Bioelectromagnetics 36:10^26 (2015)

Generation of Infant Anatomical Models for Evaluating Electromagnetic Field Exposures Congsheng Li,1,2 Zhiye Chen,3 Lei Yang,1 Bin Lv,1 Jianzhe Liu,1
geVarsier,4 Abdelhamid Hadjem,4 JoeWiart,4 Yi Xie,1 Lin Ma,3 Nade and TongningWu1* 1

China Academy of Telecommunication Research of Ministry of Industry and Information Technology, Beijing, China 2 College of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China 3 Department of Radiology, PLA General Hospital, Beijing, China 4 Orange Labs, Issy Les Moulineaux, France

Realistic anatomical modeling is essential in analyzing human exposure to electromagnetic fields. Infants have significant physical and anatomical differences compared with other age groups. However, few realistic infant models are available. In this work, we developed one 12-month-old male whole body model and one 17-month-old male head model from magnetic resonance images. The whole body and head models contained 28 and 30 tissues, respectively, at spatial resolution of 1 mm
1 mm
1 mm. Fewer identified tissues in the whole body model were a result of the low original image quality induced by the fast imaging sequence. The anatomical and physical parameters of the models were validated against findings in published literature (e.g., a maximum deviation as 18% in tissue mass was observed compared with the data from International Commission on Radiological Protection). Several typical exposure scenarios were realized for numerical simulation. Dosimetric comparison with various adult and child anatomical models was conducted. Significant differences in the physical and anatomical features between adult and child models demonstrated the importance of creating realistic infant models. Current safety guidelines for infant exposure to radiofrequency electromagnetic fields may not be conservative. Bioelectromagnetics 36:10–26, 2015. © 2014 Wiley Periodicals, Inc. Key words: segmentation; reconstruction; magnetic resonance; finite-difference time-domain; electromagnetic fields exposure

INTRODUCTION To protect against radiofrequency (RF) electromagnetic field (EMF) exposure, the International Commission on Non-Ionizing Radiation Protection (ICNIRP) published guidelines in 1998 for limiting excessive emission [ICNIRP, 1998]. Basic limits (e.g., specific absorption rate [SAR]) and reference levels (e.g., spatial power density) are used to evaluate RF EMF safety. Compliance with the reference levels is regarded as compliance with the basic limits. Measurement and numerical simulation are frequently used for compliance evaluation. Recent developments on computer technology have led to the adoption of high-resolution computational human models for evaluating EMF exposure. Most of the available human models, such as Visible Human [Ackerman, 1995], Norman [Dimbylow, 1995], Naomi [Dimbylow, 2005], Japanese adult models [Nagaoka et al., 2004], Korean adult models [Lee
2014 Wiley Periodicals, Inc.

et al., 2006; Kim et al., 2008], Glenn, Duke, and Ella from Virtual Family [Christ et al., 2010a], and Chinese adult male and female models [Wu et al., 2011], represent only adults. Several realistic child models, as

Grant sponsors: National Key Basic Research Project; grant number: 2011CB503705; National Natural Science Foundation of China; grant numbers: 61001159, 61201066, 61371187; French ANSES Project ACTE; grant number: 2012/2/044. Conflict of Interest: None. *Correspondence to: Tongning Wu, No. 52, Huayuanbei Road, Beijing 100191, China. E-mail: [email protected] Received for review 29 September 2013; Accepted 6 July 2014 DOI: 10.1002/bem.21868 Published online 18 October 2014 in Wiley Online Library (wileyonlinelibrary.com).

