Clinical-functional correlation with brain volumetry in severe perinatal asphyxia: a case report

Area of Science:

• Neurology
• Medical Imaging
• Machine Learning

Background:

• Hypoxic-ischemic encephalopathy (HIE) affects deep grey matter, basal ganglia, and white matter in newborns.
• Modeling HIE in neonates is complex due to intensity variability.
• This study evaluates functional measurements and 3D machine learning models for HIE assessment.

Observation:

• A term infant with perinatal asphyxia, low APGAR scores, and acidosis was analyzed.
• Longitudinal 3D brain data and machine learning models were used.
• Therapeutic interventions included neurodevelopmental therapies and epilepsy treatment.

Findings:

• 3D analysis revealed age-related volume decrease and increasing hemispheric asymmetry.
• Basal ganglia analysis showed increasing thalamus, caudate, and putamen asymmetry over time.
• Globus pallidus volume decreased over time.

Implications:

• Subtle basal ganglia and cerebellum changes in HIE require 3D volumetry for detection.
• Quantifying neurodevelopmental changes aids in understanding clinical implications.
• Neurophysiological evaluations can enhance neuroplasticity in children with neurological sequelae.