Rosette spectroscopic imaging: optimal parameters for alias-free, high sensitivity spectroscopic imaging

A silent echo-planar spectroscopic imaging readout with high spectral bandwidth MRSI using an ultrasonic gradient axis

PURPOSE

We present a novel silent echo-planar spectroscopic imaging (EPSI) readout, which uses an ultrasonic gradient insert to accelerate MRSI while producing a high spectral bandwidth (20 kHz) and a low sound level.

METHODS

The ultrasonic gradient insert consisted of a single-axis (z-direction) plug-and-play gradient coil, powered by an audio amplifier, and produced 40 mT/m at 20 kHz. The silent EPSI readout was implemented in a phase-encoded MRSI acquisition. Here, the additional spatial encoding provided by this silent EPSI readout was used to reduce the number of phase-encoding steps. Spectroscopic acquisitions using phase-encoded MRSI, a conventional EPSI-readout, and the silent EPSI readout were performed on a phantom containing metabolites with resonance frequencies in the ppm range of brain metabolites (0-4 ppm). These acquisitions were used to determine sound levels, showcase the high spectral bandwidth of the silent EPSI readout, and determine the SNR efficiency and the scan efficiency.

RESULTS

The silent EPSI readout featured a 19-dB lower sound level than a conventional EPSI readout while featuring a high spectral bandwidth of 20 kHz without spectral ghosting artifacts. Compared with phase-encoded MRSI, the silent EPSI readout provided a 4.5-fold reduction in scan time. In addition, the scan efficiency of the silent EPSI readout was higher (82.5% vs. 51.5%) than the conventional EPSI readout.

CONCLUSIONS

We have for the first time demonstrated a silent spectroscopic imaging readout with a high spectral bandwidth and low sound level. This sound reduction provided by the silent readout is expected to have applications in sound-sensitive patient groups, whereas the high spectral bandwidth could benefit ultrahigh-field MR systems.

Proton Free Induction Decay MRSI at 7T in the Human Brain Using an Egg-Shaped Modified Rosette K-Space Trajectory

Purpose

1.1 Proton ( 1 H)-MRSI via spatial-spectral encoding poses high demands on gradient hardware at ultra-high fields and high-resolutions. Rosette trajectories help alleviate these problems, but at reduced SNR-efficiency due to their k-space densities not matching any desired k-space filter. We propose modified rosette trajectories, which more closely match a Hamming filter, and thereby improve SNR performance while still staying within gradient hardware limitations and without prolonging scan time.

Methods

1.2Analytical and synthetic simulations were validated with phantom and in vivo measurements at 7 T. The rosette and modified rosette trajectories were measured in five healthy volunteers in six minutes in a 2D slice in the brain. A 3D sequence was measured in one volunteer within 19 minutes. The SNR, linewidth, CRLBs, lipid contamination and data quality of the proposed modified rosette trajectory were compared to the rosette trajectory.

Results

1.3Using the modified rosette trajectories, an improved k-space weighting function was achieved resulting in an increase of up to 12% in SNR compared to rosette's dependent on the two additional trajectory parameters. Similar results were achieved for the theoretical SNR calculation based on k-space densities, as well as when using the pseudo-replica method for simulated, in-vivo and phantom data. The CRLBs improved slightly, but non-significantly for the modified rosette trajectories, while the linewidths and lipid contamination remained similar.

Conclusion

1.4By improving the rosette trajectory's shape, modified rosette trajectories achieved higher SNR at the same scan time and data quality.

High-resolution proton metabolic mapping of the human brain at 7 T using free induction decay rosette spectroscopic imaging

Magnetic resonance spectroscopic imaging (MRSI) provides information about the spatial distribution of metabolites in the brain. These metabolite maps can be valuable in diagnosing central nervous system pathology. However, MRSI generally suffers from a long acquisition time, poor spatial resolution, and a low metabolite signal-to-noise ratio (SNR). Ultrahigh field strengths (≥ 7 T) can benefit MRSI with an improved SNR and allow high-resolution metabolic mapping. Non-Cartesian spatial-spectral encoding techniques, such as rosette spectroscopic imaging, can efficiently sample spatial and temporal domains, which significantly reduces the imaging time and enables high-resolution metabolic mapping in a clinically relevant scan time. In the current study, high-resolution (in-plane resolution of 2 × 2 mm2 ) mapping of proton (1 H) metabolites in the human brain at 7 T, is demonstrated. Five healthy subjects participated in the study. Using a time-efficient rosette trajectory and short TR/TE free induction decay MRSI, high-resolution maps of 1 H metabolites were obtained in a clinically relevant imaging time (6 min). Suppression of the water signal was achieved with an optimized water suppression enhanced through T1 effects approach and lipid removal was performed using L2 -regularization in the postprocessing. Spatial distributions of N-acetyl-aspartate, total choline, creatine, N-acetyl-aspartyl glutamate, myo-inositol, and glutamate were generated with Cramer-Rao lower bounds of less than 20%.

Atlas-Based Adaptive Hadamard-Encoded MR Spectroscopic Imaging at 3T

BACKGROUND

This study aimed to develop a time-efficient method of acquiring simultaneous, dual-slice MR spectroscopic imaging (MRSI) for the evaluation of brain metabolism.

METHODS

Adaptive Hadamard-encoded pulses were developed and integrated with atlas-based automatic prescription. The excitation profiles were evaluated via simulation, phantom and volunteer experiments. The feasibility of γ-aminobutyric acid (GABA)-edited dual-slice MRSI was also assessed.

RESULTS

The signal between slices in the dual-band MRSI was less than 1% of the slice profiles. Data from a homemade phantom containing separate, interfacing compartments of creatine and acetate solutions demonstrated ~0.4% acetate signal contamination relative to the amplitude in the excited creatine compartment. The normalized signal-to-noise ratios from atlas-based acquisitions in volunteers were found to be comparable between dual-slice, Hadamard-encoded MRSI and 3D acquisitions. The mean and standard deviation of the coefficients of variation for NAA/Cho from the repeated volunteer scans were 8.2% ± 0.8% and 10.1% ± 3.7% in the top and bottom slices, respectively. GABA-edited, dual-slice MRSI demonstrated simultaneous detection of signals from GABA and coedited macromolecules (GABA+) from both superior grey and deep grey regions of volunteers.

CONCLUSION

This study demonstrated a fully automated dual-slice MRSI acquisition using atlas-based automatic prescription and adaptive Hadamard-encoded pulses.

Feasibility of spinal cord imaging at 7 T using rosette trajectory with magnetization transfer preparation and compressed sensing

MRI is a valuable diagnostic tool to investigate spinal cord (SC) pathology. SC MRI can benefit from the increased signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) at ultra-high fields such as 7 T. However, SC MRI acquisitions with routine Cartesian readouts are prone to image artifacts caused by physiological motion. MRI acquisition techniques with non-Cartesian readouts such as rosette can help reduce motion artifacts. The purpose of this study was to demonstrate the feasibility of high-resolution SC imaging using rosette trajectory with magnetization transfer preparation (MT-prep) and compressed sensing (CS) at 7 T. Five healthy volunteers participated in the study. Images acquired with rosette readouts demonstrated reduced motion artifacts compared to the standard Cartesian readouts. The combination of multi-echo rosette-readout images improved the CNR by approximately 50% between the gray matter (GM) and white matter (WM) compared to single-echo images. MT-prep images showed excellent contrast between the GM and WM with magnetization transfer ratio (MTR) and cerebrospinal fluid normalized MT signal (MTCSF) = 0.12 ± 0.017 and 0.74 ± 0.013, respectively, for the GM; and 0.18 ± 0.011 and 0.58 ± 0.009, respectively, for the WM. Under-sampled acquisition using rosette readout with CS reconstruction demonstrated up to 6 times faster scans with comparable image quality as the fully-sampled acquisition.

