Application of phase rotation to STRESS localization scheme at 3 T

Improved detection limits of J-coupled neurometabolites in the human brain at 7 T with a J-refocused sLASER sequence

In a standard spin echo, the time evolution due to homonuclear couplings is not reversed, leading to echo time (TE)-dependent modulation of the signal amplitude and signal loss in the case of overlapping multiplet resonances. This has an adverse effect on quantification of several important metabolites such as glutamate and glutamine. Here, we propose a J-refocused variant of the sLASER sequence (J-sLASER) to improve quantification of J-coupled metabolites at ultrahigh field (UHF). The use of the sLASER sequence is particularly advantageous at UHF as it minimizes chemical shift displacement error and results in relatively homogenous refocusing. We simulated the MRS signal from brain metabolites over a broad range of TE values with sLASER and J-sLASER, and showed that the signal of J-coupled metabolites was increased with J-sLASER with TE values up to ~80 ms. We further simulated "brain-like" spectra with both sequences at the shortest TE available on our scanner. We showed that, despite the slightly longer TE, the J-sLASER sequence results in significantly lower Cramer-Rao lower bounds (CRLBs) for J-coupled metabolites compared with those obtained with sLASER. Following phantom validation, we acquired spectra from two brain regions in 10 healthy volunteers (age 38 ± 15 years) using both sequences. We showed that using J-sLASER results in a decrease of CRLBs for J-coupled metabolites. In particular, we measured a robust ~38% decrease in the mean CRLB (glutamine) in parietal white matter and posterior cingulate cortex (PCC). We further showed, in 10 additional healthy volunteers (age 34 ± 15 years), that metabolite quantification following two separate acquisitions with J-sLASER in the PCC was repeatable. The improvement in quantification of glutamine may in turn improve the independent quantification of glutamate, the main excitatory neurotransmitter in the brain, and will simultaneously help to track possible modulations of glutamine, which is a key player in the glutamatergic cycle in astrocytes.

What is the optimal schedule for multiparametric MRS? A magnetic resonance fingerprinting perspective

Clinical magnetic resonance spectroscopy (MRS) mainly concerns itself with the quantification of metabolite concentrations. Metabolite relaxation values, which reflect the microscopic state of specific cellular and sub-cellular environments, could potentially hold additional valuable information, but are rarely acquired within clinical scan times. By varying the flip angle, repetition time and echo time in a preset way (termed a schedule), and matching the resulting signals to a pre-generated dictionary - an approach dubbed magnetic resonance fingerprinting - it is possible to encode the spins' relaxation times into the acquired signal, simultaneously quantifying multiple tissue parameters for each metabolite. Herein, we optimized the schedule to minimize the averaged root mean square error (RMSE) across all estimated parameters: concentrations, longitudinal and transverse relaxation time, and transmitter inhomogeneity. The optimal schedules were validated in phantoms and, subsequently, in a cohort of healthy volunteers, in a 4.5 mL parietal white matter single voxel and an acquisition time under 5 minutes. The average intra-subject, inter-scan coefficients of variation (CVs) for metabolite concentrations, T₁ and T₂ relaxation times were found to be 3.4%, 4.6% and 4.7% in-vivo, respectively, averaged over all major singlets. Coupled metabolites were quantified using the short echo time schedule entries and spectral fitting, and reliable estimates of glutamate+glutamine, glutathione and myo-inositol were obtained.

Realistic head-shaped phantom with brain-mimicking metabolites for 7 T spectroscopy and spectroscopic imaging

PURPOSE

Moving to ultra-high fields (≥7 T), the inhomogeneity of both RF (B1 ) and static (B0 ) magnetic fields increases, which further motivates us to design a realistic head-shaped phantom, especially for spectroscopic imaging. Such phantoms provide images similar to the human brain and serve as a reliable tool for developing and examining methods in MRI. This study aims to develop and characterize a realistic head-shaped phantom filled with brain-mimicking metabolites for MRS and magnetic resonance spectroscopic imaging in a 7 T MRI scanner.

