Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor

Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor — Computational Approach Publisher Pubmed

Moradi Kashkooli F¹ ; Soltani M^{1, 2, 3, 4, 5} ; Rezaeian M¹ ; Taatizadeh E¹ ; Hamedi MH¹

Show Affiliations

1. Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
2. Advanced Bioengineering Initiative Center, Computational Medicine Center, K. N. Toosi University of Technology, Tehran, Iran
3. Department of Electrical and Computer Engineering, University of Waterloo, ON, Canada
4. Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, Ontario, Canada
5. Cancer Biology Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran

Source: Microvascular Research Published:2019

Abstract

The solute transport distribution in a tumor is an important criterion in the evaluation of the cancer treatment efficacy. The fraction of killed cells after each treatment can quantify the therapeutic effect and plays as a helpful tool to evaluate the chemotherapy treatment schedules. In the present study, an image-based spatio-temporal computational model of a solid tumor is provided for calculation of interstitial fluid flow and solute transport. Current model incorporates heterogeneous microvasculature for angiogenesis instead of synthetic mathematical modeling. In this modeling process, a comprehensive model according to Convection-Diffusion-Reaction (CDR) equations is employed due to its high accuracy for simulating the binding and the uptake of the drug by tumor cells. Based on the velocity and the pressure distribution, transient distribution of the different drug concentrations (free, bound, and internalized) is calculated. Then, the fraction of killed cells is obtained according to the internalized concentration. Results indicate the dependence of the drug distribution on both time and space, as well as the microvasculature density. Free and bound drug concentration have the same trend over time, whereas, internalized and total drug concentration increases over time and reaches a constant value. The highest amount of concentration occurred in the tumor region due to the higher permeability of the blood vessels. Moreover, the fraction of killed cells is approximately 78.87% and 24.94% after treatment with doxorubicin for cancerous and normal tissues, respectively. In general, the presented methodology may be applied in the field of personalized medicine to optimize patient-specific treatments. Also, such image-based modeling of solid tumors can be used in laboratories that working on drug delivery and evaluating new drugs before using them for any in vivo or clinical studies. © 2019 Elsevier Inc.

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Style	Citing Format
MLA	Moradi Kashkooli F, et al.. "Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor — Computational Approach." Microvascular Research, vol. 123, no. , 2019, pp. 111-124.
APA	Moradi Kashkooli F, Soltani M, Rezaeian M, Taatizadeh E, Hamedi MH (2019). Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor — Computational Approach. Microvascular Research, 123(), 111-124.
Chicago	Moradi Kashkooli F, Soltani M, Rezaeian M, Taatizadeh E, Hamedi MH. "Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor — Computational Approach." Microvascular Research 123, no. (2019): 111-124.
Harvard	Moradi Kashkooli F et al. (2019) 'Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor — Computational Approach', Microvascular Research, 123(), pp. 111-124.
Vancouver	Moradi Kashkooli F, Soltani M, Rezaeian M, Taatizadeh E, Hamedi MH. Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor — Computational Approach. Microvascular Research. 2019;123():111-124.
BibTex	@article{ author = {Moradi Kashkooli F and Soltani M and Rezaeian M and Taatizadeh E and Hamedi MH}, title = {Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor — Computational Approach}, journal = {Microvascular Research}, volume = {123}, number = {}, pages = {111-124}, year = {2019} }
RIS	TY - JOUR AU - Moradi Kashkooli F AU - Soltani M AU - Rezaeian M AU - Taatizadeh E AU - Hamedi MH TI - Image-Based Spatio-Temporal Model of Drug Delivery in a Heterogeneous Vasculature of a Solid Tumor — Computational Approach JO - Microvascular Research VL - 123 IS - SP - 111 EP - 124 PY - 2019 ER -

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