Deuterium echo-planar spectroscopic imaging (EPSI) in the human liver in vivo at 7 T

PURPOSE

To demonstrate the feasibility of deuterium echo-planar spectroscopic imaging (EPSI) to accelerate 3D deuterium metabolic imaging in the human liver at 7 T.

METHODS

A deuterium EPSI sequence, featuring a Hamming-weighted k-space acquisition pattern for the phase-encoding directions, was implemented. Three-dimensional deuterium EPSI and conventional MRSI were performed on a water/acetone phantom and in vivo in the human liver at natural abundance. Moreover, in vivo deuterium EPSI measurements were acquired after oral administration of deuterated glucose. The effect of acquisition time on SNR was evaluated by retrospectively reducing the number of averages.

RESULTS

The SNR of natural abundance deuterated water signal in deuterium EPSI was 6.5% and 5.9% lower than that of MRSI in the phantom and in vivo experiments, respectively. In return, the acquisition time of in vivo EPSI data could be reduced retrospectively to 2 min, beyond the minimal acquisition time of conventional MRSI (of 20 min in this case), while still leaving sufficient SNR. Three-dimensional deuterium EPSI, after administration of deuterated glucose, enabled monitoring of hepatic glucose dynamics with full liver coverage, a spatial resolution of 20 mm isotropic, and a temporal resolution of 9 min 50 s, which could retrospectively be shortened to 2 min.

CONCLUSION

In this work, we demonstrate the feasibility of accelerated 3D deuterium metabolic imaging of the human liver using deuterium EPSI. The acceleration obtained with EPSI can be used to increase temporal and/or spatial resolution, which will be valuable to study tissue metabolism of deuterated compounds over time.

Artifact suppression in readout-segmented consistent K-t space EPSI (RS-COKE) for fast 1 H spectroscopic imaging at 7 T

PURPOSE

Fast proton (¹ H) MRSI is an important diagnostic tool for clinical investigations, providing metabolic and spatial information. MRSI at 7 T benefits from increased SNR and improved separation of peaks but requires larger spectral widths. RS-COKE (Readout-Segmented Consistent K-t space Epsi) is an echo planar spectroscopic imaging (Epsi) variant capable to support the spectral width required for human brain metabolites spectra at 7 T. However, mismatches between readout segments lead to artifacts, particularly when subcutaneous lipid signals are not suppressed. In this study, these mismatches and their effects are analyzed and reduced.

METHODS

The following corrections to the data were performed: i) frequency-dependent phase corrections; ii) k-space trajectory corrections, derived from short reference scans; and iii) smoothing of data at segment transitions to mitigate the effect of residual mismatches. The improvement was evaluated by performing single-slice RS-COKE on a head-shaped phantom with a "lipid" layer and healthy subjects, using varying resolutions and durations ranging from 4.1 × 4.7 × 15 mm³ in 5:46 min to 3.1 × 3.3 × 15 mm³ in 13:07 min.

RESULTS

Artifacts arising from the readout-segmented acquisition were substantially reduced, thus providing high-quality spectroscopic imaging in phantom and human scans. LCModel fitting of the human data resulted in a relative Cramer-Rao lower bounds within 6% for NAA, Cr, and Cho images in the majority of the voxels.

CONCLUSION

Using the new reference scans and reconstruction steps, RS-COKE was able to deliver fast ¹ H MRSI at 7 T, overcoming the spectral width limitation of standard EPSI at this field strength.

Proton metabolic mapping of the brain at 7 T using a two-dimensional free induction decay-echo-planar spectroscopic imaging readout with lipid suppression

The increased signal-to-noise ratio (SNR) and chemical shift dispersion at high magnetic fields (≥7 T) have enabled neuro-metabolic imaging at high spatial resolutions. To avoid very long acquisition times with conventional magnetic resonance spectroscopic imaging (MRSI) phase-encoding schemes, solutions such as pulse-acquire or free induction decay (FID) sequences with short repetition time and inner volume selection methods with acceleration (echo-planar spectroscopic imaging [EPSI]), have been proposed. With the inner volume selection methods, limited spatial coverage of the brain and long echo times may still impede clinical implementation. FID-MRSI sequences benefit from a short echo time and have a high SNR per time unit; however, contamination from strong extra-cranial lipid signals remains a problem that can hinder correct metabolite quantification. L2-regularization can be applied to remove lipid signals in cases with high spatial resolution and accurate prior knowledge. In this work, we developed an accelerated two-dimensional (2D) FID-MRSI sequence using an echo-planar readout and investigated the performance of lipid suppression by L2-regularization, an external crusher coil, and the combination of these two methods to compare the resulting spectral quality in three subjects. The reduction factor of lipid suppression using the crusher coil alone varies from 2 to 7 in the lipid region of the brain boundary. For the combination of the two methods, the average lipid area inside the brain was reduced by 2% to 38% compared with that of unsuppressed lipids, depending on the subject's region of interest. 2D FID-EPSI with external lipid crushing and L2-regularization provides high in-plane coverage and is suitable for investigating brain metabolite distributions at high fields.

Cardiac MRF using rosette trajectories for simultaneous myocardial T1, T2, and proton density fat fraction mapping

The goal of this work is to extend prior work on cardiac MR Fingerprinting (cMRF) using rosette k-space trajectories to enable simultaneous T₁, T₂, and proton density fat fraction (PDFF) mapping in the heart. A rosette trajectory designed for water-fat separation at 1.5T was used in a 2D ECG-triggered 15-heartbeat cMRF sequence. Water and fat specific T₁ and T₂ maps were generated from the cMRF data. A PDFF map was also retrieved using Hierarchical IDEAL by segmenting the rosette cMRF data into multiple echoes. The accuracy of rosette cMRF in T₁, T₂, and PDFF quantification was validated in the ISMRM/NIST phantom and an in-house built fat fraction phantom, respectively. The proposed method was also applied for myocardial tissue mapping of healthy subjects and cardiac patients at 1.5T. T₁, T₂, and PDFF values measured using rosette cMRF in the ISMRM/NIST phantom and the fat fraction phantom agreed well with the reference values. In 16 healthy subjects, rosette cMRF yielded T₁ values which were 80~90 ms higher than spiral cMRF and MOLLI. T₂ values obtained using rosette cMRF were ~3 ms higher than spiral cMRF and ~5 ms lower than conventional T₂-prep bSSFP method. Rosette cMRF was also able to detect abnormal T₁ and T₂ values in cardiomyopathy patients and may provide more accurate maps due to effective fat suppression. In conclusion, this study shows that rosette cMRF has the potential for efficient cardiac tissue characterization through simultaneous quantification of myocardial T₁, T₂, and PDFF.

