## Abstract ## Purpose: To evaluate diffusion anisotropy from diffusion tensor imaging using new measures derived from Hellinger divergences and from compositional data distances. ## Materials and Methods: New anisotropy measures obtained from the diffusion tensor imaging were measured and compa
Replicability of diffusion tensor imaging measurements of fractional anisotropy and trace in brain
✍ Scribed by Adolf Pfefferbaum; Elfar Adalsteinsson; Edith V. Sullivan
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 688 KB
- Volume
- 18
- Category
- Article
- ISSN
- 1053-1807
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
Purpose
To evaluate within‐scanner and between‐scanner reliability of fractional anisotropy (FA) and trace (sum of the diagonal elements of the diffusion tensor) as measured by diffusion tensor imaging (DTI).
Materials and Methods
Ten young healthy adults were scanned on three separate days, on two different systems made by the same manufacturer. One scan was acquired at one site, and two scans were acquired on two different occasions on another scanner at another site. Three levels of analysis were used to compare the DTI metrics: 1) a voxel‐by‐voxel analysis of all supratentorial brain (gray matter + white matter + cerebrospinal fluid) and of supratentorial white matter; 2) a slice‐by‐slice analysis of supratentorial white matter; and 3) a single‐region analysis of the corpus callosum.
Results
The voxel‐by‐voxel analysis of all supratentorial brain found that FA and trace measures and correlations were equivalently and significantly higher within than across scanners. For supratentorial white matter, FA was similar within and across scanners, whereas trace demonstrated across‐scanner bias. A similar pattern was observed for the slice‐by‐slice comparison. For the single‐region analysis of the corpus callosum, within‐scanner FA and trace measures were highly reproducible for FA (CV = 1.9%) and trace (CV = 2.6%), but both DTI measures showed a systematic mean bias across scanners (CV = 4.5% for FA and CV = 7.5% for trace).
Conclusion
These estimates of measurement variation and scanner bias can be used to predict effect sizes for longitudinal and multisite studies using diffusion tensor imaging. J. Magn. Reson. Imaging 2003;18:427–433. © 2003 Wiley‐Liss, Inc.
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