Evaluating multicenter DTI data in Huntington's disease on site specific effects: an ex post facto approach

Hans-Peter Müller, Georg Grön, Reiner Sprengelmeyer, Jan Kassubek, Albert C. Ludolph, Nicola Hobbs, James Cole, Raymund A.C. Roos, Alexandra Duerr, Sarah J. Tabrizi, G. Bernhard Landwehrmeyer, Sigurd D. Süssmuth

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)161-167
Number of pages7
JournalNeuroimage: Clinical
Volume2
Early online date3 Jan 2013
DOIs
Publication statusPublished - 2013

Keywords

  • Multicenter study
  • Diffusion tensor imaging
  • Fractional anisotropy
  • Huntington's disease

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