This paper presents an optimal design strategy for therapeutic magnetic micro carriers (TMMC) guided in real time by a magnetic resonance imaging (MRI) system. As aggregates of TMMCs must be formed to carry the most amount of drug and magnetic actuation capability, different clustering agglomerations could be arranged. Nevertheless, its difficult to predict the hydrodynamic behavior of any arbitrary-shaped object due to the nonlinear hydrodynamic effects. Indeed, the drag effect is related not only to the properties of the bolus but also to its interaction with the fluid viscosity, the freestream velocity and the container geometry. In this work, we propose a mathematical framework to optimize the TMMC aggregates to improve the steering efficiency in experimental endovascular conditions. The proposed analysis is carried out on various sizes and geometries of microcarrier: spherical, ellipsoid-like and chain-like of microsphere structures. We analyze the magnetophoretic behavior of such designs to exhibit the optimal configuration. Based on the optimal design of the boluses, experimental investigations were carried out in mm-sized fluidic artery phantoms to demonstrate the steerability of the magnetic bolus using a proof-of-concept setup. The experiments demonstrate the steerability of the magnetic bolus under different velocity, shear-stress and trajectory constraints with a laminar viscous fluidic environment. Preliminary experiments with a MRI system confirms the feasibility of the steering of these TMMCs in hepatic artery microchannel phantom.

To enhance locoregional therapies for liver cancer treatment, we propose in this study a mathematical model to optimize the transcatheter arterial delivery of therapeutical agents. To maximize the effect of the treatment and minimize adverse effects on the patient, different mathematical models of the tumor growth are considered in this study to find the optimal number of the therapeutic drug-loaded magnetic nanoparticles to be administered. Three types of therapy models are considered, e.g., angiogenesis inhibition therapy, chemotherapy and radiotherapy. We use state-dependent Riccati equations (SDRE) as an optimal control methodology framework to the Hahnfeldt's tumor growth formulation. Based on this, design optimal rules are derived for each therapy to reduce the growth of a tumor through the administration of appropriate dose of antiangiogenic, radio- and chemo-therapeutic agents. Simulation results demonstrate the validity of the proposed optimal delivery approach, leading to reduced intervention time, low drug administration rates and optimal targeted delivery.