GABA-edited MEGA-PRESS at 3 T: Does a measured macromolecule background improve linear combination modeling?

PURPOSE: The J-difference edited γ-aminobutyric acid (GABA) signal is contaminated by other co-edited signals-the largest of which originates from co-edited macromolecules (MMs)-and is consequently often reported as "GABA+." MM signals are broader and less well-characterized than the metabolites, and are commonly approximated using a Gaussian model parameterization. Experimentally measured MM signals are a consensus-recommended alternative to parameterized modeling; however, they are relatively under-studied in the context of edited MRS. METHODS: To address this limitation in the literature, we have acquired GABA-edited MEGA-PRESS data with pre-inversion to null metabolite signals in 13 healthy controls. An experimental MM basis function was derived from the mean across subjects. We further derived a new parameterization of the MM signals from the experimental data, using multiple Gaussians to accurately represent their observed asymmetry. The previous single-Gaussian parameterization, mean experimental MM spectrum and new multi-Gaussian parameterization were compared in a three-way analysis of a public MEGA-PRESS dataset of 61 healthy participants. RESULTS: Both the experimental MMs and the multi-Gaussian parameterization exhibited reduced fit residuals compared to the single-Gaussian approach (p = 0.034 and p = 0.031, respectively), suggesting they better represent the underlying data than the single-Gaussian parameterization. Furthermore, both experimentally derived models estimated larger MM fractional contribution to the GABA+ signal for the experimental MMs (58%) and multi-Gaussian parameterization (58%), compared to the single-Gaussian approach (50%). CONCLUSIONS: Our results indicate that single-Gaussian parameterization of edited MM signals is insufficient and that both experimentally derived GABA+ spectra and their parameterized replicas improve the modeling of GABA+ spectra.

Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS) for Advanced MRS.

Background: To examine data quality and reproducibility using ISTHMUS, which has been implemented as the standardized MR spectroscopy sequence for the multi-site Healthy Brain and Child Development (HBCD) study. Methods: ISTHMUS is the consecutive acquisition of short-TE PRESS (32 transients) and long-TE HERCULES (224 transients) data with dual-TE water reference scans. Voxels were positioned in the centrum semiovale, dorsal anterior cingulate cortex, posterior cingulate cortex and bilateral thalamus regions. After acquisition, ISTHMUS data were separated into the PRESS and HERCULES portions for analysis and modeled separately using Osprey. In vivo experiments were performed in 10 healthy volunteers (6 female; 29.5±6.6 years). Each volunteer underwent two scans on the same day. Differences in metabolite measurements were examined. T2 correction based on the dual-TE water integrals were compared with: 1) T2 correction based the default white matter and gray matter T2 reference values in Osprey; 2) shorter WM and GM T2 values from recent literature; and 3) reduced CSF fractions. Results: No significant difference in linewidth was observed between PRESS and HERCULES. Bilateral thalamus spectra had produced significantly higher (p<0.001) linewidth compared to the other three regions. Linewidth measurements were similar between scans, with scan-to-scan differences under 1 Hz for most subjects. Paired t-tests indicated a significant difference only in PRESS NAAG between the two thalamus scans (p=0.002). T2 correction based on shorter T2 values showed better agreement to the dual-TE water integral ratio. Conclusions: ISTHMUS facilitated and standardized acquisition and post-processing and reduced operator workload to eliminate potential human error.

Model-based frequency-and-phase correction of 1H MRS data with 2D linear-combination modeling.

Purpose: Retrospective frequency-and-phase correction (FPC) methods attempt to remove frequency-and-phase variations between transients to improve the quality of the averaged MR spectrum. However, traditional FPC methods like spectral registration struggle at low SNR. Here, we propose a method that directly integrates FPC into a two-dimensional linear-combination model (2D-LCM) of individual transients ('model-based FPC'). We investigated how model-based FPC performs compared to the traditional approach, i.e., spectral registration followed by 1D-LCM in estimating frequency-and-phase drifts and, consequentially, metabolite level estimates. Methods: We created synthetic in-vivo-like 64-transient short-TE sLASER datasets with 100 noise realizations at 5 SNR levels and added randomly sampled frequency and phase variations. We then used this synthetic dataset to compare the performance of 2D-LCM with the traditional approach (spectral registration, averaging, then 1D-LCM). Outcome measures were the frequency/phase/amplitude errors, the standard deviation of those ground-truth errors, and amplitude Cramér Rao Lower Bounds (CRLBs). We further tested the proposed method on publicly available in-vivo short-TE PRESS data. Results: 2D-LCM estimates (and accounts for) frequency-and-phase variations directly from uncorrected data with equivalent or better fidelity than the conventional approach. Furthermore, 2D-LCM metabolite amplitude estimates were at least as accurate, precise, and certain as the conventionally derived estimates. 2D-LCM estimation of frequency and phase correction and amplitudes performed substantially better at low-to-very-low SNR. Conclusion: Model-based FPC with 2D linear-combination modeling is feasible and has great potential to improve metabolite level estimation for conventional and dynamic MRS data, especially for low-SNR conditions, e.g., long TEs or strong diffusion weighting.

