Background Corrupted gradient directions (GD) in diffusion weighted images may seriously affect reliability of diffusion tensor imaging (DTI)-based comparisons at the group level. In the present study a quality control (QC) algorithm1was employed to eliminate corrupted GD from DTI data. Effects of this procedure on comparisons between Huntington disease (HD) subjects and controls were assessed at the group level.
Methods Sixty-one HD patients in early stages and forty matched healthy controls were studied in a longitudinal design (baseline and two follow-ups at three time points over 15 months), in a multicenter setting with standardised acquisition protocols on four different MR scanners at four European study sites2. QC was used to identify corrupted GD in DTI data sets. Differences in fractional anisotropy (FA) maps at the group level with and without elimination of corrupted GD were analysed.
Results The elimination of corrupted GD had an impact on individual FA maps as well as on cross-sectional group comparisons between HD subjects and controls. Following application of the QC algorithm, a lower number of small clusters of FA changes were observed, compared with the analysis without QC-based elimination. However, the grosso modo pattern of regional reductions and increases in FA values was unchanged.
Conclusion An impact on the result patterns of the comparison of FA maps between HD subjects and controls was observed depending on whether QC-based elimination of corrupted GD was performed. QC-based elimination of corrupted GD in DTI scans reduces the risk of type I and type II errors in cross-sectional group comparison of FA maps contributing to an increase in reliability and stability of group comparisons.
Acknowledgment This work was supported by the European Union under the Seventh Framework programme – PADDINGTON Project, Grant Agreement No. 261358, and the European Huntington’s Disease Network (EHDN), project 070 – PADDINGTON.
Müller HP, et al. PLoS Curr2011, RRN1232
Müller HP, et al. Neuroimage Clinical2013,2:161–167
- diffusion tensor imaging
- quality control
- fractional anisotropy