Regional growth and atlasing of the developing human brain

Makropoulos, Antonios; Aljabar, Paul; Wright, Robert; Hüning, Britta; Merchant, Nazakat; Arichi, Tomoki; Tusor, Nora; Hajnal, Joseph V.; Edwards, A. David; Counsell, Serena J.; Rueckert, Daniel

doi:10.1016/j.neuroimage.2015.10.047

Cited by 187 publications

(200 citation statements)

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“…These GM probability maps are derived from an initial tissue segmentation, performed using tissue priors propagated through registration of a preterm probabilistic tissue atlas Serag et al (2012) to each term-born subject. Preterm subjects typically have increased CSF volume over term neonates (Makropoulos et al, 2016), and this is reflected in the preterm template Serag et al (2012). Therefore, to account for the effects of misregistration resulting from the different amounts of CSF (see Fig.…”

Section: Segmentation Methodsmentioning

confidence: 99%

“…Cortical thickness across the whole brain has a mean value of 1.1 mm, which increases across the age at scan. Cortical thickness measurements in the neonatal population have been previously reported in the literature in (Xue et al, 2007;Moeskops et al, 2013;Li et al, 2015a;Moeskops et al, 2015;Makropoulos et al, 2016;Geng et al, 2017) with different ranges between 1-2 mm. Dif- ferences between reported values can be due to different image acquisition, image segmentation and surface reconstruction methods.…”

Section: Surface Qcmentioning

confidence: 99%

“…http://dx.doi.org/10.1101/125526 doi: bioRxiv preprint first posted online Apr. 10, 2017; specially designed tissue segmentation (Makropoulos et al, 2012(Makropoulos et al, , 2014(Makropoulos et al, , 2016 and surface extraction protocols Schuh et al (2017) (Sections 3.2,3.3). Further differences between the dHCP and HCP pipelines, are motivated by a desire to reduce software overhead: therefore, surface inflation is performed using an in-house re-implementation of the FreeSurfer method, and spherical projection is performed using a specially designed spherical MDS tool (Section 3.4).…”

Section: Comparison To Hcp Pipelinesmentioning

confidence: 99%

“…Specifically, baby and adult brains differ vastly in terms of size, with the fetal and neonatal brain covering a volume in the range of 100-600 millilitres in contrast to an average adult brain volume of more than 1 litre (Allen et al, 2002;Orasanu et al, 2014;Makropoulos et al, 2016). Furthermore, the perinatal brain develops rapidly, which results in vast changes in scale and appearance of the brain scanned at different weeks.…”

Section: Introductionmentioning

confidence: 99%

“…The processing steps are as follows: 1) acquisition and reconstruction of T1 and T2 images Hughes et al, 2016;Kuklisova-Murgasova et al, 2012); 2) tissue segmentation and regional labelling (Makropoulos et al, 2012(Makropoulos et al, , 2014(Makropoulos et al, , 2016; 3) cortical white and pial surface extraction ; 4) inflation and projection to a sphere (for use with spherical alignment approaches) (Fischl et al, 1999a;Elad et al, 2005); and 5) definition of cortical feature descriptors, including descriptors of cortical geometry and myelination (Glasser et al, 2013). Manual quality control is performed by two independent expert raters to assess the quality of the acquired images, segmentations, and reconstructed cortical surfaces.…”

Section: Introductionmentioning

confidence: 99%

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The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

et al. 2018

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The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline * Corresponding author Email address: a.makropoulos11@imperial.ac.uk (Antonios Makropoulos) 1 These authors contributed equally Preprint submitted to NeuroImage January 7, 2018peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/125526 doi: bioRxiv preprint first posted online Apr. 10, 2017; consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

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Section: Segmentation Methodsmentioning

confidence: 99%

Section: Surface Qcmentioning

confidence: 99%

Section: Comparison To Hcp Pipelinesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

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Association Between Socioeconomic Status and In Utero Fetal Brain Development

