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Neuroimage Clin. 2015 Aug 24;9:176-93. doi: 10.1016/j.nicl.2015.07.019. eCollection 2015.

Automatic segmentation of the hippocampus for preterm neonates from early-in-life to term-equivalent age.

Author information

1
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.
2
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.
3
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.
4
Schulich School of Medicine and Dentistry, Western University, London, ON, Canada; Cerebral Imaging Centre, Douglas Mental Health Research Institute, Verdun, QC, Canada.
5
Department of Pediatrics, University of British Columbia and Child and Family Research Institute, Vancouver, BC, Canada.
6
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.

Abstract

INTRODUCTION:

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.

KEYWORDS:

Early-in-life; Hippocampus; MAGeT-Brain; MRI; Preterm neonates; Segmentation

PMID:
26740912
PMCID:
PMC4561668
DOI:
10.1016/j.nicl.2015.07.019
[Indexed for MEDLINE]
Free PMC Article

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