title: Automatic segmentation of the hippocampus for preterm neonates from early-in-life to term-equivalent age.
abstract: BACKGROUND
  The hippocampus, a medial temporal lobe structure central to learning and memory, is particularly vulnerable in preterm-born neonates. To date, segmentation of the hippocampus for preterm-born neonates has not yet been performed early-in-life (shortly after birth when clinically stable). The present study focuses on the development and validation of an automatic segmentation protocol that is based on the MAGeT-Brain (Multiple Automatically Generated Templates) algorithm to delineate the hippocampi of preterm neonates on their brain MRIs acquired at not only term-equivalent age but also early-in-life.
  
  
  METHODS
  First, we present a three-step manual segmentation protocol to delineate the hippocampus for preterm neonates and apply this protocol on 22 early-in-life and 22 term images. These manual segmentations are considered the gold standard in assessing the automatic segmentations. MAGeT-Brain, automatic hippocampal segmentation pipeline, requires only a small number of input atlases and reduces the registration and resampling errors by employing an intermediate template library. We assess the segmentation accuracy of MAGeT-Brain in three validation studies, evaluate the hippocampal growth from early-in-life to term-equivalent age, and study the effect of preterm birth on the hippocampal volume. The first experiment thoroughly validates MAGeT-Brain segmentation in three sets of 10-fold Monte Carlo cross-validation (MCCV) analyses with 187 different groups of input atlases and templates. The second experiment segments the neonatal hippocampi on 168 early-in-life and 154 term images and evaluates the hippocampal growth rate of 125 infants from early-in-life to term-equivalent age. The third experiment analyzes the effect of gestational age (GA) at birth on the average hippocampal volume at early-in-life and term-equivalent age using linear regression.
  
  
  RESULTS
  The final segmentations demonstrate that MAGeT-Brain consistently provides accurate segmentations in comparison to manually derived gold standards (mean Dice's Kappa > 0.79 and Euclidean distance <1.3 mm between centroids). Using this method, we demonstrate that the average volume of the hippocampus is significantly different (p < 0.0001) in early-in-life (621.8 mm(3)) and term-equivalent age (958.8 mm(3)). Using these differences, we generalize the hippocampal growth rate to 38.3 ± 11.7 mm(3)/week and 40.5 ± 12.9 mm(3)/week for the left and right hippocampi respectively. Not surprisingly, younger gestational age at birth is associated with smaller volumes of the hippocampi (p = 0.001).
  
  
  CONCLUSIONS
  MAGeT-Brain is capable of segmenting hippocampi accurately in preterm neonates, even at early-in-life. Hippocampal asymmetry with a larger right side is demonstrated on early-in-life images, suggesting that this phenomenon has its onset in the 3rd trimester of gestation. Hippocampal volume assessed at the time of early-in-life and term-equivalent age is linearly associated with GA at birth, whereby smaller volumes are associated with earlier birth.
authors.affiliation: Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Paediatrics, The Hospital for Sick Children and the University of Toronto, Toronto, ON, Canada.
authors.forename: Ting
authors.initials: T
authors.lastname: Guo
authors.affiliation: Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; Kimel Family Translational Imaging, Genetics Research Laboratory, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.
authors.forename: Julie L
authors.initials: JL
authors.lastname: Winterburn
authors.affiliation: Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Kimel Family Translational Imaging, Genetics Research Laboratory, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.
authors.forename: Jon
authors.initials: J
authors.lastname: Pipitone
authors.affiliation: Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Paediatrics, The Hospital for Sick Children and the University of Toronto, Toronto, ON, Canada.
authors.forename: Emma G
authors.initials: EG
authors.lastname: Duerden
authors.affiliation: Schulich School of Medicine and Dentistry, Western University, London, ON, Canada; Cerebral Imaging Centre, Douglas Mental Health Research Institute, Verdun, QC, Canada.
authors.forename: Min Tae M
authors.initials: MT
authors.lastname: Park
authors.affiliation: Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Paediatrics, The Hospital for Sick Children and the University of Toronto, Toronto, ON, Canada.
authors.forename: Vann
authors.initials: V
authors.lastname: Chau
authors.affiliation: Department of Pediatrics, University of British Columbia and Child and Family Research Institute, Vancouver, BC, Canada.
authors.forename: Kenneth J
authors.initials: KJ
authors.lastname: Poskitt
authors.affiliation: Department of Pediatrics, University of British Columbia and Child and Family Research Institute, Vancouver, BC, Canada.
authors.forename: Ruth E
authors.initials: RE
authors.lastname: Grunau
authors.affiliation: Department of Pediatrics, University of British Columbia and Child and Family Research Institute, Vancouver, BC, Canada.
authors.forename: Anne
authors.initials: A
authors.lastname: Synnes
authors.affiliation: Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Paediatrics, The Hospital for Sick Children and the University of Toronto, Toronto, ON, Canada.
authors.forename: Steven P
authors.initials: SP
authors.lastname: Miller
authors.affiliation: Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; Cerebral Imaging Centre, Douglas Mental Health Research Institute, Verdun, QC, Canada; Department of Psychiatry, McGill University, Montreal, QC, Canada.
authors.forename: M
authors.initials: M
authors.lastname: Mallar Chakravarty
mesh_terms: D000465:Algorithms; D005260:Female; D005865:Gestational Age; D006624:Hippocampus / Q000254:growth & development / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007231:Infant, Newborn; D007234:Infant, Premature; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009010:Monte Carlo Method; D015203:Reproducibility of Results
keywords: Early-in-life; Hippocampus; MAGeT-Brain; MRI; Preterm neonates; Segmentation