Novel Mammillary Body Manual Segmentation: Application for Quantitative MRI Analysis of Critically Ill Infants.

Background And Purpose: Previous qualitative studies have shown that mammillary body (MB) assessment can serve as an early marker of poor long-term neurodevelopmental outcomes. This study aims to establish a reliable quantitative method for analyzing the surface area, volume, and signal intensity of MB in infancy.

Methods: A novel methodology was retrospectively tested in a cohort of critically ill preterm and term-born patients following esophageal atresia (EA) repair, and healthy term-born controls ( = 13/group) using non-sedated brain MRI on a 3T Siemens scanner. Manual bilateral MB segmentation of T2-weighted data and quantification of MB surface area, volume, and tissue mean signal intensity were performed using ITK-SNAP. Endpoint measures were assessed for normality, and their relationship with group status was evaluated using a general linear model with age at scan as a covariate.

Results: High - and -tracer reliability was observed between a novice and neuroanatomical expert for MB segmentation. Despite straightforward manual masking and novel quantification of infant MB, no significant differences were found among the three groups (preterm and term-born patients, and term-born controls) for any of the MB endpoints analyzed: surface area, volume, and signal intensity. The data analysis revealed a trend of lower values in patient groups for signal intensity only.

Conclusions: This novel study describes efficient and accurate MB masking and quantification, supporting MB as a potential early marker. However, the negative results presented in infants born with EA should not be generalized until future prospective studies with larger sample sizes are conducted and linked to neurodevelopmental outcomes.