Dataset Information

Automatic labeling of cortical sulci for the human fetal brain based on spatio-temporal information of gyrification.

ABSTRACT: Accurate parcellation and labeling of primary cortical sulci in the human fetal brain is useful for regional analysis of brain development. However, human fetal brains show large spatio-temporal changes in brain size, cortical folding patterns, and relative position/size of cortical regions, making accurate automatic sulcal labeling challenging. Here, we introduce a novel sulcal labeling method for the fetal brain using spatio-temporal gyrification information from multiple fetal templates. First, spatial probability maps of primary sulci are generated on the templates from 23 to 33 gestational weeks and registered to an individual brain. Second, temporal weights, which determine the level of contribution to the labeling for each template, are defined by similarity of gyrification between the individual and the template brains. We combine the weighted sulcal probability maps from the multiple templates and adopt sulcal basin-wise approach to assign sulcal labels to each basin. Our labeling method was applied to 25 fetuses (22.9-29.6 gestational weeks), and the labeling accuracy was compared to manually assigned sulcal labels using the Dice coefficient. Moreover, our multi-template basin-wise approach was compared to a single-template approach, which does not consider the temporal dynamics of gyrification, and a fully-vertex-wise approach. The mean accuracy of our approach was 0.958 across subjects, significantly higher than the accuracies of the other approaches. This novel approach shows highly accurate sulcal labeling and provides a reliable means to examine characteristics of cortical regions in the fetal brain.

SUBMITTER: Yun HJ

PROVIDER: S-EPMC6452886 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Automatic labeling of cortical sulci for the human fetal brain based on spatio-temporal information of gyrification.

Yun Hyuk Jin HJ Chung Ai Wern AW Vasung Lana L Yang Edward E Tarui Tomo T Rollins Caitlin K CK Ortinau Cynthia M CM Grant P Ellen PE Im Kiho K

NeuroImage 20181212

Accurate parcellation and labeling of primary cortical sulci in the human fetal brain is useful for regional analysis of brain development. However, human fetal brains show large spatio-temporal changes in brain size, cortical folding patterns, and relative position/size of cortical regions, making accurate automatic sulcal labeling challenging. Here, we introduce a novel sulcal labeling method for the fetal brain using spatio-temporal gyrification information from multiple fetal templates. Firs ...[more]

PMID: 30553042

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Project description:Background: Spina bifida aperta (SBA) is a birth defect associated with severe anatomical changes in the developing fetal brain. Brain magnetic resonance imaging (MRI) atlases are popular tools for studying neuropathology in the brain anatomy, but previous fetal brain MRI atlases have focused on the normal fetal brain. We aimed to develop a spatio-temporal fetal brain MRI atlas for SBA. Methods: We developed a semi-automatic computational method to compute the first spatio-temporal fetal brain MRI atlas for SBA. We used 90 MRIs of fetuses with SBA with gestational ages ranging from 21 to 35 weeks. Isotropic and motion-free 3D reconstructed MRIs were obtained for all the examinations. We propose a protocol for the annotation of anatomical landmarks in brain 3D MRI of fetuses with SBA with the aim of making spatial alignment of abnormal fetal brain MRIs more robust. In addition, we propose a weighted generalized Procrustes method based on the anatomical landmarks for the initialization of the atlas. The proposed weighted generalized Procrustes can handle temporal regularization and missing annotations. After initialization, the atlas is refined iteratively using non-linear image registration based on the image intensity and the anatomical land-marks. A semi-automatic method is used to obtain a parcellation of our fetal brain atlas into eight tissue types: white matter, ventricular system, cerebellum, extra-axial cerebrospinal fluid, cortical gray matter, deep gray matter, brainstem, and corpus callosum. Results: An intra-rater variability analysis suggests that the seven anatomical land-marks are sufficiently reliable. We find that the proposed atlas outperforms a normal fetal brain atlas for the automatic segmentation of brain 3D MRI of fetuses with SBA. Conclusions: We make publicly available a spatio-temporal fetal brain MRI atlas for SBA, available here: https://doi.org/10.7303/syn25887675. This atlas can support future research on automatic segmentation methods for brain 3D MRI of fetuses with SBA.

