Image distortion correction in fMRI: A quantitative evaluation.
A well-recognized problem with the echo-planar imaging (EPI) technique most commonly used for functional magnetic resonance imaging (fMRI) studies is geometric distortion caused by magnetic field inhomogeneity. This makes it difficult to achieve an accurate registration between a functional activation map calculated from an EPI time series and an undistorted, high resolution anatomical image. A correction method based on mapping the spatial distribution of field inhomogeneities can be used to reduce these distortions. This approach is attractive in its simplicity but requires postprocessing to improve the robustness of the acquired field map and reduce any secondary artifacts. Furthermore, the distribution of the internal magnetic field throughout the head is position dependent resulting in an interaction between distortion and head motion. Therefore, a single field map may not be sufficient to correct for the distortions throughout a whole fMRI time series. In this paper we present a quantitative evaluation of image distortion correction for fMRI at 2T. We assess (i) methods for the acquisition and calculation of field maps, (ii) the effect of image distortion correction on the coregistration between anatomical and functional images, and (iii) the interaction between distortion and head motion, assessing the feasibility of using field maps to reduce this effect. We propose that field maps with acceptable noise levels can be generated easily using a dual echo-time EPI sequence and demonstrate the importance of distortion correction for anatomical coregistration, even for small distortions. Using a dual echo-time series to generate a unique field map at each time point, we characterize the interaction between head motion and geometric distortion. However, we suggest that the variance between successively measured field maps introduces additional unwanted variance in the voxel time-series and is therefore not adequate to correct for time-varying distortions.
Hutton
Chloe
C
Wellcome Department of Cognitive Neurology, Institute of Neurology, London WCIN 3BG, United Kingdom.
Bork
Andreas
A
Josephs
Oliver
O
Deichmann
Ralf
R
Ashburner
John
J
Turner
Robert
R
D000465:Algorithms; D016477:Artifacts; D001931:Brain Mapping; D017352:Echo-Planar Imaging; D019416:Head Movements / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical