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Xu Y, Liao X, Lei T, Cao M, Zhao J, Zhang J, Zhao T, Li Q, Jeon T, Ouyang M, Chalak L, Rollins N, Huang H, He Y. Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2. Cereb Cortex 2024; 34:bhae204. [PMID: 38771241 DOI: 10.1093/cercor/bhae204] [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: 12/15/2023] [Revised: 04/23/2024] [Accepted: 05/01/2024] [Indexed: 05/22/2024] Open
Abstract
The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2 years of age. Our findings highlight network-level neural substrates underlying early cognitive development.
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Affiliation(s)
- Yuehua Xu
- School of Systems Science, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Miao Cao
- Institution of Science and Technology for Brain-Inspired Intelligence, Fudan University, No. 220 Handan Road, Shanghai 200433, China
| | - Jianlong Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Jiaying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Tina Jeon
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, United States
| | - Minhui Ouyang
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, United States
- Department of Radiology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - Lina Chalak
- Department of Pediatrics, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, United States
| | - Nancy Rollins
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, United States
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, United States
- Department of Radiology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Chinese Institute for Brain Research, No. 26 Kexueyuan Road, Beijing 102206, China
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Calixto C, Machado‐Rivas F, Karimi D, Cortes‐Albornoz MC, Acosta‐Buitrago LM, Gallo‐Bernal S, Afacan O, Warfield SK, Gholipour A, Jaimes C. Detailed anatomic segmentations of a fetal brain diffusion tensor imaging atlas between 23 and 30 weeks of gestation. Hum Brain Mapp 2023; 44:1593-1602. [PMID: 36421003 PMCID: PMC9921217 DOI: 10.1002/hbm.26160] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 11/02/2022] [Accepted: 11/12/2022] [Indexed: 11/25/2022] Open
Abstract
This work presents detailed anatomic labels for a spatiotemporal atlas of fetal brain Diffusion Tensor Imaging (DTI) between 23 and 30 weeks of post-conceptional age. Additionally, we examined developmental trajectories in fractional anisotropy (FA) and mean diffusivity (MD) across gestational ages (GA). We performed manual segmentations on a fetal brain DTI atlas. We labeled 14 regions of interest (ROIs): cortical plate (CP), subplate (SP), Intermediate zone-subventricular zone-ventricular zone (IZ/SVZ/VZ), Ganglionic Eminence (GE), anterior and posterior limbs of the internal capsule (ALIC, PLIC), genu (GCC), body (BCC), and splenium (SCC) of the corpus callosum (CC), hippocampus, lentiform Nucleus, thalamus, brainstem, and cerebellum. A series of linear regressions were used to assess GA as a predictor of FA and MD for each ROI. The combination of MD and FA allowed the identification of all ROIs. Increasing GA was significantly associated with decreasing FA in the CP, SP, IZ/SVZ/IZ, GE, ALIC, hippocampus, and BCC (p < .03, for all), and with increasing FA in the PLIC and SCC (p < .002, for both). Increasing GA was significantly associated with increasing MD in the CP, SP, IZ/SVZ/IZ, GE, ALIC, and CC (p < .03, for all). We developed a set of expert-annotated labels for a DTI spatiotemporal atlas of the fetal brain and presented a pilot analysis of developmental changes in cerebral microstructure between 23 and 30 weeks of GA.
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Affiliation(s)
- Camilo Calixto
- Computational Radiology Laboratory, Department of RadiologyBoston Children's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - Fedel Machado‐Rivas
- Computational Radiology Laboratory, Department of RadiologyBoston Children's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - Davood Karimi
- Computational Radiology Laboratory, Department of RadiologyBoston Children's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - Maria C. Cortes‐Albornoz
- Computational Radiology Laboratory, Department of RadiologyBoston Children's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | | | - Sebastian Gallo‐Bernal
- Harvard Medical SchoolBostonMassachusettsUSA
- Massachusetts General HospitalBostonMassachusettsUSA
| | - Onur Afacan
- Computational Radiology Laboratory, Department of RadiologyBoston Children's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - Simon K. Warfield
- Computational Radiology Laboratory, Department of RadiologyBoston Children's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of RadiologyBoston Children's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - Camilo Jaimes
- Computational Radiology Laboratory, Department of RadiologyBoston Children's HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
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Brain Development and Maternal Behavior in Relation to Cognitive and Language Outcomes in Preterm-Born Children. Biol Psychiatry 2022; 92:663-673. [PMID: 35599181 DOI: 10.1016/j.biopsych.2022.03.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 03/08/2022] [Accepted: 03/16/2022] [Indexed: 11/21/2022]
Abstract
BACKGROUND Children born very preterm (≤32 weeks gestational age) show poorer cognitive and language development compared with their term-born peers. The importance of supportive maternal responses to the child's cues for promoting neurodevelopment is well established. However, little is known about whether supportive maternal behavior can buffer the association of early brain dysmaturation with cognitive and language performance. METHODS Infants born very preterm (N = 226) were recruited from the neonatal intensive care unit for a prospective, observational cohort study. Chart review (e.g., size at birth, postnatal infection) was conducted from birth to discharge. Magnetic resonance imaging, including diffusion tensor imaging, was acquired at approximately 32 weeks postmenstrual age and again at term-equivalent age. Fractional anisotropy, a quantitative measure of brain maturation, was obtained from 11 bilateral regions of interest in the cortical gray matter. At 3 years (n = 187), neurodevelopmental testing (Bayley Scales of Infant and Toddler Development-III) was administered, and parent-child interaction was filmed. Maternal behavior was scored using the Emotional Availability Scale-IV. A total of 146 infants with neonatal brain imaging and follow-up data were included for analysis. Generalized estimating equations were used to examine whether maternal support interacted with mean fractional anisotropy values to predict Cognitive and Language scores at 3 years, accounting for confounding neonatal and maternal factors. RESULTS Higher maternal support significantly moderated cortical fractional anisotropy values at term-equivalent age to predict higher Cognitive (interaction term β = 2.01, p = .05) and Language (interaction term β = 1.85, p = .04) scores. CONCLUSIONS Findings suggest that supportive maternal behavior following early brain dysmaturation may provide an opportunity to promote optimal neurodevelopment in children born very preterm.
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Iwata S, Katayama R, Tsuda K, Lin YC, Kurata T, Kinoshita M, Kawase K, Kato T, Kato S, Hisano T, Oda M, Ohmae E, Takashima S, Araki Y, Saitoh S, Iwata O. Near-infrared light scattering and water diffusion in newborn brains. Ann Clin Transl Neurol 2022; 9:1417-1427. [PMID: 35943446 PMCID: PMC9463954 DOI: 10.1002/acn3.51641] [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: 07/04/2022] [Accepted: 07/19/2022] [Indexed: 11/26/2022] Open
Abstract
Objective MRI provides useful information regarding brain maturation and injury in newborn infants. However, MRI studies are generally restricted during acute phase, resulting in uncertainty around upstream clinical events responsible for subtle cerebral injuries. Time‐resolved near‐infrared spectroscopy non‐invasively provides the reduced scattering coefficient (μs′), which theoretically reflects tissue structural complexity. This study aimed to test whether μs′ values of the newborn head reflected MRI findings. Methods Between June 2009 and January 2015, 77 hospitalised newborn infants (31.7 ± 3.8 weeks gestation) were assessed at 38.8 ± 1.3 weeks post‐conceptional age. Associations of μs′ values with MRI scores, mean diffusivity and fractional anisotropy were assessed. Results Univariable analysis showed that μs′ values were associated with gestational week (p = 0.035; regression coefficient [B], 0.065; 95% confidence interval [CI], 0.005–0.125), fractional anisotropy in the cortical grey matter (p = 0.020; B, −5.994; 95%CI, −11.032 to −0.957), average diffusivity in the cortical grey matter (p < 0.001; B, −4.728; 95%CI, −7.063 to −2.394) and subcortical white matter (p = 0.001; B, −2.071; 95%CI, −3.311 to −0.832), subarachnoid space (p < 0.001; B, −0.289; 95%CI, −0.376 to −0.201) and absence of brain abnormality (p = 0.042; B, −0.422; 95%CI, −0.829 to −0.015). The multivariable model to explain μs′ values comprised average diffusivity in the subcortical white matter (p < 0.001; B, −2.066; 95%CI, −3.200 to −0.932), subarachnoid space (p < 0.001; B, −0.314; 95%CI, −0.412 to −0.216) and absence of brain abnormality (p = 0.021; B, −0.400; 95%CI, −0.739 to −0.061). Interpretation Light scattering was associated with brain structure indicated by MRI‐assessed brain abnormality and diffusion‐tensor‐imaging‐assessed water diffusivity. When serially assessed in a larger population, μs′ values might help identify covert clinical events responsible for subtle cerebral injury.
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Affiliation(s)
- Sachiko Iwata
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan.,Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Reiji Katayama
- Centre for the Study of Medical Education, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Kennosuke Tsuda
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan.,Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Yung-Chieh Lin
- Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng-Kung University, Tainan, 70457, Taiwan
| | - Tsuyoshi Kurata
- Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Masahiro Kinoshita
- Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Koya Kawase
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Takenori Kato
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Shin Kato
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Tadashi Hisano
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Motoki Oda
- Central Research Laboratory, Hamamatsu Photonics K.K., Hamamatsu, Shizuoka, 434-8601, Japan
| | - Etsuko Ohmae
- Central Research Laboratory, Hamamatsu Photonics K.K., Hamamatsu, Shizuoka, 434-8601, Japan
| | - Sachio Takashima
- Yanagawa Institute for Developmental Disabilities, International University of Health and Welfare, Yanagawa, Fukuoka, 832-0813, Japan
| | - Yuko Araki
- Graduate School of Information Sciences, Tohoku University, Sendai City, Miyagi, 980-8579, Japan
| | - Shinji Saitoh
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Osuke Iwata
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan.,Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
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Pediatric Brain Maturation and Migration Disorders. Diagnostics (Basel) 2022; 12:diagnostics12051123. [PMID: 35626279 PMCID: PMC9139849 DOI: 10.3390/diagnostics12051123] [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: 03/13/2022] [Revised: 04/13/2022] [Accepted: 04/26/2022] [Indexed: 11/30/2022] Open
Abstract
Neurodevelopmental disorders, including neuronal migration disorders, are best understood in the context of altered normal development. Neurons normally migrate from their site of origin to their (usually cortical) destination using a wide range of molecular and cellular signaling as a guide. In the case of abnormal migration neurons: (1) do not migrate and remain at their site of origin; (2) incompletely migrate and remain within the white matter; (3) migrate to the cortex but fail to organize correctly; or (4) over-migrate, beyond the cortex. In this review, we discuss normal brain development, along with the malformations that result from these different migration abnormalities.
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Yuan S, Liu M, Kim S, Yang J, Barkovich AJ, Xu D, Kim H. Cyto/myeloarchitecture of cortical gray matter and superficial white matter in early neurodevelopment: multimodal MRI study in preterm neonates. Cereb Cortex 2022; 33:357-373. [PMID: 35235643 PMCID: PMC9837610 DOI: 10.1093/cercor/bhac071] [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: 09/07/2021] [Revised: 01/21/2022] [Accepted: 01/22/2022] [Indexed: 01/19/2023] Open
Abstract
The cerebral cortex undergoes rapid microstructural changes throughout the third trimester. Recently, there has been growing interest on imaging features that represent cyto/myeloarchitecture underlying intracortical myelination, cortical gray matter (GM), and its adjacent superficial whitematter (sWM). Using 92 magnetic resonance imaging scans from 78 preterm neonates, the current study used combined T1-weighted/T2-weighted (T1w/T2w) intensity ratio and diffusion tensor imaging (DTI) measurements, including fractional anisotropy (FA) and mean diffusivity (MD), to characterize the developing cyto/myeloarchitectural architecture. DTI metrics showed a linear trajectory: FA decreased in GM but increased in sWM with time; and MD decreased in both GM and sWM. Conversely, T1w/T2w measurements showed a distinctive parabolic trajectory, revealing additional cyto/myeloarchitectural signature inferred. Furthermore, the spatiotemporal courses were regionally heterogeneous: central, ventral, and temporal regions of GM and sWM exhibited faster T1w/T2w changes; anterior sWM areas exhibited faster FA increases; and central and cingulate areas in GM and sWM exhibited faster MD decreases. These results may explain cyto/myeloarchitectural processes, including dendritic arborization, synaptogenesis, glial proliferation, and radial glial cell organization and apoptosis. Finally, T1w/T2w values were significantly associated with 1-year language and cognitive outcome scores, while MD significantly decreased with intraventricular hemorrhage.
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Affiliation(s)
| | | | | | - Jingda Yang
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Anthony James Barkovich
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Duan Xu
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Hosung Kim
- Corresponding author: 2025 Zonal Ave, Los Angeles, CA 90033, USA.
