Endovascular navigation of a ferromagnetic microrobot using MRI-based predictive control

Abstract

Abstract-This paper presents real-time MRI-based control of a ferromagnetic microcapsule for endovascular navigation. The concept was studied for future development of microdevices designed to perform minimally invasive interventions in remote sites accessible through the human cardiovascular system. A system software architecture is presented illustrating the different software modules to allow 3D navigation of a microdevice in blood vessels, namely: (i) vessel path planner, (ii) magnetic gradient steering, (iii) tracking and (iv) closed-loop navigation control. First, the position recognition of the microrobot into the blood vessel is extracted using Frangi vesselness filtering from the pre-operation images (3D MRI imaging). Then, a set of minimal trajectory is predefined, using Fast Marching Method (FMM), to guide the microrobot from the injection point to the tumor area through the anarchic vessel network. Based on the pre-computed path, a Generalized Predictive Controller (GPC) is proposed for robust time-multiplexed navigation along a 2D path in presence of pulsative flow. The simulation results suggest the validation of the proposed image processing and control algorithms. A series of disturbances introduced in the presence and absence of closed-loop control affirms the robustness and effectiveness of this predictive control system.

Navigation of a rolling microrobot in cluttered environments for automated crystal harvesting

“…The first is in [14], where an optimal path was generated to limit the control effort required to move a microrobot through pulsing blood flow. In [15], the fast marching method (FMM) was used to solve the path planning problem between a start and end position in a blood vessel.…”

Simulation and Planning of a Magnetically Actuated Microrobot Navigating in the Arteries

“…The FMM provides a continuous solution to the minimum path problem by employing upwind differences and a causality condition [16]. The key issue of the FMM is then to get an appropriate metric w(x) which drives the front expansion efficiently to find a geodesic P. In previous works [17,18], we have proposed to design such a metric on spatial consideration:…”

“…This approach then allows to find the vessel centerline geodesic P c , as the considered vesselness filter gives their maximal response in the vessel center. We have applied this procedure to different sets of data, in 2D [17] as well as in 3D [18]. As mentioned previously the contact, electrostatic and van der Waals microforces are negligible when the microrobot navigates close to the centerline P c (cf.…”

“…The proposed framework is based on the Fast Marching Method (FMM) [16]. In our previous work [17,18], the classical FMM with isotropic cost function has been proposed to extract the vessel centerline path. This first solution is suitable mainly to navigate far away from the vessel wall.…”

Control of a magnetic microrobot navigating in microfluidic arterial bifurcations through pulsatile and viscous flow

“…4. This CARIMA system model is obtained from the state-space representation defined in (4) [19]. The proposed GPC is then obtained by minimizing the following criterion:…”