Altered macromolecular pattern and content in the aging human brain

Macromolecule Modelling for Improved Metabolite Quantification Using Short Echo Time Brain 1H-MRS at 3 T and 7 T: The PRaMM Model

To improve reliability of metabolite quantification at both, 3 T and 7 T, we propose a novel parametrized macromolecules quantification model (PRaMM) for brain 1H MRS, in which the ratios of macromolecule peak intensities are used as soft constraints. Full- and metabolite-nulled spectra were acquired in three different brain regions with different ratios of grey and white matter from six healthy volunteers, at both 3 T and 7 T. Metabolite-nulled spectra were used to identify highly correlated macromolecular signal contributions and estimate the ratios of their intensities. These ratios were then used as soft constraints in the proposed PRaMM model for quantification of full spectra. The PRaMM model was validated by comparison with a single-component macromolecule model and a macromolecule subtraction technique. Moreover, the influence of the PRaMM model on the repeatability and reproducibility compared with those other methods was investigated. The developed PRaMM model performed better than the two other approaches in all three investigated brain regions. Several estimates of metabolite concentration and their Cramér-Rao lower bounds were affected by the PRaMM model reproducibility, and repeatability of the achieved concentrations were tested by evaluating the method on a second repeated acquisitions dataset. Although the observed effects on both metrics were not significant, the fit quality metrics were improved for the PRaMM method (p ≤ 0.0001). Minimally detectable changes are in the range 0.5-1.9 mM, and the percentage coefficients of variations are lower than 10% for almost all the clinically relevant metabolites. Furthermore, potential overparameterization was ruled out. Here, the PRaMM model, a method for an improved quantification of metabolites, was developed, and a method to investigate the role of the MM background and its individual components from a clinical perspective is proposed.

Age and visual cortex inhibition: a TMS-MRS study

Paired-pulse transcranial magnetic stimulation is a valuable tool for investigating inhibitory mechanisms in motor cortex. We recently demonstrated its use in measuring cortical inhibition in visual cortex, using an approach in which participants trace the size of phosphenes elicited by stimulation to occipital cortex. Here, we investigate age-related differences in primary visual cortical inhibition and the relationship between primary visual cortical inhibition and local GABA+ in the same region, estimated using magnetic resonance spectroscopy. GABA+ was estimated in 28 young (18 to 28 years) and 47 older adults (65 to 84 years); a subset (19 young, 18 older) also completed a paired-pulse transcranial magnetic stimulation session, which assessed visual cortical inhibition. The paired-pulse transcranial magnetic stimulation measure of inhibition was significantly lower in older adults. Uncorrected GABA+ in primary visual cortex was also significantly lower in older adults, while measures of GABA+ that were corrected for the tissue composition of the magnetic resonance spectroscopy voxel were unchanged with age. Furthermore, paired-pulse transcranial magnetic stimulation-measured inhibition and magnetic resonance spectroscopy-measured tissue-corrected GABA+ were significantly positively correlated. These findings are consistent with an age-related decline in cortical inhibition in visual cortex and suggest paired-pulse transcranial magnetic stimulation effects in visual cortex are driven by GABAergic mechanisms, as has been demonstrated in motor cortex.

Age-related differences in macromolecular resonances observed in ultra-short-TE STEAM MR spectra at 7T

PURPOSE

To understand how macromolecular content varies in the human brain with age in a large cohort of healthy subjects.

METHODS

In-vivo 1H-MR spectra were acquired using ultra-short TE STEAM at 7T in the posterior cingulate cortex. Macromolecular content was studied in 147 datasets from a cohort ranging in age from 19 to 89 y. Three fitting approaches were used to evaluate the macromolecular content: (1) a macromolecular resonances model developed for this study; (2) LCModel-simulated macromolecules; and (3) a combination of measured and LCModel-simulated macromolecules. The effect of age on the macromolecular content was investigated by considering age both as a continuous variable (i.e., linear regressions) and as a categorical variable (i.e., multiple comparisons among sub-groups obtained by stratifying data according to age by decade).

RESULTS

While weak age-related effects were observed for macromolecular peaks at ˜0.9 (MM09), ˜1.2 (MM12), and ˜1.4 (MM14) ppm, moderate to strong effects were observed for peaks at ˜1.7 (MM17), and ˜2.0 (MM20) ppm. Significantly higher MM17 and MM20 content started from 30 to 40 y of age, while for MM09, MM12, and MM14, significantly higher content started from 60 to 70 y of age.

CONCLUSIONS

Our findings provide insights into age-related differences in macromolecular contents and strengthen the necessity of using age-matched measured macromolecules during quantification.

Precision of metabolite-selective MRS measurements of glutamate, GABA and glutathione: A review of human brain studies

