This work demonstrates a fast, sensitive method of characterizing the dynamic performance of MR gradient systems. The accuracy of gradient time-courses is often compromised by field imperfections of various causes, including eddy currents and mechanical oscillations. Characterizing these perturbations is instrumental for corrections by pre-emphasis or post hoc signal processing. Herein, a gradient chain is treated as a linear time-invariant system, whose impulse response function is determined by measuring field responses to known gradient inputs. Triangular inputs are used to probe the system and response measurements are performed with a dynamic field camera consisting of NMR probes. In experiments on a whole-body MR system, it is shown that the proposed method yields impulse response functions of high temporal and spectral resolution. Besides basic properties such as bandwidth and delay, it also captures subtle features such as mechanically induced field oscillations. For validation, measured response functions were used to predict gradient field evolutions, which was achieved with an error below 0.2%. The field camera used records responses of various spatial orders simultaneously, rendering the method suitable also for studying cross-responses and dynamic shim systems. It thus holds promise for a range of applications, including pre-emphasis optimization, quality assurance, and image reconstruction.

A flexible and versatile monitoring system is presented, delivering camera-like access to otherwise hardly accessible field dynamics with nanotesla resolution. Its stand-alone nature enables field analysis even during unknown MR system states.

Model-based trajectory prediction enables high-quality image reconstruction for technically challenging sequences such as single-shot EPI and spiral imaging. It thus holds great promise for fast structural imaging and advanced neuroimaging techniques, including functional MRI, diffusion tensor imaging, and arterial spin labeling. The method can be based on a one-time system characterization as demonstrated by successful use of 3-year-old calibration data. Magn Reson Med 76:45-58, 2016. © 2015 Wiley Periodicals, Inc.

It has been demonstrated that artifacts due to physiologically induced dynamic field perturbations can be greatly reduced by retrospective image correction based on field monitoring. The necessity to perform such correction is greatest at high fields and for field-sensitive techniques such as T2*-weighted imaging.

Use of an expanded signal model largely overcomes the traditional vulnerability of spiral imaging with long readouts. It renders single-shot spirals competitive with echo-planar readouts and thus deploys shorter echo times and superior readout efficiency for diffusion imaging and further prospective applications. Magn Reson Med 77:83-91, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Feedback field control is an effective means of eliminating dynamic field distortions in MR systems. Third-order spatial control at an update time of 100 ms has proven sufficient to largely eliminate thermal and breathing effects in brain imaging at 7 Tesla.

Magnetic resonance imaging (MRI) of the human spinal cord at 7T has been demonstrated by a handful of research sites worldwide, and the spinal cord remains one of the areas in which higher fields and resolution could have high impact. The small diameter of the cord (∼1 cm) necessitates high spatial resolution to minimize partial volume effects between gray and white matter, and so MRI of the cord can greatly benefit from increased signal-to-noise ratio and contrasts at ultra-high field (UHF). Herein we review the current state of UHF spinal cord imaging. Technical challenges to successful UHF spinal cord MRI include radiofrequency (B) nonuniformities and a general lack of optimized radiofrequency coils, amplified physiological noise, and an absence of methods for robust B shimming along the cord to mitigate image distortions and signal losses. Numerous solutions to address these challenges have been and are continuing to be explored, and include novel approaches for signal excitation and acquisition, dynamic shimming and specialized shim coils, and acquisitions with increased coverage or optimal slice angulations.

Magnetic resonance imaging and spectroscopy of the spinal cord stand to benefit greatly from the increased signal-to-noise ratio of ultra-high field. However, ultra-high field also poses considerable technical challenges, especially related to static and dynamic B0 fields. Breathing causes the field to fluctuate with the respiratory cycle, giving rise to artifacts such as ghosting and apparent motion in images. We here investigated the spatial and temporal characteristics of breathing-induced B0 fields in the cervical spinal cord at 7T.We analyzed the magnitude and spatial profile of breathing-induced fields during breath-holds in an expired and inspired breathing state. We also measured the temporal field evolution during free breathing by acquiring a time series of fast phase images, and a principal component analysis was performed on the measured field evolution.In all subjects, the field shift was largest around the vertebral level of C7 and lowest at the top of the spinal cord. At C7, we measured peak-to-peak field fluctuations of 36 Hz on average during normal free breathing; increasing to on average 113 Hz during deep breathing. The first principal component could explain more than 90% of the field variations along the foot-head axis inside the spinal cord in all subjects.We further implemented a proof-of-principle shim correction, demonstrating the feasibility of using the shim system to compensate for the breathing-induced fields inside the spinal cord. Effective correction strategies will be crucial to unlock the full potential of ultra-high field for spinal cord imaging.