The propulsion of 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 ferromagnetic objects, 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 controlled interventional targeted therapeutic applications. Through MRI-based sensing analysis, this article aims to propose a framework to plan a robust pathway to enhance the navigation ability to reach deep locations in the human body. The proposed approaches are validated with different experiments.

We report the partial core-shell nanowire motors. These nanowires are fabricated using our previously developed electrodeposition-based technique, and their catalytic locomotion in the presence of H2O2 is investigated. Unlike conventional bimetallic nanowires that are selfelectroosmotically propelled, our Au/Ru core-shell nanowires show both a noticeable decrease in rotational diffusivity and increase in motor speed with nanowire length. Numerical modelling based on self-electroosmosis attributes the decreases in rotational diffusivity to the formation of toroidal vortices at the nanowire tail, but fails to explain the speed increase with length. To reconcile this inconsistency, we propose a combined mechanism of self-diffusiophoresis and

This paper presents an endovascular navigation of a ferromagnetic microdevice using 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 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 is proposed for robust time-multiplexed navigation along a 3D path in presence of pulsative flow.The simulation results suggest the validation of the proposed image processing and control algorithms.

This paper introduces a two-dimensional autonomous navigation strategy of a 750 µm steel microrobot along a complex fluidic vascular network inside the bore of a clinical 3.0 T magnetic resonance imaging (MRI) scanner. To ensure successful magnetic resonance navigation (MRN) of a microrobot along consecutive channels, the design of autonoumous navigation strategy is needed taking into account the major MRI technological constraints and physiological perturbations, e.g. non-negligible pulsatile flow, limitations on the magnetic gradient amplitude, MRI overheating, susceptibility artifacts uncertainties, and so on. An optimal navigation planning framework based on Pareto optimality is proposed in order to deal with this multiple-objective problem. Based on these optimal conditions, a dedicated control architecture has been implemented in an interventional medical platform for real-time propulsion, control and imaging experiments. The reported experiments suggest that the likelihood of controlling autonomously untethered 750 µm magnetic microrobots is rendered possible in a complex twodimensional centimeter-sized vascular phantom. The magnetic microrobot traveled intricate paths at a mean velocity of about 4 mm s −1 with average tracking errors below 800 µm with limited magnetic gradients ±15 mT m −1 compatible with clinical MRI scanners. The experiments demonstrate that it is effectively possible to autonomously guide a magnetic microrobot using a conventional MRI scanner with only a software upgrade.

Abstract-This work 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. Secondly, 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 (PAD).Index Terms-Microrobotics, minimally invasive surgery, blood flow simulation, anisotropic path planning.

Background: A major consequence of malnutrition in cystic fibrosis (CF) patients is the loss of lean body mass (LBM) and the subsequent impairment of respiratory muscle function. Aim: To determine whether insulin-like growth factor I (IGF-I) could be related to the LBM depletion and the evolution of respiratory disease in CF patients. Methods: LBM was evaluated by dual energy x ray absorptiometry; serum concentrations of IGF-I were measured in 24 CF patients twice with a one year interval. Both values were expressed as SD score (SDS) calculated from normal data for age, sex, and pubertal stage and analysed with respect to anthropometric evaluation and disease related conditions. Results: At the initial evaluation, IGF-I SDS had a mean value of 20.98 (range 23.6 to 3.2) and correlated with weight for age index, LBM SDS, and lung disease related conditions. Multiple regression analysis showed that only LBM remained independently related to IGF-I, suggesting that the relation of IGF-I to LBM was independent of weight and that the correlation between IGF-I and the respiratory conditions was related to the level of LBM. IGF-I SDS at the first evaluation was lower for the patients who lost >5% of weight for age index or >1 SD of LBM between the two evaluations. Conclusion: Low levels of IGF-I could be crucial for clinical outcome by impairing LBM and respiratory function. IGF-I could be a tool for nutritional evaluation by identifying the CF patients at risk of LBM depletion.

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This paper presents a sensor-based controller allowing to visually drive a mobile robot towards a target while avoiding visual features occlusions and obstacle collisions. We consider the model of a cart-like robot equipped with proximetric sensors and a camera mounted on a pan-platform. The proposed method relies on the continuous switch between three controllers realizing respectively the nominal visionbased task, the obstacle bypassing and the occlusion avoidance. Simulation results are given at the end of the paper.