ArticleMagnetic resonance in medicine2019
Retrospective artifact elimination in MEGA-PRESS using a correlation approach.
Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- SMART MRS: A Simulated MEGA-PRESS ARTifacts toolbox for GABA-edited MRS.Magnetic resonance in medicine · 2025Article
- A comprehensive guide to MEGA-PRESS for GABA measurement.Analytical biochemistry · 2023Review
- MEGA-PRESS of GABA+: Influences of acquisition parameters.NMR in biomedicine · 2021Article
- Preprocessing, analysis and quantification in single-voxel magnetic resonance spectroscopy: experts' consensus recommendations.NMR in biomedicine · 2021Article
- Feasibility of Glutamate and GABA Detection in Pons and Thalamus at 3T and 7T by Proton Magnetic Resonance Spectroscopy.Frontiers in neuroscience · 2020Article
- Retrospective artifact elimination in MEGA-PRESS using a correlation approach.Magnetic resonance in medicine · 2019Article
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Authors and funding
4 authors.
Funding
Abstract
purposeTo develop a method for retrospective artifact elimination of MRS data. This retrospective method was based on an approach that combines jackknife analyses with the correlation of spectral windows, and therefore termed "JKC."
methodsTwelve healthy volunteers performed 3 separate measurement protocols using a 3T MR system. One protocol consisted of 2 cerebellar MEGA-PRESS measurements: 1 reference and 1 measurement including head movements. One-third of the artifact-influenced datasets were treated as training data for the implementation the JKC method, and the rest were used for validation.
resultsThe implemented JKC method correctly characterized most of the validation data. Additionally, after elimination of the detected artifacts, the resulting concentrations were much closer to those computed for the reference datasets. Moreover, when the JKC method was applied to the reference data, the estimated concentrations were not affected, compared with standard averaging.
conclusionThe implemented JKC method can be applied without any extra cost to MRS data, regardless of whether the dataset has been contaminated by artifacts. Furthermore, the results indicate that the JKC method could be used as a quality control of a dataset, or as an indication of whether a shift in voxel placement has occurred during the measurement.
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