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et al. 2021

JAMA Netw Open

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IMPORTANCE Children raised in settings with lower parental socioeconomic status are at increased risk for neuropsychological disorders. However, to date, the association between socioeconomic status and fetal brain development remains poorly understood.OBJECTIVE To determine the association between parental socioeconomic status and in vivo fetal brain growth and cerebral cortical development using advanced, 3-dimensional fetal magnetic resonance imaging. DESIGN, SETTING, AND PARTICIPANTSThis cohort study of fetal brain development enrolled 144 healthy pregnant women from 2 low-risk community obstetrical hospitals from 2012 through 2019 in the District of Columbia. Included women had a prenatal history without complications that included recommended screening laboratory and ultrasound studies. Exclusion criteria were multiple gestation pregnancy, known or suspected congenital infection, dysmorphic features of the fetus, and documented chromosomal abnormalities. T2-weighted fetal brain magnetic resonance images were acquired. Each pregnant woman was scanned at up to 2 points in the fetal period. Data were analyzed from June through November 2020. EXPOSURES Parental education level and occupation status were documented. MAIN OUTCOMES AND MEASURES Regional fetal brain tissue volume (for cortical gray matter, white matter, cerebellum, deep gray matter, and brainstem) and cerebral cortical features (ie, lobe volume, local gyrification index, and sulcal depth) in the frontal, parietal, temporal, and occipital lobes were calculated. RESULTS Fetal brain magnetic resonance imaging studies were performed among 144 pregnant women (median [interquartile range] age, 32.5 [27.0-36.1] years) with gestational age from 24.0 to 39.4 weeks; 75 fetuses (52.1%) were male, and 69 fetuses (47.9%) were female. Higher parental education level was associated with significantly increased volume in the fetal white matter

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Association of Preterm Birth and Socioeconomic Status With Neonatal Brain Structure

et al. 2023

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ImportancePreterm birth and socioeconomic status (SES) are associated with brain structure in childhood, but the relative contributions of each during the neonatal period are unknown.ObjectiveTo investigate associations of birth gestational age (GA) and SES with neonatal brain morphology by testing 3 hypotheses: GA and SES are associated with brain morphology; associations between SES and brain morphology vary with GA; and associations between SES and brain structure and morphology depend on how SES is operationalized.Design, Setting, and ParticipantsThis cohort study recruited participants from November 2016 to September 2021 at a single center in the United Kingdom. Participants were 170 extremely and very preterm infants and 91 full-term or near-term infants. Exclusion criteria were major congenital malformation, chromosomal abnormality, congenital infection, cystic periventricular leukomalacia, hemorrhagic parenchymal infarction, and posthemorrhagic ventricular dilatation.ExposuresBirth GA and SES, operationalized at the neighborhood level (using the Scottish Index of Multiple Deprivation), the family level (using parental education and occupation), and subjectively (World Health Organization Quality of Life measure).Main Outcomes and MeasuresBrain volume (85 parcels) and 5 whole-brain cortical morphology measures (gyrification index, thickness, sulcal depth, curvature, surface area) at term-equivalent age (median [range] age, 40 weeks, 5 days [36 weeks, 2 days to 45 weeks, 6 days] and 42 weeks [38 weeks, 2 days to 46 weeks, 1 day] for preterm and full-term infants, respectively).ResultsParticipants were 170 extremely and very preterm infants (95 [55.9%] male; 4 of 166 [2.4%] Asian, 145 of 166 [87.3%] White) and 91 full-term or near-term infants (50 [54.9%] male; 3 of 86 [3.5%] Asian, 78 of 86 [90.7%] White infants) with median (range) birth GAs of 30 weeks, 0 days (22 weeks, 1 day, to 32 weeks, 6 days) and 39 weeks, 4 days (36 weeks, 3 days, to 42 weeks, 1 day), respectively. In fully adjusted models, birth GA was associated with a higher proportion of brain volumes (27 of 85 parcels [31.8%]; β range, −0.20 to 0.24) than neighborhood-level SES (1 of 85 parcels [1.2%]; β = 0.17 [95% CI, −0.16 to 0.50]) or family-level SES (maternal education: 4 of 85 parcels [4.7%]; β range, 0.09 to 0.15; maternal occupation: 1 of 85 parcels [1.2%]; β = 0.06 [95% CI, 0.02 to 0.11] respectively). There were interactions between GA and both family-level and subjective SES measures on regional brain volumes. Birth GA was associated with cortical surface area (β = 0.10 [95% CI, 0.02 to 0.18]) and gyrification index (β = 0.16 [95% CI, 0.07 to 0.25]); no SES measure was associated with cortical measures.Conclusions and RelevanceIn this cohort study of UK infants, birth GA and SES were associated with neonatal brain morphology, but low GA had more widely distributed associations with neonatal brain structure than SES. Further work is warranted to elucidate the mechanisms underlying the association of both GA and SES with early brain development.

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Regional growth and atlasing of the developing human brain

Cited by 187 publications

References 51 publications

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

Association Between Socioeconomic Status and In Utero Fetal Brain Development

Association of Preterm Birth and Socioeconomic Status With Neonatal Brain Structure

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