Single-voxel proton magnetic resonance spectroscopy (SV 1 H-MRS) is an in vivo noninvasive imaging technique used to detect neurotransmitters and metabolites. It enables repeated measurements in living participants to build explanatory neurochemical models of psychiatric symptoms and testing of therapeutic approaches. Given the tight link among glutamate, gamma-amino butyric acid (GABA), glutathione and glutamine within the cellular machinery, MRS investigations of neurocognitive and psychiatric disorders must quantify a network of metabolites simultaneously to capture the pathophysiological states of interest. Metabolite-selective sequences typically provide improved metabolite isolation and spectral modelling simplification for a single metabolite at a time. Non-metabolite-selective sequences provide information on all detectable human brain metabolites, but feature many signal overlaps and require complicated spectral modelling. Although there are short-echo time (TE) MRS sequences that do not use spectral editing and are optimised to target either glutamate, GABA or glutathione, these approaches usually imply a precision tradeoff for the remaining two metabolites. Given the interest in assessing psychiatric and neurocognitive diseases that involve excitation-inhibition imbalances along with oxidative stress, there is a need to survey the literature on the quantification precision of current metabolite-selective MRS techniques. In this review, we locate and describe 17 studies that report on the quality of simultaneously acquired MRS metabolite data in the human brain. We note several factors that influence the data quality for single-shot acquisition of multiple metabolites of interest using metabolite-selective MRS: (1) internal in vivo references; (2) brain regions of interests; (3) field strength of scanner; and/or (4) optimised acquisition parameters. We also highlight the strengths and weaknesses of various SV spectroscopy techniques that were able to quantify in vivo glutamate, GABA and glutathione simultaneously. The insights from this review will assist in the development of new MRS pulse sequences for simultaneous, selective measurements of these metabolites and simplified spectral modelling.

Map-based B0 shimming for single voxel brain spectroscopy at 7T

While B0 shimming is an important requirement for in vivo brain spectroscopy, for single voxel spectroscopy (SVS), the role for advanced shim methods has been questioned. Specifically, with the small spatial dimensions of the voxel, the extent to which inhomogeneities higher than second order exist and the ability of higher order shims to correct them is controversial. To assess this, we acquired SVS from two loci of neurophysiological interest, the rostral prefrontal cortex (rPFC; 8 cc) and hippocampus (Hc; 9 cc). The rPFC voxel was placed using SUsceptibility Managed Optimization (SUMO) and an initial B0 map that covers the entire cerebrum to cerebellum. In each location, we compared map-based shimming (Bolero) with projection-based shimming (FAST(EST)MAP). We also compared vendor-provided spherical harmonic first- and second-order shims with additional third- and fourth-order shim hardware. The 7T SVS acquisition used stimulated echo acquisition mode (STEAM) TR/TM/TE of 6 s/20 ms/8 ms, a tissue water acquisition for concentration reference, and LCModel for spectral analysis. In the rPFC (n = 7 subjects), Bolero shimming with first- and second-order shims reduced the residual inhomogeneity σ B 0 from 9.8 ± 4.5 Hz with FAST(EST)MAP to 6.5 ± 2.0 Hz. The addition of third- and fourth-order shims further reduced σ B 0 to 4.0 ± 0.8 Hz. In the Hc (n = 7 subjects), FAST(EST)MAP, Bolero with first- and second-order shims, and Bolero with first- to fourth-order shims achieved σ B 0 values of 8.6 ± 1.9, 5.6 ± 1.0, and 4.6 ± 0.9 Hz, respectively. The spectral linewidth,Δ v σ B 0 , was estimated with a Voigt lineshape using σ B 0 and T2 = 130 ms.Δ v σ B 0 significantly correlated with the Cramer-Rao lower bounds and concentrations of several metabolites, including glutamate and glutamine in the rPFC. In both loci, if the B0 distribution is well described by a Gaussian model, the variance of the metabolite concentrations is reduced, consistent with the LCModel fit based on a unimodal lineshape. Overall, the use of the high order and map-based B0 shim methods improved the accuracy and consistency of spectroscopic data.

Scyllo-inositol: Transverse relaxation time constant at 3 T and concentration changes associated with aging and alcohol use

The goals of this study were to measure the apparent transverse relaxation time constant, T2 , of scyllo-inositol (sIns) in young and older healthy adults' brains and to investigate the effect of alcohol usage on sIns in young and older healthy adults' brains, using proton magnetic resonance spectroscopy (MRS) at 3 T. Twenty-nine young adults (age 21 ± 1 years) and 24 older adults (age 74 ± 3 years) participated in this study. MRS data were acquired from two brain regions (the occipital cortex and posterior cingulate cortex) at 3 T. The T2 of sIns was measured using a localization by adiabatic selective refocusing (LASER) sequence at various echo times, while the sIns concentrations were measured using a short-echo-time stimulated echo acquisition mode (STEAM) sequence. A trend towards lower T2 relaxation values of sIns in older adults was observed, although these were not significant. sIns concentration was higher with age in both brain regions and was significantly higher in the young when considering alcohol consumption of more than two drinks per week. This study shows that differences in sIns can be found in two distinct regions of the brain across two age groups, potentially reflecting normal aging. In addition, it is important to take into account alcohol consumption when reporting the sIns level in the brain.

GABA, glutamate and excitatory-inhibitory ratios measured using short-TE STEAM MRS at 7-Tesla: Effects of macromolecule basis sets and baseline parameters

Rationale and objectives

Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated.

Materials and methods

Twenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV).

Results

CRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2-3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR.

Conclusion

Neurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.

Quantification of GABA concentration measured noninvasively in the human posterior cingulate cortex with 7 T ultra-short-TE MR spectroscopy

PURPOSE

The increased spectral dispersion achieved at ultra-high field permits quantification of γ-aminobutyric acid (GABA) concentrations at ultra-short-TE without editing. This work investigated the influence of spectral quality and different LCModel fitting approaches on quantification of GABA. Additionally, the sensitivity with which cross-sectional and longitudinal variations in GABA concentrations can be observed was characterized.

METHODS

In - vivo spectra were acquired in the posterior cingulate cortex of 10 volunteers at 7 T using a STEAM sequence. Synthetically altered spectra with different levels of GABA signals were used to investigate the reliability of GABA quantification with different LCModel fitting approaches and different realizations of SNR. The synthetically altered spectra were also used to characterize the sensitivity of GABA quantification.

