Objective. Magnetic nanoparticle hyperthermia (MNH) emerges as a promising therapeutic strategy for cancer treatment, leveraging alternating magnetic fields (AMFs) to induce localized heating through magnetic nanoparticles. However, the interaction of AMFs with biological tissues leads to non-specific heating caused by eddy currents, triggering thermoregulatory responses and complex thermal gradients throughout the body of the patient. While previous studies have implemented the Atkinson–Brezovich limit to mitigate potential harm, recent research underscores discrepancies between this threshold and clinical outcomes, necessitating a re-evaluation of this safety limit. Therefore, in this study, through electromagnetic (EM) simulations, the complex interaction between AMFs and anatomical models was investigated. Approach. In particular, we considered a circular coil configuration placed at different positions along the craniocaudal axis of various anatomical human models. The excitation current was normalized, at different frequencies, to meet the basic restriction of local 10 g-averaged specific energy absorption rate (SAR) in the human models, as defined by the exposure guidelines of the International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the standard IEC 60601-2-33 of the International Electrotechnical Commission (IEC). Main results. The resulting permissible magnetic field strength values, for the reference levels set by the ICNIRP 2020 guidelines, emerged to be up to approximately 1.4 and 3 times less than that defined in the Atkinson–Brezovich limit. The widely used limit was found to align more closely with the first level of controlled operating mode defined in the IEC 60601-2-33 standard. Significance. The results indicate that the permissible magnetic field amplitude during MNH treatment should be much lower than that in the Atkinson–Brezovich limit. This study offers valuable insights into the role of computational simulations in advancing the potential to establish a reliable metric for safety evaluation and monitoring within the clinical framework of MNH.

The present study focuses on the development of a methodology for evaluating the safety of MNH systems, through the numerical prediction of the induced temperature rise in superficial skin layers due to eddy currents heating under an alternating magnetic field (AMF). The methodology is supported and validated through experimental measurements of the AMF’s distribution, as well as temperature data from the torsos of six patients who participated in a clinical trial study. The simulations involved a computational model of the actual coil, a computational model of the cooling system used for the cooling of the patients during treatment, and a detailed human anatomical model from the Virtual Population family. The numerical predictions exhibit strong agreement with the experimental measurements, and the deviations are below the estimated combined uncertainties, confirming the accuracy of computational modeling. This study highlights the crucial role of simulations for translational medicine and paves the way for personalized treatment planning.

Transcranial magnetic stimulation (TMS) in humans induces electric fields (E-fields, EF) that perturb and modulate the brain’s endogenous neuronal activity and result in the generation of TMS-evoked potentials (TEPs). The exact relation of the characteristics of the induced E-field and the intensity of the brains’ response, as measured by electroencephalography (EEG), is presently unclear. In this pilot study, conducted on three healthy subjects and two patients with generalized epilepsy (total: 3 males, 2 females, mean age of 26 years; healthy: 2 males, 1 female, mean age of 25.7 years; patients: 1 male, 1 female, mean age of 26.5 years), we investigated the temporal and spatial relations of the E-field, induced by single-pulse stimuli, and the brain’s response to TMS. Brain stimulation was performed with a deep TMS device (BrainsWay Ltd., Jerusalem, Israel) and an H7 coil placed over the central area. The induced EF was computed on personalized anatomical models of the subjects through magneto quasi-static simulations. We identified specific time instances and brain regions that exhibit high positive or negative associations of the E-field with brain activity. In addition, we identified significant correlations of the brain’s response intensity with the strength of the induced E-field and finally prove that TEPs are better correlated with E-field characteristics than with the stimulator’s output. These observations provide further insight in the relation between E-field and the ensuing cortical activation, validate in a clinically relevant manner the results of E-field modeling and reinforce the view that personalized approaches should be adopted in the field of non-invasive brain stimulation.

Patents are used as a reliable indicator for the study of technological evolution in specific fields. Patent citation networks can further enlighten the relation between individual classes of patents that are used to categorize innovation. The tightening or loosening of bonds between a pair of them can point to a changing landscape in either of the two, or in both. It does, however, clearly signal one or more changes. Thus, it is important to point out pairs of classes that undergo processes of this kind, and try to provide plausible explanations for them. We use patent citation data from the European Patent Office to create the time series of all IPC classes. We then examine all pairs of patent classes for correlations, and discuss those which show the greatest increase, or decrease, over time. We identify classes which show both a significant decrease in their correlation with one class and simultaneously an increase with another. We further proceed to check the cross correlations of all pairs in order to identify pairs which show a time lag in following one another. By implementing specific criteria for the selection of the most promising pairs we distinguish some cases which exhibit strong correlation values with time lags of several months (3–10), and for which we can provide a plausible explanation.