Abstract
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 T1-weighted, quantitative T1, and B0 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 T1 datasets. Regional relaxation values and histograms for both gray and white matter tissues classes were then extracted and compared.
Results:
Regional mean T1 values for both gray and white matter were significantly lower using real space compared to standard space analysis. Additionally, regional T1 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. J. Magn. Reson. Imaging 2011;33:1503–1509. © 2011 Wiley-Liss, Inc.
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 T1-weighted, quantitative T1, and B0 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 T1 datasets. Regional relaxation values and histograms for both gray and white matter tissues classes were then extracted and compared.
Results:
Regional mean T1 values for both gray and white matter were significantly lower using real space compared to standard space analysis. Additionally, regional T1 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. J. Magn. Reson. Imaging 2011;33:1503–1509. © 2011 Wiley-Liss, Inc.
| Original language | English |
|---|---|
| Pages (from-to) | 1503-1509 |
| Number of pages | 7 |
| Journal | Journal of Magnetic Resonance Imaging |
| Volume | 33 |
| Issue number | 6 |
| Early online date | 17 May 2011 |
| DOIs | |
| Publication status | Published - Jun 2011 |
Bibliographical note
Copyright © 2011 Wiley-Liss, Inc.Keywords
- automatic regional analysis
- real space
- standard space
- partial volume effects