Improving Microstructural Estimation in Time-Dependent Diffusion MRI With a Bayesian Method.

BACKGROUND: Accurately fitting diffusion-time-dependent diffusion MRI (td-dMRI) models poses challenges due to complex and nonlinear formulas, signal noise, and limited clinical data acquisition. PURPOSE: Introduce a Bayesian methodology to refine microstructural fitting within the IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion) model and optimize the prior distribution within the Bayesian framework. STUDY TYPE: Retrospective. POPULATION: Involving 69 pediatric patients (median age 6 years, interquartile range [IQR] 3-9 years, 61% male) with 41 low-grade and 28 high-grade gliomas, of which 76.8% were identified within the brainstem or cerebellum. FIELD STRENGTH/SEQUENCE: 3 T, oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE). ASSESSMENT: The Bayesian method's performance in fitting cell diameter ( d $$ d $$ ), intracellular volume fraction ( f in $$ {f}_{in} $$ ), and extracellular diffusion coefficient ( D ex $$ {D}_{ex} $$ ) was compared against the NLLS method, considering simulated and experimental data. The tumor region-of-interest (ROI) were manually delineated on the b0 images. The diagnostic performance in distinguishing high- and low-grade gliomas was assessed, and fitting accuracy was validated against H&E-stained pathology. STATISTICAL TESTS: T-test, receiver operating curve (ROC), area under the curve (AUC) and DeLong's test were conducted. Significance considered at P < 0.05. RESULTS: Bayesian methodology manifested increased accuracy with robust estimates in simulation (RMSE decreased by 29.6%, 40.9%, 13.6%, and STD decreased by 29.2%, 43.5%, and 24.0%, respectively for d $$ d $$ , f in $$ {f}_{in} $$ , and D ex $$ {D}_{ex} $$ compared to NLLS), indicating fewer outliers and reduced error. Diagnostic performance for tumor grade was similar in both methods, however, Bayesian method generated smoother microstructural maps (outliers ratio decreased by 45.3% ± 19.4%) and a marginal enhancement in correlation with H&E staining result (r = 0.721 for f in $$ {f}_{in} $$ compared to r = 0.698 using NLLS, P = 0.5764). DATA CONCLUSION: The proposed Bayesian method substantially enhances the accuracy and robustness of IMPULSED model estimation, suggesting its potential clinical utility in characterizing cellular microstructure. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation.

PURPOSE: The interest in applying and modeling dynamic MRS has recently grown. Two-dimensional modeling yields advantages for the precision of metabolite estimation in interrelated MRS data. However, it is unknown whether including all transients simultaneously in a 2D model without averaging (presuming a stable signal) performs similarly to one-dimensional (1D) modeling of the averaged spectrum. Therefore, we systematically investigated the accuracy, precision, and uncertainty estimation of both described model approaches. METHODS: Monte Carlo simulations of synthetic MRS data were used to compare the accuracy and uncertainty estimation of simultaneous 2D multitransient linear-combination modeling (LCM) with 1D-LCM of the average. A total of 2,500 data sets per condition with different noise representations of a 64-transient MRS experiment at six signal-to-noise levels for two separate spin systems (scyllo-inositol and gamma-aminobutyric acid) were analyzed. Additional data sets with different levels of noise correlation were also analyzed. Modeling accuracy was assessed by determining the relative bias of the estimated amplitudes against the ground truth, and modeling precision was determined by SDs and Cramér-Rao lower bounds (CRLBs). RESULTS: Amplitude estimates for 1D- and 2D-LCM agreed well and showed a similar level of bias compared with the ground truth. Estimated CRLBs agreed well between both models and with ground-truth CRLBs. For correlated noise, the estimated CRLBs increased with the correlation strength for the 1D-LCM but remained stable for the 2D-LCM. CONCLUSION: Our results indicate that the model performance of 2D multitransient LCM is similar to averaged 1D-LCM. This validation on a simplified scenario serves as a necessary basis for further applications of 2D modeling.

Early excitatory-inhibitory cortical modifications following skill learning are associated with motor memory consolidation and plasticity overnight.

