Water-Content Electrical Property Tomography (wEPT) for Mapping Brain Tissue Conductivity in the 200-1000 kHz Range: Results of an Animal Study

Abstract

Electrical properties tomography (EPT) has been studied in order to non-invasively map the conductivity and permittivity of brain tissues. Various approaches have been investigated for predicting the electrical properties (EPs) at either very low or high Larmor frequencies. An example of the latter is water-based EPT (wEPT), which derives the EP maps from the image ratio of two T1-weighted images with different repetition times. The rationale is based on the fact that EPs can be modeled as monotonic functions of water content, which in turn can be estimated from the image ratio. The objective of this study is to examine if wEPT can be adapted to accurately create conductivity maps of the brain in the frequency range of 200-1000 kHz, and if EPs of pathological tissues can be estimated using the same approach. These frequencies are of particular interest as a cancer treatment modality, Tumor Treating Fields, utilizes electric fields with 200 kHz to treat glioblastoma. The treatment efficacy depends on the delivered field intensity at the target, which is determined by the EP distribution within the brain and specifically within the heterogeneous tumor. Experimental measurements and wEPT imaging estimations were performed in animal brain samples and tumor-bearing rats. These studies suggest that wEPT-estimated water content maps are reliable. In calf samples, the average error of wEPT-estimated water content is between 2.5% and 3.5%, and in rat samples between 2.2% and 6.4% (measurement error ± 1%). For wEPT estimations of conductivity at 200 kHz, the average errors range from 13.2% to 13.6% in calf tissue samples and from 20.7% to 22.1% rat tissue samples (measurement error ± 10%). Testing various brain and tumor tissues demonstrates a clear trend for wEPT estimations of water content and EPs. The approach might be enhanced by including adaptions according to additional radiological features derived from other imaging modalities, such as T2-weighted imaging or diffusion imaging.