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Wisnowski JL, Wintermark P, Bonifacio SL, Smyser CD, Barkovich AJ, Edwards AD, de Vries LS, Inder TE, Chau V. Neuroimaging in the term newborn with neonatal encephalopathy. Semin Fetal Neonatal Med 2021; 26:101304. [PMID: 34736808 PMCID: PMC9135955 DOI: 10.1016/j.siny.2021.101304] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Neuroimaging is widely used to aid in the diagnosis and clinical management of neonates with neonatal encephalopathy (NE). Yet, despite widespread use clinically, there are few published guidelines on neuroimaging for neonates with NE. This review outlines the primary patterns of brain injury associated with hypoxic-ischemic injury in neonates with NE and their frequency, associated neuropathological features, and risk factors. In addition, it provides an overview of neuroimaging methods, including the most widely used scoring systems used to characterize brain injury in these neonates and their utility as predictive biomarkers. Last, recommendations for neuroimaging in neonates with NE are presented.
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Affiliation(s)
- Jessica L. Wisnowski
- Departments of Radiology and Pediatrics (Neonatology), Children’s Hospital Los Angeles, 4650 Sunset Blvd. MS #81, Los Angeles CA 90027, USA
| | - Pia Wintermark
- Department of Pediatrics (Neonatology), McGill University/Montreal Children's Hospital, Division of Newborn Medicine, Research Institute of the McGill University Health Centre, 1001 boul. Décarie, Site Glen Block E, EM0.3244, Montréal, QC H4A 3J1, Canada.
| | - Sonia L. Bonifacio
- Division of Neonatal and Developmental Medicine, Department of Pediatrics (Neonatology), Lucile Packard Children’s Hospital, Stanford University School of Medicine, 750 Welch Road, Suite 315, Palo Alto, CA 94304, USA
| | - Christopher D. Smyser
- Departments of Neurology, Radiology, and Pediatrics, Washington University School of Medicine, 660 South Euclid Avenue, Campus Box 8111, St Louis, MO 63110-1093, USA
| | - A. James Barkovich
- Department of Radiology, UCSF Benioff Children’s Hospital, University of California San Francisco, 505 Parnassus Avenue, M-391, San Francisco, CA 94143-0628, USA
| | - A. David Edwards
- Evelina London Children’s Hospital, Centre for Developing Brain, King’s College London, Westminster Bridge Road, London, SE1 7EH, United Kingdom
| | - Linda S. de Vries
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Lundlaan 6, 3584 EA, Utrecht, the Netherlands
| | - Terrie E. Inder
- Department of Pediatric Newborn Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Vann Chau
- Department of Pediatrics (Neurology), The Hospital for Sick Children, University of Toronto, 555 University Avenue, Room 6513, Toronto, ON M5G 1X8, Canada.
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Dhari Z, Leonetti C, Lin S, Prince A, Howick J, Zurakowski D, Wang PC, Jonas RA, Ishibashi N. Impact of Cardiopulmonary Bypass on Neurogenesis and Cortical Maturation. Ann Neurol 2021; 90:913-926. [PMID: 34590341 DOI: 10.1002/ana.26235] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 09/22/2021] [Accepted: 09/26/2021] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Neurodevelopmental delays and frontal lobe cortical dysmaturation are widespread among children with congenital heart disease (CHD). The subventricular zone (SVZ) is the largest pool of neural stem/progenitor cells in the postnatal brain. Our aim is to determine the effects of cardiopulmonary bypass (CPB) on neurogenesis and cortical maturation in piglets whose SVZ development is similar to human infants. METHODS Three-week-old piglets (n = 29) were randomly assigned to control (no surgery), mild-CPB (34°C full flow for 60 minutes) and severe-CPB groups (25°C circulatory-arrest for 60 minutes). The SVZ and frontal lobe were analyzed with immunohistochemistry 3 days and 4 weeks postoperatively. MRI of the frontal lobe was used to assess cortical development. RESULTS SVZ neurogenic activity was reduced up to 4 weeks after both mild and severe CPB-induced insults. CPB also induced decreased migration of young neurons to the frontal lobe, demonstrating that CPB impairs postnatal neurogenesis. MRI 4 weeks after CPB displayed a decrease in gyrification index and cortical volume of the frontal lobe. Cortical fractional anisotropy was increased after severe CPB injury, indicating a prolonged deleterious impact of CPB on cortical maturation. Both CPB-induced insults displayed a significant change in densities of three major inhibitory neurons, suggesting excitatory-inhibitory imbalance in the frontal cortex. In addition, different CPB insults altered different subpopulations of inhibitory neurons. INTERPRETATION Our results provide novel insights into cellular mechanisms contributing to CHD-induced neurological impairments. Further refinement of CPB hardware and techniques is necessary to improve long-term frontal cortical dysmaturation observed in children with CHD. ANN NEUROL 2021.
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Affiliation(s)
- Zaenab Dhari
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC
| | - Camille Leonetti
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC
| | - Stephen Lin
- Department of Radiology, Howard University, Washington, DC
| | - Arianna Prince
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC.,George Washington University School of Medicine and Health Science, Washington, DC
| | - James Howick
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC
| | - David Zurakowski
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Paul C Wang
- Department of Radiology, Howard University, Washington, DC.,Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan
| | - Richard A Jonas
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC.,George Washington University School of Medicine and Health Science, Washington, DC
| | - Nobuyuki Ishibashi
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC.,George Washington University School of Medicine and Health Science, Washington, DC
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Hickmott RA, Bosakhar A, Quezada S, Barresi M, Walker DW, Ryan AL, Quigley A, Tolcos M. The One-Stop Gyrification Station - Challenges and New Technologies. Prog Neurobiol 2021; 204:102111. [PMID: 34166774 DOI: 10.1016/j.pneurobio.2021.102111] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 05/31/2021] [Accepted: 06/18/2021] [Indexed: 12/12/2022]
Abstract
The evolution of the folded cortical surface is an iconic feature of the human brain shared by a subset of mammals and considered pivotal for the emergence of higher-order cognitive functions. While our understanding of the neurodevelopmental processes involved in corticogenesis has greatly advanced over the past 70 years of brain research, the fundamental mechanisms that result in gyrification, along with its originating cytoarchitectural location, remain largely unknown. This review brings together numerous approaches to this basic neurodevelopmental problem, constructing a narrative of how various models, techniques and tools have been applied to the study of gyrification thus far. After a brief discussion of core concepts and challenges within the field, we provide an analysis of the significant discoveries derived from the parallel use of model organisms such as the mouse, ferret, sheep and non-human primates, particularly with regard to how they have shaped our understanding of cortical folding. We then focus on the latest developments in the field and the complementary application of newly emerging technologies, such as cerebral organoids, advanced neuroimaging techniques, and atomic force microscopy. Particular emphasis is placed upon the use of novel computational and physical models in regard to the interplay of biological and physical forces in cortical folding.
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Affiliation(s)
- Ryan A Hickmott
- School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC, 3083, Australia; BioFab3D@ACMD, St Vincent's Hospital Melbourne, Fitzroy, VIC, 3065, Australia
| | - Abdulhameed Bosakhar
- School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC, 3083, Australia
| | - Sebastian Quezada
- School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC, 3083, Australia
| | - Mikaela Barresi
- School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC, 3083, Australia
| | - David W Walker
- School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC, 3083, Australia
| | - Amy L Ryan
- Hastings Centre for Pulmonary Research, Department of Pulmonary, Critical Care and Sleep Medicine, USC Keck School of Medicine, University of Southern California, CA, USA and Department of Stem Cell and Regenerative Medicine, University of Southern California, CA, 90033, USA
| | - Anita Quigley
- School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC, 3083, Australia; BioFab3D@ACMD, St Vincent's Hospital Melbourne, Fitzroy, VIC, 3065, Australia; School of Engineering, RMIT University, Melbourne, VIC, 3000, Australia; Department of Medicine, University of Melbourne, St Vincent's Hospital, Fitzroy, VIC, 3065, Australia; ARC Centre of Excellence in Electromaterials Science, University of Wollongong, Wollongong, NSW, 2522, Australia
| | - Mary Tolcos
- School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC, 3083, Australia.
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10
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Xu Y, Cao M, Liao X, Xia M, Wang X, Jeon T, Ouyang M, Chalak L, Rollins N, Huang H, He Y. Development and Emergence of Individual Variability in the Functional Connectivity Architecture of the Preterm Human Brain. Cereb Cortex 2020; 29:4208-4222. [PMID: 30534949 DOI: 10.1093/cercor/bhy302] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 11/07/2018] [Indexed: 01/10/2023] Open
Abstract
Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31-42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.
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Affiliation(s)
- Yuehua Xu
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875 China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875 China
| | - Miao Cao
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875 China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875 China
| | - Xuhong Liao
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875 China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875 China
| | - Mingrui Xia
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875 China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875 China
| | - Xindi Wang
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875 China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875 China
| | - Tina Jeon
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Minhui Ouyang
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Lina Chalak
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Nancy Rollins
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yong He
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875 China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875 China
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11
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Generalization of diffusion magnetic resonance imaging–based brain age prediction model through transfer learning. Neuroimage 2020; 217:116831. [DOI: 10.1016/j.neuroimage.2020.116831] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 03/18/2020] [Accepted: 03/19/2020] [Indexed: 11/23/2022] Open
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12
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Kelly CJ, Christiaens D, Batalle D, Makropoulos A, Cordero-Grande L, Steinweg JK, O'Muircheartaigh J, Khan H, Lee G, Victor S, Alexander DC, Zhang H, Simpson J, Hajnal JV, Edwards AD, Rutherford MA, Counsell SJ. Abnormal Microstructural Development of the Cerebral Cortex in Neonates With Congenital Heart Disease Is Associated With Impaired Cerebral Oxygen Delivery. J Am Heart Assoc 2020; 8:e009893. [PMID: 30821171 PMCID: PMC6474935 DOI: 10.1161/jaha.118.009893] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Background Abnormal macrostructural development of the cerebral cortex has been associated with hypoxia in infants with congenital heart disease ( CHD ). Animal studies have suggested that hypoxia results in cortical dysmaturation at the cellular level. New magnetic resonance imaging techniques offer the potential to investigate the relationship between cerebral oxygen delivery and cortical microstructural development in newborn infants with CHD . Methods and Results We measured cortical macrostructural and microstructural properties in 48 newborn infants with serious or critical CHD and 48 age-matched healthy controls. Cortical volume and gyrification index were calculated from high-resolution structural magnetic resonance imaging. Neurite density and orientation dispersion indices were modeled using high-angular-resolution diffusion magnetic resonance imaging. Cerebral oxygen delivery was estimated in infants with CHD using phase contrast magnetic resonance imaging and preductal pulse oximetry. We used gray matter-based spatial statistics to examine voxel-wise group differences in cortical microstructure. Microstructural development of the cortex was abnormal in 48 infants with CHD , with regions of increased fractional anisotropy and reduced orientation dispersion index compared with 48 healthy controls, correcting for gestational age at birth and scan (family-wise error corrected for multiple comparisons at P<0.05). Regions of reduced cortical orientation dispersion index in infants with CHD were related to impaired cerebral oxygen delivery ( R2=0.637; n=39). Cortical orientation dispersion index was associated with the gyrification index ( R2=0.589; P<0.001; n=48). Conclusions This study suggests that the primary component of cerebral cortex dysmaturation in CHD is impaired dendritic arborization, which may underlie abnormal macrostructural findings reported in this population, and that the degree of impairment is related to reduced cerebral oxygen delivery.
