David Folio

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

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 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. Then, a set of minimal trajectory is predefined, using 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 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.

Three-Dimensional Controlled Motion of a Microrobot using Magnetic Gradients

This paper presents the endovascular navigation of a ferromagnetic microdevice using magnetic resonance imaging (MRI)-based predictive control. The concept was studied for the future development of microrobots 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 three-dimensional (3-D) navigation of a microdevice in blood vessels, namely: (i) vessel path extraction, (ii) magnetic gradient steering, (iii) tracking and (iv) closed-loop navigation control. First, the navigation path of the microrobot into the blood vessel is extracted using the Fast Marching Method from the pre-operation images (3-D MRI imaging) to guide the microrobot from the injection point to the tumor area through the anarchic vessel network. Based on the pre-computed path, a Model Predictive Controller is proposed for robust time-multiplexed navigation along a 3-D path in the presence of pulsative flow. The simulation results suggest the validation of the proposed image processing and control algorithms.

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

This paper presents a preoperative microrobotic surgical simulation and planning application. The main contribution is to support computer-aided minimally invasive surgery (MIS) procedure using untethered microrobots that have to navigate within the arterial networks. We first propose a fast interactive application (with endovascular tissues) able to simulate the blood flow and microrobot interaction. Second, we also propose a microrobotic surgical planning framework, based on the anisotropic fast marching method (FMM), that provides a feasible pathway robust to biomedical navigation constraints. We demonstrate the framework performance in a case study of the treatment of peripheral arterial diseases.

MRI-based Microrobotic system for the Propulsion and Navigation of Ferromagnetic Microcapsules

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 3-D 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 (3-D MRI imaging). Then, a set of minimal trajectories is predefined, using path-planning algorithms, 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 two-dimensional (2D) path in presence of pulsative flow.

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

Navigating in bodily fluids to perform targeted diagnosis and therapy has recently raised the problem of robust control of magnetic microrobots under real endovascular conditions. Various control approaches have been proposed in the literature but few of them have been experimentally validated. In this paper, we point out the problem of navigation controllability of magnetic microrobots in high viscous fluids and under pulsatile flow for endovascular applications. We consider the experimental navigation along a desired trajectory, in a simplified millimeter-sized arterial bifurcation, operating in fluids at the low-Reynolds-number regime where viscous drag significantly dominates over inertia. Different viscosity environments are tested under a systolic pulsatile flow compatible with heart beating. The control performances in terms tracking, robustness and stability are then experimentally demonstrated.

Optimal structure of particles-based superparamagnetic microrobots: application to MRI guided targeted drug therapy

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 free-stream 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 confirm the feasibility of the steering of these TMMCs in hepatic artery microchannel phantom.

Robotized Tele-Echography: An Assisting Visibility Tool to Support Expert Diagnostic

This paper presents a robotized tele-echography system with an assisting visibility mode that helps the medical expert diagnosis. This autonomous mode is based on a multitask control approach that maintains the visibility of an anatomic element of interest while the medical expert teleoperates a 2-D ultrasound (US) probe held by a 4-degrees-of-freedom (DOF) robot. The main task is used to automatically maintain several visual constraints that guarantee an intersection between the US image plane and the organ of interest (OI). A secondary task allows the medical expert to manually apply the probe motion through the teleoperation mode. The main advantage of this approach is to give to the clinician the control of all the DOFs of the probe to examine the patient while automatically preserving the visibility of the OI when required. Experimental results, performed on a phantom and a human abdomen, demonstrate the efficiency of the visibility assistance task.

Dealing With Visual Features Loss During a Vision-Based Task For a Mobile Robot

In this article, we address the problem of computing the image features when they become temporarily unavailable during a vision-based navigation task. The method consists in analytically integrating the relation between the visual features motion in the image and the camera motion. Then, we use this approach to design sensor-based control laws that are able to tolerate the complete loss of the visual data during a vision-based navigation task in an unknown environment. Simulation and experimentation results demonstrate the validity and the interest of our method.

MRI magnetic signature imaging, tracking and navigation for targeted micro/nano-capsule therapeutics

The propulsion of nano-ferromagnetic objects by means of MRI gradients is a promising approach to enable new forms of therapy. In this work, necessary techniques are presented to make this approach work. This includes path planning algorithms working on MRI data, ferromagnetic artifact imaging and a tracking algorithm which delivers position feedback for the microdevice and a propulsion sequence to enable interleaved magnetic propulsion and imaging. Using a dedicated software environment integrating path-planning methods and real-time tracking, a clinical MRI system is adapted to provide this new functionality for potential controlled interventional targeted therapeutic applications. Through MRI-based sensing analysis, this paper aims to propose a framework to plan a robust pathway to enhance the navigation ability to reach deep locations in human body. The proposed approaches are validated with different experiments.

3D MRI-based predictive control of a ferromagnetic microrobot navigating in blood vessels

This paper presents an endovascular navigation of a ferromagnetic microdevice using a MRI-based predictive control. The concept was studied for future development of microrobot 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 extraction, (ii) magnetic gradient steering, (iii) tracking and (iv) closed-loop navigation control. First, the navigation path of the microrobot into the blood vessel is extracted using Fast Marching Method (FMM) from the pre-operation images (3D MRI imaging) to guide the microrobot from the injection point to the tumor area through the anarchic vessel network. Based on the pre-computed path, a Model Predictive Controller (MPC) is proposed for robust navigation along a 3D path. The simulation results suggest the validation of the proposed image processing and control algorithms.