Emerging methods and applications of ultra-high field MR spectroscopic imaging in the human brain

Magnetic Resonance Spectroscopic Imaging (MRSI) of the brain enables insights into the metabolic changes and fluxes in diseases such as tumors, multiple sclerosis, epilepsy, or hepatic encephalopathy, as well as insights into general brain functionality. However, the routine application of MRSI is mostly hampered by very low signal-to-noise ratios (SNR) due to the low concentrations of metabolites, about 10000 times lower than water. Furthermore, MRSI spectra have a dense information content with many overlapping metabolite resonances, especially for proton MRSI. MRI scanners at ultra-high field strengths, like 7 T or above, offer the opportunity to increase SNR, as well as the separation between resonances, thus promising to solve both challenges. Yet, MRSI at ultra-high field strengths is challenged by decreased B0- and B1-homogeneity, shorter T2 relaxation times, stronger chemical shift displacement errors, and aggravated lipid contamination. Therefore, to capitalize on the advantages of ultra-high field strengths, these challenges must be overcome. This review focuses on the challenges MRSI of the human brain faces at ultra-high field strength, as well as the possible applications to this date.

MR spectroscopic imaging at 3 T and outcomes in surgical epilepsy

For the spectroscopic assessment of brain disorders that require large-volume coverage, the requirements of RF performance and field homogeneity are high. For epilepsy, this is also challenging given the inter-patient variation in location, severity and subtlety of anatomical identification and its tendency to involve the temporal region. We apply a targeted method to examine the utility of large-volume MR spectroscopic imaging (MRSI) in surgical epilepsy patients, implementing a two-step acquisition, comprised of a 3D acquisition to cover the fronto-parietal regions, and a contiguous parallel two-slice Hadamard-encoded acquisition to cover the temporal-occipital region, both with T_R /T_E = 2000/40 ms and matched acquisition times. With restricted (static, first/second-order) B₀ shimming in their respective regions, the Cramér-Rao lower bounds for creatine from the temporal lobe two-slice Hadamard and frontal-parietal 3D acquisition are 8.1 ± 2.2% and 6.3 ± 1.9% respectively. The datasets are combined to provide a total 60 mm axial coverage over the frontal, parietal and superior temporal to middle temporal-occipital regions. We applied these acquisitions at a nominal 400 mm³ voxel resolution in n = 27 pre-surgical epilepsy patients and n = 20 controls. In controls, 86.6 ± 3.2% voxels with at least 50% tissue (white + gray matter, excluding CSF) survived spectral quality inclusion criteria. Since all patients were clinically followed for at least 1 year after surgery, seizure frequency outcome was available for all. The MRSI measurements of the total fractional metabolic dysfunction (characterized by the Cr/NAA metric) in FreeSurfer MRI gray matter segmented regions, in the patients compared with the controls, exhibited a significant Spearman correlation with post-surgical outcome. This finding suggests that a larger burden of metabolic dysfunction is seen in patients with poorer post-surgical seizure control.

Fast, regional three-dimensional hybrid (1D-Hadamard 2D-rosette) proton MR spectroscopic imaging in the human temporal lobes

1 H-MRSI is commonly performed with gradient phase encoding, due to its simplicity and minimal radio frequency (RF) heating (specific absorption rate). Its two well-known main problems-(i) "voxel bleed" due to the intrinsic point-spread function, and (ii) chemical shift displacement error (CSDE) when slice-selective RF pulses are used, which worsens with increasing volume of interest (VOI) size-have long become accepted as unavoidable. Both problems can be mitigated with Hadamard multislice RF encoding. This is demonstrated and quantified with numerical simulations, in a multislice phantom and in five healthy young adult volunteers at 3 T, targeting a 2-cm thick temporal lobe VOI through the bilateral hippocampus. This frequently targeted region (e.g. in epilepsy and Alzheimer's disease) is subject to strong, 1-2 ppm.cm-1 regional B0, susceptibility gradients that can dramatically reduce the signal-to-noise ratio (SNR) and water suppression effectiveness. The chemical shift imaging (CSI) sequence used a 3-ms Shinnar-Le Roux (SLR) 90° RF pulse, acquiring eight steps in the slice direction. The Hadamard sequence acquired two overlapping slices using the same SLR 90° pulses, under twofold stronger gradients that proportionally halved the CSDE. Both sequences used 2D 20 × 20 rosette spectroscopic imaging (RSI) for in-plane spatial localization and both used RF and gradient performance characteristics that are easily met by all modern MRI instruments. The results show that Hadamard spectroscopic imaging (HSI) suffered dramatically less signal bleed within the VOI compared with CSI (<1% vs. approximately 26% in simulations; and 5%-8% vs. >50%) in a phantom specifically designed to test these effects. The voxels' SNR per unit volume per unit time was also 40% higher for HSI. In a group of five healthy volunteers, we show that HSI with in-plane 2D-RSI facilitates fast, 3D multivoxel encoding at submilliliter spatial resolution, over the bilateral human hippocampus, in under 10 min, with negligible CSDE, spectral and spatial contamination and more than 6% improved SNR per unit time per unit volume.

Accelerated MR spectroscopic imaging-a review of current and emerging techniques

Over more than 30 years in vivo MR spectroscopic imaging (MRSI) has undergone an enormous evolution from theoretical concepts in the early 1980s to the robust imaging technique that it is today. The development of both fast and efficient sampling and reconstruction techniques has played a fundamental role in this process. State-of-the-art MRSI has grown from a slow purely phase-encoded acquisition technique to a method that today combines the benefits of different acceleration techniques. These include shortening of repetition times, spatial-spectral encoding, undersampling of k-space and time domain, and use of spatial-spectral prior knowledge in the reconstruction. In this way in vivo MRSI has considerably advanced in terms of spatial coverage, spatial resolution, acquisition speed, artifact suppression, number of detectable metabolites and quantification precision. Acceleration not only has been the enabling factor in high-resolution whole-brain 1 H-MRSI, but today is also common in non-proton MRSI (31 P, 2 H and 13 C) and applied in many different organs. In this process, MRSI techniques had to constantly adapt, but have also benefitted from the significant increase of magnetic field strength boosting the signal-to-noise ratio along with high gradient fidelity and high-density receive arrays. In combination with recent trends in image reconstruction and much improved computation power, these advances led to a number of novel developments with respect to MRSI acceleration. Today MRSI allows for non-invasive and non-ionizing mapping of the spatial distribution of various metabolites' tissue concentrations in animals or humans, is applied for clinical diagnostics and has been established as an important tool for neuro-scientific and metabolism research. This review highlights the developments of the last five years and puts them into the context of earlier MRSI acceleration techniques. In addition to 1 H-MRSI it also includes other relevant nuclei and is not limited to certain body regions or specific applications.

Accelerated radial echo-planar spectroscopic imaging using golden angle view-ordering and compressed-sensing reconstruction with total variation regularization

PURPOSE

To implement a novel, accelerated, 2D radial echo-planar spectroscopic imaging (REPSI) sequence using undersampled radial k-space trajectories and compressed-sensing reconstruction, and to compare results with those from an undersampled Cartesian spectroscopic sequence.

