Reproducibility of Metabolic Mapping Using 2D Multi‐Slice Short‐TE and GABA‐Edited Spin‐Echo MRSI at 3T in a Single Protocol

MRSI is a non-invasive tool for mapping metabolic distributions in multi-focal or other diseases where the location of abnormalities may be uncertain. High-concentration metabolites can be investigated at 3T using non-edited MRSI, whereas lower-concentration metabolites, such as GABA, typically require specialized editing techniques because of spectral overlap. This study reports on the reproducibility of a protocol containing both co-localized short-TE and GABA-edited multi-slice spin-echo 2D MRSI. Multi-slice, short-TE (TE 20 ms) and GABA-edited (TE 68 ms) MRSI at a nominal spatial resolution of 2.2 cm<sup>3</sup> was performed twice (7 to 14 days apart) at 3T on 11 healthy volunteers (age range 7 to 43 years). Data analysis was performed in the "Osprey" software package, including retrospective motion compensation, consensus-recommended processing, and linear-combination modeling. Metabolite estimates for six metabolites were quantified relative to total creatine (tCr) and water in 14 regions of interest. Reproducibility was assessed using intra- and inter-subject coefficients of variation. Short-TE MRSI metabolite estimates for total N-acetylaspartate (tNAA), tCr, total choline (tCho), myo-inositol (mI), and the sum of glutamate and glutamine (Glx) were found to be highly reproducible for both creatine- and water-referenced concentration estimates, with 77% of the regions of interest meeting the quality-control criteria for both visits and 96% for at least one visit. Average intra-subject CVs were 5.8% and 4.8%, and inter-subject CVs were 11.1% and 9.7% for water-referenced and tCr-referenced estimates, respectively. For GABA+ (GABA + macromolecules) estimates, 46% of the voxels of interest met quality-control criteria for both visits, and 82% for at least one visit. In the remaining datasets, the average intra-subject CVs were 13.5% for both quantification methods, and the inter-subject CVs were 13.5% and 16.9% for water-referenced and creatine-referenced estimates, respectively. 3T-MRSI sequences can achieve reproducible mapping with extended brain coverage of five major metabolites (tNAA, tCr, tCho, mI, and Glx). Reproducibility assessment for GABA+ mapping remains challenging, with 18% of the data being rejected in at least one visit, but it yielded acceptable reproducibility in datasets that met quality control criteria in both visits (46%).

Authors

Institutions

Publication Details

Journal
NMR in Biomedicine
Published
2025-11-20
DOI
https://doi.org/10.1002/nbm.70175
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reproducibility of Metabolic Mapping Using 2D Multi‐Slice Short‐TE and GABA‐Edited Spin‐Echo MRSI at 3T in a Single Protocol

Dillip K. Senapati, Peter B. Barker, Helge J. Zöllner, Georg Oeltzschner et al.
NMR in Biomedicine
Advanced MRI Techniques and Applications
article

Reproducibility of Metabolic Mapping Using 2D Multi‐Slice Short‐TE and GABA‐Edited Spin‐Echo MRSI at 3T in a Single Protocol

Dillip K. Senapati, Peter B. Barker, Helge J. Zöllner, Georg Oeltzschner, Doris D M Lin, Kimberly L. Chan, İpek Özdemir
article en

Abstract

MRSI is a non-invasive tool for mapping metabolic distributions in multi-focal or other diseases where the location of abnormalities may be uncertain. High-concentration metabolites can be investigated at 3T using non-edited MRSI, whereas lower-concentration metabolites, such as GABA, typically require specialized editing techniques because of spectral overlap. This study reports on the reproducibility of a protocol containing both co-localized short-TE and GABA-edited multi-slice spin-echo 2D MRSI. Multi-slice, short-TE (TE 20 ms) and GABA-edited (TE 68 ms) MRSI at a nominal spatial resolution of 2.2 cm<sup>3</sup> was performed twice (7 to 14 days apart) at 3T on 11 healthy volunteers (age range 7 to 43 years). Data analysis was performed in the "Osprey" software package, including retrospective motion compensation, consensus-recommended processing, and linear-combination modeling. Metabolite estimates for six metabolites were quantified relative to total creatine (tCr) and water in 14 regions of interest. Reproducibility was assessed using intra- and inter-subject coefficients of variation. Short-TE MRSI metabolite estimates for total N-acetylaspartate (tNAA), tCr, total choline (tCho), myo-inositol (mI), and the sum of glutamate and glutamine (Glx) were found to be highly reproducible for both creatine- and water-referenced concentration estimates, with 77% of the regions of interest meeting the quality-control criteria for both visits and 96% for at least one visit. Average intra-subject CVs were 5.8% and 4.8%, and inter-subject CVs were 11.1% and 9.7% for water-referenced and tCr-referenced estimates, respectively. For GABA+ (GABA + macromolecules) estimates, 46% of the voxels of interest met quality-control criteria for both visits, and 82% for at least one visit. In the remaining datasets, the average intra-subject CVs were 13.5% for both quantification methods, and the inter-subject CVs were 13.5% and 16.9% for water-referenced and creatine-referenced estimates, respectively. 3T-MRSI sequences can achieve reproducible mapping with extended brain coverage of five major metabolites (tNAA, tCr, tCho, mI, and Glx). Reproducibility assessment for GABA+ mapping remains challenging, with 18% of the data being rejected in at least one visit, but it yielded acceptable reproducibility in datasets that met quality control criteria in both visits (46%).

NMR in BiomedicineVol. 39(1)
Kennedy Krieger Institute (US), Johns Hopkins University (US), Southwestern Medical Center (US), Advanced Imaging Research (United States) (US), The University of Texas Southwestern Medical Center (US)
Openalex Percentile: Top 50%
Advanced MRI Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.