Sveinsson B, Koonjoo N, Zhu B, Witzel T, Rosen MS. Detection of nanotesla AC magnetic fields using steady-state SIRS and ultra-low field MRI.
J Neural Eng 2020;
17:034001. [PMID:
32268305 DOI:
10.1088/1741-2552/ab87fe]
[Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE
Functional magnetic resonance imaging (fMRI) is commonly used to measure brain activity through the blood oxygen level dependent (BOLD) signal mechanism, but this only provides an indirect proxy signal to neuronal activity. Magnetoencephalography (MEG) provides a more direct measurement of the magnetic fields created by neuronal currents in the brain, but requires very specialized hardware and only measures these fields at the scalp. Recently, progress has been made to directly detect neuronal fields with MRI using the stimulus-induced rotary saturation (SIRS) effect, but interference from the BOLD response complicates such measurements. Here, we describe an approach to detect nanotesla-level, low-frequency alternating magnetic fields with an ultra-low field (ULF) MRI scanner, unaffected by the BOLD signal.
APPROACH
A steady-state implementation of the stimulus-induced rotary saturation (SIRS) method is developed. The method is designed to generate a strong signal at ultra-low magnetic field as well as allowing for efficient signal averaging, giving a high contrast-to-noise ratio (CNR). The method is tested in computer simulations and in phantom scans.
MAIN RESULTS
The simulations and phantom scans demonstrated the ability of the method to measure magnetic fields at different frequencies at ULF with a stronger contrast than non-steady-state approaches. Furthermore, the rapid imaging functionality of the method reduced noise efficiently. The results demonstrated sufficient CNR down to 7 nT, but the sensitivity will depend on the imaging parameters.
SIGNIFICANCE
A steady-state SIRS method is able to detect low-frequency alternating magnetic fields at ultra-low main magnetic field strengths with a large signal response and contrast-to-noise, presenting an important step in sensing biological fields with ULF MRI.
Collapse