Mathematically modeling the biological properties of gliomas: A review
Although mathematical modeling is a mainstay for industrial and many scientific studies, such approaches have found little application in neurosurgery. However, the fusion of biological studies and applied mathematics is rapidly changing this environment, especially for cancer research. This review...
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| Format: | Article |
| Language: | English |
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AIMS Press
2015-03-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2015.12.879 |
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| author | Nikolay L. Martirosyan Erica M. Rutter Wyatt L. Ramey Eric J. Kostelich Yang Kuang Mark C. Preul |
| author_facet | Nikolay L. Martirosyan Erica M. Rutter Wyatt L. Ramey Eric J. Kostelich Yang Kuang Mark C. Preul |
| author_sort | Nikolay L. Martirosyan |
| collection | DOAJ |
| description | Although mathematical modeling is a mainstay for industrial and many scientific studies, such approaches have found little application in neurosurgery. However, the fusion of biological studies and applied mathematics is rapidly changing this environment, especially for cancer research. This review focuses on the exciting potential for mathematical models to provide new avenues for studying the growth of gliomas to practical use. In vitro studies are often used to simulate the effects of specific model parameters that would be difficult in a larger-scale model. With regard to glioma invasive properties, metabolic and vascular attributes can be modeled to gain insight into the infiltrative mechanisms that are attributable to the tumor's aggressive behavior. Morphologically, gliomas show different characteristics that may allow their growth stage and invasive properties to be predicted, and models continue to offer insight about how these attributes are manifested visually. Recent studies have attempted to predict the efficacy of certain treatment modalities and exactly how they should be administered relative to each other. Imaging is also a crucial component in simulating clinically relevant tumors and their influence on the surrounding anatomical structures in the brain. |
| format | Article |
| id | doaj-art-5a0670ec7e7a48a49e42d790c4038465 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2015-03-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-5a0670ec7e7a48a49e42d790c40384652025-01-24T02:32:12ZengAIMS PressMathematical Biosciences and Engineering1551-00182015-03-0112487990510.3934/mbe.2015.12.879Mathematically modeling the biological properties of gliomas: A reviewNikolay L. Martirosyan0Erica M. Rutter1Wyatt L. Ramey2Eric J. Kostelich3Yang Kuang4Mark C. Preul5Division of Neurosurgery, University of Arizona, Tucson, AZ 85724School of Mathematical & Statistical Sciences, Arizona State University, Tempe, AZ 85281Creighton Medical School, Phoenix Campus, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013School of Mathematical & Statistical Sciences, Arizona State University, Tempe, AZ 85287School of Mathematics and Statistical Sciences, Arizona State University, Tempe, AZ 85281Division of Neurological Surgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013Although mathematical modeling is a mainstay for industrial and many scientific studies, such approaches have found little application in neurosurgery. However, the fusion of biological studies and applied mathematics is rapidly changing this environment, especially for cancer research. This review focuses on the exciting potential for mathematical models to provide new avenues for studying the growth of gliomas to practical use. In vitro studies are often used to simulate the effects of specific model parameters that would be difficult in a larger-scale model. With regard to glioma invasive properties, metabolic and vascular attributes can be modeled to gain insight into the infiltrative mechanisms that are attributable to the tumor's aggressive behavior. Morphologically, gliomas show different characteristics that may allow their growth stage and invasive properties to be predicted, and models continue to offer insight about how these attributes are manifested visually. Recent studies have attempted to predict the efficacy of certain treatment modalities and exactly how they should be administered relative to each other. Imaging is also a crucial component in simulating clinically relevant tumors and their influence on the surrounding anatomical structures in the brain.https://www.aimspress.com/article/doi/10.3934/mbe.2015.12.879tumor growth simulationproliferation.gliomabiomathematical modelingforecastinginvasion |
| spellingShingle | Nikolay L. Martirosyan Erica M. Rutter Wyatt L. Ramey Eric J. Kostelich Yang Kuang Mark C. Preul Mathematically modeling the biological properties of gliomas: A review Mathematical Biosciences and Engineering tumor growth simulation proliferation. glioma biomathematical modeling forecasting invasion |
| title | Mathematically modeling the biological properties of gliomas: A review |
| title_full | Mathematically modeling the biological properties of gliomas: A review |
| title_fullStr | Mathematically modeling the biological properties of gliomas: A review |
| title_full_unstemmed | Mathematically modeling the biological properties of gliomas: A review |
| title_short | Mathematically modeling the biological properties of gliomas: A review |
| title_sort | mathematically modeling the biological properties of gliomas a review |
| topic | tumor growth simulation proliferation. glioma biomathematical modeling forecasting invasion |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2015.12.879 |
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