↓ Skip to main content

A Patient-Specific Anisotropic Diffusion Model for Brain Tumour Spread

Overview of attention for article published in Bulletin of Mathematical Biology, May 2017
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
5 X users

Citations

dimensions_citation
66 Dimensions

Readers on

mendeley
48 Mendeley
Title
A Patient-Specific Anisotropic Diffusion Model for Brain Tumour Spread
Published in
Bulletin of Mathematical Biology, May 2017
DOI 10.1007/s11538-017-0271-8
Pubmed ID
Authors

Amanda Swan, Thomas Hillen, John C. Bowman, Albert D. Murtha

Abstract

Gliomas are primary brain tumours arising from the glial cells of the nervous system. The diffuse nature of spread, coupled with proximity to critical brain structures, makes treatment a challenge. Pathological analysis confirms that the extent of glioma spread exceeds the extent of the grossly visible mass, seen on conventional magnetic resonance imaging (MRI) scans. Gliomas show faster spread along white matter tracts than in grey matter, leading to irregular patterns of spread. We propose a mathematical model based on Diffusion Tensor Imaging, a new MRI imaging technique that offers a methodology to delineate the major white matter tracts in the brain. We apply the anisotropic diffusion model of Painter and Hillen (J Thoer Biol 323:25-39, 2013) to data from 10 patients with gliomas. Moreover, we compare the anisotropic model to the state-of-the-art Proliferation-Infiltration (PI) model of Swanson et al. (Cell Prolif 33:317-329, 2000). We find that the anisotropic model offers a slight improvement over the standard PI model. For tumours with low anisotropy, the predictions of the two models are virtually identical, but for patients whose tumours show higher anisotropy, the results differ. We also suggest using the data from the contralateral hemisphere to further improve the model fit. Finally, we discuss the potential use of this model in clinical treatment planning.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 31%
Researcher 10 21%
Student > Doctoral Student 3 6%
Professor > Associate Professor 3 6%
Student > Bachelor 2 4%
Other 5 10%
Unknown 10 21%
Readers by discipline Count As %
Mathematics 8 17%
Engineering 7 15%
Medicine and Dentistry 5 10%
Neuroscience 3 6%
Physics and Astronomy 2 4%
Other 8 17%
Unknown 15 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 June 2018.
All research outputs
#7,214,093
of 22,973,051 outputs
Outputs from Bulletin of Mathematical Biology
#276
of 1,103 outputs
Outputs of similar age
#113,946
of 310,788 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#7
of 29 outputs
Altmetric has tracked 22,973,051 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,103 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 74% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 310,788 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.