A fast interpolation approach for the calculation of permittivity and conductivity to estimate the SAR

• Published in: 2014 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications (IMWS-Bio2014) pp. 1 - 6
• Main Authors: Priyadarshi, Sanjay, Pitman, Sam, Glover, Paul, Shah, Simon, Jianqiao Ye, Bobo Hu, Letizia, Rosa
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2014
• Subjects: Conductivity; Equations; Interpolation; Mathematical model; Permittivity; Phantoms; Splines (mathematics)
• ISBN: 1479954454; 9781479954452
• DOI: 10.1109/IMWS-BIO.2014.7032447

The conductivity and permittivity of biological tissue are critical to estimating local radiofrequency (RF) power deposition (also known as specific absorption rate SAR) for Ultra High Field Magnetic Resonance Imaging (UH-MRI). These electrical properties may also have diagnostic value as malignant tissue types have been shown to have higher permittivity and conductivity than surrounding healthy tissue [1]. Recently a new SAR calculation method of using the transmit B 1 + map to obtain tissue electrical property has been proposed as a fast SAR calculation method, and has demonstrated great potential for practical applications. However the current numerical technique used in the B 1 + map based electrical property calculation is based on a traditional Finite-Difference algorithm, and therefore it requires high-resolution original B 1 + map to achieve accurate electrical property calculation. In this study, we have proposed the Spline interpolation of low resolution MRI B 1 + map at 1.5T. The proposed method is robust in approximating complex shapes in medical images through curve fitting and therefore could provide sufficiently accurate approximation of the high resolution B 1 + map through the low resolution raw data. This will prove to be useful in the fast real time estimation of local specific absorption rate without compromising the accuracy of SAR calculation. It is found that the Spline interpolation method helps in the reduction of MRI scan time and fast estimation of the SAR.