Distribution characteristics, reproducibility, and precision of region of interest-based hippocampal diffusion tensor imaging measures
- PMID: 16484426
- PMCID: PMC8148767
Distribution characteristics, reproducibility, and precision of region of interest-based hippocampal diffusion tensor imaging measures
Abstract
Background and purpose: For adequate interpretation of diffusion tensor imaging (DTI) parameters empirical distribution characteristics, precision, and reproducibility should be known. The present study investigated distribution and reliability parameters of hippocampal fractional anisotropy (FA) and mean diffusivity (MD).
Methods: FA and MD values were averaged in hippocampal regions of interest in 20 subjects (10 women and 10 men; age range, 25-69 years). Regions of interest were manually placed bilaterally by one investigator at 2 occasions, and by a second independent investigator. Sample distributions of FA and MD values were compared with normal distributions. Intraclass coefficients (ICCs), standard errors of measurement (SEMs), and coefficients of variation (CVs) with confidence intervals (CI95s) were computed.
Results: The results did not show any deviation of averaged FA (0.237 +/- 0.017) and MD (775 +/- 28 microm2/s) values from normal distribution. Intraobserver reliability (ICC > or = 0.90) and precision (CV < or = 3.5%) were high for all measures. Interobserver reliability reached values of ICC > or = 0.84 and CV < or = 4.1%. FA yielded lower precision (CV 2.2-4.1%) than MD (CV 1.3-2.5%), CI95s were around +/-0.015-0.020 and +/-25-30 microm2/s for FA and MD, respectively. FA differences of 0.020-0.030 and MD differences of 40-50 microm2/s can be assumed to reflect reliably distinct values in hippocampal regions.
Conclusion: The results are in line with previous reports on reliability of DTI measures by using different designs and methodology. Notwithstanding the difficulties associated with region of interest-derived DTI measurements in hippocampal regions, the present approach provides estimates of distribution characteristics and precision applicable to routine assessments of DTI parameters in clinical and research context.
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References
-
- Ramnani N, Behrens TE, Penny W, et al. New approaches for exploring anatomical and functional connectivity in the human brain. Biol Psychiatry 2004;56:613–19 - PubMed
-
- Loevner LA, Grossman RI, Cohen JA, et al. Microscopic disease in normal-appearing white matter on conventional MR images in patients with multiple sclerosis: assessment with magnetization-transfer measurements. Radiology 1995;96:511–15 - PubMed
-
- Tortorella C, Viti B, Bozzali M. A magnetization transfer histogram study of normal-appearing brain tissue in MS. Neurology 2000;54:186–93 - PubMed
-
- Fellgiebel A, Wille P, Müller MJ, et al. Ultrastructural hippocampal and white matter alterations in mild cognitive impairment: a diffusion tensor imaging study. Dement Geriatr Cogn Disord 2004;18:101–08 - PubMed
-
- Basser PJ, Pajevic S. A normal distribution for tensor-valued random variables: applications to diffusion tensor MRI. IEEE Trans Med Imaging 2003;22:785–94 - PubMed
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