METHODS

The REPSI sequence was implemented using golden-angle view-ordering on a 3T MRI scanner. Radial and Cartesian echo-planar spectroscopic imaging (EPSI) data were acquired at six acceleration factors, each with time-equivalent scan durations, and reconstructed using compressed sensing with total variation regularization. Results from prospectively and retrospectively undersampled phantom and in vivo brain data were compared over estimated concentrations and Cramer-Rao lower-bound values, normalized RMS errors of reconstructed metabolite maps, and percent absolute differences between fully sampled and reconstructed spectroscopic images.

RESULTS

The REPSI method with compressed sensing is able to tolerate greater reductions in scan time compared with EPSI. The reconstruction and quantitation metrics (i.e., spectral normalized RMS error maps, metabolite map normalized RMS error values [e.g., for total N-acetyl asparate, REPSI = 9.4% vs EPSI = 16.3%; acceleration factor = 2.5], percent absolute difference maps, and concentration and Cramer-Rao lower-bound estimates) showed that accelerated REPSI can reduce the scan time by a factor of 2.5 while retaining image and quantitation quality.

CONCLUSION

Accelerated MRSI using undersampled radial echo-planar acquisitions provides greater reconstruction accuracy and more reliable quantitation for a range of acceleration factors compared with time-equivalent compressed-sensing reconstructions of undersampled Cartesian EPSI. Compared to the Cartesian approach, radial undersampling with compressed sensing could help reduce 2D spectroscopic imaging acquisition time, and offers a better trade-off between imaging speed and quality.

Myocardial T1 and T2 quantification and water-fat separation using cardiac MR fingerprinting with rosette trajectories at 3T and 1.5T

PURPOSE

This work aims to develop an approach for simultaneous water-fat separation and myocardial T₁ and T₂ quantification based on the cardiac MR fingerprinting (cMRF) framework with rosette trajectories at 3T and 1.5T.

METHODS

Two 15-heartbeat cMRF sequences with different rosette trajectories designed for water-fat separation at 3T and 1.5T were implemented. Water T₁ and T₂ maps, water image, and fat image were generated with B₀ inhomogeneity correction using a B₀ map derived from the cMRF data themselves. The proposed water-fat separation rosette cMRF approach was validated in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom and water/oil phantoms. It was also applied for myocardial tissue mapping of healthy subjects at both 3T and 1.5T.

RESULTS

Water T₁ and T₂ values measured using rosette cMRF in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom agreed well with the reference values. In the water/oil phantom, oil was well suppressed in the water images and vice versa. Rosette cMRF yielded comparable T₁ but 2~3 ms higher T₂ values in the myocardium of healthy subjects than the original spiral cMRF method. Epicardial fat deposition was also clearly shown in the fat images.

CONCLUSION

Rosette cMRF provides fat images along with myocardial T₁ and T₂ maps with significant fat suppression. This technique may improve visualization of the anatomical structure of the heart by separating water and fat and could provide value in diagnosing cardiac diseases associated with fibrofatty infiltration or epicardial fat accumulation. It also paves the way toward comprehensive myocardial tissue characterization in a single scan.

Rosette Trajectories Enable Ungated, Motion-Robust, Simultaneous Cardiac and Liver T2 * Iron Assessment

BACKGROUND

Quantitative T₂ * MRI is the standard of care for the assessment of iron overload. However, patient motion corrupts T₂ * estimates.

PURPOSE

To develop and evaluate a motion-robust, simultaneous cardiac and liver T₂ * imaging approach using non-Cartesian, rosette sampling and a model-based reconstruction as compared to clinical-standard Cartesian MRI.

STUDY TYPE

Prospective.

PHANTOM/POPULATION

Six ferumoxytol-containing phantoms (26-288 μg/mL). Eight healthy subjects and 18 patients referred for clinically indicated iron overload assessment.

FIELD STRENGTH/SEQUENCE

1.5T, 2D Cartesian and rosette gradient echo (GRE) ASSESSMENT: GRE T₂ * values were validated in ferumoxytol phantoms. In healthy subjects, test-retest and spatial coefficient of variation (CoV) analysis was performed during three breathing conditions. Cartesian and rosette T₂ * were compared using correlation and Bland-Altman analysis. Images were rated by three experienced radiologists on a 5-point scale.

STATISTICAL TESTS

Linear regression, analysis of variance (ANOVA), and paired Student's t-testing were used to compare reproducibility and variability metrics in Cartesian and rosette scans. The Wilcoxon rank test was used to assess reader score comparisons and reader reliability was measured using intraclass correlation analysis.

RESULTS

Rosette R2* (1/T₂ *) was linearly correlated with ferumoxytol concentration (r² = 1.00) and not significantly different than Cartesian values (P = 0.16). During breath-holding, ungated rosette liver and heart T₂ * had lower spatial CoV (liver: 18.4 ± 9.3% Cartesian, 8.8% ± 3.4% rosette, P = 0.02, heart: 37.7% ± 14.3% Cartesian, 13.4% ± 1.7% rosette, P = 0.001) and higher-quality scores (liver: 3.3 [3.0-3.6] Cartesian, 4.7 [4.1-4.9] rosette, P = 0.005, heart: 3.0 [2.3-3] Cartesian, 4.5 [3.8-5.0] rosette, P = 0.005) compared to Cartesian values. During free-breathing and failed breath-holding, Cartesian images had very poor to average image quality with significant artifacts, whereas rosette remained very good, with minimal artifacts (P = 0.001).

DATA CONCLUSION

Rosette k-sampling with a model-based reconstruction offers a clinically useful motion-robust T₂ * mapping approach for iron quantification. J. MAGN. RESON. IMAGING 2020;52:1688-1698.

Ultrafast magnetic resonance spectroscopic imaging using SPICE with learned subspaces

PURPOSE

To develop a subspace learning method for the recently proposed subspace-based MRSI approach known as SPICE, and achieve ultrafast 1 H-MRSI of the brain.

THEORY AND METHODS

A novel strategy is formulated to learn a low-dimensional subspace representation of MR spectra from specially acquired training data and use the learned subspace for general MRSI experiments. Specifically, the subspace learning problem is formulated as learning "empirical" distributions of molecule-specific spectral parameters (e.g., concentrations, lineshapes, and frequency shifts) by integrating physics-based model and the training data. The learned spectral parameters and quantum mechanical simulation basis can then be combined to construct acquisition-specific subspace for spatiospectral encoding and processing. High-resolution MRSI acquisitions combining ultrashort-TE/short-TR excitation, sparse sampling, and the elimination of water suppression have been performed to evaluate the feasibility of the proposed method.

RESULTS

The accuracy of the learned subspace and the capability of the proposed method in producing high-resolution 3D 1 H metabolite maps and high-quality spatially resolved spectra (with a nominal resolution of ∼2.4 × 2.4 × 3 mm3 in 5 minutes) were demonstrated using phantom and in vivo studies. By eliminating water suppression, we are also able to extract valuable information from the water signals for data processing ( B 0 map, frequency drift, and coil sensitivity) as well as for mapping tissue susceptibility and relaxation parameters.

CONCLUSIONS

The proposed method enables ultrafast 1 H-MRSI of the brain using a learned subspace, eliminating the need of acquiring subject-dependent navigator data (known as D 1 ) in the original SPICE technique. It represents a new way to perform MRSI experiments and an important step toward practical applications of high-resolution MRSI.

