Objective To define thresholds of safe local temperature increases for MR equipment that exposes patients to radiofrequency fields of high intensities for long duration. These MR systems induce heterogeneous energy absorption patterns inside the body and can create localised hotspots with a risk of overheating. Methods The MRI + EUREKA research consortium organised a “Thermal Workshop on RF Hotspots”. The available literature on thresholds for thermal damage and the validity of the thermal dose (TD) model were discussed. Results/Conclusions The following global TD threshold guidelines for safe use of MR are proposed: All persons: maximum local temperature of any tissue limited to 39 °CPersons with compromised thermoregulation AND Uncontrolled conditions: maximum local temperature limited to 39 °CControlled conditions: TD<2 CEM43°CPersons with uncompromised thermoregulation AND Uncontrolled conditions: TD<2 CEM43°CControlled conditions: TD<9 CEM43°C The following definitions are applied: Controlled conditions A medical doctor or a dedicated trained person can respond instantly to heat-induced physiological stress Compromised thermoregulation All persons with impaired systemic or reduced local thermoregulation

The results are found to be consistent with the history of safe use in MR scanning, but not with current safety guidelines. For future safety concepts, we suggest to use thermal dose models instead of temperatures or SAR. Special safety concerns for patients with impaired thermoregulation (e.g., the elderly, diabetics) should be addressed.

We present unequally spaced linear array synthesis with sidelobe suppression under constraints to beamwidth and null control using a design technique based on a Comprehensive Learning Particle Swarm Optimizer (CLPSO). CLPSO utilizes a new learning strategy that achieves the goal to accelerate the convergence of the classical PSO. Numerical examples are compared to the existing array designs in the literature and to those found by the other evolutionary algorithms. The synthesis examples that are presented show that the CLPSO algorithm outperforms the common PSO algorithms and a real-coded genetic algorithm (GA).Index Terms-Array synthesis, comprehensive learning particle swarm optimizer (CLPSO), genetic algorithms (GAs), linear array design, null control, particle swarm optimization (PSO), sidelobe suppression.

In this work, we present the arrangement of Fe3O4 magnetic nanoparticles into 3D linear chains and its effect on magnetic particle hyperthermia efficiency. The alignment has been performed under a 40 mT magnetic field in an agarose gel matrix. Two different sizes of magnetite nanoparticles, 10 and 40 nm, have been examined, exhibiting room temperature superparamagnetic and ferromagnetic behavior, in terms of DC magnetic field, respectively. The chain formation is experimentally visualized by scanning electron microscopy images. A molecular Dynamics anisotropic diffusion model that outlines the role of intrinsic particle properties and inter-particle distances on dipolar interactions has been used to simulate the chain formation process. The anisotropic character of the aligned samples is also reflected to ferromagnetic resonance and static magnetometry measurements. Compared to the non-aligned samples, magnetically aligned ones present enhanced heating efficiency increasing specific loss power value by a factor of two. Dipolar interactions are responsible for the chain formation of controllable density and thickness inducing shape anisotropy, which in turn enhances magnetic particle hyperthermia efficiency.

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