Saipavitra Murali‐Manohar

The paper estimates age-related changes in metabolite relaxation times in pediatric thalamus using MRS and provides linear equations for age-specific correction.

This paper introduces an AI-integrated MRI pulse sequence that detects and adapts to out-of-voxel artifacts in real-time, improving data quality through gradient adjustments.

The paper analyzes age-related changes in neurometabolite concentrations in infants using 1H-MRS data from the HBCD study, finding significant increases in some metabolites and decreases in others.

This paper develops a Hadamard-edited MRS method to separate methylmalonic acid and lactate signals, demonstrating its effectiveness in vivo for MMAemia diagnosis.

The paper introduces a method to identify out-of-voxel signals in MRS by analyzing phase cycles, leading to improved suppression of artifacts through optimized gradients.

This paper optimizes a gradient scheme for PRESS-localized edited MRS to suppress out-of-voxel artifacts using a volume-based likelihood model and genetic algorithm.

The paper measures metabolite T1 relaxation times in healthy adults across age groups and finds age-related decreases in several metabolites in specific brain regions.

The paper examines age-related GABA level changes in cognitively-intact oldest-old adults, finding that GABA decline flattens after age 80, suggesting a link between GABAergic function and successful cognitive aging.

The paper investigates age-related changes in metabolite T2 relaxation times across the adult lifespan in a multi-site cohort, finding significant declines in several metabolites with aging.

This paper introduces a novel 2D J-resolved metabolite-cycled semiLASER spectroscopy method to quantify 16 metabolites in the human brain at 9.4 T, demonstrating improved sensitivity and reduced acquisition time.

This paper develops a water relaxation atlas to correct metabolite concentrations in MRS by integrating age and region-specific relaxation values into the analysis workflow.

The paper evaluates the ISTHMUS MRS sequence for reproducibility and data quality in the HBCD study, finding improved T2 correction and reduced operator workload.

This study found no significant differences in cerebral glutathione or GABA levels between autistic children and typically developing children, but found a positive correlation between GABA levels and ADHD inattention scores.

This study evaluates how acquisition and modeling parameters affect test-retest reproducibility of GABA+ measurements using edited MRS, finding that model selection significantly impacts reproducibility.

This paper introduces AGNOSTIC, a synthetic 1H MRS dataset for training deep learning models to detect and predict out-of-voxel echoes in brain MRS data.

This study compares PRESS and sLASER for detecting metabolite-age correlations in brain regions, finding similar results despite technical differences.

The paper examines age-related changes in metabolite T1 relaxation times in brain regions using a cross-sectional dataset and finds significant decreases in white-matter-rich areas with age.

The paper investigates neurometabolic changes with age using MR spectroscopy in a cross-sectional cohort, finding age correlations for several metabolites but not others.

The paper shows that over half of the variance in 1H-MRS metabolite estimates is shared across all metabolites, with age and sex affecting this common variance.

This paper presents quantitative metabolite maps of 12 metabolites in human brains at 9.4 T, using voxel-specific T1-relaxation corrections for water and metabolites.

This paper demonstrates that 2x zero-filling improves modeling accuracy in in vivo MRS data compared to no zero-filling, with no additional benefit from higher zero-filling.

This study compares metabolite estimation using different macromolecular modeling strategies and finds that cohort-mean measured MM basis functions yield more robust results than subject-specific or parameterized ones.

The paper compares two techniques for measuring glucose metabolism in the human brain using deuterium-labeled compounds and MR spectroscopy, estimating TCA cycle and glutamine synthesis rates.