RESULTS

The best LCModel fitting approach used stiff spline baseline, no soft constraints, and measured macromolecules in the basis set. With lower SNR, coefficients of variation increased dramatically. Longitudinal and cross-sectional variations in GABA of 10% could be detected with 79 and 48 participants per group, respectively. However, the small cohort may bias the calculation of the coefficients of variation and of the sample size that would be needed to detect variations in GABA.

CONCLUSION

Reliable quantification of normal and abnormal GABA concentrations was achieved for high quality 7 T spectra using LCModel fitting.

Insights from auditory cortex for GABA+ magnetic resonance spectroscopy studies of aging

Changes in levels of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) may underlie aging-related changes in brain function. GABA and co-edited macromolecules (GABA+) can be measured with MEGA-PRESS magnetic resonance spectroscopy (MRS). The current study investigated how changes in the aging brain impact the interpretation of GABA+ measures in bilateral auditory cortices of healthy young and older adults. Structural changes during aging appeared as decreasing proportion of grey matter in the MRS volume of interest and corresponding increase in cerebrospinal fluid. GABA+ referenced to H₂ O without tissue correction declined in aging. This decline persisted after correcting for tissue differences in MR-visible H₂ O and relaxation times but vanished after considering the different abundance of GABA+ in grey and white matter. However, GABA+ referenced to creatine and N-acetyl aspartate (NAA), which showed no dependence on tissue composition, decreased in aging. All GABA+ measures showed hemispheric asymmetry in young but not older adults. The study also considered aging-related effects on tissue segmentation and the impact of co-edited macromolecules. Tissue segmentation differed significantly between commonly used algorithms, but aging-related effects on tissue-corrected GABA+ were consistent across methods. Auditory cortex macromolecule concentration did not change with age, indicating that a decline in GABA caused the decrease in the compound GABA+ measure. Most likely, the macromolecule contribution to GABA+ leads to underestimating an aging-related decrease in GABA. Overall, considering multiple GABA+ measures using different reference signals strengthened the support for an aging-related decline in auditory cortex GABA levels.

Task-Related Modulation of Sensorimotor GABA+ Levels in Association with Brain Activity and Motor Performance: A Multimodal MRS-fMRI Study in Young and Older Adults

Recent studies suggest an important role of the principal inhibitory neurotransmitter GABA for motor performance in the context of aging. Nonetheless, as previous magnetic resonance spectroscopy (MRS) studies primarily reported resting-state GABA levels, much less is known about transient changes in GABA levels during motor task performance and how these relate to behavior and brain activity patterns. Therefore, we investigated GABA+ levels of left primary sensorimotor cortex (SM1) acquired before, during, and after execution of a unimanual/bimanual action selection task in 30 (human) young adults (YA; age 24.5 ± 4.1, 15 male) and 30 older adults (OA; age 67.8 ± 4.9, 14 male). In addition to task-related MRS data, task-related functional magnetic resonance imaging (fMRI) data were acquired. Behavioral results indicated lower motor performance in OA as opposed to YA, particularly in complex task conditions. MRS results demonstrated lower GABA+ levels in OA as compared with YA. Furthermore, a transient task-related decrease of GABA+ levels was observed, regardless of age. Notably, this task-induced modulation of GABA+ levels was linked to task-related brain activity patterns in SM1 such that a more profound task-induced instantaneous lowering of GABA+ was related to higher SM1 activity. Additionally, higher brain activity was related to better performance in the bimanual conditions, despite some age-related differences. Finally, the modulatory capacity of GABA+ was positively related to motor performance in OA but not YA. Together, these results underscore the importance of transient dynamical changes in neurochemical content for brain function and behavior, particularly in the context of aging.SIGNIFICANCE STATEMENT Emerging evidence designates an important role to regional GABA levels in motor control, especially in the context of aging. However, it remains unclear whether changes in GABA levels emerge when executing a motor task and how these changes relate to brain activity patterns and performance. Here, we identified a transient decrease of sensorimotor GABA+ levels during performance of an action selection task across young adults (YA) and older adults (OA). Interestingly, whereas a more profound GABA+ modulation related to higher brain activity across age groups, its association with motor performance differed across age groups. Within OA, our results highlighted a functional merit of a task-related release from inhibitory tone, i.e. lowering regional GABA+ levels was associated with task-relevant brain activity.

Frontal Metabolites and Alzheimer's Disease Biomarkers in Healthy Older Women and Women Diagnosed with Mild Cognitive Impairment

BACKGROUND

Women account for two thirds of the prevalence and incidence of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Evidence suggest that sex may differently influence the expression of proteins amyloid-beta (Aβ1-42) and tau, for which early detection is crucial in prevention of the disease.

OBJECTIVE

We investigated the effect of aging and cerebrospinal fluid (CSF) levels of Aβ1-42 and tau on frontal metabolites measured with proton magnetic resonance spectroscopy (MRS) in a cohort of cognitively normal older women and women with MCI.

METHODS

3T single-voxel MRS was performed on the medial frontal cortex, using Point Resolved Spectroscopy (PRESS) and Mescher-Garwood Point Resolved Spectroscopy (MEGA-PRESS) in 120 women (age range 50-85). CSF samples of Aβ1-42 and tau and scores of general cognition were also obtained.

RESULTS

Levels of frontal gamma aminobutyric acid (GABA+) were predicted by age, independently of disease and CSF biomarkers. Importantly, levels of GABA+ were reduced in MCI patients. Additionally, we found that levels of N-acetylaspartate relative to myo-inositol (tNAA/mI) predicted cognition in MCI patients only and were not related to CSF biomarkers.

