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Abstract #3371

QUIQI – using a QUality Index for the analysis of Quantitative Imaging data

Giulia Di Domenicantonio1, Nadège Corbin2, John Ashburner2, Martina Callaghan2, and Antoine Lutti1
1Department for Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, 2Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, UCL, London, London, United Kingdom

Image degradation due to head motion is ubiquitous in MRI, reduces sensitivity, hinders clinical diagnosis and increases the risk of spurious findings. The few existing objective measures of degradation are often used sub-optimally, to remove the most degraded datasets from analysis. Using a large dataset (N~1400) we show how to incorporate an validated index of degradation into the analysis of group studies. The benefit is demonstrated for the case of healthy age-related difference in brain relaxometry data using the SPM software. However, the proposed framework is flexible with broad potential, including the analysis of other metrics and body regions.

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