Swarm of magnetic nanoparticles steering in multi-bifurcation vessels under fluid flow

Generation of magnetic biohybrid microrobots based on MSC.sTRAIL for targeted stem cell delivery and treatment of cancer

Background

Combining the power of magnetic guidance and the biological activities of stem cells transformed into biohybrid microrobots holds great promise for the treatment of several diseases including cancer.

Results

We found that human MSCs can be readily loaded with magnetic particles and that the resulting biohybrid microrobots could be guided by a rotating magnetic field. Rotating magnetic fields have the potential to be applied in the human setting and steer therapeutic stem cells to the desired sites of action in the body. We could demonstrate that the required loading of magnetic particles into stem cells is compatible with their biological activities. We examined this issue with a particular focus on the expression and functionality of therapeutic genes inside of human MSC-based biohybrid microrobots. The loading with magnetic particles did not cause a loss of viability or apoptosis in the human MSCs nor did it impact on the therapeutic gene expression from the cells. Furthermore, the therapeutic effect of the gene products was not affected, and the cells also did not lose their migration potential.

Conclusion

These results demonstrate that the fabrication of guidable MSC-based biohybrid microrobots is compatible with their biological and therapeutic functions. Thus, MSC-based biohybrid microrobots represent a novel way of delivering gene therapies to tumours as well as in the context of other diseases.

Improved magnetic drug targeting with maximized magnetic forces and limited particle spreading

BACKGROUND

In magnetic drug targeting (MDT), micro- or nanoparticles are injected into the human body to locally deliver therapeutics. These magnetic particles can be guided from a distance by external magnetic fields and gradients from electromagnets.

PURPOSE

During the particles' movement through the vascular network, they are affected by magnetic forces, fluid (drag) forces, particle interactions, diffusion, etc. Adequate targeting is hindered when drag forces overcome the magnetic forces and particles present in vessels are carried away from the targeted region. Moreover, the magnetic force directions and diffusion mechanisms can cause particles to scatter, while they should remain together for an effective targeting performance. In this work, these adverse effects are tackled using optimization methods.

METHODS

We formulate an optimization problem with respect to the currents in surrounding electromagnets that aims to maximize the magnetic force on a particle along a predefined direction. A boundary on the magnetic force divergence is introduced as a constraint to limit particle spreading. We also consider particles to be moved from an initial to a target location in a finite-time interval. To this end dynamic optimization is applied.

RESULTS

Simulations for particles in a bifurcated vessel show an increase of particle speed by 20% and a successful movement towards the targeted regions without spreading. For the dynamic optimization, simulation results demonstrate that particle collections are accurately guided with 10 times less scattering and 10 times more particles at the target than without the divergence constraint.

CONCLUSIONS

The proposed methods significantly improve the steering and capturing of particles in a region of interest. They are applicable to any magnetic drug targeting configuration with electromagnets.

Electrical Optimization Method Based on a Novel Arrangement of the Magnetic Navigation System with Gradient and Uniform Saddle Coils

The magnetic navigation system (MNS) with gradient and uniform saddle coils is an effective system for manipulating various medical magnetic robots because of its compact structure and the uniformity of its magnetic field and field gradient. Since each coil of the MNS was geometrically optimized to generate strong uniform magnetic field or field gradient, it is considered that no special optimization is required for the MNS. However, its electrical characteristics can be still optimized to utilize the maximum power of a power supply unit with improved operating time and a stronger time-varying magnetic field. Furthermore, the conventional arrangement of the coils limits the maximum three-dimensional (3D) rotating magnetic field. In this paper, we propose an electrical optimization method based on a novel arrangement of the MNS. We introduce the objective functions, constraints, and design variables of the MNS considering electrical characteristics such as resistance, current density, and inductance. Then, we design an MNS using an optimization algorithm and compare it with the conventional MNS; the proposed MNS generates a magnetic field or field gradient 22% stronger on average than that of the conventional MNS with a sevenfold longer operating time limit, and the maximum three-dimensional rotating magnetic field is improved by 42%. We also demonstrate that the unclogging performance of the helical robot improves by 54% with the constructed MNS.

Blood flow and diameter effect in the navigation process of magnetic nanocarriers inside the carotid artery

BACKGROUND AND OBJECTIVE

Serious side effects are occurred during the cancer therapy. Magnetic driving of nanoparticles is a novel method for the elimination of these effects by supplying with anticancer drug or increase the temperature of the infected area. For this reason, a numerical model for optimal guidance of nanoparticles, through the gradient magnetic field, inside the human artery system is presented in this study.

METHODS

The present method couples Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) techniques. In addition, the optimum magnetic intensity each time is evaluated by using the covariance matrix adaptation evolution strategy (CMA-ES). Under five feature blood flow velocities in cardiac cycle, the developed method evaluate and select the optimum gradient magnetic field in order to eliminate the deviation of the guided nanoparticles from a pre-described trajectory.

