Correction of eddy-current distortions in diffusion tensor images using the known directions and strengths of diffusion gradients - PubMed (original) (raw)

Correction of eddy-current distortions in diffusion tensor images using the known directions and strengths of diffusion gradients

Jiancheng Zhuang et al. J Magn Reson Imaging. 2006 Nov.

Abstract

Purpose: To correct eddy-current artifacts in diffusion tensor (DT) images without the need to obtain auxiliary scans for the sole purpose of correction.

Materials and methods: DT images are susceptible to distortions caused by eddy currents induced by large diffusion gradients. We propose a new postacquisition correction algorithm that does not require any auxiliary reference scans. It also avoids the problematic procedure of cross-correlating images with significantly different contrasts. A linear model is used to describe the dependence of distortion parameters (translation, scaling, and shear) on the diffusion gradients. The model is solved numerically to provide an individual correction for every diffusion-weighted (DW) image.

Results: The assumptions of the linear model were successfully verified in a series of experiments on a silicon oil phantom. The correction obtained for this phantom was compared with correction obtained by a previously published method. The algorithm was then shown to markedly reduce eddy-current distortions in DT images from human subjects.

Conclusion: The proposed algorithm can accurately correct eddy-current artifacts in DT images. Its principal advantages are that only images with comparable signals and contrasts are cross-correlated, and no additional scans are required.

Copyright (c) 2006 Wiley-Liss, Inc.

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Figures

Figure 1

Figure 1

The parameters for each component of eddy-current distortion at slices 1, 18, and 35 vary linearly with the changed component of the diffusion gradients (presented in b-value on the top x-axis, and in gradient strength on the bottom x-axis), as described in experiment 2 and schemes Bx, By, and Bz of Table 1.

Figure 2

Figure 2

In experiment 3, the three components of distortion (shear, scaling, and translation) calculated by the proposed modeling algorithm (dashed lines) agree well with the distortions measured by Haselgrove and Moore’s (8) method (solid lines) on the experimental phantom data at slices 1, 18, and 35.

Figure 3

Figure 3

Representative DT maps constructed with and without prior application of the proposed algorithm at slice 18. a: The uncorrected tensor eigenvector map. b: The corrected tensor eigenvector map. The color bar at the bottom left is the color-coding scheme indicating the direction of the eigenvectors. The white arrows point to regions of significant improvement in the map. c: An FA map after distortion correction. The white contours outline the uncorrected FA map. The arrow indicates one obvious difference between the corrected and uncorrected maps.

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