Poster Presentation Australian & New Zealand Society of Magnetic Resonance Conference 2017

Whole brain diffusion analysis of insomnia disorder subtypes (#100)

Michael A Green 1 2 , Christopher B Miller 3 4 , Delwyn J Bartlett 3 4 , Ronald R Grunstein 2 3 5 , Caroline D Rae 1 2
  1. Neuroscience Research Australia, Sydney, NSW, Australia
  2. School of Medical Sciences, The University of New South Wales, Sydney, Australia
  3. Woolcock Institute of Medical Research, CIRUS, Centre for Sleep and Chronobiology, Sydney, NSW, Australia
  4. Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
  5. Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, Sydney, NSW, Australia

Insomnia is the most common sleep disorder (1) and has been associated with daytime fatigue, mood disorder, and cognitive impairments which affect daily function and quality of life (2,3). A recent study has proposed to subtypes of insomnia based on total sleep time, one of which - short sleep duration insomnia is thought to be more biologically severe.

Despite the development of neuroimaging and analysis techniques, there are differences in the diffusion measurements across studies, which may be obscured by including insomnia patients of varying severity. Here we proposed to acquire MR diffusion images to examine the white matter density and morphology in the two proposed insomnia subtypes

Insomnia and control participants were scanned with on a Philips 3T Achieva MRI system using a 32 channel head coil to acquire high resolution T1-weighted images (TR/TE = 6/2.7ms, 200 coronal slices, voxel size = 1mm3) and high angular resolution diffusion imaging (HARDI) data sets (b=2400 s/mm2, voxel size = 2.5mm3, 61 diffusion gradients).

Diffusion imaging data were processed using a fixel-based analysis method (4) in MRTrix to quantify apparent fibre density and cross-sectional information to compare with controls and the two insomnia subtypes, and to perform fixel-wise correlations with other global measures. Diffusion data was also processed with tbss for comparison with previous studies.

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  2. Ohayon MM. Epidemiology of insomnia: what we know and what we stillneed to learn.Sleep Med Rev2002;6:97e111
  3. Bonnet MH, Arand DL. Hyperarousal and insomnia: state of the science. Sleep medicine reviews 2010;14:9-15
  4. Vgontzas AN, Fernandez-Mendoza J, Liao D, Bixler EO. Insomnia with objective short sleep duration: the most biologically severe phenotype of the disorder. Sleep medicine reviews 2013;17:241-54
  5. Raffelt, D. A. et al. Investigating white matter fibre density and morphology using fixel-based analysis, Neuroimage. 2017 Jan 1;144(Pt A):58-73