How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study
- Authors
- Kim, Dae-Jin; Park, Hae-Jeong; Kang, Kyung-Whun; Shin, Yong-Wook; Kim, Jae-Jin; Moon, Won-Jin; Chung, Eun-Chul; Kim, In Young; Kwon, Jun Soo; Kim, Sun I.
- Issue Date
- Dec-2006
- Publisher
- ELSEVIER SCIENCE INC
- Keywords
- diffusion tensor imaging; distortion correction; image registration; evaluation
- Citation
- MAGNETIC RESONANCE IMAGING, v.24, no.10, pp.1369 - 1376
- Indexed
- SCIE
SCOPUS
- Journal Title
- MAGNETIC RESONANCE IMAGING
- Volume
- 24
- Number
- 10
- Start Page
- 1369
- End Page
- 1376
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/180665
- DOI
- 10.1016/j.mri.2006.07.014
- ISSN
- 0730-725X
- Abstract
- Purpose: The purpose of this study was to determine a suitable registration algorithm for diffusion tensor imaging (DTI) using conventional preprocessing tools [statistical parametric mapping (SPM) and automated image registration (AIR)] and to investigate how anisotropic indices for clinical assessments are affected by these distortion corrections. Materials and Methods: Brain DTI data from 15 normal healthy volunteers were used to evaluate four spatial registration schemes within subjects to correct image distortions: noncorrection, SPM-based affine registration, AIR-based affine registration and AIR-based nonlinear polynomial warping. The performance of each distortion correction was assessed using: (a) quantitative parameters: tensor-fitting error (E-f), mean dispersion index (MDI), mean fractional anisotropy (MFA) and mean variance (MV) within I I regions of interest (ROI) defined from homogeneous fiber bundles; and (b) fiber tractography through the uncinate fasciculus and the corpus callosum. Fractional anisotropy (FA) and mean diffusivity (MD) were calculated to demonstrate the effects of distortion correction. Repeated-measures analysis of variance was used to investigate differences among the four registration paradigms. Results: AIR-based nonlinear registration showed the best performance for reducing image distortions with respect to smaller E-f (P <.02), MDI (P <.01) and MV (P <.01) with larger MFA (P <.01). FA was decreased to correct distortions (P <.0001) whether the applied registration was linear or nonlinear and was lowest after nonlinear correction (P <.001). No significant differences were found in MD. Conclusion: In conventional DTI processing, anisotropic indices of FA can be misestimated by noncorrection or inappropriate distortion correction, which leads to an erroneous increase in FA. AIR-based nonlinear distortion correction would be required for a more accurate measurement of this diffusion parameter.
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