Numerical Simulation of the Radiofrequency Safety of 128-Channel hd-EEG Nets on a 29-Month-Old Whole-Body Model in a 3 Tesla MRI

Jeong, Hongbae; Ntolkeras, Georgios; Grant, P. Ellen; Bonmassar, Giorgio

doi:10.1109/temc.2021.3097732

Cited by 4 publications

(9 citation statements)

References 47 publications

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“…The increased lead resistivity provided by PTF/thin-film technology allows for safe and high-quality recordings at fields up to 7 T in adults [ 44 ]. Our recent simulation study on EEG safety in infants and toddlers [ 45 ] showed a similar finding concerning the low risk of RF heating when using conductive EEG traces in 3 T MRI: thin-film-based resistive traces, with similar resistivity to the one used in the MotoNet, reduced the risk of RF heating as per the Medical Devices for Safety in the MRI Environment guideline of the FDA [ 35 ]. PTF technology thus provides a promising approach for safely recording EEG in the MR environment.…”

Section: Discussionmentioning

confidence: 68%

The MotoNet: A 3 Tesla MRI-Conditional EEG Net with Embedded Motion Sensors

Levitt

Kouwe

Jeong

et al. 2023

Sensors

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We introduce a new electroencephalogram (EEG) net, which will allow clinicians to monitor EEG while tracking head motion. Motion during MRI limits patient scans, especially of children with epilepsy. EEG is also severely affected by motion-induced noise, predominantly ballistocardiogram (BCG) noise due to the heartbeat. Methods: The MotoNet was built using polymer thick film (PTF) EEG leads and motion sensors on opposite sides in the same flex circuit. EEG/motion measurements were made with a standard commercial EEG acquisition system in a 3 Tesla (T) MRI. A Kalman filtering-based BCG correction tool was used to clean the EEG in healthy volunteers. Results: MRI safety studies in 3 T confirmed the maximum heating below 1 °C. Using an MRI sequence with spatial localization gradients only, the position of the head was linearly correlated with the average motion sensor output. Kalman filtering was shown to reduce the BCG noise and recover artifact-clean EEG. Conclusions: The MotoNet is an innovative EEG net design that co-locates 32 EEG electrodes with 32 motion sensors to improve both EEG and MRI signal quality. In combination with custom gradients, the position of the net can, in principle, be determined. In addition, the motion sensors can help reduce BCG noise.

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Section: Discussionmentioning

confidence: 68%

The MotoNet: A 3 Tesla MRI-Conditional EEG Net with Embedded Motion Sensors

Levitt

Kouwe

Jeong

et al. 2023

Sensors

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“…An uncertainty analysis of the numerical simulation with the segmented EEG cap was performed similarly to previous works 30,31 . The sensitivity factor of each parameter was computed by comparing the peak

{\mathrm{SAR}}_{10\mathrm{g}}

between two simulations differing by only this parameter.…”

Section: Methodsmentioning

confidence: 99%

“…An uncertainty analysis of the numerical simulation with the segmented EEG cap was performed similarly to previous works. 30,31 The sensitivity factor of each parameter was computed by comparing the peak SAR 10g between two simulations differing by only this parameter. In distinct simulations, the conductivity and permittivity of head tissues and dielectric gel as well as the resistance of EEG resistors were changed by 10%, while the position of the imaging subject was shifted by 20 mm in three directions or rotated by 10…”

Section: Uncertainty Analysismentioning

confidence: 99%

Segmenting electroencephalography wires reduces radiofrequency shielding artifacts in simultaneous electroencephalography and functional magnetic resonance imaging at 7 T

Lê

Gruetter

Jorge

et al. 2022

Magnetic Resonance in Med

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Simultaneous scalp electroencephalography and functional magnetic resonance imaging (EEG-fMRI) enable noninvasive assessment of brain function with high spatial and temporal resolution. However, at ultra-high field, the data quality of both modalities is degraded by mutual interactions. Here, we thoroughly investigated the radiofrequency (RF) shielding artifact of a state-of-the-art EEG-fMRI setup, at 7 T, and design a practical solution to limit this issue. Methods: Electromagnetic field simulations and MR measurements assessed the shielding effect of the EEG setup, more specifically the EEG wiring. The effectiveness of segmenting the wiring with resistors to reduce the transmit field disruption was evaluated on a wire-only EEG model and a simulation model of the EEG cap. Results:The EEG wiring was found to exert a dominant effect on the disruption of the transmit field, whose intensity varied periodically as a function of the wire length. Breaking the electrical continuity of the EEG wires into segments shorter than one quarter RF wavelength in air (25 cm at 7 T) reduced significantly the RF shielding artifacts. Simulations of the EEG cap with segmented wires indicated similar improvements for a moderate increase of the power deposition. Conclusion:We demonstrated that segmenting the EEG wiring into shorter lengths using commercially available nonmagnetic resistors is effective at reducing RF shielding artifacts in simultaneous EEG-fMRI. This prevents the formation of RF-induced standing waves, without substantial specific absorption rate (SAR) penalties, and thereby enables benefiting from the functional sensitivity boosts achievable at ultra-high field.

