Considerations in applying compressed sensing to in vivo phosphorus MR spectroscopic imaging of human brain at 3T

Optimized multi-voxel TE-averaged PRESS for glutamate detection in the human brain at 3T

PURPOSE

To optimize possible combinations of echo times (TE) for multi-voxel TE-averaged Point RESolved Spectroscopy (PRESS) while reducing the total number of TEs required to separate glutamate (Glu) and glutamine (Gln) within a clinically feasible scan time.

METHODS

General Approach to Magnetic resonance Mathematical Analysis (GAMMA) was used to implement 2D J-resolved PRESS technique, and the spectra of 14 individual brain metabolites were simulated at 64 different TEs. Monte Carlo simulations were used for selecting the best TE combinations to separate Glu and Gln using TE-averaged PRESS with a total number of two, three, four and five TEs. Single-voxel 1H-MRS data were acquired using 64 different TEs from a healthy volunteer on a clinical 3T MR scanner to validate the echo time combinations selected with simulations. Additionally, 2D 1H-MRSI data of eight healthy volunteers were acquired on a clinical 3T MR scanner using four different TEs that were determined by Monte Carlo simulations. Optimized TE-averaged PRESS spectra were created by averaging the spectra acquired at selected TEs. LCModel was used for spectral quantification. A Wilcoxon signed-rank test was used to detect statistically significant differences in Glu/Gln ratios between 35 ms PRESS and optimized TE-averaged PRESS data.

RESULTS

Glu could be clearly separated from Gln at 2.35 ppm, using optimized TE-averaged PRESS with only four TEs (35, 37, 40, and 42 ms) that were selected through Monte Carlo simulations. Glu/Gln ratios were significantly higher in the optimized TE-averaged PRESS data of healthy volunteers than in the 35 ms PRESS data (P = 0.008).

CONCLUSION

Optimized multi-voxel TE-averaged PRESS enabled faster and unobstructed quantification of Glu at multiple voxels in the human brain in vivo at 3T.

Achieving high-resolution 1H-MRSI of the human brain with compressed-sensing and low-rank reconstruction at 7 Tesla

Low sensitivity MR techniques such as magnetic resonance spectroscopic imaging (MRSI) greatly benefit from the gain in signal-to-noise provided by ultra-high field MR. High-resolution and whole-slab brain MRSI remains however very challenging due to lengthy acquisition, low signal, lipid contamination and field inhomogeneity. In this study, we propose an acquisition-reconstruction scheme that combines 1H free-induction-decay (FID)-MRSI sequence, short TR acquisition, compressed sensing acceleration and low-rank modeling with total-generalized-variation constraint to achieve metabolite imaging in two and three dimensions at 7 Tesla. The resulting images and volumes reveal highly detailed distributions that are specific to each metabolite and follow the underlying brain anatomy. The MRSI method was validated in a high-resolution phantom containing fine metabolite structures, and in five healthy volunteers. This new application of compressed sensing acceleration paves the way for high-resolution MRSI in clinical setting with acquisition times of 5 min for 2D MRSI at 2.5 mm and of 20 min for 3D MRSI at 3.3 mm isotropic.

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.

Accelerating Brain 3D T1-Weighted Turbo Field Echo MRI Using Compressed Sensing-Sensitivity Encoding (CS-SENSE)

PURPOSE

To evaluate the clinical application of the accelerated 3D T1-weighted turbo field echo (T1W-TFE) using the compressed sensing-sensitivity encoding (CS-SENSE) and identify the appropriate acceleration factor.

METHODS

33 healthy controls (HC), 10 multiple sclerosis (MS) and 10 Alzheimer's disease (AD) patients were prospectively recruited. A conventional 3D T1W-TFE sequence and accelerated sequences with CS-SENSE factors of 3, 4.5, 6 and with SENSE factors of 3, 4.5 were acquired for all participants on a 3.0T MR system. The visual evaluation was independently assessed by two experienced radiologists. Quantitative image quality metrics and intraclass correlation coefficients (ICCs) between the conventional and the accelerated sequences were performed at the voxel level. Group comparisons were performed between HC and AD or MS patients.

RESULTS

There were no significant differences in the visual image quality metrics between conventional sequence and CS-SENSE factor of 3. The sequences with CS-SENSE factor of 6 and SENSE factors of 3, 4.5 showed significantly decreased overall image quality. The ICC values based on the voxel level of each accelerated scan and conventional scan were high (>0.9, 85.2%). For different accelerated sequences, AD and MS patients showed consistent results with the conventional sequence in gray matter atrophy when compared to HC.

CONCLUSIONS

CS-SENSE factor of 3 is the appropriate parameter to accelerate the 3D T1W-TFE (65% time reduction) with preserved visual image quality. The voxel-based analysis demonstrated high ICCs for brain volume measurements in the majority of brain regions, implying the feasibility of the accelerated technique.