Consolidation of motor memories is vital to offline enhancement of new motor skills and involves short and longer-term offline processes following learning. While emerging evidence link glutamate and GABA dynamics in the primary motor cortex (M1) to online motor skill practice, its relationship with offline consolidation processes in humans is unclear. Using two-day repeated measures of behavioral and multimodal neuroimaging data before and following motor sequence learning, we show that short-term glutamatergic and GABAergic responses in M1 within minutes after learning were associated with longer-term learning-induced functional, structural, and behavioral modifications overnight. Furthermore, Glutamatergic and GABAergic modifications were differentially associated with different facets of motor memory consolidation. Our results point to unique and distinct roles of Glutamate and GABA in motor memory consolidation processes in the human brain across timescales and mechanistic levels, tying short-term changes on the neurochemical level to overnight changes in macroscale structure, function, and behavior.

Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation.

Purpose: The interest in applying and modeling dynamic MRS has recently grown. 2D modeling yields advantages for the precision of metabolite estimation in interrelated MRS data. However, it is unknown whether including all transients simultaneously in a 2D model without averaging (presuming a stable signal) performs similarly to 1D modeling of the averaged spectrum. Therefore, we systematically investigated the accuracy, precision, and uncertainty estimation of both described model approaches. Methods: Monte Carlo simulations of synthetic MRS data were used to compare the accuracy and uncertainty estimation of simultaneous 2D multi-transient LCM with 1D-LCM of the average. 2,500 datasets per condition with different noise representations of a 64-transient MRS experiment at 6 signal-to-noise levels for two separate spin systems (scyllo-inositol and GABA) were analyzed. Additional datasets with different levels of noise correlation were also analyzed. Modeling accuracy was assessed by determining the relative bias of the estimated amplitudes against the ground truth, and modeling precision was determined by standard deviations and Cramér-Rao Lower Bounds (CRLB). Results: Amplitude estimates for 1D- and 2D-LCM agreed well and showed similar level of bias compared to the ground truth. Estimated CRLBs agreed well between both models and with ground truth CRLBs. For correlated noise the estimated CRLBs increased with the correlation strength for the 1D-LCM but remained stable for the 2D-LCM. Conclusion: Our results indicate that the model performance of 2D multi-transient LCM is similar to averaged 1D-LCM. This validation on a simplified scenario serves as necessary basis for further applications of 2D modeling.

Autonomous animal heating and cooling system for temperature-regulated magnetic resonance experiments.

Temperature is a hallmark parameter influencing almost all magnetic resonance properties (e.g., T1 , T2 , proton density, and diffusion). In the preclinical setting, temperature has a large influence on animal physiology (e.g., respiration rate, heart rate, metabolism, and oxidative stress) and needs to be carefully regulated, especially when the animal is under anesthesia and thermoregulation is disrupted. We present an open-source heating and cooling system capable of regulating the temperature of the animal. The system was designed using Peltier modules capable of heating or cooling a circulating water bath with active temperature feedback. Feedback was obtained using a commercial thermistor, placed in the animal rectum, and a proportional-integral-derivative controller was used to modulate the temperature. Its operation was demonstrated in a phantom as well as in mouse and rat animal models, where the standard deviation of the temperature of the animal upon convergence was less than a 10th of a degree. An application where brain temperature of a mouse was modulated was demonstrated using an invasive optical probe and noninvasive magnetic resonance spectroscopic thermometry measurements.

Diffusion-weighted MR spectroscopy: Consensus, recommendations, and resources from acquisition to modeling.

Brain cell structure and function reflect neurodevelopment, plasticity, and aging; and changes can help flag pathological processes such as neurodegeneration and neuroinflammation. Accurate and quantitative methods to noninvasively disentangle cellular structural features are needed and are a substantial focus of brain research. Diffusion-weighted MRS (dMRS) gives access to diffusion properties of endogenous intracellular brain metabolites that are preferentially located inside specific brain cell populations. Despite its great potential, dMRS remains a challenging technique on all levels: from the data acquisition to the analysis, quantification, modeling, and interpretation of results. These challenges were the motivation behind the organization of the Lorentz Center workshop on "Best Practices & Tools for Diffusion MR Spectroscopy" held in Leiden, the Netherlands, in September 2021. During the workshop, the dMRS community established a set of recommendations to execute robust dMRS studies. This paper provides a description of the steps needed for acquiring, processing, fitting, and modeling dMRS data, and provides links to useful resources.