Metabolite T1 relaxation times decrease across the adult lifespan.

Relaxation correction is an integral step in quantifying brain metabolite concentrations measured by in vivo magnetic resonance spectroscopy (MRS). While most quantification routines assume constant T1 relaxation across age, it is possible that aging alters T1 relaxation rates, as is seen for T2 relaxation. Here, we investigate the age dependence of metabolite T1 relaxation times at 3 T in both gray- and white-matter-rich voxels using publicly available metabolite and metabolite-nulled (single inversion recovery TI = 600 ms) spectra acquired at 3 T using Point RESolved Spectroscopy (PRESS) localization. Data were acquired from voxels in the posterior cingulate cortex (PCC) and centrum semiovale (CSO) in 102 healthy volunteers across 5 decades of life (aged 20-69 years). All spectra were analyzed in Osprey v.2.4.0. To estimate T1 relaxation times for total N-acetyl aspartate at 2.0 ppm (tNAA2.0) and total creatine at 3.0 ppm (tCr3.0), the ratio of modeled metabolite residual amplitudes in the metabolite-nulled spectrum to the full metabolite signal was calculated using the single-inversion-recovery signal equation. Correlations between T1 and subject age were evaluated. Spearman correlations revealed that estimated T1 relaxation times of tNAA2.0 (rs = -0.27; p < 0.006) and tCr3.0 (rs = -0.40; p < 0.001) decreased significantly with age in white-matter-rich CSO, and less steeply for tNAA2.0 (rs = -0.228; p = 0.005) and (not significantly for) tCr3.0 (rs = -0.13; p = 0.196) in graymatter-rich PCC. The analysis harnessed a large publicly available cross-sectional dataset to test an important hypothesis, that metabolite T1 relaxation times change with age. This preliminary study stresses the importance of further work to measure age-normed metabolite T1 relaxation times for accurate quantification of metabolite levels in studies of aging.

Brain glutathione and GABA+ levels in autistic children.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a cohort of children aged 8-12 years with ASD (n = 52) and typically developing children (TDC, n = 49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.

Impact of acquisition and modeling parameters on the test-retest reproducibility of edited GABA.

Literature values vary widely for within-subject test-retest reproducibility of gamma-aminobutyric acid (GABA) measured with edited magnetic resonance spectroscopy (MRS). Reasons for this variation remain unclear. Here, we tested whether three acquisition parameters-(1) sequence complexity (two-experiment MEscher-GArwood Point RESolved Spectroscopy [MEGA-PRESS] vs. four-experiment Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy [HERMES]); (2) editing pulse duration (14 vs. 20 ms); and (3) scanner frequency drift (interleaved water referencing [IWR] turned ON vs. OFF)-and two linear combination modeling variations-(1) three different coedited macromolecule models (called "1to1GABA", "1to1GABAsoft", and "3to2MM" in the Osprey software package); and (2) 0.55- versus 0.4-ppm spline baseline knot spacing-affected the within-subject coefficient of variation of GABA + macromolecules (GABA+). We collected edited MRS data from the dorsal anterior cingulate cortex from 20 participants (mean age: 30.8 ± 9.5 years; 10 males). Test and retest scans were separated by removing the participant from the scanner for 5-10 min. Each acquisition consisted of two MEGA-PRESS and two HERMES sequences with editing pulse durations of 14 and 20 ms (referred to here as MEGA-14, MEGA-20, HERMES-14, and HERMES-20; all TE = 80 ms, 224 averages). We identified the best test-retest reproducibility following postprocessing with a composite model of the 0.9- and 3-ppm macromolecules ("3to2MM"); this model performed particularly well for the HERMES data. Furthermore, sparser (0.55- compared with 0.4-ppm) spline baseline knot spacing yielded generally better test-retest reproducibility for GABA+. Replicating our prior results, linear combination modeling in Osprey compared with simple peak fitting in Gannet resulted in substantially better test-retest reproducibility. However, reproducibility did not consistently differ for MEGA-PRESS compared with HERMES, for 14- compared with 20-ms editing pulses, or for IWR-ON versus IWR-OFF. These results highlight the importance of model selection for edited MRS studies of GABA+, particularly for clinical studies that focus on individual patient differences in GABA+ or changes following an intervention.

sLASER and PRESS perform similarly at revealing metabolite-age correlations at 3 T.

