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Calixto C, Taymourtash A, Karimi D, Snoussi H, Velasco-Annis C, Jaimes C, Gholipour A. Advances in Fetal Brain Imaging. Magn Reson Imaging Clin N Am 2024; 32:459-478. [PMID: 38944434 DOI: 10.1016/j.mric.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2024]
Abstract
Over the last 20 years, there have been remarkable developments in fetal brain MR imaging analysis methods. This article delves into the specifics of structural imaging, diffusion imaging, functional MR imaging, and spectroscopy, highlighting the latest advancements in motion correction, fetal brain development atlases, and the challenges and innovations. Furthermore, this article explores the clinical applications of these advanced imaging techniques in comprehending and diagnosing fetal brain development and abnormalities.
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Affiliation(s)
- Camilo Calixto
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA.
| | - Athena Taymourtash
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Spitalgasse 23, Wien 1090, Austria
| | - Davood Karimi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Haykel Snoussi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Clemente Velasco-Annis
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Camilo Jaimes
- Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA; Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02215, USA
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
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Wang Y, Zhu D, Zhao L, Wang X, Zhang Z, Hu B, Wu D, Zheng W. Profiling cortical morphometric similarity in perinatal brains: Insights from development, sex difference, and inter-individual variation. Neuroimage 2024; 295:120660. [PMID: 38815676 DOI: 10.1016/j.neuroimage.2024.120660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 05/17/2024] [Accepted: 05/28/2024] [Indexed: 06/01/2024] Open
Abstract
The topological organization of the macroscopic cortical networks important for the development of complex brain functions. However, how the cortical morphometric organization develops during the third trimester and whether it demonstrates sexual and individual differences at this particular stage remain unclear. Here, we constructed the morphometric similarity network (MSN) based on morphological and microstructural features derived from multimodal MRI of two independent cohorts (cross-sectional and longitudinal) scanned at 30-44 postmenstrual weeks (PMW). Sex difference and inter-individual variations of the MSN were also examined on these cohorts. The cross-sectional analysis revealed that both network integration and segregation changed in a nonlinear biphasic trajectory, which was supported by the results obtained from longitudinal analysis. The community structure showed remarkable consistency between bilateral hemispheres and maintained stability across PMWs. Connectivity within the primary cortex strengthened faster than that within high-order communities. Compared to females, male neonates showed a significant reduction in the participation coefficient within prefrontal and parietal cortices, while their overall network organization and community architecture remained comparable. Furthermore, by using the morphometric similarity as features, we achieved over 65 % accuracy in identifying an individual at term-equivalent age from images acquired after birth, and vice versa. These findings provide comprehensive insights into the development of morphometric similarity throughout the perinatal cortex, enhancing our understanding of the establishment of neuroanatomical organization during early life.
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Affiliation(s)
- Ying Wang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Dalin Zhu
- Department of Medical Imaging Center, Gansu Provincial Maternity and Child-Care Hospital, Lanzhou, China
| | - Leilei Zhao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Xiaomin Wang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Zhe Zhang
- Institute of Brain Science, Hangzhou Normal University, Hangzhou, China; School of Physics, Hangzhou Normal University, Hangzhou, China
| | - Bin Hu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China; School of Medical Technology, Beijing Institute of Technology, Beijing, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China.
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Kebiri H, Gholipour A, Lin R, Vasung L, Calixto C, Krsnik Ž, Karimi D, Bach Cuadra M. Deep learning microstructure estimation of developing brains from diffusion MRI: A newborn and fetal study. Med Image Anal 2024; 95:103186. [PMID: 38701657 DOI: 10.1016/j.media.2024.103186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 02/06/2024] [Accepted: 04/22/2024] [Indexed: 05/05/2024]
Abstract
Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. Fiber orientation distribution functions (FODs) are a common way of representing the orientation and density of white matter fibers. However, with standard FOD computation methods, accurate estimation requires a large number of measurements that usually cannot be acquired for newborns and fetuses. We propose to overcome this limitation by using a deep learning method to map as few as six diffusion-weighted measurements to the target FOD. To train the model, we use the FODs computed using multi-shell high angular resolution measurements as target. Extensive quantitative evaluations show that the new deep learning method, using significantly fewer measurements, achieves comparable or superior results than standard methods such as Constrained Spherical Deconvolution and two state-of-the-art deep learning methods. For voxels with one and two fibers, respectively, our method shows an agreement rate in terms of the number of fibers of 77.5% and 22.2%, which is 3% and 5.4% higher than other deep learning methods, and an angular error of 10° and 20°, which is 6° and 5° lower than other deep learning methods. To determine baselines for assessing the performance of our method, we compute agreement metrics using densely sampled newborn data. Moreover, we demonstrate the generalizability of the new deep learning method across scanners, acquisition protocols, and anatomy on two clinical external datasets of newborns and fetuses. We validate fetal FODs, successfully estimated for the first time with deep learning, using post-mortem histological data. Our results show the advantage of deep learning in computing the fiber orientation density for the developing brain from in-vivo dMRI measurements that are often very limited due to constrained acquisition times. Our findings also highlight the intrinsic limitations of dMRI for probing the developing brain microstructure.
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Affiliation(s)
- Hamza Kebiri
- CIBM Center for Biomedical Imaging, Switzerland; Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Rizhong Lin
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Lana Vasung
- Department of Pediatrics, Boston Children's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Camilo Calixto
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Željka Krsnik
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Davood Karimi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Switzerland; Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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Huang SM, Cho KH, Chang K, Huang PH, Kuo LW. Altered thalamocortical tract trajectory growth with undisrupted thalamic parcellation pattern in human lissencephaly brain at mid-gestational stage. Neurobiol Dis 2024; 199:106577. [PMID: 38914171 DOI: 10.1016/j.nbd.2024.106577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 06/19/2024] [Accepted: 06/21/2024] [Indexed: 06/26/2024] Open
Abstract
Proper topographically organized neural connections between the thalamus and the cerebral cortex are mandatory for thalamus function. Thalamocortical (TC) fiber growth begins during the embryonic period and completes by the third trimester of gestation, so that human neonates at birth have a thalamus with a near-facsimile of adult functional parcellation. Whether congenital neocortical anomaly (e.g., lissencephaly) affects TC connection in humans is unknown. Here, via diffusion MRI fiber-tractography analysis of long-term formalin-fixed postmortem fetal brain diagnosed as lissencephaly in comparison with an age-matched normal one, we found similar topological patterns of thalamic subregions and of internal capsule parcellated by TC fibers. However, lissencephaly fetal brain showed white matter structural changes, including fewer/less organized TC fibers and optic radiations, and much less cortical plate invasion by TC fibers - particularly around the shallow central sulcus. Diffusion MRI fiber tractography of normal fetal brains at 15, 23, and 26 gestational weeks (GW) revealed dynamic volumetric change of each parcellated thalamic subregion, suggesting coupled developmental progress of the thalamus with the corresponding cortex. Moreover, from GW23 and GW26 normal fetal brains, TC endings in the cortical plate could be delineated to reflect cumulative progressive TC invasion of cortical plate. By contrast, lissencephaly brain showed a dramatic decrease in TC invasion of the cortical plate. Our study thus shows the feasibility of diffusion MRI fiber tractography in postmortem long-term formalin-fixed fetal brains to disclose the developmental progress of TC tracts coordinating with thalamic and neocortical growth both in normal and lissencephaly fetal brains at mid-gestational stage.
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Affiliation(s)
- Sheng-Min Huang
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan, Miaoli County 350, Taiwan
| | - Kuan-Hung Cho
- Department of Electronic Engineering, National United University, Miaoli 360, Taiwan
| | - Koping Chang
- Department of Pathology, National Taiwan University Hospital, Taipei 100, Taiwan; Graduate Institute of Pathology, National Taiwan University College of Medicine, Taipei 100, Taiwan
| | - Pei-Hsin Huang
- Department of Pathology, National Taiwan University Hospital, Taipei 100, Taiwan; Graduate Institute of Pathology, National Taiwan University College of Medicine, Taipei 100, Taiwan.
| | - Li-Wei Kuo
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan, Miaoli County 350, Taiwan; Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei 100, Taiwan.
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Arichi T. Characterizing Large-Scale Human Circuit Development with In Vivo Neuroimaging. Cold Spring Harb Perspect Biol 2024; 16:a041496. [PMID: 38438187 PMCID: PMC11146311 DOI: 10.1101/cshperspect.a041496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Large-scale coordinated patterns of neural activity are crucial for the integration of information in the human brain and to enable complex and flexible human behavior across the life span. Through recent advances in noninvasive functional magnetic resonance imaging (fMRI) methods, it is now possible to study this activity and how it emerges in the living fetal brain across the second half of human gestation. This work has demonstrated that functional activity in the fetal brain has several features in keeping with highly organized networks of activity, which are undergoing a highly programmed and rapid sequence of development before birth, in which long-range connections emerge and core features of the mature functional connectome (such as hub regions and a gradient organization) are established. In this review, the findings of these studies are summarized, their relationship to the known changes in developmental neurobiology is considered, and considerations for future work in the context of limitations to the fMRI approach are presented.
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Affiliation(s)
- Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, New Hunt's House, Guy's Campus, London SE1 1UL, United Kingdom
- Children's Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London SE1 7EH, United Kingdom
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Wang T, Huang X, Dai LX, Zhan KM, Wang J. Functional connectivity alterations in the thalamus among patients with bronchial asthma. Front Neurol 2024; 15:1378362. [PMID: 38798710 PMCID: PMC11116975 DOI: 10.3389/fneur.2024.1378362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 04/15/2024] [Indexed: 05/29/2024] Open
Abstract
Objective Bronchial Asthma (BA) is a common chronic respiratory disease worldwide. Earlier research has demonstrated abnormal functional connectivity (FC) in multiple cognition-related cortices in asthma patients. The thalamus (Thal) serves as a relay center for transmitting sensory signals, yet the modifications in the thalamic FC among individuals with asthma remain uncertain. This research employed the resting-state functional connectivity (rsFC) approach to explore alterations in thalamic functional connectivity among individuals with BA. Patients and methods After excluding participants who did not meet the criteria, this study finally included 31 patients with BA, with a gender distribution of 16 males and 15 females. Subsequently, we recruited 31 healthy control participants (HC) matched for age, gender, and educational background. All participants underwent the Montreal Cognitive Assessment (MoCA) and the Hamilton Depression Rating Scale (HAMD) assessment. Following this, both groups underwent head magnetic resonance imaging scans, and resting-state functional magnetic resonance imaging (rs-fMRI) data was collected. Based on the AAL (Automated Anatomical Labeling) template, the bilateral thalamic regions were used as seed points (ROI) for subsequent rsFC research. Pearson correlation analysis was used to explore the relationship between thalamic functional connectivity and neuropsychological scales in both groups. After controlling for potential confounding factors such as age, gender, intelligence, and emotional level, a two-sample t-test was further used to explore differences in thalamic functional connectivity between the two groups of participants. Result Compared to the HC group, the BA group demonstrated heightened functional connectivity (FC) between the left thalamus and the left cerebellar posterior lobe (CPL), left postcentral gyrus (PCG), and right superior frontal gyrus (SFG). Concurrently, there was a decrease in FC with both the Lentiform Nucleus (LN) and the left corpus callosum (CC). Performing FC analysis with the right thalamus as the Region of Interest (ROI) revealed an increase in FC between the right thalamus and the right SFG as well as the left CPL. Conversely, a decrease in FC was observed between the right thalamus and the right LN as well as the left CC. Conclusion In our study, we have verified the presence of aberrant FC patterns in the thalamus of BA patients. When compared to HCs, BA patients exhibit aberrant alterations in FC between the thalamus and various brain areas connected to vision, hearing, emotional regulation, cognitive control, somatic sensations, and wakefulness. This provides further confirmation of the substantial role played by the thalamus in the advancement of BA.
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Affiliation(s)
- Tao Wang
- Jiangxi Medical College, Nanchang University, Nanchang, China
- Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Xin Huang
- Department of Ophthalmology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Li-xue Dai
- Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Kang-min Zhan
- Jiangxi Medical College, Nanchang University, Nanchang, China
- Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Jun Wang
- Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
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Franco F, Chifa M, Politimou N. Home Musical Activities Boost Premature Infants' Language Development. CHILDREN (BASEL, SWITZERLAND) 2024; 11:542. [PMID: 38790537 PMCID: PMC11120229 DOI: 10.3390/children11050542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/21/2024] [Accepted: 04/03/2024] [Indexed: 05/26/2024]
Abstract
Infants born prematurely are considered at risk for language development delay and impairments. Using online parental reports, the present study investigated the influence of early musical experience in the home environment (Music@Home Infant Questionnaire) on language development (MacArthur-Bates Communicative Development Inventory) while controlling for general enrichment at home (Stim-Q Cognitive Home Environment Questionnaire) and perinatal post-traumatic stress disorder (Perinatal PTSD Questionnaire). Caregivers of 117 infants between 8 and 18 months of age (corrected age) without reported developmental difficulties completed an online survey. Results revealed that the musical home environment significantly predicted outcomes in reported infants' receptive vocabulary and gestural communication, independently from infants' corrected age and general enrichment of home activities. These findings constitute the first evidence that an enriched musical experience can enhance the development of early communication skills in a population at risk for language delays, namely infants born prematurely, opening the path for future intervention research in home and/or early childcare settings. Given that the majority of participants in this study were highly educated and from socioeconomically stable backgrounds, considerations regarding the generalizability of these results are discussed.