Increased cortical inhibition following brief motor memory reactivation supports reconsolidation and overnight offline learning gains.

Practicing motor skills stabilizes and strengthens motor memories by repeatedly reactivating and reconsolidating them. The conventional view, by which a repetitive practice is required for substantially improving skill performance, has been recently challenged by behavioral experiments, in which even brief reactivations of the motor memory have led to significant improvements in skill performance. However, the mechanisms which facilitate brief reactivation-induced skill improvements remain elusive. While initial memory consolidation has been repeatedly associated with increased neural excitation and disinhibition, reconsolidation has been shown to involve a poorly understood mixture of both excitatory and inhibitory alterations. Here, we followed a 3-d reactivation-reconsolidation framework to examine whether the excitatory/inhibitory mechanisms which underlie brief reactivation and repetitive practice differ. Healthy volunteers practiced a motor sequence learning task using either brief reactivation or repetitive practice and were assessed using ultrahigh field (7T) magnetic resonance spectroscopy at the primary motor cortex (M1). We found that increased inhibition (GABA concentrations) and decreased excitation/inhibition (glutamate/GABA ratios) immediately following the brief reactivation were associated with overnight offline performance gains. These gains were on par with those exhibited following repetitive practice, where no correlations with inhibitory or excitatory changes were observed. Our findings suggest that brief reactivation and repetitive practice depend on fundamentally different neural mechanisms and that early inhibition-and not excitation-is particularly important in supporting the learning gains exhibited by brief reactivation.

Adaptive model-based Magnetic Resonance.

PURPOSE: Conventional sequences are static in nature, fixing measurement parameters in advance in anticipation of a wide range of expected tissue parameter values. We set out to design and benchmark a new, personalized approach-termed adaptive MR-in which incoming subject data is used to update and fine-tune the pulse sequence parameters in real time. METHODS: We implemented an adaptive, real-time multi-echo (MTE) experiment for estimating T2 s. Our approach combined a Bayesian framework with model-based reconstruction. It maintained and continuously updated a prior distribution of the desired tissue parameters, including T2 , which was used to guide the selection of sequence parameters in real time. RESULTS: Computer simulations predicted accelerations between 1.7- and 3.3-fold for adaptive multi-echo sequences relative to static ones. These predictions were corroborated in phantom experiments. In healthy volunteers, our adaptive framework accelerated the measurement of T2 for n-acetyl-aspartate by a factor of 2.5. CONCLUSION: Adaptive pulse sequences that alter their excitations in real time could provide substantial reductions in acquisition times. Given the generality of our proposed framework, our results motivate further research into other adaptive model-based approaches to MRI and MRS.

Autonomous animal heating and cooling system for temperature-regulated MR experiments.

Temperature is a hallmark parameter influencing almost all magnetic resonance properties (e.g., T\textsubscript{1}, T\textsubscript{2}, proton density, diffusion and more). In the pre-clinical setting, temperature has a large influence on animal physiology (e.g., respiration rate, heart rate, metabolism, cellular stress, and more) and needs to be carefully regulated, especially when the animal is under anesthesia and thermoregulation is disrupted. We present an open-source heating and cooling system capable of stabilizing the temperature of the animal. The system was designed using Peltier modules capable of heating or cooling a circulating water bath with active temperature feedback. Feedback was obtained using a commercial thermistor, placed in the animal rectum, and a proportional{\text -}integral{\text -}derivative (PID) controller capable of locking the temperature. Operation was demonstrated in a phantom as well as mouse and rat animal models, where the standard deviation of the temperature of the animal upon convergence was less than a tenth of a degree. An application where brain temperature of a mouse was modulated was demonstrated using an invasive optical probe and non-invasive magnetic resonance spectroscopic thermometry measurements.

