Magnetic Drug Targeting in Blood Vessels

Numerical Study Using Magnetic Nanoparticles and CFD Simulation

Master's Thesis Presentation

Numerical Study of Magnetic Drug Targeting in Blood Vessels Using Magnetic Nanoparticles

Master's Thesis - Urmia University of Technology (2014-2016)

Project Overview

This research focuses on the numerical simulation of magnetic drug targeting in blood vessels using computational fluid dynamics (CFD) and magnetic field analysis. The study investigates how magnetic nanoparticles can be controlled and directed to specific locations in blood vessels using external magnetic fields, enabling targeted drug delivery for cancer treatment and other medical applications.

Magnetic Field Control

External magnetic field guidance

Nanoparticle Dynamics

2nm, 5nm, and 10nm diameter particles

CFD Simulation

Blood flow and particle transport

Vessel Geometry & Magnetic Field Configuration

Magnetic Configuration 1
Magnetic Configuration 2
Magnetic Configuration 3
Magnetic Configuration 4

Computational domain showing the vessel geometry and different magnetic field configurations used in CFD simulations

Governing Equations

Continuity Equation

$\frac{\partial \rho}{\partial t} + \frac{\partial}{\partial x_i}(\rho V_i) = 0$

Momentum Equation

$\frac{\partial}{\partial t}(\rho V_i) + \frac{\partial}{\partial x_j}(\rho V_i V_j) = -\frac{\partial p}{\partial x_i} + \frac{\partial}{\partial x_j}\mu\left(\frac{\partial V_i}{\partial x_j} + \frac{\partial V_j}{\partial x_i}\right) + \mu_0 M_i \frac{\partial H_j}{\partial x_i}$

Mass Transfer Equation

$\frac{\partial \alpha}{\partial t} + \frac{\partial}{\partial x_j}(\alpha V_j) = \frac{\partial J_j}{\partial x_j}$

where

$J_j = \Gamma\left(\frac{\partial \alpha}{\partial x_j} + S_T\frac{\partial T}{\partial x_j} - \frac{\alpha}{H}\xi L(\xi)\frac{\partial H_j}{\partial x_j}\right)$

Auxiliary Equations

$\Gamma = \frac{K_B T}{3\pi\mu_b d_p}$

$\xi = \frac{m_i\mu_0 H_i}{K_B T}$

$L(\xi) = \coth\xi - \frac{1}{\xi}$

$m_i = \frac{4\mu_B\pi d_p^3}{6 \times 91.25 \times 10^{-30}}$

$M_i = Nm_i L(\xi)$

Spatio-Temporal Evolution of Nanoparticles

Baseline Study: d = 10nm

Without Magnetic Field

With Magnetic Field

Smaller Nanoparticles Under Magnetic Field

Diameter: d = 5nm

Diameter: d = 2nm

Parametric Study: Magnetic Number & Reynolds Number Effects

Mnf = 32.8, Re = 100, X = x1

Mnf = 328, Re = 100, X = x2

Key Research Findings

Particle Size Effect

Smaller nanoparticles (2nm) demonstrate higher responsiveness to magnetic field gradients compared to larger particles (10nm), enabling more precise drug targeting.

Magnetic Field Strength

Higher magnetic field strength (Mnf = 328) significantly improves particle capture efficiency at target locations compared to lower field strengths (Mnf = 32.8).

Blood Flow Impact

Reynolds number variations demonstrate the critical balance between blood flow velocity and magnetic force for optimal particle accumulation at target sites.

Spatial Distribution

CFD simulations reveal optimal magnet positioning and field geometry for maximizing nanoparticle concentration at tumor or diseased tissue locations.

Related Publications

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