WIP 79 - Resting-State Functional Brain Connectivity and Network Topology of Neonates with Hypoxic-ischemic Encephalopathy using Functional Near-Infrared Spectroscopy.

Publication Number: WIP 79.7653

Anagha Vinod, McMaster University, Hamilton, ON, Canada; Sabrina Mastroianni, McMaster University Michael G. DeGroote School of Medicine, Thornhill, ON, Canada; Heather Johnson, McMaster University Michael G. DeGroote School of Medicine, Hamilton, ON, Canada; Naiqi G. Xiao, McMaster University, Hamilton, ON, Canada; Ipsita Goswami, McMaster University, Hamilton, ON, Canada

Background: Neonatal hypoxic-ischemic encephalopathy (HIE) is associated with cognitive delays, behavioral concerns, and learning disabilities. Bedside assessment of functional brain connectivity during the tertiary phase of injury may help understand the recovery process and effectiveness of therapeutic hypothermia.

Objective: This study aims to characterize the resting-state functional connectivity (rsFC) patterns and investigate their relationship with brain injury severity after HIE. We hypothesize that greater HIE brain injury may result in weaker inter-hemispheric connectivity and stronger intra-hemispheric connectivity, which may reflect adaptive mechanisms after brain injury.

Design/Methods: The prospective cohort study will recruit 15 neonates born at >35 weeks gestation and birthweights >1800g admitted with any stage of HIE. Resting-state brain activity will be measured for 20 minutes using dual BabyBrite fNIRS system (Artinis Medical Systems) between 5-15 days of life. We customized a neonatal cap with 20 emitters and 16 detectors (54 channels) covering frontal, parietal, occipital, and bilateral temporal lobes.
Raw data will be preprocessed using HOMER3 software to correct motion artifacts and remove noisy channels. Network topology will be characterized for the whole brain and specific regions of interest (ROI) [default mode network, sensorimotor, visual, and auditory cortex]. Intra- and inter-hemispheric rsFCs will be calculated for each participant using Pearson correlation using NIRS KIT software. Graph theory metrics (assortativity, hierarchy, global and local efficiency, and small worldness) will be calculated using GRETNA software.
We have currently enrolled 8 subjects [mean (SD) gestation 38(2) weeks; birth weight 2981(225) g; mild HIE (n=2); moderate HIE (n=6)]. The recruitment and analysis will be complete by April 2025.
Our findings may elucidate the organization and efficiency of functional architecture in HIE patients, identifying potential network biomarkers to predict cognitive outcomes, and inform early interventions.