Probing lipids relaxation times in breast cancer using magnetic resonance spectroscopic fingerprinting.

OBJECTIVES: To investigate the clinical relevance of the relaxation times of lipids within breast cancer and normal fibroglandular tissue in vivo, using magnetic resonance spectroscopic fingerprinting (MRSF). METHODS: Twelve patients with biopsy-confirmed breast cancer and 14 healthy controls were prospectively scanned at 3 T using a protocol consisting of diffusion tensor imaging (DTI), MRSF, and dynamic contrast-enhanced (DCE) MRI. Single-voxel MRSF data was recorded from the tumor (patients) - identified using DTI - or normal fibroglandular tissue (controls), in under 20 s. MRSF data was analyzed using in-house software. Linear mixed model analysis was used to compare the relaxation times of lipids in breast cancer VOIs vs. normal fibroglandular tissue. RESULTS: Seven distinguished lipid metabolite peaks were identified and their relaxation times were recorded. Of them, several exhibited statistically significant changes between controls and patients, with strong significance (p < 10-3) recorded for several of the lipid resonances at 1.3 ppm (T1 = 355 ± 17 ms vs. 389 ± 27 ms), 4.1 ppm (T1 = 255 ± 86 ms vs. 127 ± 33 ms), 5.22 ppm (T1 = 724 ± 81 ms vs. 516 ± 62 ms), and 5.31 ppm (T2 = 56 ± 5 ms vs. 44 ± 3.5 ms, respectively). CONCLUSIONS: The application of MRSF to breast cancer imaging is feasible and achievable in clinically relevant scan time. Further studies are required to verify and comprehend the underling biological mechanism behind the differences in lipid relaxation times in cancer and normal fibroglandular tissue. KEY POINTS: •The relaxation times of lipids in breast tissue are potential markers for quantitative characterization of the normal fibroglandular tissue and cancer. •Lipid relaxation times can be acquired rapidly in a clinically relevant manner using a single-voxel technique, termed MRSF. •Relaxation times of T1 at 1.3 ppm, 4.1 ppm, and 5.22 ppm, as well as of T2 at 5.31 ppm, were significantly different between measurements within breast cancer and the normal fibroglandular tissue.

The future is 2D: spectral-temporal fitting of dynamic MRS data provides exponential gains in precision over conventional approaches.

PURPOSE: Many MRS paradigms produce 2D spectral-temporal datasets, including diffusion-weighted, functional, and hyperpolarized and enriched (carbon-13, deuterium) experiments. Conventionally, temporal parameters-such as T2 , T1 , or diffusion constants-are assessed by first fitting each spectrum independently and subsequently fitting a temporal model (1D fitting). We investigated whether simultaneously fitting the entire dataset using a single spectral-temporal model (2D fitting) would improve the precision of the relevant temporal parameter. METHODS: We derived a Cramer Rao lower bound for the temporal parameters for both 1D and 2D approaches for 2 experiments: a multi-echo experiment designed to estimate metabolite T2 s, and a functional MRS experiment designed to estimate fractional change ( δ $$ \delta $$ ) in metabolite concentrations. We investigated the dependence of the relative standard deviation (SD) of T2 in multi-echo and δ $$ \delta $$ in functional MRS. RESULTS: When peaks were spectrally distant, 2D fitting improved precision by approximately 20% relative to 1D fitting, regardless of the experiment and other parameter values. These gains increased exponentially as peaks drew closer. Dependence on temporal model parameters was weak to negligible. CONCLUSION: Our results strongly support a 2D approach to MRS fitting where applicable, and particularly in nuclei such as hydrogen and deuterium, which exhibit substantial spectral overlap.

Quantifying the excitatory-inhibitory balance: A comparison of SemiLASER and MEGA-SemiLASER for simultaneously measuring GABA and glutamate at 7T.

