Charting the human amygdala development across childhood and adolescence: Manual and automatic segmentation

Zhou, Quan; Liu, Siman; Jiang, Chao; He, Ye; Zuo, Xi‐Nian

doi:10.1016/j.dcn.2021.101028

Cited by 10 publications

(9 citation statements)

References 76 publications

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“…Similarly, the hippocampus growth trajectory is consistent with prior studies, which reported a fast volume increase until 8 to 10 years of life followed by a slower volume increase [ 37 ]. The hippocampal volume at 5 years of age is consistent with manual segmentations in a cohort from Finland [ 38 ] and the amygdala volume is consistent with a prior study by Zhou and colleagues [ 39 ]. Østby et al reported the thalamic volume in normal developing children at ages 8–11 and 12–15.…”

Section: Discussionsupporting

confidence: 87%

MRI Volumetric Analysis of the Hypothalamus and Limbic System across the Pediatric Age Span

et al. 2023

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Purpose: Literature is scarce regarding volumetric measures of limbic system components across the pediatric age range. The purpose of this study is to remedy this scarcity by reporting continuous volumetric measurements of limbic system components, and to provide consistent stratification data including age-related trajectories and sex-related differences in the pediatric age range in order to improve the recognition of structural variations that might reflect pathology. Methods: In this retrospective study, MRI sequences of children with normal clinical MRI examinations of the brain acquired between January 2010 and December 2019 were included. Isotropic 3D T1-weighted were processed using FreeSurfer version 7.3. Total brain volume and volumes of the limbic system including the hippocampus, parahippocampal gyrus, amygdala, hypothalamus, cingulate gyrus, entorhinal cortex, anteroventral thalamic nucleus, and whole thalamus were assessed. Parcellated output was displayed with the respective label map overlay and images were visually inspected for accuracy of regional segmentation results. Continuous data are provided as mean and standard deviation with quadratic trendlines and as mean and 95% confidence intervals. Categorical data are presented as integers and percentages (%). Results: A total of 724 children (401 female, 55.4%), with a mean age at time of MRI of 10.9 ± 4.2 years (range: 1.9–18.2 years), were included in the study. For females, the total brain volume increased from 955 ± 70 mL at the age of 2–3 years to 1140 ± 110 mL at the age of 17–18 years. Similarly, the total brain volume increased for males from 1004 ± 83 mL to 1263 ± 96 mL. The maximum volume was noted at 11–12 years for females (1188 ± 90 mL) and at 14–15 years for males (1310 ± 159 mL). Limbic system structures reached their peak volume more commonly between the 13–14 years to 17–18 years age groups. The male cingulate gyrus, entorhinal cortex, and anteroventral thalamic nucleus reached peak volume before or at 9–10 years. Conclusion: This study provides unique age- and sex-specific volumes of the components of the limbic system throughout the pediatric age range to serve as normal values in comparative studies. Quantification of volumetric abnormalities of the limbic system on brain MRI may offer insights into phenotypical variations of diseases and may help elucidate new pathological phenotypes.

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Section: Discussionsupporting

confidence: 87%

MRI Volumetric Analysis of the Hypothalamus and Limbic System across the Pediatric Age Span

et al. 2023

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“…Here, child sex was not a significant moderator of the depression‐volume relationships in the amygdala or hippocampus. There is evidence that females and males have different amygdala and hippocampal volume trajectories (Uematsu et al, 2012 ), but more recent work has shown that growth rates do not appear to differ by sex (Zhou et al, 2021 ). Child sex did moderate the relationship between second trimester prenatal depressive symptoms and limbic global efficiency and average node degree.…”

Section: Discussionmentioning

confidence: 99%

“…Statistical analysis was performed in RStudio version 4.0.5 using the lme4 (Bates et al, 2015) and lmerTest (Kuznetsova et al, 2017) ICV was included as a covariate in models looking at amygdala and hippocampal volume. We also tested total gray matter volume instead of ICV based on work advocating for this approach to achieve consistency across segmentation methods (Zhou et al, 2021); there was no difference in optimal model fits when controlling for total gray matter over ICV.…”

Section: Discussionmentioning

confidence: 99%

Prenatal depressive symptoms and childhood development of brain limbic and default mode network structure

Donnici

Long

Reynolds

et al. 2023

Human Brain Mapping

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Prenatal depressive symptoms are linked to negative child behavioral and cognitive outcomes and predict later psychopathology in adolescent children. Prior work links prenatal depressive symptoms to child brain structure in regions like the amygdala; however, the relationship between symptoms and the development of brain structure over time remains unclear. We measured maternal depressive symptoms during pregnancy and acquired longitudinal T1‐weighted and diffusion imaging data in children ( n = 111; 60 females) between 2.6 and 8 years of age. Controlling for postnatal symptoms, we used linear mixed effects models to test relationships between prenatal depressive symptoms and age‐related changes in (i) amygdala and hippocampal volume and (ii) structural properties of the limbic and default‐mode networks using graph theory. Higher prenatal depressive symptoms in the second trimester were associated with more curvilinear trajectories of left amygdala volume changes. Higher prenatal depressive symptoms in the third trimester were associated with slower age‐related changes in limbic global efficiency and average node degree across childhood. Our work provides evidence that moderate symptoms of prenatal depression in a low sociodemographic risk sample are associated with structural brain development in regions and networks implicated in emotion processing.

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“…Zhou et al . ( 2021 ) observed systematic distinctions in amygdala volumes between manual and automatic segmentation approaches. Regarding manual segmentation as the “gold standard”, FreeSurfer estimated larger amygdala, volBrain underestimated the amygdala volume, and FSL demonstrated a mixed pattern.…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, Zhou et al . ( 2021 ) charted the amygdala developmental curves of children and adolescents in devCCNP and compared different segmentation measurements with the manual tracing method. These two studies have important implications in promoting the methodology development of the reliability and validity in brain development research, which are detailed in the next section.…”

Section: Cohortsmentioning

confidence: 99%

Neuroimaging brain growth charts: A road to mental health

et al. 2021

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Mental disorders are common health concerns and contribute to a heavy global burden on our modern society. It is challenging to identify and treat them timely. Neuroimaging evidence suggests the incidence of various psychiatric and behavioral disorders is closely related to the atypical development of brain structure and function. The identification and understanding of atypical brain development provide chances for clinicians to detect mental disorders earlier, perhaps even prior to onset, and treat them more precisely. An invaluable and necessary method in identifying and monitoring atypical brain development are growth charts of typically developing individuals in the population. The brain growth charts can offer a series of standard references on typical neurodevelopment, representing an important resource for the scientific and medical communities. In the present paper, we review the relationship between mental disorders and atypical brain development from a perspective of normative brain development by surveying the recent progress in the development of brain growth charts, including four aspects on growth chart utility: 1) cohorts, 2) measures, 3) mechanisms, and 4) clinical translations. In doing so, we seek to clarify the challenges and opportunities in charting brain growth, and to promote the application of brain growth charts in clinical practice.

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Charting the human amygdala development across childhood and adolescence: Manual and automatic segmentation

Cited by 10 publications

References 76 publications

MRI Volumetric Analysis of the Hypothalamus and Limbic System across the Pediatric Age Span

MRI Volumetric Analysis of the Hypothalamus and Limbic System across the Pediatric Age Span

Prenatal depressive symptoms and childhood development of brain limbic and default mode network structure

Neuroimaging brain growth charts: A road to mental health

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