Spectral fitting using basis set modified by measured B0 field distribution

Monte Carlo study of metabolite correlations originating from spectral overlap

Monte Carlo simulations and a mathematical model of spectral fitting were used to study the correlations between metabolites with overlapping resonances. The dependence of the polarity and the magnitude of cross-correlation coefficients between overlapping metabolites on the spectral patterns of MRS signals was investigated. The results demonstrate the importance of quantifying metabolite correlations originating from spectral overlap as they may confound determination of correlations of biological origin. The findings also indicate that it is possible to minimize unwanted metabolite correlations by altering spectral patterns in the presence of significant spectral overlap.

Optimizing acquisition and fitting conditions for 1 H MR spectroscopy investigations in global brain pathology

PURPOSE

To optimize acquisition and fitting conditions for nonfocal disease in terms of voxel size and use of individual coil element data. Increasing the voxel size yields a higher signal-to-noise ratio, but leads to larger linewidths and more artifacts. Several ways to improve the spectral quality for large voxels are exploited and the optimal use of individual coil signals investigated.

METHODS

Ten human subjects were measured at 3 T using a 64-channel receive head coil with a semi-LASER localization sequence under optimized and deliberately mis-set field homogeneity. Eight different voxel sizes (8 to 99 cm³ ) were probed. Spectra were fitted either as weighted sums of the individual coil elements or simultaneously without summation. Eighteen metabolites were included in the fit model that also included the lineshapes from all coil elements as reflected in water reference data. Fitting errors for creatine, myo-Inositol and glutamate are reported as representative parameters to judge optimal acquisition and evaluation conditions.

RESULTS

Minimal Cramér-Rao lower bounds and thus optimal acquisition conditions were found for a voxel size of ~ 70 cm³ for the representative upfield metabolites. Spectral quality in terms of lineshape and artifact appearance was determined to differ substantially between coil elements. Simultaneous fitting of spectra from individual coil elements instead of traditional fitting of a weighted sum spectrum reduced Cramer-Rao lower bounds by up to 17% for large voxel sizes.

CONCLUSION

The optimal voxel size for best precision in determined metabolite content is surprisingly large. Such an acquisition condition is most relevant for detection of low-concentration metabolites, like NAD⁺ or phenylalanine, but also for longitudinal studies where very small alterations in metabolite content are targeted. In addition, simultaneous fitting of single channel spectra enforcing lineshape and coil sensitivity information proved to be superior to traditional signal combination with subsequent fitting.

Effect of linewidth on estimation of metabolic concentration when using water lineshape spectral model fitting for single voxel proton spectroscopy at 7 T

Good B₀ field homogeneity is considered an essential requirement to obtain high-quality MRS data. Many commonly used spectral fitting methods assume that all metabolite signals have Lorentzian or Gaussian shapes. However, B₀ inhomogeneity can both broaden the linewidth and modify the lineshape. In this study, it is hypothesized that a realistic metabolite fitting model, which accounts for B₀ homogeneity on the basis of the water lineshape, will improve the accuracy of estimation of metabolite concentrations. In-vivo water suppressed/unsuppressed single voxel spectroscopy signals were acquired under three different B₀ field homogeneity regimes. Individual realistic basis sets were created for each acquisition. Frequency-domain spectral fitting with LCModel was used to quantify the metabolite concentrations with fitting uncertainties given in terms of the Cramer-Rao lower bound. The quantification results obtained using the water lineshape basis set yielded similar concentrations independent of linewidth and showed a larger fitting error as the linewidth increased. The conventional approach, however quantifies metabolite concentrations with greater variations despite showing a supposedly improved fitting quality. The water lineshape basis set achieved single voxel spectroscopy accuracy that is less sensitive to the linewidth compared to the conventional spectral fitting method for the range of linewidths used in this study, but the precision deteriorated with worsening B₀ field inhomogeneity. The beneficial effect was ascribed to a reduction in the number of degrees of freedom when using the water lineshape to generate the basis set.