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Affiliation(s)
- Fabia Franco
- Psychology Department, Faculty of Science and Technology, Middlesex University, London NW4 4BT, UK;
| | - Maria Chifa
- Psychology Department, Faculty of Science and Technology, Middlesex University, London NW4 4BT, UK;
| | - Nina Politimou
- Department of Psychology and Human Development, IOE Faculty of Education and Society, University College London, London WC1H 0AA, UK
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Calixto C, Soldatelli MD, Jaimes C, Warfield SK, Gholipour A, Karimi D. A detailed spatio-temporal atlas of the white matter tracts for the fetal brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.26.590815. [PMID: 38712296 PMCID: PMC11071632 DOI: 10.1101/2024.04.26.590815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
This study presents the construction of a comprehensive spatiotemporal atlas detailing the development of white matter tracts in the fetal brain using diffusion magnetic resonance imaging (dMRI). Our research leverages data collected from fetal MRI scans conducted between 22 and 37 weeks of gestation, capturing the dynamic changes in the brain's microstructure during this critical period. The atlas includes 60 distinct white matter tracts, including commissural, projection, and association fibers. We employed advanced fetal dMRI processing techniques and tractography to map and characterize the developmental trajectories of these tracts. Our findings reveal that the development of these tracts is characterized by complex patterns of fractional anisotropy (FA) and mean diffusivity (MD), reflecting key neurodevelopmental processes such as axonal growth, involution of the radial-glial scaffolding, and synaptic pruning. This atlas can serve as a useful resource for neuroscience research and clinical practice, improving our understanding of the fetal brain and potentially aiding in the early diagnosis of neurodevelopmental disorders. By detailing the normal progression of white matter tract development, the atlas can be used as a benchmark for identifying deviations that may indicate neurological anomalies or predispositions to disorders.
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Wang X, de Groot ER, Tataranno ML, van Baar A, Lammertink F, Alderliesten T, Long X, Benders MJNL, Dudink J. Machine Learning-Derived Active Sleep as an Early Predictor of White Matter Development in Preterm Infants. J Neurosci 2024; 44:e1024232023. [PMID: 38124010 PMCID: PMC10860564 DOI: 10.1523/jneurosci.1024-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/15/2023] [Accepted: 09/19/2023] [Indexed: 12/23/2023] Open
Abstract
White matter dysmaturation is commonly seen in preterm infants admitted to the neonatal intensive care unit (NICU). Animal research has shown that active sleep is essential for early brain plasticity. This study aimed to determine the potential of active sleep as an early predictor for subsequent white matter development in preterm infants. Using heart and respiratory rates routinely monitored in the NICU, we developed a machine learning-based automated sleep stage classifier in a cohort of 25 preterm infants (12 females). The automated classifier was subsequently applied to a study cohort of 58 preterm infants (31 females) to extract active sleep percentage over 5-7 consecutive days during 29-32 weeks of postmenstrual age. Each of the 58 infants underwent high-quality T2-weighted magnetic resonance brain imaging at term-equivalent age, which was used to measure the total white matter volume. The association between active sleep percentage and white matter volume was examined using a multiple linear regression model adjusted for potential confounders. Using the automated classifier with a superior sleep classification performance [mean area under the receiver operating characteristic curve (AUROC) = 0.87, 95% CI 0.83-0.92], we found that a higher active sleep percentage during the preterm period was significantly associated with an increased white matter volume at term-equivalent age [β = 0.31, 95% CI 0.09-0.53, false discovery rate (FDR)-adjusted p-value = 0.021]. Our results extend the positive association between active sleep and early brain development found in animal research to human preterm infants and emphasize the potential benefit of sleep preservation in the NICU setting.
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Affiliation(s)
- Xiaowan Wang
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
| | - Eline R de Groot
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
| | - Maria Luisa Tataranno
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| | - Anneloes van Baar
- Child and Adolescent Studies, Utrecht University, Utrecht 3584 CS, The Netherlands
| | - Femke Lammertink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
| | - Thomas Alderliesten
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| | - Xi Long
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven 5612 AZ, The Netherlands
| | - Manon J N L Benders
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht 3584 EA, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht 3584 CX, The Netherlands
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Xiao J, Sun C, Chen R, Zhao Z, Wang G, Wu D. Reproducibility of Diffusion MRI-Based Tractography in the Fetal Brain. J Magn Reson Imaging 2024. [PMID: 38284561 DOI: 10.1002/jmri.29253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 01/09/2024] [Accepted: 01/11/2024] [Indexed: 01/30/2024] Open
Abstract
BACKGROUND Tractography based on diffusion MRI (dMRI) is a useful tool to study white matter of the developing brain. However, its application in fetal brains is limited due to motion artifacts and low resolution of in utero dMRI, leading to reduced reliability, which was scarcely investigated in previous studies. PURPOSE To identify reliably traceable fibers in fetal brains and assess whether reproducibility varies with gestational age (GA) and varies between brain regions. STUDY TYPE Prospective cohort study. SUBJECTS A total of 44 healthy fetuses with GAs between 25 and 37 (31 ± 6). FIELD STRENGTH/SEQUENCE 3-T, diffusion-weighted echo-planar imaging sequence (2-5 repeated dMRI scans within the same session per subject). ASSESSMENT We fitted dMRI with constrained spherical deconvolution model and conducted tractography on eight fibers. We extracted volume, fractional anisotropy, and fiber count for each fiber and assessed the reproducibility of these metrics between repeated scans within each subject. Data were divided into two age-based subgroups (≤30 weeks, N = 28, and >30 weeks, N = 16) for further tests. STATISTICAL TESTS The reproducibility were compared between fibers by analysis of variance and two-sample t tests. Multiple comparisons were corrected by the false discovery rate (5% was accepted). RESULTS The reproducibility of the anterior thalamic radiation, inferior longitudinal fasciculus (ILF), genu of the corpus callosum (GCC), and body of the corpus callosum (BCC) significantly decreased with advancing GA (correlation coefficient = 0.525-0.823), as confirmed by group comparisons between fetuses in early GA (≤30 weeks) and late GA (>30 weeks) groups. Corticospinal tract, inferior fronto-occipital fasciculus, and GCC showed high reproducibility for fiber count (weighted dice average = 0.846 vs. 0.814), while BCC and ILF exhibited the lowest reproducibility in both age groups. DATA CONCLUSION The study indicates that the reliability of fetal brain tractography depends on GA and varies among different fibers. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Jiaxin Xiao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Cong Sun
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Ruike Chen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
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Calixto C, Machado-Rivas F, Cortes-Albornoz MC, Karimi D, Velasco-Annis C, Afacan O, Warfield SK, Gholipour A, Jaimes C. Characterizing microstructural development in the fetal brain using diffusion MRI from 23 to 36 weeks of gestation. Cereb Cortex 2024; 34:bhad409. [PMID: 37948665 PMCID: PMC10793585 DOI: 10.1093/cercor/bhad409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/09/2023] [Accepted: 10/10/2023] [Indexed: 11/12/2023] Open
Abstract
We utilized motion-corrected diffusion tensor imaging (DTI) to evaluate microstructural changes in healthy fetal brains during the late second and third trimesters. Data were derived from fetal magnetic resonance imaging scans conducted as part of a prospective study spanning from 2013 March to 2019 May. The study included 44 fetuses between the gestational ages (GAs) of 23 and 36 weeks. We reconstructed fetal brain DTI using a motion-tracked slice-to-volume registration framework. Images were segmented into 14 regions of interest (ROIs) through label propagation using a fetal DTI atlas, with expert refinement. Statistical analysis involved assessing changes in fractional anisotropy (FA) and mean diffusivity (MD) throughout gestation using mixed-effects models, and identifying points of change in trajectory for ROIs with nonlinear trends. Results showed significant GA-related changes in FA and MD in all ROIs except in the thalamus' FA and corpus callosum's MD. Hemispheric asymmetries were found in the FA of the periventricular white matter (pvWM), intermediate zone, and subplate and in the MD of the ganglionic eminence and pvWM. This study provides valuable insight into the normal patterns of development of MD and FA in the fetal brain. These changes are closely linked with cytoarchitectonic changes and display indications of early functional specialization.
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Affiliation(s)
- Camilo Calixto
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Fedel Machado-Rivas
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Maria C Cortes-Albornoz
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Davood Karimi
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Clemente Velasco-Annis
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Onur Afacan
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Camilo Jaimes
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, United States
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12
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Zhang L, Li P, Ge Q, Sun Z, Cai J, Xiao C, Yu C, Nosarti C, Liao J, Liu Z. Maternal Prenatal Depressive Symptoms and Fetal Growth During the Critical Rapid Growth Stage. JAMA Netw Open 2023; 6:e2346018. [PMID: 38048129 PMCID: PMC10696489 DOI: 10.1001/jamanetworkopen.2023.46018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 10/23/2023] [Indexed: 12/05/2023] Open
Abstract
Importance Fetal growth in the critical rapid growth stage (CRGS) before delivery, approximately between 30 to 37 gestational weeks, carries significant implications for subsequent overweight, obesity, and arterial health. Previous evidence has demonstrated the association between maternal depressive symptoms and fetal growth trajectories from early to late pregnancy, but there remains limited understanding of the association of these symptoms with the longitudinal fetal growth change within the CRGS. Objective To investigate the association between maternal depressive symptoms and fetal growth during the CRGS before delivery. Design, Setting, and Participants This prospective birth cohort study was conducted from January 2018 to December 2020. Volunteer pregnant women were enrolled in their first trimester of prenatal visits. Women with severe disease before pregnancy and multiple births, fetuses with congenital anomalies, and preterm or postterm births were excluded. This multicenter study was based in 13 hospitals covering 81 counties across 12 cities in Sichuan Province, China. Follow-up visits were performed at the second trimester, the third trimester, and 24 hours after delivery. The analysis was conducted from January to May 2023. Exposures Maternal depressive symptoms, as a continuous variable, measured by the Edinburgh Postpartum Depression Scale (EPDS) at a median gestational week of 24 (range, 14 to 27) weeks of gestation. A higher score on the EPDS indicates worse depressive symptoms. Main Outcomes and Measures The main outcomes included ultrasonography-measured biparietal diameter (BPD), femur length (FL), and abdominal circumference (AC), along with calculated estimated fetal weight (EFW). These parameters were evaluated longitudinally at a median gestational week of 30 (range, 28 to 32) and 37 (range, 35 to 39) weeks. Linear mixed models were used to estimate the associations between maternal depressive symptoms and fetal growth parameters. Results A total of 2676 mother-offspring dyads were included, in which the mean (SD) age of mothers was 28.0 (4.4) years, and 1294 (48.4%) of the offspring were female. The median (IQR) maternal EPDS score was 5.0 (4.0 to 9.0). After adjustment for confounders, a significant correlation was found between a higher score of depressive symptoms in mothers and a slower rate of fetal growth across FL (β = -0.40; 95% CI, -0.58 to -0.22), AC (β = -1.97; 95% CI, -2.90 to -1.03), and EFW (β = -50.11; 95% CI, -68.46 to -31.75). These associations were stronger in female fetuses or those with better family socioeconomic conditions. Conclusions and Relevance In this prospective cohort study, maternal depressive symptoms were associated with slower fetal growth rate in the CRGS before delivery. Early screening for depressive disorders in pregnant women appears to be essential for fetal growth and later health.
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Affiliation(s)
- Lu Zhang
- Department of Maternal and Child Health, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ping Li
- Department of Maternal and Child Health, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiaoyue Ge
- Department of Maternal and Child Health, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Zeyuan Sun
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, United Kingdom
| | - Jiarui Cai
- Department of Maternal and Child Health, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chenghan Xiao
- Department of Maternal and Child Health, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chuan Yu
- Department of Maternal and Child Health, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chiara Nosarti
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, United Kingdom
| | - Jiaqiang Liao
- Department of Maternal and Child Health, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhenmi Liu
- Department of Maternal and Child Health, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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13
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Cook KM, De Asis-Cruz J, Kim JH, Basu SK, Andescavage N, Murnick J, Spoehr E, Liggett M, du Plessis AJ, Limperopoulos C. Experience of early-life pain in premature infants is associated with atypical cerebellar development and later neurodevelopmental deficits. BMC Med 2023; 21:435. [PMID: 37957651 PMCID: PMC10644599 DOI: 10.1186/s12916-023-03141-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 10/30/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Infants born very and extremely premature (V/EPT) are at a significantly elevated risk for neurodevelopmental disorders and delays even in the absence of structural brain injuries. These risks may be due to earlier-than-typical exposure to the extrauterine environment, and its bright lights, loud noises, and exposures to painful procedures. Given the relative underdeveloped pain modulatory responses in these infants, frequent pain exposures may confer risk for later deficits. METHODS Resting-state fMRI scans were collected at term equivalent age from 148 (45% male) infants born V/EPT and 99 infants (56% male) born at term age. Functional connectivity analyses were performed between functional regions correlating connectivity to the number of painful skin break procedures in the NICU, including heel lances, venipunctures, and IV placements. Subsequently, preterm infants returned at 18 months, for neurodevelopmental follow-up and completed assessments for autism risk and general neurodevelopment. RESULTS We observed that V/EPT infants exhibit pronounced hyperconnectivity within the cerebellum and between the cerebellum and both limbic and paralimbic regions correlating with the number of skin break procedures. Moreover, skin breaks were strongly associated with autism risk, motor, and language scores at 18 months. Subsample analyses revealed that the same cerebellar connections strongly correlating with breaks at term age were associated with language dysfunction at 18 months. CONCLUSIONS These results have significant implications for the clinical care of preterm infants undergoing painful exposures during routine NICU care, which typically occurs without anesthesia. Repeated pain exposures appear to have an increasingly detrimental effect on brain development during a critical period, and effects continue to be seen even 18 months later.
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Affiliation(s)
- Kevin M Cook
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Josepheen De Asis-Cruz
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Jung-Hoon Kim
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Sudeepta K Basu
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Nickie Andescavage
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Jonathan Murnick
- Dept. of Diagnostic Imaging & Radiology, Children's National Hospital, 111 Michigan Ave. NW, Washington, D.C, 20010, USA
| | - Emma Spoehr
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Melissa Liggett
- Division of Psychology, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC, 20010, USA
| | - Adré J du Plessis
- Prenatal Pediatrics Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Catherine Limperopoulos
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA.
