During an MRI scan, the radiofrequency field from the scanner's transmit coil, but also the switched gradient fields, induce currents in any conductive object in the bore. This makes any metallic medical implant an additional risk for an MRI patient, because those currents can heat up the surrounding tissues to dangerous levels. This is one of the reasons why implants are, until today, considered a contraindication for MRI; for example, by scanner manufacturers. Due to the increasing prevalence of medical implants in our aging societies, such general exclusion is no longer acceptable. Also, it should be no longer needed, because of a much‐improved safety‐assessment methodology, in particular in the field of numerical simulations. The present article reviews existing literature on implant‐related heating effects in MRI. Concepts for risk assessment and quantification are presented and also some first attempts towards an active safety management and risk mitigation. Level of Evidence 5 Technical Efficacy Stage 5

This work focuses on the in silico evaluation of the energy deposed by MRI switched gradient fields in bulk metallic implants and the consequent temperature increase in the surrounding tissues. An original computational strategy, based on the subdivision of the gradient coil switching sequences into sub-signals and on the time-harmonic electromagnetic field solution, allows to realistically simulate the evolution of the phenomena produced by the gradient coils fed according to any MRI sequence. Then, Pennes’ bioheat equation is solved through a Douglas–Gunn time split scheme to compute the time-dependent temperature increase. The procedure is validated by comparison with laboratory results, using a component of a realistic hip implant embedded within a phantom, obtaining an agreement on the temperature increase better than 5%, lower than the overall measurement uncertainty. The heating generated inside the body of a patient with a unilateral hip implant when undergoing an Echo-Planar Imaging (EPI) MRI sequence is evaluated and the role of the parameters affecting the thermal results (body position, coil performing the frequency encoding, effects of thermoregulation) is discussed. The results show that the gradient coils can generate local increases of temperature up to some kelvin when acting without radiofrequency excitation. Hence, their contribution in general should not be disregarded when evaluating patients’ safety.

Contrast source inversion electric properties tomography (CSI-EPT) is a recently developed technique for the electric properties tomography that recovers the electric properties distribution starting from measurements performed by magnetic resonance imaging scanners. This method is an optimal control approach based on the contrast source inversion technique, which distinguishes itself from other electric properties tomography techniques for its capability to recover also the local specific absorption rate distribution, essential for online dosimetry. Up to now, CSI-EPT has only been described in terms of integral equations, limiting its applicability to homogeneous unbounded background. In order to extend the method to the presence of a shield in the domain-as in the recurring case of shielded radio frequency coils-a more general formulation of CSI-EPT, based on a functional viewpoint, is introduced here. Two different implementations of CSI-EPT are proposed for a 2-D transverse magnetic model problem, one dealing with an unbounded domain and one considering the presence of a perfectly conductive shield. The two implementations are applied on the same virtual measurements obtained by numerically simulating a shielded radio frequency coil. The results are compared in terms of both electric properties recovery and local specific absorption rate estimate, in order to investigate the requirement of an accurate modeling of the underlying physical problem.

This work aims at investigating the exposure experienced by the nursing staff executing transcranial magnetic stimulations (TMS) and proposing a shielding system composed of an aluminum half cylinder placed around the coil. The analysis is carried out through a finite element approach, using the Duke (Virtual Family) anatomical model to represent the operator body. The TMS apparatus, a spiral circular coil supplied by a short duration sinusoidal current of  6 kA, has been analyzed with and without shield. Sixty relative positions of the coil with respect to the TMS operator body have been considered, involving distance, orientation angle and vertical height. The results show that the operator exposure exceeds the basic restrictions, suggested by the Guidelines of the International Commission On Non-Ionizing Radiation Protection, when the distance from the coil decreases below 64 cm, but the minimal distance is reduced to 38 cm by the conductive shield. Moreover, the staff exposure reduces when the coil overlooks the operator head, while it worsens as the position of the coil descends at the height of shoulders and chest.

In this article, we discuss numerical aspects related to the accuracy and the computational efficiency of numerical dosimetric simulations, performed in the context of human exposure to static inductive charging systems of electric vehicles. Two alternative numerical methods based on electric vector potential and electric scalar potential formulations, respectively, are here considered for the electric field computation in highly detailed anatomical human models. The results obtained by the numerical implementation of both approaches are discussed in terms of compliance assessment with ICNIRP guidelines limits for human exposure to electromagnetic fields. In particular, different strategies for smoothing localized unphysical outliers are compared, including novel techniques based on statistical considerations. The outlier removal is particularly relevant when comparison with basic restrictions is required to define the safety of electromagnetic fields exposure. The analysis demonstrates that it is not possible to derive general conclusions about the most robust method for dosimetric solutions. Nevertheless, the combined use of both formulations, together with the use of an algorithm for outliers removal based on a statistical approach, allows to determine final results to be compared with reference limits with a significant level of reliability.