METHODS

A 3D head-shaped container with three sections-mimicking brain, muscle and precranial lipid-was constructed. The phantom was designed to provide robustness to heating, mechanical damage and leakage, with easy refilling. The head's shape and the agarose mixture were optimized to provide B0 and B1 distributions and T1 /T2 relaxation values similar to those of human brain. Eight brain-tissue-mimicking metabolites were included for spectroscopy. The phantom was evaluated for localized spectroscopy, fast spectroscopic imaging and fat suppression.

RESULTS

The B0 and B1 maps showed distribution similar to that of human brain, with increased B0 inhomogeneity near the nasal and ear areas and reduced B1 in the temporal lobe and brain stem regions, as expected in vivo. The metabolites' concentrations were verified by single-voxel spectroscopy, showing an average deviation of 11%. Fast spectroscopic imaging and imaging with fat suppression were demonstrated.

CONCLUSION

A 3D head-shaped phantom for human brain imaging and spectroscopic imaging in 7 T MRI was demonstrated, making it a realistic phantom for methodology development at 7 T.

Potential clinical impact of multiparametric quantitative MR spectroscopy in neurological disorders: A review and analysis

PURPOSE

Unlike conventional MR spectroscopy (MRS), which only measures metabolite concentrations, multiparametric MRS also quantifies their longitudinal (T1 ) and transverse (T2 ) relaxation times, as well as the radiofrequency transmitter inhomogeneity (B1+ ). To test whether knowledge of these additional parameters can improve the clinical utility of brain MRS, we compare the conventional and multiparametric approaches in terms of expected classification accuracy in differentiating controls from patients with neurological disorders.

THEORY AND METHODS

A literature review was conducted to compile metabolic concentrations and relaxation times in a wide range of neuropathologies and regions of interest. Simulations were performed to construct receiver operating characteristic curves and compute the associated areas (area under the curve) to examine the sensitivity and specificity of MRS for detecting each pathology in each region. Classification accuracy was assessed using metabolite concentrations corrected using population-averages for T1 , T2 , and B1+ (conventional MRS); using metabolite concentrations corrected using per-subject values (multiparametric MRS); and using an optimal linear multiparametric estimator comprised of the metabolites' concentrations and relaxation constants (multiparametric MRS). Additional simulations were conducted to find the minimal intra-subject precision needed for each parameter.

RESULTS

Compared with conventional MRS, multiparametric approaches yielded area under the curve improvements for almost all neuropathologies and regions of interest. The median area under the curve increased by 0.14 over the entire dataset, and by 0.24 over the 10 instances with the largest individual increases.

CONCLUSIONS

Multiparametric MRS can substantially improve the clinical utility of MRS in diagnosing and assessing brain pathology, motivating the design and use of novel multiparametric sequences.

Analysis of magnetization transfer (MT) influence on quantitative mapping of T2 relaxation time

PURPOSE

Multi-echo spin-echo (MESE) protocol is the most effective tool for mapping T₂ relaxation in vivo. Still, MESE extensive use of radiofrequency pulses causes magnetization transfer (MT)-related bias of the water signal, instigated by the presence of macromolecules (MMP). Here, we analyze the effects of MT on MESE signal, alongside their impact on quantitative T₂ measurements.

METHODS

Study used 3 models: in vitro urea phantom, ex vivo horse brain, and in vivo human brain. MT ratio (MTR) was measured between single-SE and MESE protocols under different scan settings including varying echo train lengths, number of slices, and inter-slice gap. MTR and T₂ values were extracted for each model and protocol.

RESULTS

MT interactions biased MESE signals, and in certain settings, the corresponding T₂ values. T₂ underestimation of up to 4.3% was found versus single-SE values in vitro and up to 13.8% ex vivo, correlating with the MMP content. T₂ bias originated from intra-slice saturation of the MMP, rather than from indirect saturation in multi-slice acquisitions. MT-related signal attenuation was caused by slice crosstalk and/or partial T₁ recovery, whereas smaller contribution was caused by MMP interactions. Inter-slice gap had a similar effect on in vivo MTR (21.2%), in comparison to increasing the number of slices (18.9%).

CONCLUSIONS

MT influences MESE protocols either by uniformly attenuating the entire echo train or by cumulatively attenuating the signal along the train. Although both processes depend on scan settings and MMP content, only the latter will cause underestimation of T₂ .