Poster No:
1298
Submission Type:
Abstract Submission
Authors:
Hyukjin Yun1, Sungmin You1, Seungyoon Jeong1, Pablo Jáquez Vergara1, Sian Wilson2, Ellen Grant1, Kiho Im1
Institutions:
1Boston Children's Hospital, Boston, MA, 2King's College London, London, England
First Author:
Co-Author(s):
Kiho Im
Boston Children's Hospital
Boston, MA
Introduction:
Fetal brain magnetic resonance imaging (MRI) has been employed to visualize fetal brain growth during pregnancy. The cortical plate (CP) is one of distinguishable tissues in fetal brain MRI which is a transient tissue formed as a result of the migration of neuronal precursors from the germinal matrix and ganglionic eminence, giving rise to the developing cerebral cortex [1]. In an ex vivo fetal MRI study, the CP thickness showed a small change (< 1 mm) between 15 and 40 weeks of gestational age (GA), however, it varied significantly across cortical regions [2]. The regionally different growth of the CP thickness may be related to rapid growth and regional expansion of functional areas under genetic controls [3,4]. Investigating regionally different growth pattern of the CP thickness in living fetuses may provide more regional information of functional development in human brain development. In this study, we measured the CP thickness using multi-site fetal brain MRI data and quantify regionally growth rates of the CP thickness.
Methods:
The study was approved by the local Institutional Review Board at Boston Children's Hospital (BCH) and by the Ethics Committee of Hospital Clínic Barcelona, Spain (HCB/2020/0267). A total of 28 typically developing (TD) fetuses (GA: 27.6 ± 3.5 [mean ± standard deviation]) were included in this study (twenty from BCH and eight from developing Human Connectome Project (dHCP, https://www.developingconnectome.org/project/)). Multiplanar MRI stacks of thick 2D slices from BCH and dHCP data were acquired using T2-weighted Half-Fourier Acquisition Single-Shot Turbo Spin-Echo and Single-shot fast spin-echo sequences, respectively. After motion correction of MRI stacks [5,6], we performed CP segmentation [7] and extracted the inner CP surface using Marching cube algorithm [8]. The outer CP surfaces was expanded from the inner surface using a topology-preserving deformation technique [9,10]. Based on vertex-wise correspondence between the inner and outer surfaces we estimated cortical thickness by distance between the corresponding vertices [11]. For inter-subject vertex correspondence, we aligned the surfaces to 29 GW template surface [12]. On the template surface, we manually 21 parcellated cortical regions (Figure 1A) based on the Freesurfer Desikan atlas [13]. Then the regional linear growth rates were calculated by fitting a line to the average thickness and GA.

Results:
All the regions showed small growth rates (< 0.1mm/week) but the rates were regionally diverse (Table 1). Among the regions, bilateral cingulate cortex and insular showed high growth rate (> 0.7 mm/week) (Figure 1B). Superior and inferior temporal cortices also showed relatively high growth rate (> 0.6mm/week). In contrast, the regions belonging to parietal and occipital lobes showed relatively low growth rate (< 0.45mm/week).
Conclusions:
This study presented regional growth rates of the CP thickness in the TD fetuses. We observed high thickness growth rates in the central region compared to the peripheral regions. The age-related growth patterns of the CP thickness are similar to gyrification. In our previous studies, we found that early cortical folding emerged in the central regions and proceeded in the temporo-parieto-occipital lobes, and then the frontal lobe [12,14]. This regional pattern of growth rates may reflect the phylogenic and functional localization of the cerebral cortex. The phylogenetically older allocortex cortical regions such as the anterior insular cortex mature earlier than the newer cortical regions [15,16]. Therefore, the diverse growth rates of CP thickness during early fetal life may agree with regionally relevant indices in functional development in the human brain. The findings in this study may be used in the future investigations to reveal the relationship between CP thickness and functional development with a large sample of fetal brain MRI in wide GA range.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 2
Lifespan Development:
Early life, Adolescence, Aging
Normal Brain Development: Fetus to Adolescence 1
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping
Normal Development
Keywords:
Aging
Cortex
Development
STRUCTURAL MRI
Other - cortical thickness
1|2Indicates the priority used for review
Provide references using author date format
[1] I. Kostović (2007), Transient patterns of cortical lamination during prenatal life: Do they have implications for treatment?, Neuroscience & Biobehavioral Reviews. 31 1157–1168.
[2] L. Vasung (2016) , Quantitative and Qualitative Analysis of Transient Fetal Compartments during Prenatal Human Brain Development, Frontiers in Neuroanatomy. 10 11.
[3] L. Ronan (2015), From genes to folds: a review of cortical gyrification theory, Brain Structure and Function. 220 2475–2483.
[4] W. Welker (1990), Why Does Cerebral Cortex Fissure and Fold?, in: Cerebral Cortex, Springer, Boston, MA, : pp. 3–136.
[5] M. Kuklisova-Murgasova (2012), Reconstruction of fetal brain MRI with intensity matching and complete outlier removal, Med Image Anal.
[6] A. Makropoulos (2018), The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction, NeuroImage. 173 88–112.
[7] J. Hong (2020), Fetal Cortical Plate Segmentation Using Fully Convolutional Networks With Multiple Plane Aggregation, Frontiers in Neuroscience. 14.
[8] C. Lepage (2017), Human MR evaluation of cortical thickness using CIVET v2. 1, Organization for Human Brain Mapping.
[9] J.S. Kim (2005), Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification, NeuroImage. 27 210–221.
[10] M. Liu (2021), Robust Cortical Thickness Morphometry of Neonatal Brain and Systematic Evaluation Using Multi-Site MRI Datasets, Frontiers in Neuroscience. 15.
[11] S. Robbins (2004), Tuning and comparing spatial normalization methods, Med Image Anal. 8 311–323.
[12] H.J. Yun (2020), Temporal Patterns of Emergence and Spatial Distribution of Sulcal Pits During Fetal Life, Cereb Cortex. 30 4257–4268.
[13] R.S. Desikan (2006), An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest, NeuroImage. 31 968–980.
[14] H.J. Yun (2022), Quantification of sulcal emergence timing and its variability in early fetal life: Hemispheric asymmetry and sex difference, NeuroImage. 263 119629.
[15] N. Gogtay (2004), Dynamic mapping of human cortical development during childhood through early adulthood, Proceedings of the National Academy of Sciences. 101 8174–8179.
[16] J.L.R. Rubenstein (1999), Genetic Control of Cortical Development, Cereb Cortex. 9 521–523.