Super-Resolution 1H Magnetic Resonance Spectroscopic Imaging Utilizing Deep Learning

Magnetic resonance spectroscopic imaging (SI) is a unique imaging technique that provides biochemical information from in vivo tissues. The 1H spectra acquired from several spatial regions are quantified to yield metabolite concentrations reflective of tissue metabolism. However, since these metabolites are found in tissues at very low concentrations, SI is often acquired with limited spatial resolution. In this work, we test the hypothesis that deep learning is able to upscale low resolution SI, together with the T1-weighted (T1w) image, to reconstruct high resolution SI. We report on a novel densely connected UNet (D-UNet) architecture capable of producing super-resolution spectroscopic images. The inputs for the D-UNet are the T1w image and the low resolution SI image while the output is the high resolution SI. The results of the D-UNet are compared both qualitatively and quantitatively to simulated and in vivo high resolution SI. It is found that this deep learning approach can produce high quality spectroscopic images and reconstruct entire 1H spectra from low resolution acquisitions, which can greatly advance the current SI workflow.

Combining multiband slice selection with consistent k-t-space EPSI for accelerated spectral imaging

PURPOSE

To design and implement a multislice MRSI method for fast spectroscopic imaging, using a modified version of echo planar spectroscopic imaging (EPSI) that offers higher spectral width and/or shorter scan time.

METHODS

Echo planar spectroscopic imaging suffers from inconsistencies between readout lines acquired with gradients of opposite signs, which has typically been addressed by reconstructing the "positive" and "negative" data sets separately and averaging the two. Nevertheless, consistency between the readout lines of each phase encode can be achieved by interposing the EPSI readouts with alternating "blipped" phase-encode gradients. This method exchanges inconsistencies along the temporal dimension with inconsistencies along the phase-encode dimension, which are straightforward to correct, as is conventionally done in various EPI reconstruction schemes. Such consistent k-t-space EPSI doubles the spectral width in comparison to EPSI, or, in an alternative realization, yields the same spectral width as EPSI, but at half the acquisition time. In this work, multiband CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) slice selection was integrated with consistent k-t-space EPSI to further accelerate the measurement 2-fold.

RESULTS

The feasibility of a consistent k-t-space EPSI was demonstrated in both phantoms and in vivo brain imaging at 3 T, and four pulse scheme variants were evaluated. It was demonstrated to be useful in optimizing the spectral width and scan acceleration, both of which are limiting factors in vivo. Dual-band implementation was shown to shorten the duration of the scan 4-fold.

CONCLUSION

The consistent k-t-space EPSI can be used to accelerate MRSI or, alternatively, double its spectral width. Adding dual-band CAIPIRINHA further accelerates the acquisition by a factor of 2.

Fast data acquisition techniques in magnetic resonance spectroscopic imaging

Magnetic resonance spectroscopic imaging (MRSI) is an important technique for assessing the spatial variation of metabolites in vivo. The long scan times in MRSI limit clinical applicability due to patient discomfort, increased costs, motion artifacts, and limited protocol flexibility. Faster acquisition strategies can address these limitations and could potentially facilitate increased adoption of MRSI into routine clinical protocols with minimal addition to the current anatomical and functional acquisition protocols in terms of imaging time. Not surprisingly, a lot of effort has been devoted to the development of faster MRSI techniques that aim to capture the same underlying metabolic information (relative metabolite peak areas and spatial distribution) as obtained by conventional MRSI, in greatly reduced time. The gain in imaging time results, in some cases, in a loss of signal-to-noise ratio and/or in spatial and spectral blurring. This review examines the current techniques and advances in fast MRSI in two and three spatial dimensions and their applications. This review categorizes the acceleration techniques according to their strategy for acquisition of the k-space. Techniques such as fast/turbo-spin echo MRSI, echo-planar spectroscopic imaging, and non-Cartesian MRSI effectively cover the full k-space in a more efficient manner per T_R . On the other hand, techniques such as parallel imaging and compressed sensing acquire fewer k-space points and employ advanced reconstruction algorithms to recreate the spatial-spectral information, which maintains statistical fidelity in test conditions (ie no statistically significant differences on voxel-wise comparisions) with the fully sampled data. The advantages and limitations of each state-of-the-art technique are reviewed in detail, concluding with a note on future directions and challenges in the field of fast spectroscopic imaging.

Density-weighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T

PURPOSE

Full-slice magnetic resonance spectroscopic imaging at ≥7 T is especially vulnerable to lipid contaminations arising from regions close to the skull. This contamination can be mitigated by improving the point spread function via higher spatial resolution sampling and k-space filtering, but this prolongs scan times and reduces the signal-to-noise ratio (SNR) efficiency. Currently applied parallel imaging methods accelerate magnetic resonance spectroscopic imaging scans at 7T, but increase lipid artifacts and lower SNR-efficiency further. In this study, we propose an SNR-efficient spatial-spectral sampling scheme using concentric circle echo planar trajectories (CONCEPT), which was adapted to intrinsically acquire a Hamming-weighted k-space, thus termed density-weighted-CONCEPT. This minimizes voxel bleeding, while preserving an optimal SNR.

THEORY AND METHODS

Trajectories were theoretically derived and verified in phantoms as well as in the human brain via measurements of five volunteers (single-slice, field-of-view 220 × 220 mm2 , matrix 64 × 64, scan time 6 min) with free induction decay magnetic resonance spectroscopic imaging. Density-weighted-CONCEPT was compared to (a) the originally proposed CONCEPT with equidistant circles (here termed e-CONCEPT), (b) elliptical phase-encoding, and (c) 5-fold Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase-encoding.

RESULTS

By intrinsically sampling a Hamming-weighted k-space, density-weighted-CONCEPT removed Gibbs-ringing artifacts and had in vivo +9.5%, +24.4%, and +39.7% higher SNR than e-CONCEPT, elliptical phase-encoding, and the Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase-encoding (all P < 0.05), respectively, which lead to improved metabolic maps.

CONCLUSION

Density-weighted-CONCEPT provides clinically attractive full-slice high-resolution magnetic resonance spectroscopic imaging with optimal SNR at 7T. Magn Reson Med 79:2874-2885, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Compressed sensing for high-resolution nonlipid suppressed 1 H FID MRSI of the human brain at 9.4T

PURPOSE

The aim of this study was to apply compressed sensing to accelerate the acquisition of high resolution metabolite maps of the human brain using a nonlipid suppressed ultra-short TR and TE ¹ H FID MRSI sequence at 9.4T.

METHODS

X-t sparse compressed sensing reconstruction was optimized for nonlipid suppressed ¹ H FID MRSI data. Coil-by-coil x-t sparse reconstruction was compared with SENSE x-t sparse and low rank reconstruction. The effect of matrix size and spatial resolution on the achievable acceleration factor was studied. Finally, in vivo metabolite maps with different acceleration factors of 2, 4, 5, and 10 were acquired and compared.

