Quantitative ultra-micro angiography assessment of dynamic cerebral microperfusion patterns by gestational age in neonates: a prospective observational cohort study

Introduction We aimed to establish normative developmental patterns of cerebral microperfusion using ultra-micro angiography and evaluate regional microvascular differences in neonates across gestational ages. Methods This prospective observational cohort study enrolled 115 neonates from a single-center neonatal intensive care unit or neonatal ward at Peking University Third Hospital (2023–2024). The patients were stratified by postmenstrual age into extremely/very preterm ( n = 30), moderate/late preterm ( n = 23), and term ( n = 62) groups, excluding those with major anomalies/hemodynamic instability. Ultra-micro angiography was performed via the anterior/sphenoid fontanelles during quiet sleep (3–14 days postnatal). Regional color pixel percentage (CPP) and large-vessel hemodynamics [peak systolic velocity [PSV]/end-diastolic velocity [EDV]/ resistance index [RI]] were measured. Results Ultra-micro angiography revealed distinct postmenstrual age-dependent microvascular perfusion patterns, with cortical and white matter CPP demonstrating progressive increase across postmenstrual age groups (extremely preterm vs. term infants: frontal lobe CPP 22.97 [IQR 20.12–28.92] vs. 47.57 [40.07–55.93]; parietal lobe CPP 25.09 [20.96–29.94] vs. 47.69 [38.93–55.97]), while basal ganglia CPP remained stable [32.96 [30.64–35.02] vs. 33.77 [31.52–37.46]]. Midline regions consistently exhibited the highest perfusion across all ages [term infants: 66.26 (61.33–70.62)]. Concurrent macrovascular assessment showed that anterior/middle cerebral artery peak systolic and end-diastolic velocities increased with maturation, although resistance indices maintained stability. Conclusion Ultra-micro angiography-derived CPP quantifies gestational age-dependent microvascular maturation, revealing distinct regional perfusion patterns. Differences in the progression of CPP in various brain regions may serve as a biomarker for risk stratification of neurodevelopment in premature infants.