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Affiliation(s)
- Christopher J Kelly
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom
| | - Daan Christiaens
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom
| | - Dafnis Batalle
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom
| | - Antonios Makropoulos
- 2 Biomedical Image Analysis Group Department of Computing Imperial College London London United Kingdom
| | - Lucilio Cordero-Grande
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom
| | - Johannes K Steinweg
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom
| | - Jonathan O'Muircheartaigh
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom.,3 Department of Forensic and Neurodevelopmental Sciences King's College London Institute of Psychiatry, Psychology and Neuroscience London United Kingdom.,4 Department of Neuroimaging King's College London Institute of Psychiatry, Psychology and Neuroscience London United Kingdom.,5 MRC Centre for Neurodevelopmental Disorders King's College London London United Kingdom
| | - Hammad Khan
- 6 Neonatal Intensive Care Unit St Thomas' Hospital London United Kingdom
| | - Geraint Lee
- 6 Neonatal Intensive Care Unit St Thomas' Hospital London United Kingdom
| | - Suresh Victor
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom
| | - Daniel C Alexander
- 7 Department of Computer Science and Centre for Medical Image Computing University College London London United Kingdom
| | - Hui Zhang
- 7 Department of Computer Science and Centre for Medical Image Computing University College London London United Kingdom
| | - John Simpson
- 8 Paediatric Cardiology Department Evelina London Children's Hospital St Thomas' Hospital London United Kingdom
| | - Joseph V Hajnal
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom
| | - A David Edwards
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom.,5 MRC Centre for Neurodevelopmental Disorders King's College London London United Kingdom
| | - Mary A Rutherford
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom
| | - Serena J Counsell
- 1 Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King's College London St Thomas' Hospital London United Kingdom
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13
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Quezada S, van de Looij Y, Hale N, Rana S, Sizonenko SV, Gilchrist C, Castillo-Melendez M, Tolcos M, Walker DW. Genetic and microstructural differences in the cortical plate of gyri and sulci during gyrification in fetal sheep. Cereb Cortex 2020; 30:6169-6190. [PMID: 32609332 DOI: 10.1093/cercor/bhaa171] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 05/29/2020] [Accepted: 05/29/2020] [Indexed: 12/28/2022] Open
Abstract
Gyrification of the cerebral cortex is a developmentally important process, but the mechanisms that drive cortical folding are not fully known. Theories propose that changes within the cortical plate (CP) cause gyrification, yet differences between the CP below gyri and sulci have not been investigated. Here we report genetic and microstructural differences in the CP below gyri and sulci assessed before (at 70 days of gestational age [GA] 70), during (GA 90), and after (GA 110) gyrification in fetal sheep. The areal density of BDNF, CDK5, and NeuroD6 immunopositive cells were increased, and HDAC5 and MeCP2 mRNA levels were decreased in the CP below gyri compared with sulci during gyrification, but not before. Only the areal density of BDNF-immunopositive cells remained increased after gyrification. MAP2 immunoreactivity and neurite outgrowth were also increased in the CP below gyri compared with sulci at GA 90, and this was associated with microstructural changes assessed via diffusion tensor imaging and neurite orientation dispersion and density imaging at GA 98. Differential neurite outgrowth may therefore explain the localized changes in CP architecture that result in gyrification.
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Affiliation(s)
- Sebastian Quezada
- The Ritchie Centre, Hudson Institute of Medical Research, Monash University, Clayton, VIC 3168, Australia.,Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC 3168, Australia.,School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC 3083 Australia
| | - Yohan van de Looij
- Division of Development and Growth, Department of Paediatrics and Gynaecology-Obstetrics, School of Medicine, University of Geneva, 1204 Geneva, Switzerland.,Functional and Metabolic Imaging Lab, Federal Institute of Technology of Lausanne, Lausanne 1015, Switzerland
| | - Nadia Hale
- The Ritchie Centre, Hudson Institute of Medical Research, Monash University, Clayton, VIC 3168, Australia.,Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC 3168, Australia
| | - Shreya Rana
- The Ritchie Centre, Hudson Institute of Medical Research, Monash University, Clayton, VIC 3168, Australia.,Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC 3168, Australia
| | - Stéphane V Sizonenko
- Division of Development and Growth, Department of Paediatrics and Gynaecology-Obstetrics, School of Medicine, University of Geneva, 1204 Geneva, Switzerland
| | - Courtney Gilchrist
- School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC 3083 Australia.,Clinical Sciences, Murdoch Children's Research Institute, Parkville, VIC 3052, Australia
| | - Margie Castillo-Melendez
- The Ritchie Centre, Hudson Institute of Medical Research, Monash University, Clayton, VIC 3168, Australia.,Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC 3168, Australia
| | - Mary Tolcos
- The Ritchie Centre, Hudson Institute of Medical Research, Monash University, Clayton, VIC 3168, Australia.,Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC 3168, Australia.,School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC 3083 Australia
| | - David W Walker
- The Ritchie Centre, Hudson Institute of Medical Research, Monash University, Clayton, VIC 3168, Australia.,Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC 3168, Australia.,School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC 3083 Australia
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14
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Palombo M, Ianus A, Guerreri M, Nunes D, Alexander DC, Shemesh N, Zhang H. SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI. Neuroimage 2020; 215:116835. [PMID: 32289460 PMCID: PMC8543044 DOI: 10.1016/j.neuroimage.2020.116835] [Citation(s) in RCA: 120] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 03/26/2020] [Accepted: 04/06/2020] [Indexed: 11/29/2022] Open
Abstract
This work introduces a compartment-based model for apparent cell body (namely soma) and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in brain microstructure imaging through DW-MRI presents water diffusion in white (WM) and gray (GM) matter as restricted diffusion in neurites, modelled by infinite cylinders of null radius embedded in the hindered extra-neurite water. The extra-neurite pool in WM corresponds to water in the extra-axonal space, but in GM it combines water in the extra-cellular space with water in soma. While several studies showed that this microstructure model successfully describe DW-MRI data in WM and GM at b ≤ 3,000 s/mm2 (or 3 ms/μm2), it has been also shown to fail in GM at high b values (b≫3,000 s/mm2 or 3 ms/μm2). Here we hypothesise that the unmodelled soma compartment (i.e. cell body of any brain cell type: from neuroglia to neurons) may be responsible for this failure and propose SANDI as a new model of brain microstructure where soma of any brain cell type is explicitly included. We assess the effects of size and density of soma on the direction-averaged DW-MRI signal at high b values and the regime of validity of the model using numerical simulations and comparison with experimental data from mouse (bmax = 40,000 s/mm2, or 40 ms/μm2) and human (bmax = 10,000 s/mm2, or 10 ms/μm2) brain. We show that SANDI defines new contrasts representing complementary information on the brain cyto- and myelo-architecture. Indeed, we show maps from 25 healthy human subjects of MR soma and neurite signal fractions, that remarkably mirror contrasts of histological images of brain cyto- and myelo-architecture. Although still under validation, SANDI might provide new insight into tissue architecture by introducing a new set of biomarkers of potential great value for biomedical applications and pure neuroscience.
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Affiliation(s)
- Marco Palombo
- Centre for Medical Image Computing and Dept of Computer Science, University College London, London, UK.
| | - Andrada Ianus
- Centre for Medical Image Computing and Dept of Computer Science, University College London, London, UK; Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Michele Guerreri
- Centre for Medical Image Computing and Dept of Computer Science, University College London, London, UK
| | - Daniel Nunes
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Daniel C Alexander
- Centre for Medical Image Computing and Dept of Computer Science, University College London, London, UK
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Hui Zhang
- Centre for Medical Image Computing and Dept of Computer Science, University College London, London, UK
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15
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Kim H, Shon SH, Joo SW, Yoon W, Lee JH, Hur JW, Lee J. Gray Matter Microstructural Abnormalities and Working Memory Deficits in Individuals with Schizophrenia. Psychiatry Investig 2019; 16:234-243. [PMID: 30934191 PMCID: PMC6444097 DOI: 10.30773/pi.2018.10.14.1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 09/12/2018] [Accepted: 10/14/2018] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVE Working memory impairments serve as prognostic factors for patients with schizophrenia. Working memory deficits are mainly associated with gray matter (GM) thickness and volume. We investigated the association between GM diffusivity and working memory in controls and individuals with schizophrenia. METHODS T1 and diffusion tensor images of the brain, working memory task (letter number sequencing) scores, and the demographic data of 90 individuals with schizophrenia and 97 controls were collected from the SchizConnect database. T1 images were parcellated into the 68 GM Regions of Interest (ROI). Axial Diffusivity (AD), Fractional Anisotropy (FA), Radial Diffusivity (RD), and Trace (TR) were calculated for each of the ROIs. RESULTS Compared to the controls, schizophrenia group showed significantly increased AD, RD, and TR in specific regions on the frontal, temporal, and anterior cingulate area. Moreover, working memory was negatively correlated with AD, RD, and TR in the lateral orbitofrontal, superior temporal, inferior temporal, and rostral anterior cingulate area on left hemisphere in the individuals with schizophrenia. CONCLUSION These results demonstrated GM microstructural abnormalities in the frontal, temporal, and anterior cingulate regions of individuals with schizophrenia. Furthermore, these regional GM microstructural abnormalities suggest a neuropathological basis for the working memory deficits observed clinically in individuals with schizophrenia.
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Affiliation(s)
- HyunJung Kim
- Department of Clinical & Counseling Psychology, Graduate School of Psychological Service, Chung-Ang University, Seoul, Republic of Korea
| | - Seung-Hyun Shon
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Sung Woo Joo
- Republic of Korea Marine Corps Education and Training Center, Pohang, Republic of Korea
| | - Woon Yoon
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Jang-Han Lee
- Department of Psychology, Chung-Ang University, Seoul, Republic of Korea
| | - Ji-Won Hur
- Department of Psychology, Chung-Ang University, Seoul, Republic of Korea
| | - JungSun Lee
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
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16
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Differential cortical microstructural maturation in the preterm human brain with diffusion kurtosis and tensor imaging. Proc Natl Acad Sci U S A 2019; 116:4681-4688. [PMID: 30782802 PMCID: PMC6410816 DOI: 10.1073/pnas.1812156116] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Delineating cortical microstructure differentiation is important for understanding complicated yet precisely organized patterns in early developing brain. Knowledge of cortical differentiation predominantly from histological studies is limited in localized and discrete cortical regions. We quantified the preterm brain cerebral cortical profile with microstructural complexity [indexed by mean kurtosis (MK)] and microstructural organization [indexed by fractional anisotropy (FA)] from advanced diffusion MRI. Cortical MK and FA maps revealed a heterogeneous maturation signature. Spatiotemporally distinctive disruption of radial glia and decrease of neuronal density among cortical regions were inferred by FA and MK decreases, respectively. These findings suggest that diffusion kurtosis metrics are significant imaging markers for microstructural differentiation of the developmental brain in health and disease. During the third trimester, the human brain undergoes rapid cellular and molecular processes that reshape the structural architecture of the cerebral cortex. Knowledge of cortical differentiation obtained predominantly from histological studies is limited in localized and small cortical regions. How cortical microstructure is differentiated across cortical regions in this critical period is unknown. In this study, the cortical microstructural architecture across the entire cortex was delineated with non-Gaussian diffusion kurtosis imaging as well as conventional diffusion tensor imaging of 89 preterm neonates aged 31–42 postmenstrual weeks. The temporal changes of cortical mean kurtosis (MK) or fractional anisotropy (FA) were heterogeneous across the cortical regions. Cortical MK decreases were observed throughout the studied age period, while cortical FA decrease reached its plateau around 37 weeks. More rapid decreases in MK were found in the primary visual region, while faster FA declines were observed in the prefrontal cortex. We found that distinctive cortical microstructural changes were coupled with microstructural maturation of associated white matter tracts. Both cortical MK and FA measurements predicted the postmenstrual age of preterm infants accurately. This study revealed a differential 4D spatiotemporal cytoarchitectural signature inferred by non-Gaussian diffusion barriers inside the cortical plate during the third trimester. The cytoarchitectural processes, including dendritic arborization and neuronal density decreases, were inferred by regional cortical FA and MK measurements. The presented findings suggest that cortical MK and FA measurements could be used as effective imaging markers for cortical microstructural changes in typical and potentially atypical brain development.
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17
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Counsell SJ, Arichi T, Arulkumaran S, Rutherford MA. Fetal and neonatal neuroimaging. HANDBOOK OF CLINICAL NEUROLOGY 2019; 162:67-103. [PMID: 31324329 DOI: 10.1016/b978-0-444-64029-1.00004-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Magnetic resonance imaging (MRI) can provide detail of the soft tissues of the fetal and neonatal brain that cannot be obtained by any other imaging modality. Conventional T1 and T2 weighted sequences provide anatomic detail of the normally developing brain and can demonstrate lesions, including those associated with preterm birth, hypoxic ischemic encephalopathy, perinatal arterial stroke, infections, and congenital malformations. Specialized imaging techniques can be used to assess cerebral vasculature (magnetic resonance angiography and venography), cerebral metabolism (magnetic resonance spectroscopy), cerebral perfusion (arterial spin labeling), and function (functional MRI). A wealth of quantitative tools, most of which were originally developed for the adult brain, can be applied to study the developing brain in utero and postnatally including measures of tissue microstructure obtained from diffusion MRI, morphometric studies to measure whole brain and regional tissue volumes, and automated approaches to study cortical folding. In this chapter, we aim to describe different imaging approaches for the fetal and neonatal brain, and to discuss their use in a range of clinical applications.
