The magnetic field noise in superconducting quantum interference devices (SQUIDs) used for biomagnetic research such as magnetoencephalography or ultra-low-field nuclear magnetic resonance is usually limited by instrumental dewar noise. We constructed a wideband, ultra-low noise system with a 45 mm diameter superconducting pick-up coil inductively coupled to a current sensor SQUID. Thermal noise in the liquid helium dewar is minimized by using aluminized polyester fabric as superinsulation and aluminum oxide strips as heat shields, respectively. With a magnetometer pick-up coil in the center of the Berlin magnetically shielded room 2 (BMSR2) a noise level of around 150 aT Hz −1/2 is achieved in the white noise regime between about 20 kHz and the system bandwidth of about 2.5 MHz. At lower frequencies, the resolution is limited by magnetic field noise arising from the walls of the shielded room. Modeling the BMSR2 as a closed cube with continuous µ-metal walls we can quantitatively reproduce its measured field noise.Biomagnetism aims at the detection of magnetic fields generated by the human body. As these fields are typically in the range of femtotesla to picotesla when detected outside the human body, high sensitivity magnetometry is required. Traditionally, the preferred detectors are low critical temperature (low-T c ) superconducting quantum interference devices (SQUIDs) operated at liquid helium (LHe) temperatures. Owing to their exquisite sensitivity SQUIDs facilitated the measurements of magnetic fields of the brain, and commercial multichannel systems for magnetoencephalography (MEG) are available with a field noise of about 2 fT Hz −1/2 . SQUID performance is usually limited by the LHe dewar due to Johnson noise in the superinsulation comprised of aluminized foils and the thermal radiation shields made from copper mesh.

Direct imaging of impressed dc currents inside the head can provide valuable conductivity information, possibly improving electro-magnetic neuroimaging. Ultra-low field magnetic resonance imaging (ULF MRI) at μT Larmor fields can be utilized for current density imaging (CDI). Here, a measurable impact of the magnetic field B J , generated by the impressed current density J, on the MR signal is probed using specialized sequences. In contrast to high-field MRI, the full tensor of B J can be derived without rotation of the subject in the scanner, due to a larger flexibility in the sequence design.We present an ULF MRI setup based on a superconducting quantum interference device (SQUID), which is operating at a noise level of 380 aT Hz −1/2 and capable of switching all imaging fields within a pulse sequence. Thereby, the system enables zero-field encoding, where the full tensor of B J is probed in the absence of other magnetic fields. 3D CDI is demonstrated on phantoms with different geometries carrying currents of approximately 2 mA corresponding to current densities between 0.45 and 8 A/m 2 . By comparison to an in vivo acquired head image, we provide insights to necessary improvements in signal-to-noise ratio.

Using an ultra-sensitive single-channel SQUID system an upper limit of 80 aT Hz−1/2 for the body noise contribution of the human head in ultra-low-field SQUID-based MRI or MEG is determined. We discuss in detail the various noise contributions which need to be taken into account. Simulations and measurements of conducting phantoms show that presumably residual radio frequency interference cause an increase in the sensor noise at the aT Hz−1/2-level and need to be considered. Using a phenomenological approach, the body noise contribution of the human head is determined to 55 aT Hz−1/2 for our setup. We also provide simulations of the expected body noise for other sensor geometries.

Magnetic fields associated with currents flowing in tissue can be measured non-invasively by means of zero-field-encoded ultra-low-field magnetic resonance imaging (ULF MRI) enabling current-density imaging (CDI) and possibly conductivity mapping of human head tissues. Since currents applied to a human are limited by safety regulations and only a small fraction of the current passes through the relatively highly-resistive skull, a sufficient signal-to-noise ratio (SNR) may be difficult to obtain when using this method. In this work, we study the relationship between the image SNR and the SNR of the field reconstructions from zero-field-encoded data. We evaluate these results for two existing ULF-MRI scanners-one ultra-sensitive single-channel system and one whole-head multi-channel system-by simulating sequences necessary for current-density reconstruction. We also derive realistic current-density and magnetic-field estimates from finite-element-method simulations based on a three-compartment head model. We found that existing ULF-MRI systems reach sufficient SNR to detect intra-cranial current distributions with statistical uncertainty below 10%. However, the results also reveal that image artifacts influence the reconstruction quality. Further, our simulations indicate that current-density reconstruction in the scalp requires a resolution <5 mm and demonstrate that the necessary sensitivity coverage can be accomplished by multi-channel devices.

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