CONCLUSION

This study is the first to demonstrate a strong association between frontal GABA+ levels and neurological aging in a sample consisting exclusively of healthy older women with various levels of CSF tau and Aβ1-42 and women with MCI. Importantly, our results show no correlation between CSF biomarkers and MRS metabolites in this sample.

Comparison of linear combination modeling strategies for edited magnetic resonance spectroscopy at 3 T

J-difference-edited spectroscopy is a valuable approach for the in vivo detection of γ-aminobutyric-acid (GABA) with magnetic resonance spectroscopy (MRS). A recent expert consensus article recommends linear combination modeling (LCM) of edited MRS but does not give specific details regarding implementation. This study explores different modeling strategies to adapt LCM for GABA-edited MRS. Sixty-one medial parietal lobe GABA-edited MEGA-PRESS spectra from a recent 3-T multisite study were modeled using 102 different strategies combining six different approaches to account for co-edited macromolecules (MMs), three modeling ranges, three baseline knot spacings, and the use of basis sets with or without homocarnosine. The resulting GABA and GABA+ estimates (quantified relative to total creatine), the residuals at different ranges, standard deviations and coefficients of variation (CVs), and Akaike information criteria, were used to evaluate the models' performance. Significantly different GABA+ and GABA estimates were found when a well-parameterized MM_3co basis function was included in the model. The mean GABA estimates were significantly lower when modeling MM_3co , while the CVs were similar. A sparser spline knot spacing led to lower variation in the GABA and GABA+ estimates, and a narrower modeling range-only including the signals of interest-did not substantially improve or degrade modeling performance. Additionally, the results suggest that LCM can separate GABA and the underlying co-edited MM_3co . Incorporating homocarnosine into the modeling did not significantly improve variance in GABA+ estimates. In conclusion, GABA-edited MRS is most appropriately quantified by LCM with a well-parameterized co-edited MM_3co basis function with a constraint to the nonoverlapped MM_0.93 , in combination with a sparse spline knot spacing (0.55 ppm) and a modeling range of 0.5-4 ppm.

The macromolecular MR spectrum does not change with healthy aging

PURPOSE

To acquire the mobile macromolecule (MM) spectrum from healthy participants, and to investigate changes in the signals with age and sex.

METHODS

102 volunteers (49 M/53 F) between 20 and 69 years were recruited for in vivo data acquisition in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). Spectral data were acquired at 3T using PRESS localization with a voxel size of 30 × 26 × 26 mm³ , pre-inversion (TR/TI 2000/600 ms) and CHESS water suppression. Metabolite-nulled spectra were modeled to eliminate residual metabolite signals, which were then subtracted out to yield a "clean" MM spectrum using the Osprey software. Pearson's correlation coefficient was calculated between integrals and age for the 14 MM signals. One-way ANOVA was performed to determine differences between age groups. An independent t-test was carried out to determine differences between sexes.

RESULTS

MM spectra were successfully acquired in 99 (CSO) and 96 (PCC) of 102 subjects. No significant correlations were seen between age and MM signals. One-way ANOVA also suggested no age-group differences for any MM peak (all p > .004). No differences were observed between sex groups. WM and GM voxel fractions showed a significant (p < .05) negative linear association with age in the WM-predominant CSO (R = -0.29) and GM-predominant PCC regions (R = -0.57) respectively while CSF increased significantly with age in both regions.

CONCLUSION

Our findings suggest that a pre-defined MM basis function can be used for linear combination modeling of metabolite data from different age and sex groups.

Relationships between frontal metabolites and Alzheimer's disease biomarkers in cognitively normal older adults

Elevated expression of β-amyloid (Aβ_1-42) and tau are considered risk-factors for Alzheimer's disease in healthy older adults. We investigated the effect of aging and cerebrospinal fluid levels of Aβ_1-42 and tau on 1) frontal metabolites measured with proton magnetic resonance spectroscopy (MRS) and 2) cognition in cognitively normal older adults (n = 144; age range 50-85). Levels of frontal gamma aminobutyric acid (GABA+) and myo-inositol relative to creatine (mI/tCr) were predicted by age. Levels of GABA+ predicted cognitive performance better than mI/tCr. Additionally, we found that frontal levels of n-acetylaspartate relative to creatine (tNAA/tCr) were predicted by levels of t-tau. In cognitively normal older adults, levels of frontal GABA+ and mI/tCr are predicted by aging, with levels of GABA+ decreasing with age and the opposite for mI/tCr. These results suggest that age- and biomarker-related changes in brain metabolites are not only located in the posterior cortex as suggested by previous studies and further demonstrate that MRS is a viable tool in the study of aging and biomarkers associated with pathological aging and Alzheimer's disease.

