Mechanistic modelling of dynamic MRI data predicts that tumour heterogeneity decreases therapeutic response.

Abstract:

BACKGROUND:Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) contains crucial information about tumour heterogeneity and the transport limitations that reduce drug efficacy. Mathematical modelling of drug delivery and cellular responsiveness based on underutilised DCE-MRI data has the unique potential to predict therapeutic responsiveness for individual patients. METHODS:To interpret DCE-MRI data, we created a modelling framework that operates over multiple time and length scales and incorporates intracellular metabolism, nutrient and drug diffusion, trans-vascular permeability, and angiogenesis. The computational methodology was used to analyse DCE-MR images collected from eight breast cancer patients at Baystate Medical Center in Springfield, MA. RESULTS:Computer simulations showed that trans-vascular transport was correlated with tumour aggressiveness because increased vessel growth and permeability provided more nutrients for cell proliferation. Model simulations also indicate that vessel density minimally affects tissue growth and drug response, and nutrient availability promotes growth. Finally, the simulations indicate that increased transport heterogeneity is coupled with increased tumour growth and poor drug response. CONCLUSION:Mathematical modelling based on DCE-MRI has the potential to aid treatment decisions and improve overall cancer care. This model is the critical first step in the creation of a comprehensive and predictive computational method.

journal_name

Br J Cancer

authors

Venkatasubramanian R,Arenas RB,Henson MA,Forbes NS

doi

10.1038/sj.bjc.6605773

subject

Has Abstract

pub_date

2010-08-10 00:00:00

pages

486-97

issue

4

eissn

0007-0920

issn

1532-1827

pii

6605773

journal_volume

103

pub_type

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