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.

J-difference GABA-edited MRS reveals altered cerebello-thalamo-cortical metabolism in patients with hepatic encephalopathy.

Hepatic encephalopathy (HE) is a common neurological manifestation of liver cirrhosis and is characterized by an increase of ammonia in the brain accompanied by a disrupted neurotransmitter balance, including the GABAergic and glutamatergic systems. The aim of this study is to investigate metabolic abnormalities in the cerebello-thalamo-cortical system of HE patients using GABA-edited MRS and links between metabolite levels, disease severity, critical flicker frequency (CFF), motor performance scores, and blood ammonia levels. GABA-edited MRS was performed in 35 participants (16 controls, 19 HE patients) on a clinical 3 T MRI system. MRS voxels were placed in the right cerebellum, left thalamus, and left motor cortex. Levels of GABA+ and of other metabolites of interest (glutamine, glutamate, myo-inositol, glutathione, total choline, total NAA, and total creatine) were assessed. Group differences in metabolite levels and associations with clinical metrics were tested. GABA+ levels were significantly increased in the cerebellum of patients with HE. GABA+ levels in the motor cortex were significantly decreased in HE patients, and correlated with the CFF (r = 0.73; p < .05) and motor performance scores (r = -0.65; p < .05). Well-established HE-typical metabolite patterns (increased glutamine, decreased myo-inositol and total choline) were confirmed in all three regions and were closely linked to clinical metrics. In summary, our findings provide further evidence for alterations in the GABAergic system in the cerebellum and motor cortex in HE. These changes were accompanied by characteristic patterns of osmolytes and oxidative stress markers in the cerebello-thalamo-cortical system. These metabolic disturbances are a likely contributor to HE motor symptoms in HE. In patients with hepatic encephalopathy, GABA+ levels in the cerebello-thalamo-cortical loop are significantly increased in the cerebellum and significantly decreased in the motor cortex. GABA+ levels in the motor cortex strongly correlate with critical flicker frequency (CFF) and motor performance score (pegboard test tPEG), but not blood ammonia levels (NH3).

Continuous Automated Analysis Workflow for MRS Studies.

Magnetic resonance spectroscopy (MRS) can non-invasively measure levels of endogenous metabolites in living tissue and is of great interest to neuroscience and clinical research. To this day, MRS data analysis workflows differ substantially between groups, frequently requiring many manual steps to be performed on individual datasets, e.g., data renaming/sorting, manual execution of analysis scripts, and manual assessment of success/failure. Manual analysis practices are a substantial barrier to wider uptake of MRS. They also increase the likelihood of human error and prevent deployment of MRS at large scale. Here, we demonstrate an end-to-end workflow for fully automated data uptake, processing, and quality review.The proposed continuous automated MRS analysis workflow integrates several recent innovations in MRS data and file storage conventions. They are efficiently deployed by a directory monitoring service that automatically triggers the following steps upon arrival of a new raw MRS dataset in a project folder: (1) conversion from proprietary manufacturer file formats into the universal format NIfTI-MRS; (2) consistent file system organization according to the data accumulation logic standard BIDS-MRS; (3) executing a command-line executable of our open-source end-to-end analysis software Osprey; (4) e-mail delivery of a quality control summary report for all analysis steps.The automated architecture successfully completed for a demonstration dataset. The only manual step required was to copy a raw data folder into a monitored directory.Continuous automated analysis of MRS data can reduce the burden of manual data analysis and quality control, particularly for non-expert users and multi-center or large-scale studies and offers considerable economic advantages.

Spectral diffusion analysis of kidney intravoxel incoherent motion MRI in healthy volunteers and patients with renal pathologies.

