Spectral analysis of multichannel MRS data

Multi-channel magnetic resonance spectroscopy graphical user interface (McMRSGUI)

This work introduces an open-sourced graphical user interface (GUI) software enabling the combination of multi-channel magnetic resonance spectroscopy data with different literature-based methods for the improvement of the quality and reliability of combined spectra. The multi-channel magnetic resonance spectroscopy graphical user interface (McMRSGUI) is a MATLAB-based spectroscopy processing GUI equipped to load multi-channel MRS data, pre-process, combine, and export combined data for evaluation with open-source quantification software (jMRUI). A literature-based, decision-tree process was incorporated into the combination type selection to serve as a guide to minimize spectral distortion in selecting between weighting methods. Multi-channel, simulated spectra were combined with the different combination techniques and evaluated for spectral distortion to validate the code. The incorporation of the combination methods into a single processing software enables multi-channel magnetic resonance spectroscopy (MRS) data to be combined and compared for improved spectral quality with little user knowledge of combination techniques. Through the spectral peak distortion simulation of the combination methods, combined signal-to-noise ratio (SNR) values from the literature were verified. The spectral peak distortion simulation provides a secondary tool for researchers to estimate the spectral SNR levels when spectral distortion could occur and use this knowledge to further guide the selection of their combination technique. The McMRSGUI provides a software toolkit for evaluating multi-channel MRS data and their combination. Simulations evaluating spectral distortion at different noise levels were performed for each combination method to validate the GUI and demonstrate a method for researchers to assess the combined SNR levels at which they could be introducing spectral distortion.

High-resolution, 3D multi-TE 1 H MRSI using fast spatiospectral encoding and subspace imaging

PURPOSE

To develop a novel method to achieve fast, high-resolution, 3D multi-TE ¹ H-MRSI of the brain.

METHODS

A new multi-TE MRSI acquisition strategy was developed that integrates slab selective excitation with adiabatic refocusing for better volume coverage, rapid spatiospectral encoding, sparse multi-TE sampling, and interleaved water navigators for field mapping and calibration. Special data processing strategies were developed to interpolate the sparsely sampled data, remove nuisance signals, and reconstruct multi-TE spatiospectral distributions with high SNR. Phantom and in vivo experiments have been carried out to demonstrate the capability of the proposed method.

RESULTS

The proposed acquisition can produce multi-TE ¹ H-MRSI data with three TEs at a nominal spatial resolution of 3.4 × 3.4 × 5.3 mm³ in around 20 min. High-SNR brain metabolite spatiospectral reconstructions can be obtained from both a metabolite phantom and in vivo experiments by the proposed method.

CONCLUSION

High-resolution, 3D multi-TE ¹ H-MRSI of the brain can be achieved within clinically feasible time. This capability, with further optimizations, could be translated to clinical applications and neuroscience studies where simultaneously mapping metabolites and neurotransmitters and TE-dependent molecular spectral changes are of interest.

Effects of apodization smoothing and denoising on spectral fitting

PURPOSE

Visual review of individual spectra in magnetic resonance spectroscopic imaging (MRSI) data benefits from the application of spectral smoothing; however, if this processing step is applied prior to spectral analysis this can impact the accuracy of the quantitation. This study aims to analyze the effect of spectral denoising and apodization smoothing on the quantitation of whole-brain MRSI data obtained at short TE.

METHODS

Short-TE MRSI data obtained at 3 T were analyzed with no spectral smoothing, following (i) Gaussian apodization with values of 1, 2, 4, 6, and 8 Hz, and (ii) denoising using principal component analysis (dnPCA) with 3 different values for the number of retained principal components. The mean lobar white matter estimates for four metabolites, signal-to-noise ratio (SNR), spectral linewidth, and confidence intervals were compared to data reconstructed using no smoothing. Additionally, a voxel-wise comparison for N-acetylaspartate quantitation with different smoothing schemes was performed.

RESULTS

Significant pairwise differences were seen for all Gaussian smoothing methods as compared to no smoothing (p<0.001) in linewidth and metabolite estimates, whereas dnPCA methods showing no statistically significant differences in these measures. Confidence intervals decreased, and SNR increased with increasing levels of apodization smoothing or dnPCA denoising.

