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Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733946/ https://www.ncbi.nlm.nih.gov/pubmed/35004656 http://dx.doi.org/10.3389/fbioe.2021.803725 |
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author | Kelly, Emily S. Worsley, Peter R. Bowen, Catherine J. Cherry, Lindsey S. Keenan, Bethany E. Edwards, Christopher J. O’Brien, Neil King, Leonard Dickinson, Alex S. |
author_facet | Kelly, Emily S. Worsley, Peter R. Bowen, Catherine J. Cherry, Lindsey S. Keenan, Bethany E. Edwards, Christopher J. O’Brien, Neil King, Leonard Dickinson, Alex S. |
author_sort | Kelly, Emily S. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8733946 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87339462022-01-07 Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling Kelly, Emily S. Worsley, Peter R. Bowen, Catherine J. Cherry, Lindsey S. Keenan, Bethany E. Edwards, Christopher J. O’Brien, Neil King, Leonard Dickinson, Alex S. Front Bioeng Biotechnol Bioengineering and Biotechnology 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. Frontiers Media S.A. 2021-12-23 /pmc/articles/PMC8733946/ /pubmed/35004656 http://dx.doi.org/10.3389/fbioe.2021.803725 Text en Copyright © 2021 Kelly, Worsley, Bowen, Cherry, Keenan, Edwards, O’Brien, King and Dickinson. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Bioengineering and Biotechnology Kelly, Emily S. Worsley, Peter R. Bowen, Catherine J. Cherry, Lindsey S. Keenan, Bethany E. Edwards, Christopher J. O’Brien, Neil King, Leonard Dickinson, Alex S. Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling |
title | Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling |
title_full | Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling |
title_fullStr | Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling |
title_full_unstemmed | Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling |
title_short | Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling |
title_sort | predicting forefoot-orthosis interactions in rheumatoid arthritis using computational modelling |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733946/ https://www.ncbi.nlm.nih.gov/pubmed/35004656 http://dx.doi.org/10.3389/fbioe.2021.803725 |
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