Two-Dimensional FDTD Simulation of Specific Absorption Rate Distribution in a Segmented Human Brain Model Derived from MRI

This paper presents a two-dimensional finite-difference time-domain (FDTD) investigation of the local specific absorption rate (SAR) distribution in a heterogeneous human brain model derived from a segmented magnetic resonance imaging (MRI) dataset. The electromagnetic problem is solved at 900 MHz for a normally incident plane wave using a total-field/scattered-field (TF/SF) formulation. A uniaxial perfectly matched layer (UPML) is employed to truncate the computational domain and reduce artificial boundary reflections. The anatomical model is derived from the BrainWeb database and includes gray matter, white matter, cerebrospinal fluid (CSF), and skull. Published dielectric-property data at 900 MHz are assigned to the different tissue classes. The numerical model uses a spatial resolution of 1 mm, a 280 × 290 computational grid, a 40-cell absorbing layer, and 15,666 time steps. The calculated SAR distribution is strongly non-uniform as a consequence of the dielectric contrasts between tissues, multiple reflections at tissue interfaces, and local electromagnetic-field interference. The CSF exhibits the largest mean and maximum SAR values among the considered tissues, whereas the skull exhibits the lowest mean SAR. The tissue-averaged absorption is quantitatively interpreted through the decomposition $\text{SAR}=\left(\sigma /\rho \right)？{\left|E\right|}^2？$ , which separates a material factor determined by the tissue properties from a field factor governed by the local electromagnetic environment. Tissue-wise statistical indicators are reported in terms of the mean, standard deviation, and maximum SAR. A systematic verification strategy is established using one-dimensional benchmarks for numerical dispersion, dielectric interfaces, and parallel dielectric slabs, together with a two-dimensional benchmark based on the Mie-series solution for a lossy dielectric cylinder. These tests provide a quantitative assessment of the numerical accuracy of the FDTD solver and establish the reliability of the computed electromagnetic fields used for the anatomical configuration. The results demonstrate the relevance of anatomically heterogeneous models for investigating local