Dissociable effects of age and Parkinson's disease on instruction-based learning

The cognitive deficits associated with Parkinson's disease vary across individuals and change across time, with implications for prognosis and treatment. Key outstanding challenges are to define the distinct behavioural characteristics of this disorder and develop diagnostic paradigms that can assess these sensitively in individuals. In a previous study, we measured different aspects of attentional control in Parkinson's disease using an established fMRI switching paradigm. We observed no deficits for the aspects of attention the task was designed to examine; instead those with Parkinson's disease learnt the operational requirements of the task more slowly. We hypothesized that a subset of people with early-to-mid stage Parkinson's might be impaired when encoding rules for performing new tasks. Here, we directly test this hypothesis and investigate whether deficits in instruction-based learning represent a characteristic of Parkinson's Disease. Seventeen participants with Parkinson's disease (8 male; mean age: 61.2 years), 18 older adults (8 male; mean age: 61.3 years) and 20 younger adults (10 males; mean age: 26.7 years) undertook a simple instruction-based learning paradigm in the MRI scanner. They sorted sequences of coloured shapes according to binary discrimination rules that were updated at two-minute intervals. Unlike common reinforcement learning tasks, the rules were unambiguous, being explicitly presented; consequently, there was no requirement to monitor feedback or estimate contingencies. Despite its simplicity, a third of the Parkinson's group, but only one older adult, showed marked increases in errors, 4 SD greater than the worst performing young adult. The pattern of errors was consistent, reflecting a tendency to misbind discrimination rules. The misbinding behaviour was coupled with reduced frontal, parietal and anterior caudate activity when rules were being encoded, but not when attention was initially oriented to the instruction slides or when discrimination trials were performed. Concomitantly, Magnetic Resonance Spectroscopy showed reduced gamma-Aminobutyric acid levels within the mid-dorsolateral prefrontal cortices of individuals who made misbinding errors. These results demonstrate, for the first time, that a subset of early-to-mid stage people with Parkinson's show substantial deficits when binding new task rules in working memory. Given the ubiquity of instruction-based learning, these deficits are likely to impede daily living. They will also confound clinical assessment of other cognitive processes. Future work should determine the value of instruction-based learning as a sensitive early marker of cognitive decline and as a measure of responsiveness to therapy in Parkinson's disease.

In vivo macromolecule signals in rat brain 1 H-MR spectra at 9.4T: Parametrization, spline baseline estimation, and T2 relaxation times

PURPOSE

Reliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short-echo time (TE) ¹ H-MR spectra. An experimentally acquired single MM spectrum is commonly used. Higher spectral resolution at ultra-high field (UHF) led to increased interest in using a parametrized MM spectrum together with flexible spline baselines to address unpredicted spectroscopic components. Herein, we aimed to: (1) implement an advanced methodological approach for post-processing, fitting, and parametrization of 9.4T rat brain MM spectra; (2) assess the concomitant impact of the LCModel baseline and MM model (ie, single vs parametrized); and (3) estimate the apparent T₂ relaxation times for seven MM components.

METHODS

A single inversion recovery sequence combined with advanced AMARES prior knowledge was used to eliminate the metabolite residuals, fit, and parametrize 10 MM components directly from 9.4T rat brain in vivo ¹ H-MR spectra at different TEs. Monte Carlo simulations were also used to assess the concomitant influence of parametrized MM and DKNTMN parameter in LCModel.

RESULTS

A very stiff baseline (DKNTMN ≥ 1 ppm) in combination with a single MM spectrum led to deviations in metabolite concentrations. For some metabolites the parametrized MM showed deviations from the ground truth for all DKNTMN values. Adding prior knowledge on parametrized MM improved MM and metabolite quantification. The apparent T₂ ranged between 12 and 24 ms for seven MM peaks.

CONCLUSION

Moderate flexibility in the spline baseline was required for reliable quantification of real/experimental spectra based on in vivo and Monte Carlo data. Prior knowledge on parametrized MM improved MM and metabolite quantification.

Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations

Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

Longitudinal quantification of metabolites and macromolecules reveals age- and sex-related changes in the healthy Fischer 344 rat brain

Normal aging is associated with numerous biological changes, including altered brain metabolism and tissue chemistry. In vivo characterization of the neurochemical profile during aging is possible using magnetic resonance spectroscopy, a powerful noninvasive technique capable of quantifying brain metabolites involved in physiological processes that become impaired with age. A prominent macromolecular signal underlies those of brain metabolites and is particularly visible at high fields; parameterization of this signal into components improves quantification and expands the number of biomarkers comprising the neurochemical profile. The present study reports, for the first time, the simultaneous absolute quantification of brain metabolites and individual macromolecules in aging male and female Fischer 344 rats, measured longitudinally using proton magnetic resonance spectroscopy at 7 T. We identified age- and sex-related changes in neurochemistry, with prominent differences in metabolites implicated in anaerobic energy metabolism, antioxidant defenses, and neuroprotection, as well as numerous macromolecule changes. These findings contribute to our understanding of the neurobiological processes associated with healthy aging, critical for the proper identification and management of pathologic aging trajectories. This article is part of the Virtual Special Issue titled COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING. The full issue can be found on ScienceDirect athttps://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

Influence of fitting approaches in LCModel on MRS quantification focusing on age-specific macromolecules and the spline baseline

Quantification of neurochemical concentrations from ¹ H MR spectra is challenged by incomplete knowledge of contributing signals. Some experimental conditions hinder the acquisition of artifact-free spectra and impede the acquisition of condition-specific macromolecule (MM) spectra. This work studies differences caused by fitting solutions routinely employed to manage resonances from MM and lipids. High quality spectra (free of residual water and lipid artifacts and for which condition-specific MM spectra are available) are used to understand the influences of spline baseline flexibility and noncondition-specific MM on neurochemical quantification. Fitting with moderate spline flexibility or using noncondition-specific MM led to quantification that differed from when an appropriate, fully specified model was used. This occurred for all neurochemicals to an extent that varied in magnitude among and within approaches. The spline baseline was more tortuous when less constrained and when used in combination with noncondition-specific MM. Increasing baseline flexibility did not reproduce concentrations quantified under appropriate conditions when spectra were fitted using a MM spectrum measured from a mismatched cohort. Using the noncondition-specific MM spectrum led to quantification differences that were comparable in size with using a fitting model that had moderate freedom, and these influences were additive. Although goodness of fit was better with greater fitting flexibility, quantification differed from when fitting with a fully specified model that is appropriate for low noise data. Notable GABA and PE concentration differences occurred with lower estimates of measurement error when fitting with greater spline flexibility or noncondition-specific MM. These data support the need for improved metrics of goodness of fit. Attempting to correct for artifacts or absence of a condition-specific MM spectrum via increased spline flexibility and usage of noncondition-specific MM spectra cannot replace artifact-free data quantified with a condition-specific MM spectrum.