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14
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Namburete AIL, Papież BW, Fernandes M, Wyburd MK, Hesse LS, Moser FA, Ismail LC, Gunier RB, Squier W, Ohuma EO, Carvalho M, Jaffer Y, Gravett M, Wu Q, Lambert A, Winsey A, Restrepo-Méndez MC, Bertino E, Purwar M, Barros FC, Stein A, Noble JA, Molnár Z, Jenkinson M, Bhutta ZA, Papageorghiou AT, Villar J, Kennedy SH. Normative spatiotemporal fetal brain maturation with satisfactory development at 2 years. Nature 2023; 623:106-114. [PMID: 37880365 PMCID: PMC10620088 DOI: 10.1038/s41586-023-06630-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 09/08/2023] [Indexed: 10/27/2023]
Abstract
Maturation of the human fetal brain should follow precisely scheduled structural growth and folding of the cerebral cortex for optimal postnatal function1. We present a normative digital atlas of fetal brain maturation based on a prospective international cohort of healthy pregnant women2, selected using World Health Organization recommendations for growth standards3. Their fetuses were accurately dated in the first trimester, with satisfactory growth and neurodevelopment from early pregnancy to 2 years of age4,5. The atlas was produced using 1,059 optimal quality, three-dimensional ultrasound brain volumes from 899 of the fetuses and an automated analysis pipeline6-8. The atlas corresponds structurally to published magnetic resonance images9, but with finer anatomical details in deep grey matter. The between-study site variability represented less than 8.0% of the total variance of all brain measures, supporting pooling data from the eight study sites to produce patterns of normative maturation. We have thereby generated an average representation of each cerebral hemisphere between 14 and 31 weeks' gestation with quantification of intracranial volume variability and growth patterns. Emergent asymmetries were detectable from as early as 14 weeks, with peak asymmetries in regions associated with language development and functional lateralization between 20 and 26 weeks' gestation. These patterns were validated in 1,487 three-dimensional brain volumes from 1,295 different fetuses in the same cohort. We provide a unique spatiotemporal benchmark of fetal brain maturation from a large cohort with normative postnatal growth and neurodevelopment.
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Affiliation(s)
- Ana I L Namburete
- Oxford Machine Learning in Neuroimaging Laboratory, Department of Computer Science, University of Oxford, Oxford, UK.
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
- Department of Engineering Science, University of Oxford, Oxford, UK.
| | - Bartłomiej W Papież
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Michelle Fernandes
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- MRC Lifecourse Epidemiology Centre, Human Development and Health Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK
- Oxford Maternal and Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK
| | - Madeleine K Wyburd
- Oxford Machine Learning in Neuroimaging Laboratory, Department of Computer Science, University of Oxford, Oxford, UK
| | - Linde S Hesse
- Oxford Machine Learning in Neuroimaging Laboratory, Department of Computer Science, University of Oxford, Oxford, UK
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - Felipe A Moser
- Oxford Machine Learning in Neuroimaging Laboratory, Department of Computer Science, University of Oxford, Oxford, UK
| | - Leila Cheikh Ismail
- Department of Clinical Nutrition and Dietetics, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
| | - Robert B Gunier
- Center for Environmental Research and Children's Health, School of Public Health, University of California, Berkeley, CA, USA
| | - Waney Squier
- Department of Neuropathology, John Radcliffe Hospital, Oxford, UK
| | - Eric O Ohuma
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- Maternal, Adolescent, Reproductive and Child Health Centre, London School of Hygiene and Tropical Medicine, London, UK
| | - Maria Carvalho
- Department of Obstetrics and Gynaecology, Faculty of Health Sciences, Aga Khan University Hospital, Nairobi, Kenya
| | - Yasmin Jaffer
- Department of Family and Community Health, Ministry of Health, Muscat, Sultanate of Oman
| | - Michael Gravett
- Departments of Obstetrics and Gynecology and of Global Health, University of Washington, Seattle, WA, USA
| | - Qingqing Wu
- School of Public Health, Peking University, Beijing, China
| | - Ann Lambert
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- Oxford Maternal and Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK
| | - Adele Winsey
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
| | | | - Enrico Bertino
- Dipartimento di Scienze Pediatriche e dell' Adolescenza, SCDU Neonatologia, Universita di Torino, Turin, Italy
| | - Manorama Purwar
- Nagpur INTERGROWTH-21st Research Centre, Ketkar Hospital, Nagpur, India
| | - Fernando C Barros
- Programa de Pós-Graduação em Saúde e Comportamento, Universidade Católica de Pelotas, Pelotas, Brazil
| | - Alan Stein
- Department of Psychiatry, University of Oxford, Oxford, UK
- African Health Research Institute, KwaZulu-Natal, South Africa
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
| | - J Alison Noble
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - Zoltán Molnár
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Australian Institute for Machine Learning, Department of Computer Science, University of Adelaide, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Zulfiqar A Bhutta
- Center for Global Child Health, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Aris T Papageorghiou
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- Oxford Maternal and Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK
| | - José Villar
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- Oxford Maternal and Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK
| | - Stephen H Kennedy
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- Oxford Maternal and Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK
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15
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Ahmadzadeh E, Polglase GR, Stojanovska V, Herlenius E, Walker DW, Miller SL, Allison BJ. Does fetal growth restriction induce neuropathology within the developing brainstem? J Physiol 2023; 601:4667-4689. [PMID: 37589339 PMCID: PMC10953350 DOI: 10.1113/jp284191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Accepted: 08/04/2023] [Indexed: 08/18/2023] Open
Abstract
Fetal growth restriction (FGR) is a complex obstetric issue describing a fetus that does not reach its genetic growth potential. The primary cause of FGR is placental dysfunction resulting in chronic fetal hypoxaemia, which in turn causes altered neurological, cardiovascular and respiratory development, some of which may be pathophysiological, particularly for neonatal life. The brainstem is the critical site of cardiovascular, respiratory and autonomic control, but there is little information describing how chronic hypoxaemia and the resulting FGR may affect brainstem neurodevelopment. This review provides an overview of the brainstem-specific consequences of acute and chronic hypoxia, and what is known in FGR. In addition, we discuss how brainstem structural alterations may impair functional control of the cardiovascular and respiratory systems. Finally, we highlight the clinical and translational findings of the potential roles of the brainstem in maintaining cardiorespiratory adaptation in the transition from fetal to neonatal life under normal conditions and in response to the pathological environment that arises during development in growth-restricted infants. This review emphasises the crucial role that the brainstem plays in mediating cardiovascular and respiratory responses during fetal and neonatal life. We assess whether chronic fetal hypoxaemia might alter structure and function of the brainstem, but this also serves to highlight knowledge gaps regarding FGR and brainstem development.
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Affiliation(s)
- Elham Ahmadzadeh
- The Ritchie CentreHudson Institute of Medical ResearchClaytonVictoriaAustralia
- Department of Obstetrics and GynaecologyMonash UniversityClaytonVictoriaAustralia
| | - Graeme R. Polglase
- The Ritchie CentreHudson Institute of Medical ResearchClaytonVictoriaAustralia
- Department of Obstetrics and GynaecologyMonash UniversityClaytonVictoriaAustralia
| | - Vanesa Stojanovska
- The Ritchie CentreHudson Institute of Medical ResearchClaytonVictoriaAustralia
- Department of Obstetrics and GynaecologyMonash UniversityClaytonVictoriaAustralia
| | - Eric Herlenius
- Department of Women's and Children's HealthKarolinska InstitutetSolnaSweden
- Astrid Lindgren Children´s HospitalKarolinska University Hospital StockholmSolnaSweden
| | - David W. Walker
- The Ritchie CentreHudson Institute of Medical ResearchClaytonVictoriaAustralia
- Neurodevelopment in Health and Disease Research Program, School of Health and Biomedical SciencesRoyal Melbourne Institute of Technology (RMIT)MelbourneVictoriaAustralia
| | - Suzanne L. Miller
- The Ritchie CentreHudson Institute of Medical ResearchClaytonVictoriaAustralia
- Department of Obstetrics and GynaecologyMonash UniversityClaytonVictoriaAustralia
| | - Beth J. Allison
- The Ritchie CentreHudson Institute of Medical ResearchClaytonVictoriaAustralia
- Department of Obstetrics and GynaecologyMonash UniversityClaytonVictoriaAustralia
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16
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Zheng W, Wang X, Liu T, Hu B, Wu D. Preterm-birth alters the development of nodal clustering and neural connection pattern in brain structural network at term-equivalent age. Hum Brain Mapp 2023; 44:5372-5386. [PMID: 37539754 PMCID: PMC10543115 DOI: 10.1002/hbm.26442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 08/05/2023] Open
Abstract
Preterm-born neonates are prone to impaired neurodevelopment that may be associated with disrupted whole-brain structural connectivity. The present study aimed to investigate the longitudinal developmental pattern of the structural network from preterm birth to term-equivalent age (TEA), and identify how prematurity influences the network topological organization and properties of local brain regions. Multi-shell diffusion-weighted MRI of 28 preterm-born scanned a short time after birth (PB-AB) and at TEA (PB-TEA), and 28 matched term-born (TB) neonates in the Developing Human Connectome Project (dHCP) were used to construct structural networks through constrained spherical deconvolution tractography. Structural network development from preterm birth to TEA showed reduced shortest path length, clustering coefficient, and modularity, and more "connector" hubs linking disparate communities. Furthermore, compared with TB newborns, premature birth significantly altered the nodal properties (i.e., clustering coefficient, within-module degree, and participation coefficient) in the limbic/paralimbic, default-mode, and subcortical systems but not global topology at TEA, and we were able to distinguish the PB from TB neonates at TEA based on the nodal properties with 96.43% accuracy. Our findings demonstrated a topological reorganization of the structural network occurs during the perinatal period that may prioritize the optimization of global network organization to form a more efficient architecture; and local topology was more vulnerable to premature birth-related factors than global organization of the structural network, which may underlie the impaired cognition and behavior in PB infants.
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Affiliation(s)
- Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and EngineeringLanzhou UniversityLanzhouChina
| | - Xiaomin Wang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and EngineeringLanzhou UniversityLanzhouChina
| | - Tingting Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument ScienceZhejiang UniversityHangzhouChina
| | - Bin Hu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and EngineeringLanzhou UniversityLanzhouChina
- School of Medical TechnologyBeijing Institute of TechnologyBeijingChina
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological SciencesChinese Academy of SciencesShanghaiChina
- Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of SemiconductorsChinese Academy of SciencesLanzhouChina
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument ScienceZhejiang UniversityHangzhouChina
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17
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Morin C, Bokobza C, Fleiss B, Hill-Yardin EL, Van Steenwinckel J, Gressens P. Preterm Birth by Cesarean Section: The Gut-Brain Axis, a Key Regulator of Brain Development. Dev Neurosci 2023; 46:179-187. [PMID: 37717575 DOI: 10.1159/000534124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 09/11/2023] [Indexed: 09/19/2023] Open
Abstract
Understanding the long-term functional implications of gut microbial communities during the perinatal period is a bourgeoning area of research. Numerous studies have revealed the existence of a "gut-brain axis" and the impact of an alteration of gut microbiota composition in brain diseases. Recent research has highlighted how gut microbiota could affect brain development and behavior. Many factors in early life such as the mode of delivery or preterm birth could lead to disturbance in the assembly and maturation of gut microbiota. Notably, global rates of cesarean sections (C-sections) have increased in recent decades and remain important when considering premature delivery. Both preterm birth and C-sections are associated with an increased risk of neurodevelopmental disorders such as autism spectrum disorders, with neuroinflammation a major risk factor. In this review, we explore links between preterm birth by C-sections, gut microbiota alteration, and neuroinflammation. We also highlight C-sections as a risk factor for developmental disorders due to alterations in the microbiome.
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Affiliation(s)
- Cécile Morin
- Université Paris Cité, Inserm, NeuroDiderot, Paris, France
- Hôpital Robert Debré, Assistance Publique, Hôpitaux de Paris (APHP), Paris, France
| | - Cindy Bokobza
- Université Paris Cité, Inserm, NeuroDiderot, Paris, France
| | - Bobbi Fleiss
- Université Paris Cité, Inserm, NeuroDiderot, Paris, France
- School of Health and Biomedical Sciences, STEM College, RMIT University, Bundoora, Victoria, Australia
| | - Elisa L Hill-Yardin
- School of Health and Biomedical Sciences, STEM College, RMIT University, Bundoora, Victoria, Australia
| | | | - Pierre Gressens
- Université Paris Cité, Inserm, NeuroDiderot, Paris, France
- Hôpital Robert Debré, Assistance Publique, Hôpitaux de Paris (APHP), Paris, France
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18
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Nivins S, Kennedy E, McKinlay C, Thompson B, Harding JE. Size at birth predicts later brain volumes. Sci Rep 2023; 13:12446. [PMID: 37528153 PMCID: PMC10393952 DOI: 10.1038/s41598-023-39663-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 07/28/2023] [Indexed: 08/03/2023] Open
Abstract
We aimed to investigate whether gestation at birth, birth weight, and head circumference at birth are still associated with brain volume and white matter microstructure at 9-10 years in children born late-preterm and at term. One hundred and eleven children born at ≥ 36 weeks gestation from the CHYLD Study cohort underwent brain magnetic resonance imaging at 9 to 10 years. Images were analysed using FreeSurfer for volumetric data and tract-based spatial statistics for diffusion data. Of the cohort, 101 children were included for volumetric analysis [boys, 49(49%); median age, 9.5 (range: 8.9-12.4) years]. Shorter gestation at birth, lower birthweight, and smaller birth head circumference were associated with smaller brain volumes at 9 to 10 years, both globally and regionally. Amongst the perinatal factors studied, head circumference at birth was the strongest predictor of later brain volumes. Gestation at birth and absolute birthweight were not associated with diffusion metrics of white matter skeleton. However, lower birthweight z-score was associated with higher fractional anisotropy and lower radial diffusivity. Our findings suggest that even in children born late preterm and at term, growth before birth and timing of birth are still associated with brain development in mid-childhood.
