Recent findings implicate brain vulnerability following long-gap esophageal atresia (LGEA) repair. We explored the relationship between easily quantifiable clinical measures and previously reported brain findings in a pilot cohort of infants following LGEA repair. MRI measures (number of qualitative brain findings; normalized brain and corpus callosum volumes) were previously reported in term-born and early-to-late premature infants (n = 13/group) <1 year following LGEA repair with the Foker process. The severity of underlying disease was classified by an (1) American Society of Anesthesiologist (ASA) physical status and (2) Pediatric Risk Assessment (PRAm) scores. Additional clinical end-point measures included: anesthesia exposure (number of events; cumulative minimal alveolar concentration (MAC) exposure in hours), length (in days) of postoperative intubated sedation, paralysis, antibiotic, steroid, and total parenteral nutrition (TPN) treatment. Associations between clinical end-point measures and brain MRI data were tested using Spearman rho and multivariable linear regression. Premature infants were more critically ill per ASA scores, which showed a positive association with the number of cranial MRI findings. Clinical end-point measures together significantly predicted the number of cranial MRI findings for both term-born and premature infant groups, but none of the individual clinical measures did on their own. Listed easily quantifiable clinical end-point measures could be used together as indirect markers in assessing the risk of brain abnormalities following LGEA repair.

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 long‐gap esophageal atresia (EA) repair, and healthy term‐born controls ( n = 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 intra ‐ and inter ‐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 long‐gap EA should not be generalized until future prospective studies with larger sample sizes are conducted and linked to neurodevelopmental outcomes.