Aaron T. Gudmundson

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 study benchmarks how different anatomical segmentation tools affect MRS-derived metabolite concentration estimates in brain imaging.

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

This study compares the test-retest reproducibility of DESPOT and QALAS for T1 and T2 mapping in healthy volunteers, finding QALAS provides better reproducibility and reduced acquisition time.

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 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 examines how brain glutathione levels change with age and their link to cognitive function in healthy adults, finding age-related declines in specific brain regions and sex differences in GSH dynamics.

This paper introduces an automated MRS analysis workflow that reduces manual steps and integrates with neuroimaging standards, improving efficiency and scalability.

The paper conducts a meta-analysis of brain MRS studies to establish metabolite concentration ranges and relaxation rates for use in simulations and as references.

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.