4.7 Article

Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling

Journal

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fbioe.2021.803725

Keywords

foot orthosis; computational modeling; FEA; tissue strain; deep tissue injury; foot

Funding

  1. University of Southampton's EPSRC Doctoral Training Program [EP/R513325/1]
  2. EPSRC-NIHR Medical Device and Vulnerable Skin Network [EP/N02723X/1]
  3. Pfizer Inc., The epidemiology of MRI-detected rheumatoid arthritis disease activity within the forefoot

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This study compared biomechanical predictions between individuals with different severity of rheumatoid arthritis and a healthy control, finding differences at the orthotic interface. Factors such as BMI and bony morphology were assessed to better understand the impact of foot orthoses.
Foot orthoses are prescribed to reduce forefoot plantar pressures and pain in people with rheumatoid arthritis. Computational modelling can assess how the orthoses affect internal tissue stresses, but previous studies have focused on a single healthy individual. This study aimed to ascertain whether simplified forefoot models would produce differing biomechanical predictions at the orthotic interface between people with rheumatoid arthritis of varying severity, and in comparison to a healthy control. The forefoot models were developed from magnetic resonance data of 13 participants with rheumatoid arthritis and one healthy individual. Measurements of bony morphology and soft tissue thickness were taken to assess deformity. These were compared to model predictions (99th% shear strain and plantar pressure, max. pressure gradient, volume of soft tissue over 10% shear strain), alongside clinical data including body mass index and Leeds Foot Impact Scale-Impairment/Footwear score (LFIS-IF). The predicted pressure and shear strain for the healthy participant fell at the lower end of the rheumatoid models' range. Medial first metatarsal head curvature moderately correlated to all model predicted outcomes (0.529 < r < 0.574, 0.040 < p < 0.063). BMI strongly correlated to all model predictions except pressure gradients (0.600 < r < 0.652, p < 0.05). There were no apparent relationships between model predictions and instances of bursae, erosion and synovial hypertrophy or LFIS-IF score. The forefoot models produced differing biomechanical predictions between a healthy individual and participants with rheumatoid arthritis, and between individuals with rheumatoid arthritis. Models capable of predicting subject specific biomechanical orthotic interactions could be used in the future to inform more personalised devices to protect skin and soft tissue health. While the model results did not clearly correlate with all clinical measures, there was a wide range in model predictions and morphological measures across the participants. Thus, the need for assessment of foot orthoses across a population, rather than for one individual, is clear.

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