RESULTS

Coil-by-coil x-t sparse compressed sensing reconstruction was not able to reliably recover the nonlipid suppressed data, rather a combination of parallel and sparse reconstruction was necessary (SENSE x-t sparse). For acceleration factors of up to 5, both the low-rank and the compressed sensing methods were able to reconstruct the data comparably well (root mean squared errors [RMSEs] ≤ 10.5% for Cre). However, the reconstruction time of the low rank algorithm was drastically longer than compressed sensing. Using the optimized compressed sensing reconstruction, acceleration factors of 4 or 5 could be reached for the MRSI data with a matrix size of 64 × 64. For lower spatial resolutions, an acceleration factor of up to R∼4 was successfully achieved.

CONCLUSION

By tailoring the reconstruction scheme to the nonlipid suppressed data through parameter optimization and performance evaluation, we present high resolution (97 µL voxel size) accelerated in vivo metabolite maps of the human brain acquired at 9.4T within scan times of 3 to 3.75 min.

A singular K-space model for fast reconstruction of magnetic resonance images from undersampled data

Reconstructing magnetic resonance images from undersampled k-space data is a challenging problem. This paper introduces a novel method of image reconstruction from undersampled k-space data based on the concept of singularizing operators and a novel singular k-space model. Exploring the sparsity of an image in the k-space, the singular k-space model (SKM) is proposed in terms of the k-space functions of a singularizing operator. The singularizing operator is constructed by combining basic difference operators. An algorithm is developed to reliably estimate the model parameters from undersampled k-space data. The estimated parameters are then used to recover the missing k-space data through the model, subsequently achieving high-quality reconstruction of the image using inverse Fourier transform. Experiments on physical phantom and real brain MR images have shown that the proposed SKM method constantly outperforms the popular total variation (TV) and the classical zero-filling (ZF) methods regardless of the undersampling rates, the noise levels, and the image structures. For the same objective quality of the reconstructed images, the proposed method requires much less k-space data than the TV method. The SKM method is an effective method for fast MRI reconstruction from the undersampled k-space data. Graphical abstract Two Real Images and their sparsified images by singularizing operator.

Assessing tissue metabolism by phosphorous-31 magnetic resonance spectroscopy and imaging: a methodology review

Many human diseases are caused by an imbalance between energy production and demand. Magnetic resonance spectroscopy (MRS) and magnetic resonance imaging (MRI) provide the unique opportunity for in vivo assessment of several fundamental events in tissue metabolism without the use of ionizing radiation. Of particular interest, phosphate metabolites that are involved in ATP generation and utilization can be quantified noninvasively by phosphorous-31 (31P) MRS/MRI. Furthermore, 31P magnetization transfer (MT) techniques allow in vivo measurement of metabolic fluxes via creatine kinase (CK) and ATP synthase. However, a major impediment for the clinical applications of 31P-MRS/MRI is the prohibitively long acquisition time and/or the low spatial resolution that are necessary to achieve adequate signal-to-noise ratio. In this review, current 31P-MRS/MRI techniques used in basic science and clinical research are presented. Recent advances in the development of fast 31P-MRS/MRI methods are also discussed.

Fast 3D rosette spectroscopic imaging of neocortical abnormalities at 3 T: Assessment of spectral quality

PURPOSE

To use a fast 3D rosette spectroscopic imaging acquisition to quantitatively evaluate how spectral quality influences detection of the endogenous variation of gray and white matter metabolite differences in controls, and demonstrate how rosette spectroscopic imaging can detect metabolic dysfunction in patients with neocortical abnormalities.

METHODS

Data were acquired on a 3T MR scanner and 32-channel head coil, with rosette spectroscopic imaging covering a 4-cm slab of fronto-parietal-temporal lobes. The influence of acquisition parameters and filtering on spectral quality and sensitivity to tissue composition was assessed by LCModel analysis, the Cramer-Rao lower bound, and the standard errors from regression analyses. The optimized protocol was used to generate normative white and gray matter regressions and evaluate three patients with neocortical abnormalities.

RESULTS

As a measure of the sensitivity to detect abnormalities, the standard errors of regression for Cr/NAA and Ch/NAA were significantly correlated with the Cramer-Rao lower bound values (R = 0.89 and 0.92, respectively, both with P < 0.001). The rosette acquisition with a duration of 9.6 min, produces a mean Cramer-Rao lower bound (%) over the entire slab of 4.6 ± 2.6 and 5.8 ± 2.3 for NAA and Cr, respectively. This enables a Cr/NAA standard error of 0.08 (i.e., detection sensitivity of 25% for a 50/50 mixed gray and white matter voxel). In healthy controls, the regression of Cr/NAA versus fraction gray matter in the cingulate differs from frontal and parietal regions.

CONCLUSIONS

Fast rosette spectroscopic imaging acquisitions with regression analyses are able to identify metabolic differences across 4-cm slabs of the brain centrally and over the cortical periphery with high efficiency, generating results that are consistent with clinical findings. Magn Reson Med 79:2470-2480, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Prior-knowledge Fitting of Accelerated Five-dimensional Echo Planar J-resolved Spectroscopic Imaging: Effect of Nonlinear Reconstruction on Quantitation

¹H Magnetic Resonance Spectroscopic imaging (SI) is a powerful tool capable of investigating metabolism in vivo from mul- tiple regions. However, SI techniques are time consuming, and are therefore difficult to implement clinically. By applying non-uniform sampling (NUS) and compressed sensing (CS) reconstruction, it is possible to accelerate these scans while re- taining key spectral information. One recently developed method that utilizes this type of acceleration is the five-dimensional echo planar J-resolved spectroscopic imaging (5D EP-JRESI) sequence, which is capable of obtaining two-dimensional (2D) spectra from three spatial dimensions. The prior-knowledge fitting (ProFit) algorithm is typically used to quantify 2D spectra in vivo, however the effects of NUS and CS reconstruction on the quantitation results are unknown. This study utilized a simulated brain phantom to investigate the errors introduced through the acceleration methods. Errors (normalized root mean square error >15%) were found between metabolite concentrations after twelve-fold acceleration for several low concentra- tion (<2 mM) metabolites. The Cramér Rao lower bound% (CRLB%) values, which are typically used for quality control, were not reflective of the increased quantitation error arising from acceleration. Finally, occipital white (OWM) and gray (OGM) human brain matter were quantified in vivo using the 5D EP-JRESI sequence with eight-fold acceleration.

Non-water-suppressed short-echo-time magnetic resonance spectroscopic imaging using a concentric ring k-space trajectory

Water-suppressed MRS acquisition techniques have been the standard MRS approach used in research and for clinical scanning to date. The acquisition of a non-water-suppressed MRS spectrum is used for artefact correction, reconstruction of phased-array coil data and metabolite quantification. Here, a two-scan metabolite-cycling magnetic resonance spectroscopic imaging (MRSI) scheme that does not use water suppression is demonstrated and evaluated. Specifically, the feasibility of acquiring and quantifying short-echo (TE  = 14 ms), two-dimensional stimulated echo acquisition mode (STEAM) MRSI spectra in the motor cortex is demonstrated on a 3 T MRI system. The increase in measurement time from the metabolite-cycling is counterbalanced by a time-efficient concentric ring k-space trajectory. To validate the technique, water-suppressed MRSI acquisitions were also performed for comparison. The proposed non-water-suppressed metabolite-cycling MRSI technique was tested for detection and correction of resonance frequency drifts due to subject motion and/or hardware instability, and the feasibility of high-resolution metabolic mapping over a whole brain slice was assessed. Our results show that the metabolite spectra and estimated concentrations are in agreement between non-water-suppressed and water-suppressed techniques. The achieved spectral quality, signal-to-noise ratio (SNR) > 20 and linewidth <7 Hz allowed reliable metabolic mapping of five major brain metabolites in the motor cortex with an in-plane resolution of 10 × 10 mm2 in 8 min and with a Cramér-Rao lower bound of less than 20% using LCModel analysis. In addition, the high SNR of the water peak of the non-water-suppressed technique enabled voxel-wise single-scan frequency, phase and eddy current correction. These findings demonstrate that our non-water-suppressed metabolite-cycling MRSI technique can perform robustly on 3 T MRI systems and within a clinically feasible acquisition time.

