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Perfusion kinetics in human brain tumor with DCE-MRI derived model and CFD analysis
A Bhandari1, A Bansal2, A Singh3
1Department of Mechanical Engineering, Indian Institute of Technology, Kanpur 208016, India.
Journal of Biomechanics
|June 18, 2017
Summary
This study developed a patient-specific computational model to predict chemotherapy drug delivery in brain tumors. Accurate predictions can improve treatment effectiveness by optimizing drug uptake and selection.
Area of Science:
- Biomedical Engineering
- Computational Biology
- Oncology
Background:
- Chemotherapy effectiveness is limited by non-uniform drug distribution within tumors.
- Accurate prediction of drug transport is essential for enhancing cancer treatment outcomes.
Purpose of the Study:
- To develop a patient-specific computational model for predicting chemotherapeutic drug transport and deposition in human brain tumors.
- To integrate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data into a voxelized porous media model.
Main Methods:
- Developed a voxelized porous media model incorporating DCE-MRI data.
- Included realistic transport and perfusion kinetics, heterogeneous tumor vasculature, and patient-specific arterial input function (AIF).
Main Results:
- Computational results for interstitial fluid pressure (IFP), interstitial fluid velocity (IFV), and tracer concentration showed good agreement with experimental data.
- The model demonstrated patient-specific accuracy in predicting drug transport dynamics.
Conclusions:
- The developed computational model accurately predicts drug transport within brain tumors.
- This model can be extended to predict chemotherapeutic drug deposition and aid in personalized drug selection for cancer patients.