Comparison of different linear-combination modeling algorithms for short-TE proton spectra

Short-TE proton MRS is used to study metabolism in the human brain. Common analysis methods model the data as a linear combination of metabolite basis spectra. This large-scale multi-site study compares the levels of the four major metabolite complexes in short-TE spectra estimated by three linear-combination modeling (LCM) algorithms. 277 medial parietal lobe short-TE PRESS spectra (TE = 35 ms) from a recent 3 T multi-site study were preprocessed with the Osprey software. The resulting spectra were modeled with Osprey, Tarquin and LCModel, using the same three vendor-specific basis sets (GE, Philips and Siemens) for each algorithm. Levels of total N-acetylaspartate (tNAA), total choline (tCho), myo-inositol (mI) and glutamate + glutamine (Glx) were quantified with respect to total creatine (tCr). Group means and coefficient of variations of metabolite estimates agreed well for tNAA and tCho across vendors and algorithms, but substantially less so for Glx and mI, with mI systematically estimated as lower by Tarquin. The cohort mean coefficient of determination for all pairs of LCM algorithms across all datasets and metabolites was R 2 ¯ = 0.39, indicating generally only moderate agreement of individual metabolite estimates between algorithms. There was a significant correlation between local baseline amplitude and metabolite estimates (cohort mean R 2 ¯ = 0.10). While mean estimates of major metabolite complexes broadly agree between linear-combination modeling algorithms at group level, correlations between algorithms are only weak-to-moderate, despite standardized preprocessing, a large sample of young, healthy and cooperative subjects, and high spectral quality. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes.

GABA levels are differentially associated with bimanual motor performance in older as compared to young adults

Although gamma aminobutyric acid (GABA) is of particular importance for efficient motor functioning, very little is known about the relationship between regional GABA levels and motor performance. Some studies suggest this relation to be subject to age-related differences even though literature is scarce. To clarify this matter, we employed a comprehensive approach and investigated GABA levels within young and older adults across multiple motor tasks as well as multiple brain regions. Specifically, 30 young and 30 older adults completed a task battery of three different bimanual tasks. Furthermore, GABA levels were obtained within bilateral primary sensorimotor cortex (SM1), bilateral dorsal premotor cortex, the supplementary motor area and bilateral dorsolateral prefrontal cortex (DLPFC) using magnetic resonance spectroscopy. Results indicated that older adults, as compared to their younger counterparts, performed worse on all bimanual tasks and exhibited lower GABA levels in bilateral SM1 only. Moreover, GABA levels across the motor network and DLPFC were differentially associated with performance in young as opposed to older adults on a manual dexterity and bimanual coordination task but not a finger tapping task. Specifically, whereas higher GABA levels related to better manual dexterity within older adults, higher GABA levels predicted poorer bimanual coordination performance in young adults. By determining a task-specific and age-dependent association between GABA levels across the cortical motor network and performance on distinct bimanual tasks, the current study advances insights in the role of GABA for motor performance in the context of aging.

Macromolecule suppressed GABA levels show no relationship with age in a pediatric sample

The inhibitory neurotransmitter γ-Aminobutyric acid (GABA) plays a crucial role in cortical development. Therefore, characterizing changes in GABA levels during development has important implications for the study of healthy development and developmental disorders. Brain GABA levels can be measured non-invasively using GABA-edited magnetic resonance spectroscopy (MRS). However, the most commonly used editing technique to measure GABA results in contamination of the GABA signal with macromolecules (MM). Therefore, GABA measured using this technique is often referred to as GABA+ . While few in number, previous studies have shown GABA+ levels increase with age during development. However, these studies are unable to specify whether it is specifically GABA that is increasing or, instead, if levels of MM increase. In this study, we use a GABA-editing technique specifically designed to suppress the MM signal (MM-supp GABA). We find no relationship between MM-supp GABA and age in healthy children aged 7-14 years. These findings suggest that the relationship between GABA+ and age is driven by changes in MM levels, not by changes in GABA levels. Moreover, these findings highlight the importance of accounting for MM levels in MRS quantification.

ECLIPSE utilizing gradient-modulated offset-independent adiabaticity (GOIA) pulses for highly selective human brain proton MRSI