(2 + 1)D-CAIPIRINHA accelerated MR spectroscopic imaging of the brain at 7T

Purpose

To compare a new parallel imaging (PI) method for multislice proton magnetic resonance spectroscopic imaging (¹H‐MRSI), termed (2 + 1)D‐CAIPIRINHA, with two standard PI methods: 2D‐GRAPPA and 2D‐CAIPIRINHA at 7 Tesla (T).

Methods

(2 + 1)D‐CAIPIRINHA is a combination of 2D‐CAIPIRINHA and slice‐CAIPIRINHA. Eight healthy volunteers were measured on a 7T MR scanner using a 32‐channel head coil. The best undersampling patterns were estimated for all three PI methods. The artifact powers, g‐factors, Cramér–Rao lower bounds (CRLB), and root mean square errors (RMSE) were compared quantitatively among the three PI methods. Metabolic maps and spectra were compared qualitatively.

Results

(2 + 1)D‐CAIPIRINHA allows acceleration in three spatial dimensions in contrast to 2D‐GRAPPA and 2D‐CAIPIRINHA. Thus, this sequence significantly decreased the RMSE of the metabolic maps by 12.1 and 6.9%, on average, for 4 < R < 11, compared with 2D‐GRAPPA and 2D‐CAIPIRINHA, respectively. The artifact power was 22.6 and 8.4% lower, and the CRLB were 3.4 and 0.6% lower, respectively.

Conclusion

(2 + 1)‐CAIPIRINHA can be implemented for multislice MRSI in the brain, enabling higher accelerations than possible with two‐dimensional (2D) parallel imaging methods. An eight‐fold acceleration was still feasible in vivo with negligible PI artifacts with lipid decontamination, thus decreasing the measurement time from 120 to 15 min for a 64 × 64 × 4 matrix. Magn Reson Med 78:429–440, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Analysis of generalized rosette trajectory for compressed sensing MRI

PURPOSE

The application of compressed sensing (CS) technology in magnetic resonance imaging (MRI) is to accelerate the MRI scan speed by incoherent undersampling of k-space data and nonlinear iterative reconstruction of MRI images. This paper generalizes the existing rosette trajectories to configure the sampling patterns for undersampled k-space data acquisition in MRI scans. The arch and curvature characteristics of the generalized rosette trajectories are analyzed to explore their feasibility and advantages for CS reconstruction of MRI images.

METHODS

Two key properties crucial to the CS MRI application, the scan speed and sampling incoherence of the generalized rosette trajectories, are analyzed. The analysis on the scan speed of generalized rosette trajectories is based on the transversal time derived from the curvature of the trajectories, and the sampling incoherence is based on the evaluation of the point spread function for the measurement matrix. The results of analysis are supported by extensive simulations where the performances of rosette, spiral, and radial sampling patterns at different acceleration factors are compared.

RESULTS

It is shown that compared with spiral trajectories, the arch and curvature characteristics of the generalized rosette trajectories are more feasible to meet the physical requirements of undersampled k-space data acquisition in terms of time shortness and scan area. It is further shown that the sampling pattern of the rosette trajectory has higher incoherence than that of the other trajectories and can thus achieve higher reconstruction performance. Reconstruction performances illustrate that the rosette trajectory can achieve about 10% higher peak signal-to-noise ratio than radial and spiral trajectories under the high acceleration factor R = 10.

CONCLUSIONS

The generalized rosette trajectories can be a desirable candidate for CS reconstruction of MRI.

High-resolution (1) H-MRSI of the brain using SPICE: Data acquisition and image reconstruction

PURPOSE

To develop data acquisition and image reconstruction methods to enable high-resolution (1) H MR spectroscopic imaging (MRSI) of the brain, using the recently proposed subspace-based spectroscopic imaging framework called SPICE (SPectroscopic Imaging by exploiting spatiospectral CorrElation).

THEORY AND METHODS

SPICE is characterized by the use of a subspace model for both data acquisition and image reconstruction. For data acquisition, we propose a novel spatiospectral encoding scheme that provides hybrid data sets for determining the subspace structure and for image reconstruction using the subspace model. More specifically, we use a hybrid chemical shift imaging /echo-planar spectroscopic imaging sequence for two-dimensional (2D) MRSI and a dual-density, dual-speed echo-planar spectroscopic imaging sequence for three-dimensional (3D) MRSI. For image reconstruction, we propose a method that can determine the subspace structure and the high-resolution spatiospectral reconstruction from the hybrid data sets generated by the proposed sequences, incorporating field inhomogeneity correction and edge-preserving regularization.

RESULTS

Phantom and in vivo brain experiments were performed to evaluate the performance of the proposed method. For 2D MRSI experiments, SPICE is able to produce high-SNR spatiospectral distributions with an approximately 3 mm nominal in-plane resolution from a 10-min acquisition. For 3D MRSI experiments, SPICE is able to achieve an approximately 3 mm in-plane and 4 mm through-plane resolution in about 25 min.

CONCLUSION

Special data acquisition and reconstruction methods have been developed for high-resolution (1) H-MRSI of the brain using SPICE. Using these methods, SPICE is able to produce spatiospectral distributions of (1) H metabolites in the brain with high spatial resolution, while maintaining a good SNR. These capabilities should prove useful for practical applications of SPICE. Magn Reson Med 76:1059-1070, 2016. © 2015 Wiley Periodicals, Inc.

In vivo brain rosette spectroscopic imaging (RSI) with LASER excitation, constant gradient strength readout, and automated LCModel quantification for all voxels

PURPOSE

To optimize the Rosette trajectories for high-sensitivity in vivo brain spectroscopic imaging and reduced gradient demands.

METHODS

Using LASER localization, a rosette based sampling scheme for in vivo brain spectroscopic imaging data on a 3 Tesla (T) system is described. The two-dimensional (2D) and 3D rosette spectroscopic imaging (RSI) data were acquired using 20 × 20 in-plane resolution (8 × 8 mm(2) ), and 1 (2D) -18 mm (1.1 cc) or 12 (3D) -8 mm partitions (0.5 cc voxels). The performance of the RSI acquisition was compared with a conventional spectroscopic imaging (SI) sequence using LASER localization and 2D or 3D elliptical phase encoding (ePE). Quantification of the entire RSI data set was performed using an LCModel based pipeline.

