Jessica Archibald

Purpose: Quantification of metabolite concentrations using MRS requires tissue‐dependent signal corrections. Accurate estimation of voxel tissue composition is therefore essential. Commonly used brain tissue segmentation tools differ in their algorithms and implementation, potentially introducing variability in MRS‐derived concentration estimates. This study investigates the impact and reliability of tissue segmentation on metabolite quantification. Methods: Three segmentation tools (ANTs, FSL, SPM) were evaluated using an in vivo test–retest MRI/MRS dataset. Voxelwise GM/WM/CSF fractions were applied to compute tissue‐corrected total creatine (tCr) concentrations. Linear mixed‐effects modeling, variance‐component partitioning, and intraclass correlation coefficients (ICCs) quantified tool‐, session‐, and participant‐related variance under permutation scenarios that isolated segmentation‐ and MRS‐related effects. As a benchmark for segmentation performance, comparisons with manually segmented data were conducted across three brain regions. Results: Segmentation tools produced systematically different tissue fractions that propagated into differences in tCr concentration estimates. Variance partitioning attributed 56.8%, 50.0%, and 51.3% of total tCr concentration variability to segmentation tool across the three permutations, with participant‐specific factors accounting for 34.7%, 36.2%, and 28.5%, respectively. When segmentation variability was held constant, test–retest reliability was high (ICC > 0.8) but dropped to ∼0.5 when both segmentation and MRS variability varied. Agreement with manual segmentation was region‐ and tool‐dependent, with the lowest agreement in the thalamus. Conclusion: Tissue segmentation contributes substantially to the variability in MRS‐derived metabolite concentration estimates. These results underscore the need for transparent segmentation reporting and data sharing to ensure reproducibility and cross‐study comparability in MRS research.

Purpose: Spectral editing is the most common MRS approach for noninvasive in vivo measurement of low‐concentration, strongly overlapped metabolites in the brain, such as γ‐aminobutyric acid (GABA) and glutathione (GSH). Multi‐metabolite editing methods, such as HERMES and HERCULES, enable the editing of multiple J ‐coupled metabolites in a single acquisition without increasing the total scan time. Yet little is known regarding the reliability of these methods. This study assessed the test–retest reliability of HERMES and HERCULES, where volume localization was achieved using both PRESS and sLASER. Methods: Sixteen healthy adult volunteers were scanned twice in two separate sessions. Single‐voxel edited MRS data were acquired in the medial parietal lobe using the following sequences: (1) HERMES‐PRESS; (2) HERMES‐sLASER; (3) HERCULES‐PRESS; (4) HERCULES‐sLASER. Spectra were processed and metabolites were quantified relative to tCr. Data quality metrics and reliability statistics were estimated for all four acquisitions. Results: HERMES‐sLASER produced lower within‐subject coefficients of variation (CV _ws ) for GABA + co‐edited macromolecules (GABA+), GSH, glutamine (Gln), myo ‐inositol (mI), NAA, and total Cho (tCho), suggesting improved reliability compared to HERMES‐PRESS. HERCULES‐sLASER produced better reliability than HERCULES‐PRESS for GABA+, GSH, aspartate, Gln, lactate, mI, NAA, and tCho with lower CV _ws . N ‐acetylaspartylglutamate (NAAG) showed higher CV _ws for HERCULES‐sLASER, and Glu showed higher CV _ws for HERMES‐sLASER and HERCULES‐sLASER. Overall, these findings suggest that sLASER yields lower within‐subject variability than PRESS for several metabolites for both HERMES and HERCULES, supporting improved measurement reliability. Conclusion: sLASER yielded better test–retest reliability than PRESS for most metabolites than for multi‐metabolite edited MRS.

Purpose: Estimation of metabolite concentrations in brain magnetic resonance spectroscopy (MRS) requires correction for differences in tissue water content, relaxation properties, and the proportions of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). Accurate knowledge of the relative proportions of these tissue classes within the volume of interest is therefore essential for reliable quantification. Commonly used brain segmentation tools differ in their algorithms, priors, and implementation, potentially introducing variability in MRS-derived concentration estimates. This study investigates the impact of segmentation software on estimated absolute concentrations. Methods: Three segmentation software tools, ANTs, FSL, and SPM, were evaluated. Segmentations were applied to an in vivo test-retest MR dataset to assess (1) differences in estimated tissue fractions, and (2) how these differences propagate into tissue-corrected metabolite concentrations. As an additional validity check and biological benchmark of segmentation performance, age-related associations with GM and total creatine (tCr) were examined. Results: Significant differences ( p < 0.0001) were observed in tissue fraction estimates between segmentation tools, leading to differences in metabolite concentration estimates of up to 9% under identical acquisition and modeling conditions. Although the strength of the correlation varied between segmentation methods, no statistically significant differences were found. Conclusion: The choice of segmentation methodology contributed substantially to variability in MRS “absolute” metabolite concentration estimates. These results underscore the need for transparent segmentation reporting to ensure reproducibility and cross-study comparability in MRS research. Quantifying the segmentation-driven variability allows researchers to contextualize cross-study differences, helping determine whether observed effects are methodological or biologically meaningful.

