Wide-band Dielectric Tissue Property Characterization by Quantitative Multinuclear MRI based Tissue Composition Assessment

Medical device design and device safety assessment increasingly rely on computational modeling-based methods. Accurate knowledge of the dielectric properties of human tissue therefore becomes increasingly crucial. In this study, we investigated the feasibility for determining dielectric tissue properties in the frequency range of 50 to 600 MHz using mixture models combined with quantitative multinuclear MRI-based tissue composition electrical property tomography (EPT): “1H23NaTiCEPT”. The composition of muscles can be approximated by protein, fat, sodium, and water. Four phantoms with different compositions were prepared (healthy, obese, obese+, and dehydrated). Mixture models were used to relate the dielectric properties (DP) of the muscle to its constituents. The Looyenga mixture model was used for the relative permittivity, and the Maxwell-Garnett equation for the effective conductivity. The constituents of muscle are saline as background solution, protein and fat as additive, and the water fraction is used to find the volume fraction of the additive. All MRI measurements were performed using a Siemens 7T whole-body MRI system at Scannexus (Ultra-High-Field MRI center, Maastricht). The water fraction was determined based on the measured T1 times. Calibration phantoms, consisting of water, sodium chloride and sugar, were used to correlate the T1 times with the water fraction. The sodium concentration measurements of the phantoms were performed with a 23Na knee coil using an ultrashort TE sodium sequence. Four calibration samples with water, agar, and varying salt concentrations were used for a linear fit to find the sodium content in the muscle phantoms. A rational fit was used for the water fraction and a linear one for the sodium concentration. The measured water fraction and sodium concentration were inserted into the Looyenga and Maxwell-Garnett equation. The mean error is 8.2% for the relative permittivity and 15.5% for the effective conductivity. This study demonstrates the potential of reconstructing the DP’s of human tissue by quantitative multinuclear MRI supplemented by the Looyenga and Maxwell-Garnett mixture model.