RESULTS

The RSI acquisitions took 32 s for the 2D scan, and as short as 5 min for the 3D 20 × 20 × 12 scan, using a maximum gradient strength Gmax=5.8 mT/m and slew-rate Smax=45 mT/m/ms. The Bland-Altman agreement between RSI and ePE CSI, characterized by the 95% confidence interval for their difference (RSI-ePE), is within 13% of the mean (RSI+ePE)/2. Compared with the 3D ePE at the same nominal resolution, the effective RSI voxel size was three times smaller while the measured signal-to-noise ratio sensitivity, after normalization for differences in effective size, was 43% greater.

CONCLUSION

3D LASER-RSI is a fast, high-sensitivity spectroscopic imaging sequence, which can acquire medium-to-high resolution SI data in clinically acceptable scan times (5-10 min), with reduced stress on the gradient system. Magn Reson Med 76:380-390, 2016. © 2015 Wiley Periodicals, Inc.

Radiofrequency field inhomogeneity compensation in high spatial resolution magnetic resonance spectroscopic imaging

Clinical magnetic resonance spectroscopy imaging (MRSI) is a non-invasive functional technique, whose mathematical framework falls into the category of linear inverse problems. However, its use in medical diagnostics is hampered by two main problems, both linked to the Fourier-based technique usually implemented for spectra reconstruction: poor spatial resolution and severe blurring in the spatial localization of the reconstructed spectra. Moreover, the intrinsic ill-posedness of the MRSI problem might be worsened by (i) spatially dependent distortions of the static magnetic field (B0) distribution, as well as by (ii) inhomogeneity in the power deposition distribution of the radiofrequency magnetic field (B1). Among several alternative methods, slim (Spectral Localization by IMaging) and bslim (B0 compensated slim) are reconstruction algorithms in which a priori information concerning the spectroscopic target is introduced into the reconstruction kernel. Nonetheless, the influence of the B1 field, particularly when its operating wavelength is close to the size of the human organs being studied, continues to be disregarded. starslim (STAtic and Radiofrequency-compensated slim), an evolution of the slim and bslim methods, is therefore proposed, in which the transformation kernel also includes the B1 field inhomogeneity map, thus allowing almost complete 3D modelling of the MRSI problem. Moreover, an original method for the experimental determination of the B1 field inhomogeneity map specific to the target under evaluation is also included. The compensation capabilities of the proposed method have been tested and illustrated using synthetic raw data reproducing the human brain.

A subspace approach to high-resolution spectroscopic imaging

PURPOSE

To accelerate spectroscopic imaging using sparse sampling of (k,t)-space and subspace (or low-rank) modeling to enable high-resolution metabolic imaging with good signal-to-noise ratio.

METHODS

The proposed method, called SPectroscopic Imaging by exploiting spatiospectral CorrElation, exploits a unique property known as partial separability of spectroscopic signals. This property indicates that high-dimensional spectroscopic signals reside in a very low-dimensional subspace and enables special data acquisition and image reconstruction strategies to be used to obtain high-resolution spatiospectral distributions with good signal-to-noise ratio. More specifically, a hybrid chemical shift imaging/echo-planar spectroscopic imaging pulse sequence is proposed for sparse sampling of (k,t)-space, and a low-rank model-based algorithm is proposed for subspace estimation and image reconstruction from sparse data with the capability to incorporate prior information and field inhomogeneity correction.

RESULTS

The performance of the proposed method has been evaluated using both computer simulations and phantom studies, which produced very encouraging results. For two-dimensional spectroscopic imaging experiments on a metabolite phantom, a factor of 10 acceleration was achieved with a minimal loss in signal-to-noise ratio compared to the long chemical shift imaging experiments and with a significant gain in signal-to-noise ratio compared to the accelerated echo-planar spectroscopic imaging experiments.

CONCLUSION

The proposed method, SPectroscopic Imaging by exploiting spatiospectral CorrElation, is able to significantly accelerate spectroscopic imaging experiments, making high-resolution metabolic imaging possible.

Neurologic 3D MR spectroscopic imaging with low-power adiabatic pulses and fast spiral acquisition

PURPOSE

To improve clinical three-dimensional (3D) MR spectroscopic imaging with more accurate localization and faster acquisition schemes.

MATERIALS AND METHODS

Institutional review board approval and patient informed consent were obtained. Data were acquired with a 3-T MR imager and a 32-channel head coil in phantoms, five healthy volunteers, and five patients with glioblastoma. Excitation was performed with localized adiabatic spin-echo refocusing (LASER) by using adiabatic gradient-offset independent adiabaticity wideband uniform rate and smooth truncation (GOIA-W[16,4]) pulses with 3.5-msec duration, 20-kHz bandwidth, 0.81-kHz amplitude, and 45-msec echo time. Interleaved constant-density spirals simultaneously encoded one frequency and two spatial dimensions. Conventional phase encoding (PE) (1-cm3 voxels) was performed after LASER excitation and was the reference standard. Spectra acquired with spiral encoding at similar and higher spatial resolution and with shorter imaging time were compared with those acquired with PE. Metabolite levels were fitted with software, and Bland-Altman analysis was performed.

RESULTS

Clinical 3D MR spectroscopic images were acquired four times faster with spiral protocols than with the elliptical PE protocol at low spatial resolution (1 cm3). Higher-spatial-resolution images (0.39 cm3) were acquired twice as fast with spiral protocols compared with the low-spatial-resolution elliptical PE protocol. A minimum signal-to-noise ratio (SNR) of 5 was obtained with spiral protocols under these conditions and was considered clinically adequate to reliably distinguish metabolites from noise. The apparent SNR loss was not linear with decreasing voxel sizes because of longer local T2* times. Improvement of spectral line width from 4.8 Hz to 3.5 Hz was observed at high spatial resolution. The Bland-Altman agreement between spiral and PE data is characterized by narrow 95% confidence intervals for their differences (0.12, 0.18 of their means). GOIA-W(16,4) pulses minimize chemical-shift displacement error to 2.1%, reduce nonuniformity of excitation to 5%, and eliminate the need for outer volume suppression.

CONCLUSION

The proposed adiabatic spiral 3D MR spectroscopic imaging sequence can be performed in a standard clinical MR environment. Improvements in image quality and imaging time could enable more routine acquisition of spectroscopic data than is possible with current pulse sequences.

Linear Response Equilibrium versus echo-planar encoding for fast high-spatial resolution 3D chemical shift imaging

In this work Linear Response Equilibrium (LRE) and Echo-planar spectroscopic imaging (EPSI) are compared in terms of sensitivity per unit time and power deposition. In addition an extended dual repetition time scheme to generate broad stopbands for improved inherent water suppression in LRE is presented. The feasibility of LRE and EPSI for assessing cholesterol esters in human carotid plaques with high spatial resolution of 1.95×1.15×1.15 mm(3) on a clinical 3T MR system is demonstrated. In simulations and phantom experiments it is shown that LRE has comparable but lower sensitivity per unit time relative to EPSI despite stronger signal generated. This relates to the lower sampling efficiency in LRE relative to EPSI as a result of limited gradient performance on clinical MR systems. At the same time, power deposition of LRE is significantly reduced compared to EPSI making it an interesting niche application for in vivo high field spectroscopic imaging of metabolites within a limited bandwidth.