Back to Search Start Over

Segmenting hypothalamic subunits in human newborn magnetic resonance imaging data.

Authors :
Rasmussen JM
Wang Y
Graham AM
Fair DA
Posner J
O'Connor TG
Simhan HN
Yen E
Madan N
Entringer S
Wadhwa PD
Buss C
Source :
Human brain mapping [Hum Brain Mapp] 2024 Feb 01; Vol. 45 (2), pp. e26582.
Publication Year :
2024

Abstract

Preclinical evidence suggests that inter-individual variation in the structure of the hypothalamus at birth is associated with variation in the intrauterine environment, with downstream implications for future disease susceptibility. However, scientific advancement in humans is limited by a lack of validated methods for the automatic segmentation of the newborn hypothalamus. N = 215 healthy full-term infants with paired T1-/T2-weighted MR images across four sites were considered for primary analyses (mean postmenstrual age = 44.3 ± 3.5 weeks, n <subscript>male</subscript> /n <subscript>female</subscript>  = 110/106). The outputs of FreeSurfer's hypothalamic subunit segmentation tools designed for adults (segFS) were compared against those of a novel registration-based pipeline developed here (segATLAS) and against manually edited segmentations (segMAN) as reference. Comparisons were made using Dice Similarity Coefficients (DSCs) and through expected associations with postmenstrual age at scan. In addition, we aimed to demonstrate the validity of the segATLAS pipeline by testing for the stability of inter-individual variation in hypothalamic volume across the first year of life (n = 41 longitudinal datasets available). SegFS and segATLAS segmentations demonstrated a wide spread in agreement (mean DSC = 0.65 ± 0.14 SD; range = {0.03-0.80}). SegATLAS volumes were more highly correlated with postmenstrual age at scan than segFS volumes (n = 215 infants; R <subscript>segATLAS</subscript> <superscript>2</superscript>  = 65% vs. R <subscript>segFS</subscript> <superscript>2</superscript>  = 40%), and segATLAS volumes demonstrated a higher degree of agreement with segMAN reference segmentations at the whole hypothalamus (segATLAS DSC = 0.89 ± 0.06 SD; segFS DSC = 0.68 ± 0.14 SD) and subunit levels (segATLAS DSC = 0.80 ± 0.16 SD; segFS DSC = 0.40 ± 0.26 SD). In addition, segATLAS (but not segFS) volumes demonstrated stability from near birth to ~1 years age (n = 41; R <superscript>2</superscript>  = 25%; p < 10 <superscript>-3</superscript> ). These findings highlight segATLAS as a valid and publicly available (https://github.com/jerodras/neonate_hypothalamus_seg) pipeline for the segmentation of hypothalamic subunits using human newborn MRI up to 3 months of age collected at resolutions on the order of 1 mm isotropic. Because the hypothalamus is traditionally understudied due to a lack of high-quality segmentation tools during the early life period, and because the hypothalamus is of high biological relevance to human growth and development, this tool may stimulate developmental and clinical research by providing new insight into the unique role of the hypothalamus and its subunits in shaping trajectories of early life health and disease.<br /> (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Details

Language :
English
ISSN :
1097-0193
Volume :
45
Issue :
2
Database :
MEDLINE
Journal :
Human brain mapping
Publication Type :
Academic Journal
Accession number :
38339904
Full Text :
https://doi.org/10.1002/hbm.26582