Electrodeless conductivity tensor imaging (CTI) using MRI: basic theory and animal experiments

Abstract

The electrical conductivity is a passive material property primarily determined by concentrations of charge carriers and their mobility. The macroscopic conductivity of a biological tissue at low frequency may exhibit anisotropy related with its structural directionality. When expressed as a tensor and properly quantified, the conductivity tensor can provide diagnostic information of numerous diseases. Imaging conductivity distributions inside the human body requires probing it by externally injecting conduction currents or inducing eddy currents. At low frequency, the Faraday induction is negligible and it has been necessary in most practical cases to inject currents through surface electrodes. Here we report a novel method to reconstruct conductivity tensor images using an MRI scanner without current injection. This electrodeless method of conductivity tensor imaging (CTI) utilizes B1 mapping to recover a high-frequency isotropic conductivity image which is influenced by contents in both extracellular and intracellular spaces. Multi-b diffusion weighted imaging is then utilized to extract the effects of the extracellular space and incorporate its directional structural property. Implementing the novel CTI method in a clinical MRI scanner, we reconstructed in vivo conductivity tensor images of canine brains. Depending on the details of the implementation, it may produce conductivity contrast images for conductivity weighted imaging (CWI). Clinical applications of CTI and CWI may include imaging of tumor, ischemia, inflammation, cirrhosis, and other diseases. CTI can provide patient-specific models for source imaging, transcranial dc stimulation, deep brain stimulation, and electroporation. Keywords Conductivity tensor imaging (CTI) Á Diffusion weighted imaging Á Magnetic resonance electrical properties tomography Á Anisotropy & Eung Je Woo

Statistical analysis of the accuracy of water content‐based electrical properties tomography

“…For example, the retrieved EPs information can be used to do fast and subject‐specific SAR estimation, which is a very important concern for safety evaluation in high filed MRI. Also, the EPs can significantly benefit the neurostimulation techniques (such as TMS or tDCS) or MEG/EEG source detection, by extending the EP values at Larmor frequency to low frequency . In one word, besides what traditional T 1 /T 2 can do, wEPT can also provide rich information in tissue physical or physiological characteristics.…”

Extracellular electrical conductivity property imaging by decomposition of high-frequency conductivity at Larmor-frequency using multi-b-value diffusion-weighted imaging

“…To estimate the ratio of ion concentrations in ICS and ECS, for the human brain, the ratio value b ¼ � c i � c e ¼ 0:41 was suggested by adopting reference values of intracellular and extracellular ion concentrations of four predominant ions (Na + , Cl − , K + , and Ca 2+ ) [25,26]. Using the reference ratio value β = 0.41, the apparent extracellular ion concentration � c e can be estimated as…”

“…Lately, an electrodeless method providing the low-frequency conductivity tensor image (LF-CTI) using a clinical MRI scanner without any external hardware has been initiated [25,26]. The proposed LF-CTI method based on the observation that the conductivity is proportional to the product of mobility and concentration of charge carriers.…”

“…The LF-CTI method provides a possible way to visualize the low-frequency conductivity tensor map without additional external injection current, human imaging experiments, however, were deferred mainly due to lack of validation studies. The LF-CTI method needs to overcome several difficulties [25,26]:…”

“…For MREPT experiments, a multi-spin-echo pulse sequence with multiple refocusing pulses was used to reduce measured noise artifact. Since measured multi-b-value DWIs exponentially decayed, it is difficult to avoid the noise amplification from the three compartment model even with 15 b-values [25]. To quantitatively compare the quality of reconstructed parameters, we used 7 and 4 b-value DWIs to extract the microstructural parameters such as the volume fraction and mean diffusivity in ECS.…”