AI Article Synopsis

  • The study aimed to assess two post-processing techniques for analyzing MRS MEGA-PRESS data affected by motion artifacts, comparing conventional averaging to order statistic filtering (OSF) for better GABA quantification.
  • Twelve healthy participants underwent scanning multiple times, using both techniques to analyze datasets resulting from different measurement conditions, including controlled and motion-affected scans.
  • Results indicated that while OSF helped reduce the underestimation of concentrations from motion artifacts, it did not significantly improve GABA concentration estimates, rendering it as effective as averaging for low-SNR signals and potentially superior for high-SNR signals, suggesting its routine application may be beneficial.

Article Abstract

Purpose: The aim of this study was to evaluate two post-processing techniques applied to MRS MEGA-PRESS data influenced by motion-induced artifacts. In contrast to the conventional averaging technique, order statistic filtering (OSF) is a known method for artifact reduction. Therefore, this method may be suitable to incorporate in the GABA quantification.

Methods: Twelve healthy volunteers were scanned three times using a 3 T MR system. One measurement protocol consisted of two MEGA-PRESS measurements, one reference measurement and one measurement including head motions. The resulting datasets were analyzed with the standard averaging technique and with the OSF-technique in two schemes; filtering phase cycles 'RAW PC' and filtering dynamics 'RAW Dyn'.

Results: The datasets containing artifacts resulted in an underestimation of the concentrations. There was a trend for the OSF-technique to compensate for this reduction when quantifying SNR-intense signals. However, there was no indication that OSF improved the estimated GABA concentrations. Moreover, when only considering the reference measurements, the OSF technique was equally as effective as averaging, which suggests that the techniques are interchangeable.

Conclusion: OSF performed equally well as the conventional averaging technique for low-SNR signals. For high-SNR signals, OSF performed better and thus could be considered for routine usage.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5433745PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0177795PLOS

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