PURPOSE: To compare the respective ability of PRESS and sLASER to reveal biological relationships, using age as a validation covariate at 3 T. METHODS: MRS data were acquired from 102 healthy volunteers using PRESS and sLASER in centrum semiovale and posterior cingulate cortex (PCC). Acquisition parameters included TR/TE = 2000/30 ms, 96 transients, and 2048 datapoints sampled at 2 kHz. Spectra were analyzed using Osprey. SNR, FWHM linewidth of total creatine, and metabolite concentrations were extracted. A linear model was used to compare SNR and linewidth. Paired t-tests were used to assess differences in metabolite measurements between PRESS and sLASER. Correlations were used to evaluate the relationship between PRESS and sLASER metabolite estimates, as well as the strength of each metabolite-age relationship. Coefficients of variation were calculated to assess inter-subject variability in each metabolite measurement. RESULTS: SNR and linewidth were significantly higher (p < 0.01) for sLASER than PRESS in PCC. Paired t-tests showed significant differences between PRESS and sLASER in most metabolite measurements. PRESS-sLASER measurements were significantly correlated (p < 0.05) for most metabolites. Metabolite-age relationships were consistently identified using both methods. Similar coefficients of variation were observed for most metabolites. CONCLUSION: The study results suggest strong agreement between PRESS and sLASER in identifying relationships between brain metabolites and age in centrum semiovale and PCC data acquired at 3 T. sLASER is technically desirable due to the reduced chemical shift displacement artifact; however, PRESS performed similarly in homogeneous brain regions at clinical field strength.

Brain Glutathione and GABA+ levels in autistic children.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a large cohort of children aged 8-12 years with ASD (n=52) and typically developing children (TDC, n=49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.

Impacts of spaceflight experience on human brain structure.

Spaceflight induces widespread changes in human brain morphology. It is unclear if these brain changes differ with varying mission duration or spaceflight experience history (i.e., novice or experienced, number of prior missions, time between missions). Here we addressed this issue by quantifying regional voxelwise changes in brain gray matter volume, white matter microstructure, extracellular free water (FW) distribution, and ventricular volume from pre- to post-flight in a sample of 30 astronauts. We found that longer missions were associated with greater expansion of the right lateral and third ventricles, with the majority of expansion occurring during the first 6 months in space then appearing to taper off for longer missions. Longer inter-mission intervals were associated with greater expansion of the ventricles following flight; crew with less than 3 years of time to recover between successive flights showed little to no enlargement of the lateral and third ventricles. These findings demonstrate that ventricle expansion continues with spaceflight with increasing mission duration, and inter-mission intervals less than 3 years may not allow sufficient time for the ventricles to fully recover their compensatory capacity. These findings illustrate some potential plateaus in and boundaries of human brain changes with spaceflight.

Application of a 1H Brain MRS Benchmark Dataset to Deep Learning for Out-of-Voxel Artifacts.

Neural networks are potentially valuable for many of the challenges associated with MRS data. The purpose of this manuscript is to describe the AGNOSTIC dataset, which contains 259,200 synthetic 1H MRS examples for training and testing neural networks. AGNOSTIC was created using 270 basis sets that were simulated across 18 field strengths and 15 echo times. The synthetic examples were produced to resemble in vivo brain data with combinations of metabolite, macromolecule, residual water signals, and noise. To demonstrate the utility, we apply AGNOSTIC to train two Convolutional Neural Networks (CNNs) to address out-of-voxel (OOV) echoes. A Detection Network was trained to identify the point-wise presence of OOV echoes, providing proof of concept for real-time detection. A Prediction Network was trained to reconstruct OOV echoes, allowing subtraction during post-processing. Complex OOV signals were mixed into 85% of synthetic examples to train two separate CNNs for the detection and prediction of OOV signals. AGNOSTIC is available through Dryad and all Python 3 code is available through GitHub. The Detection network was shown to perform well, identifying 95% of OOV echoes. Traditional modeling of these detected OOV signals was evaluated and may prove to be an effective method during linear-combination modeling. The Prediction Network greatly reduces OOV echoes within FIDs and achieved a median log10 normed-MSE of -1.79, an improvement of almost two orders of magnitude.