Multimodal imaging reveals a complex pattern of dysfunction in corticolimbic pathways in major depressive disorder

Major depressive disorder (MDD) is highly prevalent and associated with considerable morbidity, yet its pathophysiology remains only partially understood. While numerous studies have investigated the neurobiological correlates of MDD, most have used only a single neuroimaging modality. In particular, diffusion tensor imaging (DTI) studies have failed to yield uniform results. In this context, examining key tracts and using information from multiple neuroimaging modalities may better characterize potential abnormalities in the MDD brain. This study analyzed data from 30 participants with MDD and 26 healthy participants who underwent DTI, magnetic resonance spectroscopy (MRS), resting-state functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG). Tracts connecting the subgenual anterior cingulate cortex (sgACC) and the left and right amygdala, as well as connections to the left and right hippocampus and thalamus, were examined as target areas. Reduced fractional anisotropy (FA) was observed in the studied tracts. Significant differences in the correlation between medial prefrontal glutamate concentrations and FA were also observed between MDD and healthy participants along tracts connecting the sgACC and right amygdala; healthy participants exhibited a strong correlation but MDD participants showed no such relationship. In the same tract, a correlation was observed between FA and subsequent antidepressant response to ketamine infusion in MDD participants. Exploratory models also suggested group differences in the relationship between DTI, fMRI, and MEG measures. This study is the first to combine MRS, DTI, fMRI, and MEG data to obtain multimodal indices of MDD and antidepressant response and may lay the foundation for similar future analyses.

Quantification of in vivo transverse relaxation of glutamate in the frontal cortex of human brain by radio frequency pulse-driven longitudinal steady state

PURPOSE

The principal excitatory neurotransmitter glutamate plays an important role in many central nervous system disorders. Because glutamate resides predominantly in glutamatergic neurons, its relaxation properties reflect the intracellular environment of glutamatergic neurons. This study developed an improved echo time-independent technique for measuring transverse relaxation time and demonstrated that this radio frequency (RF)-driven longitudinal steady state technique can reliably measure glutamate transverse relaxation in the frontal cortex, where structural and functional abnormalities have been associated with psychiatric symptoms.

METHOD

Bloch and Monte Carlo simulations were performed to improve and optimize the RF-driven, longitudinal, steady-state (MARzss) technique to significantly shorten scan time and increase measurement precision. Optimized four-flip angle measurements at 0°,12°, 24°, and 36° with matched repetition time were used in nine human subjects (6F, 3M; 27-49 years old) at 7 Tesla. Longitudinal and transverse relaxation rates for glutamate were measured from a 2 x 2 x 2 cm3 voxel placed in three different brain regions: gray matter-dominated medial prefrontal lobe, white matter-dominated left frontal lobe, and gray matter-dominated occipital lobe.

RESULTS

Compared to the original MARzss technique, the scan time per voxel for measuring glutamate transverse relaxation was shortened by more than 50%. In the medial frontal, left frontal, and occipital voxels, the glutamate T2 was found to be 117.5±12.9 ms (mean ± standard deviation, n = 9), 107.3±12.1 (n = 9), and 124.4±16.6 ms (n = 8), respectively.

CONCLUSIONS

The improvements described in this study make the MARZSS technique a viable tool for reliably measuring glutamate relaxation from human subjects in a typical clinical setting. It is expected that this improved technique can be applied to characterize the intracellular environment of glutamatergic neurons in a variety of brain disorders.

Phase-encoded single-voxel magnetic resonance spectroscopy for suppressing outer volume signals at 7 Tesla

BACKGROUND

Due to imperfect slice profiles, unwanted signals from outside the selected voxel may significantly contaminate metabolite signals acquired using in vivo magnetic resonance spectroscopy (MRS). The use of outer volume suppression may exceed the SAR threshold, especially at high field.

OBJECTIVE

We propose using phase-encoding gradients after radiofrequency (RF) excitation to spatially encode unwanted signals originating from outside of the selected single voxel.

METHODS

Phase-encoding gradients were added to a standard single voxel point-resolved spectroscopy (PRESS) sequence which selects a 2 × 2 × 2 cm³ voxel. Subsequent spatial Fourier transform was used to encode outer volume signals. Phantom and in vivo experiments were performed using both phase-encoded PRESS and standard PRESS at 7 Tesla. Quantification was performed using fitting software developed in-house.