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Affiliation(s)
- Samson Nivins
- Liggins Institute, University of Auckland, Building 503, Level 2, 85 Park Road, Auckland, New Zealand
| | - Eleanor Kennedy
- Liggins Institute, University of Auckland, Building 503, Level 2, 85 Park Road, Auckland, New Zealand
| | - Christopher McKinlay
- Liggins Institute, University of Auckland, Building 503, Level 2, 85 Park Road, Auckland, New Zealand
- Kidz First Neonatal Care, Counties Manukau Health, Auckland, New Zealand
| | - Benjamin Thompson
- Liggins Institute, University of Auckland, Building 503, Level 2, 85 Park Road, Auckland, New Zealand
- School of Optometry and Vision Science, University of Waterloo, Waterloo, ON, Canada
- Centre for Eye and Vision Research, The Hong Kong Polytechnic University, 17W Science Park, Shatin, Hong Kong
| | - Jane E Harding
- Liggins Institute, University of Auckland, Building 503, Level 2, 85 Park Road, Auckland, New Zealand.
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19
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Abstract
All mammalian cell membranes contain cholesterol to maintain membrane integrity. The transport of this hydrophobic lipid is mediated by lipoproteins. Cholesterol is especially enriched in the brain, particularly in synaptic and myelin membranes. Aging involves changes in sterol metabolism in peripheral organs and also in the brain. Some of those alterations have the potential to promote or to counteract the development of neurodegenerative diseases during aging. Here, we summarize the current knowledge of general principles of sterol metabolism in humans and mice, the most widely used model organism in biomedical research. We discuss changes in sterol metabolism that occur in the aged brain and highlight recent developments in cell type-specific cholesterol metabolism in the fast-growing research field of aging and age-related diseases, focusing on Alzheimer's disease. We propose that cell type-specific cholesterol handling and the interplay between cell types critically influence age-related disease processes.
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Affiliation(s)
- Gesine Saher
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany;
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20
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Kebiri H, Gholipour A, Vasung L, Krsnik Ž, Karimi D, Cuadra MB. Deep learning microstructure estimation of developing brains from diffusion MRI: a newborn and fetal study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.01.547351. [PMID: 37425859 PMCID: PMC10327173 DOI: 10.1101/2023.07.01.547351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. Fiber orientation distribution functions (FODs) are a common way of representing the orientation and density of white matter fibers. However, with standard FOD computation methods, accurate estimation of FODs requires a large number of measurements that usually cannot be acquired for newborns and fetuses. We propose to overcome this limitation by using a deep learning method to map as few as six diffusion-weighted measurements to the target FOD. To train the model, we use the FODs computed using multi-shell high angular resolution measurements as target. Extensive quantitative evaluations show that the new deep learning method, using significantly fewer measurements, achieves comparable or superior results to standard methods such as Constrained Spherical Deconvolution. We demonstrate the generalizability of the new deep learning method across scanners, acquisition protocols, and anatomy on two clinical datasets of newborns and fetuses. Additionally, we compute agreement metrics within the HARDI newborn dataset, and validate fetal FODs with post-mortem histological data. The results of this study show the advantage of deep learning in inferring the microstructure of the developing brain from in-vivo dMRI measurements that are often very limited due to subject motion and limited acquisition times, but also highlight the intrinsic limitations of dMRI in the analysis of the developing brain microstructure. These findings, therefore, advocate for the need for improved methods that are tailored to studying the early development of human brain.
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Affiliation(s)
- Hamza Kebiri
- CIBM Center for Biomedical Imaging, Switzerland
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lana Vasung
- Department of Pediatrics, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Željka Krsnik
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Davood Karimi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Switzerland
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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21
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Mallela AN, Deng H, Gholipour A, Warfield SK, Goldschmidt E. Heterogeneous growth of the insula shapes the human brain. Proc Natl Acad Sci U S A 2023; 120:e2220200120. [PMID: 37279278 PMCID: PMC10268209 DOI: 10.1073/pnas.2220200120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 04/13/2023] [Indexed: 06/08/2023] Open
Abstract
The human cerebrum consists of a precise and stereotyped arrangement of lobes, primary gyri, and connectivity that underlies human cognition [P. Rakic, Nat. Rev. Neurosci. 10, 724-735 (2009)]. The development of this arrangement is less clear. Current models explain individual primary gyrification but largely do not account for the global configuration of the cerebral lobes [T. Tallinen, J. Y. Chung, J. S. Biggins, L. Mahadevan, Proc. Natl. Acad. Sci. U.S.A. 111, 12667-12672 (2014) and D. C. Van Essen, Nature 385, 313-318 (1997)]. The insula, buried in the depths of the Sylvian fissure, is unique in terms of gyral anatomy and size. Here, we quantitatively show that the insula has unique morphology and location in the cerebrum and that these key differences emerge during fetal development. Finally, we identify quantitative differences in developmental migration patterns to the insula that may underlie these differences. We calculated morphologic data in the insula and other lobes in adults (N = 107) and in an in utero fetal brain atlas (N = 81 healthy fetuses). In utero, the insula grows an order of magnitude slower than the other lobes and demonstrates shallower sulci, less curvature, and less surface complexity both in adults and progressively throughout fetal development. Spherical projection analysis demonstrates that the lenticular nuclei obstruct 60 to 70% of radial pathways from the ventricular zone (VZ) to the insula, forcing a curved migration to the insula in contrast to a direct radial pathway. Using fetal diffusion tractography, we identify radial glial fascicles that originate from the VZ and curve around the lenticular nuclei to form the insula. These results confirm existing models of radial migration to the cortex and illustrate findings that suggest differential insular and cerebral development, laying the groundwork to understand cerebral malformations and insular function and pathologies.
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Affiliation(s)
- Arka N. Mallela
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA15213
| | - Hansen Deng
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA15213
| | - Ali Gholipour
- Department of Radiology, Harvard Medical School, Boston, MA02115
- Department of Radiology, Boston Children’s Hospital, Boston, MA02115
| | - Simon K. Warfield
- Department of Radiology, Harvard Medical School, Boston, MA02115
- Department of Radiology, Boston Children’s Hospital, Boston, MA02115
| | - Ezequiel Goldschmidt
- Department of Radiology, Harvard Medical School, Boston, MA02115
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA94143
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22
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Van Essen DC. Biomechanical models and mechanisms of cellular morphogenesis and cerebral cortical expansion and folding. Semin Cell Dev Biol 2023; 140:90-104. [PMID: 35840524 PMCID: PMC9942585 DOI: 10.1016/j.semcdb.2022.06.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 05/31/2022] [Accepted: 06/16/2022] [Indexed: 01/28/2023]
Abstract
Morphogenesis of the nervous system involves a highly complex spatio-temporal pattern of physical forces (mainly tension and pressure) acting on cells and tissues that are pliable but have an intricately organized cytoskeletal infrastructure. This review begins by covering basic principles of biomechanics and the core cytoskeletal toolkit used to regulate the shapes of cells and tissues during embryogenesis and neural development. It illustrates how the principle of 'tensegrity' provides a useful conceptual framework for understanding how cells dynamically respond to forces that are generated internally or applied externally. The latter part of the review builds on this foundation in considering the development of mammalian cerebral cortex. The main focus is on cortical expansion and folding - processes that take place over an extended period of prenatal and postnatal development. Cortical expansion and folding are likely to involve many complementary mechanisms, some related to regulating cell proliferation and migration and others related to specific types and patterns of mechanical tension and pressure. Three distinct multi-mechanism models are evaluated in relation to a set of 18 key experimental observations and findings. The Composite Tension Plus (CT+) model is introduced as an updated version of a previous multi-component Differential Expansion Sandwich Plus (DES+) model (Van Essen, 2020); the new CT+ model includes 10 distinct mechanisms and has the greatest explanatory power among published models to date. Much needs to be done in order to validate specific mechanistic components and to assess their relative importance in different species, and important directions for future research are suggested.
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23
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Janson E, Willemsen MF, Van Beek PE, Dudink J, Van Elburg RM, Hortensius LM, Tam EWY, de Pipaon MS, Lapillonne A, de Theije CGM, Benders MJNL, van der Aa NE. The influence of nutrition on white matter development in preterm infants: a scoping review. Pediatr Res 2023:10.1038/s41390-023-02622-1. [PMID: 37147439 DOI: 10.1038/s41390-023-02622-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 02/16/2023] [Accepted: 03/22/2023] [Indexed: 05/07/2023]
Abstract
White matter (WM) injury is the most common type of brain injury in preterm infants and is associated with impaired neurodevelopmental outcome (NDO). Currently, there are no treatments for WM injury, but optimal nutrition during early preterm life may support WM development. The main aim of this scoping review was to assess the influence of early postnatal nutrition on WM development in preterm infants. Searches were performed in PubMed, EMBASE, and COCHRANE on September 2022. Inclusion criteria were assessment of preterm infants, nutritional intake before 1 month corrected age, and WM outcome. Methods were congruent with the PRISMA-ScR checklist. Thirty-two articles were included. Negative associations were found between longer parenteral feeding duration and WM development, although likely confounded by illness. Positive associations between macronutrient, energy, and human milk intake and WM development were common, especially when fed enterally. Results on fatty acid and glutamine supplementation remained inconclusive. Significant associations were most often detected at the microstructural level using diffusion magnetic resonance imaging. Optimizing postnatal nutrition can positively influence WM development and subsequent NDO in preterm infants, but more controlled intervention studies using quantitative neuroimaging are needed. IMPACT: White matter brain injury is common in preterm infants and associated with impaired neurodevelopmental outcome. Optimizing postnatal nutrition can positively influence white matter development and subsequent neurodevelopmental outcome in preterm infants. More studies are needed, using quantitative neuroimaging techniques and interventional designs controlling for confounders, to define optimal nutritional intakes in preterm infants.
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Affiliation(s)
- Els Janson
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Marle F Willemsen
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- Faculty of Medicine, Utrecht University, Utrecht, The Netherlands
| | - Pauline E Van Beek
- Department of Neonatology, Máxima Medical Center, Veldhoven, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Ruurd M Van Elburg
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Pediatrics, Emma Children's Hospital, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Lisa M Hortensius
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Emily W Y Tam
- Department of Paediatrics, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Miguel Saenz de Pipaon
- Neonatology, Instituto de Investigación Sanitaria, La Paz University Hospital-IdiPAZ (Universidad Autonoma), Madrid, Spain
| | - Alexandre Lapillonne
- Department of Neonatology, Necker-Enfants Malades Hospital, University of Paris, Paris, France
| | - Caroline G M de Theije
- Department for Developmental Origins of Disease, University Medical Center Utrecht Brain Center and Wilhelmina Children's Hospital, Utrecht University, 3508 AB, Utrecht, The Netherlands
| | - Manon J N L Benders
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Niek E van der Aa
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands.
- University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands.
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24
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Razban RM, Pachter JA, Dill KA, Mujica-Parodi LR. Early path dominance as a principle for neurodevelopment. Proc Natl Acad Sci U S A 2023; 120:e2218007120. [PMID: 37053187 PMCID: PMC10120000 DOI: 10.1073/pnas.2218007120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 03/15/2023] [Indexed: 06/19/2023] Open
Abstract
We perform targeted attack, a systematic computational unlinking of the network, to analyze its effects on global communication across the brain network through its giant cluster. Across diffusion magnetic resonance images from individuals in the UK Biobank, Adolescent Brain Cognitive Development Study and Developing Human Connectome Project, we find that targeted attack procedures on increasing white matter tract lengths and densities are remarkably invariant to aging and disease. Time-reversing the attack computation suggests a mechanism for how brains develop, for which we derive an analytical equation using percolation theory. Based on a close match between theory and experiment, our results demonstrate that tracts are limited to emanate from regions already in the giant cluster and tracts that appear earliest in neurodevelopment are those that become the longest and densest.
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Affiliation(s)
- Rostam M. Razban
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
| | - Jonathan Asher Pachter
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
- Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY11794
| | - Ken A. Dill
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
- Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY11794
- Department of Chemistry, Stony Brook University, Stony Brook, NY11794
| | - Lilianne R. Mujica-Parodi
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
- Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY11794
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY11794
- Program in Neuroscience, Stony Brook University, Stony Brook, NY11794
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA02129
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25
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Wilson S, Pietsch M, Cordero-Grande L, Christiaens D, Uus A, Karolis VR, Kyriakopoulou V, Colford K, Price AN, Hutter J, Rutherford MA, Hughes EJ, Counsell SJ, Tournier JD, Hajnal JV, Edwards AD, O’Muircheartaigh J, Arichi T. Spatiotemporal tissue maturation of thalamocortical pathways in the human fetal brain. eLife 2023; 12:e83727. [PMID: 37010273 PMCID: PMC10125021 DOI: 10.7554/elife.83727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 03/31/2023] [Indexed: 04/04/2023] Open
Abstract
The development of connectivity between the thalamus and maturing cortex is a fundamental process in the second half of human gestation, establishing the neural circuits that are the basis for several important brain functions. In this study, we acquired high-resolution in utero diffusion magnetic resonance imaging (MRI) from 140 fetuses as part of the Developing Human Connectome Project, to examine the emergence of thalamocortical white matter over the second to third trimester. We delineate developing thalamocortical pathways and parcellate the fetal thalamus according to its cortical connectivity using diffusion tractography. We then quantify microstructural tissue components along the tracts in fetal compartments that are critical substrates for white matter maturation, such as the subplate and intermediate zone. We identify patterns of change in the diffusion metrics that reflect critical neurobiological transitions occurring in the second to third trimester, such as the disassembly of radial glial scaffolding and the lamination of the cortical plate. These maturational trajectories of MR signal in transient fetal compartments provide a normative reference to complement histological knowledge, facilitating future studies to establish how developmental disruptions in these regions contribute to pathophysiology.