Daily artificial gravity is associated with greater neural efficiency during sensorimotor adaptation.

Altered vestibular signaling and body unloading in microgravity results in sensory reweighting and adaptation. Microgravity effects are well-replicated in head-down tilt bed rest (HDBR). Artificial gravity (AG) is a potential countermeasure to mitigate the effects of microgravity on human physiology and performance. We examined the effectiveness of daily AG for mitigating brain and/or behavioral changes in 60 days of HDBR. One group received AG for 30 minutes daily (AG; n = 16) and a control group spent the same time in HDBR but received no AG (CTRL; n = 8). All participants performed a sensorimotor adaptation task five times during fMRI scanning: twice prior to HDBR, twice during HDBR, and once following HDBR. The AG group showed similar behavioral adaptation effects compared with the CTRLs. We identified decreased brain activation in the AG group from pre to late HDBR in the cerebellum for the task baseline portion and in the thalamus, calcarine, cuneus, premotor cortices, and superior frontal gyrus in the AG group during the early adaptation phase. The two groups also exhibited differential brain-behavior correlations. Together, these results suggest that AG may result in a reduced recruitment of brain activity for basic motor processes and sensorimotor adaptation. These effects may stem from the somatosensory and vestibular stimulation that occur with AG.

sLASER and PRESS Perform Similarly at Revealing Metabolite-Age Correlations.

Purpose: To compare the respective ability of PRESS and sLASER to reveal biological relationships, using age as a validation covariate. Methods: MRS data were acquired from 102 healthy volunteers using PRESS and sLASER in centrum semiovale (CSO) and posterior cingulate cortex (PCC) regions. Acquisition parameters included TR/TE 2000/30 ms; 96 transients; 2048 datapoints sampled at 2 kHz.Spectra were analyzed using Osprey. Signal-to-noise ratio (SNR), full-width-half-maximum linewidth of tCr, and metabolite concentrations were extracted. A linear model was used to compare SNR and linewidth. Paired t-tests were used to assess differences in metabolite measurements between PRESS and sLASER. Correlations were used to evaluate the relationship between PRESS and sLASER metabolite estimates, as well as the strength of each metabolite-age relationship. Coefficients of variation were calculated to assess inter-subject variability in each metabolite measurement. Results: SNR and linewidth were significantly higher (p<0.05) for sLASER than PRESS. Paired t-tests showed significant differences between PRESS and sLASER in most metabolite measurements. Metabolite measures were significantly correlated (p<0.05) for most metabolites between the two methods except GABA, Gln and Lac in CSO and GSH, Lac and NAAG in PCC. Metabolite-age relationships were consistently identified using both PRESS and sLASER. Similar CVs were observed for most metabolites. Conclusion: The study results suggest strong agreement between PRESS and sLASER in identifying relationships between brain metabolites and age in CSO and PCC data acquired at 3T. sLASER is technically desirable due to the reduced chemical shift displacement artifact; however, PRESS performed similarly in 'good' brain regions at clinical field strength.

Impact of acquisition and modeling parameters on test-retest reproducibility of edited GABA.

Literature values for within-subject test-retest reproducibility of gamma-aminobutyric acid (GABA), measured with edited magnetic resonance spectroscopy (MRS), vary widely. Reasons for this variation remain unclear. Here we tested whether sequence complexity (two-experiment MEGA-PRESS versus four-experiment HERMES), editing pulse duration (14 versus 20 ms), scanner frequency drift (interleaved water referencing (IWR) turned ON versus OFF), and linear combination modeling variations (three different co-edited macromolecule models and 0.55 versus 0.4 ppm spline baseline knot spacing) affected the within-subject coefficient of variation of GABA + macromolecules (GABA+). We collected edited MRS data from the dorsal anterior cingulate cortex from 20 participants (30.8 ± 9.5 years; 10 males). Test and retest scans were separated by removing the participant from the scanner for 5-10 minutes. Each acquisition consisted of two MEGA-PRESS and two HERMES sequences with editing pulse durations of 14 and 20 ms (referred to here as: MEGA-14, MEGA-20, HERMES-14, and HERMES-20; all TE = 80 ms, 224 averages). Reproducibility did not consistently differ for MEGA-PRESS compared with HERMES or for 14 compared with 20 ms editing pulses. A composite model of the 0.9 and 3 ppm macromolecules (particularly for HERMES) and sparser (0.55 compared with 0.4 ppm) spline baseline knot spacing yielded generally better test-retest reproducibility for GABA+. Replicating our prior results, linear combination modeling in Osprey compared with simple peak fitting in Gannet resulted in substantially better test-retest reproducibility. These results highlight the importance of model selection for edited MRS studies of GABA+, particularly for clinical studies which focus on individual patient differences in GABA+ or changes following an intervention.

