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How does motion affect GABA-measurements? Order statistic filtering compared to conventional analysis of MEGA-PRESS MRS
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-7809-2481
Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0001-8661-2232
2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 5, e0177795Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Public Library of Science , 2017. Vol. 12, no 5, e0177795
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-138250DOI: 10.1371/journal.pone.0177795ISI: 000401485500071PubMedID: 28520793ScopusID: 2-s2.0-85019539851OAI: oai:DiVA.org:liu-138250DiVA: diva2:1109374
Note

Funding Agencies|Knut and Alice Wallenberg Foundation [KAW 2013.0076]; NIH [P41 015909, R01 016089]

Available from: 2017-06-14 Created: 2017-06-14 Last updated: 2017-06-22Bibliographically approved

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Tapper, SofieTisell, AndersLundberg, Peter
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Division of Radiological SciencesFaculty of Medicine and Health SciencesCenter for Medical Image Science and Visualization (CMIV)Department of Medical and Health SciencesDepartment of Radiation Physics
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Signal Processing

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