Year: 2024
Type: article
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, nmale/nfemale = 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; RsegATLAS2 = 65% vs. RsegFS2 = 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; R2 = 25%; p < 10−3). 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.
Source: Human Brain Mapping
DOI: 10.1002/hbm.26582
Authors: Jerod M. Rasmussen, Yun Wang, Alice M. Graham, Damien A. Fair, Jonathan Posner, Thomas G. O'Connor, Hyagriv N. Simhan, Elizabeth Yen, Neel Madan, Sonja Entringer, Pathik D. Wadhwa, Claudia Buss, program collaborators for Environmental influences on Child Health Outcomes
Institutions: University of California, Irvine, Duke University, New York State Psychiatric Institute, Oregon Health & Science University, University of Minnesota, University of Rochester Medicine, University of Rochester, University of Pittsburgh, Tufts Medical Center, Humboldt-Universität zu Berlin, Freie Universität Berlin, Charité - Universitätsmedizin Berlin
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,200
Funders: Northwestern University, Johns Hopkins University, National Institutes of Health, Johns Hopkins Bloomberg School of Public Health, Vagelos College of Physicians and Surgeons, Columbia University, National Institute of Mental Health, National Institute on Drug Abuse, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Child Health and Human Development, Duke Clinical Research Institute, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G1024156842, G1585348129, G2466927160, G3746692809, G3811309158, FETAL PROGRAMMING OF THE NEWBORN AND INFANT HUMAN BRAIN, G41400351, G4675071797, G474757497, G4852271397, G5293274170, Human Newborn Energy Homeostasis Brain Networks And Infant Adiposity, G6072882080, G6626789751, G7546031624, G8736256602, G8910038813, G9000027450, G9000031755, G9000217686, Fetal Programming of Human Newborn Energy Homeostasis Brain Networks, 12/24 Healthy Brain and Child Development National Consortium, Environmental influences on Child Health Outcomes (ECHO) Coordinating Center, ECHO DAC (Environmental Influences on Child Health Outcomes Data Analysis Center), G930197008
OpenAlex ID: W4391362355