PURPOSE: To assess the feasibility of measuring tubular and vascular signal fractions in the human kidney using nonnegative least-square (NNLS) analysis of intravoxel incoherent motion data collected in healthy volunteers and patients with renal pathologies. METHODS: MR imaging was performed at 3 Tesla in 12 healthy subjects and 3 patients with various kidney pathologies (fibrotic kidney disease, failed renal graft, and renal masses). Relative signal fractions f and mean diffusivities of the diffusion components in the cortex, medulla, and renal lesions were obtained using the regularized NNLS fitting of the intravoxel incoherent motion data. Test-retest repeatability of the NNLS approach was tested in 5 volunteers scanned twice. RESULTS: In the healthy kidneys, the NNLS method yielded diffusion spectra with 3 distinguishable components that may be linked to the slow tissue water diffusion, intermediate tubular and vascular flow, and fast blood flow in larger vessels with the relative signal fractions, fslow , finterm and ffast , respectively. In the pathological kidneys, the diffusion spectra varied substantially from those acquired in the healthy kidneys. Overall, the renal cyst showed substantially higher finterm and lower fslow , whereas the fibrotic kidney, failed renal graft, and renal cell carcinoma demonstrated the opposite trend. CONCLUSION: NNLS-based intravoxel incoherent motion could potentially become a valuable tool in assessing changes in tubular and vascular volume fractions under pathophysiological conditions.

In silico GABA+ MEGA-PRESS: Effects of signal-to-noise ratio and linewidth on modeling the 3 ppm GABA+ resonance.

To investigate the GABA+ modeling accuracy of MEGA-PRESS GABA+-edited MRS data with various spectral quality scenarios, the influence of varying signal-to-noise ratio (SNR) and linewidth on the model estimates was quantified. MEGA-PRESS data from 46 volunteers were averaged to generate a template MEGA-PRESS spectrum, which was modeled and quantified to generate a GABA+ level ground truth. This spectrum was then manipulated by adding 427 combinations of varying artificial noise levels and line broadening, mimicking variations in GABA+ SNR and B0 homogeneity. GABA+ modeling and quantification was performed with 100 simulated spectra per condition using automated routines in both Gannet 3.0 and Tarquin. The GABA+ estimation error was calculated as the relative deviation to the quantified GABA+ ground truth levels to assess the accuracy of GABA+ modeling. Finally, the accordance between the simulations and different in vivo scenarios was assessed. The GABA+ estimation error was smaller than 5% for all GABA+ SNR values with creatine linewidths lower than 9.7 Hz in Gannet 3.0 or unequal 10.6 Hz in Tarquin. The standard deviation of the GABA+ amplitude over 100 spectra per condition varied between 3.1 and 17% (Gannet 3.0) and between 1 and 11% (Tarquin) over the in vivo relevant GABA+ SNR range between 2.6 and 3.5. GABA+ edited studies might be realized for voxels with low GABA+ SNR at the cost of higher group-level variance. The accuracy of GABA+ modeling had no relation to commonly used quality metrics. The Tarquin algorithm was found to be more robust against linewidth changes than the fitting algorithm in Gannet.

Ammonia-weighted imaging by chemical exchange saturation transfer MRI at 3 T.

Hepatic encephalopathy (HE) is triggered by liver cirrhosis and is associated with an increased ammonia level within the brain tissue. The goal of this study was to investigate effects of ammonia on in vitro amide proton transfer (APT)-weighted chemical exchange saturation transfer (CEST) imaging in order to develop an ammonia-sensitive brain imaging method. APT-weighted CEST imaging was performed on phantom solutions including pure ammonia, bovine serum albumin (BSA), and tissue homogenate samples doped with various ammonia concentrations. All CEST data were assessed by magnetization transfer ratio asymmetry. In addition, optical methods were used to determine possible structural changes of the proteins in the BSA phantom. In vivo feasibility measurements were acquired in one healthy participant and two patients suffering from HE, a disease associated with increased brain ammonia levels. The CEST effect of pure ammonia showed a base-catalyzed behavior. At pH values greater than 5.6 no CEST effect was observed. The APT-weighted signal was significantly reduced for ammonia concentrations of 5mM or more at fixed pH values within the different protein phantom solutions. The optical methods revealed no protein aggregation or denaturation for ammonia concentrations less than 5mM. The in vivo measurements showed tissue specific and global reduction of the observed CEST signal in patients with HE, possibly linked to pathologically increased ammonia levels. APT-weighted CEST imaging is sensitive to changes in ammonia concentrations. Thus, it seems useful for the investigation of pathologies with altered tissue ammonia concentrations such as HE. However, the underlying mechanism needs to be explored in more detail in future in vitro and in vivo investigations.