Infant Models for EMF Evaluation

well as some child-sized models scaled down from adults, have been developed and used in EMF calculations [Williams et al., 1986; Lee et al., 2009; Christ et al., 2010a]. However, these models generally represent children older than 5 years old. Few infant models (ages between several weeks and 2 years old) are available. These models include University of Florida (UF) hybrid non-uniform rational B-spline (NURBS) phantoms [Lee et al., 2007, 2010], software-generated baby models [Cassola et al., 2013], Japanese infant models [Hirata et al., 2008], and the baby model from the National Research Center for Environment and Health (GSF) voxel family in Germany [Petoussi-Henss et al., 2002]. Of these, the first two models use scaled tissues/organs from different individuals to form a reference model. The Japanese infant model is linearly scaled from a child-size model. Only the UF model is a realistic model of an 8-week-old female infant. As such, realistic infant models, during which the growth rate is the highest over the entire human lifespan (from several months to 2 years old) are lacking. Proportional [Nagaoka et al., 2008] or nonproportional [Wang and Fujiwara, 2003; Hadjem et al., 2005; Beard et al., 2006; Monebhurrun, 2010] scaling of adult models into an infant model is technically feasible. However, significant physical and anatomical differences exist between infants and adults. First, an infant has an unproportionally large head, short neck and tongue. Second, an infant’s immature hypothalamus reduces its temperature regulation capability. An infant also has thinner skin, and its brain mass experiences the most rapid increase during the first 2 years after birth [Huelke, 1998]. Thus, scaled models from adults or children cannot accurately be used to represent infants for evaluating EMF exposure. To address this issue, the French Agency for Food, Environmental, and Occupational Health and Safety (ANSES) launched a 3-year international research program to assess infant exposure to long-term evolution (LTE) EMF exposure (ACTE, Analyse et Caractérisation de l’exposition des Tr
es jeunes Enfants aux syst
emes de communication sans fil LTE, which is analysis and characterization for the very young infant’s exposure to the LTE wireless communication system, in English); this program requires the development of realistic infant numerical models. Epidemiological evidence has indicated the risk of extremely low-frequency (ELF) EMF exposure on childhood leukemia [National Cancer Institute, 2013]. At birth, all bone marrow is red [Ellis, 1961]; it gradually converts into yellow with age. Only about half of the adult bone marrow is red. Thus, investigat-

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ing the effect of EMF exposure on infants is of particular importance, especially when the central nervous system (CNS) undergoes rapid development. Generation of the realistic infant models can help elucidate whether the current EMF safety limits are conservative for the subjects of this age group in various exposure scenarios. These important scenarios include the exposure to the near field of the mobile phone [Monebhurrun, 2010], exposure during highintensity MRI scan [Jin et al., 2012], and the environmental exposures by various wireless communication signals [Bakker et al., 2010]. In this study, one whole body model and one head model were developed from the magnetic resonance (MR) images of the two 12- and 17-monthold male infants. The whole body model included 28 tissues, while the head model contained 30 tissues. Comparison of results with the published anatomical and physical data was performed to validate the developed models. Numerical simulation by the finitedifference time-domain (FDTD) [Taflove and Hagness, 2000] method was used to compute SAR in several typical RF EMF exposure scenarios, and the results were compared with adults and children. Dosimetric differences between the infant and adult models confirm the necessity of constructing realistic infant models. The correct anatomical data of the infant models were also validated via numerical evaluations. The models are free for non-commercial research with the permission of the corresponding author. The distributable models are available in the format as segmented images (.jpg, .bmp, .png, or .bmp) or as the three-dimensional (3D) binary array. MATERIALS AND METHODS Data Acquisition MR scans were performed on two male infants, one 12-month-old and the other 17-month-old; both infants had auditory abnormalities (ear canal stenosis). The abnormality might hinder its application in EMF evaluation for the external auditory canals. Procedural sedation was administered by the pediatric staff. The potential risks were discussed with the legal guardians of the infants prior to the scans. To prevent movement during the scans, the infants were strapped to the MR bed at waist level. A 3.0T scanner (GE Healthcare, Little Chalfont, UK) was used for T1-weighted image acquisition with a 3D fast spoiled gradient recalled echo sequence. Separate scans were performed on the 12-month-old male for imaging the upper and lower parts of the Bioelectromagnetics

