Showing 5 results for Sefidgar
Madjid Soltani, Hossein Bazmara, Mostafa Sefidgar, Madjid Bazargan, Seyyed Mojtaba Musavi Naeenian,
Volume 14, Issue 7 (10-2014)
Abstract
Tumor induced angiogenesis is the bridge between benign and malignant tumor growth stages. In this process, growth and migration of endothelial cells build capillaries to supply the tumor with blood for its further growth. Regarding the importance of capillary formation and blood flow in angiogenesis, simulation of this phenomenon plays important role in tumor growth and cancer development studies. In this work, considering intracellular, cellular, and extracellular scales a mathematical model of tumor-induced angiogenesis is used to consider mechanical effects of extracellular matrix on growth and migration of endothelial cells. These effects are matrix density and its fiber length. In this study, to model cellular dynamics, a discrete lattice based Monte Carlo method is used. Results show that migration of endothelial cells and development of capillaries are possible in a specified range of matrix density and matrix fiber length. Based on the results, medium matrix densities and low fiber length provide a suitable environment for capillaries growth and development. The model is a promising tool for modeling tumor induced angiogenesis and is a base for development of models for loop formation and blood flow in capillaries around tumor.
Mostafa Sefidgar, Hossein Bazmara, Majid Bazargan, S. Mojtaba Mousavi Naeenian, Madjid Soltani,
Volume 14, Issue 9 (12-2014)
Abstract
Nowadays, solid tumor modeling and simulation results are used to predict how therapeutic drugs are transported to tumor cells by blood flow through capillaries and fluid flow in tissues. This model involves processes such as fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. In this paper, a complete model of interstitial fluid flow in tumor and normal tissue is presented with considering multi scale of solution such as blood flow through a capillary (as the smallest scale) to interstitial flow (as the biggest scale). The advanced mathematical model is used to generate a capillary network induce by tumor with two parent vessel around the tumor for the first time. In the following, the blood flow is modeled through the network with considering the non-continuous behavior of blood rheology and adaptability of capillary diameter to hemodynamics and metabolic stimuli. This flow is simultaneously simulated with interstitial flow which is coupled to blood flow through capillary with extravascular flow. The results predict elevated interstitial pressure in tumor region and heterogeneous capillary network which are introduced as barriers to drug delivery.
Mehdi Ahmadvand, Mostafa Mafi, Mostafa Sefidgar, Majid Soltani,
Volume 16, Issue 11 (1-2017)
Abstract
The Nowadays the use of modified compartmental model in order to estimate the transmission of tracer to the cells or cancerous tissues is focused extensively. The modified compartmental model includes two compartments, one to predict the mass transfer from vessels and a compartment to describe metabolism occurring inside the tissue. In the modified compartmental model, the kinetic rate constants can be obtained by estimating the parameters between the compartments. The accurate calculation (estimation) of rate factors over the region under study has an important role in coinciding the time activity curve obtained by compartmental modeling and the curve resulted from experimental data which is the main tool to distinguish the cancerous and normal tissues. Today most of doctors us the standard uptake value to study the amount of tracer uptake in cancer suspicious regions in order to have a more accurate recognition of cancerous and normal tissues. In this paper the Patlak graphical analysis method and standard uptake value (SUV) method are used to predict the tracer uptake into the tissue. A comparison between the uptake parameter resulted from the two mentioned methods with the uptake parameter obtained by modified compartmental model in a rat shows the accuracy of the Patlak method in distinguishing the cancerous tissues from the normal ones.
Mostafa Sefidgar, Ramin Sijanivandi, Madjid Soltani, Mohammad Hossein Hamedi,
Volume 17, Issue 10 (1-2018)
Abstract
In this paper, a numerical algorithm based inverse method is used to estimate effective diffusion coefficient by using experimental tracer distribution. The Algorithm uses factitious experimental data which are produced by adding noise to numerical data obtained from direct problem. A comprehensive model (Diffusion-Convection-Reaction) is used to derive PET tracer distribution in tumor tissue with microvasculature network. This model was used because of considering all transport phenomena in tissue. In this work to achieve accurate distribution of tracer in tumor tissue, convection diffusion reaction equation which is a PDE is implemented. The proposed tracer in this work is Fluorodeoxyglucose (18F). Solution of inverse problem for estimating effective Diffusion Coefficient is based on minimization of least squares norm. In this work Levenberg-Marquardt technique is applied. Solution of parameter estimation problem require calculation of sensitivity matrix which elements are sensitivity coefficients. Sensitivity coefficients shows differentiation of Tracer concentration with respect to Effective Diffusion coefficient variation is calculated using first derivation of concentration equation. The equations of concentration distribution and sensitivity coefficients are solved using Finite volume method. The results show that the numerical algorithm is able to estimate the effective diffusion coefficient in tissue.
M. Mohammadi, M. Sefidgar,
Volume 19, Issue 12 (December 2019)
Abstract
Today, mathematical models and numerical methods are highly regarded according to their ability to predict and understand the cancer treatment process. In this research, the drug delivery to the solid tumor with considering its normal surrounding tissue has been studied by stimulating the blood flow in the dynamic capillary network and interstitial flow and adding the solute transport equation to the fluid flow equations. In the present study for the first time, drug delivery has been studied by a multi-scale comprehensive model with considering two parent vessels with different branches and different input and output pressures. In this paper, the intravascular flow was simultaneously simulated with the interstitial fluid flow. The distribution of drug concentration has been investigated at different times. The results show the dependence of the drug delivery to the interstitial fluid pressure, the pressure of the parent vessel and in fact, the blood pressure of each patient, and the capillary network structure. In addition, an increase of about 20% of the average drug concentration in the tumor site in the present study compared to the previous study with a parent vessel is evidence of the key role of the capillary network and its dependent parameters.