RESULTS

Results of the simulations indicate both the influence of the blood flow and the volume of nanocarriers in the magnetic driving process in real conditions. Specifically, the blood flow and the volume of particles are inversely proportional parameters in the magnetic navigation process. As the blood flow is decreased, the deviation of nanoparticles compared to the desired path is minimized. On the contrary, the decrease of the volume of nanocarriers increase the distance of particles from the described trajectory. However, greater magnetic gradient values are needed as the blood flow is increased. Furthermore, the imposed gradient magnetic values are strongly connected with the position of the nanoparticles and the blood blow velocity.

CONCLUSIONS

Based on the results of the present study, the most important parameter in the navigation process is the magnetic volume of particles. Under real conditions, the effect of the blood flow is insignificant compared to the volume of particles in the navigation process. In addition, great differences in the optimized magnetic sequence are presented both among the different blood flows and the volume of particles.

Euler-Lagrange numerical simulation of improved magnetic drug delivery in a three-dimensional CT-based carotid artery bifurcation

BACKGROUND AND OBJECTIVE

Magnetic drug targeting (MDT) is a promising method to improve the therapy efficiency for cardiovascular diseases (CVDs) and cancers. In MDT, therapeutic agents are bonded to superparamagnetic iron oxide nanoparticle (SPION) cores and then are guided toward the damaged tissue through a magnetic field. Fundamentally, it's vital to steer the SPIONs to the desired location to increase the capture efficiency at the target lesion. Hence, the present study aims to enhance the drug delivery to the desired branch in a carotid bifurcation. Besides, it is tried to decrement the particles' entry to the unwanted outlet by using four different magnet configurations (with a maximum magnetic flux density of 0.4 T) implanted adjacent to the artery wall. Also, the effect of particles' diameter -ranging from 200 nm to 2 µm- on the drug delivery performance is studied in the four cases.

METHODS

The Eulerian-Lagrangian approach with one-way coupling is employed for numerical simulation of the problem using the finite element method (FEM). The dominant forces acting on particles are drag and magnetophoretic. A computed tomography (CT) model of the carotid bifurcation is adopted to have a 3D realistic geometry. The blood flow is considered to be laminar, incompressible, pulsatile, and non-Newtonian. Boundary conditions are applied using the three-element Windkessel equation.

RESULTS

Results are presented in terms of velocity, pressure, magnetic field flux density, wall shear stress, and streamlines. Also, the number of particles in each direction is presented for the four studied cases. The results show that using proper magnets configurations makes it possible to guide more particles to the desired branch (up to 4%) while preventing particles from entering the unwanted branch (up to 13%). By defining connectivity between oscillatory shear index (OSI) value and magnetic drug delivery efficacy, it becomes clear that places with lower OSI values are more proper to place the magnets than areas with higher OSI values.

CONCLUSIONS

It was observed that increasing the diameter of particles does not necessarily result in a higher drug delivery efficiency. The configuration of the magnets and the size of particles are the main affecting parameters that should be chosen precisely to meet the most efficient drug delivery performance. Magnetic drug targeting (MDT) is a promising method to improve the therapy efficiency for cardiovascular diseases (CVDs) and cancers. Fundamentally, it's vital to steer the superparamagnetic iron oxide nanoparticles (SPIONs) to the target lesion location to increase the capture efficiency. Hence, the present study aims to enhance the drug delivery to the desired branch in a 3D carotid bifurcation. Besides, it is tried to decrement the particles' entry to the unwanted outlet by using four different magnet configurations implanted adjacent to the artery wall. The Eulerian-Lagrangian approach with one-way coupling is employed for numerical simulation of the problem using the finite element method (FEM). The dominant forces acting on particles are drag and magnetophoretic. The blood flow is laminar, incompressible, pulsatile, and non-Newtonian. The results show that it is possible to guide more particles to the desired branch (up to 4%) while preventing particles from entering the unwanted branch (up to 13%). By defining connectivity between oscillatory shear index (OSI) value and magnetic drug delivery efficacy, it becomes clear that places with lower OSI values are more proper to place the magnets than areas with higher OSI values.