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body. Combination of the different image datasets was performed at the chest level. Since the subject was strapped to the MR bed, the different image datasets could be aligned without further manipulation. A radiologist examined the surface continuity and organ integrity. The in-plane resolutions were 1.8715 mm
2.0 mm and 0.4688 mm
0.7 mm for the wholebody and head models, and the slice thicknesses were 1.8715 and 0.4688 mm, respectively. No slice interval was assumed in the scans. Segmentation Identified tissues and resolutions depend on the original image quality. To ensure infant safety and expedite the imaging process, we employed an efficient whole-body scan configuration at the cost of degraded image quality. As this configuration can obscure small tissues, we focused on segmenting major tissues and organs (in terms of volume), tissues featuring large dielectric variabilities with age [Peyman et al., 2009], CNS tissues, and other tissues with functional and physiological importance. Segmentation was performed on two-dimensional (2D) slices and 3D volumes. The interactive segmentation tool, iSeg (ZMT, Zurich, Switzerland), and in-house software [Wu et al., 2013a; Li et al., 2014] based on Insight Segmentation and Registration Toolkit (ITK) [Ibáñez et al., 2003] and Visualization Toolkit (VTK) [Schroeder et al., 2003] were used. Manual segmentation of the whole-body images with relatively low quality was performed by anatomical experts of the 12-month-old infant. This procedure is fairly common in terms of technology. Relevant details can be found in our previous report [Wu et al., 2011]. A segmentation example at the chest level is shown Figure 1.

The original T1 MR images of the 17-month-old head were corrected for bias fields and intensity nonuniformity using the N3 algorithm [Sled et al., 1998] and followed by image smoothing with an anisotropic filter. The 3D region growing method was applied to generate a head mask by eliminating the background noise. The resultant images were further processed for atlas-based segmentation by tissue registration. This work was conducted using two open-source software suites, FreeSurfer [Fischl, 2012] and Statistical Parametric Mapping (SPM) [Friston et al., 2006]. The scalp, white matter, gray matter, cerebrospinal fluid, and hippocampus can be identified from the images. Consequently, the partially segmented images were imported by iSeg and our in-house software for segmenting other tissues. The selected methods included thresholding with different values, morphological operation (e.g., filling holes, opening and closing operators, etc.), region growing, and the graph cut method [Chen et al., 2012]. Manual segmentation and expert inspection was performed before head model reconstruction. Figure 2 shows the segmentation process. For both the whole-body and head models, skin was invisible in the original images. A single skin layer (1 mm thickness) surrounding the models was artificially added. The thickness of the skin corresponded with the ultrasonic measurement results [Usher and McLean, 1969; Kil et al., 2007; Zhang et al., 2007]. We linearly interpolated and adjusted the voxel resolution to 1 mm
1 mm
1mm. The reconstructed models are shown in Figure 3. Simulation Configuration To demonstrate the application of the reconstructed models in RF EMF numerical calculations, three typical exposure scenarios were created. These simulations did not aim to cover all aspects of EMF exposure. Dosimetric studies with extensive exposure

Fig.1. Example of segmentation for the12-month-old infant whole-bodyimages at the chest level (a) theoriginalimageand (b) the correspondingsegmentedimage. Bioelectromagnetics

Infant Models for EMF Evaluation

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Fig. 2. Segmentation for the 17-month-old infant head images.The original T1 MR images of the 17-month-old head images (a) were corrected for bias fields and intensity non-uniformity (b). Smoothingoftheimageswith an anisotropic filterandapplicationofthe 3Dregiongrowingmethod to generate a head mask to eliminate background noise followed (c,d).The resultant images were further processed for atlas-based segmentation by tissue registration. The scalp, white matter, graymatter, cerebrospinalfluid, andhippocampuscan beidentified fromtheimages (e-g).Subsequently, thepartiallysegmentedimageswereimportedbyiSegandourin-house softwareforsegmentingother tissues (h).

configurations will be presented in subsequent manuscripts in the frame of the same project. The FDTD method was used to update the E and H fields in the human models under RF EMF exposure. The FDTD spatial lattice was as 1 mm
1 mm
1 mm for 20 MHz to 3 GHz corresponding to a time update step as 1.8 ps. Sinusoidal E field was applied to the transverse mode (TEM) plane-wave exposure scenario and sinusoidal voltage source was applied to the localized exposure scenarios. Eightlayer uniaxial perfectly matched layer (UPML) [Gedney, 1996] was used as an absorption boundary condition (ABC). We inserted 30 grid cells between the PML boundary and the models. The number of iterations varied from 2 periods (20 MHz) to 40 periods (3 GHz). Selection of the iteration time

corresponded to a propagation distance of at least two times the maximum diameter of the computational domain. To verify our results, the whole body averaged SAR (WBASAR) from the Thelonious and Billie models was validated against published data [Bakker et al., 2010]; a difference of less than 5% was observed for all the frequencies. In addition, one study [Bakker et al., 2010] also reported that even a drastic increase in the padding distance and the updating steps from our current configurations could insignificantly impact WBASAR (about 6%). However, the consequential computational domain will exceed the memory capacity of our simulation hardware. Frequency dependent dielectric parameters were obtained from Gabriel et al. [1996] and the tissue densities were imported from the database of IT’IS Bioelectromagnetics

