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A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee

A personalized model of the human knee for enhancing the inter-individual reproducibility of a measurement method for monitoring Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) after transdermal delivery is proposed. The model is based on the solution of Maxwell Equations in the electric-quasi-statio...

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Autores principales: Arpaia, Pasquale, Crauso, Federica, Frosolone, Mirco, Mariconda, Massimo, Minucci, Simone, Moccaldi, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758660/
https://www.ncbi.nlm.nih.gov/pubmed/35027630
http://dx.doi.org/10.1038/s41598-021-04718-2
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author Arpaia, Pasquale
Crauso, Federica
Frosolone, Mirco
Mariconda, Massimo
Minucci, Simone
Moccaldi, Nicola
author_facet Arpaia, Pasquale
Crauso, Federica
Frosolone, Mirco
Mariconda, Massimo
Minucci, Simone
Moccaldi, Nicola
author_sort Arpaia, Pasquale
collection PubMed
description A personalized model of the human knee for enhancing the inter-individual reproducibility of a measurement method for monitoring Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) after transdermal delivery is proposed. The model is based on the solution of Maxwell Equations in the electric-quasi-stationary limit via Finite Element Analysis. The dimensions of the custom geometry are estimated on the basis of knee circumference at the patella, body mass index, and sex of each individual. An optimization algorithm allows to find out the electrical parameters of each subject by experimental impedance spectroscopy data. Muscular tissues were characterized anisotropically, by extracting Cole–Cole equation parameters from experimental data acquired with twofold excitation, both transversal and parallel to tissue fibers. A sensitivity and optimization analysis aiming at reducing computational burden in model customization achieved a worst-case reconstruction error lower than 5%. The personalized knee model and the optimization algorithm were validated in vivo by an experimental campaign on thirty volunteers, 67% healthy and 33% affected by knee osteoarthritis (Kellgren–Lawrence grade ranging in [1,4]), with an average error of 3%.
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spelling pubmed-87586602022-01-14 A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee Arpaia, Pasquale Crauso, Federica Frosolone, Mirco Mariconda, Massimo Minucci, Simone Moccaldi, Nicola Sci Rep Article A personalized model of the human knee for enhancing the inter-individual reproducibility of a measurement method for monitoring Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) after transdermal delivery is proposed. The model is based on the solution of Maxwell Equations in the electric-quasi-stationary limit via Finite Element Analysis. The dimensions of the custom geometry are estimated on the basis of knee circumference at the patella, body mass index, and sex of each individual. An optimization algorithm allows to find out the electrical parameters of each subject by experimental impedance spectroscopy data. Muscular tissues were characterized anisotropically, by extracting Cole–Cole equation parameters from experimental data acquired with twofold excitation, both transversal and parallel to tissue fibers. A sensitivity and optimization analysis aiming at reducing computational burden in model customization achieved a worst-case reconstruction error lower than 5%. The personalized knee model and the optimization algorithm were validated in vivo by an experimental campaign on thirty volunteers, 67% healthy and 33% affected by knee osteoarthritis (Kellgren–Lawrence grade ranging in [1,4]), with an average error of 3%. Nature Publishing Group UK 2022-01-13 /pmc/articles/PMC8758660/ /pubmed/35027630 http://dx.doi.org/10.1038/s41598-021-04718-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Arpaia, Pasquale
Crauso, Federica
Frosolone, Mirco
Mariconda, Massimo
Minucci, Simone
Moccaldi, Nicola
A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee
title A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee
title_full A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee
title_fullStr A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee
title_full_unstemmed A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee
title_short A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee
title_sort personalized fem model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758660/
https://www.ncbi.nlm.nih.gov/pubmed/35027630
http://dx.doi.org/10.1038/s41598-021-04718-2
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