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Affiliation(s)
- Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Sophie Arulkumaran
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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18
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Kroenke CD. Using diffusion anisotropy to study cerebral cortical gray matter development. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 292:106-116. [PMID: 29705039 PMCID: PMC6420781 DOI: 10.1016/j.jmr.2018.04.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2017] [Revised: 03/07/2018] [Accepted: 04/20/2018] [Indexed: 06/03/2023]
Abstract
Diffusion-weighted magnetic resonance imaging (diffusion MRI) is being used to characterize morphological development of cells within developing cerebral cortical gray matter. Abnormal morphology is a shared characteristic of cerebral cortical neurons for many neurodevelopmental disorders, and therefore diffusion MRI is potentially of high value for monitoring growth-related anatomical changes of relevance to brain function. Here, the theoretical framework for analyzing diffusion MRI data is summarized. An overview of quantitative methods for validating the interpretations of diffusion MRI data using light microscopy is then presented. These theoretical modeling and validation methods have been used to precisely characterize changes in water diffusion anisotropy with development in the context of several animal model systems. Further, in diffusion MRI studies of several preclinical models of neurodevelopmental disorders, the ability is demonstrated of diffusion MRI to detect abnormal morphological neural development. These animal model studies are reviewed along with recent initial efforts to translate the findings into an approach for studies of human subjects. This body of data indicates that diffusion MRI has the requisite sensitivity to detect abnormal cellular development in the context of several models of neurodevelopmental disorders, and therefore may provide a new strategy for detecting abnormalities in early stages of brain development in humans.
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Affiliation(s)
- Christopher D Kroenke
- Division of Neuroscience, Oregon National Primate Research Center, Department of Behavioral Neuroscience, and Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, United States.
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19
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Zhao T, Mishra V, Jeon T, Ouyang M, Peng Q, Chalak L, Wisnowski JL, Heyne R, Rollins N, Shu N, Huang H. Structural network maturation of the preterm human brain. Neuroimage 2018; 185:699-710. [PMID: 29913282 DOI: 10.1016/j.neuroimage.2018.06.047] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Revised: 06/13/2018] [Accepted: 06/14/2018] [Indexed: 12/16/2022] Open
Abstract
During the 3rd trimester, large-scale neural circuits are formed in the human brain, resulting in a highly efficient and segregated connectome at birth. Despite recent findings identifying important preterm human brain network properties such as rich-club organization, how the structural network develops differentially across brain regions and among different types of connections in this period is not yet known. Here, using high resolution diffusion MRI of 77 preterm-born and full-term neonates scanned at 31.9-41.7 postmenstrual weeks (PMW), we constructed structural connectivity matrices and performed graph-theory-based analyses. Faster increases of nodal efficiency were mainly located at the brain hubs distributed in primary sensorimotor regions, superior-middle frontal, and precuneus regions during 31.9-41.7PMW. Higher rates of edge strength increases were found in the rich-club and within-module connections, compared to other connections. The edge strength of short-range connections increased faster than that of long-range connections. Nodal efficiencies of the hubs predicted individual postmenstrual ages more accurately than those of non-hubs. Collectively, these findings revealed more rapid efficiency increases of the hub and rich-club connections as well as higher developmental rates of edge strength in short-range and within-module connections. These jointly underlie network segregation and differentiated emergence of brain functions.
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Affiliation(s)
- Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
| | - Virendra Mishra
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, 75390, United States
| | - Tina Jeon
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, United States
| | - Minhui Ouyang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, United States
| | - Qinmu Peng
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, United States
| | - Lina Chalak
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, United States
| | - Jessica Lee Wisnowski
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, United States; Department of Radiology, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, Chile
| | - Roy Heyne
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, United States
| | - Nancy Rollins
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, 19104, United States
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China.
| | - Hao Huang
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, 75390, United States; Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, 19104, United States.
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20
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Batalle D, O'Muircheartaigh J, Makropoulos A, Kelly CJ, Dimitrova R, Hughes EJ, Hajnal JV, Zhang H, Alexander DC, Edwards AD, Counsell SJ. Different patterns of cortical maturation before and after 38 weeks gestational age demonstrated by diffusion MRI in vivo. Neuroimage 2018; 185:764-775. [PMID: 29802969 PMCID: PMC6299264 DOI: 10.1016/j.neuroimage.2018.05.046] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 04/19/2018] [Accepted: 05/18/2018] [Indexed: 12/17/2022] Open
Abstract
Human cortical development during the third trimester is characterised by macro- and microstructural changes which are reflected in alterations in diffusion MRI (dMRI) measures, with significant decreases in cortical mean diffusivity (MD) and fractional anisotropy (FA). This has been interpreted as reflecting increased cellular density and dendritic arborisation. However, the fall in FA stops abruptly at 38 weeks post-menstrual age (PMA), and then tends to plateau, while MD continues to fall, suggesting a more complex picture and raising the hypothesis that after this age development is dominated by continuing increase in neural and organelle density rather than alterations in the geometry of dendritic trees. To test this, we used neurite orientation dispersion and density imaging (NODDI), acquiring multi-shell, high angular resolution dMRI and measures of cortical volume and mean curvature in 99 preterm infants scanned between 25 and 47 weeks PMA. We predicted that increased neurite and organelle density would be reflected in increases in neurite density index (NDI), while a relatively unchanging geometrical structure would be associated with constant orientation dispersion index (ODI). As dendritic arborisation is likely to be one of the drivers of gyrification, we also predicted that measures of cortical volume and curvature would correlate with ODI and show slower growth after 38 weeks. We observed a decrease of MD throughout the period, while cortical FA decreased from 25 to 38 weeks PMA and then increased. ODI increased up to 38 weeks and then plateaued, while NDI rose after 38 weeks. The evolution of ODI correlated with cortical volume and curvature. Regional analysis of cortical microstructure revealed a heterogenous pattern with increases in FA and NDI after 38 weeks confined to primary motor and sensory regions. These results support the interpretation that cortical development between 25 and 38 weeks PMA shows a predominant increase in dendritic arborisation and neurite growth, while between 38 and 47 weeks PMA it is dominated by increasing cellular and organelle density. DTI and NODDI cortical measures between 25 and 47 weeks GA Early cortical changes consistent with dendritic arborisation and neurite growth After 38 weeks cortical changes consistent with increasing cellular density Cortical curvature evolves in parallel with dendritic arborisation
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Affiliation(s)
- Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, SE1 7EH, London, United Kingdom
| | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, SE1 7EH, London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences & Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, United Kingdom
| | | | - Christopher J Kelly
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, SE1 7EH, London, United Kingdom
| | - Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, SE1 7EH, London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences & Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, United Kingdom
| | - Emer J Hughes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, SE1 7EH, London, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, SE1 7EH, London, United Kingdom
| | - Hui Zhang
- Department of Computer Science & Centre for Medical Image Computing, University College London, United Kingdom
| | - Daniel C Alexander
- Department of Computer Science & Centre for Medical Image Computing, University College London, United Kingdom
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, SE1 7EH, London, United Kingdom.
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, SE1 7EH, London, United Kingdom
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21
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Cottaar M, Bastiani M, Chen C, Dikranian K, Van Essen D, Behrens TE, Sotiropoulos SN, Jbabdi S. A gyral coordinate system predictive of fibre orientations. Neuroimage 2018; 176:417-430. [PMID: 29684644 DOI: 10.1016/j.neuroimage.2018.04.040] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Revised: 04/17/2018] [Accepted: 04/18/2018] [Indexed: 12/13/2022] Open
Abstract
When axonal fibres approach or leave the cortex, their trajectories tend to closely follow the cortical convolutions. To quantify this tendency, we propose a three-dimensional coordinate system based on the gyral geometry. For every voxel in the brain, we define a "radial" axis orthogonal to nearby surfaces, a "sulcal" axis along the sulcal depth gradient that preferentially points from deep white matter to the gyral crown, and a "gyral" axis aligned with the long axis of the gyrus. When compared with high-resolution, in-vivo diffusion MRI data from the Human Connectome Project, we find that in superficial white matter the apparent diffusion coefficient (at b = 1000) along the sulcal axis is on average 16% larger than along the gyral axis and twice as large as along the radial axis. This is reflected in the vast majority of observed fibre orientations lying close to the tangential plane (median angular offset < 7°), with the dominant fibre orientation typically aligning with the sulcal axis. In cortical grey matter, fibre orientations transition to a predominantly radial orientation. We quantify the width and location of this transition and find strong reproducibility in test-retest data, but also a clear dependence on the resolution of the diffusion data. The ratio of radial to tangential diffusion is fairly constant throughout most of the cortex, except for a decrease of the diffusivitiy ratio in the sulcal fundi and the primary somatosensory cortex (Brodmann area 3) and an increase in the primary motor cortex (Brodmann area 4). Although only constrained by cortical folds, the proposed gyral coordinate system provides a simple and intuitive representation of white and grey matter fibre orientations near the cortex, and may be useful for future studies of white matter development and organisation.
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Affiliation(s)
- Michiel Cottaar
- Wellcome Centre for Integrative Neuroscience - Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), John Radcliffe Hospital, University of Oxford, UK.
| | - Matteo Bastiani
- Wellcome Centre for Integrative Neuroscience - Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), John Radcliffe Hospital, University of Oxford, UK
| | - Charles Chen
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Krikor Dikranian
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - David Van Essen
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Timothy E Behrens
- Wellcome Centre for Integrative Neuroscience - Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), John Radcliffe Hospital, University of Oxford, UK
| | - Stamatios N Sotiropoulos
- Wellcome Centre for Integrative Neuroscience - Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), John Radcliffe Hospital, University of Oxford, UK; Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroscience - Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), John Radcliffe Hospital, University of Oxford, UK
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22
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Ouyang M, Dubois J, Yu Q, Mukherjee P, Huang H. Delineation of early brain development from fetuses to infants with diffusion MRI and beyond. Neuroimage 2018; 185:836-850. [PMID: 29655938 DOI: 10.1016/j.neuroimage.2018.04.017] [Citation(s) in RCA: 135] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 04/01/2018] [Accepted: 04/08/2018] [Indexed: 02/08/2023] Open
Abstract
Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders.
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Affiliation(s)
- Minhui Ouyang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States
| | - Jessica Dubois
- INSERM, UMR992, CEA, NeuroSpin Center, University Paris Saclay, Gif-sur-Yvette, France
| | - Qinlin Yu
- Radiology Research, Children's Hospital of Philadelphia, PA, United States
| | - Pratik Mukherjee
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA, United States
| | - Hao Huang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States.
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23
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Garcia KE, Robinson EC, Alexopoulos D, Dierker DL, Glasser MF, Coalson TS, Ortinau CM, Rueckert D, Taber LA, Van Essen DC, Rogers CE, Smyser CD, Bayly PV. Dynamic patterns of cortical expansion during folding of the preterm human brain. Proc Natl Acad Sci U S A 2018; 115:3156-3161. [PMID: 29507201 PMCID: PMC5866555 DOI: 10.1073/pnas.1715451115] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
During the third trimester of human brain development, the cerebral cortex undergoes dramatic surface expansion and folding. Physical models suggest that relatively rapid growth of the cortical gray matter helps drive this folding, and structural data suggest that growth may vary in both space (by region on the cortical surface) and time. In this study, we propose a unique method to estimate local growth from sequential cortical reconstructions. Using anatomically constrained multimodal surface matching (aMSM), we obtain accurate, physically guided point correspondence between younger and older cortical reconstructions of the same individual. From each pair of surfaces, we calculate continuous, smooth maps of cortical expansion with unprecedented precision. By considering 30 preterm infants scanned two to four times during the period of rapid cortical expansion (28-38 wk postmenstrual age), we observe significant regional differences in growth across the cortical surface that are consistent with the emergence of new folds. Furthermore, these growth patterns shift over the course of development, with noninjured subjects following a highly consistent trajectory. This information provides a detailed picture of dynamic changes in cortical growth, connecting what is known about patterns of development at the microscopic (cellular) and macroscopic (folding) scales. Since our method provides specific growth maps for individual brains, we are also able to detect alterations due to injury. This fully automated surface analysis, based on tools freely available to the brain-mapping community, may also serve as a useful approach for future studies of abnormal growth due to genetic disorders, injury, or other environmental variables.