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Fig. 3. Reconstructed infant models (a) the 12-month-old male infant whole body model and (b) the17-month-oldmaleinfant headmodel.

[Hasgall et al., 2013]. The database was based on the averaged values found in the published literatures. The simulations were realized by SEMCAD-X v14.8 (SPEAG, Zurich, Switzerland). The hardware configuration is as follows: two central processing units (CPU): Xeon X5677 (3.46 GHz); memory on board: 48 GB; and four graphic processing units (GPU): NVIDIA FX 5800 (16 GB memory in total). The field update speed may vary during the simulations, but a minimum speed of 500 MVoxels/s was maintained. The following scenarios were simulated. TEM plane-wave exposure. Frequency-dependent WBASAR was calculated for the TEM plan-wave Bioelectromagnetics

exposure scenario for human models. The E field polarization was parallel to the length of the anatomical model with propagation direction pointing to the face of the anatomical models. In total, seven models were used in the simulations: the whole-body 12month-old infant, Korean child, Billie and Thelonious (Virtual Family), standing Chinese male and female adults [Wu et al., 2013b,c], and a Chinese female adult proportionally downscaled to achieve the same height as the whole-body infant. In the simulations, the models were isolated from the ground. WBASAR was normalized to the plane-wave power density as prescribed by the reference levels from the ICNIRP guidelines.

Infant Models for EMF Evaluation

Dipole exposure. Infants can gain access to mobile terminals at a very young age. In this scenario, we simulated the near-field exposure of an infant’s head to the popular 3G and 4G wireless telecommunication bands of 2.1, 2.4, and 2.53 GHz. Five human models were used in the simulations: the 12-month-old infant, the 17-month-old infant, Thelonious, Billie, and the Chinese male. Half-wavelength dipoles were used in the simulations. The dipole length was parallel to the length of the head, and the dipole gap aligned to the entrance of the ear canal. The distance between the head and the top of the dipole was 3.5 cm. This setup could ensure an identical distance from the dipole to the head for all the models while preventing the result variability induced by the compressed pinna (a minimum separation of 1 cm was kept between the dipole and the pinna for all the simulated models). PC tablet in front of the eye. Infants can also be exposed to EMF via smartphones or PC tablets in data-transfer mode. A PC tablet with tri-frequency antenna was numerically modeled, and the antenna prototype was obtained from the SEMCAD-X v14.8 user manual [SPEAG, 2013]. Optimization for the antenna adaptation was performed. Figure 4 shows the schematic diagram of the PC tablet and the simulated S11 parameters (S11 describes the reflection from the input port when the output port was terminated). In the simulation, five head models were involved: the 12-month-old infant, the 17-month-old infant, Thelonious, Billie, and a Chinese male. The

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center of the PC tablet was aligned to the midpoint of the two eyes. A 20 cm separation was maintained between the dielectric substrate of the PC tablet and the midpoint of the eyes. RESULTS The whole-body model weighed 9.84 kg and measured 73.0 cm. The corresponding data from WHO Multicentre Growth Reference Study Group [2006] for weight and height are 9.65 kg and 75.7 cm, respectively. The head circumferences of the 12- and 17-month-old models were 44 and 48 cm, respectively. Reference data from WHO Multicentre Growth Reference Study Group indicate circumferences of 46 and 48.7 cm for these two ages. Table 1 compares the tissue masses with the International Commission on Radiological Protection (ICRP) data [Valentin, 2002]. The maximum deviation from the ICRP values was approximately 18% while the mean value  standard deviation for all the surveyed tissues was 12.36  4.79%. The tissue mass of the head models is listed in Table 2. We observed a 20% increase in total brain tissue mass (including the gray matter, white matter, cerebellum, midbrain, pons, hippocampus, and thalamus) between the 12-monthold and the 17-month-old model. The WBASAR is plotted in Figure 5, and the tissue-specific SAR (TSSAR) of major tissues from the simulated models is shown in Figure 6. The resonance frequency of the whole-body infant model