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“…Additionally, this study concluded "Based on our findings, we strongly recommend against using the structural images obtained during simultaneous EEG-MRI recordings for further anatomical data analysis". Our previous studies showed the MRI RF safety of the NeoNet using numerical simulation [19]. This study showed that the high-power MPRAGE heating was well below 2 • C. Our recent simulation study on EEG safety with an infant/toddler [55] also showed a similar finding based on the dielectric properties of the resistive traces in infants/toddlers for safe EEG-MRI [56], where thin film resistive traces reduced the RF heating at 3 T MRI within the safety guidelines by the FDA [57].…”

Section: Mri Safetymentioning

confidence: 99%

“…However, in order for

, resistors were added at the end of the trace that are commonly used by the industry for safety [ 19 ], whereas the aluminum traces required a nanoscale thickness to avoid the need for additional resistors. Several studies have shown that the resistivity of aluminum conductors may increase just by reducing one dimension to the nanoscale [ 20 , 21 , 22 ], which is a desirable property since too thin a width in the traces may have manufacturing and reliability issues.…”

Section: Theorymentioning

confidence: 99%

Aluminum Thin Film Nanostructure Traces in Pediatric EEG Net for MRI and CT Artifact Reduction

Jeong

Ntolkeras

Warbrick

et al. 2023

Sensors

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Magnetic resonance imaging (MRI) and continuous electroencephalogram (EEG) monitoring are essential in the clinical management of neonatal seizures. EEG electrodes, however, can significantly degrade the image quality of both MRI and CT due to substantial metallic artifacts and distortions. Thus, we developed a novel thin film trace EEG net (“NeoNet”) for improved MRI and CT image quality without compromising the EEG signal quality. The aluminum thin film traces were fabricated with an ultra-high-aspect ratio (up to 17,000:1, with dimensions 30 nm × 50.8 cm × 100 µm), resulting in a low density for reducing CT artifacts and a low conductivity for reducing MRI artifacts. We also used numerical simulation to investigate the effects of EEG nets on the B1 transmit field distortion in 3 T MRI. Specifically, the simulations predicted a 65% and 138% B1 transmit field distortion higher for the commercially available copper-based EEG net (“CuNet”, with and without current limiting resistors, respectively) than with NeoNet. Additionally, two board-certified neuroradiologists, blinded to the presence or absence of NeoNet, compared the image quality of MRI images obtained in an adult and two children with and without the NeoNet device and found no significant difference in the degree of artifact or image distortion. Additionally, the use of NeoNet did not cause either: (i) CT scan artifacts or (ii) impact the quality of EEG recording. Finally, MRI safety testing confirmed a maximum temperature rise associated with the NeoNet device in a child head-phantom to be 0.84 °C after 30 min of high-power scanning, which is within the acceptance criteria for the temperature for 1 h of normal operating mode scanning as per the FDA guidelines. Therefore, the proposed NeoNet device has the potential to allow for concurrent EEG acquisition and MRI or CT scanning without significant image artifacts, facilitating clinical care and EEG/fMRI pediatric research.

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Numerical Simulation of the Radiofrequency Safety of 128-Channel hd-EEG Nets on a 29-Month-Old Whole-Body Model in a 3 Tesla MRI

Cited by 4 publications

References 47 publications

The MotoNet: A 3 Tesla MRI-Conditional EEG Net with Embedded Motion Sensors

The MotoNet: A 3 Tesla MRI-Conditional EEG Net with Embedded Motion Sensors

Segmenting electroencephalography wires reduces radiofrequency shielding artifacts in simultaneous electroencephalography and functional magnetic resonance imaging at 7 T

Aluminum Thin Film Nanostructure Traces in Pediatric EEG Net for MRI and CT Artifact Reduction

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