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Affiliation(s)
- Siân Wilson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
| | - Maximilian Pietsch
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de MadridMadridSpain
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN)MadridSpain
| | - Daan Christiaens
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Department of Electrical Engineering (ESAT/PSI), Katholieke Universiteit LeuvenLeuvenBelgium
| | - Alena Uus
- Department of Biomedical Engineering, School Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas' HospitalLondonUnited Kingdom
| | - Vyacheslav R Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Kathleen Colford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Emer J Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Jacques-Donald Tournier
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
- Department of Forensic and Neurodevelopmental Sciences, King’s College LondonLondonUnited Kingdom
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College LondonLondonUnited Kingdom
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
- Children’s Neurosciences, Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation TrustLondonUnited Kingdom
- Department of Bioengineering, Imperial College LondonLondonUnited Kingdom
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26
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Machado-Rivas F, Cortes-Albornoz MC, Afacan O, Bedoya MA, Calixto C, Choi JJ, Ruggiero M, Gholipour A, Jaimes C. Fetal MRI at 3 T: Principles to Optimize Success. Radiographics 2023; 43:e220141. [PMID: 36995947 PMCID: PMC10091224 DOI: 10.1148/rg.220141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 08/08/2022] [Accepted: 08/10/2022] [Indexed: 03/31/2023]
Abstract
Fetal MRI has emerged as a cornerstone of prenatal imaging, helping to establish the correct diagnosis in pregnancies affected by congenital anomalies. In the past decade, 3 T imaging was introduced as an alternative to increase the signal-to-noise ratio (SNR) of the pulse sequences and improve anatomic detail. However, imaging at a higher field strength is not without challenges. Many artifacts that are barely appreciable at 1.5 T are amplified at 3 T. A systematic approach to imaging at 3 T that incorporates appropriate patient positioning, a thoughtful protocol design, and sequence optimization minimizes the impact of these artifacts and allows radiologists to reap the benefits of the increased SNR. The sequences used are the same at both field strengths and include single-shot T2-weighted, balanced steady-state free-precession, three-dimensional T1-weighted spoiled gradient-echo, and echo-planar imaging. Synergistic use of these acquisitions to sample various tissue contrasts and in various planes provides valuable information about fetal anatomy and pathologic conditions. In the authors' experience, fetal imaging at 3 T outperforms imaging at 1.5 T for most indications when performed under optimal circumstances. The authors condense the cumulative experience of fetal imaging specialists and MRI technologists who practice at a large referral center into a guideline covering all major aspects of fetal MRI at 3 T, from patient preparation to image interpretation. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Fedel Machado-Rivas
- From the Department of Radiology, Boston Children’s Hospital,
300 Longwood Ave, Boston, MA 02215 (F.M.R., M.C.C.A., O.A., M.A.B., C.C., M.R.,
A.G., C.J.); Department of Radiology, Harvard Medical School, Boston, Mass
(J.J.C.); and Department of Radiology, Cincinnati Children’s Hospital,
Cincinnati, Ohio (F.M.R., M.C.C.A., O.A., M.A.B., C.C., A.G., C.J.)
| | - Maria Camila Cortes-Albornoz
- From the Department of Radiology, Boston Children’s Hospital,
300 Longwood Ave, Boston, MA 02215 (F.M.R., M.C.C.A., O.A., M.A.B., C.C., M.R.,
A.G., C.J.); Department of Radiology, Harvard Medical School, Boston, Mass
(J.J.C.); and Department of Radiology, Cincinnati Children’s Hospital,
Cincinnati, Ohio (F.M.R., M.C.C.A., O.A., M.A.B., C.C., A.G., C.J.)
| | - Onur Afacan
- From the Department of Radiology, Boston Children’s Hospital,
300 Longwood Ave, Boston, MA 02215 (F.M.R., M.C.C.A., O.A., M.A.B., C.C., M.R.,
A.G., C.J.); Department of Radiology, Harvard Medical School, Boston, Mass
(J.J.C.); and Department of Radiology, Cincinnati Children’s Hospital,
Cincinnati, Ohio (F.M.R., M.C.C.A., O.A., M.A.B., C.C., A.G., C.J.)
| | - Maria Alejandra Bedoya
- From the Department of Radiology, Boston Children’s Hospital,
300 Longwood Ave, Boston, MA 02215 (F.M.R., M.C.C.A., O.A., M.A.B., C.C., M.R.,
A.G., C.J.); Department of Radiology, Harvard Medical School, Boston, Mass
(J.J.C.); and Department of Radiology, Cincinnati Children’s Hospital,
Cincinnati, Ohio (F.M.R., M.C.C.A., O.A., M.A.B., C.C., A.G., C.J.)
| | - Camilo Calixto
- From the Department of Radiology, Boston Children’s Hospital,
300 Longwood Ave, Boston, MA 02215 (F.M.R., M.C.C.A., O.A., M.A.B., C.C., M.R.,
A.G., C.J.); Department of Radiology, Harvard Medical School, Boston, Mass
(J.J.C.); and Department of Radiology, Cincinnati Children’s Hospital,
Cincinnati, Ohio (F.M.R., M.C.C.A., O.A., M.A.B., C.C., A.G., C.J.)
| | - Jungwhan John Choi
- From the Department of Radiology, Boston Children’s Hospital,
300 Longwood Ave, Boston, MA 02215 (F.M.R., M.C.C.A., O.A., M.A.B., C.C., M.R.,
A.G., C.J.); Department of Radiology, Harvard Medical School, Boston, Mass
(J.J.C.); and Department of Radiology, Cincinnati Children’s Hospital,
Cincinnati, Ohio (F.M.R., M.C.C.A., O.A., M.A.B., C.C., A.G., C.J.)
| | - Matthew Ruggiero
- From the Department of Radiology, Boston Children’s Hospital,
300 Longwood Ave, Boston, MA 02215 (F.M.R., M.C.C.A., O.A., M.A.B., C.C., M.R.,
A.G., C.J.); Department of Radiology, Harvard Medical School, Boston, Mass
(J.J.C.); and Department of Radiology, Cincinnati Children’s Hospital,
Cincinnati, Ohio (F.M.R., M.C.C.A., O.A., M.A.B., C.C., A.G., C.J.)
| | - Ali Gholipour
- From the Department of Radiology, Boston Children’s Hospital,
300 Longwood Ave, Boston, MA 02215 (F.M.R., M.C.C.A., O.A., M.A.B., C.C., M.R.,
A.G., C.J.); Department of Radiology, Harvard Medical School, Boston, Mass
(J.J.C.); and Department of Radiology, Cincinnati Children’s Hospital,
Cincinnati, Ohio (F.M.R., M.C.C.A., O.A., M.A.B., C.C., A.G., C.J.)
| | - Camilo Jaimes
- From the Department of Radiology, Boston Children’s Hospital,
300 Longwood Ave, Boston, MA 02215 (F.M.R., M.C.C.A., O.A., M.A.B., C.C., M.R.,
A.G., C.J.); Department of Radiology, Harvard Medical School, Boston, Mass
(J.J.C.); and Department of Radiology, Cincinnati Children’s Hospital,
Cincinnati, Ohio (F.M.R., M.C.C.A., O.A., M.A.B., C.C., A.G., C.J.)
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27
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Charvet CJ. Mapping Human Brain Pathways: Challenges and Opportunities in the Integration of Scales. BRAIN, BEHAVIOR AND EVOLUTION 2023; 98:194-209. [PMID: 36972574 DOI: 10.1159/000530317] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 03/16/2023] [Indexed: 03/29/2023]
Abstract
The human brain is composed of a complex web of pathways. Diffusion magnetic resonance (MR) tractography is a neuroimaging technique that relies on the principle of diffusion to reconstruct brain pathways. Its tractography is broadly applicable to a range of problems as it is amenable for study in individuals of any age and from any species. However, it is well known that this technique can generate biologically implausible pathways, especially in regions of the brain where multiple fibers cross. This review highlights potential misconnections in two cortico-cortical association pathways with a focus on the aslant tract and inferior frontal occipital fasciculus. The lack of alternative methods to validate observations from diffusion MR tractography means there is a need to develop new integrative approaches to trace human brain pathways. This review discusses integrative approaches in neuroimaging, anatomical, and transcriptional variation as having much potential to trace the evolution of human brain pathways.
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Affiliation(s)
- Christine J Charvet
- Department of Anatomy, Physiology and Pharmacology, College of Veterinary Medicine, Auburn University, Auburn, Alabama, USA
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28
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Kumpulainen V, Merisaari H, Silver E, Copeland A, Pulli EP, Lewis JD, Saukko E, Shulist SJ, Saunavaara J, Parkkola R, Lähdesmäki T, Karlsson L, Karlsson H, Tuulari JJ. Sex differences, asymmetry, and age-related white matter development in infants and 5-year-olds as assessed with tract-based spatial statistics. Hum Brain Mapp 2023; 44:2712-2725. [PMID: 36946076 PMCID: PMC10089102 DOI: 10.1002/hbm.26238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 01/24/2023] [Accepted: 02/08/2023] [Indexed: 03/23/2023] Open
Abstract
The rapid white matter (WM) maturation of first years of life is followed by slower yet long-lasting development, accompanied by learning of more elaborate skills. By the age of 5 years, behavioural and cognitive differences between females and males, and functions associated with brain lateralization such as language skills are appearing. Diffusion tensor imaging (DTI) can be used to quantify fractional anisotropy (FA) within the WM and increasing values correspond to advancing brain development. To investigate the normal features of WM development during early childhood, we gathered a DTI data set of 166 healthy infants (mean 3.8 wk, range 2-5 wk; 89 males; born on gestational week 36 or later) and 144 healthy children (mean 5.4 years, range 5.1-5.8 years; 76 males). The sex differences, lateralization patterns and age-dependent changes were examined using tract-based spatial statistics (TBSS). In 5-year-olds, females showed higher FA in wide-spread regions in the posterior and the temporal WM and more so in the right hemisphere, while sex differences were not detected in infants. Gestational age showed stronger association with FA values compared to age after birth in infants. Additionally, child age at scan associated positively with FA around the age of 5 years in the body of corpus callosum, the connections of which are important especially for sensory and motor functions. Lastly, asymmetry of WM microstructure was detected already in infants, yet significant changes in lateralization pattern seem to occur during early childhood, and in 5-year-olds the pattern already resembles adult-like WM asymmetry.
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Affiliation(s)
- Venla Kumpulainen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Elmo P Pulli
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - John D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Ekaterina Saukko
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Satu J Shulist
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital and University of Turku, Turku, Finland
| | - Riitta Parkkola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Tuire Lähdesmäki
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Pediatric Neurology, Turku University Hospital, University of Turku, Turku, Finland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Paediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital & University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital & University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital & University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
- Department of Psychiatry, University of Oxford, Oxford, UK
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Chen HK, Wang SL, Chang YH, Sun CW, Wu MT, Chen ML, Lin YJ, Hsieh CJ. Associations between maternal phthalate exposure and neonatal neurobehaviors: The Taiwan maternal and infant cohort study (TMICS). ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 319:120956. [PMID: 36581241 DOI: 10.1016/j.envpol.2022.120956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 12/23/2022] [Accepted: 12/24/2022] [Indexed: 06/17/2023]
Abstract
Previous studies have shown associations between prenatal phthalate exposure and neurobehavioral changes in children. However, few studies have focused on neonatal neurobehavioral development. This study aimed to examine the associations between prenatal phthalate exposure and neonatal neurobehavioral development in the early days of life after birth. This cohort study included 283 mother-infant pairs who participated in the Taiwan Mother Infant Cohort Study during 2012-2015. Each mother was interviewed, and urine samples were collected during the third trimester of pregnancy (weeks 29-40). Eleven common phthalate metabolites in maternal urine were analyzed. The Chinese version of the Neonatal Neurobehavioral Examination was used to evaluate early infant neurobehavioral development within five days of birth. We performed multiple linear regressions to explore the associations between phthalate exposure and neonatal neurobehavioral development. Sex differences in the association between phthalate metabolites and neonatal neurobehaviors were noted. Among girls, tertiles of phthalate metabolite concentrations were associated with worse behavioral responses and tone and motor patterns in the high-molecular-weight phthalate (HMW) and low-molecular-weight phthalate (LMW) groups. Girls in the highest tertile of di-2-ethylhexyl phthalate (DEHP) and mono-isobutyl phthalate (MiBP) had a negative association with tone and motor patterns. Girls in the highest tertile of mono-n-butyl phthalate (MnBP) and MiBP showed a negative association with behavioral responses. In contrast, tertiles of phthalate metabolite exposure were associated with improved neurobehaviors in mono-methyl phthalate (MMP) among boys. The highest tertile of MMP was positively associated with behavioral responses, primitive reflexes, and tone and motor patterns. Our findings suggest that maternal phthalate exposure affects neonatal neurobehavioral development in a sex-specific manner. Despite the relatively small sample size, our findings add to the existing research linking maternal phthalate exposure to neonatal neurobehavioral development. Additional research is needed to determine the potential long-term effects of prenatal phthalate exposure on children.
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Affiliation(s)
- Hsing-Kang Chen
- Institute of Medical Sciences, Tzu Chi University, Hualien, Taiwan; Department of Psychiatry, Yuli Hospital, Ministry of Health and Welfare, Hualien, Taiwan
| | - Shu-Li Wang
- National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli, Taiwan; Department of Public Health, National Defense Medical Center, Taipei, Taiwan; Department of Safety, Health, and Environmental Engineering, National United University, Miaoli, Taiwan
| | - Yu-Hsun Chang
- Department of Pediatrics, Hualien Tzu Chi General Hospital, Hualien, Taiwan; School of Medicine, Tzu Chi University, Hualien, Taiwan; Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan
| | - Chien-Wen Sun
- National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli, Taiwan
| | - Ming-Tsang Wu
- Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Family Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan; Graduate Institute of Clinical Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Mei-Lien Chen
- Institute of Environmental and Occupational Health Sciences, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yu-Jie Lin
- Department of Public Health, Tzu Chi University, Hualien, Taiwan
| | - Chia-Jung Hsieh
- Institute of Medical Sciences, Tzu Chi University, Hualien, Taiwan; Department of Public Health, Tzu Chi University, Hualien, Taiwan.
