Image-Based Modeling of Drug Delivery during Intraperitoneal Chemotherapy in a Heterogeneous Tumor Nodule

Mohsen Rezaeian; Hamidreza Heidari; Kaamran Raahemifar; Madjid Soltani

doi:10.3390/cancers15205069

Image-Based Modeling of Drug Delivery during Intraperitoneal Chemotherapy in a Heterogeneous Tumor Nodule

Cancers (Basel). 2023 Oct 20;15(20):5069. doi: 10.3390/cancers15205069.

Authors

Mohsen Rezaeian¹, Hamidreza Heidari², Kaamran Raahemifar^{3

4

5}, Madjid Soltani^{1

6

7

8

9}

Affiliations

¹ Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran.
² Otto H. York Department of Chemical and Materials Engineering, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA.
³ Data Science and Artificial Intelligence Program, College of Information Sciences and Technology (IST), Penn State University, State College, PA 16801, USA.
⁴ School of Optometry and Vision Science, Faculty of Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
⁵ Department of Chemical Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
⁶ Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
⁷ Advanced Bioengineering Initiative Center, Multidisciplinary International Complex, K. N. Toosi University of Technology, Tehran 19967-15433, Iran.
⁸ Computational Medicine Center, K. N. Toosi University of Technology, Tehran 19967-15433, Iran.
⁹ Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, ON N2L 3G1, Canada.

Abstract

Intraperitoneal (IP) chemotherapy is a promising treatment approach for patients diagnosed with peritoneal carcinomatosis, allowing the direct delivery of therapeutic agents to the tumor site within the abdominal cavity. Nevertheless, limited drug penetration into the tumor remains a primary drawback of this method. The process of delivering drugs to the tumor entails numerous complications, primarily stemming from the specific pathophysiology of the tumor. Investigating drug delivery during IP chemotherapy and studying the parameters affecting it are challenging due to the limitations of experimental studies. In contrast, mathematical modeling, with its capabilities such as enabling single-parameter studies, and cost and time efficiency, emerges as a potent tool for this purpose. In this study, we developed a numerical model to investigate IP chemotherapy by incorporating an actual image of a tumor with heterogeneous vasculature. The tumor's geometry is reconstructed using image processing techniques. The model also incorporates drug binding and uptake by cancer cells. After 60 min of IP treatment with Doxorubicin, the area under the curve (AUC) of the average free drug concentration versus time curve, serving as an indicator of drug availability to the tumor, reached 295.18 mol·m^-3·s^-1. Additionally, the half-width parameter W_1/2, which reflects drug penetration into the tumor, ranged from 0.11 to 0.14 mm. Furthermore, the treatment resulted in a fraction of killed cells reaching 20.4% by the end of the procedure. Analyzing the spatial distribution of interstitial fluid velocity, pressure, and drug concentration in the tumor revealed that the heterogeneous distribution of tumor vasculature influences the drug delivery process. Our findings underscore the significance of considering the specific vascular network of a tumor when modeling intraperitoneal chemotherapy. The proposed methodology holds promise for application in patient-specific studies.

Keywords: computational oncology; drug delivery; image-based spatiotemporal model; intraperitoneal chemotherapy; peritoneal carcinomatosis.

Grants and funding

This research received no external funding.