CONCLUSION

Mild Gaussian apodization (≤2 Hz at 3 T) can be applied with minimal (1%) errors in quantitation; however, smoothing values greater than that can significantly affect metabolite quantification. In contrast, mild to moderate dnPCA based denoising provides quantitative results that are consistent with the analysis of unsmoothed data and this method is recommended for spectral denoising.

Overdiscrete echo-planar spectroscopic imaging with correlated higher-order phase correction

PURPOSE

To introduce a robust methodology for fast ¹ H MRSI of the brain at 3T with improved SNR and reduced phase-related artifacts.

METHOD

An accelerated acquisition scheme using echo-planar spectroscopic imaging (EPSI) was combined with the overdiscrete reconstruction framework. This approach enables the interleaved acquisition of a water reference scan at each phase encoding step, maximizing its correlation with the water-suppressed measurement. Moreover, a generalized high-order phase correction was incorporated into the reconstruction pipeline. The spatial-temporal phase correction term was estimated from the reference scan and interpolated to high resolution using a polynomial basis. The method was implemented at 3T and validated with phantom and in vivo experiments.

RESULTS

The methodology showed the elimination of spectral artifacts generated by phase disturbances and achieved mean SNR gains in vivo of 3.18 and 1.19 compared to standard reconstructions with corrections performed at nominal and high resolution, respectively. EPSI scans with interleaved water acquisition showed to be robust to system instabilities and potentially to patient motion. Moreover, phase distortions were effectively corrected in a single step, avoiding additional reference measurements and post-processing steps.

CONCLUSION

The overdiscrete reconstruction framework with high-order phase correction allowed to effectively correct for distortions, related to B₀ inhomogeneities, B₀ drift, eddy currents, and system vibrations. Furthermore, the presented reconstruction method, combined with EPSI acquisitions, demonstrated improved measurement stability, substantial SNR enhancement, better spectral linewidth, and effective artifact removal.

Optimal Phased-Array Signal Combination For Polyunsaturated Fatty Acids Measurement In Breast Cancer Using Multiple Quantum Coherence MR Spectroscopy At 3T

Polyunsaturated fatty acid (PUFA), a key marker in breast cancer, is non-invasively quantifiable using multiple quantum coherence (MQC) magnetic resonance spectroscopy (MRS) at the expense of losing half of the signal. Signal combination for phased array coils provides potential pathways to enhance the signal to noise ratio (SNR), with current algorithms developed for conventional brain MRS. Since PUFA spectra and the biochemical environment in the breast deviate significantly from those in the brain, we set out to identify the optimal algorithm for PUFA in breast cancer. Combination algorithms were compared using PUFA spectra from 17 human breast tumour specimens, 15 healthy female volunteers, and 5 patients with breast cancer on a clinical 3 T MRI scanner. Adaptively Optimised Combination (AOC) yielded the maximum SNR improvement in specimens (median, 39.5%; interquartile range: 35.5-53.2%, p < 0.05), volunteers (82.4 ± 37.4%, p < 0.001), and patients (median, 61%; range: 34-105%, p < 0.05), while independent from voxel volume (rho = 0.125, p = 0.632), PUFA content (rho = 0.256, p = 0.320) or water/fat ratio (rho = 0.353, p = 0.165). Using AOC, acquisition in patients is 1.5 times faster compared to non-noise decorrelated algorithms. Therefore, AOC is the most suitable current algorithm to improve SNR or accelerate the acquisition of PUFA MRS from breast in a clinical setting.

Coil combination methods for multi-channel hyperpolarized 13C imaging data from human studies

Effective coil combination methods for human hyperpolarized ¹³C spectroscopy multi-channel data had been relatively unexplored. This study implemented and tested several coil combination methods, including (1) the sum-of-squares (SOS), (2) singular value decomposition (SVD), (3) Roemer method by using reference peak area as a sensitivity map (RefPeak), and (4) Roemer method by using ESPIRiT-derived sensitivity map (ESPIRiT). These methods were evaluated by numerical simulation, thermal phantom experiments, and human cancer patient studies. Overall, the SVD, RefPeak, and ESPIRiT methods demonstrated better accuracy and robustness than the SOS method. Extracting complex pyruvate signal provides an easy and excellent approximation of the coil sensitivity map while maintaining valuable phase information of the coil-combined data.