The importance of the excitatory-inhibitory (E/I) balance in a wide range of cognitive and behavioral processes has prompted a commensurate interest in methods for reliably quantifying it. Proton Magnetic Resonance Spectroscopy (1H-MRS) remains the only method capable of safely and non-invasively measuring the concentrations of the brain's major excitatory (glutamate) and inhibitory (γ-aminobutyric-acid, GABA) neurotransmitters in-vivo. MRS relies on spectral Mescher-Garwood (MEGA) editing techniques at 3T to distinguish GABA from its overlapping resonances. However, with the increased spectral resolution at ultrahigh field strengths of 7T and above, non-edited spectroscopic techniques become potential viable alternatives to MEGA based approaches, and also address some of their shortcomings, such as signal loss, sensitivity to transmitter inhomogeneities and temporal resolution. We present a comprehensive comparison of both edited and non-edited strategies at 7T for simultaneously quantifying glutamate and GABA from the dorsal anterior cingulate cortex (dACC), and evaluate their reproducibility and relative bias. The combined root-mean-square test-retest reproducibility of Glu and GABA (CVE/I) was as low as 13.3% for unedited MRS at TE=80 ms using SemiLASER localization, while edited MRS at TE=80 ms yielded CVE/I=20% and 21% for asymmetric and symmetric MEGA editing, respectively. An unedited SemiLASER acquisition using a shorter echo time of TE=42 ms yielded CVE/I as low as 24.9%. Our results show that non-edited sequences at an echo time of 80 ms provide better reproducibility than either edited sequences at the same TE, or non-edited sequences at a shorter TE of 42 ms. This is supported by numerical simulations and is driven in part by a pseudo-singlet appearance of the GABA multiplets at TE=80 ms, and the excellent spectral resolution at 7T. Our results uphold a transition to non-edited MRS for monitoring the E/I balance at ultrahigh fields, and stress the importance of using a properly-optimized echo time.

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 TR /TE = 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.

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

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

Increased Glutamate concentrations during prolonged motor activation as measured using functional Magnetic Resonance Spectroscopy at 3T.

Recent implications of glutamatergic signaling in a wide range of psychiatric disorders has highlighted the need to study the dynamics of glutamate (Glu) in the brain outside of steady state. A promising modality for doing so is functional Magnetic Resonance Spectroscopy (fMRS). Recent human studies at high magnetic fields (7T) have reported small but consistent changes in metabolite concentrations, in particular a 2-4% increase in Glu during visual and motor stimulation. While the origins of these changes remain the topic of ongoing research, the ability of fMRS to observe metabolites directly associated with neurotransmission and brain energetics could potentially aid our understanding of brain pathophysiology and the interpretation of functional imaging experiments. For this to happen, the current ultrahigh field results must be reproduced at lower, widely available clinical field strengths, in response to a wide variety of stimuli classes. Our goal herein was to investigate metabolite changes during a hand-clenching motor task at 3T, and to investigate the effect of the stimulation's temporal characteristics on the magnitude of the fMRS changes; specifically, we compared two block-designed functional activation paradigms, using short- and long-cycled clenching designs. Small but statistically significant increases in Glx=Glutamate+Glutamine (3.8%) and Glu (4.0%) concentrations were detected during the long-cycled design, while no statistically significant changes were observed during the short-cycled design. Activation during the long-cycled tasks was correlated to the frequency of clenching. We have also shown that using subject-level analysis in combination with a linear mixed model increases the observed effect size, and could help analyzing the weak MRS signals. Our results are in good agreement with the previous reports acquired at higher field systems, and support the viability of fMRS as a research tool at clinical field strengths, while also emphasizing the importance of the functional paradigm itself.

Optimal echo times for multi-gradient echo-based B0 field-mapping.

B0 field maps are used ubiquitously in neuroimaging, in disciplines ranging from magnetic resonance spectroscopy to temperature mapping and susceptibility-weighted imaging. Most B0 maps are acquired using standard gradient-echo-based vendor-provided sequences, often comprised of two echoes spaced a few milliseconds apart. Herein, we analyze the optimal spacing of echo times, defined as those maximizing precision-minimizing the standard deviation-for a fixed total acquisition time. Field estimation is carried out using a weighted least squares estimator. The standard deviation is shown to be approximately inversely proportional to the total acquisition time, suggesting a law of diminishing returns, whereby substantial gains are obtained up to a certain point, with little improvement beyond that point. Validations are provided in a phantom and a group of volunteers. Multi-gradient echo sequences are readily available on all manufacturer platforms, making our recommendations straightforward to implement on any modern scanner.

