Temperature dependence of relaxation times and temperature mapping in ultra-low-field MRI.

Ultra-low-field MRI is an emerging technology that allows MRI and NMR measurements in microtesla-range fields. In this work, the possibilities of relaxation-based temperature measurements with ultra-low-field MRI were investigated by measuring T1 and T2 relaxation times of agarose gel at 50 µT-52 mT and at temperatures 5-45°C. Measurements with a 3T scanner were made for comparison. The Bloembergen-Purcell-Pound relaxation theory was combined with a two-state model to explain the field-strength and temperature dependence of the data. The results show that the temperature dependencies of agarose gel T1 and T2 in the microtesla range differ drastically from those at 3T; the effect of temperature on T1 is reversed at approximately 5 mT. The obtained results were used to reconstruct temperature maps from ultra-low-field scans. These time-dependent temperature maps measured from an agarose gel phantom at 50 µT reproduced the temperature gradient with good contrast.

Suppressing multi-channel ultra-low-field MRI measurement noise using data consistency and image sparsity.

Ultra-low-field (ULF) MRI (B 0 = 10-100 µT) typically suffers from a low signal-to-noise ratio (SNR). While SNR can be improved by pre-polarization and signal detection using highly sensitive superconducting quantum interference device (SQUID) sensors, we propose to use the inter-dependency of the k-space data from highly parallel detection with up to tens of sensors readily available in the ULF MRI in order to suppress the noise. Furthermore, the prior information that an image can be sparsely represented can be integrated with this data consistency constraint to further improve the SNR. Simulations and experimental data using 47 SQUID sensors demonstrate the effectiveness of this data consistency constraint and sparsity prior in ULF-MRI reconstruction.

Hybrid ultra-low-field MRI and magnetoencephalography system based on a commercial whole-head neuromagnetometer.

Ultra-low-field MRI uses microtesla fields for signal encoding and sensitive superconducting quantum interference devices for signal detection. Similarly, modern magnetoencephalography (MEG) systems use arrays comprising hundreds of superconducting quantum interference device channels to measure the magnetic field generated by neuronal activity. In this article, hybrid MEG-MRI instrumentation based on a commercial whole-head MEG device is described. The combination of ultra-low-field MRI and MEG in a single device is expected to significantly reduce coregistration errors between the two modalities, to simplify MEG analysis, and to improve MEG localization accuracy. The sensor solutions, MRI coils (including a superconducting polarizing coil), an optimized pulse sequence, and a reconstruction method suitable for hybrid MEG-MRI measurements are described. The performance of the device is demonstrated by presenting ultra-low-field-MR images and MEG recordings that are compared with data obtained with a 3T scanner and a commercial MEG device.

Noise amplification in parallel whole-head ultra-low-field magnetic resonance imaging using 306 detectors.

In ultra-low-field magnetic resonance imaging, arrays of up to hundreds of highly sensitive superconducting quantum interference devices (SQUIDs) can be used to detect the weak magnetic fields emitted by the precessing magnetization. Here, we investigate the noise amplification in sensitivity-encoded ultra-low-field MRI at various acceleration rates using a SQUID array consisting of 102 magnetometers, 102 gradiometers, or 306 magnetometers and gradiometers, to cover the whole head. Our results suggest that SQUID arrays consisting of 102 magnetometers and 102 gradiometers are similar in g-factor distribution. A SQUID array of 306 sensors (102 magnetometers and 204 gradiometers) only marginally improves the g-factor. Corroborating with previous studies, the g-factor in 2D sensitivity-encoded ultra-low-field MRI with 9 to 16-fold 2D accelerations using the SQUID array studied here may be acceptable.