Proton MR spectroscopy in the breast: Technical innovations and clinical applications

Proton magnetic resonance spectroscopy (MRS) is a promising noninvasive diagnostic technique for investigation of breast cancer metabolism. Spectroscopic imaging data may be obtained following contrast-enhanced MRI by applying the point-resolved spectroscopy sequence (PRESS) or the stimulated echo acquisition mode (STEAM) sequence from the MR voxel encompassing the breast lesion. Total choline signal (tCho) measured in vivo using either a qualitative or quantitative approach has been used as a diagnostic test in the workup of malignant breast lesions. In addition to tCho metabolites, other relevant metabolites, including multiple lipids, can be detected and monitored. MRS has been heavily investigated as an adjunct to morphologic and dynamic MRI to improve diagnostic accuracy in breast cancer, obviating unnecessary benign biopsies. Besides its use in the staging of breast cancer, other promising applications have been recently investigated, including the assessment of treatment response and therapy monitoring. This review provides guidance on spectroscopic acquisition and quantification methods and highlights current and evolving clinical applications of proton MRS. Level of Evidence 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.

A comparison of coil combination strategies in 3D multi-channel MRSI reconstruction for patients with brain tumors

The goal of this study was to find the most robust algorithm for a phase-sensitive coil combination of 3D single-cycle and lactate-edited, multi-channel H-1 point-resolved spectroscopy (PRESS) localized echo planar spectroscopic imaging (EPSI) data for clinical applications in the brain. Data were acquired over 5-10 minutes at 3T using 8- or 32-channel array coils. Peak referencing with residual water and N-acetyl-aspartate, first-point phasing, generalized least squared (GLS) and whitened singular-value decomposition (WSVD) combination algorithms were evaluated relative to unsuppressed water with data from a phantom, six volunteers and 55 patients with brain tumors. Comparison metrics were signal-to-noise ratio, coefficient of variance and percent signal increase. Where residual water was present, using it as a reference peak for phasing and weighting factors from an imaging calibration scan gave the best overall performance. Greater improvement was seen for large selected volumes (>720 cm³ ) and for the 32-channel array (25%) compared with the 8-channel array (19%). Applying voxel-by-voxel phase corrections produced a larger increase in performance for the 32- versus 8-channel coil. We conclude that, for clinically relevant 3D H-1 PRESS localized EPSI studies, the most robust technique employed individual phase maps generated from high residual water and individual amplitude maps generated from calibration scans.

High-resolution echo-planar spectroscopic imaging at ultra-high field

MR spectroscopic imaging (MRSI) at ultra-high field (≥7 T) benefits from improved sensitivity that allows the detection of low-concentration metabolites in the brain. However, optimized acquisition techniques are required to overcome inherent limitations of MRSI at ultra-high field. This work describes an optimized method for fast high-resolution ¹ H-MRSI of the brain at 7 T. The proposed acquisition sequence combines precise volume localization using semi-localization by adiabatic selective refocusing, fast spatial encoding using high-bandwidth symmetric echo-planar spectroscopic imaging (EPSI), and robust water suppression with variable power and optimized relaxation delays. This showed improved robustness to B₀ and B₁⁺ inhomogeneities, eddy currents, nuisance signal contamination and system instabilities. Furthermore, a method for correction of phase inconsistencies in symmetric EPSI enabled high-bandwidth measurements at 7 T. The proposed correction effectively removed spectral ghosting using a single-shot water reference scan. This framework was tested in healthy volunteers at 7 T and spectral quality was compared with lower-spatial-resolution scans, measured at 3 T using the same methodology. A gain in the signal-to-noise ratio (SNR) per unit volume and unit time of 1.57 was achieved, keeping acquisition time short (5 min) and the specific absorption rate within the permitted limits. This SNR enhancement obtained at ultra-high field enabled high-resolution (0.25-0.375 mL) metabolite mapping of the brain within a clinically feasible scan time. The correlation of the reconstructed maps with anatomical structures was observed, showing the diagnostic potential of the technique.