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Spatiotemporal Developmental Gradient of Thalamic Morphology, Microstructure, and Connectivity fromthe Third Trimester to Early Infancy. J Neurosci 2023; 43:559-570. [PMID: 36639904 PMCID: PMC9888512 DOI: 10.1523/jneurosci.0874-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 10/19/2022] [Accepted: 11/26/2022] [Indexed: 12/12/2022] Open
Abstract
Thalamus is a critical component of the limbic system that is extensively involved in both basic and high-order brain functions. However, how the thalamic structure and function develops at macroscopic and microscopic scales during the perinatal period development is not yet well characterized. Here, we used multishell high-angular resolution diffusion MRI of 144 preterm-born and full-term infants in both sexes scanned at 32-44 postmenstrual weeks (PMWs) from the Developing Human Connectome Project database to investigate the thalamic development in morphology, microstructure, associated connectivity, and subnucleus division. We found evident anatomic expansion and linear increases of fiber integrity in the lateral side of thalamus compared with the medial part. The tractography results indicated that thalamic connection to the frontal cortex developed later than the other thalamocortical connections (parieto-occipital, motor, somatosensory, and temporal). Using a connectivity-based segmentation strategy, we revealed that functional partitions of thalamic subdivisions were formed at 32 PMWs or earlier, and the partition developed toward the adult pattern in a lateral-to-medial pattern. Collectively, these findings revealed faster development of the lateral thalamus than the central part as well as a posterior-to-anterior developmental gradient of thalamocortical connectivity from the third trimester to early infancy.SIGNIFICANCE STATEMENT This is the first study that characterizes the spatiotemporal developmental pattern of thalamus during the third trimester to early infancy. We found that thalamus develops in a lateral-to-medial pattern for both thalamic microstructures and subdivisions; and thalamocortical connectivity develops in a posterior-to-anterior gradient that thalamofrontal connectivity appears later than the other thalamocortical connections. These findings may enrich our understanding of the developmental principles of thalamus and provide references for the atypical brain growth in neurodevelopmental disorders.
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De Asis-Cruz J, Limperopoulos C. Harnessing the Power of Advanced Fetal Neuroimaging to Understand In Utero Footprints for Later Neuropsychiatric Disorders. Biol Psychiatry 2022; 93:867-879. [PMID: 36804195 DOI: 10.1016/j.biopsych.2022.11.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 11/03/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022]
Abstract
Adverse intrauterine events may profoundly impact fetal risk for future adult diseases. The mechanisms underlying this increased vulnerability are complex and remain poorly understood. Contemporary advances in fetal magnetic resonance imaging (MRI) have provided clinicians and scientists with unprecedented access to in vivo human fetal brain development to begin to identify emerging endophenotypes of neuropsychiatric disorders such as autism spectrum disorder, attention-deficit/hyperactivity disorder, and schizophrenia. In this review, we discuss salient findings of normal fetal neurodevelopment from studies using advanced, multimodal MRI that have provided unparalleled characterization of in utero prenatal brain morphology, metabolism, microstructure, and functional connectivity. We appraise the clinical utility of these normative data in identifying high-risk fetuses before birth. We highlight available studies that have investigated the predictive validity of advanced prenatal brain MRI findings and long-term neurodevelopmental outcomes. We then discuss how ex utero quantitative MRI findings can inform in utero investigations toward the pursuit of early biomarkers of risk. Lastly, we explore future opportunities to advance our understanding of the prenatal origins of neuropsychiatric disorders using precision fetal imaging.
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Chen R, Sun C, Liu T, Liao Y, Wang J, Sun Y, Zhang Y, Wang G, Wu D. Deciphering the developmental order and microstructural patterns of early white matter pathways in a diffusion MRI based fetal brain atlas. Neuroimage 2022; 264:119700. [PMID: 36270621 DOI: 10.1016/j.neuroimage.2022.119700] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 10/14/2022] [Accepted: 10/18/2022] [Indexed: 11/09/2022] Open
Abstract
White matter (WM) of the fetal brain undergoes rapid development to form early structural connections. Diffusion magnetic resonance imaging (dMRI) has shown to be a useful tool to depict fetal brain WM in utero, and many studies have observed increasing fractional anisotropy and decreasing diffusivity in the fetal brain during the second-to-third trimester, whereas others reported non-monotonic changes. Unbiased dMRI atlases of the fetal brain are important for characterizing the developmental trajectories of WM and providing normative references for in utero diagnosis of prenatal abnormalities. To date, the sole fetal brain dMRI atlas was collected from a Caucasian/mixed population and was constructed based on the diffusion tensor model with limited spatial resolution. In this work, we proposed a fiber orientation distribution (FOD) based pipeline for generating fetal brain dMRI atlases, which showed better registration accuracy than a diffusion tensor based pipeline. Based on the FOD-based pipeline, we constructed the first Chinese fetal brain dMRI atlas using 89 dMRI scans of normal fetuses at gestational age between 24 and 38 weeks. Complex non-monotonic trends of tensor- and FOD-derived microstructural parameters in eight WM tracts were observed, which jointly pointed to different phases of microstructural development. Specifically, we speculated that the turning point of the diffusivity trajectory may correspond to the starting point of pre-myelination, based on which, the developmental order of WM tracts can be mapped and the order was in agreement with the order of myelination from histological studies. The normative atlas also provided a reference for the detection of abnormal WM development, such as that in congenital heart disease. Therefore, the established high-order fetal brain dMRI atlas depicted the spatiotemporal pattern of early WM development, and findings may help decipher the distinct microstructural events in utero.
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Affiliation(s)
- Ruike Chen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Cong Sun
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Tingting Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yuhao Liao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | | | - Yi Sun
- MR Collaboration, Siemens Healthineers Ltd., Shanghai, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
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Wang J, Nichols ES, Mueller ME, de Vrijer B, Eagleson R, McKenzie CA, de Ribaupierre S, Duerden EG. Semi-automatic segmentation of the fetal brain from magnetic resonance imaging. Front Neurosci 2022; 16:1027084. [PMID: 36440277 PMCID: PMC9692018 DOI: 10.3389/fnins.2022.1027084] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 10/19/2022] [Indexed: 11/13/2023] Open
Abstract
BACKGROUND Volumetric measurements of fetal brain maturation in the third trimester of pregnancy are key predictors of developmental outcomes. Improved understanding of fetal brain development trajectories may aid in identifying and clinically managing at-risk fetuses. Currently, fetal brain structures in magnetic resonance images (MRI) are often manually segmented, which requires both time and expertise. To facilitate the targeting and measurement of brain structures in the fetus, we compared the results of five segmentation methods applied to fetal brain MRI data to gold-standard manual tracings. METHODS Adult women with singleton pregnancies (n = 21), of whom five were scanned twice, approximately 3 weeks apart, were recruited [26 total datasets, median gestational age (GA) = 34.8, IQR = 30.9-36.6]. T2-weighted single-shot fast spin echo images of the fetal brain were acquired on 1.5T and 3T MRI scanners. Images were first combined into a single 3D anatomical volume. Next, a trained tracer manually segmented the thalamus, cerebellum, and total cerebral volumes. The manual segmentations were compared with five automatic methods of segmentation available within Advanced Normalization Tools (ANTs) and FMRIB's Linear Image Registration Tool (FLIRT) toolboxes. The manual and automatic labels were compared using Dice similarity coefficients (DSCs). The DSC values were compared using Friedman's test for repeated measures. RESULTS Comparing cerebellum and thalamus masks against the manually segmented masks, the median DSC values for ANTs and FLIRT were 0.72 [interquartile range (IQR) = 0.6-0.8] and 0.54 (IQR = 0.4-0.6), respectively. A Friedman's test indicated that the ANTs registration methods, primarily nonlinear methods, performed better than FLIRT (p < 0.001). CONCLUSION Deformable registration methods provided the most accurate results relative to manual segmentation. Overall, this semi-automatic subcortical segmentation method provides reliable performance to segment subcortical volumes in fetal MR images. This method reduces the costs of manual segmentation, facilitating the measurement of typical and atypical fetal brain development.
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Affiliation(s)
- Jianan Wang
- Biomedical Engineering, Western University, London, ON, Canada
| | - Emily S. Nichols
- Applied Psychology, Faculty of Education, Western University, London, ON, Canada
- Western Institute for Neuroscience, Western University, London, ON, Canada
| | - Megan E. Mueller
- Applied Psychology, Faculty of Education, Western University, London, ON, Canada
| | - Barbra de Vrijer
- Department of Obstetrics and Gynaecology, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
| | - Roy Eagleson
- Biomedical Engineering, Western University, London, ON, Canada
- Western Institute for Neuroscience, Western University, London, ON, Canada
- Department of Electrical and Computer Engineering, Western University, London, ON, Canada
| | - Charles A. McKenzie
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
| | - Sandrine de Ribaupierre
- Biomedical Engineering, Western University, London, ON, Canada
- Western Institute for Neuroscience, Western University, London, ON, Canada
- Department of Clinical Neurological Sciences, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
- Department of Anatomy and Cell Biology, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
| | - Emma G. Duerden
- Biomedical Engineering, Western University, London, ON, Canada
- Applied Psychology, Faculty of Education, Western University, London, ON, Canada
- Western Institute for Neuroscience, Western University, London, ON, Canada
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Xie Q, Zhang Y, Zhang J, Cui D, Zhou Q, Guo M. Promotion effect of the blend containing 2'-FL, OPN and DHA on oligodendrocyte progenitor cells myelination in vitro. Front Nutr 2022; 9:1054431. [DOI: 10.3389/fnut.2022.1054431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 10/17/2022] [Indexed: 11/11/2022] Open
Abstract
During early neurodevelopment of infant, myelination plays an essential role in brain connectivity and emergence of behavioral and cognitive function. Early life nutrition is an important factor to shape myelination and consequently cognitive appearance. To analyze the effects of additive nutrients, including 2'-fucosyllactose (2'-FL), osteopontin (OPN), docosahexaenoic acid (DHA), on neurocognitive function and brain structure, the current study evaluated the effects of different composition of breast milk nutrients on oligodendrocyte progenitor cells (OPCs) myelination with a neural primary cell model in vitro. The study showed that the three nutrients promoted the proliferation, maturation and differentiation of OPCs into mature oligodendrocytes (OLs) in each phage of the cell growth, and the effect of the nutrients blend is obviously stronger than that of the nutrient treatment alone, showing a synergistic effect in promotion of OPCs. The results of this experiment clarified the effects of 2′-FL OPN and DHA to promote myelination development of neural cells, and laid an experimental basis for further optimization of infant formula.
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Liang W, Yu Q, Wang W, Dhollander T, Suluba E, Li Z, Xu F, Hu Y, Tang Y, Liu S. A comparative study of the superior longitudinal fasciculus subdivisions between neonates and young adults. Brain Struct Funct 2022; 227:2713-2730. [PMID: 36114859 PMCID: PMC9618541 DOI: 10.1007/s00429-022-02565-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 09/03/2022] [Indexed: 12/04/2022]
Abstract
The superior longitudinal fasciculus (SLF) is a complex associative tract comprising three distinct subdivisions in the frontoparietal cortex, each of which has its own anatomical connectivity and functional roles. However, many studies on white matter development, hampered by limitations of data quality and tractography methods, treated the SLF as a single entity. The exact anatomical trajectory and developmental status of each sub-bundle of the human SLF in neonates remain poorly understood. Here, we compared the morphological and microstructural characteristics of each branch of the SLF at two ages using diffusion MRI data from 40 healthy neonates and 40 adults. A multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) algorithm was used to ensure the successful separation of the three SLF branches (SLF I, SLF II and SLF III). Then, between-group differences in the diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics were investigated in all the SLF branches. Meanwhile, Mahalanobis distances based on all the diffusion metrics were computed to quantify the maturation of neonatal SLF branches, considering the adult brain as the reference. The SLF branches, excluding SLF II, had similar fibre morphology and connectivity between the neonatal and adult groups. The Mahalanobis distance values further supported the notion of heterogeneous maturation among SLF branches. The greatest Mahalanobis distance was observed in SLF II, possibly indicating that it was the least mature. Our findings provide a new anatomical basis for the early diagnosis and treatment of diseases caused by abnormal neonatal SLF development.
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Affiliation(s)
- Wenjia Liang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Qiaowen Yu
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Wenjun Wang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Emmanuel Suluba
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Zhuoran Li
- Department of Ultrasound, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Feifei Xu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Yang Hu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Yuchun Tang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China.
| | - Shuwei Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China.
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Imaging fetal anatomy. Semin Cell Dev Biol 2022; 131:78-92. [PMID: 35282997 DOI: 10.1016/j.semcdb.2022.02.023] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/23/2022] [Accepted: 02/23/2022] [Indexed: 02/07/2023]
Abstract
Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development.
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Epigenetic regulation of fetal brain development in pig. Gene 2022; 844:146823. [PMID: 35988784 DOI: 10.1016/j.gene.2022.146823] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 07/27/2022] [Accepted: 08/15/2022] [Indexed: 02/01/2023]
Abstract
How fetal brain development is regulated at the molecular level is not well understood. Due to ethical challenges associated with research on the human fetus, large animals particularly pigs are increasingly used to study development and disorders of fetal brain. The pig fetal brain grows rapidly during the last ∼ 50 days before birth which is around day 60 (d60) of pig gestation. But what regulates the onset of accelerated growth of the brain is unknown. The current study tests the hypothesis that epigenetic alteration around d60 is involved in the onset of rapid growth of fetal brain of pig. To test this hypothesis, DNA methylation changes of fetal brain was assessed in a genome-wide manner by Enzymatic Methyl-seq (EM-seq) during two gestational periods (GP): d45 vs. d60 (GP1) and d60 vs. d90 (GP2). The cytosine-guanine (CpG) methylation data was analyzed in an integrative manner with the RNA-seq data generated from the same brain samples from our earlier study. A neural network based modeling approach was implemented to learn changes in methylation patterns of the differentially expressed genes, and then predict methylations of the brain in a genome-wide manner during rapid growth. This approach identified specific methylations that changed in a mutually informative manner during rapid growth of the fetal brain. These methylations were significantly overrepresented in specific genic as well as intergenic features including CpG islands, introns, and untranslated regions. In addition, sex-bias methylations of known single nucleotide polymorphic sites were also identified in the fetal brain ide during rapid growth.