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Affiliation(s)
- Kara E Garcia
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130;
| | - Emma C Robinson
- Department of Computer Science, Imperial College London, London SW7 2AZ, United Kingdom
- Department of Biomedical Engineering, Division of Imaging Sciences, St. Thomas' Hospital, King's College London, London SE1 7EH, United Kingdom
- Department of Perinatal Imaging and Health, Division of Imaging Sciences, St. Thomas' Hospital, King's College London, London SE1 7EH, United Kingdom
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Donna L Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Matthew F Glasser
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
- Internal Medicine, St. Luke's Hospital, St. Louis, MO 63017
| | - Timothy S Coalson
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
| | - Daniel Rueckert
- Department of Computer Science, Imperial College London, London SW7 2AZ, United Kingdom
| | - Larry A Taber
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO 63130
| | - David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
| | - Cynthia E Rogers
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Christopher D Smyser
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
| | - Philip V Bayly
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO 63130
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24
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Bouyssi-Kobar M, Brossard-Racine M, Jacobs M, Murnick J, Chang T, Limperopoulos C. Regional microstructural organization of the cerebral cortex is affected by preterm birth. Neuroimage Clin 2018; 18:871-880. [PMID: 29876271 PMCID: PMC5988027 DOI: 10.1016/j.nicl.2018.03.020] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Revised: 03/09/2018] [Accepted: 03/15/2018] [Indexed: 10/31/2022]
Abstract
Objectives To compare regional cerebral cortical microstructural organization between preterm infants at term-equivalent age (TEA) and healthy full-term newborns, and to examine the impact of clinical risk factors on cerebral cortical micro-organization in the preterm cohort. Study design We prospectively enrolled very preterm infants (gestational age (GA) at birth<32 weeks; birthweight<1500 g) and healthy full-term controls. Using non-invasive 3T diffusion tensor imaging (DTI) metrics, we quantified regional micro-organization in ten cerebral cortical areas: medial/dorsolateral prefrontal cortex, anterior/posterior cingulate cortex, insula, posterior parietal cortex, motor/somatosensory/auditory/visual cortex. ANCOVA analyses were performed controlling for sex and postmenstrual age at MRI. Results We studied 91 preterm infants at TEA and 69 full-term controls. Preterm infants demonstrated significantly higher diffusivity in the prefrontal, parietal, motor, somatosensory, and visual cortices suggesting delayed maturation of these cortical areas. Additionally, postnatal hydrocortisone treatment was related to accelerated microstructural organization in the prefrontal and somatosensory cortices. Conclusions Preterm birth alters regional microstructural organization of the cerebral cortex in both neurocognitive brain regions and areas with primary sensory/motor functions. We also report for the first time a potential protective effect of postnatal hydrocortisone administration on cerebral cortical development in preterm infants.
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Affiliation(s)
- Marine Bouyssi-Kobar
- The Developing Brain Research Laboratory, Department of Diagnostic Imaging and Radiology, Children's National Health System, Washington, DC 20010, USA; Institute for Biomedical Sciences, George Washington University, Washington, DC 20037, USA.
| | - Marie Brossard-Racine
- Department of Pediatrics Neurology, McGill University Health Center, Montreal, QC H4A3J1, Canada.
| | - Marni Jacobs
- Division of Biostatistics and Study Methodology, Children's Research Institute, Children's National Health System, Washington, DC 20010, USA.
| | - Jonathan Murnick
- The Developing Brain Research Laboratory, Department of Diagnostic Imaging and Radiology, Children's National Health System, Washington, DC 20010, USA.
| | - Taeun Chang
- Department of Neurology, Children's National Health System, Washington, DC 20010, USA.
| | - Catherine Limperopoulos
- The Developing Brain Research Laboratory, Department of Diagnostic Imaging and Radiology, Children's National Health System, Washington, DC 20010, USA.
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25
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Yu Q, Ouyang A, Chalak L, Jeon T, Chia J, Mishra V, Sivarajan M, Jackson G, Rollins N, Liu S, Huang H. Structural Development of Human Fetal and Preterm Brain Cortical Plate Based on Population-Averaged Templates. Cereb Cortex 2018; 26:4381-4391. [PMID: 26405055 DOI: 10.1093/cercor/bhv201] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
We hypothesized that the distinct maturational processes take place across different cortical areas from middle fetal stage to normal time of birth and these maturational processes are altered in late third trimester. Fractional anisotropies (FA) from diffusion tensor imaging (DTI) infer the microstructures of the early developing cortical plate. High-resolution DTI of 11 fetal brain specimens at postmenstrual age of 20 weeks (or simplified as 20 weeks), 19 in vivo brains at 35 weeks, and 17 in vivo brains at normal time of birth at term (40 weeks) were acquired. Population-averaged age-specific DTI templates were established with large deformation diffeomorphic metric mapping for subject groups at 20, 35, and 40 weeks. To alleviate partial volume effects, skeletonized FA values were used for mapping averaged cortical FA to the cortical surface and measuring FA at 12 functionally distinctive cortical regions. Significant and heterogeneous FA decreases take place in distinct cortical areas from 20 to 35 weeks and from 35 to 40 weeks, suggesting differentiated cortical development patterns. Temporally nonuniform FA decrease patterns during 35-40 weeks compared with those during 20-35 weeks were observed in higher-order association cortex. Measured skeletonized FA suggested dissociated changes between cerebral cortex and white matter during 35-40 weeks.
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Affiliation(s)
- Qiaowen Yu
- Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorders, Shandong University School of Medicine, Jinan, Shandong 250012, China
- Advanced Imaging Research Center
| | | | | | | | | | | | | | | | - Nancy Rollins
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Radiology, Children's Medical Center at Dallas
| | - Shuwei Liu
- Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorders, Shandong University School of Medicine, Jinan, Shandong 250012, China
| | - Hao Huang
- Advanced Imaging Research Center
- Department of Radiology, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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26
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Eaton-Rosen Z, Scherrer B, Melbourne A, Ourselin S, Neil JJ, Warfield SK. Investigating the maturation of microstructure and radial orientation in the preterm human cortex with diffusion MRI. Neuroimage 2017; 162:65-72. [PMID: 28801253 DOI: 10.1016/j.neuroimage.2017.08.013] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Revised: 07/24/2017] [Accepted: 08/03/2017] [Indexed: 11/28/2022] Open
Abstract
Preterm birth disrupts and alters the complex developmental processes in the cerebral cortex. This disruption may be a contributing factor to widespread delay and cognitive difficulties in the preterm population. Diffusion-weighted magnetic resonance imaging (DW MRI) is a noninvasive imaging technique that makes inferences about cellular structures, at scales smaller than the imaging resolution. One established finding is that DW MRI shows a transient radial alignment in the preterm cortex. In this study, we quantify this maturational process with the "radiality index", a parameter that measures directional coherence, which we expect to change rapidly in the perinatal period. To measure this index, we used structural T2-weighted MRI to segment the cortex and generate cortical meshes. We obtained normal vectors for each face of the mesh and compared them to the principal diffusion direction, calculated by both the DTI and DIAMOND models, to generate the radiality index. The subjects included in this study were 89 infants born at fewer than 34 weeks completed gestation, each imaged at up to four timepoints between 27 and 42 weeks gestational age. In this manuscript, we quantify the longitudinal trajectory of radiality, fractional anisotropy and mean diffusivity from the DTI and DIAMOND models. For the radiality index and fractional anisotropy, the DIAMOND model offers improved sensitivity over the DTI model. The radiality index has a consistent progression across time, with the rate of change depending on the cortical lobe. The occipital lobe changes most rapidly, and the frontal and temporal least: this is commensurate with known developmental anatomy. Analysing the radiality index offers information complementary to other diffusion parameters.
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Affiliation(s)
| | - Benoit Scherrer
- Department of Radiology, Boston Childrens Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA, USA
| | | | | | - Jeffrey J Neil
- Department of Neurology, Boston Children's Hospital, 333 Longwood Ave, LO450, 02115, Boston, MA, USA
| | - Simon K Warfield
- Department of Radiology, Boston Childrens Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA, USA
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27
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Ouyang M, Kang H, Detre JA, Roberts TPL, Huang H. Short-range connections in the developmental connectome during typical and atypical brain maturation. Neurosci Biobehav Rev 2017; 83:109-122. [PMID: 29024679 DOI: 10.1016/j.neubiorev.2017.10.007] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2017] [Revised: 09/09/2017] [Accepted: 10/06/2017] [Indexed: 01/10/2023]
Abstract
The human brain is remarkably complex with connectivity constituting its basic organizing principle. Although long-range connectivity has been focused on in most research, short-range connectivity is characterized by unique and spatiotemporally heterogeneous dynamics from infancy to adulthood. Alterations in the maturational dynamics of short-range connectivity has been associated with neuropsychiatric disorders, such as autism and schizophrenia. Recent advances in neuroimaging techniques, especially diffusion magnetic resonance imaging (dMRI), resting-state functional MRI (rs-fMRI), electroencephalography (EEG) and magnetoencephalography (MEG), have made quantification of short-range connectivity possible in pediatric populations. This review summarizes findings on the development of short-range functional and structural connections at the macroscale. These findings suggest an inverted U-shaped pattern of maturation from primary to higher-order brain regions, and possible "hyper-" and "hypo-" short-range connections in autism and schizophrenia, respectively. The precisely balanced short- and long-range connections contribute to the integration and segregation of the connectome during development. The mechanistic relationship among short-range connectivity maturation, the developmental connectome and emerging brain functions needs further investigation, including the refinement of methodological approaches.
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Affiliation(s)
- Minhui Ouyang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States
| | - Huiying Kang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - John A Detre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Timothy P L Roberts
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Hao Huang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States.
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28
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Uematsu A, Hata J, Komaki Y, Seki F, Yamada C, Okahara N, Kurotaki Y, Sasaki E, Okano H. Mapping orbitofrontal-limbic maturation in non-human primates: A longitudinal magnetic resonance imaging study. Neuroimage 2017; 163:55-67. [PMID: 28923274 DOI: 10.1016/j.neuroimage.2017.09.028] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 09/08/2017] [Accepted: 09/14/2017] [Indexed: 12/22/2022] Open
Abstract
Brain development involves spatiotemporally complex microstructural changes. A number of neuropsychiatric disorders are linked to the neural processes of development and aging. Thus, it is important to understanding the typical developmental patterns of various brain structures, which will help to define critical periods of vulnerability for neural maturation, as well as anatomical mechanisms of brain structure-related neuropathology. In this study, we used magnetic resonance imaging to assess development of the orbitofrontal cortex, cingulate cortex, amygdala, and hippocampus in a non-human primate species, the common marmoset (Callithrix jacchus). We collected a total of 114 T2-weighted and 91 diffusion-weighted scans from 23 animals from infancy to early adulthood. Quantitative and qualitative evaluation of age-related brain growth patterns showed non-linear structural developmental changes in all measured brain regions, consistent with reported human data. Overall, robust volumetric growth was observed from 1 to 3 months of age (from infancy to the early juvenile period). This rapid brain growth was associated with the largest decrease in mean, axial, and radial diffusivities of diffusion tensor imaging in all brain regions, suggesting an increase in the number and size of cells, dendrites, and spines during this period. After this developmental period, the volume of various brain regions steadily increased until adolescence (7-13 months of age, depending on the region). Further, structural connectivity derived from tractography data in various brain regions continuously changed from infancy to adolescence, suggesting that the increase in brain volume was related to continued axonal myelination during adolescence. Thereafter, the volume of the cortical regions decreased considerably, while there was no change in subcortical regions. Familial factors, rather than sex, contributed the development of the front-limbic brain regions. Overall, this study provides further data on the factors and timing important for normal brain development, and suggest that the common marmoset is a useful animal model for human neural development.
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Affiliation(s)
- Akiko Uematsu
- Department of Physiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan; RIKEN BSI Laboratory for Marmoset Neural Architecture, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan; Central Institute for Experimental Animals, 3-25-12 Tonomachi, Kawasaki-ku, Kawasaki, 210-0821, Japan
| | - Junichi Hata
- Department of Physiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan; RIKEN BSI Laboratory for Marmoset Neural Architecture, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan; Central Institute for Experimental Animals, 3-25-12 Tonomachi, Kawasaki-ku, Kawasaki, 210-0821, Japan
| | - Yuji Komaki
- Department of Physiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan; RIKEN BSI Laboratory for Marmoset Neural Architecture, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan
| | - Fumiko Seki
- Department of Physiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan; RIKEN BSI Laboratory for Marmoset Neural Architecture, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan; Central Institute for Experimental Animals, 3-25-12 Tonomachi, Kawasaki-ku, Kawasaki, 210-0821, Japan
| | - Chihoko Yamada
- Central Institute for Experimental Animals, 3-25-12 Tonomachi, Kawasaki-ku, Kawasaki, 210-0821, Japan
| | - Norio Okahara
- Central Institute for Experimental Animals, 3-25-12 Tonomachi, Kawasaki-ku, Kawasaki, 210-0821, Japan
| | - Yoko Kurotaki
- Central Institute for Experimental Animals, 3-25-12 Tonomachi, Kawasaki-ku, Kawasaki, 210-0821, Japan
| | - Erika Sasaki
- Department of Physiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan; RIKEN BSI Laboratory for Marmoset Neural Architecture, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan; Central Institute for Experimental Animals, 3-25-12 Tonomachi, Kawasaki-ku, Kawasaki, 210-0821, Japan
| | - Hideyuki Okano
- Department of Physiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan; RIKEN BSI Laboratory for Marmoset Neural Architecture, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan.