RESULTS

Both phantom and in vivo studies showed that spectra from the phase-encoded PRESS sequence were relatively immune from contamination by oil signals and have more accurate quantification results than spectra from standard PRESS spectra of the same voxel.

CONCLUSION

The proposed phase-encoded single-voxel PRESS method can significantly suppress outer volume signals that may appear in the spectra of standard PRESS without increasing RF power deposition.

High Field In vivo13C Magnetic Resonance Spectroscopy of Brain by Random Radiofrequency Heteronuclear Decoupling and Data Undersampling

In vivo¹³C magnetic resonance spectroscopy (MRS) is a unique and effective tool for studying dynamic human brain metabolism and the cycling of neurotransmitters. One of the major technical challenges for in vivo¹³C-MRS is the high radio frequency (RF) power necessary for heteronuclear decoupling. In the common practice of in vivo¹³C-MRS, alkanyl carbons are detected in the spectra range of 10-65 ppm. The amplitude of decoupling pulses has to be significantly greater than the large one-bond ¹H-¹³C scalar coupling (¹J_CH = 125-145 Hz). Two main proton decoupling methods have been developed: broadband stochastic decoupling and coherent composite or adiabatic pulse decoupling (e.g., WALTZ); the latter is widely used because of its efficiency and superb performance under inhomogeneous B₁ field. Because the RF power required for proton decoupling increases quadratically with field strength, in vivo¹³C-MRS using coherent decoupling is often limited to lowmagnetic fields [<=4 Tesla (T)] to keep the local and averaged specific absorption rate (SAR) under the safety guidelines established by the International Electrotechnical Commission (IEC) and the US Food and Drug Administration (FDA). Alternately, carboxylic/amide carbons are coupled to protons via weak long-range ¹H-¹³C scalar couplings, which can be decoupled using low RF power broadband stochastic decoupling. Recently, the carboxylic/amide ¹³C-MRS technique using low power random RF heteronuclear decoupling was safely applied to human brain studies at 7T. Here, we review the two major decoupling methods and the carboxylic/amide ¹³C-MRS with low power decoupling strategy. Further decreases in RF power deposition by frequency-domain windowing and time-domain random under-sampling are also discussed. Low RF power decoupling opens the possibility of performing in vivo¹³C experiments of human brain at very high magnetic fields (such as 11.7T), where signal-to-noise ratio as well as spatial and temporal spectral resolution are more favorable than lower fields.

Reconstruction of randomly under-sampled spectra for in vivo13C magnetic resonance spectroscopy

PURPOSE

Over the past decade, many techniques have been developed to reduce radiofrequency (RF) power deposition associated with proton decoupling in in vivo Carbon-13 (¹³C) magnetic resonance spectroscopy (MRS). In this work we propose a new strategy that uses data under-sampling to achieve reduction in RF power deposition.

MATERIALS AND METHODS

Essentially, proton decoupling is required only during randomly selected segments of data acquisition. By taking advantage of the sparse spectral pattern of the carboxylic/amide region of in vivo¹³C spectra of brain, we developed an iterative algorithm to reconstruct spectra from randomly under-sampled data. Fully sampled data were used as references. Reconstructed spectra were compared with the fully sampled references and evaluated using residuals and relative signal intensity errors.

RESULTS

Numerical simulations and in vivo experiments at 7Tesla demonstrated that this novel decoupling and data processing strategy can effectively reduce decoupling power deposition by greater than 30%.

CONCLUSION

This study proposes and evaluates a novel approach to acquire ¹³C data with reduced proton decoupling power deposition and reconstruct in vivo¹³C spectra of carboxylic/amide metabolite signals using randomly under-sampled data. Because proton decoupling is not needed over a significant portion of data acquisition, this novel approach can effectively reduce the required decoupling power and thus SAR. It opens the possibility of performing in vivo¹³C experiments of human brain at very high magnetic fields.