Enhancing Neurocognitive Outcome Prediction in Congenital Heart Disease Patients: The Role of Brain Age Biomarkers and Beyond

ABSTRACT This paper aimed to investigate the predictive power of combining demographic, socioeconomic, and genetic factors with a brain MRI-based quantified measure of accelerated brain aging (referred to as deltaAGE ) for neurocognitive outcomes in adolescents and young adults with Congenital Heart Disease (CHD). Our hypothesis posited that including the brain age biomarker ( deltaAGE ) would enhance neurocognitive outcome predictions compared to models excluding it. We conducted comprehensive analyses, including leave-one-subject-out and leave-one-group-out cross-validation techniques. Our results demonstrated that the inclusion of deltaAGE consistently improved prediction performance when considering the Pearson correlation coefficient, a preferable metric for this study. Notably, the deltaAGE -augmented models consistently outperformed those without deltaAGE across all cross-validation setups, and these correlations were statistically significant ( p -value < 0.05). Therefore, our hypothesis that incorporating the brain-age biomarker alongside demographic, socioeconomic, and genetic factors enhances neurocognitive outcome predictions in adolescents and young adults with CHD is supported by the findings.