Thrombus Removal with Magnetically Actuated Micro-Transformers

Abstract

Thrombotic disorders rank among the principal global mortality factors. Despite significant advancements in interventional therapy technologies, conventional medical robots remain constrained by rigid architectures and elevated invasiveness, inducing vascular wall stress and frictional injury. Furthermore, these systems face challenges in reconciling the flexibility necessary for untethered navigation with reliable vascular traversal. Conversely, untethered microrobots are generally limited by suboptimal thrombus clearance efficacy. To overcome these limitations, the development of a hybrid microrobot merging the benefits of interventional and untethered systems is critically needed. Here, we present a magnetically actuated microrobot with in vivo structural reconfigurability. The microrobot, constructed from SMP, leverages the magnetothermal effect of Fe3O4 magnetic nanoparticles induced by AMF. This induces temperature increase within the microrobot. When the temperature surpasses the glass transition temperature (50°C) of the SMP, the robot's structure transitions from its initial rod-like form to a final helical shape. In its initial state, the microrobot has a rod-shaped structure. Driven by magnetic field gradients, it demonstrates excellent mobility and flexibility within complex vascular environments. In its final state, the microrobot adopts a helical structure with enhanced mechanical rigidity. This configuration enables it to generate rotary motion when driven by a rotating magnetic field, effectively fragmenting and removing vascular blockages. Experimental results confirm that this reconfigurable microrobot successfully combines high mobility, flexibility, and strong mechanical fragmentation capabilities. It significantly reduces the risk of vascular wall injury and enhances the efficiency and safety of thrombus removal, offering an innovative solution for thrombus treatment.

Keywords: Magnetic microrobot, magnetothermal effect, shape memory, structure transformation