SAR distribution in human beings when using body-worn RF transmitters

This study analyzes the exposure of the human torso to electromagnetic fields caused by wireless body-mounted or handheld devices. Because of the frequency and distance ranges from 30-5800 MHz and 10 to 200 mm, respectively, both near-field and far-field effects are considered. A generic body model and simulations of anatomical models are used to evaluate the worst case tissue composition with respect to the absorption of electromagnetic energy. Both standing wave effects and enhanced coupling of reactive near-field components can lead to a specific absorption rate (SAR) increase in comparison to homogeneous tissue. In addition, the exposure and temperature increase of different inner organs is assessed. With respect to compliance testing, the observed SAR enhancement may require the introduction of a multiplication factor for the spatial peak SAR measured in the liquid-filled phantom in order to obtain a conservative exposure assessment. The observed tissue heating at the body surface under adiabatic conditions can be significant, whereas the temperature increase in the inner organs turned out to be negligible for the cases investigate

Functionalized Anatomical Models for Computational Life Sciences

The advent of detailed computational anatomical models has opened new avenues for computational life sciences (CLS). To date, static models representing the anatomical environment have been used in many applications but are insufficient when the dynamics of the body prevents separation of anatomical geometrical variability from physics and physiology. Obvious examples include the assessment of thermal risks in magnetic resonance imaging and planning for radiofrequency and acoustic cancer treatment, where posture and physiology-related changes in shape (e.g., breathing) or tissue behavior (e.g., thermoregulation) affect the impact. Advanced functionalized anatomical models can overcome these limitations and dramatically broaden the applicability of CLS in basic research, the development of novel devices/therapies, and the assessment of their safety and efficacy. Various forms of functionalization are discussed in this paper: (i) shape parametrization (e.g., heartbeat, population variability), (ii) physical property distributions (e.g., image-based inhomogeneity), (iii) physiological dynamics (e.g., tissue and organ behavior), and (iv) integration of simulation/measurement data (e.g., exposure conditions, “validation evidence” supporting model tuning and validation). Although current model functionalization may only represent a small part of the physiology, it already facilitates the next level of realism by (i) driving consistency among anatomy and different functionalization layers and highlighting dependencies, (ii) enabling third-party use of validated functionalization layers as established simulation tools, and (iii) therefore facilitating their application as building blocks in network or multi-scale computational models. Integration in functionalized anatomical models thus leverages and potentiates the value of sub-models and simulation/measurement data toward ever-increasing simulation realism. In our o2S2PARC platform, we propose to expand the concept of functionalized anatomical models to establish an integration and sharing service for heterogeneous computational models, ranging from the molecular to the organ level. The objective of o2S2PARC is to integrate all models developed within the National Institutes of Health SPARC initiative in a unified anatomical and computational environment, to study the role of the peripheral nervous system in controlling organ physiology. The functionalization concept, as outlined for the o2S2PARC platform, could form the basis for many other application areas of CLS. The relationship to other ongoing initiatives, such as the Physiome Project, is also presented

ESHO benchmarks for computational modeling and optimization in hyperthermia therapy

Background: The success of cancer hyperthermia (HT) treatments is strongly dependent on the temperatures achieved in the tumor and healthy tissues as it correlates with treatment efficacy and safety, respectively. Hyperthermia treatment planning (HTP) simulations have become pivotal for treatment optimization due to the possibility for pretreatment planning, optimization and decision making, as well as real-time treatment guidance. Materials and methods: The same computational methods deployed in HTP are also used for in silico studies. These are of great relevance for the development of new HT devices and treatment approaches. To aid this work, 3 D patient models have been recently developed and made available for the HT community. Unfortunately, there is no consensus regarding tissue properties, simulation settings, and benchmark applicators, which significantly influence the clinical relevance of computational outcomes. Results and discussion: Herein, we propose a comprehensive set of applicator benchmarks, efficacy and safety optimization algorithms, simulation settings and clinical parameters, to establish benchmarks for method comparison and code verification, to provide guidance, and in view of the 2021 ESHO Grand Challenge (Details on the ESHO grand challenge on HTP will be provided at https://www.esho.info/). Conclusion: We aim to establish guidelines to promote standardization within the hyperthermia community such that novel approaches can quickly prove their benefit as quickly as possible in clinically relevant simulation scenarios. This paper is primarily focused on radiofrequency and microwave hyperthermia but, since 3 D simulation studies on heating with ultrasound are now a reality, guidance as well as a benchmark for ultrasound-based hyperthermia are also included

On the Use of Conformal Models and Methods in Dosimetry for Nonuniform Field Exposure

Numerical artifacts affect the reliability of computational dosimetry of human exposure to low-frequency electromagnetic fields. In the guidelines of the International Commission of Non-Ionizing Radiation Protection (ICNIRP), a reduction factor of 3 was considered to take into account numerical uncertainties when determining the limit values for human exposure. However, the rationale for this value is unsure. The IEEE International Committee on Electromagnetic Safety has published a research agenda to resolve numerical uncertainties in low-frequency dosimetry. For this purpose, intercomparison of results computed using different methods by different research groups is important. In previous intercomparison studies for low-frequency exposures, only a few computational methods were used, and the computational scenario was limited to a uniform magnetic field exposure. This study presents an application of various numerical techniques used: different Finite Element Method (FEM) schemes, Method of Moments (MoM) and Boundary Element Method (BEM) variants and finally by using a hybrid FEM/BEM approach. As a computational example, the induced electric field in the brain by the coil used in transcranial magnetic stimulation is investigated. Intercomparison of the computational results are presented qualitatively. Some remarks are given for the effectiveness and limitations of application of the various computational methods

Quantification of clinically applicable stimulation parameters for precision near-organ neuromodulation of human splenic nerves

Abstract: Neuromodulation is a new therapeutic pathway to treat inflammatory conditions by modulating the electrical signalling pattern of the autonomic connections to the spleen. However, targeting this sub-division of the nervous system presents specific challenges in translating nerve stimulation parameters. Firstly, autonomic nerves are typically embedded non-uniformly among visceral and connective tissues with complex interfacing requirements. Secondly, these nerves contain axons with populations of varying phenotypes leading to complexities for axon engagement and activation. Thirdly, clinical translational of methodologies attained using preclinical animal models are limited due to heterogeneity of the intra- and inter-species comparative anatomy and physiology. Here we demonstrate how this can be accomplished by the use of in silico modelling of target anatomy, and validation of these estimations through ex vivo human tissue electrophysiology studies. Neuroelectrical models are developed to address the challenges in translation of parameters, which provides strong input criteria for device design and dose selection prior to a first-in-human trial