Difference optimization: Automatic correction of relative frequency and phase for mean non-edited and edited GABA 1H MEGA-PRESS spectra

Phase and frequency corrections of magnetic resonance spectroscopic data are of major importance to obtain reliable and unambiguous metabolite estimates as validated in recent research for single-shot scans with the same spectral fingerprint. However, when using the J-difference editing technique ¹H MEGA-PRESS, misalignment between mean edited (ON‾) and non-edited (OFF‾) spectra that may remain even after correction of the corresponding individual single-shot scans results in subtraction artefacts compromising reliable GABA quantitation. We present a fully automatic routine that iteratively optimizes simultaneously relative frequencies and phases between the mean ON‾ and OFF‾¹H MEGA-PRESS spectra while minimizing the sum of the magnitude of the difference spectrum (L¹ norm). The proposed method was applied to simulated spectra at different SNR levels with deliberately preset frequency and phase errors. Difference optimization proved to be more sensitive to small signal fluctuations, as e.g. arising from subtraction artefacts, and outperformed the alternative spectral registration approach, that, in contrast to our proposed linear approach, uses a nonlinear least squares minimization (L² norm), at all investigated levels of SNR. Moreover, the proposed method was applied to 47 MEGA-PRESS datasets acquired in vivo at 3T. The results of the alignment between the mean OFF‾ and ON‾ spectra were compared by applying (a) no correction, (b) difference optimization or (c) spectral registration. Since the true frequency and phase errors are not known for in vivo data, manually corrected spectra were used as the gold standard reference (d). Automatically corrected data applying both, method (b) or method (c), showed distinct improvements of spectra quality as revealed by the mean Pearson correlation coefficient between corresponding real part mean DIFF‾ spectra of R_bd=0.997±0.003 (method (b) vs. (d)), compared to R_ad=0.764±0.220 (method (a) vs. (d)) with no alignment between OFF‾ and ON‾. Method (c) revealed a slightly lower correlation coefficient of R_cd=0.972±0.028 compared to R_bd, that can be ascribed to small remaining subtraction artefacts in the final DIFF‾ spectrum. In conclusion, difference optimization performs robustly with no restrictions regarding the input data range or user intervention and represents a complementary tool to optimize the final DIFF‾ spectrum following the mandatory frequency and phase corrections of single ON and OFF scans prior to averaging.

Integration of 2-hydroxyglutarate-proton magnetic resonance spectroscopy into clinical practice for disease monitoring in isocitrate dehydrogenase-mutant glioma

BACKGROUND

The majority of WHO grades II and III gliomas harbor a missense mutation in the metabolic gene isocitrate dehydrogenase (IDH) and accumulate the metabolite R-2-hydroxyglutarate (R-2HG). Prior studies showed that this metabolite can be detected in vivo using proton magnetic-resonance spectroscopy (MRS), but the sensitivity of this methodology and its clinical implications are unknown.

METHODS

We developed an MR imaging protocol to integrate 2HG-MRS into routine clinical glioma imaging and examined its performance in 89 consecutive glioma patients.

RESULTS

Detection of 2-hydroxyglutarate (2HG) in IDH-mutant gliomas was closely linked to tumor volume, with sensitivity ranging from 8% for small tumors (<3.4 mL) to 91% for larger tumors (>8 mL). In patients undergoing 2HG-MRS prior to surgery, tumor levels of 2HG corresponded with tumor cellularity but not with tumor grade or mitotic index. Cytoreductive therapy resulted in a gradual decrease in 2HG levels with kinetics that closely mirrored changes in tumor volume.

CONCLUSIONS

Our study demonstrates that 2HG-MRS can be linked with routine MR imaging to provide quantitative measurements of 2HG in glioma and may be useful as an imaging biomarker to monitor the abundance of IDH-mutant tumor cells noninvasively during glioma therapy and disease monitoring.

