Calibrating a Predictive Model of Tumor Growth and Angiogenesis with Quantitative MRI

David A. Hormuth, Angela M. Jarrett, Xinzeng Feng, Thomas E. Yankeelov

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The spatiotemporal variations in tumor vasculature inevitably alters cell proliferation and treatment efficacy. Thus, rigorous characterization of tumor dynamics must include a description of this phenomenon. We have developed a family of biophysical models of tumor growth and angiogenesis that are calibrated with diffusion-weighted magnetic resonance imaging (DW-MRI) and dynamic contrast-enhanced (DCE-) MRI data to provide individualized tumor growth forecasts. Tumor and blood volume fractions were evolved using two, coupled partial differential equations consisting of proliferation, diffusion, and death terms. To evaluate these models, rats (n = 8) with C6 gliomas were imaged seven times. The tumor volume fraction was estimated using DW-MRI, while DCE-MRI provided estimates of the blood volume fraction. The first three time points were used to calibrate model parameters, which were then used to predict growth at the remaining four time points and compared directly to the measurements. The best performing model predicted tumor growth with less than 10.3% error in tumor volume and with less than 9.4% error at the voxel-level at all prediction time points. The best performing model resulted in less than 9.3% error in blood volume at the voxel-level. This pre-clinical study demonstrates the potential for image-based, mechanistic modeling of tumor growth and angiogenesis.

Original languageEnglish (US)
Pages (from-to)1539-1551
Number of pages13
JournalAnnals of Biomedical Engineering
Volume47
Issue number7
DOIs
StatePublished - Jul 15 2019

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Magnetic resonance imaging
Tumors
Volume fraction
Blood
Magnetic resonance
Imaging techniques
Cell proliferation
Partial differential equations
Rats

Keywords

  • DCE-MRI
  • DW-MRI
  • Diffusion
  • Glioma
  • Modeling

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Calibrating a Predictive Model of Tumor Growth and Angiogenesis with Quantitative MRI. / Hormuth, David A.; Jarrett, Angela M.; Feng, Xinzeng; Yankeelov, Thomas E.

In: Annals of Biomedical Engineering, Vol. 47, No. 7, 15.07.2019, p. 1539-1551.

Research output: Contribution to journalArticle

Hormuth, David A. ; Jarrett, Angela M. ; Feng, Xinzeng ; Yankeelov, Thomas E. / Calibrating a Predictive Model of Tumor Growth and Angiogenesis with Quantitative MRI. In: Annals of Biomedical Engineering. 2019 ; Vol. 47, No. 7. pp. 1539-1551.
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