Quantifying the role of anisotropic invasion in human glioblastoma

R. Sodt, R. Rockne, R. Rockne, M. L. Neal, Kristin Swanson

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Gliomas are highly invasive primary brain tumors, notorious for their recurrence after treatment, and are considered uniformly fatal. Confounding progress is the fact that there is a diffuse extent of tumor cell invasion well beyond what is visible on routine clinical imaging such as MRI. By incorporating diffusion tensor imaging (DTI) which shows the directional orientation of fiber tracts in the brain, we compare patient-specific model simulations to observed tumor growth for two patients, visually, volumetrically and spatially to quantify the effect of anisotropic diffusion on the ability to predict the actual shape and diffuse invasion of tumor as observed on MRI. The ultimate goal is the development of the best patient-specific tool for predicting brain tumor growth and invasion in individual patients, which can aid in treatment planning.

Original languageEnglish (US)
Title of host publicationComputational Surgery and Dual Training: Computing, Robotics and Imaging
PublisherSpringer New York
Pages315-330
Number of pages16
ISBN (Electronic)9781461486480
ISBN (Print)9781461486473
DOIs
StatePublished - Jan 1 2014
Externally publishedYes

Fingerprint

Tumors
Brain
Magnetic resonance imaging
Diffusion tensor imaging
Medical imaging
Cells
Planning
Fibers

Keywords

  • Anisotropic invasion
  • Axonal fibers
  • Biopsy
  • Brain tumor
  • Cell migration
  • Clinical imaging
  • Diffusion tensor imaging
  • Glioblastoma
  • Logistic growth
  • Mathematical modeling
  • Partial differential equation
  • Radiotherapy
  • Tumor growth

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Sodt, R., Rockne, R., Rockne, R., Neal, M. L., & Swanson, K. (2014). Quantifying the role of anisotropic invasion in human glioblastoma. In Computational Surgery and Dual Training: Computing, Robotics and Imaging (pp. 315-330). Springer New York. https://doi.org/10.1007/978-1-4614-8648-0_20

Quantifying the role of anisotropic invasion in human glioblastoma. / Sodt, R.; Rockne, R.; Rockne, R.; Neal, M. L.; Swanson, Kristin.

Computational Surgery and Dual Training: Computing, Robotics and Imaging. Springer New York, 2014. p. 315-330.

Research output: Chapter in Book/Report/Conference proceedingChapter

Sodt, R, Rockne, R, Rockne, R, Neal, ML & Swanson, K 2014, Quantifying the role of anisotropic invasion in human glioblastoma. in Computational Surgery and Dual Training: Computing, Robotics and Imaging. Springer New York, pp. 315-330. https://doi.org/10.1007/978-1-4614-8648-0_20
Sodt R, Rockne R, Rockne R, Neal ML, Swanson K. Quantifying the role of anisotropic invasion in human glioblastoma. In Computational Surgery and Dual Training: Computing, Robotics and Imaging. Springer New York. 2014. p. 315-330 https://doi.org/10.1007/978-1-4614-8648-0_20
Sodt, R. ; Rockne, R. ; Rockne, R. ; Neal, M. L. ; Swanson, Kristin. / Quantifying the role of anisotropic invasion in human glioblastoma. Computational Surgery and Dual Training: Computing, Robotics and Imaging. Springer New York, 2014. pp. 315-330
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