A multitude of extracranial lipid suppression methods exist for proton MRSI acquisitions. Popular and emerging lipid suppression methods each have their inherent set of advantages and disadvantages related to the achievable level of lipid suppression, RF power deposition, insensitivity to B₁⁺ field and lipid T₁ heterogeneity, brain coverage, spatial selectivity, chemical shift displacement (CSD) errors and the reliability of spectroscopic data spanning the observed 0.9-4.7 ppm band. The utility of elliptical localization with pulsed second order fields (ECLIPSE) was previously demonstrated with a greater than 100-fold in extracranial lipid suppression and low power requirements utilizing 3 kHz bandwidth AFP pulses. Like all gradient-based localization methods, ECLIPSE is sensitive to CSD errors, resulting in a modified metabolic profile in edge-of-ROI voxels. In this work, ECLIPSE is extended with 15 kHz bandwidth second order gradient-modulated RF pulses based on the gradient offset-independent adiabaticity (GOIA) algorithm to greatly reduce CSD and improve spatial selectivity. An adiabatic double spin-echo ECLIPSE inner volume selection (TE = 45 ms) MRSI method and an ECLIPSE outer volume suppression (TE = 3.2 ms) FID-MRSI method were implemented. Both GOIA-ECLIPSE MRSI sequences provided artifact-free metabolite spectra in vivo, with a greater than 100-fold in lipid suppression and less than 2.6 mm in-plane CSD and less than 3.3 mm transition width for edge-of-ROI voxels, representing an ~5-fold improvement compared with the parent, nongradient-modulated method. Despite the 5-fold larger bandwidth, GOIA-ECLIPSE only required a 1.9-fold increase in RF power. The highly robust lipid suppression combined with low CSD and sharp ROI edge transitions make GOIA-ECLIPSE an attractive alternative to commonly employed lipid suppression methods. Furthermore, the low RF power deposition demonstrates that GOIA-ECLIPSE is very well suited for high field (≥3 T) MRSI applications.

Regional Myo-Inositol, Creatine, and Choline Levels Are Higher at Older Age and Scale Negatively with Visuospatial Working Memory: A Cross-Sectional Proton MR Spectroscopy Study at 7 Tesla on Normal Cognitive Ageing

Proton MR spectroscopy (¹H-MRS) has been used to assess regional neurochemical brain changes during normal ageing, but results have varied. Exploiting the increased sensitivity at ultra-high field, we performed ¹H-MRS in 60 healthy human volunteers to asses age-related differences in metabolite levels and their relation to cognitive ageing. Sex was balanced, and participants were assigned to a younger, middle, and older group according to their age, ranging from 18 to 79 years. They underwent 7T ¹H-MRS of the ACC, DLPFC, hippocampus, and thalamus and performed a visuospatial working memory task outside the scanner. A multivariate ANCOVA revealed a significant overall effect of age group on metabolite levels in all regions. Higher levels in the middle than the younger group were observed for myo-inositol (mIns) in DLPFC and hippocampus and total choline (tCho) in ACC. Higher levels in the older than the younger group were observed for mIns in hippocampus and thalamus, total creatine (tCr) and tCho in ACC and hippocampus; lower levels of glutamate (Glu) were observed in DLPFC. Higher levels in the older than the middle group were observed for mIns in hippocampus, tCr in ACC and hippocampus, tCho in hippocampus, and total N-acetyl aspartate (tNAA) in hippocampus. Working memory performance correlated negatively with tCr and tCho levels in ACC and mIns levels in hippocampus and thalamus, but not with tNAA or glutamate levels. As NAA and Glu are commonly regarded to reflect neuronal health and function and concentrations of mIns, tCr, and tCho are higher in glia than neurons, the findings of this study suggest a potential in vivo connection between cognitive ageing and higher regional levels of glia-related metabolites.SIGNIFICANCE STATEMENT Neurochemical ageing is an integral component of age-related cognitive decline. Proton MR spectroscopy (¹H-MRS) studies of in vivo neurochemical changes across the lifespan have, however, yielded inconclusive results. ¹H-MRS at ultra-high field strength can potentially improve the consistency of findings. Using 7T ¹H-MRS, we assessed levels of mIns, tCr, and tCho (glia-related metabolites) and tNAA and Glu (neuron-related metabolites) in ACC, DLPFC, hippocampus, and thalamus. We found higher levels of glia-related metabolites in all brain regions in older individuals. Working memory performance correlated negatively with regional levels of glia-related metabolites. This study is the first to investigate normal ageing in these brain regions using 7T ¹H-MRS and findings indicate that glia-related metabolites could be valuable in cognitive ageing studies.

A novel method to measure T1 -relaxation times of macromolecules and quantification of the macromolecular resonances

PURPOSE

Macromolecular peaks underlying metabolite spectra influence the quantification of metabolites. Therefore, it is important to understand the extent of contribution from macromolecules (MMs) in metabolite quantification. However, to model MMs more accurately in spectral fitting, differences in T₁ relaxation times among individual MM peaks must be considered. Characterization of T₁ -relaxation times for all individual MM peaks using a single inversion recovery technique is difficult due to eventual contributions from metabolites. On the contrary, a double inversion recovery (DIR) technique provided flexibility to acquire MM spectra spanning a range of longitudinal magnetizations with minimal metabolite influence. Thus, a novel method to determine T₁ -relaxation times of individual MM peaks is reported in this work.

METHODS

Extensive Bloch simulations were performed to determine inversion time combinations for a DIR technique that yielded adequate MM signal with varying longitudinal magnetizations while minimizing metabolite contributions. MM spectra were acquired using DIR-metabolite-cycled semi-LASER sequence. LCModel concentrations were fitted to the DIR signal equation to calculate T₁ -relaxation times.

RESULTS

T₁ -relaxation times of MMs range from 204 to 510 ms and 253 to 564 ms in gray- and white-matter rich voxels respectively at 9.4T. Additionally, concentrations of 13 MM peaks are reported.

CONCLUSION

A novel DIR method is reported in this work to calculate T₁ -relaxation times of MMs in the human brain. T₁ -relaxation times and relaxation time corrected concentrations of individual MMs are reported in gray- and white-matter rich voxels for the first time at 9.4T.

Adaptive baseline fitting for 1 H MR spectroscopy analysis

PURPOSE

Accurate baseline modeling is essential for reliable MRS analysis and interpretation-particularly at short echo-times, where enhanced metabolite information coincides with elevated baseline interference. The degree of baseline smoothness is a key analysis parameter for metabolite estimation, and in this study, a new method is presented to estimate its optimal value.

