Literature DB >> 30711547

Image-based spatio-temporal model of drug delivery in a heterogeneous vasculature of a solid tumor - Computational approach.

Farshad Moradi Kashkooli1, M Soltani2, Mohsen Rezaeian1, Erfan Taatizadeh1, Mohammad-Hossein Hamedi1.   

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.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Drug delivery; Fraction of killed cells; Heterogeneous capillary network; Image-based spatio-temporal model; Mathematical modeling; Microvasculature; Solid tumor

Mesh:

Substances:

Year:  2019        PMID: 30711547     DOI: 10.1016/j.mvr.2019.01.005

Source DB:  PubMed          Journal:  Microvasc Res        ISSN: 0026-2862            Impact factor:   3.514


  12 in total

1.  A Mathematical Model to Estimate Chemotherapy Concentration at the Tumor-Site and Predict Therapy Response in Colorectal Cancer Patients with Liver Metastases.

Authors:  Daniel A Anaya; Prashant Dogra; Zhihui Wang; Mintallah Haider; Jasmina Ehab; Daniel K Jeong; Masoumeh Ghayouri; Gregory Y Lauwers; Kerry Thomas; Richard Kim; Joseph D Butner; Sara Nizzero; Javier Ruiz Ramírez; Marija Plodinec; Richard L Sidman; Webster K Cavenee; Renata Pasqualini; Wadih Arap; Jason B Fleming; Vittorio Cristini
Journal:  Cancers (Basel)       Date:  2021-01-25       Impact factor: 6.639

2.  A multiscale cell-based model of tumor growth for chemotherapy assessment and tumor-targeted therapy through a 3D computational approach.

Authors:  Sahar Jafari Nivlouei; Madjid Soltani; Ebrahim Shirani; Mohammad Reza Salimpour; Rui Travasso; João Carvalho
Journal:  Cell Prolif       Date:  2022-02-07       Impact factor: 6.831

3.  Numerical Investigation on the Anti-Angiogenic Therapy-Induced Normalization in Solid Tumors.

Authors:  Mahya Mohammadi; Cyrus Aghanajafi; M Soltani; Kaamran Raahemifar
Journal:  Pharmaceutics       Date:  2022-02-05       Impact factor: 6.321

4.  Mathematical Modeling of Targeted Drug Delivery Using Magnetic Nanoparticles during Intraperitoneal Chemotherapy.

Authors:  Mohsen Rezaeian; M Soltani; Ahmad Naseri Karimvand; Kaamran Raahemifar
Journal:  Pharmaceutics       Date:  2022-01-29       Impact factor: 6.321

5.  Computational modeling of PET tracer distribution in solid tumors integrating microvasculature.

Authors:  Niloofar Fasaeiyan; M Soltani; Farshad Moradi Kashkooli; Erfan Taatizadeh; Arman Rahmim
Journal:  BMC Biotechnol       Date:  2021-11-25       Impact factor: 2.563

Review 6.  Enhancing Clinical Translation of Cancer Using Nanoinformatics.

Authors:  Madjid Soltani; Farshad Moradi Kashkooli; Mohammad Souri; Samaneh Zare Harofte; Tina Harati; Atefeh Khadem; Mohammad Haeri Pour; Kaamran Raahemifar
Journal:  Cancers (Basel)       Date:  2021-05-19       Impact factor: 6.639

7.  Numerical modeling of high-intensity focused ultrasound-mediated intraperitoneal delivery of thermosensitive liposomal doxorubicin for cancer chemotherapy.

Authors:  Mohsen Rezaeian; Amir Sedaghatkish; M Soltani
Journal:  Drug Deliv       Date:  2019-12       Impact factor: 6.419

8.  Effects of hypoxia and nanocarrier size on pH-responsive nano-delivery system to solid tumors.

Authors:  M Soltani; Mohammad Souri; Farshad Moradi Kashkooli
Journal:  Sci Rep       Date:  2021-09-29       Impact factor: 4.379

9.  Evaluation of solid tumor response to sequential treatment cycles via a new computational hybrid approach.

Authors:  Farshad Moradi Kashkooli; M Soltani
Journal:  Sci Rep       Date:  2021-11-02       Impact factor: 4.379

10.  Enhanced Drug Delivery to Solid Tumors via Drug-Loaded Nanocarriers: An Image-Based Computational Framework.

Authors:  Farshad Moradi Kashkooli; M Soltani; Mohammad Masoud Momeni; Arman Rahmim
Journal:  Front Oncol       Date:  2021-06-24       Impact factor: 6.244

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