Frontiers in Neuroscience (Oct 2015)

ICA-based artifact removal diminishes scan site differences in multi-center resting-state fMRI.

  • Rogier Alexander Feis,
  • Rogier Alexander Feis,
  • Stephen M Smith,
  • Nicola eFilippini,
  • Nicola eFilippini,
  • Gwenaëlle eDouaud,
  • Elise G P Dopper,
  • Elise G P Dopper,
  • Verena eHeise,
  • Verena eHeise,
  • Aaron J Trachtenberg,
  • John C Van Swieten,
  • Mark A Van Buchem,
  • Mark A Van Buchem,
  • Serge A R B Rombouts,
  • Serge A R B Rombouts,
  • Serge A R B Rombouts,
  • Clare E Mackay,
  • Clare E Mackay

DOI
https://doi.org/10.3389/fnins.2015.00395
Journal volume & issue
Vol. 9

Abstract

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Resting-state fMRI (R-fMRI) has shown considerable promise in providing potential biomarkers for diagnosis, prognosis and drug response across a range of diseases. Incorporating R-fMRI into multi-center studies is becoming increasingly popular, imposing technical challenges on data acquisition and analysis, as fMRI data is particularly sensitive to structured noise resulting from hardware, software and environmental differences. Here, we investigated whether a novel clean up tool for structured noise was capable of reducing center-related R-fMRI differences between healthy subjects.We analyzed 3 Tesla R-fMRI data from 72 subjects, half of whom were scanned with eyes closed in a Philips Achieva system in The Netherlands, and half of whom were scanned with eyes open in a Siemens Trio system in the UK. After pre-statistical processing and individual Independent Component Analysis (ICA), FMRIB’s ICA-based X-noiseifier (FIX) was used to remove noise components from the data. GICA and dual regression were run and non-parametric statistics were used to compare spatial maps between groups before and after applying FIX.Large significant differences were found in all resting-state networks between study sites before using FIX, most of which were reduced to non-significant after applying FIX. The between-center difference in the medial/primary visual network, presumably reflecting a between-center difference in protocol, remained statistically different.FIX helps facilitate multi-center R-fMRI research by diminishing structured noise from R-fMRI data. In doing so, it improves combination of existing data from different centers in new settings and comparison of rare diseases and risk genes for which adequate sample size remains a challenge.

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