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Friedrichs-Maeder CL, Griffa A, Schneider J, Hüppi PS, Truttmann A, Hagmann P. Exploring the role of white matter connectivity in cortex maturation. PLoS One 2017; 12:e0177466. [PMID: 28545040 PMCID: PMC5435226 DOI: 10.1371/journal.pone.0177466] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 04/27/2017] [Indexed: 12/18/2022] Open
Abstract
The maturation of the cortical gray matter (GM) and white matter (WM) are described as sequential processes following multiple, but distinct rules. However, neither the mechanisms driving brain maturation processes, nor the relationship between GM and WM maturation are well understood. Here we use connectomics and two MRI measures reflecting maturation related changes in cerebral microstructure, namely the Apparent Diffusion Coefficient (ADC) and the T1 relaxation time (T1), to study brain development. We report that the advancement of GM and WM maturation are inter-related and depend on the underlying brain connectivity architecture. Particularly, GM regions and their incident WM connections show corresponding maturation levels, which is also observed for GM regions connected through a WM tract. Based on these observations, we propose a simple computational model supporting a key role for the connectome in propagating maturation signals sequentially from external stimuli, through primary sensory structures to higher order functional cortices.
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Affiliation(s)
| | - Alessandra Griffa
- Department of Radiology, Centre Hospitalier Universitaire Vaudoise (CHUV), Lausanne, Switzerland
- Signal Processing Laboratory (LTSS), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Juliane Schneider
- Clinic of Neonatology and Follow-up, Department of Pediatrics, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, Canada
| | - Petra Susan Hüppi
- Division of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland
| | - Anita Truttmann
- Clinic of Neonatology and Follow-up, Department of Pediatrics, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudoise (CHUV), Lausanne, Switzerland
- Signal Processing Laboratory (LTSS), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Folding, But Not Surface Area Expansion, Is Associated with Cellular Morphological Maturation in the Fetal Cerebral Cortex. J Neurosci 2017; 37:1971-1983. [PMID: 28069920 DOI: 10.1523/jneurosci.3157-16.2017] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Revised: 12/22/2016] [Accepted: 01/04/2017] [Indexed: 01/26/2023] Open
Abstract
Altered macroscopic anatomical characteristics of the cerebral cortex have been identified in individuals affected by various neurodevelopmental disorders. However, the cellular developmental mechanisms that give rise to these abnormalities are not understood. Previously, advances in image reconstruction of diffusion magnetic resonance imaging (MRI) have made possible high-resolution in utero measurements of water diffusion anisotropy in the fetal brain. Here, diffusion anisotropy within the developing fetal cerebral cortex is longitudinally characterized in the rhesus macaque, focusing on gestation day (G85) through G135 of the 165 d term. Additionally, for subsets of animals characterized at G90 and G135, immunohistochemical staining was performed, and 3D structure tensor analyses were used to identify the cellular processes that most closely parallel changes in water diffusion anisotropy with cerebral cortical maturation. Strong correlations were found between maturation of dendritic arbors on the cellular level and the loss of diffusion anisotropy with cortical development. In turn, diffusion anisotropy changes were strongly associated both regionally and temporally with cortical folding. Notably, the regional and temporal dependence of diffusion anisotropy and folding were distinct from the patterns observed for cerebral cortical surface area expansion. These findings strengthen the link proposed in previous studies between cellular-level changes in dendrite morphology and noninvasive diffusion MRI measurements of the developing cerebral cortex and support the possibility that, in gyroencephalic species, structural differentiation within the cortex is coupled to the formation of gyri and sulci.SIGNIFICANCE STATEMENT Abnormal brain morphology has been found in populations with neurodevelopmental disorders. However, the mechanisms linking cellular level and macroscopic maturation are poorly understood, even in normal brains. This study contributes new understanding to this subject using serial in utero MRI measurements of rhesus macaque fetuses, from which macroscopic and cellular information can be derived. We found that morphological differentiation of dendrites was strongly associated both regionally and temporally with folding of the cerebral cortex. Interestingly, parallel associations were not observed with cortical surface area expansion. These findings support the possibility that perturbed morphological differentiation of cells within the cortex may underlie abnormal macroscopic characteristics of individuals affected by neurodevelopmental disorders.
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31
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Ouyang M, Liu P, Jeon T, Chalak L, Heyne R, Rollins NK, Licht DJ, Detre JA, Roberts TPL, Lu H, Huang H. Heterogeneous increases of regional cerebral blood flow during preterm brain development: Preliminary assessment with pseudo-continuous arterial spin labeled perfusion MRI. Neuroimage 2016; 147:233-242. [PMID: 27988320 DOI: 10.1016/j.neuroimage.2016.12.034] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Revised: 12/10/2016] [Accepted: 12/13/2016] [Indexed: 01/11/2023] Open
Abstract
The human brain develops rapidly during 32-45 postmenstrual weeks (PMW), a critical stage characterized by dramatic increases of metabolic demand. The increasing metabolic demand can be inferred through measurements of regional cerebral blood flow (CBF), which might be coupled to regional metabolism in preterm brains. Arterial spin labeled (ASL) perfusion MRI is one of the few viable approaches for imaging regional CBF of preterm brains, but must be optimized for the extremely slow blood velocity unique in preterm brains. In this study, we explored the spatiotemporal CBF distribution in newborns scanned at the age of 32-45PMW using a pseudo-continuous ASL (pCASL) protocol adapted to slow blood flow in neonates. A total of 89 neonates were recruited. PCASL MRI was acquired from 34 normal newborns and phase contrast (PC) images from 19 newborns. Diffusion tensor images (DTI) were acquired from all 89 neonates for measuring cortical fractional anisotropy (FA), which characterizes cortical microstructure. Reproducible CBF measurements were obtained with the adjusted pCASL sequence. Global CBF measurement based on PC MRI was found to double its value in the 3rd trimester. Regional CBF increases were heterogeneous across the brain with a significantly higher rate of CBF increase in the frontal lobe and a lower rate of CBF increase in the occipital lobe. A significant correlation was found between frontal cortical CBF and cortical FA measurements (p<0.01). Increasing CBF values observed in the frontal lobe corresponded to lower FA values, suggesting that dendritic arborization and synaptic formation might be associated with an elevated local CBF. These results offer a preliminary account of heterogeneous regional CBF increases in a vital early developmental period and may shed the light on underlying metabolic support for cortical microstructural changes during the developmental period of 32-45PMW. Preterm effects and limitations of pCASL techniques in newborns need to be carefully considered for interpretation these results.
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Affiliation(s)
- Minhui Ouyang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, TX, United States; Biomedical Engineering Joint Graduate Program, University of Texas at Arlington-University of Texas Southwestern Medical Center, TX, United States
| | - Peiying Liu
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, TX, United States; Department of Radiology, School of Medicine, Johns Hopkins University, MD, United States
| | - Tina Jeon
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, TX, United States; Biomedical Engineering Joint Graduate Program, University of Texas at Arlington-University of Texas Southwestern Medical Center, TX, United States
| | - Lina Chalak
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Roy Heyne
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Nancy K Rollins
- Departemnt of Radiology, Children's Medical Center, Dallas, TX, United States
| | - Daniel J Licht
- Division of Neurology, Children's Hospital of Philadelphia, PA, United States
| | - John A Detre
- Department of Neurology, University of Pennsylvania, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Timothy P L Roberts
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Hanzhang Lu
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, TX, United States; Department of Radiology, School of Medicine, Johns Hopkins University, MD, United States
| | - Hao Huang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, TX, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States.
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32
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Verriotis M, Chang P, Fitzgerald M, Fabrizi L. The development of the nociceptive brain. Neuroscience 2016; 338:207-219. [DOI: 10.1016/j.neuroscience.2016.07.026] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2016] [Revised: 06/28/2016] [Accepted: 07/16/2016] [Indexed: 12/20/2022]
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Bekiesińska-Figatowska M, Helwich E, Rutkowska M, Stankiewicz J, Terczyńska I. Magnetic resonance imaging of neonates in the magnetic resonance compatible incubator. Arch Med Sci 2016; 12:1064-1070. [PMID: 27695498 PMCID: PMC5016588 DOI: 10.5114/aoms.2016.61913] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2014] [Accepted: 06/14/2014] [Indexed: 11/17/2022] Open
Abstract
INTRODUCTION The authors present the first experience in neonatal magnetic resonance imaging (MRI) examinations using an MR compatible incubator (INC) at the Institute of Mother and Child. MATERIAL AND METHODS Forty-nine examinations of 47 newborns (20 girls, 27 boys) were performed using the GE Signa HDxt 1.5T system and INC Nomag IC 1.5. Demographic data, anesthetic methods and MRI findings in the INC in comparison with previously performed imaging were analyzed. RESULTS Thirty-two neonates were prematurely born (68.1%) at gestational age 23-37 weeks, mean: 29.9 weeks. They were examined at 26 weeks postmenstrual age to 1 month corrected age, mean: 37.5 weeks. Body weight of newborns on the study day was 600-4300 g, mean: 2724 g. Seventeen (34.7%) children were examined in physiological sleep, 32 (65.3%) anesthetized. In none of them did anesthesiological complications or disease worsening occur. In 43 (91.5%) children brain MRI was performed, in 4 (8.5%) MRI of the spinal cord and canal and of the abdomen/pelvis. In children prenatally examined by MRI, the INC provided new diagnostic information in 5 (83.3%) cases, in neonates studied after birth by ultrasound in 32 (82%). Magnetic resonance imaging in the INC did not entail additional knowledge in 9 (18.7%) cases. CONCLUSIONS The INC enables MRI in preterm newborns and those with low/extremely low body weight. These studies are necessary to assess the extent of changes in the central nervous system and other organs. Incubator coils, designed specifically for neonates, allow more accurate diagnosis than previously used coils for adults. MRI results allow one to determine prognosis, for more accurate planning of diagnostics, helping to make appropriate therapeutic decisions.
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Affiliation(s)
| | - Ewa Helwich
- Clinic of Neonatology and Neonatal Intensive Care, Institute of Mother and Child, Warsaw, Poland
| | - Magdalena Rutkowska
- Clinic of Neonatology and Neonatal Intensive Care, Institute of Mother and Child, Warsaw, Poland
| | - Joanna Stankiewicz
- Intensive Care and Anesthesiology Clinic, Institute of Mother and Child, Warsaw, Poland
| | - Iwona Terczyńska
- Clinic of Neurology of Children and Adolescents, Institute of Mother and Child, Warsaw, Poland
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Levman J, Takahashi E. Multivariate Analyses Applied to Healthy Neurodevelopment in Fetal, Neonatal, and Pediatric MRI. Front Neuroanat 2016; 9:163. [PMID: 26834576 PMCID: PMC4720794 DOI: 10.3389/fnana.2015.00163] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Accepted: 12/04/2015] [Indexed: 11/13/2022] Open
Abstract
Multivariate analysis (MVA) is a class of statistical and pattern recognition techniques that involve the processing of data that contains multiple measurements per sample. MVA can be used to address a wide variety of neurological medical imaging related challenges including the evaluation of healthy brain development, the automated analysis of brain tissues and structures through image segmentation, evaluating the effects of genetic and environmental factors on brain development, evaluating sensory stimulation's relationship with functional brain activity and much more. Compared to adult imaging, pediatric, neonatal and fetal imaging have attracted less attention from MVA researchers, however, recent years have seen remarkable MVA research growth in pre-adult populations. This paper presents the results of a systematic review of the literature focusing on MVA applied to healthy subjects in fetal, neonatal and pediatric magnetic resonance imaging (MRI) of the brain. While the results of this review demonstrate considerable interest from the scientific community in applications of MVA technologies in brain MRI, the field is still young and significant research growth will continue into the future.
