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Investigation of Biotransport in a Tumor With Uncertain Material Properties Using a Nonintrusive Spectral Uncertainty
Alen Alexanderian1, Liang Zhu2, Maher Salloum3
1Department of Mathematics, North Carolina State University, Raleigh, NC 27695
Journal of Biomechanical Engineering
|June 21, 2017
Summary
This study quantifies flow uncertainties in tumors using statistical models and spectral uncertainty quantification (UQ). The approach effectively models heterogeneous material properties, improving predictions for intratumoral injections.
Area of Science:
- Computational fluid dynamics
- Biomedical engineering
- Mathematical modeling
Background:
- Tumor microenvironments exhibit complex, heterogeneous material properties like permeability and porosity.
- Accurate modeling of fluid flow during intratumoral injections is crucial for drug delivery and treatment efficacy.
- Uncertainties in these properties can significantly impact pressure and velocity fields.
Purpose of the Study:
- To develop and validate statistical models for uncertain tumor permeability and porosity.
- To quantify the impact of these uncertainties on pressure and velocity fields during intratumoral injection.
- To assess the efficacy of a nonintrusive spectral uncertainty quantification (UQ) method.
Main Methods:
- Modeling uncertain permeability as a log-Gaussian random field using Karhunen-Lòeve (KL) expansion.
- Modeling uncertain porosity as a log-normal random variable.
- Employing polynomial chaos (PC) expansions and Smolyak sparse quadrature for UQ.
- Performing global sensitivity analysis to identify key contributors to pressure field variance.
Main Results:
- Validated statistical models showed reasonable agreement between simulated and experimental concentration fields.
- The UQ approach successfully quantified uncertainties in pressure and velocity fields.
- Sensitivity analysis revealed the impact of individual KL modes of log-permeability on pressure variance.
Conclusions:
- The developed UQ approach effectively quantifies flow uncertainties arising from heterogeneous tumor properties.
- This methodology provides a robust framework for analyzing and predicting fluid dynamics in complex biological systems.
- The findings support improved computational modeling for intratumoral therapies.
