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Abstract #1021

Digital Probabilistic and Principal Component Analysis of Hypoxic-Ischemic Brain Injury

Jian Chen1, Shaloos Singhal2, 3, Henry Ma3, John Ly3, Thanh G. Phan2, 3

1Department of Medicine, Monash University , Melbourne, VIC, Australia; 2Department of Medicine, Monash University, Melbourne, VIC, Australia; 3Stroke Unit, Monash Medical Centre, Melbourne, VIC, Australia

The regions at risk of ischemic injury following cardiorespiratory arrest have not been systematically analysed. In present study we use the digital probabilistic method and principal component analysis to study topography of ischemic injury following cardiorespiratory arrest. In the probabilistic atlas , the highest frequency of ischemic injury was caudo-putamen (0.250), temporal lobes (0.0175), occipital (0.0150) and hippocampus (0.125). The first component showed covariance between the deep gray matter nuclei and posterior cortical structures . The two different methods show similarity in their emphasis on the deep gray matter nuclei and the posterior cortical structures.

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Keywords

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