Spectroscopic localization by simultaneous acquisition of the double-spin and stimulated echoes

Estimation of subvoxel fat infiltration in neurodegenerative muscle disorders using quantitative multi-T2 analysis

MRI's T₂ relaxation time is a valuable biomarker for neuromuscular disorders and muscle dystrophies. One of the hallmarks of these pathologies is the infiltration of adipose tissue and a loss of muscle volume. This leads to a mixture of two signal components, from fat and from water, to appear in each imaged voxel, each having a specific T₂ relaxation time. In this proof-of-concept work, we present a technique that can separate the signals from water and from fat within each voxel, measure their separate T₂ values, and calculate their relative fractions. The echo modulation curve (EMC) algorithm is a dictionary-based technique that offers accurate and reproducible mapping of T₂ relaxation times. We present an extension of the EMC algorithm for estimating subvoxel fat and water fractions, alongside the T₂ and proton-density values of each component. To facilitate data processing, calf and thigh anatomy were automatically segmented using a fully convolutional neural network and FSLeyes software. The preprocessing included creating two signal dictionaries, for water and for fat, using Bloch simulations of the prospective protocol. Postprocessing included voxelwise fitting for two components, by matching the experimental decay curve to a linear combination of the two simulated dictionaries. Subvoxel fat and water fractions and relaxation times were generated and used to calculate a new quantitative biomarker, termed viable muscle index, and reflecting disease severity. This biomarker indicates the fraction of remaining muscle out of the entire muscle region. The results were compared with those using the conventional Dixon technique, showing high agreement (R = 0.98, p < 0.001). It was concluded that the new extension of the EMC algorithm can be used to quantify abnormal fat infiltration as well as identify early inflammatory processes corresponding to elevation in the T₂ value of the water (muscle) component. This new ability may improve the diagnostic accuracy of neuromuscular diseases, help stratification of patients according to disease severity, and offer an efficient tool for tracking disease progression.

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.

Magnetic resonance Spectrum simulator (MARSS), a novel software package for fast and computationally efficient basis set simulation

The aim of this study was to develop a novel software platform for the simulation of magnetic resonance spin systems, capable of simulating a large number of spatial points (128³ ) for large in vivo spin systems (up to seven coupled spins) in a time frame of the order of a few minutes. The quantum mechanical density-matrix formalism is applied, a coherence pathway filter is utilized for handling unwanted coherence pathways, and the 1D projection method, which provides a substantial reduction in computation time for a large number of spatial points, is extended to include sequences of an arbitrary number of RF pulses. The novel software package, written in MATLAB, computes a basis set of 23 different metabolites (including the two anomers of glucose, seven coupled spins) with 128³ spatial points in 26 min for a three-pulse experiment on a personal desktop computer. The simulated spectra are experimentally verified with data from both phantom and in vivo MEGA-sLASER experiments. Recommendations are provided regarding the various assumptions made when computing a basis set for in vivo MRS with respect to the number of spatial points simulated and the consideration of relaxation.

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 .

Application of phase rotation to STRESS localization scheme at 3 T

PURPOSE

Application of phase rotation to the STRESS (=STEAM+PRESS) localization scheme, to shorten echo time, minimize J-coupling dephasing and estimate B₁₊ inhomogeneity. STRESS (=STEAM + PRESS) simultaneously refocuses and acquires the double spin echo (SE₁₂₃ ) and stimulated echo (STE_- ) pathways, combining PRESS-like signal with lower chemical shift displacement as in STEAM. Phase rotation effectively separates coherence pathways, allows reduction of spoiling gradients moments leading to reduction in echo time. Implementing it in STRESS allows one to individually phase-correct SE₁₂₃ and STE_- prior to combination. Moreover, B₁₊ inhomogeneity can be assessed by comparing the measured ratio of resonance intensities of SE₁₂₃ and STE_- pathways to the simulated one.

METHODS

In vivo spectra were acquired from a single voxel placed in the sensory-motor cortex of 10 healthy volunteers, using phase rotation-STRESS/PRESS/STEAM sequences at 3 T scanner. The phases of each slice-selective pulse were incremented by Δϕ1/2/3=22.5°/-45°/45°.

RESULTS

Phase rotation-STRESS showed quantification accuracy (% Cramer Rao lower bounds) and reproducibility (% coefficients of variation) comparable to PRESS and STEAM, in both phantoms and in vivo study. Minimal echo time achieved was 13 ms.

CONCLUSION

Phase rotation complements STRESS by reducing echo time, allowing processing of each pathway individually prior to addition and providing B₁₊ estimation in single voxel proton magnetic resonance spectroscopy. Magn Reson Med 79:2481-2490, 2018. © 2017 International Society for Magnetic Resonance in Medicine.