Project description:The development of the human brain is a complex and precisely regulated process that unfolds over a protracted period of time. Human-specific features of this process, especially the ways in which highly complex neural circuits of the cerebral cortex form, are likely to be important factors in the evolution of human specializations. However, in addition to giving us remarkable cognitive and motor abilities, the formation of intricate neural circuits may have also increased our susceptibility to psychiatric and neurodegenerative disorders. Furthermore, substantial evidence suggests that the symptoms and progression of many brain disorders are dramatically influenced by genetic and developmental processes that define regional cell phenotypes and connectivity. Sex differences also play an important role in brain development and function and are a risk factor for several brain disorders, such as autism spectrum disorders (ASD) and depression. Thus understanding the spatiotemporal dynamics and functional organization of the brain transcriptome is essential to teasing out the keys to human neurodevelopment, sexual dimorphism, and evolution as well as our increased susceptibility to certain brain disorders. Most transcriptome studies of the developing brain have been restricted to rodents, and those performed in humans and nonhuman primates have included relatively small sample sizes and predominantly focused on few regions or developmental time points. Because many prominent features of human brain development significantly diverge from those of well-characterized model organisms, the translation of knowledge across species is difficult, and it is likely that many underlying genetic processes have gone undetected. In this study, we have taken a genome-wide approach to analyze the human transcriptome at single-exon resolution with ~1.4 million exon-level probe sets in 16 brain regions from donors representing both sexes and multiple ethnicities, across pre and postnatal development, including adolescence, and adulthood. We also generated genome-wide genotype data for 2.5 million single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for each specimen. Our analyses of the data revealed several features of the human brain transcriptome: spatiotemporal expression dynamics of individual and functionally related groups of genes, differential exon usage, sex-specific expression patterns and exon usage, and organization of the transcriptome into functional modules. We also profiled developmental trajectories of genes important for neurobiological themes and genes associated with ASD and schizophrenia. Finally, we present associations between specific SNPs and gene expression levels in different brain regions across development. The dataset presented here provides research opportunities and a wealth of information not previously available to the scientific community. Here we report the generation and analysis of genome-wide exon-level transcriptome data from 16 brain regions comprising the cerebellar cortex, mediodorsal nucleus of the thalamus, striatum, amygdala, hippocampus, and 11 areas of the neocortex. The dataset was generated from 1,340 samples collected from both hemispheres of 57 postmortem human brains, spanning from embryonic development to late adulthood and representing males and females of multiple ethnicities. We also performed genome-wide genotyping of 2.5 million single nucleotide polymorphisms (SNPs) and assessed copy number variations for all donors. We found that approximately 86% of protein-coding genes are expressed above background, and over 90% of these are differentially regulated at the whole transcript or exon level across regions and/or time. The majority of these spatiotemporal differences occur before birth, followed by a progressive increase in the similarity among regional transcriptome during the postnatal lifespan. Distinctive transcriptional patterns were also identified among neocortical areas, including an alternative isoform of ANKRD32 that is transiently upregulated in the late midfetal frontal cortex of human but not mouse. Developmentally and regionally regulated differences in gene expression and exon usage were also identified between males and females, including IGF2, an imprinted gene implicated in brain growth and cognitive function, and NLGN4X, a candidate gene for autism spectrum disorders. We found that the developing transcriptome is organized into functionally distinct large-scale networks of co-regulated transcripts. We also observed marked differences in expression trajectories of genes associated with specific neurodevelopmental processes, neural cell types, neurotransmitter systems, autism spectrum disorders, and schizophrenia. Association analysis of the SNP genotypes and transcriptome revealed potential polymorphic regulators of gene expression in different regions across development. This study provides a comprehensive, publicly available dataset on the spatiotemporal human brain transcriptome and new insights into the transcriptional foundations of brain development and evolution. This submission represents the transcriptome component of the study. Submitter did not submit SNP and CNV data due to privacy issue of patients.

Dataset Information

Automatic labeling of cortical sulci for the human fetal brain based on spatio-temporal information of gyrification.

Publications

Automatic labeling of cortical sulci for the human fetal brain based on spatio-temporal information of gyrification.

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