Studies on Aggregated Nanoparticles Steering during Deep Brain Membrane Crossing

Many central nervous system (CNS) diseases, such as Alzheimer's disease (AD), affect the deep brain region, which hinders their effective treatment. The hippocampus, a deep brain area critical for learning and memory, is especially vulnerable to damage during early stages of AD. Magnetic drug targeting has shown high potential in delivering drugs to a targeted disease site effectively by applying a strong electromagnetic force. This study illustrates a nanotechnology-based scheme for delivering magnetic nanoparticles (MNP) to the deep brain region. First, we developed a mathematical model and a molecular dynamic simulation to analyze membrane crossing, and to study the effects of particle size, aggregation, and crossing velocities. Then, using in vitro experiments, we studied effective parameters in aggregation. We have also studied the process and environmental parameters. We have demonstrated that aggregation size can be controlled when particles are subjected to external electromagnetic fields. Our simulations and experimental studies can be used for capturing MNPs in brain, the transport of particles across the intact BBB and deep region targeting. These results are in line with previous in vivo studies and establish an effective strategy for deep brain region targeting with drug loaded MNPs through the application of an external electromagnetic field.

Navigation of Microrobots by MRI: Impact of Gravitational, Friction and Thrust Forces on Steering Success

INTRODUCTION

Magnetic resonance navigation (MRN) uses MRI gradients to steer magnetic drug-eluting beads (MDEBs) across vascular bifurcations. We aim to experimentally verify our theoretical forces balance model (gravitational, thrust, friction, buoyant and gradient steering forces) to improve the MRN targeted success rate.

METHOD

A single-bifurcation phantom (3 mm inner diameter) made of poly-vinyl alcohol was connected to a cardiac pump at 0.8 mL/s, 60 beats/minutes with a glycerol solution to reproduce the viscosity of blood. MDEB aggregates (25 ± 6 particles, 200 [Formula: see text]) were released into the main branch through a 5F catheter. The phantom was tilted horizontally from - 10° to +25° to evaluate the MRN performance.

RESULTS

The gravitational force was equivalent to 71.85 mT/m in a 3T MRI. The gradient duration and amplitude had a power relationship (amplitude=78.717 [Formula: see text]). It was possible, in 15° elevated vascular branches, to steer 87% of injected aggregates if two MRI gradients are simultaneously activated ([Formula: see text] = +26.5 mT/m, [Formula: see text]= +18 mT/m for 57% duty cycle), the flow velocity was minimized to 8 cm/s and a residual pulsatile flow to minimize the force of friction.

CONCLUSION

Our experimental model can determine the maximum elevation angle MRN can perform in a single-bifurcation phantom simulating in vivo conditions.

A Feasibility Study of In Vivo Control and Tracking of Microrobot Using Taxicab Geometry for Direct Drug Targeting

In vivo direct drug targeting aims at delivering drug molecules loaded on microrobots to the diseased site using the shortest possible physiological routes, which potentially improves targeting efficiency and reduces systemic toxicity. It is thus essential to consider realistic in-body limitations for direct drug targeting applications. Here, we present a novel controller for microrobot maneuver by considering four key in vivo constraints: non-Euclidean structure of capillaries, irreversibility of blood flow, invisibility of microvasculature, and inaccuracy of microrobot tracking. We use the taxicab geometry of capillaries as the a priori knowledge for steering and tracking a microrobot in lattice-like vessels. Furthermore, we introduce a minimax repulsive boundary function to prevent the microrobot from getting too close to the boundaries imposed by the direction of blood flow. We also propose a novel Kalman filtering algorithm to reduce tracking error, while avoiding possible obstacles such as vessel walls without knowing their actual locations. The proposed control method consists of four modules, namely a model predictive control module for tumor targeting, a Kalman filtering module for microrobot tracking, a blind obstacle detection module, and a vessel structure estimation module. The interplay of these four modules offers successful maneuver and tracking of the microrobot while avoiding obstacles in a blind manner by utilizing the taxicab geometry of blood vessels. We present a comprehensive in silico simulation study to verify our designed controller.

An Optimized Method for 3D Magnetic Navigation of Nanoparticles inside Human Arteries

A computational method for optimum magnetic navigation of nanoparticles that are coated with anticancer drug inside the human vascular system is presented in this study. For this reason a 3D carotid model is employed. The present model use Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) techniques along with Covariance Matrix Adaptation (CMA) evolution strategy for the evaluation of the optimal values of the gradient magnetic field. Under the influence of the blood flow the model evaluates the effect of different values of the gradient magnetic field in order to minimize the distance of particles from a pre-described desired trajectory. Results indicate that the diameter of particles is a crucial parameter for an effective magnetic navigation. The present numerical model can navigate nanoparticles with diameter above 500 nm with an efficiency of approximately 99%. It is found that the velocity of the blood seems to play insignificant role in the navigation process. A reduction of 25% in the inlet velocity leads the particles only 3% closer to the desired trajectory. Finally, the computational method is more efficient as the diameter of the vascular system is minimized because of the weak convective flow. Under a reduction of 50% in the diameter of the carotid artery the computational method navigate the particles approximately 75% closer to the desired trajectory. The present numerical model can be used as a tool for the determination of the parameters that mostly affect the magnetic navigation method.