Cerebral Magnetic Resonance Biomarkers in Neonatal Encephalopathy: a Meta-analysis

Objective: Accurate prediction of neurodevelopmental outcome in neonatal encephalopathy (NE) is important for clinical management and to evaluate neuroprotective therapies. We undertook a meta-analysis of the prognostic accuracy of cerebral magnetic resonance (MR) biomarkers in infants with neonatal encephalopathy.

Methods: We reviewed all studies that compared an MR biomarker performed during the neonatal period with neurodevelopmental outcome at > or =1 year. We followed standard methods recommended by the Cochrane Diagnostic Accuracy Method group and used a random-effects model for meta-analysis. Summary receiver operating characteristic curves and forest plots of each MR biomarker were calculated. chi(2) tests examined heterogeneity.

Results: Thirty-two studies (860 infants with NE) were included in the meta-analysis. For predicting adverse outcome, conventional MRI during the neonatal period (days 1-30) had a pooled sensitivity of 91% (95% confidence interval [CI]: 87%-94%) and specificity of 51% (95% CI: 45%-58%). Late MRI (days 8-30) had higher sensitivity but lower specificity than early MRI (days 1-7). Proton MR spectroscopy deep gray matter lactate/N-acetyl aspartate (Lac/NAA) peak-area ratio (days 1-30) had 82% overall pooled sensitivity (95% CI: 74%-89%) and 95% specificity (95% CI: 88%-99%). On common study analysis, Lac/NAA had better diagnostic accuracy than conventional MRI performed at any time during neonatal period. The discriminatory powers of the posterior limb of internal capsule sign and brain-water apparent diffusion coefficient were poor.

Conclusions: Deep gray matter Lac/NAA is the most accurate quantitative MR biomarker within the neonatal period for prediction of neurodevelopmental outcome after NE. Lac/NAA may be useful in early clinical management decisions and counseling parents and as a surrogate end point in clinical trials that evaluate novel neuroprotective therapies.