Yi-Cheng Hsu, Ying-Hua Chu, Fa-Hsuan Lin, Maxim Zaitsev

We demonstrate that a negative quadratic phase accrual, which we term a pseudo-concomitant field, is likely to be caused by gradient vibration and has a nearly constant spatial distribution. Accounting for this effect may be of importance for phase-sensitive MR applications utilizing strong gradients, such as flow imaging.

Manuel Stich, Tobias Wech, Anne Slawig, Gudrun Ruyters, Andrew Dewdney, Ralf Ringler, Thorsten Bley, Herbert Köstler

As a linear and time-invariant (LTI) system, the dynamic gradient system can be described by the system transfer function. While special measurement equipment like field cameras can be used to precisely determine even higher orders of the transfer function, phantom-based approaches were introduced for alternative determination without additional hardware needed. This study reports on phantom-based measurements of B₀-components, which resulted in transfer functions with sufficiently high resolution for the characterization of mechanical resonances.

Peter Mazurkewitz, Jürgen Rahmer, Peter Börnert

Gradient-impulse-response-function (GIRF) measurement is a well-established method for MRI gradient-system characterization. Typical GIRF input-functions are triangles or chirps. For triangles, measurements have to be performed with different pulse lengths to get a continuous frequency spectrum due to blind spots in the spectrum, requiring long scan times. In contrast, the spectrum of the chirp waveform covers a large frequency range without blind spots. However, at low frequencies the chirp fails due to a diverging intensity in its spectrum. We interleaved both waveforms and obtained a continuous gradient modulation transfer function (GMTF) spectrum down to low frequencies in short measurement time.

Jason Stockmann, Nicolas Arango, Benedikt Poser, Thomas Witzel, Jacob White, Lawrence Wald, Jonathan Polimeni

Multi-coil ΔB₀ shim arrays have recently been used for zoomed imaging of target ROIs in mice, providing improved acquisition efficiency without the high SAR, long RF pulses, and other limitations of conventional selective excitation methods that rely solely on linear gradients.  We extend this work to zoomed 3D EPI in humans using an integrated ΔB₀/Rx array coil to dynamically switch-on a static, spatially-tailored nonlinear ΔB₀ pattern during RF excitation.  Proof-of-concept selective excitations of the occipital visual cortex and the peripheral cerebrum are shown, with strong correspondence to the target patterns.  Four-fold in-plane undersampled EPI of occipital visual cortex demonstrates the method’s potential for efficient high-resolution neuroimaging.

Vanessa Landes, Krishna Nayak

The Gradient Reversal Approach to Evaluate RF (GRATER) has been shown to accurately measure small-tip RF pulses in phantoms, without the need for added hardware or sophisticated processing. Imperfect RF production can be measured with GRATER, and RF waveforms can be appropriately predistorted. We demonstrate substantial improvements in multi-band RF performance using this approach.  For example, a 0.648 ms, 30º FA, 4- band RF pulse with 2 cm center-to-center spacing and 5 mm slice thickness (desirable for SMS cardiac imaging) excites spurious side-lobes with 10.4% and 3.4% max signal before and after GRATER-based RF predistortion, respectively. 

Huihui Ye, Qing Li, Xiaozhi Cao, Qiuping Ding, Hongjian He, Huafeng Liu, Jianghui Zhong

MR fingerprinting with B1+ and B0 field inhomogeneity detection is proposed with an IR-spoiled GRE based sequence. With this sequence, a 12s/slice acquisition simultaneously provide unbiased T1, T2* maps and B1+, B0 information at isotropic 1mm resolution.

Kavitha Manickam, Jaganathan Vellagoundar

In MRI, automatic estimation of main (B0) and RF (B1) field maps from the scanned images will help daily quality assurance and field corrected reconstruction.  In this paper, a novel approach based on deep learning technique is presented to estimate B0 and B1 maps from the scanned images.  A modified version of stacked convolutional encoder with random skip connections deep learning network is constructed.  Two separate networks  are used to estimate B0 and B1 maps individually. The networks are trained and tested with phantom images. The results show that the estimated maps are comparable to the actual field maps. Automatic map estimation based on deep learning approach is the first step towards achieving daily quality assurance and field correction from the regular scanned images.

Frederick Damen, Kejia Cai

Radio Frequency (RF) receiving coil arrays improve the signal-to-noise ratio (SNR), and enable partial parallel imaging. However, these benefits often come at the cost of image non-uniformity.  $$$B^-_1$$$ non-uniformity correction techniques are confounded by signal that not only varies due to coil induced $$$B^-_1$$$ sensitivity, but also due to true signal variations in proton density, susceptibility, and relaxation rates. Herein, we propose an empirical method that produces a $$$B^-_1$$$ non-uniformity-corrected complex image from the phased-array coil images themselves using minimal assumptions and without measuring the coil sensitivities. This method is validated using MRI of the abdomen, brain, and a homogeneous phantom.

Giang-Chau Ngo, Alex Cerjanic, Bradley Sutton

Trajectories such as spiral or EPI enable fast acquisition compared to spin warp imaging. While a spin warp acquisition has a readout of 2-3 ms, a spiral trajectory readout can be as long as 60 ms. The efficiency of the spiral trajectory comes at a cost of image quality through magnetic field inhomogeneity and T2* decay during long readouts. In this work, a signal model with a piecewise linear field map is used to correct for the magnetic field inhomogeneity effects during long imaging readouts . The proposed method shows the ability to correct for resulting image artifacts.

Mark Chiew, Jostein Holmgren, Dean Fido, Catherine Warnaby, S Vannesjo

Simultaneous EEG-FMRI data acquisition provides an opportunity for characterization of magnetic field dynamics during imaging, by leveraging the information contained in the EEG induced gradient artefacts. Using a simple effective loop model, we reduce the complex EEG electrode geometry to small effective loops located at off-isocentre positions, which we use to fit first order (linear in space) models of the magnetic field rate of change. From these, estimates of the actual field dynamics, and trajectory/encoding information can be derived at no cost. In this proof-of-principle, we demonstrate estimation of gradient dynamics during a conventional EPI acquisition using simultaneous EEG recordings.