Improved Precision in the Measurement of Longitudinal Global and Regional Volumetric Changes via a Novel MRI Gradient Distortion Characterization and Correction Technique
Reducing measurement variability in MRI-based morphometric analysis of human brain structures will increase statistical power to detect changes between groups and longitudinally over time in individual subjects. One source of measurement error in anatomical MR is magnetic field gradient-induced geometric distortion. This work proposes a method to characterize and compensate for these distortions using a novel image processing technique relying on the image acquisition of a phantom with known geometrical dimensions, without the need to acquire the magnetic field mapping. The method is not specific to any particular shape of the phantom, as long as it provides enough coverage of the volume of interest and enough structure to densely sample the distortion field. The distortions are expressed in terms of spherical harmonic functions, which are then used to define the distortion correction field for the volume of interest. Accuracy of the distortion measurement was evaluated using numerical simulation and reproducibility was estimated using multiple scans of the phantom in the same scanner. Finally, scan-rescan experiments with nine healthy subjects demonstrated that 90% of the distortion (in terms of local volume change) can be corrected with this technique.
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