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A quantitative model for differential motility of gliomas in grey and white matter
Open accessAbstract
We have extended a mathematical model of gliomas based on proliferation and diffusion rates to incorporate the effects of augmented cell motility in white matter as compared to grey matter. Using a detailed mapping of the white and grey matter in the brain developed for a MRI simulator, we have been able to simulate model tumours on an anatomically accurate brain domain. Our simulations show good agreement with clinically observed tumour geometries and suggest paths of submicroscopic tumour invasion not detectable on CT or MRI images. We expect this model to give insight into microscopic and submicroscopic invasion of the human brain by glioma cells. This method gives insight in microscopic and submicroscopic invasion of the human brain by glioma cells. Additionally, the model can be useful in defining expected pathways of invasion by glioma cells and thereby identify regions of the brain on which to focus treatments.
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Cited by
A survey of MRI-based medical image analysis for brain tumor studies
Bauer, S., Wiest, R., Nolte, L.-P., & Reyes, M. (2013) · Physics in Medicine and Biology · doi:10.1088/0031-9155/58/13/r97 · Cited by 1,036
Dissecting cancer through mathematics: From the cell to the animal model
Byrne, H. M. (2010) · Nature reviews. Cancer · doi:10.1038/nrc2808 · Cited by 442
Szalisznyo, K., Silverstein, D. N., Duffau, H., & Smits, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0069798 · Cited by 40
Metadata
- Authors
- Swanson, K. R., Alvord, E. C., & Murray, J. D.
- Venue
- Cell Proliferation
- Publisher
- Wiley
- Published
- 2000-10
- Volume
- 33
- Issue
- 5
- Pages
- 317-329
- ISSN
- 0960-7722 (ISSN-L)
- 1365-2184
- OpenAlex
- W2157358125
- Cited by
- 458
- References
- 0
- FWCI
- 8.15
- Type
- journal article
- Language
- en
- Open access
- bronze
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
