial using a randomised crossover design to test the biomechanical effects of the novel insoles produced during the project against current devices in at-risk patients with diabetic foot disease. In developing the protocol a novel approach to measuring plantar tissue properties, incorporating in-shoe embedded ultrasonography was tested and its reliability assessed. In addition, I developed custom software to standardise and improve the reproducibility of the analysis of plantar pressure data collected from different systems. This will be made freely available for use by other research and clinical groups. In the clinical trial I tested the insoles in a group of 20 people with diabetes and peripheral neuropathy. Areas on the sole of the foot identified as having elevated pressures were targeted and pressure reductions in these areas were used as the primary outcome measure for this study. Results from the trial showed that the novel, virtually optimised insoles provided statistically significant pressure reductions at areas of elevated forefoot pressure that were 20-30% greater than that those seen when the participants wore the insoles designed and manufactured using standard methods. The health and economic burden of diabetic foot disease is poorly acknowledged in terms of the attention it receives. These results however, demonstrate that the use of virtual optimisation and additive manufacture can have a positive effect on one of the key mechanisms that leads to plantar ulceration in this patient group. Further work is required to fully explore the potential of this approach and to allow direct clinical implementation, however I expect that this approach will be relevant in other patient populations beyond those explored in this project (Telfer et al., 2014c). As part of the D-FOOTPRINT project a number of workshops have been given to clinically relevant groups to promote this approach, as well as presentations at academic conferences and public outreach events. References Spirka TA, Erdemir A, Ewers Spaulding S, Yamane A, Telfer S, Cavanagh PR. Simple finite element models for use in the design of therapeutic footwear. J Biomech. 2014b;47:2948–55. Telfer S, Erdemir A, Woodburn J, Cavanagh PR. What Has Finite Element Analysis Taught Us about Diabetic Foot Disease and Its Management? A Systematic Review. PLoS One. 2014a;9(10):e109994. Telfer S, Baeten E, Gibson KS, Steultjens MP, Turner DE, Woodburn J, et al. Dynamic plantar loading index detects altered foot function in individuals with rheumatoid arthritis but not changes due to orthotic use. Clin Biomech (Bristol, Avon). 2014c;29:1027–31. Telfer S, Erdemir A, Woodburn J, Cavanagh PR. Simplified vs geometrically accurate models of forefoot geometry to predict plantar pressures: a finite element study. J Biomech. 2015 Accepted Contact Dr Scott Telfer Institute for Applied Health Research Glasgow Caledonian University Glasgow, G4 0BA United Kingdom Phone: +44(0)141 331 8475 Email: scott.telfer@gcu.ac.uk

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