Abstract #0046

Detecting individual variation in white matter microstructure in a high-risk infant population using deep normative modelling

Claire E Kelly^1,2,3, Peter J Anderson^1,2, Sila Genc^3,4, Thijs Dhollander³, Deanne K Thompson^2,3,5, Alice C Burnett^2,5,6,7, Lex W Doyle^2,5,6,8, and Jeanie LY Cheong^2,6,8

¹Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia, ²Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Australia, ³Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia, ⁴Neurosurgery Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children's Hospital, Melbourne, Australia, ⁵Department of Paediatrics, The University of Melbourne, Melbourne, Australia, ⁶The Royal Women’s Hospital, Melbourne, Australia, ⁷Neonatal Medicine, The Royal Children's Hospital, Melbourne, Australia, ⁸Department of Obstetrics and Gynaecology, The University of Melbourne, Melbourne, Australia

Synopsis

Keywords: Neonatal, NeuroThere is large inter-individual variation in cognitive outcomes of adults born preterm, which may relate to under-recognised heterogeneity in white matter tract microstructural disturbances. This study created a normative model of white matter tract profiles using deep learning in term-born adults (n=95). The model was then applied to detect anomalies in tract profiles of preterm adults (n=111). The location and extent of anomalies varied across preterm adults. Further, tract anomalies were correlated with neonatal brain injury and IQ. Thus, this study demonstrates inter-individual variation in white matter abnormalities in preterm adults, helping to explain variation in cognitive outcomes.

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