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Lookup NU author(s): Dr Benjamin Aribisala,
Professor Andrew BlamireORCiD
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Purpose: To compare the robustness of region of interest (ROI) analysis of magnetic resonance imaging (MRI) brain data in real space with analysis in standard space and to test the hypothesis that standard space image analysis introduces more partial volume effect errors compared to analysis of the same dataset in real space. Materials and Methods: Twenty healthy adults with no history or evidence of neurological diseases were recruited; high-resolution T-1-weighted, quantitative T-1, and B-O field-map measurements were collected. Algorithms were implemented to perform analysis in real and standard space and used to apply a simple standard ROI template to quantitative T-1 datasets. Regional relaxation values and histograms for both gray and white matter tissues classes were then extracted and compared. Results: Regional mean T-1 values for both gray and white matter were significantly lower using real space compared to standard space analysis. Additionally, regional T-1 histograms were more compact in real space, with smaller right-sided tails indicating lower partial volume errors compared to standard space analysis. Conclusion: Standard space analysis of quantitative MRI brain data introduces more partial volume effect errors biasing the analysis of quantitative data compared to analysis of the same dataset in real space.
Author(s): Aribisala BS, He JB, Blamire AM
Publication type: Article
Publication status: Published
Journal: Journal of Magnetic Resonance Imaging
Print publication date: 17/05/2011
ISSN (print): 1053-1807
ISSN (electronic): 1522-2586
Publisher: John Wiley & Sons, Inc.
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