Development of a new generation of high-resolution anatomical models for medical device evaluation: the Virtual Population 3.0.

The Virtual Family computational whole-body anatomical human models were originally developed for electromagnetic (EM) exposure evaluations, in particular to study how absorption of radiofrequency radiation from external sources depends on anatomy. However, the models immediately garnered much broader interest and are now applied by over 300 research groups, many from medical applications research fields. In a first step, the Virtual Family was expanded to the Virtual Population to provide considerably broader population coverage with the inclusion of models of both sexes ranging in age from 5 to 84 years old. Although these models have proven to be invaluable for EM dosimetry, it became evident that significantly enhanced models are needed for reliable effectiveness and safety evaluations of diagnostic and therapeutic applications, including medical implants safety. This paper describes the research and development performed to obtain anatomical models that meet the requirements necessary for medical implant safety assessment applications. These include implementation of quality control procedures, re-segmentation at higher resolution, more-consistent tissue assignments, enhanced surface processing and numerous anatomical refinements. Several tools were developed to enhance the functionality of the models, including discretization tools, posing tools to expand the posture space covered, and multiple morphing tools, e.g., to develop pathological models or variations of existing ones. A comprehensive tissue properties database was compiled to complement the library of models. The results are a set of anatomically independent, accurate, and detailed models with smooth, yet feature-rich and topologically conforming surfaces. The models are therefore suited for the creation of unstructured meshes, and the possible applications of the models are extended to a wider range of solvers and physics. The impact of these improvements is shown for the MRI exposure of an adult woman with an orthopedic spinal implant. Future developments include the functionalization of the models for specific physical and physiological modeling tasks.

Estimation of head tissue-specific exposure from mobile phones based on measurements in the homogeneous SAM head.

The maximum spatial peak exposure of each commercial mobile phone determined in compliance with the relevant safety and product standards is publicly available. However, this information is not sufficient for epidemiological studies aiming to correlate the use of mobile phones with specific cancers or to behavioral alterations, as the dominant location of the exposure may be anywhere in the head between the chin to above the ear, depending on the phone design. The objective of this study was to develop a methodology to determine tissue-specific exposure by expanding the post-processing of the measured surface or volume scans using standardized compliance testing equipment, that is, specific absorption rate (SAR) scanners. The transformation matrix was developed using the results from generic dipoles to evaluate the relation between the SAR in many brain regions of the Virtual Family anatomical phantoms and in virtual brain regions mapped onto the homogeneous SAM head. A set of transformation factors was derived to correlate the SAR induced in the SAM head to the SAR in the anatomical heads. The evaluation included the uncertainty associated with each factor, arising from the anatomical differences between the phantoms (typically less than 6 dB (4×)). The applicability of these factors was validated by performing simulations of four head models exposed to four realistic mobile phone models. The new methodology enables the reliable determination of the maximum and averaged exposure of specific tissues and functional brain regions to mobile phones when combined with mobile phone power control data, and therefore greatly strengthens epidemiological evaluations and improves information for the consumer.