Comparison of compressed sensing reconstruction algorithms for 31P magnetic resonance spectroscopic imaging

Phosphorus MR spectroscopy and spectroscopic imaging (³¹P-MRS/MRSI) provide information about energy metabolism, membrane degradation and pH in vivo. In spite of their proven utility, ³¹P-MRS/MRSI are not often used primarily because of the challenges imposed by the low sensitivity and low concentration of metabolites leading to low signal to noise ratio (SNR), coarse spatial resolution and prolonged acquisition time. More recently there has been considerable interest in compressed sensing as an acceleration method for MR signal acquisition. This approach takes advantage of the intrinsic sparsity of the spectral data. In this work, we present a ³¹P-MRSI sequence that combines a flyback EPSI trajectory and compressed sensing, and we compared two different reconstruction methods, L1 norm minimization and low rank Hankel matrix completion. Our phantom results showed good preservation of spectral quality for both ×2.0 and ×3.0 acceleration factors, using both CS reconstruction methods. However, in vivo ³¹P-MRS brain data showed the low rank reconstruction approach was most suitable. Overall, this study shows the feasibility of combining a flyback EPSI trajectory and compressed sensing in the acquisition of ³¹P-MRSI as well as the better suitability of a low rank reconstruction approach.

Dynamic 31 P spectroscopic imaging of skeletal muscles combining flyback echo-planar spectroscopic imaging and compressed sensing

PURPOSE

Dynamic phosphorus MR spectroscopic imaging (³¹ P-MRSI) experiments require temporal resolution on the order of seconds to concurrently assess different muscle groups. A highly accelerated pulse sequence combining flyback echo-planar spectroscopic imaging (EPSI) and compressed sensing was developed and tested in a phantom and healthy humans during an exercise-recovery challenge of the lower leg muscles, using a clinical 3T MRI.

METHODS

A flyback EPSI readout designed to achieve 2.25 × 2.25 cm² resolution over a 18 × 18 cm² field of view (i.e., 8 × 8 matrix) was combined with compressed sensing through the inclusion of pseudorandom gradient blips to sub-sample the ky-kt dimensions by a factor of 2.7×, achieving a temporal resolution of 9 s. The sequence was first tested in a phantom to assess performance compared to fully sampled EPSI (fidEPSI) and phase encoded chemical shift imaging (fidCSI). Then, tests were performed in 11 healthy volunteers during an exercise-recovery challenge of the lower leg muscles. Voxels containing tissue from different muscle groups were evaluated measuring percentage phosphocreatine (%PCr) depletion, time constant of PCr recovery (τPCr) and intracellular pH at rest and following exercise.

RESULTS

The sequence was capable to track the dynamic PCr response of multiple muscles simultaneously. No statistical differences were found in the metabolite ratio, pH or linewidth when compared with fidEPSI and fidCSI in the phantom study. Dynamic experiments showed differences in PCr depletion when comparing soleus with gastrocnemius muscles. Intracellular pH, τPCr and %PCr decrease were consistent with reported values.

CONCLUSION

Highly accelerated ³¹ P-MRSI combining flyback EPSI and compressed sensing is capable of assessing concurrent energy metabolism in multiple muscle groups using a clinical 3T MR system.

Phosphorus magnetic resonance spectroscopic imaging using flyback echo planar readout trajectories

OBJECT

To present and evaluate a fast phosphorus magnetic resonance spectroscopic imaging (MRSI) sequence using echo planar spectroscopic imaging with flyback readout gradient trajectories.

MATERIALS AND METHODS

Waveforms were designed and implemented using a 3 Tesla MRI system. ³¹P spectra were acquired with 2 × 2 cm² and 3 × 3 cm² resolution over a 20- and 21-cm field of view and spectral bandwidths up to 1923 Hz. The sequence was first tested using a 20-cm-diameter phosphate phantom, and subsequent in vivo tests were performed on healthy human calf muscles and brains from five volunteers.

RESULTS

Flyback EPSI achieved 10× and 7× reductions in acquisition time, with 68.0 ± 1.2 and 69.8 ± 2.2% signal-to-noise ratio (SNR) per unit of time efficiency (theoretical SNR efficiency was 74.5 and 76.4%) for the in vivo experiments, compared to conventional phase-encoded MRSI for the 2 × 2 cm² and 3 × 3 cm² resolution waveforms, respectively. Statistical analysis showed no difference in the quantification of most metabolites. Time savings and SNR comparisons were consistent across phantom, leg and brain experiments.

CONCLUSION

EPSI using flyback readout trajectories was found to be a reliable alternative for acquiring ³¹P-MRSI data in a shorter acquisition time.

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.

Workshop on reconstruction schemes for magnetic resonance data: summary of findings and recommendations

The high-fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is essential for simultaneously improving patient care, accuracy in diagnosis and quality in clinical research. Sponsored by the Royal Society through the Newton Mobility Grant Scheme, we held a half-day workshop on reconstruction schemes for MR data on 17 August 2016 to discuss new ideas from related research fields that could be useful to overcome the shortcomings of the conventional reconstruction methods that have been evaluated to date. Participants were 21 university students, computer scientists, image analysts, engineers and physicists from institutions from six different countries. The discussion evolved around exploring new avenues to achieve high resolution, high quality and fast acquisition of MR imaging. In this article, we summarize the topics covered throughout the workshop and make recommendations for ongoing and future works.