Changes in working memory brain activity and task-based connectivity after long-duration spaceflight.

We studied the longitudinal effects of approximately 6 months of spaceflight on brain activity and task-based connectivity during a spatial working memory (SWM) task. We further investigated whether any brain changes correlated with changes in SWM performance from pre- to post-flight. Brain activity was measured using functional magnetic resonance imaging while astronauts (n = 15) performed a SWM task. Data were collected twice pre-flight and 4 times post-flight. No significant effects on SWM performance or brain activity were found due to spaceflight; however, significant pre- to post-flight changes in brain connectivity were evident. Superior occipital gyrus showed pre- to post-flight reductions in task-based connectivity with the rest of the brain. There was also decreased connectivity between the left middle occipital gyrus and the left parahippocampal gyrus, left cerebellum, and left lateral occipital cortex during SWM performance. These results may reflect increased visual network modularity with spaceflight. Further, increased visual and visuomotor connectivity were correlated with improved SWM performance from pre- to post-flight, while decreased visual and visual-frontal cortical connectivity were associated with poorer performance post-flight. These results suggest that while SWM performance remains consistent from pre- to post-flight, underlying changes in connectivity among supporting networks suggest both disruptive and compensatory alterations due to spaceflight.

Brain total creatine differs between primary progressive aphasia (PPA) subtypes and correlates with disease severity.

Primary progressive aphasia (PPA) is comprised of three subtypes: logopenic (lvPPA), non-fluent (nfvPPA), and semantic (svPPA). We used magnetic resonance spectroscopy (MRS) to measure tissue-corrected metabolite levels in the left inferior frontal gyrus (IFG) and right sensorimotor cortex (SMC) from 61 PPA patients. We aimed to: (1) characterize subtype differences in metabolites; and (2) test for metabolite associations with symptom severity. tCr differed by subtype across the left IFG and right SMC. tCr levels were lowest in lvPPA and highest in svPPA. tCr levels predicted lvPPA versus svPPA diagnosis. Higher IFG tCr and lower Glx correlated with greater disease severity. As tCr is involved in brain energy metabolism, svPPA pathology might involve changes in specific cellular energy processes. Perturbations to cellular energy homeostasis in language areas may contribute to symptoms. Reduced cortical excitatory capacity (i.e. lower Glx) in language regions may also contribute to symptoms. Thus, tCr may be useful for differentiating between PPA subtypes, and both tCr and Glx might have utility in understanding PPA mechanisms and tracking progression.

Impact of gradient scheme and non-linear shimming on out-of-voxel echo artifacts in edited MRS.

Out-of-voxel (OOV) signals are common spurious echo artifacts in MRS. These signals often manifest in the spectrum as very strong "ripples," which interfere with spectral quantification by overlapping with targeted metabolite resonances. Dephasing optimization through coherence order pathway selection (DOTCOPS) gradient schemes are algorithmically optimized to suppress all potential alternative coherence transfer pathways (CTPs), and should suppress unwanted OOV echoes. In addition, second-order shimming uses non-linear gradient fields to maximize field homogeneity inside the voxel, which unfortunately increases the diversity of local gradient fields outside of the voxel. Given that strong local spatial B0 gradients can refocus unintended CTPs, it is possible that OOVs are less prevalent when only linear first-order shimming is applied. Here we compare the size of unwanted OOV signals in Hadamard-edited (HERMES) data acquired with either a local gradient scheme (which we refer to here as "Shared") or DOTCOPS, and with first- or second-order shimming. We collected data from 15 healthy volunteers in two brain regions (voxel size 30 × 26 × 26 mm3 ) from which it is challenging to acquire MRS data: medial prefrontal cortex and left temporal cortex. Characteristic OOV echoes were seen in both GABA- and GSH-edited spectra for both brain regions, gradient schemes, and shimming approaches. A linear mixed-effect model revealed a statistically significant difference in the average residual based on the gradient scheme in both GABA- (p < 0.001) and GSH-edited (p < 0.001) spectra: that is, the DOTCOPS gradient scheme resulted in smaller OOV artifacts compared with the Shared scheme. There were no significant differences in OOV artifacts associated with shimming method. Thus, these results suggest that the DOTCOPS gradient scheme for J-difference-edited PRESS acquisitions yields spectra with smaller OOV echo artifacts than the Shared gradient scheme implemented in a widely disseminated editing sequence.