Fig.4. Numericalmodelofthe PCtablet (a) isthestructuresandthedimensionsand (b) isthesimulated S11.Theprototype oftheantennaisfromthe SEMCADusermanual [SPEAG,2013]. Bioelectromagnetics

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TABLE 1. Identified Tissues in the 12-Month-Old Infant Whole-Body Model Whole body model Tissue

Reference value

Grayscale label

Density (kg/m3)

kg

Body composition %

Mass (kg)

Body composition (%)

Deviationc (%)

6 12 30 54 42 24 72 18 126 36 48 60 66 78 84 90 96 102 108 114 120 132 138 144 150 156 162 168

1.2 1908 1908 1908 1090.4 911 1045.5 1007 980 1028.5 1109 1075 1090.4 1035 1004.5 1080.8 1030 1045.2 1066.25 1078.75 394 1089 1088 1045.2 1080 1.2 1.2 1101.5

0.000046 0.38 0.038 0.43 1.72 4.27 1.02 0.092 0.017 0.12 0.41 0.0065 0.010 0.0087 0.008 0.11 0.12 0.51 0.064 0.28 0.13 0.031 0.017 0.033 0.0014 0.00000046 0.000054 0.0040

0.00047 3.82 0.39 4.34 17.50 43.57 10.43 0.94 0.18 1.22 4.15 0.066 0.10 0.088 0.082 1.13 1.18 5.16 0.66 2.84 1.28 0.32 0.17 0.34 0.014 0 0.001 0.041

/ 1.00a

/ 10.00

/ 14.5

1.90 3.80 0.95 / 0.02 0.15 0.35 / 0.010 0.0090 0.0070 0.098 0.135b / 0.070 0.33 0.15 0.029 0.020 / 0.0015 / / /

19.00 38.00 9.50 / 0.20 1.50 3.50 / 0.10 0.090 0.070 0.98 1.35 / 0.70 3.30 1.50 0.29 0.20 / 0.015 / / /

7.9 14.66 9.79 / 10 18.67 18.57

Air_internal Bone Mandible Skull Muscle Fat Brain CSF Marrow_yellow Marrow_red Skin Spinal_cord Tongue Bladder Eye Heart Intestines Intestine_lumen Kidney Liver Lungs Spleen Stomach Stomach_lumen Trachea Trachea_lumen bladder_lumen (Urine) Penis

0 2.22 17.14 15.31 12.59 / 5.71 13.94 14.67 10.35 15 / 6.67 / / /

The comparison is made with the data from ICRP89. Marrows exclusive. b Walls of the large, small intestines, colons, and rectosigmoid inclusive. a

Deviation ð%Þ ¼

c

Body compositionwholebody model Body compositionreference Body compositionreference


100%. The reference values are from ICRP 89.

TABLE 2. Identified Tissues in the 17-Month-Old Infant Head Model Tissue Air_internal Mandible Skull Muscle Fat CSF Marrow_red Skin Spinal_cord Tongue Artery Cornea Eye_lens Eye_sclera Vitreous_humor Bioelectromagnetics

Grayscale label

Denisity (kg/m3)

Mass (kg)

6 30 54 42 24 18 36 48 60 66 74 98 110 116 122

0 1908 1908 1090.4 911 1007 1030 1109 1075 1090.4 1049.8 1050.5 1075.5 1032 1004.5

0 0.024 0.38 0.17 0.40 0.15 0.057 0.050 0.0022 0.012 0.0048 0.00045 0.00027 0.0030 0.0085

Tissue Ear cartilage Nerve Pharynx Vein Grey matter White matter Cerebellum Midbrain Pons Hippocampus Thalamus Hypophysis Hypothalamus Medulla_oblongate Pineal_body

Grayscale label

Denisity (kg/m3)

Mass (kg)

