Effects of Frequency Drift on the Quantification of Gamma-Aminobutyric Acid Using MEGA-PRESS

Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy

BACKGROUND

Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have found a variety of applications on the process of MRS data. A quantification strategy compatible to DL base MRS spectral processing method is, therefore, useful.

MATERIALS AND METHODS

This study aims to investigate whether metabolite concentrations quantified using a convolutional neural network (CNN) based method, coupled with a scaling procedure that normalizes spectral signals for CNN input and linear regression, can effectively reflect variations in metabolite concentrations in IU across different brain regions with varying signal-to-noise ratios (SNR) and linewidths (LW). An error index based on standard error (SE) is proposed to indicate the confidence levels associated with metabolite predictions. In vivo MRS spectra were acquired from three brain regions of 43 subjects using a 3T system.

RESULTS

The metabolite concentrations in IU of five major metabolites, quantified using CNN and LCModel, exhibit similar ranges with Pearson's correlation coefficients ranging from 0.24 to 0.78. The SE of the metabolites shows a positive correlation with Cramer-Rao lower bound (CRLB) (r=0.46) and  absolute CRLB (r=0.81), calculated by multiplying CRLBs with the quantified metabolite content.

CONCLUSION

In conclusion, the CNN based method with the proposed scaling procedures can be employed to quantify in vivo MRS spectra and derive metabolites concentrations in IU. The SE can be used as error index, indicating predicted uncertainties for metabolites and sharing information similar to the absolute CRLB.

Frequency drift in MR spectroscopy at 3T

PURPOSE

Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.

METHOD

A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).

RESULTS

Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.

DISCUSSION

This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.

Pain sensitivity and the primary sensorimotor cortices: a multimodal neuroimaging study

ABSTRACT

The primary somatosensory cortex (SI) is a critical part of the neural substrate underlying interindividual differences in pain sensitivity. Here, we investigated whether resting-state functional connectivity, gray matter density (GMD), and GABA and Glx (glutamate and glutamine) levels of the sensorimotor cortices were related to pain thresholds and whether such imaging measures could predict high and low pain sensitivity. Functional, structural, and spectroscopic magnetic resonance data were obtained from 48 healthy participants together with pain thresholds of the right index finger. Left and right sensorimotor networks (SMN) were extracted by means of independent component analysis, and GMD was measured within the combined SMN by means of voxel-based morphometry. Spectroscopic data were acquired from the bilateral sensorimotor cortices. Within the left SMN, functional connectivity to the right SI correlated positively with pain thresholds. In addition, GMD in the left SI and the GABA laterality index correlated positively with pain thresholds. A positive correlation was also found between the GABA laterality index and the left SMN connectivity to the right SI. Finally, the above mentioned functional connectivity and GMD measures could correctly predict high and low pain sensitivity in 83.7% of the study population. In summary, we showed that interindividual differences in pain sensitivity were related to the resting-state functional connectivity, interhemispheric GABA tone, and GMD of the sensorimotor cortices. Furthermore, high and low pain sensitivity could be predicted with high accuracy using imaging measures from the primary sensorimotor cortices.

Retrospective correction of frequency drift in spectral editing: The GABA editing example

GABA levels can be measured using proton MRS with a two-step editing sequence. However due to the low concentration of GABA, long acquisition time is usually needed to achieve sufficient SNR to detect small differences in many psychiatric disorders. During this long scan time the frequency offset of the measured voxel can change because of magnetic field drift and patient movement. This drift will change the frequency of the editing pulse relative to that of metabolites, leading to errors in quantification. In this article we describe a retrospective method to correct for frequency drift in spectral editing. A series of reference signals for each metabolite was generated for a range of frequency offsets and then averaged together based on the history of frequency changes over the scan. These customized basis sets were used to fit the in vivo data. Our results demonstrate the effectiveness of the correction method and the remarkable robustness of a GABA editing technique with a top hat editing profile in the presence of frequency drift.

Automatic inhibitory function in the human somatosensory and motor cortices: An MEG-MRS study

While the automatic inhibitory function of the human cerebral cortex has been extensively investigated by means of electrophysiological recordings, the corresponding modulating neurochemical mechanisms remain unclear. We aimed to examine whether the primary somatosensory (SI) and primary motor cortical (MI) inhibitory function is associated with endogenous GABA levels. Eighteen young participants received paired-pulse and single-pulse electrical stimulation to the median nerve during magnetoencephalographic recordings. The SI sensory gating (SG), considered as an automatic inhibitory ability, was measured as the amplitude ratio of Stimulus 2 over Stimulus 1, in the paired-pulse paradigm. In addition, stimulus-induced beta activity, considered to originate from MI and also to be related to inhibitory function, was estimated using the single-pulse paradigm. The GABA+ concentration of the sensorimotor cortex was acquired from each subject by using magnetic resonance spectroscopy (MRS). A lower SG ratio in SI was significantly associated with an increased beta power in MI. More importantly, the beta rebound power, but not SI SG ratio, was positively correlated with GABA+ concentration. Our findings show a tight functional relationship between SI and MI during processing of automatic inhibition. GABA+ levels appear to be more closely related to the automatic inhibitory function of MI than SI.

Prospective frequency correction for macromolecule-suppressed GABA editing at 3T

PURPOSE

To investigate the effects of B₀ field offsets and drift on macromolecule (MM)-suppressed GABA-editing experiments, and to implement and test a prospective correction scheme. "Symmetric" editing schemes are proposed to suppress unwanted coedited MM signals in GABA editing.

MATERIALS AND METHODS

Full density-matrix simulations of both conventional (nonsymmetric) and symmetric MM-suppressed editing schemes were performed for the GABA spin system to evaluate their offset-dependence. Phantom and in vivo (15 subjects at 3T) GABA-edited experiments with symmetrical suppression of MM signals were performed to quantify the effects of field offsets on the total GABA+MM signal (designated GABA+). A prospective frequency correction method based on interleaved water referencing (IWR) acquisitions was implemented and its experimental performance evaluated during positive and negative drift.

RESULTS

Simulations show that the signal from MM-suppressed symmetrical editing schemes is an order of magnitude more susceptible to field offsets than the signal from nonsymmetric editing schemes. The MM-suppressed GABA signal changes by 8.6% per Hz for small field offsets. IWR significantly reduces variance in the field offset and measured GABA levels (both P < 0.001 by F-tests), maintaining symmetric suppression of MM signal.

CONCLUSION

Symmetrical editing schemes substantially increase the dependence of measurements on B₀ field offsets, which can arise due to patient movement and/or scanner instability. It is recommended that symmetrical editing should be used in combination with effective B₀ stabilization, such as that provided by IWR. J. Magn. Reson. Imaging 2016;44:1474-1482.