Early brain morphometrics from neonatal MRI predict motor and cognitive outcomes at 2-years corrected age in very preterm infants
Alex M. Pagnozzi,
Liza van Eijk,
Kerstin Pannek,
Roslyn N. Boyd,
Susmita Saha,
Joanne George,
Samudragupta Bora,
DanaKai Bradford,
Michael Fahey,
Michael Ditchfield,
Atul Malhotra,
Helen Liley,
Paul B. Colditz,
Stephen Rose,
Jurgen Fripp
Affiliations
Alex M. Pagnozzi
CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD 4029, Australia; Corresponding author.
Liza van Eijk
CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD 4029, Australia; Department of Psychology, James Cook University, Townsville, Queensland, Australia
Kerstin Pannek
CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD 4029, Australia
Roslyn N. Boyd
Child Health Research Centre, Queensland Cerebral Palsy and Rehabilitation Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
Susmita Saha
CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD 4029, Australia
Joanne George
Child Health Research Centre, Queensland Cerebral Palsy and Rehabilitation Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia; Physiotherapy Department, Queensland Children's Hospital, Children's Health Queensland Hospital and Health Service, Brisbane, Australia
Samudragupta Bora
Mothers, Babies and Women's Health Program, Mater Research Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
DanaKai Bradford
CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD 4029, Australia
Michael Fahey
Monash Health Paediatric Neurology Unit and Department of Paediatrics, School of Clinical Sciences, Monash University, Clayton, Victoria, Australia
Michael Ditchfield
Monash Imaging, Monash Health, Melbourne, Victoria, Australia; Department of Medicine, Monash University, Melbourne, Victoria, Australia
Atul Malhotra
Monash Health Paediatric Neurology Unit and Department of Paediatrics, School of Clinical Sciences, Monash University, Clayton, Victoria, Australia; Monash Newborn, Monash Children's Hospital, Melbourne, Victoria, Australia
Helen Liley
Mothers, Babies and Women's Health Program, Mater Research Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
Paul B. Colditz
Perinatal Research Centre, Faculty of Medicine, The University of Queensland Centre for Clinical Research, The University of Queensland, Brisbane, Queensland, Australia
Stephen Rose
CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD 4029, Australia
Jurgen Fripp
CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Brisbane, QLD 4029, Australia
Infants born very preterm face a range of neurodevelopmental challenges in cognitive, language, behavioural and/or motor domains. Early accurate identification of those at risk of adverse neurodevelopmental outcomes, through clinical assessment and Magnetic Resonance Imaging (MRI), enables prognostication of outcomes and the initiation of targeted early interventions. This study utilises a prospective cohort of 181 infants born <31 weeks gestation, who had 3T MRIs acquired at 29-35 weeks postmenstrual age and a comprehensive neurodevelopmental evaluation at 2 years corrected age (CA). Cognitive, language and motor outcomes were assessed using the Bayley Scales of Infant and Toddler Development – Third Edition and functional motor outcomes using the Neuro-sensory Motor Developmental Assessment. By leveraging advanced structural MRI pre-processing steps to standardise the data, and the state-of-the-art developing Human Connectome Pipeline, early MRI biomarkers of neurodevelopmental outcomes were identified. Using Least Absolute Shrinkage and Selection Operator (LASSO) regression, significant associations between brain structure on early MRIs with 2-year outcomes were obtained (r = 0.51 and 0.48 for motor and cognitive outcomes respectively) on an independent 25% of the data. Additionally, important brain biomarkers from early MRIs were identified, including cortical grey matter volumes, as well as cortical thickness and sulcal depth across the entire cortex. Adverse outcome on the Bayley-III motor and cognitive composite scores were accurately predicted, with an Area Under the Curve of 0.86 for both scores. These associations between 2-year outcomes and patient prognosis and early neonatal MRI measures demonstrate the utility of imaging prior to term equivalent age for providing earlier commencement of targeted interventions for infants born preterm.