104 158 176 188 80 86 92 152 170 128 182 134 140 146 164

1099.5 1075 0 1049.75 1044.5 1041 1045 1045.5 1045.5 1044.5 1044.5 1053 1053 1075 1053

0.0048 0.0017 0 0.0011 0.78 0.21 0.13 0.0067 0.0099 0.0060 0.011 0.00018 0.00025 0.0018 0.000068

Infant Models for EMF Evaluation

Fig. 5. WBASAR for the different humanmodels.Theresult isnormalized to theplane-wavepowerdensityasprescribedby thereferencelevelsof ICNIRPguidelines.

occurred at around 150 MHz. Below this frequency, the WBASAR for the infant model was lower than that for the larger models. Beyond 150 MHz, this trend was reversed. Peak spatial-average SAR over 1 and 10 g cubic mass (pSAR1g and pSAR10g) for dipole exposure is shown in Figure 7. The two infant head models did not show higher pSAR compared with the other two children models when exposed to the dipoles. In particular, similar pSAR10g values were obtained between these child and infant models. In contrast, the adult head had the largest pSAR10g and pSAR1g. Dealing with the SAR averaged over the brain and the nerve tissues, the 12-month-old head model showed the highest absorption in all of the surveyed frequencies (Fig. 8). pSAR1g and pSAR10g for the PC tablet exposure are shown in Figure 9. The infant models showed modest pSAR compared with the other models. On the contrary, brain and nerve tissue for the 12-month-old model featured the highest SAR among all the surveyed models (Fig. 10). DISCUSSION We observed substantial differences in terms of mass percentages when the infant model was compared with the adult or child models. The mass percentages of the brain, fat, muscle, bone, and skin of the models in Table 3 (Chinese adult female, Chinese adult male, Korean child, Billie, and Thelonious) are around 3–6%, 15–35%, 30–40%, 12–15%, and 6–9%, respectively. In comparison, the corresponding values are 10.43%, 43.57%, 17.50%, 3.82%, and 4.15% for the constructed infant model (Table 1). We also observed a rapid increase in brain mass between the

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12- and 17-month-old models. These differences in anatomical and physical features confirm the need to establish realistic models rather than simply using scaled models for assessing the effects of infant exposure to EMF. Since the thickness of the infant’s skin in our model was 1 mm, remeshing the models with coarser resolutions must be performed with caution. The variation of the frequency dependant WBASAR could be attributed to the penetration depth and cross-sectional dimensions of the infant models. From 20 to 100 MHz, the penetration depths of the major tissues ranged from 0.24 to 0.10 m for brain tissues, from 0.15 to 0.08 m for muscles, from 0.30 to 0.10 m for the skin, from 0.74 to 0.40 m for fats, and from 0.66 to 0.34 m for bones. By contrast, the maximum dimensions of the trunks of the simulated models were 0.27 m (posterior to anterior) and 0.32 m (left to right). The detailed dimensions for the simulated models are listed in Table 3. These findings indicate that EM waves can effectively penetrate into the bodies of all the models. Therefore, the tissue composition in the body will determine power absorption. The infant model had the largest proportion of fat (tissue has lower conductivity and, thus, lower power absorption ability). Hence, the WBASAR of the infant model was the smallest among all of the surveyed models. By contrast, at higher frequency (e.g., 450 MHz), the penetration depth decreased to 0.05 m for brain tissues, muscles, and skin, and 0.20 m for bones. Therefore, the EMF power can penetrate deeper into the infant model (in terms of crosssectional proportion) than into the larger models. Higher EMF powers cannot only deposit in superficial and less lossy layers (e.g., fat), but also in deeper and lossy tissues (e.g., muscles and internal organs) for the infant model. When averaging over the entire body mass, larger models tended to show smaller WBASAR than infant models. In this case, the ICNIRP guidelines may not be conservative for infants. The aforementioned assumption is supported by the WBASAR obtained from the whole-body 12month-old infant model and the scaled Chinese female adult model; these models had similar cross-sectional depth and, thus, featured a similar WBASAR (Fig. 5). Figure 11 shows the absorbed power (at 450, 900, 2400, and 3000 MHz) by a slice at the chest level from the whole-body infant, Chinese female, and scaled Chinese female models. The infant and scaled female models showed similar patterns in EMF power distribution. As the Chinese adult female had larger dimensions, absorption occurred only in superficial tissues. The TSSAR results demonstrated a similar trend (Fig. 6). Bioelectromagnetics

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Fig. 6. SAR of the major tissues from the different human models.The result is normalized to the plane-wavepowerdensityasprescribedby thereferencelevelsof ICNIRPguidelines.