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Lautarescu A, Bonthrone AF, Pietsch M, Batalle D, Cordero-Grande L, Tournier JD, Christiaens D, Hajnal JV, Chew A, Falconer S, Nosarti C, Victor S, Craig MC, Edwards AD, Counsell SJ. Maternal depressive symptoms, neonatal white matter, and toddler social-emotional development. Transl Psychiatry 2022; 12:323. [PMID: 35945202 PMCID: PMC9363426 DOI: 10.1038/s41398-022-02073-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/01/2022] [Accepted: 07/18/2022] [Indexed: 11/25/2022] Open
Abstract
Maternal prenatal depression is associated with increased likelihood of neurodevelopmental and psychiatric conditions in offspring. The relationship between maternal depression and offspring outcome may be mediated by in-utero changes in brain development. Recent advances in magnetic resonance imaging (MRI) have enabled in vivo investigations of neonatal brains, minimising the effect of postnatal influences. The aim of this study was to examine associations between maternal prenatal depressive symptoms, infant white matter, and toddler behaviour. 413 mother-infant dyads enrolled in the developing Human Connectome Project. Mothers completed the Edinburgh Postnatal Depression Scale (median = 5, range = 0-28, n = 52 scores ≥ 11). Infants (n = 223 male) (median gestational age at birth = 40 weeks, range 32.14-42.29) underwent MRI (median postmenstrual age at scan = 41.29 weeks, range 36.57-44.71). Fixel-based fibre metrics (mean fibre density, fibre cross-section, and fibre density modulated by cross-section) were calculated from diffusion imaging data in the left and right uncinate fasciculi and cingulum bundle. For n = 311, internalising and externalising behaviour, and social-emotional abilities were reported at a median corrected age of 18 months (range 17-24). Statistical analysis used multiple linear regression and mediation analysis with bootstrapping. Maternal depressive symptoms were positively associated with infant fibre density in the left (B = 0.0005, p = 0.003, q = 0.027) and right (B = 0.0006, p = 0.003, q = 0.027) uncinate fasciculus, with left uncinate fasciculus fibre density, in turn, positively associated with social-emotional abilities in toddlerhood (B = 105.70, p = 0.0007, q = 0.004). In a mediation analysis, higher maternal depressive symptoms predicted toddler social-emotional difficulties (B = 0.342, t(307) = 3.003, p = 0.003), but this relationship was not mediated by fibre density in the left uncinate fasciculus (Sobel test p = 0.143, bootstrapped indirect effect = 0.035, SE = 0.02, 95% CI: [-0.01, 0.08]). There was no evidence of an association between maternal depressive and cingulum fibre properties. These findings suggest that maternal perinatal depressive symptoms are associated with neonatal uncinate fasciculi microstructure, but not fibre bundle size, and toddler behaviour.
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Affiliation(s)
- Alexandra Lautarescu
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK.
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Alexandra F Bonthrone
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Maximilian Pietsch
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Dafnis Batalle
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
- CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Madrid, Spain
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
| | - J-Donald Tournier
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Daan Christiaens
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Joseph V Hajnal
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Andrew Chew
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Shona Falconer
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Suresh Victor
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
- Neonatal Unit, Evelina London Children's Hospital, London, UK
| | - Michael C Craig
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Female Hormone Clinic, South London and Maudsley National Health Service Foundation Trust, London, UK
| | - A David Edwards
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
- Neonatal Unit, Evelina London Children's Hospital, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
- EPSRC/Wellcome Centre for Medical Engineering, King's College London, London, UK
| | - Serena J Counsell
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
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Avery SN, Huang AS, Sheffield JM, Rogers BP, Vandekar S, Anticevic A, Woodward ND. Development of Thalamocortical Structural Connectivity in Typically Developing and Psychosis Spectrum Youths. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:782-792. [PMID: 34655804 PMCID: PMC9008075 DOI: 10.1016/j.bpsc.2021.09.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/30/2021] [Accepted: 09/30/2021] [Indexed: 12/13/2022]
Abstract
BACKGROUND Thalamocortical white matter connectivity is disrupted in psychosis and is hypothesized to play a role in its etiology and associated cognitive impairment. Attenuated cognitive symptoms often begin in adolescence, during a critical phase of white matter and cognitive development. However, little is known about the development of thalamocortical white matter connectivity and its association with cognition. METHODS This study characterized effects of age, sex, psychosis symptomatology, and cognition in thalamocortical networks in a large sample of youths (N = 1144, ages 8-22 years, 46% male) from the Philadelphia Neurodevelopmental Cohort, which included 316 typically developing youths, 330 youths on the psychosis spectrum, and 498 youths with other psychopathology. Probabilistic tractography was used to quantify percent total connectivity between the thalamus and six cortical regions and assess microstructural properties (i.e., fractional anisotropy) of thalamocortical white matter tracts. RESULTS Overall, percent total connectivity of the thalamus was weakly associated with age and was not associated with psychopathology or cognition. In contrast, fractional anisotropy of all thalamocortical tracts increased significantly with age, was generally higher in males than females, and was lowest in youths on the psychosis spectrum. Fractional anisotropy of tracts linking the thalamus to prefrontal and posterior parietal cortices was related to better cognitive function across subjects. CONCLUSIONS By characterizing the pattern of typical development and alterations in those at risk for psychotic disorders, this study provides a foundation for further conceptualization of thalamocortical white matter microstructure as a marker of neurodevelopment supporting cognition and an important risk marker for psychosis.
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Affiliation(s)
- Suzanne N Avery
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee.
| | - Anna S Huang
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Julia M Sheffield
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Sciences, Nashville, Tennessee
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Neil D Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
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Zheng W, Zhang X, Feng Y, Liu B, Zhu J, Zou Y, Qin J, Li B. Association of Corpus Callosum Development With Fetal Growth Restriction and Maternal Preeclampsia or Gestational Hypertension. JAMA Netw Open 2022; 5:e2226696. [PMID: 35969398 PMCID: PMC9379741 DOI: 10.1001/jamanetworkopen.2022.26696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
IMPORTANCE It remains unknown whether neurodevelopmental impairments are directly associated with the structural development of the brain in offspring with fetal growth restriction (FGR) and mothers with preeclampsia (PE) or gestational hypertension (GH). OBJECTIVES To assess whether fetal corpus callosum (CC) development differed among pregnancies with PE or GH with FGR, pregnancies with PE or GH without FGR, and normotensive pregnancies, particularly the severity of maternal disease and FGR, and to identify the association between adverse perinatal outcomes and structural development of the CC in fetuses with FGR in pregnancies with PE or GH. DESIGN, SETTING, AND PARTICIPANTS This retrospective matched case-control study was conducted between January 1, 2014, and January 31, 2021, at Women's Hospital, Zhejiang University School of Medicine in Hangzhou, China. The participant group included cases of singleton pregnancies with PE or GH with FGR; the control groups included cases with PG or GH without FGR and cases with paired normotensive pregnancy. EXPOSURES Maternal PE or GH and FGR. MAIN OUTCOMES AND MEASURES The length, thickness, total area, subdivision areas, and apparent diffusion coefficient (ADC) values of fetal CC were measured on magnetic resonance imaging (MRI) and analyzed. The association between adverse perinatal outcomes and structural development of CC was further investigated. RESULTS A total of 56 pregnant individuals with singleton pregnancies and PE or GH and fetuses with FGR were enrolled (maternal median [IQR] age, 29.0 [26.0-34.0] years; mean [SD] gestational age at MRI, 33.6 [2.5] weeks). Significant patterns of decreased median (IQR) fetal CC length (0.4284 [0.4079-0.4470] mm vs 0.4614 [0.4461-0.4944] mm, P < .001, vs 0.4591 [0.4310-0.4927] mm, P < .001) and mean (SD) CC total area (1.0779 [0.1931] mm2 vs 1.1896 [0.1803] mm2, P = .001, vs 1.1438 [0.1935] mm2, P = .02), adjusted for the cephalic index, was observed in cases of PE or GH with FGR compared with cases without FGR and cases with normotensive pregnancy. The splenium region of fetal CC also exhibited the distinct alterations in macrostructural development (with FGR: 0.3149 [0.0697] mm2 vs without FGR: 0.3727 [0.0698] mm2, P < .001, vs normotensive pregnancies: 0.3565 [0.0763] mm2, P < .001) and microstructural development (median [IQR] ADC values: 1.47 [1.38-1.57] × 10-3 mm2/s vs 1.57 [1.53-1.63] × 10-3 mm2/s, P = .009, vs 1.63 [1.50-1.70] × 10-3 mm2/s, P < .001) in all groups. Furthermore, significant associations were found between structural abnormality of the splenium region and adverse perinatal outcomes in the PE or GH with FGR group (mean [SD] ADC value: 1.40 [0.07] × 10-3 mm2/s; P = .04). CONCLUSIONS AND RELEVANCE Results of this study suggest that, in fetuses with FGR in pregnancies with PE or GH, decreased structural development of the CC, predominantly the splenium region, may be significantly associated with a higher risk of adverse perinatal outcomes and may be regarded as an MRI-based biomarker for better prenatal counseling and early management decisions.
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Affiliation(s)
- Weizeng Zheng
- Department of Radiology, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaodan Zhang
- Department of Radiology, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yan Feng
- Department of Obstetrics, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Bingqing Liu
- Department of Women’s Health, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiajun Zhu
- Department of Neonatology, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yu Zou
- Department of Radiology, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiale Qin
- Department of Ultrasound, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Women’s Reproductive Health Key Laboratory of Zhejiang Province, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Baohua Li
- Department of Obstetrics, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Women’s Reproductive Health Key Laboratory of Zhejiang Province, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Kebiri H, Canales-Rodríguez EJ, Lajous H, de Dumast P, Girard G, Alemán-Gómez Y, Koob M, Jakab A, Bach Cuadra M. Through-Plane Super-Resolution With Autoencoders in Diffusion Magnetic Resonance Imaging of the Developing Human Brain. Front Neurol 2022; 13:827816. [PMID: 35585848 PMCID: PMC9109939 DOI: 10.3389/fneur.2022.827816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 03/28/2022] [Indexed: 11/13/2022] Open
Abstract
Fetal brain diffusion magnetic resonance images (MRI) are often acquired with a lower through-plane than in-plane resolution. This anisotropy is often overcome by classical upsampling methods such as linear or cubic interpolation. In this work, we employ an unsupervised learning algorithm using an autoencoder neural network for single-image through-plane super-resolution by leveraging a large amount of data. Our framework, which can also be used for slice outliers replacement, overperformed conventional interpolations quantitatively and qualitatively on pre-term newborns of the developing Human Connectome Project. The evaluation was performed on both the original diffusion-weighted signal and the estimated diffusion tensor maps. A byproduct of our autoencoder was its ability to act as a denoiser. The network was able to generalize fetal data with different levels of motions and we qualitatively showed its consistency, hence supporting the relevance of pre-term datasets to improve the processing of fetal brain images.
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Affiliation(s)
- Hamza Kebiri
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Erick J. Canales-Rodríguez
- Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Hélène Lajous
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Priscille de Dumast
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Gabriel Girard
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Yasser Alemán-Gómez
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Mériam Koob
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - András Jakab
- Center for MR Research University Children's Hospital Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland
| | - Meritxell Bach Cuadra
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Zhang R, Manza P, Volkow ND. Prenatal caffeine exposure: association with neurodevelopmental outcomes in 9- to 11-year-old children. J Child Psychol Psychiatry 2022; 63:563-578. [PMID: 34318489 PMCID: PMC9291501 DOI: 10.1111/jcpp.13495] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/18/2021] [Indexed: 01/07/2023]
Abstract
BACKGROUND Despite the widespread use of caffeine including consumption during pregnancy, the effect of prenatal caffeine exposure on child brain development and behavior is unclear. METHODS To address this, we used data from the Adolescent Brain and Cognitive Development Study (n = 11,875 children aged 9-11 years from 22 sites across the United States). We explored the associations between prenatal caffeine exposure and various developmental outcomes including birth outcomes, physical health, behavior problems, cognition, substance use and brain structure in children, and evaluated dose effects. RESULTS Among 9,978 children (4,745 females) who had valid data for prenatal caffeine exposure and whose mothers did not use drugs of abuse after knowing of pregnancy, 4,170 (41.79%) had no prenatal caffeine exposure, 2,292 (22.97%) had daily, 1,933 (19.37%) had weekly, and 1,583 (15.86%) had less than weekly exposures. Prenatal caffeine exposure including the widely recommended 'safe' dose was associated with greater externalizing problems, whereas greater BMI and soda consumption were only observed in children with high dose exposures (3+ per day). Notably, the effect size for association of externalizing problems with prenatal caffeine exposure was comparable with that reported for prenatal alcohol (The American Journal of Psychiatry, 177, 2020 and 1060) and prenatal cannabis (JAMA Psychiatry, 78, 2020 and 64) exposures from previous ABCD publications. Additionally, prenatal caffeine exposure was associated with brain structural changes that included greater posterior and lower frontal cortical thickness and altered parietooccipital sulcal depth. CONCLUSIONS The recommended 'safe' dose of caffeine during pregnancy should be carefully studied to assess whether the behavioral and brain correlates observed here are clinically relevant and determine whether it needs adjustment. Because of the high prevalence of caffeine use in the general population, studies on prenatal exposure to drugs of abuse should include prenatal caffeine use as a covariate.
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Affiliation(s)
- Rui Zhang
- Laboratory of NeuroimagingNational Institute on Alcohol Abuse and AlcoholismNational Institutes of HealthBethesdaMDUSA
| | - Peter Manza
- Laboratory of NeuroimagingNational Institute on Alcohol Abuse and AlcoholismNational Institutes of HealthBethesdaMDUSA
| | - Nora D. Volkow
- Laboratory of NeuroimagingNational Institute on Alcohol Abuse and AlcoholismNational Institutes of HealthBethesdaMDUSA,National Institute on Drug AbuseNational Institutes of HealthBethesdaMDUSA
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Zhang F, Daducci A, He Y, Schiavi S, Seguin C, Smith RE, Yeh CH, Zhao T, O'Donnell LJ. Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review. Neuroimage 2022; 249:118870. [PMID: 34979249 PMCID: PMC9257891 DOI: 10.1016/j.neuroimage.2021.118870] [Citation(s) in RCA: 78] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 12/03/2021] [Accepted: 12/31/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.
