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Abstract #0852

Structural Covariance Network Analysis Reveals Altered Brain Development in Neonates with Congenital Heart Disease After Surgery

Mirthe E. M. van der Meijden1, Barat Gal-Er1, Daniel Cromb1, Sîan Wilson1,2,3, Andrew Chew1, Alexia Egloff1, Kuberan Pushparajah4,5, John Simpson4,6, Joseph V. Hajnal1,7, A. David Edwards1, Mary Rutherford1, Jonathan O’Muircheartaigh1,8, Alexandra F. Bonthrone 1, and Serena J. Counsell1
1Early Life Imaging Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2Division of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States, 3Department of Pediatrics, Harvard Medical School, Boston, MA, United States, 4Department of Cardiovascular Imaging, King's College London, London, United Kingdom, 5Department of Fetal and Paediatric Cardiology, Evelina London Children’s Hospital, London, United Kingdom, 6Department of Fetal and Paediatric Cardiology, Evelina Children's Hospital, London, United Kingdom, 7Imaging Physics & Engineering Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 8Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, King's College London, London, United Kingdom

Synopsis

Keywords: Neuro, Neonatal, Congenital Heart Disease, Structural Covariance Network

Motivation: Early identification of altered neurodevelopment in neonates with congenital heart disease (CHD) is crucial for improving long-term outcomes. Structural covariance network (SCN) analysis is a data-driven approach to identify regions of synchronously developing structural organization.

Goal(s): To identify SCNs that differ between neonates with CHD after cardiac surgery and healthy controls.

Approach: Jacobian determinants were calculated using warps from non-linear registration and input into an Independent Component Analysis to identify SCNs.

Results: Out of forty identified SCNs, twelve showed significant differences between neonates with CHD and controls, involving extracerebral CSF, white matter, and cortical- and deep grey matter.

Impact: Structural covariance network analysis, a data-driven approach to characterise networks of simultaneously developing brain regions, identified 12 networks that were significantly different in neonates with CHD after cardiac surgery compared to healthy neonates, highlighting altered brain development in this population.

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