Predicting forefoot-orthosis interactions in rheumatoid arthritis using computational modelling
Predicting forefoot-orthosis interactions in rheumatoid arthritis using computational modelling
Background: 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 of people with rheumatoid arthritis of varying severity produced differing biomechanical predictions from each other and from a healthy control, for the future purpose of aiding orthosis design.
Methods: forefoot models were developed from MR data of 13 participants with rheumatoid arthritis and 1 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 BMI and Leeds Foot Impact Scale– Impairment/Footwear score (LFIS-IF).
Findings: the predicted pressure and shear strain for the healthy participant fell at the lower end of the rheumatoid models’ range. Medial 1st 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.
Interpretation: the forefoot models produced differing biomechanical predictions between a healthy individual and participants with rheumatoid arthritis, and between individuals with rheumatoid arthritis. 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.
FEA, computational modeling, deep tissue injury, foot, foot orthosis, tissue strain
Kelly, Emily, Sarah
422cd3cb-e7a0-4fa1-869a-51c0ac27e29e
Worsley, Peter
6d33aee3-ef43-468d-aef6-86d190de6756
Bowen, Catherine, Jane
e970151b-cd51-4a7e-835d-6e796d7b859f
Cherry, Lindsey
95256156-ce8c-4e7c-b04d-b6e459232441
Keenan, Bethany
cb0d2f90-0d73-4b67-9b60-933b98aa8eaa
Edwards, Christopher
dcb27fec-75ea-4575-a844-3588bcf14106
O'Brien, Neil
7856f2e1-73fc-4cb9-a1f4-9b6c8b9373e7
King, Leonard
7442bd3c-ed4c-46aa-9d9b-1898a113c740
Dickinson, Alexander
10151972-c1b5-4f7d-bc12-6482b5870cad
23 December 2021
Kelly, Emily, Sarah
422cd3cb-e7a0-4fa1-869a-51c0ac27e29e
Worsley, Peter
6d33aee3-ef43-468d-aef6-86d190de6756
Bowen, Catherine, Jane
e970151b-cd51-4a7e-835d-6e796d7b859f
Cherry, Lindsey
95256156-ce8c-4e7c-b04d-b6e459232441
Keenan, Bethany
cb0d2f90-0d73-4b67-9b60-933b98aa8eaa
Edwards, Christopher
dcb27fec-75ea-4575-a844-3588bcf14106
O'Brien, Neil
7856f2e1-73fc-4cb9-a1f4-9b6c8b9373e7
King, Leonard
7442bd3c-ed4c-46aa-9d9b-1898a113c740
Dickinson, Alexander
10151972-c1b5-4f7d-bc12-6482b5870cad
Kelly, Emily, Sarah, Worsley, Peter, Bowen, Catherine, Jane, Cherry, Lindsey, Keenan, Bethany, Edwards, Christopher, O'Brien, Neil, King, Leonard and Dickinson, Alexander
(2021)
Predicting forefoot-orthosis interactions in rheumatoid arthritis using computational modelling.
Frontiers in Bioengineering and Biotechnology, 9, [803725].
(doi:10.3389/fbioe.2021.803725).
Abstract
Background: 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 of people with rheumatoid arthritis of varying severity produced differing biomechanical predictions from each other and from a healthy control, for the future purpose of aiding orthosis design.
Methods: forefoot models were developed from MR data of 13 participants with rheumatoid arthritis and 1 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 BMI and Leeds Foot Impact Scale– Impairment/Footwear score (LFIS-IF).
Findings: the predicted pressure and shear strain for the healthy participant fell at the lower end of the rheumatoid models’ range. Medial 1st 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.
Interpretation: the forefoot models produced differing biomechanical predictions between a healthy individual and participants with rheumatoid arthritis, and between individuals with rheumatoid arthritis. 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.
Text
Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis using Computational Modellin
- Accepted Manuscript
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fbioe-09-803725
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More information
Accepted/In Press date: 7 December 2021
e-pub ahead of print date: 23 December 2021
Published date: 23 December 2021
Additional Information:
Ethics Statement
The studies involving human participants were reviewed and approved by Southampton and South West Hampshire Local Research Ethics Committee (NIHR ref. 24,427), Cardiff University School of Psychology Ethics Committee (EC.18.03.13.5264), and University of Southampton (ERGO ID: 48,707 and 48,710), United Kingdom. The patients/participants provided their written informed consent to participate in this study.
Author Contributions
EK, PW, CB, AD were involved in conception of the study, data analysis and interpretation. CB, CE, LC, LK, BK, NO were involved in data collection and preparation of the original datasets. EK collected further data and drafted the manuscript. All authors reviewed and approved the manuscript.
Funding
The authors would like to thank the following for their financial support:
• ESK: the University of Southampton’s EPSRC Doctoral Training Program (ref EP/R513325/1)
• PRW: the EPSRC-NIHR “Medical Device and Vulnerable Skin Network” (ref EP/N02723X/1)
• CB, CE, LC, LK: Pfizer Inc., “The epidemiology of MRI-detected rheumatoid arthritis disease activity within the forefoot”
• ASD: the Royal Academy of Engineering, United Kingdom, (ref RF/130).
The FeeTURA study received funding from Pfizer Inc. The funder was not involved in the present study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.
Keywords:
FEA, computational modeling, deep tissue injury, foot, foot orthosis, tissue strain
Identifiers
Local EPrints ID: 454021
URI: http://eprints.soton.ac.uk/id/eprint/454021
PURE UUID: 8a4008c8-be29-4f19-8e22-da8021a3be72
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Date deposited: 27 Jan 2022 18:44
Last modified: 17 Mar 2024 03:15
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Author:
Emily, Sarah Kelly
Author:
Catherine, Jane Bowen
Author:
Bethany Keenan
Author:
Neil O'Brien
Author:
Leonard King
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