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Affiliation(s)
- Jacob Levman
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical SchoolBoston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestown, MA, USA
| | - Emi Takahashi
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical SchoolBoston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestown, MA, USA
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35
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Lockwood Estrin G, Kyriakopoulou V, Makropoulos A, Ball G, Kuhendran L, Chew A, Hagberg B, Martinez-Biarge M, Allsop J, Fox M, Counsell SJ, Rutherford MA. Altered white matter and cortical structure in neonates with antenatally diagnosed isolated ventriculomegaly. NEUROIMAGE-CLINICAL 2016; 11:139-148. [PMID: 26937382 PMCID: PMC4753810 DOI: 10.1016/j.nicl.2016.01.012] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2015] [Revised: 01/05/2016] [Accepted: 01/12/2016] [Indexed: 12/31/2022]
Abstract
Ventriculomegaly (VM) is the most common central nervous system abnormality diagnosed antenatally, and is associated with developmental delay in childhood. We tested the hypothesis that antenatally diagnosed isolated VM represents a biological marker for altered white matter (WM) and cortical grey matter (GM) development in neonates. 25 controls and 21 neonates with antenatally diagnosed isolated VM had magnetic resonance imaging at 41.97(± 2.94) and 45.34(± 2.14) weeks respectively. T2-weighted scans were segmented for volumetric analyses of the lateral ventricles, WM and cortical GM. Diffusion tensor imaging (DTI) measures were assessed using voxel-wise methods in WM and cortical GM; comparisons were made between cohorts. Ventricular and cortical GM volumes were increased, and WM relative volume was reduced in the VM group. Regional decreases in fractional anisotropy (FA) and increases in mean diffusivity (MD) were demonstrated in WM of the VM group compared to controls. No differences in cortical DTI metrics were observed. At 2 years, neurodevelopmental delays, especially in language, were observed in 6/12 cases in the VM cohort. WM alterations in isolated VM cases may be consistent with abnormal development of WM tracts involved in language and cognition. Alterations in WM FA and MD may represent neural correlates for later neurodevelopmental deficits. This study compared brain development in neonates with isolated VM to controls. Neonates with isolated VM have enlarged cortical volumes compared to controls. FA was reduced and MD was increased in the WM of the VM cohort. Children with antenatal isolated VM are at increased risk for language delay.
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Affiliation(s)
- G Lockwood Estrin
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, United Kingdom; Robert Steiner Unit, Imaging Sciences Department, MRC Clinical Sciences Centre, Hammersmith Hospital, Imperial College London, London W12 0HS, United Kingdom
| | - V Kyriakopoulou
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, United Kingdom
| | - A Makropoulos
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, United Kingdom
| | - G Ball
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, United Kingdom
| | - L Kuhendran
- Robert Steiner Unit, Imaging Sciences Department, MRC Clinical Sciences Centre, Hammersmith Hospital, Imperial College London, London W12 0HS, United Kingdom
| | - A Chew
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, United Kingdom; Robert Steiner Unit, Imaging Sciences Department, MRC Clinical Sciences Centre, Hammersmith Hospital, Imperial College London, London W12 0HS, United Kingdom
| | - B Hagberg
- Robert Steiner Unit, Imaging Sciences Department, MRC Clinical Sciences Centre, Hammersmith Hospital, Imperial College London, London W12 0HS, United Kingdom; Gillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Kungsgatan 12, 411 18 Gothenburg, Sweden
| | - M Martinez-Biarge
- Robert Steiner Unit, Imaging Sciences Department, MRC Clinical Sciences Centre, Hammersmith Hospital, Imperial College London, London W12 0HS, United Kingdom
| | - J Allsop
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, United Kingdom
| | - M Fox
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, United Kingdom
| | - S J Counsell
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, United Kingdom
| | - M A Rutherford
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, United Kingdom
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Schneider J, Kober T, Bickle Graz M, Meuli R, Hüppi PS, Hagmann P, Truttmann AC. Evolution of T1 Relaxation, ADC, and Fractional Anisotropy during Early Brain Maturation: A Serial Imaging Study on Preterm Infants. AJNR Am J Neuroradiol 2015; 37:155-62. [PMID: 26494693 DOI: 10.3174/ajnr.a4510] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Accepted: 06/11/2015] [Indexed: 12/16/2022]
Abstract
BACKGROUND AND PURPOSE The alteration of brain maturation in preterm infants contributes to neurodevelopmental disabilities during childhood. Serial imaging allows understanding of the mechanisms leading to dysmaturation in the preterm brain. The purpose of the present study was to provide reference quantitative MR imaging measures across time in preterm infants, by using ADC, fractional anisotropy, and T1 maps obtained by using the magnetization-prepared dual rapid acquisition of gradient echo technique. MATERIALS AND METHODS We included preterm neonates born at <30 weeks of gestational age without major brain lesions on early cranial sonography and performed 3 MRIs (3T) from birth to term-equivalent age. Multiple measurements (ADC, fractional anisotropy, and T1 relaxation) were performed on each examination in 12 defined white and gray matter ROIs. RESULTS We acquired 107 MRIs (35 early, 33 intermediary, and 39 at term-equivalent age) in 39 cerebral low-risk preterm infants. Measures of T1 relaxation time showed a gradual and significant decrease with time in a region- and hemispheric-specific manner. ADC values showed a similar decline with time, but with more variability than T1 relaxation. An increase of fractional anisotropy values was observed in WM regions and inversely a decrease in the cortex. CONCLUSIONS The gradual change with time reflects the progressive maturation of the cerebral microstructure in white and gray matter. Our study provides reference trajectories from 25 to 40 weeks of gestation of T1 relaxation, ADC, and fractional anisotropy values in low-risk preterm infants. We speculate that deviation thereof might reflect disturbed cerebral maturation; the correlation of this disturbed maturation with neurodevelopmental outcome remains to be addressed.
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Affiliation(s)
- J Schneider
- From the Clinic of Neonatology and Follow-up (J.S., M.B.G., A.C.T.), Department of Pediatrics
| | - T Kober
- Department of Radiology (T.K., R.M., P.H.), University Hospital Center and University of Lausanne, Lausanne, Switzerland Advanced Clinical Imaging Technology (T.K.), Siemens Healthcare IM BM PI, Lausanne, Switzerland LTS5 (T.K.), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - M Bickle Graz
- From the Clinic of Neonatology and Follow-up (J.S., M.B.G., A.C.T.), Department of Pediatrics
| | - R Meuli
- Department of Radiology (T.K., R.M., P.H.), University Hospital Center and University of Lausanne, Lausanne, Switzerland
| | - P S Hüppi
- Division of Development and Growth (P.S.H.), Department of Pediatrics, University Hospital of Geneva, Geneva, Switzerland
| | - P Hagmann
- Department of Radiology (T.K., R.M., P.H.), University Hospital Center and University of Lausanne, Lausanne, Switzerland
| | - A C Truttmann
- From the Clinic of Neonatology and Follow-up (J.S., M.B.G., A.C.T.), Department of Pediatrics
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van den Heuvel MP, Kersbergen KJ, de Reus MA, Keunen K, Kahn RS, Groenendaal F, de Vries LS, Benders MJNL. The Neonatal Connectome During Preterm Brain Development. Cereb Cortex 2015; 25:3000-13. [PMID: 24833018 PMCID: PMC4537441 DOI: 10.1093/cercor/bhu095] [Citation(s) in RCA: 228] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The human connectome is the result of an elaborate developmental trajectory. Acquiring diffusion-weighted imaging and resting-state fMRI, we studied connectome formation during the preterm phase of macroscopic connectome genesis. In total, 27 neonates were scanned at week 30 and/or week 40 gestational age (GA). Examining the architecture of the neonatal anatomical brain network revealed a clear presence of a small-world modular organization before term birth. Analysis of neonatal functional connectivity (FC) showed the early formation of resting-state networks, suggesting that functional networks are present in the preterm brain, albeit being in an immature state. Moreover, structural and FC patterns of the neonatal brain network showed strong overlap with connectome architecture of the adult brain (85 and 81%, respectively). Analysis of brain development between week 30 and week 40 GA revealed clear developmental effects in neonatal connectome architecture, including a significant increase in white matter microstructure (P < 0.01), small-world topology (P < 0.01) and interhemispheric FC (P < 0.01). Computational analysis further showed that developmental changes involved an increase in integration capacity of the connectivity network as a whole. Taken together, we conclude that hallmark organizational structures of the human connectome are present before term birth and subject to early development.
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Affiliation(s)
- Martijn P van den Heuvel
- Department of Psychiatry, Wilhelmina Children's Hospital, University Medical Center Utrecht, The Netherlands Brain Center Rudolf Magnus, The Netherlands
| | - Karina J Kersbergen
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, The Netherlands
| | - Marcel A de Reus
- Department of Psychiatry, Wilhelmina Children's Hospital, University Medical Center Utrecht, The Netherlands Brain Center Rudolf Magnus, The Netherlands
| | - Kristin Keunen
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, The Netherlands Brain Center Rudolf Magnus, The Netherlands
| | - René S Kahn
- Department of Psychiatry, Wilhelmina Children's Hospital, University Medical Center Utrecht, The Netherlands Brain Center Rudolf Magnus, The Netherlands
| | - Floris Groenendaal
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, The Netherlands Brain Center Rudolf Magnus, The Netherlands
| | - Linda S de Vries
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, The Netherlands Brain Center Rudolf Magnus, The Netherlands
| | - Manon J N L Benders
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, The Netherlands Brain Center Rudolf Magnus, The Netherlands
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Smyser TA, Smyser CD, Rogers CE, Gillespie SK, Inder TE, Neil JJ. Cortical Gray and Adjacent White Matter Demonstrate Synchronous Maturation in Very Preterm Infants. Cereb Cortex 2015. [PMID: 26209848 DOI: 10.1093/cercor/bhv164] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Spatial and functional gradients of development have been described for the maturation of cerebral gray and white matter using histological and radiological approaches. We evaluated these patterns in very preterm (VPT) infants using diffusion tensor imaging. Data were obtained from 3 groups: 1) 22 VPT infants without white matter injury (WMI), of whom all had serial MRI studies during the neonatal period, 2) 19 VPT infants with WMI, of whom 3 had serial MRI studies and 3) 12 healthy, term-born infants. Regions of interest were placed in the cortical gray and adjacent white matter in primary motor, primary visual, visual association, and prefrontal regions. From the MRI data at term-equivalent postmenstrual age, differences in mean diffusivity were found in all areas between VPT infants with WMI and the other 2 groups. In contrast, minimal differences in fractional anisotropy were found between the 3 groups. These findings suggest that cortical maturation is delayed in VPT infants with WMI when compared with term control infants and VPT infants without WMI. From the serial MRI data from VPT infants, synchronous development between gray and white matter was evident in all areas and all groups, with maturation in primary motor and sensory regions preceding that of association areas. This finding highlights the regionally varying but locally synchronous nature of the development of cortical gray matter and its adjacent white matter.
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Affiliation(s)
| | - Christopher D Smyser
- Department of Neurology
- Department of Pediatrics
- Department of Radiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | | | - Sarah K Gillespie
- Department of Radiology, Washington University School of Medicine, St Louis, MO 63110, USA
- University College, Washington University, St Louis, MO 63110, USA
| | - Terrie E Inder
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Jeffrey J Neil
- Department of Neurology, Boston Children's Hospital, Boston, MA 02115, USA
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39
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Moeskops P, Benders MJNL, Kersbergen KJ, Groenendaal F, de Vries LS, Viergever MA, Išgum I. Development of Cortical Morphology Evaluated with Longitudinal MR Brain Images of Preterm Infants. PLoS One 2015; 10:e0131552. [PMID: 26161536 PMCID: PMC4498793 DOI: 10.1371/journal.pone.0131552] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2015] [Accepted: 06/03/2015] [Indexed: 12/18/2022] Open
Abstract
INTRODUCTION The cerebral cortex develops rapidly in the last trimester of pregnancy. In preterm infants, brain development is very vulnerable because of their often complicated extra-uterine conditions. The aim of this study was to quantitatively describe cortical development in a cohort of 85 preterm infants with and without brain injury imaged at 30 and 40 weeks postmenstrual age (PMA). METHODS In the acquired T2-weighted MR images, unmyelinated white matter (UWM), cortical grey matter (CoGM), and cerebrospinal fluid in the extracerebral space (CSF) were automatically segmented. Based on these segmentations, cortical descriptors evaluating volume, surface area, thickness, gyrification index, and global mean curvature were computed at both time points, for the whole brain, as well as for the frontal, temporal, parietal, and occipital lobes separately. Additionally, visual scoring of brain abnormality was performed using a conventional scoring system at 40 weeks PMA. RESULTS The evaluated descriptors showed larger change in the occipital lobes than in the other lobes. Moreover, the cortical descriptors showed an association with the abnormality scores: gyrification index and global mean curvature decreased, whereas, interestingly, median cortical thickness increased with increasing abnormality score. This was more pronounced at 40 weeks PMA than at 30 weeks PMA, suggesting that the period between 30 and 40 weeks PMA might provide a window of opportunity for intervention to prevent delay in cortical development.