Phased-array combination for MR spectroscopic imaging using a water reference

PURPOSE

To evaluate methods for multichannel combination of three-dimensional MR spectroscopic imaging (MRSI) data with a focus on using information from a water-reference spectroscopic image.

METHODS

Volumetric MRSI data were acquired for a phantom and for human brain using 8- and 32-channel detection. Acquisition included a water-reference dataset that was used to determine the weights for several multichannel combination methods. Results were compared using the signal-to-noise ratio (SNR) of the N-acetylaspartate resonance.

RESULTS

Performance of all methods was very similar for the phantom study, with the whitened singular value decomposition (WSVD) and signal magnitude (S) weighting combination having a small advantage. For in vivo studies, the S weighting, SNR weighting and signal to noise squared (S/N(2) ) weighting were the three best methods and performed similarly. Example spectra and SNR maps indicated that the SVD and WSVD methods tend to fail for voxels at the outer edges of the brain that include strong lipid signal contributions.

CONCLUSION

For data combination of MRSI data using water-reference information, the S/N(2) weighting, SNR and S weighting were the best methods in terms of spectral quality SNR. These methods are also computationally efficient and easy to implement. Magn Reson Med 76:733-741, 2016. © 2015 Wiley Periodicals, Inc.

MRS: a noninvasive window into cardiac metabolism

A well-functioning heart requires a constant supply of a balanced mixture of nutrients to be used for the production of adequate amounts of adenosine triphosphate, which is the main energy source for most cellular functions. Defects in cardiac energy metabolism are linked to several myocardial disorders. MRS can be used to study in vivo changes in cardiac metabolism noninvasively. MR techniques allow repeated measurements, so that disease progression and the response to treatment or to a lifestyle intervention can be monitored. It has also been shown that MRS can predict clinical heart failure and death. This article focuses on in vivo MRS to assess cardiac metabolism in humans and experimental animals, as experimental animals are often used to investigate the mechanisms underlying the development of metabolic diseases. Various MR techniques, such as cardiac (31) P-MRS, (1) H-MRS, hyperpolarized (13) C-MRS and Dixon MRI, are described. A short overview of current and emerging applications is given. Cardiac MRS is a promising technique for the investigation of the relationship between cardiac metabolism and cardiac disease. However, further optimization of scan time and signal-to-noise ratio is required before broad clinical application. In this respect, the ongoing development of advanced shimming algorithms, radiofrequency pulses, pulse sequences, (multichannel) detection coils, the use of hyperpolarized nuclei and scanning at higher magnetic field strengths offer future perspective for clinical applications of MRS.

In vivo detection of acute pain-induced changes of GABA+ and Glx in the human brain by using functional 1H MEGA-PRESS MR spectroscopy

In vivo(1)H MR spectroscopic detection of pain associated metabolic changes in the human brain may allow for an objective evaluation of the perceived pain intensity and assessment of the involved neurotransmitters. Ultimately, it may lead to a deeper understanding of the mechanisms that underlie neuronal pain processing. The present study reports results of time-resolved measurements of acute heat pain induced changes of the excitatory (Glx) and inhibitory (GABA+) neurotransmitter turnover in the anterior cingulate cortex (ACC) and occipital cortex (OC) by using (1)H MEGA-PRESS spectroscopy. In ACC and OC, the ratio Glx/tCr increased by median values of 21.5% (p < 0.001) and 15.7% (p < 0.001), respectively. At the same time, GABA+/tCr decreased by median values of 15.1% (p = 0.114) in ACC and 12.7% (p < 0.001) in OC. To our knowledge, this study demonstrates for the first time the possibility of quantifying pain-induced neurotransmitter changes in the brain by using functional (1)H MEGA-PRESS. The increase of Glx/tCr may be ascribed to an elevated glutamatergic turnover, while the decrease of GABA+/tCr may reflect reduced activity of the inhibitory system in ACC and OC during pain processing.

