Numerical Calculation of Peak-to-Average Specific Absorption Rate on Different Human Thorax Models for Magnetic Resonance Safety Considerations

• Published in: Applied magnetic resonance Vol. 38; no. 3; pp. 337 - 348
• Main Authors: Hartwig, Valentina, Giovannetti, G., Vanello, N., Landini, L., Santarelli, M. F.
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01.06.2010; Springer Nature B.V
• Subjects: Absorption; Atoms and Molecules in Strong Fields; Dosimetry; Electric fields; Energy; Finite difference time domain method; Human subjects; Ionizing radiation; Laser Matter Interaction; Magnetic fields; Magnetic resonance imaging; Mathematical models; Nuclei (nuclear physics); Numerical analysis; Organic Chemistry; Patient safety; Physical Chemistry; Physics; Physics and Astronomy; Radio frequency; Solid State Physics; Spectroscopy/Spectrometry; Thorax; Magnetic Resonance Imaging System; Static Magnetic Field; Finite Difference Time Domain; Power Deposition; Specific Absorption Rate
• ISSN: 0937-9347; 1613-7507
• DOI: 10.1007/s00723-010-0126-z

Magnetic resonance imaging (MRI) is considered a safe technology since it relies only on spatial encoding of the position of atomic nuclei (mainly protons) in a static magnetic field irradiating them with radio-frequency (RF) pulses instead of ionizing radiation. Specific absorption rate (SAR) is the most frequently used parameter for monitoring and quantifying the power deposition on a subject during an MRI examination. The peak-to-average SAR ratio is important information for the MRI operator during the acquisition sequence setup. In this work, a birdcage body coil model is used for RF excitation of several inhomogeneous human thorax models with different sizes and weights. To study the peak-to-average SAR ratio correlation with sample metrics, numerical simulations using the finite difference time domain method were performed to estimate the peak and average SAR values on the entire sample volume. Results for 11 different thorax models indicate a strong correlation between the peak-to-average SAR value and the sample metrics.