Kagan Mackenzie S, Zurakowski David, Takahashi Emi, Jennings Russell W, Bajic Dusica
Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts, USA.
Harvard Medical School, Boston, Massachusetts, USA.
Clin Neuroimaging (Hoboken). 2025;2(1). doi: 10.1002/neo2.70011. Epub 2025 Feb 26.
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.
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.
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.
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.
先前的定性研究表明，乳头体（MB）评估可作为长期神经发育不良结局的早期标志物。本研究旨在建立一种可靠的定量方法，用于分析婴儿期MB的表面积、体积和信号强度。
采用一种新方法，对一组患有食管闭锁（EA）并接受修复手术的危重新生儿和足月儿以及健康足月儿对照组（每组n = 13）进行回顾性测试，使用3T西门子扫描仪进行非镇静状态下的脑部MRI检查。使用ITK-SNAP对T2加权数据进行手动双侧MB分割，并对MB表面积、体积和组织平均信号强度进行量化。对终点指标进行正态性评估，并使用以扫描时年龄作为协变量的一般线性模型评估其与组状态的关系。
在MB分割方面，新手与神经解剖学专家之间观察到了高度的评分者间可靠性。尽管对婴儿MB进行了直接的手动掩蔽和新颖的量化，但在分析的任何MB终点指标（表面积、体积和信号强度）上，三组（早产儿和足月儿患者以及足月儿对照组）之间均未发现显著差异。数据分析仅显示患者组的信号强度值有降低的趋势。
这项新研究描述了高效且准确的MB掩蔽和量化方法，支持MB作为一种潜在的早期标志物。然而，在进行更大样本量的未来前瞻性研究并将其与神经发育结局相关联之前，不应将EA患儿的阴性结果进行推广。