Neurometabolic timecourse of healthy aging.

PURPOSE: The neurometabolic timecourse of healthy aging is not well-established, in part due to diversity of quantification methodology. In this study, a large structured cross-sectional cohort of male and female subjects throughout adulthood was recruited to investigate neurometabolic changes as a function of age, using consensus-recommended magnetic resonance spectroscopy quantification methods. METHODS: 102 healthy volunteers, with approximately equal numbers of male and female participants in each decade of age from the 20s, 30s, 40s, 50s, and 60s, were recruited with IRB approval. MR spectroscopic data were acquired on a 3T MRI scanner. Metabolite spectra were acquired using PRESS localization (TE=30 ms; 96 transients) in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). Water-suppressed spectra were modeled using the Osprey algorithm, employing a basis set of 18 simulated metabolite basis functions and a cohort-mean measured macromolecular spectrum. Pearson correlations were conducted to assess relationships between metabolite concentrations and age for each voxel; Spearman correlations were conducted where metabolite distributions were non-normal. Paired t-tests were run to determine whether metabolite concentrations differed between the PCC and CSO. Finally, robust linear regressions were conducted to assess both age and sex as predictors of metabolite concentrations in the PCC and CSO and separately, to assess age, signal-noise ratio, and full width half maximum (FWHM) linewidth as predictors of metabolite concentrations. RESULTS: Data from four voxels were excluded (2 ethanol; 2 unacceptably large lipid signal). Statistically-significant age*metabolite Pearson correlations were observed for tCho (r(98)=0.33, p<0.001), tCr (r(98)=0.60, p<0.001), and mI (r(98)=0.32, p=0.001) in the CSO and for NAAG (r(98)=0.26, p=0.008), tCho(r(98)=0.33, p<0.001), tCr (r(98)=0.39, p<0.001), and Gln (r(98)=0.21, p=0.034) in the PCC. Spearman correlations for non-normal variables revealed a statistically significant correlation between sI and age in the CSO (r(86)=0.26, p=0.013). No significant correlations were seen between age and tNAA, NAA, Glx, Glu, GSH, PE, Lac, or Asp in either region (all p>0.20). Age associations for tCho, tCr, mI and sI in the CSO and for NAAG, tCho, and tCr in the PCC remained when controlling for sex in robust regressions. CSO NAAG and Asp, as well as PCC tNAA, sI, and Lac were higher in women; PCC Gln was higher in men. When including an age*sex interaction term in robust regression models, a significant age*sex interaction was seen for tCho (F(1,96)=11.53, p=0.001) and GSH (F(1,96)=7.15, p=0.009) in the CSO and tCho (F(1,96)=9.17, p=0.003), tCr (F(1,96)=9.59, p=0.003), mI (F(1,96)=6.48, p=0.012), and Lac (F(1,78)=6.50, p=0.016) in the PCC. In all significant interactions, metabolite levels increased with age in females, but not males. There was a significant positive correlation between linewidth and age. Age relationships with tCho, tCr, and mI in the CSO and tCho, tCr, mI, and sI in the PCC were significant after controlling for linewidth and FWHM in robust regressions. CONCLUSION: The primary (correlation) results indicated age relationships for tCho, tCr, mI, and sI in the CSO and for NAAG, tCho, tCr, and Gln in the PCC, while no age correlations were found for tNAA, NAA, Glx, Glu, GSH, PE, Lac, or Asp in either region. Our results provide a normative foundation for future work investigating the neurometabolic time course of healthy aging using MRS.

Longitudinal MRI-visible perivascular space (PVS) changes with long-duration spaceflight.

