Evaluating multicenter DTI data in Huntington's disease on site specific effects : an ex post facto approach
Abstract
Purpose: Assessment of the feasibility to average diffusion tensor imaging (DTI) metrics of MRI data acquired in the course of a multicenter study. Materials and methods: Sixty-one early stage Huntington's disease patients and forty healthy controls were studied using four different MR scanners at four European sites with acquisition protocols as close as possible to a given standard protocol. The potential and feasibility of averaging data acquired at different sites was evaluated quantitatively by region-of-interest (ROI) based statistical comparisons of coefficients of variation (CV) across centers, as well as by testing for significant group-by-center differences on averaged fractional anisotropy (FA) values between patients and controls. In addition, a whole-brain based statistical between-group comparison was performed using FA maps. Results: The ex post facto statistical evaluation of CV and FA-values in a priori defined ROIs showed no differences between sites above chance indicating that data were not systematically biased by center specific factors. Conclusion: Averaging FA-maps from DTI data acquired at different study sites and different MR scanner types does not appear to be systematically biased. A suitable recipe for testing on the possibility to pool multicenter DTI data is provided to permit averaging of DTI-derived metrics to differentiate patients from healthy controls at a larger scale.
Citation
Müller , H-P , Grön , G , Sprengelmeyer , R , Kassubek , J , Ludolph , A C , Hobbs , N , Cole , J , Roos , R A C , Duerr , A , Tabrizi , S J , Landwehrmeyer , G B & Süssmuth , S D 2013 , ' Evaluating multicenter DTI data in Huntington's disease on site specific effects : an ex post facto approach ' , Neuroimage: Clinical , vol. 2 , pp. 161-167 . https://doi.org/10.1016/j.nicl.2012.12.005
Publication
Neuroimage: Clinical
Status
Peer reviewed
Type
Journal article
Rights
© 2013 The Authors. Published by Elsevier Inc. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.
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