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Sensitivity Analysis of an Image-Based Solid Tumor Computational Model with Heterogeneous Vasculature and Porosity

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Abstract

An MR image-based computational model of a murine KHT sarcoma is presented that allows the calculation of plasma fluid and solute transport within tissue. Such image-based models of solid tumors may be used to optimize patient-specific therapies. This model incorporates heterogeneous vasculature and tissue porosity to account for nonuniform perfusion of an MR-visible tracer, gadolinium-diethylenetriamine pentaacetic acid (Gd-DTPA). Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was conducted following intravenous infusion of Gd-DTPA to provide 1 h of tracer-concentration distribution data within tissue. Early time points (19 min) were used to construct 3D K trans and porosity maps using a two-compartment model; tracer transport was predicted at later time points using a 3D porous media model. Model development involved selecting an arterial input function (AIF) and conducting a sensitivity analysis of model parameters (tissue, vascular, and initial estimation of solute concentration in plasma) to investigate the effects on transport for a specific tumor. The developed model was then used to predict transport in two additional tumors. The sensitivity analysis suggests that plasma fluid transport is more sensitive to parameter changes than solute transport due to the dominance of transvascular exchange. Gd-DTPA distribution was similar to experimental patterns, but differences in Gd-DTPA magnitude at later time points may result from inaccurate selection of AIF. Thus, accurate AIF estimation is important for later time point prediction of low molecular weight tracer or drug transport in smaller tumors.

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Acknowledgments

We would like to thank Dr. Dietmar Siemann, Dr. Lori Rice, and Chris Pampo for providing the murine KHT sarcoma cells and tumor inoculation. This research was funded by the University of Florida’s Research and Graduate Programs Opportunity Fund and a grant from the National Institutes of Health (R21 NS05270). MR data was obtained at the Advanced Magnetic Resonance Imaging and Spectroscopy facility in the McKnight Brain Institute of the University of Florida.

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Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, University of Florida, 212 MAE-A, Post Box 116250, Gainesville, FL, 32611-6250, USA

    Gregory L. Pishko & Malisa Sarntinoranont

  2. Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA

    Garrett W. Astary

  3. Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA

    Thomas H. Mareci

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  1. Gregory L. Pishko
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  2. Garrett W. Astary
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  4. Malisa Sarntinoranont
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Correspondence to Malisa Sarntinoranont.

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Associate Editor Jeffrey L. Duerk oversaw the review of this article.

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Pishko, G.L., Astary, G.W., Mareci, T.H. et al. Sensitivity Analysis of an Image-Based Solid Tumor Computational Model with Heterogeneous Vasculature and Porosity. Ann Biomed Eng 39, 2360–2373 (2011). https://doi.org/10.1007/s10439-011-0349-7

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