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In Silico Modelling of Tumour Margin Diffusion and Infiltration: Review of Current Status
As a result of advanced treatment techniques, requiring precise target definitions, a need for more accurate delineation of the Clinical Target Volume (CTV) has arisen. Mathematical modelling is found to be a powerful tool to provide fairly accurate predictions for the Microscopic Extension (ME) of...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3418724/ https://www.ncbi.nlm.nih.gov/pubmed/22919432 http://dx.doi.org/10.1155/2012/672895 |
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author | Moghaddasi, Fatemeh Leyla Bezak, Eva Marcu, Loredana |
author_facet | Moghaddasi, Fatemeh Leyla Bezak, Eva Marcu, Loredana |
author_sort | Moghaddasi, Fatemeh Leyla |
collection | PubMed |
description | As a result of advanced treatment techniques, requiring precise target definitions, a need for more accurate delineation of the Clinical Target Volume (CTV) has arisen. Mathematical modelling is found to be a powerful tool to provide fairly accurate predictions for the Microscopic Extension (ME) of a tumour to be incorporated in a CTV. In general terms, biomathematical models based on a sequence of observations or development of a hypothesis assume some links between biological mechanisms involved in cancer development and progression to provide quantitative or qualitative measures of tumour behaviour as well as tumour response to treatment. Generally, two approaches are taken: deterministic and stochastic modelling. In this paper, recent mathematical models, including deterministic and stochastic methods, are reviewed and critically compared. It is concluded that stochastic models are more promising to provide a realistic description of cancer tumour behaviour due to being intrinsically probabilistic as well as discrete, which enables incorporation of patient-specific biomedical data such as tumour heterogeneity and anatomical boundaries. |
format | Online Article Text |
id | pubmed-3418724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-34187242012-08-23 In Silico Modelling of Tumour Margin Diffusion and Infiltration: Review of Current Status Moghaddasi, Fatemeh Leyla Bezak, Eva Marcu, Loredana Comput Math Methods Med Review Article As a result of advanced treatment techniques, requiring precise target definitions, a need for more accurate delineation of the Clinical Target Volume (CTV) has arisen. Mathematical modelling is found to be a powerful tool to provide fairly accurate predictions for the Microscopic Extension (ME) of a tumour to be incorporated in a CTV. In general terms, biomathematical models based on a sequence of observations or development of a hypothesis assume some links between biological mechanisms involved in cancer development and progression to provide quantitative or qualitative measures of tumour behaviour as well as tumour response to treatment. Generally, two approaches are taken: deterministic and stochastic modelling. In this paper, recent mathematical models, including deterministic and stochastic methods, are reviewed and critically compared. It is concluded that stochastic models are more promising to provide a realistic description of cancer tumour behaviour due to being intrinsically probabilistic as well as discrete, which enables incorporation of patient-specific biomedical data such as tumour heterogeneity and anatomical boundaries. Hindawi Publishing Corporation 2012 2012-07-11 /pmc/articles/PMC3418724/ /pubmed/22919432 http://dx.doi.org/10.1155/2012/672895 Text en Copyright © 2012 Fatemeh Leyla Moghaddasi et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Moghaddasi, Fatemeh Leyla Bezak, Eva Marcu, Loredana In Silico Modelling of Tumour Margin Diffusion and Infiltration: Review of Current Status |
title |
In Silico Modelling of Tumour Margin Diffusion and Infiltration: Review of Current Status |
title_full |
In Silico Modelling of Tumour Margin Diffusion and Infiltration: Review of Current Status |
title_fullStr |
In Silico Modelling of Tumour Margin Diffusion and Infiltration: Review of Current Status |
title_full_unstemmed |
In Silico Modelling of Tumour Margin Diffusion and Infiltration: Review of Current Status |
title_short |
In Silico Modelling of Tumour Margin Diffusion and Infiltration: Review of Current Status |
title_sort | in silico modelling of tumour margin diffusion and infiltration: review of current status |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3418724/ https://www.ncbi.nlm.nih.gov/pubmed/22919432 http://dx.doi.org/10.1155/2012/672895 |
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