Combination of multichannel single-voxel MRS signals using generalized least squares

PURPOSE

To propose using the generalized least square (GLS) algorithm for combining multichannel single-voxel magnetic resonance spectroscopy (MRS) signals.

MATERIALS AND METHODS

Phantom and in vivo brain MRS experiments on a 7 T scanner equipped with a 32-channel receiver coil, as well as Monte Carlo simulations, were performed to compare the coefficient of variation (CV) of the GLS method with those of two recently reported spectral combination methods.

RESULTS

Compared to the two existing methods, the GLS method significantly reduced CV values for the simulation, phantom, and in vivo experiments.

CONCLUSION

The GLS method can lead to improved precision of peak quantification.

Proton magnetic resonance spectroscopy: technique for the neuroradiologist

Magnetic resonance spectroscopy (MRS) provides information on neuronal and axonal viability, energetics of cellular structures, and status of cellular membranes. Proton MRS appeals to clinicians and scientists because its application in the clinical setting can increase the specificity of MR imaging. The objective of this article is to provide descriptive concepts of the technique and its application in vivo for a variety of patient populations. When appropriately incorporating MRS into the neuroradiologic evaluation, this technique produces relevant information to radiologists and clinicians for their understanding of adult and pediatric neurologically based disease processes.

Frequency-selective analysis of multichannel magnetic resonance spectroscopy data

In several practical magnetic resonance spectroscopy (MRS) applications the user is interested only in the spectral content of a specific frequency band of the spectrum. A frequency-selective (or sub-band) method estimates only the parameters of those spectroscopic components that lie in a pre-selected frequency band of the spectrum in a computationally efficient manner. Multichannel MRS is a technique that employs phased-array receive coils to increase the signal-to-noise ratio (SNR) in the spectra by combining several simultaneous measurements of the magnetic resonance (MR) relaxation of an excited sample. In this paper we suggest a frequency-selective multichannel parameter estimation approach that combines the appealing features (high speed and improved SNR) of the two techniques above. The presented method shows parameter estimation accuracies comparable to those of existing fullband multichannel techniques in the high SNR case, but at a considerably lower computational complexity, and significantly better parameter estimation accuracies in low SNR scenarios.

Signal-to-noise ratio enhancement of intermolecular double-quantum coherence MR spectroscopy in inhomogeneous fields with phased array coils on a 3 Tesla whole-body scanner

PURPOSE

To improve signal-to-noise ratio (SNR) of intermolecular double-quantum coherence (iDQC) MRS on a 3 Tesla (T) whole-body scanner.

MATERIALS AND METHODS

A 32-channel phased array coil was used to acquire iDQC signal of a MRS phantom in the presence of large field inhomogeneity. The obtained individual spectra from the array elements were combined together in the time domain using a multichannel nonparametric singular value decomposition algorithm. The results were compared quantitatively with those acquired with a circularly polarized (CP) head coil.

RESULTS

The achieved gain in SNR ranges from 1.63 to 2.10 relative to the CP coil, mainly depending on the relative position between the surface of the phased array coil and the voxel of acquisition.

CONCLUSION

SNR enhancement of iDQC MRS in inhomogeneous fields on a 3T whole-body scanner is feasible with phased array coils. This can facilitate iDQC applications of high-resolution in vivo spectroscopy in the presence of field inhomogeneity for potential disease diagnosis in humans.

Receive array magnetic resonance spectroscopy: Whitened singular value decomposition (WSVD) gives optimal Bayesian solution

Receive array coils play a pivotal role in modern MRI. MR spectroscopy can also benefit from the enhanced signal-to-noise ratio and field of view provided by a receive array. In any experiment using an n-element array, n different complex spectra will be recorded and each spectrum unavoidably contains an undesired noise contribution. Previous algorithms for combining spectra have ignored the fact that the noise detected by different array elements is correlated. We introduce here an algorithm for efficiently, robustly, and automatically combining these n spectra using noise whitening and the singular value decomposition to provide the single combined spectrum that has maximum likelihood in the presence of this correlated noise. Simulations are performed that demonstrate the superiority of this approach to previous methods. Experiments in phantoms and in vivo on the brain, heart, and liver of normal volunteers, at 1.5 T and 3 T, using array coils from eight to 32 elements and with (1)H and (31)P nuclei, validate our approach, which provides signal-to-noise ratio improvements of up to 60% in our tests. The whitening and the singular value decomposition algorithm become most advantageous for large arrays, when the noise is markedly correlated, and when the signal-to-noise ratio is low.