Chemical exchange saturation transfer imaging in hepatic encephalopathy.

Hepatic encephalopathy (HE) is a common complication in liver cirrhosis and associated with an invasion of ammonia into the brain through the blood-brain barrier. Resulting higher ammonia concentrations in the brain are suggested to lead to a dose-dependent gradual increase of HE severity and an associated impairment of brain function. Amide proton transfer-weighted (APTw) chemical exchange saturation transfer (CEST) imaging has been found to be sensitive to ammonia concentration. The aim of this work was to study APTw CEST imaging in patients with HE and to investigate the relationship between disease severity, critical flicker frequency (CFF), psychometric test scores, blood ammonia, and APTw signals in different brain regions. Whole-brain APTw CEST images were acquired in 34 participants (14 controls, 20 patients (10 minimal HE, 10 manifest HE)) on a 3 T clinical MRI system accompanied by T1 mapping and structural images. T1 normalized magnetization transfer ratio asymmetry analysis was performed around 3 ppm after B0 and B1 correction to create APTw images. All APTw images were spatially normalized into a cohort space to allow direct comparison. APTw images in 6 brain regions (cerebellum, occipital cortex, putamen, thalamus, caudate, white matter) were tested for group differences as well as the link to CFF, psychometric test scores, and blood ammonia. A decrease in APTw intensities was found in the cerebellum and the occipital cortex of manifest HE patients. In addition, APTw intensities in the cerebellum correlated positively with several psychometric scores, such as the fine motor performance scores MLS1 for hand steadiness / tremor (r = 0.466; p = .044) and WRT2 for motor reaction time (r = 0.523; p = .022). Moreover, a negative correlation between APTw intensities and blood ammonia was found for the cerebellum (r = -0.615; p = .007) and the occipital cortex (r = -0.478; p = .045). An increase of APTw intensities was observed in the putamen of patients with minimal HE and correlated negatively with the CFF (r = -0.423; p = .013). Our findings demonstrate that HE is associated with regional differential alterations in APTw signals. These variations are most likely a consequence of hyperammonemia or hepatocerebral degeneration processes, and develop in parallel with disease severity.

Use of quantitative brain water imaging as concentration reference for J-edited MR spectroscopy of GABA.

PURPOSE: To compare two different methods of obtaining the water reference for determination of quantitative water-scaled in vivo concentration estimates of γ-aminobutyric acid (GABA). METHODS: Water-scaled GABA estimates from localized J-difference edited MR spectroscopy experiments can be computed using standard values for tissue-specific water content and relaxation times. Water content and relaxation may, however, be altered in pathology. This work re-analyzed data from a recent study in healthy controls and patients with minimal (mHE) or grade I (HE 1) hepatic encephalopathy, a disease associated with slight elevation of brain water content. J-difference edited MR spectroscopy data were combined with quantitative brain water measures, which provided individual water density references and T1 relaxation times. Resulting GABA estimates were compared to concentration values obtained using standard tissue-specific water content and relaxation values. RESULTS: Occipital GABA concentration values obtained from individual water and T1 maps were 1.64±0.35mM in controls, and significantly higher (P<0.01) than in mHE (1.15±0.28mM) and HE 1 patients (1.18±0.09mM). Results from the tissue-dependent approach (1.58±0.30mM (controls), 1.10±0.27mM (mHE) and 1.12±0.12mM (HE 1)) were slightly lower (P<0.05 in each group). CONCLUSION: Water-scaled in vivo GABA estimates can be obtained with individual water density and T1 relaxation mapping. This approach may be useful for studying GABA levels in pathologies with substantial brain water content or relaxation changes.