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A four‐compartment multiscale model of fluid and drug distribution in vascular tumours
The subtle relationship between vascular network structure and mass transport is vital to predict and improve the efficacy of anticancer treatments. Here, mathematical homogenisation is used to derive a new multiscale continuum model of blood and chemotherapy transport in the vasculature and interst...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187161/ https://www.ncbi.nlm.nih.gov/pubmed/32031302 http://dx.doi.org/10.1002/cnm.3315 |
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author | Shipley, Rebecca J. Sweeney, Paul W. Chapman, Stephen J. Roose, Tiina |
author_facet | Shipley, Rebecca J. Sweeney, Paul W. Chapman, Stephen J. Roose, Tiina |
author_sort | Shipley, Rebecca J. |
collection | PubMed |
description | The subtle relationship between vascular network structure and mass transport is vital to predict and improve the efficacy of anticancer treatments. Here, mathematical homogenisation is used to derive a new multiscale continuum model of blood and chemotherapy transport in the vasculature and interstitium of a vascular tumour. This framework enables information at a range of vascular hierarchies to be fed into an effective description on the length scale of the tumour. The model behaviour is explored through a demonstrative case study of a simplified representation of a dorsal skinfold chamber, to examine the role of vascular network architecture in influencing fluid and drug perfusion on the length scale of the chamber. A single parameter, P, is identified that relates tumour‐scale fluid perfusion to the permeability and density of the capillary bed. By fixing the topological and physiological properties of the arteriole and venule networks, an optimal value for P is identified, which maximises tumour fluid transport and is thus hypothesised to benefit chemotherapy delivery. We calculate the values for P for eight explicit network structures; in each case, vascular intervention by either decreasing the permeability or increasing the density of the capillary network would increase fluid perfusion through the cancerous tissue. Chemotherapeutic strategies are compared and indicate that single injection is consistently more successful compared with constant perfusion, and the model predicts optimal timing of a second dose. These results highlight the potential of computational modelling to elucidate the link between vascular architecture and fluid, drug distribution in tumours. |
format | Online Article Text |
id | pubmed-7187161 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71871612020-04-28 A four‐compartment multiscale model of fluid and drug distribution in vascular tumours Shipley, Rebecca J. Sweeney, Paul W. Chapman, Stephen J. Roose, Tiina Int J Numer Method Biomed Eng Research Article ‐ Fundamentals The subtle relationship between vascular network structure and mass transport is vital to predict and improve the efficacy of anticancer treatments. Here, mathematical homogenisation is used to derive a new multiscale continuum model of blood and chemotherapy transport in the vasculature and interstitium of a vascular tumour. This framework enables information at a range of vascular hierarchies to be fed into an effective description on the length scale of the tumour. The model behaviour is explored through a demonstrative case study of a simplified representation of a dorsal skinfold chamber, to examine the role of vascular network architecture in influencing fluid and drug perfusion on the length scale of the chamber. A single parameter, P, is identified that relates tumour‐scale fluid perfusion to the permeability and density of the capillary bed. By fixing the topological and physiological properties of the arteriole and venule networks, an optimal value for P is identified, which maximises tumour fluid transport and is thus hypothesised to benefit chemotherapy delivery. We calculate the values for P for eight explicit network structures; in each case, vascular intervention by either decreasing the permeability or increasing the density of the capillary network would increase fluid perfusion through the cancerous tissue. Chemotherapeutic strategies are compared and indicate that single injection is consistently more successful compared with constant perfusion, and the model predicts optimal timing of a second dose. These results highlight the potential of computational modelling to elucidate the link between vascular architecture and fluid, drug distribution in tumours. John Wiley and Sons Inc. 2020-02-25 2020-03 /pmc/articles/PMC7187161/ /pubmed/32031302 http://dx.doi.org/10.1002/cnm.3315 Text en © 2020 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article ‐ Fundamentals Shipley, Rebecca J. Sweeney, Paul W. Chapman, Stephen J. Roose, Tiina A four‐compartment multiscale model of fluid and drug distribution in vascular tumours |
title | A four‐compartment multiscale model of fluid and drug distribution in vascular tumours |
title_full | A four‐compartment multiscale model of fluid and drug distribution in vascular tumours |
title_fullStr | A four‐compartment multiscale model of fluid and drug distribution in vascular tumours |
title_full_unstemmed | A four‐compartment multiscale model of fluid and drug distribution in vascular tumours |
title_short | A four‐compartment multiscale model of fluid and drug distribution in vascular tumours |
title_sort | four‐compartment multiscale model of fluid and drug distribution in vascular tumours |
topic | Research Article ‐ Fundamentals |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187161/ https://www.ncbi.nlm.nih.gov/pubmed/32031302 http://dx.doi.org/10.1002/cnm.3315 |
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