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Affiliation(s)
- Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
| | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
| | - Chun-Hung Yeh
- Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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Pollatou A, Filippi CA, Aydin E, Vaughn K, Thompson D, Korom M, Dufford AJ, Howell B, Zöllei L, Martino AD, Graham A, Scheinost D, Spann MN. An ode to fetal, infant, and toddler neuroimaging: Chronicling early clinical to research applications with MRI, and an introduction to an academic society connecting the field. Dev Cogn Neurosci 2022; 54:101083. [PMID: 35184026 PMCID: PMC8861425 DOI: 10.1016/j.dcn.2022.101083] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/17/2021] [Accepted: 02/04/2022] [Indexed: 12/14/2022] Open
Abstract
Fetal, infant, and toddler neuroimaging is commonly thought of as a development of modern times (last two decades). Yet, this field mobilized shortly after the discovery and implementation of MRI technology. Here, we provide a review of the parallel advancements in the fields of fetal, infant, and toddler neuroimaging, noting the shifts from clinical to research use, and the ongoing challenges in this fast-growing field. We chronicle the pioneering science of fetal, infant, and toddler neuroimaging, highlighting the early studies that set the stage for modern advances in imaging during this developmental period, and the large-scale multi-site efforts which ultimately led to the explosion of interest in the field today. Lastly, we consider the growing pains of the community and the need for an academic society that bridges expertise in developmental neuroscience, clinical science, as well as computational and biomedical engineering, to ensure special consideration of the vulnerable mother-offspring dyad (especially during pregnancy), data quality, and image processing tools that are created, rather than adapted, for the young brain.
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Affiliation(s)
- Angeliki Pollatou
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Courtney A Filippi
- Section on Development and Affective Neuroscience, National Institute of Mental Health, Bethesda, MD, USA; Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, USA
| | - Ezra Aydin
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Kelly Vaughn
- Department of Pediatrics, University of Texas Health Sciences Center, Houston, TX, USA
| | - Deanne Thompson
- Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Marta Korom
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA
| | - Alexander J Dufford
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Brittany Howell
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA; Department of Human Development and Family Science, Virginia Tech, Blacksburg, VA, USA
| | - Lilla Zöllei
- Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | - Alice Graham
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | | | - Dustin Scheinost
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Marisa N Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA; Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA.
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Eryomin AL. Biophysics of Evolution of Intellectual Systems. Biophysics (Nagoya-shi) 2022; 67:320-326. [PMID: 35789557 PMCID: PMC9244026 DOI: 10.1134/s0006350922020051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 11/09/2021] [Accepted: 11/12/2021] [Indexed: 11/26/2022] Open
Abstract
The first work on noogenesis as evolution of intellect was published 150 years ago. However, it was not until the 21st century that quantitation became possible for certain parameters that contribute to the understanding of the evolution of intellectual systems in natural sciences, the progress being due to basic achievements in physics, biology, medicine, and interdisciplinary fields. Analyses of the parameters of intellectual systems, patterns of their emergence and evolution, distinctive features, and the constants and limits of their structures and functions made it possible to measure and compare the capacity of communications (~100 to 300 million m/s), to quantify the number of components in intellectual systems (10–100 billion components), and to calculate the number of successful links responsible for cooperation (from 150 to 1 trillion links). Prognostic models can be developed by studying the phenomenon of the origin and evolution of the brain as a population of neurons within the biological evolution of Homo sapiens and the advent of cognition; by studying the brain of an individual throughout individual anatomic and physiological development, including the development of creativity, thinking, consciousness, idea, insight, intuition, and eureka; and by studying and “noo” in the context of the hypothesis of the morphological and functional evolution of the human population.
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Affiliation(s)
- A. L. Eryomin
- Kuban State University, 350040 Krasnodar, Russia
- Kuban Medical Institute, 350015 Krasnodar, Russia
- Institute of Hygiene and Ecology, 350040 Krasnodar, Russia
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Neonatal brain injury influences structural connectivity and childhood functional outcomes. PLoS One 2022; 17:e0262310. [PMID: 34986206 PMCID: PMC8730412 DOI: 10.1371/journal.pone.0262310] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 12/21/2021] [Indexed: 11/19/2022] Open
Abstract
Neonatal brain injury may impact brain development and lead to lifelong functional impairments. Hypoxic-ischemic encephalopathy (HIE) and congenital heart disease (CHD) are two common causes of neonatal brain injury differing in timing and mechanism. Maturation of whole-brain neural networks can be quantified during development using diffusion magnetic resonance imaging (dMRI) in combination with graph theory metrics. DMRI of 35 subjects with CHD and 62 subjects with HIE were compared to understand differences in the effects of HIE and CHD on the development of network topological parameters and functional outcomes. CHD newborns had worse 12–18 month language (P<0.01) and 30 month cognitive (P<0.01), language (P = 0.05), motor outcomes (P = 0.01). Global efficiency, a metric of brain integration, was lower in CHD (P = 0.03) than in HIE, but transitivity, modularity and small-worldness were similar. After controlling for clinical factors known to affect neurodevelopmental outcomes, we observed that global efficiency was highly associated with 30 month motor outcomes (P = 0.02) in both groups. To explore neural correlates of adverse language outcomes in CHD, we used hypothesis-based and data-driven approaches to identify pathways with altered structural connectivity. We found that connectivity strength in the superior longitudinal fasciculus (SLF) tract 2 was inversely associated with expressive language. After false discovery rate correction, a whole connectome edge analysis identified 18 pathways that were hypoconnected in the CHD cohort as compared to HIE. In sum, our study shows that neonatal structural connectivity predicts early motor development after HIE or in subjects with CHD, and regional SLF connectivity is associated with language outcomes. Further research is needed to determine if and how brain networks change over time and whether those changes represent recovery or ongoing dysfunction. This knowledge will directly inform strategies to optimize neurologic functional outcomes after neonatal brain injury.
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Volumetric Segmentation of White Matter Tracts with Label Embedding. Neuroimage 2022; 250:118934. [PMID: 35091078 DOI: 10.1016/j.neuroimage.2022.118934] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 01/04/2022] [Accepted: 01/24/2022] [Indexed: 11/23/2022] Open
Abstract
Convolutional neural networks have achieved state-of-the-art performance for white matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI). However, the segmentation can still be difficult for challenging WM tracts with thin bodies or complicated shapes; the segmentation is even more problematic in challenging scenarios with reduced data quality or domain shift between training and test data, which can be easily encountered in clinical settings. In this work, we seek to improve the segmentation of WM tracts, especially for challenging WM tracts in challenging scenarios. In particular, our method is based on volumetric WM tract segmentation, where voxels are directly labeled without performing tractography. To improve the segmentation, we exploit the characteristics of WM tracts that different tracts can cross or overlap and revise the network design accordingly. Specifically, because multiple tracts can co-exist in a voxel, we hypothesize that the different tract labels can be correlated. The tract labels at a single voxel are concatenated as a label vector, the length of which is the number of tract labels. Due to the tract correlation, this label vector can be projected into a lower-dimensional space-referred to as the embedded space-for each voxel, which allows the segmentation network to solve a simpler problem. By predicting the coordinate in the embedded space for the tracts at each voxel and subsequently mapping the coordinate to the label vector with a reconstruction module, the segmentation result can be achieved. To facilitate the learning of the embedded space, an auxiliary label reconstruction loss is integrated with the segmentation accuracy loss during network training, and network training and inference are end-to-end. Our method was validated on two dMRI datasets under various settings. The results show that the proposed method improves the accuracy of WM tract segmentation, and the improvement is more prominent for challenging tracts in challenging scenarios.
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48
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Machado-Rivas F, Afacan O, Khan S, Marami B, Velasco-Annis C, Lidov H, Warfield SK, Gholipour A, Jaimes C. Spatiotemporal changes in diffusivity and anisotropy in fetal brain tractography. Hum Brain Mapp 2021; 42:5771-5784. [PMID: 34487404 PMCID: PMC8559496 DOI: 10.1002/hbm.25653] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 08/22/2021] [Accepted: 08/25/2021] [Indexed: 02/03/2023] Open
Abstract
Population averaged diffusion atlases can be utilized to characterize complex microstructural changes with less bias than data from individual subjects. In this study, a fetal diffusion tensor imaging (DTI) atlas was used to investigate tract-based changes in anisotropy and diffusivity in vivo from 23 to 38 weeks of gestational age (GA). Healthy pregnant volunteers with typically developing fetuses were imaged at 3 T. Acquisition included structural images processed with a super-resolution algorithm and DTI images processed with a motion-tracked slice-to-volume registration algorithm. The DTI from individual subjects were used to generate 16 templates, each specific to a week of GA; this was accomplished by means of a tensor-to-tensor diffeomorphic deformable registration method integrated with kernel regression in age. Deterministic tractography was performed to outline the forceps major, forceps minor, bilateral corticospinal tracts (CST), bilateral inferior fronto-occipital fasciculus (IFOF), bilateral inferior longitudinal fasciculus (ILF), and bilateral uncinate fasciculus (UF). The mean fractional anisotropy (FA) and mean diffusivity (MD) was recorded for all tracts. For a subset of tracts (forceps major, CST, and IFOF) we manually divided the tractograms into anatomy conforming segments to evaluate within-tract changes. We found tract-specific, nonlinear, age related changes in FA and MD. Early in gestation, these trends appear to be dominated by cytoarchitectonic changes in the transient white matter fetal zones while later in gestation, trends conforming to the progression of myelination were observed. We also observed significant (local) heterogeneity in within-tract developmental trajectories for the CST, IFOF, and forceps major.
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Affiliation(s)
- Fedel Machado-Rivas
- Computational Radiology Laboratory (CRL), Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Onur Afacan
- Computational Radiology Laboratory (CRL), Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Shadab Khan
- Computational Radiology Laboratory (CRL), Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Bahram Marami
- Computational Radiology Laboratory (CRL), Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Clemente Velasco-Annis
- Computational Radiology Laboratory (CRL), Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Hart Lidov
- Department of Pathology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Simon K Warfield
- Computational Radiology Laboratory (CRL), Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Ali Gholipour
- Computational Radiology Laboratory (CRL), Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Camilo Jaimes
- Computational Radiology Laboratory (CRL), Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA
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Oldham S, Ball G, Fornito A. Early and late development of hub connectivity in the human brain. Curr Opin Psychol 2021; 44:321-329. [PMID: 34896927 DOI: 10.1016/j.copsyc.2021.10.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 10/14/2021] [Accepted: 10/28/2021] [Indexed: 12/28/2022]
Abstract
Human brain networks undergo pronounced changes during development. The emergence of highly connected hub regions that can support integrated brain function is central to this maturational process, with these areas undergoing a particularly protracted period of development that extends into adulthood. The location of cortical network hubs emerges early but connections to and from hubs continue to strengthen throughout childhood and adolescence. Patterns of functional coupling in cortical association hubs are immature and incomplete at birth, but gradually strengthen during development. Early establishment of hub connectivity may provide a stable substrate that is refined by changes in tissue organization and microstructure, resulting in the emergence of complex functional dynamics by adulthood.
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Affiliation(s)
- Stuart Oldham
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia; Developmental Imaging, Murdoch Children's Research Institute, Victoria, Australia.
| | - Gareth Ball
- Developmental Imaging, Murdoch Children's Research Institute, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
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Yee E, Ma D, Popuri K, Chen S, Lee H, Chow V, Ma C, Wang L, Beg MF. 3D hemisphere-based convolutional neural network for whole-brain MRI segmentation. Comput Med Imaging Graph 2021; 95:102000. [PMID: 34839147 PMCID: PMC10116838 DOI: 10.1016/j.compmedimag.2021.102000] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 09/30/2021] [Accepted: 10/04/2021] [Indexed: 10/19/2022]
Abstract
Whole-brain segmentation is a crucial pre-processing step for many neuroimaging analyses pipelines. Accurate and efficient whole-brain segmentations are important for many neuroimage analysis tasks to provide clinically relevant information. Several recently proposed convolutional neural networks (CNN) perform whole brain segmentation using individual 2D slices or 3D patches as inputs due to graphical processing unit (GPU) memory limitations, and use sliding windows to perform whole brain segmentation during inference. However, these approaches lack global and spatial information about the entire brain and lead to compromised efficiency during both training and testing. We introduce a 3D hemisphere-based CNN for automatic whole-brain segmentation of T1-weighted magnetic resonance images of adult brains. First, we trained a localization network to predict bounding boxes for both hemispheres. Then, we trained a segmentation network to segment one hemisphere, and segment the opposing hemisphere by reflecting it across the mid-sagittal plane. Our network shows high performance both in terms of segmentation efficiency and accuracy (0.84 overall Dice similarity and 6.1 mm overall Hausdorff distance) in segmenting 102 brain structures. On multiple independent test datasets, our method demonstrated a competitive performance in the subcortical segmentation task and a high consistency in volumetric measurements of intra-session scans.
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Affiliation(s)
- Evangeline Yee
- School of Engineering Science, Simon Fraser University, Canada
| | - Da Ma
- School of Engineering Science, Simon Fraser University, Canada
| | - Karteek Popuri
- School of Engineering Science, Simon Fraser University, Canada
| | - Shuo Chen
- School of Engineering Science, Simon Fraser University, Canada
| | - Hyunwoo Lee
- School of Engineering Science, Simon Fraser University, Canada; Division of Neurology, Department of Medicine, University of British Columbia, Canada
| | - Vincent Chow
- School of Engineering Science, Simon Fraser University, Canada
| | - Cydney Ma
- School of Engineering Science, Simon Fraser University, Canada
| | - Lei Wang
- Department of Psychiatry and Behavioral Health, College of Medicine, The Ohio State University, Canada; Feinberg School of Medicine, Northwest University, Canada
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