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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