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

PURPOSE: Unlike conventional MR spectroscopy (MRS), which only measures metabolite concentrations, multiparametric MRS also quantifies their longitudinal (T1 ) and transverse (T2 ) relaxation times, as well as the radiofrequency transmitter inhomogeneity (B1+ ). To test whether knowledge of these additional parameters can improve the clinical utility of brain MRS, we compare the conventional and multiparametric approaches in terms of expected classification accuracy in differentiating controls from patients with neurological disorders. THEORY AND METHODS: A literature review was conducted to compile metabolic concentrations and relaxation times in a wide range of neuropathologies and regions of interest. Simulations were performed to construct receiver operating characteristic curves and compute the associated areas (area under the curve) to examine the sensitivity and specificity of MRS for detecting each pathology in each region. Classification accuracy was assessed using metabolite concentrations corrected using population-averages for T1 , T2 , and B1+ (conventional MRS); using metabolite concentrations corrected using per-subject values (multiparametric MRS); and using an optimal linear multiparametric estimator comprised of the metabolites' concentrations and relaxation constants (multiparametric MRS). Additional simulations were conducted to find the minimal intra-subject precision needed for each parameter. RESULTS: Compared with conventional MRS, multiparametric approaches yielded area under the curve improvements for almost all neuropathologies and regions of interest. The median area under the curve increased by 0.14 over the entire dataset, and by 0.24 over the 10 instances with the largest individual increases. CONCLUSIONS: Multiparametric MRS can substantially improve the clinical utility of MRS in diagnosing and assessing brain pathology, motivating the design and use of novel multiparametric sequences.

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.

Quantitative multivoxel proton MR spectroscopy for the identification of white matter abnormalities in mild traumatic brain injury: Comparison between regional and global analysis.

BACKGROUND: 3D brain proton MR spectroscopic imaging (1 H MRSI) facilitates simultaneous metabolic profiling of multiple loci, at higher, sub-1 cm3 , spatial resolution than single-voxel 1 H MRS with the ability to separate tissue-type partial volume contribution(s). PURPOSE: To determine if: 1) white matter (WM) damage in mild traumatic brain injury (mTBI) is homogeneously diffuse, or if specific regions are more affected; 2) partial-volume-corrected, structure-specific 1 H MRSI voxel averaging is sensitive to regional WM metabolic abnormalities. STUDY TYPE: Retrospective cross-sectional cohort study. POPULATION: Twenty-seven subjects: 15 symptomatic mTBI patients, 12 matched controls. FIELD STRENGTH/SEQUENCE: 3T using 3D 1 H MRSI over a 360-cm3 volume of interest (VOI) centered over the corpus callosum, partitioned into 480 voxels, each 0.75 cm3 . ASSESSMENT: N-acetyl-aspartate (NAA), creatine, choline, and myo-inositol concentrations estimated in predominantly WM regions: body, genu, and splenium of the corpus callosum, corona radiata, frontal, and occipital WM. STATISTICAL TESTS: Analysis of covariance (ANCOVA) to compare patients with controls in terms of regional concentrations. The effect sizes (Cohen's d) of the mean differences were compared across regions and with previously published global data obtained with linear regression of the WM over the entire VOI in the same dataset. RESULTS: Despite patients' global VOI WM NAA being significantly lower than the controls', no regional differences were observed for any metabolite. Regional NAA comparisons, however, were all unidirectional (patients' NAA concentrations < controls') within a narrow range: 0.3 ≤ Cohen's d ≤ 0.6. DATA CONCLUSION: Since the patient group was symptomatic and exhibiting global WM NAA deficits, these findings suggest: 1) diffuse axonal mTBI damage; that is 2) below the 1 H MRSI detection threshold in small regions. Therefore, larger, ie, more sensitive, single-voxel 1 H MRS, placed anywhere in WM regions, may be well suited for mTBI 1 H MRS studies, given that these results are confirmed in other cohorts. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1424-1432.