METHODS

An adaptive baseline fitting algorithm (ABfit) is described, incorporating a spline basis into a frequency-domain analysis model, with a penalty parameter to enforce baseline smoothness. A series of candidate analyses are performed over a range of smoothness penalties, as part of a 4-stage algorithm, and the Akaike information criterion is used to estimate the appropriate penalty. ABfit is applied to a set of simulated spectra with differing baseline features and experimentally acquired 2D MRSI-both at a field strength of 3 Tesla.

RESULTS

Simulated analyses demonstrate metabolite errors result from 2 main sources: bias from an inflexible baseline (underfitting) and increased variance from an overly flexible baseline (overfitting). In the case of an ideal flat baseline, ABfit is shown to correctly estimate a highly rigid baseline, and for more realistic spectra a reasonable compromise between bias and variance is found. Analysis of experimentally acquired data demonstrates good agreement with known correlations between metabolite ratios and the contributing volumes of gray and white matter tissue.

CONCLUSIONS

ABfit has been shown to perform accurate baseline estimation and is suitable for fully automated routine MRS analysis.

Changes in the intracellular microenvironment in the aging human brain

Normal brain aging is associated with changes occurring at all levels. This study investigates age-related differences in the brain intracellular microenvironment by comparing the apparent diffusion coefficients (ADC) and apparent transverse relaxation time constants (T₂) of 5 neurochemicals (i.e., total N-acetyl-aspartate, total creatine, total choline, glutamate, and myo-inositol) between young and older adults. Thirty-two young healthy adults (18-22 years) and 26 older healthy adults (70-83 years) were recruited. Three brain regions were studied at 3 T: prefrontal, posterior cingulate and occipital cortices. ADC and T₂ were measured using stimulated echo acquisition mode and localization by adiabatic selective refocusing sequences, respectively. This study shows that the diffusivities of several neurochemicals are higher in older than in younger adults. In contrast, shorter apparent T₂ values for several metabolites were measured in older adults. Age-related difference in ADC and apparent T₂ of metabolites seem to be region-specific. Furthermore, this study shows that it is feasible to observe age-related differences in the cellular microenvironment of neurochemicals in the normal aging brain.

Brain GABA Levels Are Associated with Inhibitory Control Deficits in Older Adults

Healthy aging is accompanied by motor inhibition deficits that involve a slower process of stopping a prepotent motor response (i.e., reactive inhibition) rather than a diminished ability to anticipate stopping (i.e., proactive inhibition). Some studies suggest that efficient motor inhibition is related to GABAergic function. Since age-related alterations in the GABA system have also been reported, motor inhibition impairments might be linked to GABAergic alterations in the cortico-subcortical network that mediates motor inhibition. Thirty young human adults (mean age, 23.2 years; age range, 18-34 years; 14 men) and 29 older human adults (mean age, 67.5 years; age range, 60-74 years; 13 men) performed a stop-signal task with varying levels of stop-signal probability. GABA⁺ levels were measured with magnetic resonance spectroscopy (MRS) in right inferior frontal cortex, pre-supplementary motor area (pre-SMA), left sensorimotor cortex, bilateral striatum, and occipital cortex. We found that reactive inhibition was worse in older adults compared with young adults, as indicated by longer stop-signal reaction times (SSRTs). No group differences in proactive inhibition were observed as both groups slowed down their response to a similar degree with increasing stop-signal probability. The MRS results showed that tissue-corrected GABA⁺ levels were on average lower in older as compared with young adults. Moreover, older adults with lower GABA⁺ levels in the pre-SMA were slower at stopping (i.e., had longer SSRTs). These findings suggest a role for the GABA system in reactive inhibition deficits.SIGNIFICANCE STATEMENT Inhibitory control has been shown to diminish as a consequence of aging. We investigated whether the ability to stop a prepotent motor response and the ability to prepare to stop were related to GABA levels in different regions of the network that was previously identified to mediate inhibitory control. Overall, we found lower GABA levels in older adults compared with young adults. Importantly, those older adults who were slower at stopping had less GABA in the pre-supplementary motor area, a key node of the inhibitory control network. We propose that deficits in the stop process in part depend on the integrity of the GABA system.

Age-related differences in GABA levels are driven by bulk tissue changes

Levels of GABA, the main inhibitory neurotransmitter in the brain, can be regionally quantified using magnetic resonance spectroscopy (MRS). Although GABA is crucial for efficient neuronal functioning, little is known about age-related differences in GABA levels and their relationship with age-related changes in brain structure. Here, we investigated the effect of age on GABA levels within the left sensorimotor cortex and the occipital cortex in a sample of 85 young and 85 older adults using the MEGA-PRESS sequence. Because the distribution of GABA varies across different brain tissues, various correction methods are available to account for this variation. Considering that these correction methods are highly dependent on the tissue composition of the voxel of interest, we examined differences in voxel composition between age groups and the impact of these various correction methods on the identification of age-related differences in GABA levels. Results indicated that, within both voxels of interest, older (as compared to young adults) exhibited smaller gray matter fraction accompanied by larger fraction of cerebrospinal fluid. Whereas uncorrected GABA levels were significantly lower in older as compared to young adults, this age effect was absent when GABA levels were corrected for voxel composition. These results suggest that age-related differences in GABA levels are at least partly driven by the age-related gray matter loss. However, as alterations in GABA levels might be region-specific, further research should clarify to what extent gray matter changes may account for age-related differences in GABA levels within other brain regions.