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Abstract #2585

Automated detection of brain regions associated with post-stroke depression: A hypothesis

Jhimli Mitra 1 , Jurgen Fripp 1 , Kaikai Shen 1 , Kerstin Pannek 1 , Pierrick Bourgeat 1 , Olivier Salvado 1 , Bruce Campbell 2 , Susan Palmer 3 , Leeanne Carey 3 , and Stephen Rose 1

1 The Australian e-Health Research Centre, CSIRO Computational Informatics, CSIRO Preventative-Health Flagship, Herston, QLD, Australia, 2 Department of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, Parkville, VIC, Australia, 3 The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia

Our hypothesis is that loss-in-connectivity in brain regions post-stroke is correlated with post-stroke depression (PSD). We propose an automated detection of cortical/sub-cortical regions that are associated with PSD. The method involves pairwise comparison of network connectivity matrices between normal and stroke patients using diffusion tractography and network based statistics to identify the networks affected by ischemic stroke. Then a groupwise linear regression analysis is performed between the loss-in-connectivity in each brain region and the respective patients' depression scores at 3 month post-stroke stage. The results revealed positive correlations between loss-in-connectivity and PSD in some brain regions including the thalamus.

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