AUTHOR=Zheng Qiang, Martin-Saavedra Juan Sebastian, Saade-Lemus Sandra, Vossough Arastoo, Zuccoli Giulio, Gonçalves Fabrício Guimarães, Freeman Colbey W., Ouyang Minhui, Singh Varun, Padula Michael A., Demauro Sara B., Flibotte John, Eichenwald Eric C., Detre John A., Sze Raymond Wang, Huang Hao, Hwang Misun TITLE=Cerebral Pulsed Arterial Spin Labeling Perfusion Weighted Imaging Predicts Language and Motor Outcomes in Neonatal Hypoxic-Ischemic Encephalopathy JOURNAL=Frontiers in Pediatrics VOLUME=8 YEAR=2020 URL=https://www.frontiersin.org/articles/10.3389/fped.2020.576489 DOI=10.3389/fped.2020.576489 ISSN=2296-2360 ABSTRACT=Rationale and Objectives: To compare cerebral pulsed arterial spin labeling (PASL) perfusion among controls, hypoxic ischemic encephalopathy (HIE) neonates with normal conventional MRI(HIE/MRI⊕), and HIE neonates with abnormal conventional MRI(HIE/MRI⊖). To create a predictive machine learning model of neurodevelopmental outcomes using cerebral PASL perfusion.Materials and Methods: A total of 73 full-term neonates were evaluated. The cerebral perfusion values were compared by permutation test to identify brain regions with significant perfusion changes among 18 controls, 40 HIE/MRI⊖ patients, and 15 HIE/MRI⊕ patients. A machine learning model was developed to predict neurodevelopmental outcomes using the averaged perfusion in those identified brain regions.Results: Significantly decreased PASL perfusion in HIE/MRI⊖ group, when compared with controls, were found in the anterior corona radiata, caudate, superior frontal gyrus, precentral gyrus. Both significantly increased and decreased cerebral perfusion changes were detected in HIE/MRI⊕ group, when compared with HIE/MRI⊖ group. There were no significant perfusion differences in the cerebellum, brainstem and deep structures of thalamus, putamen, and globus pallidus among the three groups. The machine learning model demonstrated significant correlation (p < 0.05) in predicting language(r = 0.48) and motor(r = 0.57) outcomes in HIE/MRI⊖ patients, and predicting language(r = 0.76), and motor(r = 0.53) outcomes in an additional group combining HIE/MRI⊖ and HIE/MRI⊕.Conclusion: Perfusion MRI can play an essential role in detecting HIE regardless of findings on conventional MRI and predicting language and motor outcomes in HIE survivors. The perfusion changes may also reveal important insights into the reperfusion response and intrinsic autoregulatory mechanisms. Our results suggest that perfusion imaging may be a useful adjunct to conventional MRI in the evaluation of HIE in clinical practice.