Purpose: Spectral editing is the most common MRS approach for noninvasive in vivo measurement of low-concentration, strongly overlapped metabolites in the brain, such as γ-aminobutyric acid (GABA) and glutathione (GSH). Multi-metabolite editing methods, including HERMES and HERCULES, have recently been introduced, where multiple J -coupled metabolites can be edited in a single acquisition without increasing total scan time. Yet little is known regarding the reliability of these methods. This study assessed the test-retest reliability of HERMES and HERCULES, where volume localization was achieved using either PRESS or sLASER. Methods: Sixteen healthy adult volunteers were scanned twice in two separate sessions. Single-voxel edited MRS data were acquired in the medial parietal lobe using the following sequences: (1) HERMES-PRESS; (2) HERMES-sLASER; (3) HERCULES-PRESS; (4) HERCULES-sLASER. Spectra were processed and metabolites were quantified using the Osprey software. Data quality metrics and reliability statistics were estimated for all four acquisitions. Results: HERMES-sLASER demonstrated lower within-subjects coefficients of variation (CV _ws ) for GSH, glutamine (Gln), and glutamate (Glu) + Gln (Glx), suggesting improved reliability compared to HERMES-PRESS. However, GABA + co-edited macromolecules (GABA+) and Glu showed higher CV _ws for HERMES-sLASER. HERCULES-sLASER produced better reliability than HERCULES-PRESS for GABA+, GSH, Glu, Gln, Glx, aspartate (Asp), and lactate (Lac). N -acetylaspartate (NAA) and N -acetylaspartylglutamate (NAAG) showed higher CV _ws for HERCULES-sLASER. These findings suggest that sLASER may be more advantageous than PRESS for volume localization in simultaneous multi-metabolite editing. Conclusion: Using sLASER yielded better test-retest reliability for most metabolites than using PRESS for volume localization for HERMES and HERCULES.

A 3T multimodal MRI study of healthy adults (n=19; 10 female; 21.3 - 53.4 years) was performed to investigate the relationship between fMRI long-range temporal correlations and excitatory/inhibitory balance. The study objective was to determine if the Hurst exponent (H) — an estimate of the self-correlation and signal complexity — of the blood-oxygen-level-dependent signal is correlated with the excitatory-inhibitory (E:I) ratio. E:I has been proposed to serve as a control parameter for brain criticality — the theory that the brain operates near a critical point between order and disorder, optimizing information processing and adaptability — which H is believed to be a measure of. Thus, understanding if H and E:I are correlated would clarify this relationship. Moreover, findings in this domain have implications for neurological and neuropsychiatric conditions with disrupted E:I balance, such as autism spectrum disorder, schizophrenia, and Alzheimer’s disease. From a practical perspective, H is easier to accurately measure than E:I ratio at 3T MRI. If H can serve as a proxy for E:I, it may serve as a more practical clinical biomarker for this imbalance and for neuroscience research in general. The study collected functional MRI and magnetic resonance spectroscopy data during rest and movie-watching. H was found to increase with movie-watching compared to rest, while E:I (glutamate/GABA) did not change between conditions. H and E:I were not correlated during either movie-watching or rest. This study represents the first attempt to investigate this connection in vivo in humans. We conclude that, at 3T and with our particular methodologies, no association was found. We end with lessons learned and suggestions for future research.

The utilization of structural, functional, and biochemical data from the human brain has grown in addressing inquiries related to neurodegenerative and neuropsychiatric conditions. However, the normal variability within these measures has not been systematically reported. In this work, a database comprising these outcome measures in a healthy population (n=51) was established to potentially serve as a comparative reference. Healthy individuals underwent standardized procedures to ensure consistent collection of magnetic resonance imaging (MRI) and spectroscopy data. The MR data was acquired using a 3T scanner with various sequences, including MPRAGE 3D T1w, pseudo-continuous arterial spin labelling (pCASL), and single voxel proton magnetic resonance spectroscopy (1H-MRS). Established and custom software tools were employed to analyze outcome measures such as tissue segmentation, cortical thickness, cerebral blood flow, metabolite levels, and temperature estimated using MRS. This study provides a comprehensive overview of the data analysis process, aiming to facilitate future utilization of the collected data through an interactive dashboard developed in R using the Shiny framework.

In a large, sex-balanced sample of healthy individuals, we demonstrate that average regional differences (rostral to caudal) in cingulate cortex glutamate exist, using optimized experimental conditions and 3 T magnetic resonance spectroscopy techniques. Results align with observations from 7 T. A novel clustering approach was introduced to determine the number of patterns for glutamate in the healthy adult brain for the first time. These findings demonstrate that regional differences are detectable at 3 T when present and suggest the occurrence of multiple glutamate metabolism patterns in the cingulate.

We provide evidence for supraspinal faciliation measured via laser-evoked potentails in response to a shortened and methodologically improved repetitive painful stimulation paradigm, serving the broader scientific community, insofar as providing a paradigm can feasibly be completed in a caldendar week. These findings provide new evidence using laser-evoked potentials indicating increased activation of the anterior cingulate cortex during prolonged pain processing.

To understand neurochemical brain responses to pain, proton magnetic resonance spectroscopy (¹H-MRS) is used in humans in vivo to examine various metabolites. Recent MRS investigations have adopted a functional approach, where acquisitions of MRS are performed over time to track task-related changes. Previous studies suggest glutamate is of primary interest, as it may play a role during cortical processing of noxious stimuli. The objective of this study was to examine the metabolic effect (i.e., glutamate) in the anterior cingulate cortex during noxious stimulation using fMRS. The analysis addressed changes in glutamate and glutamate + glutamine (Glx) associated with the onset of pain, and the degree by which fluctuations in metabolites corresponded with continuous pain outcomes. Results suggest healthy participants undergoing tonic noxious stimulation demonstrated increased concentrations of glutamate and Glx at the onset of pain. Subsequent reports of pain were not accompanied by corresponding changes in glutamate of Glx concentrations. An exploratory analysis on sex revealed large effect size changes in glutamate at pain onset in female participants, compared with medium-sized effects in male participants. We propose a role for glutamate in the ACC related to the detection of a noxious stimulus.