How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study

Dae Jin Kim; Hae Jeong Park; Kyung Whun Kang; Yong Wook Shin; Jae Jin Kim; Won Jin Moon; Eun Chul Chung; In Young Kim; Jun Soo Kwon; Sun I. Kim

doi:10.1016/j.mri.2006.07.014

How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study

Dae Jin Kim, Hae Jeong Park, Kyung Whun Kang, Yong Wook Shin, Jae Jin Kim, Won Jin Moon, Eun Chul Chung, In Young Kim, Jun Soo Kwon, Sun I. Kim

Department of Psychiatry

Research output: Contribution to journal › Article › peer-review

26 Citations (Scopus)

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 11 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.

Original language	English
Pages (from-to)	1369-1376
Number of pages	8
Journal	Magnetic Resonance Imaging
Volume	24
Issue number	10
DOIs	https://doi.org/10.1016/j.mri.2006.07.014
Publication status	Published - 2006 Dec

Bibliographical note

Funding Information:
This work was supported by grant no. R01-2002-000-00362-0-2004 (JSK) and no. R01-2005-000-10522-0-2006 (HJP) from the Basic Research Program of the Korea Science & Engineering Foundation.

All Science Journal Classification (ASJC) codes

Biophysics
Biomedical Engineering
Radiology Nuclear Medicine and imaging

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10.1016/j.mri.2006.07.014

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title = "How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study",

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 (Ef), mean dispersion index (MDI), mean fractional anisotropy (MFA) and mean variance (MV) within 11 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 Ef (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.",

author = "Kim, {Dae Jin} and Park, {Hae Jeong} and Kang, {Kyung Whun} and Shin, {Yong Wook} and Kim, {Jae Jin} and Moon, {Won Jin} and Chung, {Eun Chul} and Kim, {In Young} and Kwon, {Jun Soo} and Kim, {Sun I.}",

note = "Funding Information: This work was supported by grant no. R01-2002-000-00362-0-2004 (JSK) and no. R01-2005-000-10522-0-2006 (HJP) from the Basic Research Program of the Korea Science & Engineering Foundation.",

year = "2006",

month = dec,

doi = "10.1016/j.mri.2006.07.014",

language = "English",

volume = "24",

pages = "1369--1376",

journal = "Magnetic Resonance Imaging",

issn = "0730-725X",

publisher = "Elsevier Inc.",

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T1 - How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study

AU - Kim, Dae Jin

AU - Park, Hae Jeong

AU - Kang, Kyung Whun

AU - Shin, Yong Wook

AU - Kim, Jae Jin

AU - Moon, Won Jin

AU - Chung, Eun Chul

AU - Kim, In Young

AU - Kwon, Jun Soo

AU - Kim, Sun I.

N1 - Funding Information: This work was supported by grant no. R01-2002-000-00362-0-2004 (JSK) and no. R01-2005-000-10522-0-2006 (HJP) from the Basic Research Program of the Korea Science & Engineering Foundation.

PY - 2006/12

Y1 - 2006/12

N2 - 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 (Ef), mean dispersion index (MDI), mean fractional anisotropy (MFA) and mean variance (MV) within 11 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 Ef (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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How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study

Abstract

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