Patient-Specific Mathematical Neuro-Oncology: Using a Simple Proliferation and Invasion Tumor Model to Inform Clinical Practice

Pamela R. Jackson, Joseph Juliano, Andrea Hawkins-Daarud, Russell C. Rockne, Kristin Swanson

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor associated with a poor median survival of 15–18 months, yet there is wide heterogeneity across and within patients. This heterogeneity has been the source of significant clinical challenges facing patients with GBM and has hampered the drive toward more precision or personalized medicine approaches to treating these challenging tumors. Over the last two decades, the field of Mathematical Neuro-oncology has grown out of desire to use (often patient-specific) mathematical modeling to better treat GBMs. Here, we will focus on a series of clinically relevant results using patient-specific mathematical modeling. The core model at the center of these results incorporates two hallmark features of GBM, proliferation (ρ) and invasion (D), as key parameters. Based on routinely obtained magnetic resonance images, each patient’s tumor can be characterized using these two parameters. The Proliferation-Invasion (PI) model uses ρ and D to create patient-specific growth predictions. The PI model, its predictions, and parameters have been used in a number of ways to derive biological insight. Beyond predicting growth, the PI model has been utilized to identify patients who benefit from different surgery strategies, to prognosticate response to radiation therapy, to develop a treatment response metric, and to connect clinical imaging features and genetic information. Demonstration of the PI model’s clinical relevance supports the growing role for it and other mathematical models in routine clinical practice.

Original languageEnglish (US)
Pages (from-to)846-856
Number of pages11
JournalBulletin of Mathematical Biology
Volume77
Issue number5
DOIs
StatePublished - Mar 21 2015
Externally publishedYes

Fingerprint

Oncology
Invasion
Proliferation
tumor
Tumors
Tumor
Glioblastoma
neoplasms
Precision Medicine
Neoplasms
Mathematical Modeling
mathematical models
Radiation Therapy
Brain Tumor
Magnetic Resonance Image
Model
Medical imaging
Radiotherapy
Magnetic resonance
Growth

Keywords

  • Glioblastoma
  • Mathematical model
  • Patient-specific

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Environmental Science(all)
  • Immunology
  • Mathematics(all)
  • Computational Theory and Mathematics
  • Neuroscience(all)
  • Pharmacology

Cite this

Patient-Specific Mathematical Neuro-Oncology : Using a Simple Proliferation and Invasion Tumor Model to Inform Clinical Practice. / Jackson, Pamela R.; Juliano, Joseph; Hawkins-Daarud, Andrea; Rockne, Russell C.; Swanson, Kristin.

In: Bulletin of Mathematical Biology, Vol. 77, No. 5, 21.03.2015, p. 846-856.

Research output: Contribution to journalArticle

Jackson, Pamela R. ; Juliano, Joseph ; Hawkins-Daarud, Andrea ; Rockne, Russell C. ; Swanson, Kristin. / Patient-Specific Mathematical Neuro-Oncology : Using a Simple Proliferation and Invasion Tumor Model to Inform Clinical Practice. In: Bulletin of Mathematical Biology. 2015 ; Vol. 77, No. 5. pp. 846-856.
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