Noise correlations and SNR in phased-array MRS

The acquisition of magnetic resonance spectroscopy (MRS) signals by multiple receiver coils can improve the signal-to-noise ratio (SNR) or alternatively can reduce the scan time maintaining a reliable SNR. However, using phased array coils in MRS studies requires efficient data processing and data combination techniques in order to exploit the sensitivity improvement of the phased array coil acquisition method. This paper describes a novel method for the combination of MRS signals acquired by phased array coils, even in presence of correlated noise between the acquisition channels. In fact, although it has been shown that electric and magnetic coupling mechanisms produce correlated noise in the coils, previous algorithms developed for MRS data combination have ignored this effect. The proposed approach takes advantage of a noise decorrelation stage to maximize the SNR of the combined spectra. In particular Principal Component Analysis (PCA) was exploited to project the acquired spectra in a subspace where the noise vectors are orthogonal. In this subspace the SNR weighting method will provide the optimal overall SNR. Performance evaluation of the proposed method is carried out on simulated (1)H-MRS signals and experimental results are obtained on phantom (1)H-MR spectra using a commercially available 8-element phased array coil. Noise correlations between elements were generally low due to the optimal coil design, leading to a fair SNR gain (about 0.5%) in the center of the field of view (FOV). A greater SNR improvement was found in the peripheral FOV regions.

Optimal phased-array combination for spectroscopy

A method for making weighted linear combinations of the spectra acquired by a phased-array coil is described. Unlike most previous combination methods, no special reference points in the data are chosen to represent the coil weights. Instead, all the data points are used, which results in optimal signal-to-noise ratio more reliable estimation. The method uses singular value decomposition to identify the coil weights and extract the principal component of variation in the signal. Subsequent processing of the combined signal (e.g., Fourier transform, baseline correction, phasing) may proceed as per a single coil acquisition.

Proton MR spectroscopy of the brain at 3 T: an update

Proton magnetic resonance spectroscopy ((1)H-MRS) provides specific metabolic information not otherwise observable by any other imaging method. (1)H-MRS of the brain at 3 T is a new tool in the modern neuroradiological armamentarium whose main advantages, with respect to the well-established and technologically advanced 1.5-T (1)H-MRS, include a higher signal-to-noise ratio, with a consequent increase in spatial and temporal resolutions, and better spectral resolution. These advantages allow the acquisition of higher quality and more easily quantifiable spectra in smaller voxels and/or in shorter times, and increase the sensitivity in metabolite detection. However, these advantages may be hampered by intrinsic field-dependent technical issues, such as decreased T(2) signal, chemical shift dispersion errors, J-modulation anomalies, increased magnetic susceptibility, eddy current artifacts, challenges in designing and obtaining appropriate radiofrequency coils, magnetic field instability and safety hazards. All these limitations have been tackled by manufacturers and researchers and have received one or more solutions. Furthermore, advanced (1)H-MRS techniques, such as specific spectral editing, fast (1)H-MRS imaging and diffusion tensor (1)H-MRS imaging, have been successfully implemented at 3 T. However, easier and more robust implementations of these techniques are still needed before they can become more widely used and undertake most of the clinical and research (1)H-MRS applications.

Current diagnostic trends in radiology

Since the discovery of X-rays by Wilhelm Conrad R?entgen at the end of the 19th century, diagnostic imaging techniques have been continously improved by technological advances, bringing radiological diagnosis into the very center of modern medicine. Nowadays, it is hard to imagine therapy planning without previous radiological examination. Great advances in the field of computer technology have been accompanied by development of radiological techniques, and today they include not only morphological and anatomical, but also dynamic, functional and molecular imaging. This paper is an overview of new and improved radiological techniques and their implementation.