Effects of gradient non-linearity correction and intensity non-uniformity correction in longitudinal studies using structural image evaluation using normalization of atrophy (SIENA)
✍ Scribed by Hidemasa Takao; Osamu Abe; Naoto Hayashi; Hiroyuki Kabasawa; Kuni Ohtomo
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 132 KB
- Volume
- 32
- Category
- Article
- ISSN
- 1053-1807
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✦ Synopsis
Abstract
Purpose:
To evaluate the effects of gradient nonlinearity correction and intensity nonuniformity correction on longitudinal (two‐year) changes in global and regional brain volumes.
Materials and Methods:
A total of 208 subjects (70 females and 138 males, age range = 38.1–83.0 years) were included in this study. Each subject was scanned twice, at an interval of approximately two years (range = 1.5–2.3 years). Three‐dimensional fast spoiled‐gradient recalled acquisition in the steady state (3D‐FSPGR) images corrected for gradient nonlinearity and/or intensity nonuniformity were compared with uncorrected 3D‐FSPGR images with use of structural image evaluation using normalization of atrophy 2.6 (SIENA).
Results:
The mean absolute deviations of percentage brain volume change (PBVC) values in the gradient nonlinearity ± intensity nonuniformity corrected images were significantly less than that in the uncorrected images, and the difference in the mean absolute deviation of PBVC was the most significant between the uncorrected images and the images corrected for both gradient nonlinearity and intensity nonuniformity. Voxel‐wise comparisons showed large significant differences between the uncorrected images and the corrected images.
Conclusion:
Correction for gradient nonlinearity and intensity nonuniformity reduces the variance of measured longitudinal changes in brain volumes and will improve accuracy for detecting subtle brain changes. J. Magn. Reson. Imaging 2010;32:489–492. © 2010 Wiley‐Liss, Inc.