Diffusion tensor imaging of early relapsing-remitting multiple sclerosis with histogram analysis using automated segmentation and brain volume correction

Abstract

Diffusion tensor magnetic resonance imaging (DTI) reveals measurable abnormalities in normal-appear ing brain tissue (NA BT) in established multiple sclerosis (MS). However, it is unclear how early this occurs. Recent studies have employed whole brain histogram analysis to improve sensitivity, but concern exists regarding reliability of tissue/cerebrospinal fluid segmentation and possible intersubject brain volume differences, which can introduce partial volume error. To address this, 28 early relapsing-remitting MS subjects [median disease duration 1.6 years; median Expanded Disability Status Scale (EDSS) score 1.5] and 20 controls were compared with whole brain histogram analysis using an automated segmentation algorithm to improve reproducibility. Brain parenchymal volumes (BPV) were estimated for each subject in the analysis. The mean, peak height and peak location were calculated for DTI parameters [fractional anisotropy (FA), mean diffusivity and volume ratio]. A n increased FA peak height in MS subject NA BT was observed (P =0.02) accounting for age, gender and BPV. Removing BPV revealed additional abnormalities in NABT. The main conclusions are i) FA peak height is increased in NA BT in early MS, ii) partial volume edge effects may contribute to apparent NA BT histogram abnormalities, and iii) correction for brain volume differences should reduce potential partial volume edge effects.

Keywords

brain volume diffusion fractional anisotropy histograms MRI multiple sclerosis segmentation

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