When exposed by the dipoles, the Chinese adult male model had the highest pSAR10g/pSAR1g; this feature was attributed to the individual profile of the pinna since pSAR10g/pSAR1g of the adult model occurred in this tissue (Fig. 12). We observed comparative low pSAR for the head of the infant models (Fig. 7) but very high SAR in their brain and nerve tissues (Fig. 8). Two factors can account for this effect. First, the dimensions of the ear influence EMF power absorption. The dimensions of an individual ear and its Bioelectromagnetics

power absorption are shown in Table 4 and Figure 13. The 12-month-old infant model had the smallest ear and, thus, the least power absorption in this part. Higher EMF powers can penetrate into the head, resulting in higher power absorption in the brain. Second, the head model of the 12-month-old infant had the fewest identified tissues and a smooth brain profile (less remarkable gyri and sulci) partially because of the immature stage of the infant brain [Richman et al., 1975; Hofman, 1985, 1989; Ruoss et al., 2001]

Infant Models for EMF Evaluation

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pSAR1g (W/kg)

20 15 10 5 0 900

1800

2100

2530

Frequency (MHz) 12-month-old infant

17-month-old infant

Thelonious

Billie

Chinese male

a

pSAR10g (W/kg)

8 7 6 5 4 3 2 1 0 900

1800

2100

2530

Frequency (MHz) 12-month-old infant

17-month-old infant

Thelonious

Billie

Chinese male

b Fig.7. pSAR10gandpSAR1gfor thesimulatedmodelsexposedtothedipoles.Theresultisnormalizedtotheincident power tothedipoleas1W.

and partially because the images used to construct this model were of relatively low quality. A less-diversified tissue composition results in both uniform distribution

of dielectric properties and fewer interfaces between heterogeneous tissues. EMF power reflection from different dielectric layers was minimized, while the

SAR (W/kg)

0.2 0.15 0.1 0.05 0 900

1800

2100

2530

Frequency (MHz) 12-month-old infant

17-month-old infant

Thelonious

Billie

Chinese male

Fig. 8. SAR averaging over the brain and CNS tissues for the simulated models exposed to the dipoles.Theresultisnormalizedtothenetincident power tothedipoleas1W. Bioelectromagnetics

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3.50E-04 3.00E-04 2.50E-04 2.00E-04 1.50E-04 1.00E-04 5.00E-05 0.00E+00 2100

2400

2530

Frequency (MHz) 12-month-old infant

17-month-old infant

Thelonious

Billie

Chinese male

pSAR10g (W/kg)

a 2.25E-04 2.00E-04 1.75E-04 1.50E-04 1.25E-04 1.00E-04 7.50E-05 5.00E-05 2.50E-05 0.00E+00 2100

2400

2530

Frequency (MHz) 12-month-old infant

17-month-old infant

Thelonious

Billie

Chinese male

b Fig. 9. pSAR10g and pSAR1g for the simulated models exposed to the PC tablet.The result is normalizedtothenetincident power totheantennaas1W. (a) pSAR1gand (b) pSAR10g.

absorption was enhanced. This assumption is supported by the slice view of EMF power absorption (Fig. 14). The EMF power distribution pattern in the head of

the 12-month-old infant was more uniform than that in the other head models. Previous studies also confirmed that the uniform head phantom was slightly

2.50E-05

SAR (W/kg)

2.00E-05 1.50E-05 1.00E-05 5.00E-06 0.00E+00 2100

2400

2530

Frequency (MHz) 12-month-old infant

17-month-old infant

Thelonious

Billie

Chinese male

Fig. 10. SAR averaging over the brain and CNS tissues for the simulated models exposed to the PC tablet.Theresultisnormalizedtothenetincident power totheantennaas1W. Bioelectromagnetics

Infant Models for EMF Evaluation

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TABLE 3. Dimensions for the Cross-Sectional Slice of the Simulated Models Front to back (mm)