Humans are exposed to extreme environmental stressors during spaceflight and return with alterations in brain structure and shifts in intracranial fluids. To date, no studies have evaluated the effects of spaceflight on perivascular spaces (PVSs) within the brain, which are believed to facilitate fluid drainage and brain homeostasis. Here, we examined how the number and morphology of magnetic resonance imaging (MRI)-visible PVSs are affected by spaceflight, including prior spaceflight experience. Fifteen astronauts underwent six T1-weighted 3 T MRI scans, twice prior to launch and four times following their return to Earth after ~ 6-month missions to the International Space Station. White matter MRI-visible PVS number and morphology were calculated using an established, automated segmentation algorithm. We validated our automated segmentation algorithm by comparing algorithm PVS counts with those identified by two trained raters in 50 randomly selected slices from this cohort; the automated algorithm performed similarly to visual ratings (r(48) = 0.77, p < 0.001). In addition, we found high reliability for four of five PVS metrics across the two pre-flight time points and across the four control time points (ICC(3,k) > 0.50). Among the astronaut cohort, we found that novice astronauts showed an increase in total PVS volume from pre- to post-flight, whereas experienced crewmembers did not (p = 0.020), suggesting that experienced astronauts may exhibit holdover effects from prior spaceflight(s). Greater pre-flight PVS load was associated with more prior flight experience (r = 0.60-0.71), though these relationships did not reach statistical significance (p > 0.05). Pre- to post-flight changes in ventricular volume were not significantly associated with changes in PVS characteristics, and the presence of spaceflight associated neuro-ocular syndrome (SANS) was not associated with PVS number or morphology. Together, these findings demonstrate that PVSs can be consistently identified on T1-weighted MRI scans, and that spaceflight is associated with PVS changes. Specifically, prior spaceflight experience may be an important factor in determining PVS characteristics.

Differential Relationships Between Brain Structure and Dual Task Walking in Young and Older Adults.

Almost 25% of all older adults experience difficulty walking. Mobility difficulties for older adults are more pronounced when they perform a simultaneous cognitive task while walking (i.e., dual task walking). Although it is known that aging results in widespread brain atrophy, few studies have integrated across more than one neuroimaging modality to comprehensively examine the structural neural correlates that may underlie dual task walking in older age. We collected spatiotemporal gait data during single and dual task walking for 37 young (18-34 years) and 23 older adults (66-86 years). We also collected T 1-weighted and diffusion-weighted MRI scans to determine how brain structure differs in older age and relates to dual task walking. We addressed two aims: (1) to characterize age differences in brain structure across a range of metrics including volumetric, surface, and white matter microstructure; and (2) to test for age group differences in the relationship between brain structure and the dual task cost (DTcost) of gait speed and variability. Key findings included widespread brain atrophy for the older adults, with the most pronounced age differences in brain regions related to sensorimotor processing. We also found multiple associations between regional brain atrophy and greater DTcost of gait speed and variability for the older adults. The older adults showed a relationship of both thinner temporal cortex and shallower sulcal depth in the frontal, sensorimotor, and parietal cortices with greater DTcost of gait. Additionally, the older adults showed a relationship of ventricular volume and superior longitudinal fasciculus free-water corrected axial and radial diffusivity with greater DTcost of gait. These relationships were not present for the young adults. Stepwise multiple regression found sulcal depth in the left precentral gyrus, axial diffusivity in the superior longitudinal fasciculus, and sex to best predict DTcost of gait speed, and cortical thickness in the superior temporal gyrus to best predict DTcost of gait variability for older adults. These results contribute to scientific understanding of how individual variations in brain structure are associated with mobility function in aging. This has implications for uncovering mechanisms of brain aging and for identifying target regions for mobility interventions for aging populations.

Case Report: No Evidence of Intracranial Fluid Shifts in an Astronaut Following an Aborted Launch.

Spaceflight induces lasting enlargement of the brain's ventricles as well as intracranial fluid shifts. These intracranial fluid shifts have been attributed to prolonged microgravity exposure, however, the potential effects of hypergravity exposure during launch and landing have yet to be elucidated. Here we describe a case report of a Crewmember who experienced an Aborted Launch ("CAL"). CAL's launch and landing experience was dissociated from prolonged microgravity exposure. Using MRI, we show that hypergravity exposure during the aborted launch did not induce lasting ventricular enlargement or intracranial fluid shifts resembling those previously reported with spaceflight. This case study therefore rules out hypergravity during launch and landing as a contributing factor to previously reported long-lasting intracranial fluid changes following spaceflight.