Purpose The purpose of this research was to develop a 256-channel dense-array electroencephalography (dEEG) sensor net (the Ink-Net) using high-resistance polymer thick film (PTF) technology to improve safety and data quality during simultaneous dEEG/MRI. Methods Heating safety was assessed with temperature measurements in an anthropomorphic head phantom during a 30-minute, induced-heating scan at 7 T. MRI quality assessment used B1 field mapping and fMRI retinotopic scans in three humans at 3 T. Performance of the 256-channel PTF Ink-Net was compared to a 256-channel MR-conditional copper-wired EEG net and to scans with no sensor net. A visual evoked potential paradigm assessed EEG quality within and outside the 3T scanner. Results Phantom temperature measurements revealed non-significant heating (ISO 10974) in the presence of either EEG net. In human B1 field and fMRI scans, the Ink-Net showed greatly reduced cross-modal artifact and less signal degradation than the copper-wired net, and comparable quality to MRI without sensor net. Cross-modal ballistocardiogram artifact in the EEG was comparable for both nets. Conclusion High-resistance PTF technology can be effectively implemented in a 256-channel dEEG sensor net for MR-conditional use at 7 T, and with significantly improved structural and fMRI data quality as assessed at 3 T.

Electrical Bioimpedance Spectroscopy (EBIS) is currently used in different tissue characterization applications. In this work we aim to use EBIS to study changes in electrical properties of the cerebral tissues after an incident of hemorrhage/ischemic stroke. To do so a case-control study was conducted using six controls and three stroke cases. The preliminary results of this study show that by using Cole-based analysis on EBIS measurements and analyzing the Cole parameters R(0) and R(∞), it is possible to detect changes on electrical properties of cerebral tissue after stroke.

This study investigates radiofrequency (RF)-induced heating in a head model with a 256-channel electroencephalogram (EEG) cap during magnetic resonance imaging (MRI). Nine computational models were implemented each with different EEG lead electrical conductivity, ranging from 1 to 5.8 × 10 7 S/m. The peak values of specific absorption rate (SAR) averaged over different volumes were calculated for each lead conductivity. Experimental measurements were also performed at 3-T MRI with a Gracilaria Lichenoides (GL) phantom with and without a low-conductive EEG lead cap ("InkNet"). The simulation results showed that SAR was a nonlinear function of the EEG lead conductivity. The experimental results were in line with the numerical simulations. Specifically, there was a ΔT of 1.7 °C in the GL phantom without leads compared to ΔT of 1.8 °C calculated with the simulations. Additionally, there was a ΔT of 1.5 °C in the GL phantom with the InkNet compared to a ΔT of 1.7 °C in the simulations with a cap of similar conductivity. The results showed that SAR is affected by specific location, number of electrodes, and the volume of tissue considered. As such, SAR averaged over the whole head, or even SAR averaged over volumes of 1