Left to right (mm)

Twelve-month-old infant

120

160

Scaled Chinese female

128

160

Korean child

147

220

Thelonious

156

224

Billie

145

258

Chinese male

270

320

Chinese female

230

297

conservative for SAR evaluations [Gandhi et al., 1996; Hombach et al., 1996; Meier et al., 1997; Nikita et al., 2000]. We will not explain the effect as different

thicknesses in fat, skin, and skull on power absorption because no obvious difference can be observed from Table 5. Christ et al. [2010b] reported no significant

Fig.11. SAR distribution on the cross-sectional slice at the chest level for the simulated models. Theresultisnormalizedtotheplane-wavepowerdensityas1W/m2. Bioelectromagnetics

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Fig.12. SAR distribution in the head of the simulated models for the dipole exposure case.The resultisnormalizedtothenetincident power tothedipoleas1W.

difference in distance between the skull and the pinna for adults and children (6–8 years of age) when a force of 4.9 N was applied. Therefore, the realistic spacing when using a mobile phone closely against the ear might not be necessarily smaller for infants. It is a compelling issue for further study. According to previous studies [Bernardi et al., 1998, Hirata et al., 2002, 2007], localized head SAR by frontal incidence can be influenced greatly by the individual anatomy, even the air in the nose. The result also indicates that SAR variability induced by the anatomical characteristics, including the comparaBioelectromagnetics

tively smooth brain profile, requires further investigation, especially in neonates. This work does not analyze SAR variability caused by dielectric properties or influences of the adult body; these features will be discussed in future reports.

CONCLUSION We reconstructed one whole-body model and one head model from the MR datasets of two 12- and

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Power absorption (W)

0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 900

1800

2100

2530

Frequency (MHz) 12-month-old infant

17-month-old infant

Thelonious

Billie

Chinese male

Fig. 13. EMF power absorption in the ear of the simulated models for the dipole exposure case. Theresultisnormalizedtothenetincident power tothedipoleas1W

17-month old infants. The anatomical and physical parameters of these models were validated using data from published literature. We found significant physi-

cal differences between the infant models and models from other age groups. A rapid increase in brain mass was observed between the 12- and 17-month-old

Fig.14. SAR distributioninthebrains ofthe simulated modelsfor the dipole exposure case.Theresultisnormalizedtothenetincident power tothedipoleas1W. Bioelectromagnetics

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Li et al.

TABLE 4. Dimensions for the Right Ears of the Simulated Models X (mm)

Y (mm)

Z (mm)

Twelve-month-old infant

11

28

45

Seventeen-month-old infant

13

31

53

Thelonious

15

32

55

Billie

15

33

56

Chinese male

25

41

58

TABLE 5. Thickness of the Skull, Fat, and Skin of the Simulated Head Models Thickness range (mm)

Twelve-month-old infant

Seventeen-month-old infant

Thelonious

Billie

Chinese male

1 5 3.43 0.43

0.87 2.5 2.37 0.75

1 6.5 2.44 0.73

1 7 3 0.82

1 8 4 1.10

2 11.66 4.81 1.07

1 9.85 3.61 0.89

1 3.5 1.65 0.39

1 4 2 0.43

2 7 3.76 0.73

1 1 1 0

1 3 1.25 0.63

1 3 1.62 0.51

1 3 1.85 0.42

Skull Minimum (mm) Maximum (mm) Mean (mm) Std (mm) Fat Minimum (mm) Maximum (mm) Mean (mm) Std (mm) Skin Minimum (mm) Maximum (mm) Mean (mm) Std (mm)

1 1 1 0

infant heads, which was not observed in other age groups. Three RF EMF exposure scenarios were established. Results revealed that safety limits prescribed in ICNIRP guidelines might not be conservative for infants. The individual anatomy of infants may significantly influence localized SAR. These findings confirm the necessity of filling the gaps between human anatomical models for evaluating EMF exposure effects. Simulation results covering larger frequency bands and exposure scenarios using the present models will be published in future reports. ACKNOWLEDGMENTS The authors would like to thank Dr. Ae-Kyoung Lee from ETRI, Republic of Korea, for sharing the Bioelectromagnetics

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