• Rezwan Ghassemi, Robert Brown, Sridar Narayanan, Brenda Banwell, Kunio Nakamura, and Douglas L Arnold.
• Montreal Neurological Institute, McGill University, 3801 rue University, Montreal, QC, Canada, H3A 2B4.
• J Neuroimaging. 2015 Mar 1;25(2):184-90.

BackgroundIntensity variation between magnetic resonance images (MRI) hinders comparison of tissue intensity distributions in multicenter MRI studies of brain diseases. The available intensity normalization techniques generally work well in healthy subjects but not in the presence of pathologies that affect tissue intensity. One such disease is multiple sclerosis (MS), which is associated with lesions that prominently affect white matter (WM).ObjectiveTo develop a T1-weighted (T1w) image intensity normalization method that is independent of WM intensity, and to quantitatively evaluate its performance.Methods And SubjectsWe calculated median intensity of grey matter and intraconal orbital fat on T1w images. Using these two reference tissue intensities we calculated a linear normalization function and applied this to the T1w images to produce normalized T1w (NT1) images. We assessed performance of our normalization method for interscanner, interprotocol, and longitudinal normalization variability, and calculated the utility of the normalization method for lesion analyses in clinical trials.ResultsStatistical modeling showed marked decreases in T1w intensity differences after normalization (P < .0001).ConclusionsWe developed a WM-independent T1w MRI normalization method and tested its performance. This method is suitable for longitudinal multicenter clinical studies for the assessment of the recovery or progression of disease affecting WM.Copyright © 2014 by the American Society of Neuroimaging.

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