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Affiliation(s)
- Pim Moeskops
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Neonatology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Manon J N L Benders
- Department of Neonatology, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Perinatal Imaging & Health, Division of Imaging Sciences & Biomedical Engineering, King's College London, London, United Kingdom; Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Karina J Kersbergen
- Department of Neonatology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Floris Groenendaal
- Department of Neonatology, University Medical Center Utrecht, Utrecht, The Netherlands; Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Linda S de Vries
- Department of Neonatology, University Medical Center Utrecht, Utrecht, The Netherlands; Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Max A Viergever
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Ivana Išgum
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands; Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
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40
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Wu J, Awate SP, Licht DJ, Clouchoux C, du Plessis AJ, Avants BB, Vossough A, Gee JC, Limperopoulos C. Assessment of MRI-Based Automated Fetal Cerebral Cortical Folding Measures in Prediction of Gestational Age in the Third Trimester. AJNR Am J Neuroradiol 2015; 36:1369-74. [PMID: 26045578 DOI: 10.3174/ajnr.a4357] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2014] [Accepted: 12/20/2014] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Traditional methods of dating a pregnancy based on history or sonographic assessment have a large variation in the third trimester. We aimed to assess the ability of various quantitative measures of brain cortical folding on MR imaging in determining fetal gestational age in the third trimester. MATERIALS AND METHODS We evaluated 8 different quantitative cortical folding measures to predict gestational age in 33 healthy fetuses by using T2-weighted fetal MR imaging. We compared the accuracy of the prediction of gestational age by these cortical folding measures with the accuracy of prediction by brain volume measurement and by a previously reported semiquantitative visual scale of brain maturity. Regression models were constructed, and measurement biases and variances were determined via a cross-validation procedure. RESULTS The cortical folding measures are accurate in the estimation and prediction of gestational age (mean of the absolute error, 0.43 ± 0.45 weeks) and perform better than (P = .024) brain volume (mean of the absolute error, 0.72 ± 0.61 weeks) or sonography measures (SDs approximately 1.5 weeks, as reported in literature). Prediction accuracy is comparable with that of the semiquantitative visual assessment score (mean, 0.57 ± 0.41 weeks). CONCLUSIONS Quantitative cortical folding measures such as global average curvedness can be an accurate and reliable estimator of gestational age and brain maturity for healthy fetuses in the third trimester and have the potential to be an indicator of brain-growth delays for at-risk fetuses and preterm neonates.
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Affiliation(s)
- J Wu
- From the Department of Radiology (J.W., B.B.A., A.V., J.C.G.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - S P Awate
- Department of Computer Science and Engineering (S.P.A.), Indian Institute of Technology Bombay, Mumbai, India
| | - D J Licht
- Neurovascular Imaging Lab (D.J.L.), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - C Clouchoux
- Advanced Pediatric Brain Imaging Research Laboratory (C.C., C.L.), Children's National Medical Center, Washington, DC Departments of Neurology, Radiology, and Pediatrics (C.C., A.J.d.P., C.L.), George Washington University School of Medicine and Health Sciences, Washington, DC
| | - A J du Plessis
- Departments of Neurology, Radiology, and Pediatrics (C.C., A.J.d.P., C.L.), George Washington University School of Medicine and Health Sciences, Washington, DC
| | - B B Avants
- From the Department of Radiology (J.W., B.B.A., A.V., J.C.G.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - A Vossough
- From the Department of Radiology (J.W., B.B.A., A.V., J.C.G.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - J C Gee
- From the Department of Radiology (J.W., B.B.A., A.V., J.C.G.), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - C Limperopoulos
- Advanced Pediatric Brain Imaging Research Laboratory (C.C., C.L.), Children's National Medical Center, Washington, DC Departments of Neurology, Radiology, and Pediatrics (C.C., A.J.d.P., C.L.), George Washington University School of Medicine and Health Sciences, Washington, DC
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41
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Mehler K, Ulbrich L, Börner S, Joachim A, Becker I, Roth B, Hünseler C. Multidimensional response to vaccination pain in very preterm, moderate- to-late preterm and full-term infants at age three months. Early Hum Dev 2015; 91:199-204. [PMID: 25682563 DOI: 10.1016/j.earlhumdev.2015.01.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Revised: 01/22/2015] [Accepted: 01/27/2015] [Indexed: 10/24/2022]
Abstract
BACKGROUND Very early life pain exposure and stress induces alterations in the developing brain and leads to altered pain sensitivity. In premature infants with a history of numerous early postnatal adverse events, behavioral responsiveness and hypothalamic-pituitary-adrenal (HPA) axis reactivity may show alterations as well. AIMS We compared a multidimensional response to a painful situation (vaccination) in three month old infants. The study involved very preterm, moderate to late preterm infants and full-term infants with varying exposure to pain and stress within the first weeks of life. STUDY DESIGN At the age of three months, we evaluated the infants' reactivity to intramuscular injections for immunization. SUBJECTS The study included 61 very preterm infants, 30 moderate to late preterm infants and 30 full-term infants. OUTCOME MEASURES We assessed heart rate recovery, Bernese pain Score and increase of salivary cortisol following vaccination. We also evaluated the flexor withdrawal reflex threshold as well as Prechtl's General Movements. Secondly, we assessed factors potentially influencing pain reactivity such as exposure to pain/stress, gender, use of steroids or opioids and mechanical ventilation. RESULTS Very preterm, moderate to late preterm and full-term infants showed different reactivity to pain in all analyzed aspects. Very preterm infants showed a lower level of behavioral and physiologic reactivity and exposure to pain/stress predicted lower cortisol increase. CONCLUSION At three months of age, very preterm infants show an altered level of HPA axis reactivity. Efforts aiming at minimizing pain and stress in premature infants should be taken.
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Affiliation(s)
- Katrin Mehler
- University Hospital of Cologne, Department of Neonatology, Germany.
| | - Lisa Ulbrich
- University Hospital of Cologne, Department of Neonatology, Germany
| | - Sarah Börner
- University Hospital of Cologne, Department of Neonatology, Germany
| | | | - Ingrid Becker
- Institute of Medical Statistics, Informatics and Epidemiology, University of Cologne, Germany
| | - Bernhard Roth
- University Hospital of Cologne, Department of Neonatology, Germany
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42
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Pieterman K, Plaisier A, Govaert P, Leemans A, Lequin MH, Dudink J. Data quality in diffusion tensor imaging studies of the preterm brain: a systematic review. Pediatr Radiol 2015; 45:1372-81. [PMID: 25820411 PMCID: PMC4526590 DOI: 10.1007/s00247-015-3307-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Revised: 01/15/2015] [Accepted: 02/05/2015] [Indexed: 01/31/2023]
Abstract
BACKGROUND To study early neurodevelopment in preterm infants, evaluation of brain maturation and injury is increasingly performed using diffusion tensor imaging, for which the reliability of underlying data is paramount. OBJECTIVE To review the literature to evaluate acquisition and processing methodology in diffusion tensor imaging studies of preterm infants. MATERIALS AND METHODS We searched the Embase, Medline, Web of Science and Cochrane databases for relevant papers published between 2003 and 2013. The following keywords were included in our search: prematurity, neuroimaging, brain, and diffusion tensor imaging. RESULTS We found 74 diffusion tensor imaging studies in preterm infants meeting our inclusion criteria. There was wide variation in acquisition and processing methodology, and we found incomplete reporting of these settings. Nineteen studies (26%) reported the use of neonatal hardware. Data quality assessment was not reported in 13 (18%) studies. Artefacts-correction and data-exclusion was not reported in 33 (45%) and 18 (24%) studies, respectively. Tensor estimation algorithms were reported in 56 (76%) studies but were often suboptimal. CONCLUSION Diffusion tensor imaging acquisition and processing settings are incompletely described in current literature, vary considerably, and frequently do not meet the highest standards.
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Affiliation(s)
- Kay Pieterman
- Division of Neonatology, Department of Pediatrics, Erasmus Medical Center - Sophia, dr. Molewaterplein 60, 3015, GJ, Rotterdam, The Netherlands,
| | - Annemarie Plaisier
- Division of Neonatology, Department of Pediatrics, Erasmus Medical Center – Sophia, dr. Molewaterplein 60, 3015 GJ Rotterdam, The Netherlands ,Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Paul Govaert
- Division of Neonatology, Department of Pediatrics, Erasmus Medical Center – Sophia, dr. Molewaterplein 60, 3015 GJ Rotterdam, The Netherlands ,Department of Pediatrics, Koningin Paola Children’s Hospital, Antwerp, Belgium
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maarten H. Lequin
- Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jeroen Dudink
- Division of Neonatology, Department of Pediatrics, Erasmus Medical Center – Sophia, dr. Molewaterplein 60, 3015 GJ Rotterdam, The Netherlands ,Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
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43
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Kersbergen KJ, Leemans A, Groenendaal F, van der Aa NE, Viergever MA, de Vries LS, Benders MJ. Microstructural brain development between 30 and 40 weeks corrected age in a longitudinal cohort of extremely preterm infants. Neuroimage 2014; 103:214-224. [DOI: 10.1016/j.neuroimage.2014.09.039] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Revised: 08/06/2014] [Accepted: 09/15/2014] [Indexed: 12/13/2022] Open
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44
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Ouyang A, Jeon T, Sunkin SM, Pletikos M, Sedmak G, Sestan N, Lein ES, Huang H. Spatial mapping of structural and connectional imaging data for the developing human brain with diffusion tensor imaging. Methods 2014; 73:27-37. [PMID: 25448302 DOI: 10.1016/j.ymeth.2014.10.025] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2014] [Revised: 09/08/2014] [Accepted: 10/21/2014] [Indexed: 01/26/2023] Open
Abstract
During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain.
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Affiliation(s)
- Austin Ouyang
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States
| | - Tina Jeon
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States
| | - Susan M Sunkin
- Allen Institute for Brain Science, Seattle, WA, United States
| | - Mihovil Pletikos
- Department of Neurobiology and Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Goran Sedmak
- Department of Neurobiology and Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States; University of Zagreb School of Medicine, Croatian Institute for Brain Research, Salata 12, 10 000 Zagreb, Croatia
| | - Nenad Sestan
- Department of Neurobiology and Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, United States
| | - Hao Huang
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States; Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
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45
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Paydar A. Diffusional kurtosis imaging: a promising technique for detecting microstructural changes in neural development and regeneration. Neural Regen Res 2014; 9:1108-9. [PMID: 25206767 PMCID: PMC4146103 DOI: 10.4103/1673-5374.135309] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/28/2014] [Indexed: 11/09/2022] Open
Affiliation(s)
- Amir Paydar
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, 660 First Ave, 4 Floor, New York, NY, USA
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46
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Truong TK, Guidon A, Song AW. Cortical depth dependence of the diffusion anisotropy in the human cortical gray matter in vivo. PLoS One 2014; 9:e91424. [PMID: 24608869 PMCID: PMC3946789 DOI: 10.1371/journal.pone.0091424] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2013] [Accepted: 02/11/2014] [Indexed: 11/21/2022] Open
Abstract
Diffusion tensor imaging (DTI) is typically used to study white matter fiber pathways, but may also be valuable to assess the microstructure of cortical gray matter. Although cortical diffusion anisotropy has previously been observed in vivo, its cortical depth dependence has mostly been examined in high-resolution ex vivo studies. This study thus aims to investigate the cortical depth dependence of the diffusion anisotropy in the human cortex in vivo on a clinical 3 T scanner. Specifically, a novel multishot constant-density spiral DTI technique with inherent correction of motion-induced phase errors was used to achieve a high spatial resolution (0.625×0.625×3 mm) and high spatial fidelity with no scan time penalty. The results show: (i) a diffusion anisotropy in the cortical gray matter, with a primarily radial diffusion orientation, as observed in previous ex vivo and in vivo studies, and (ii) a cortical depth dependence of the fractional anisotropy, with consistently higher values in the middle cortical lamina than in the deep and superficial cortical laminae, as observed in previous ex vivo studies. These results, which are consistent across subjects, demonstrate the feasibility of this technique for investigating the cortical depth dependence of the diffusion anisotropy in the human cortex in vivo.
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Affiliation(s)
- Trong-Kha Truong
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, United States of America
- * E-mail:
| | - Arnaud Guidon
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, United States of America
| | - Allen W. Song
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, United States of America
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47
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Melbourne A, Kendall GS, Cardoso MJ, Gunny R, Robertson NJ, Marlow N, Ourselin S. Preterm birth affects the developmental synergy between cortical folding and cortical connectivity observed on multimodal MRI. Neuroimage 2013; 89:23-34. [PMID: 24315841 DOI: 10.1016/j.neuroimage.2013.11.048] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2013] [Revised: 11/26/2013] [Accepted: 11/28/2013] [Indexed: 11/18/2022] Open
Abstract
The survival rates of infants born prematurely have improved as a result of advances in neonatal care, although there remains an increased risk of subsequent disability. Accurate measurement of the shape and appearance of the very preterm brain at term-equivalent age may guide the development of predictive biomarkers of neurological outcome. We demonstrate in 92 preterm infants (born at an average gestational age of 27.0±2.7weeks) scanned at term equivalent age (scanned at 40.4±1.74weeks) that the cortical sulcation ratio varies spatially over the cortical surface at term equivalent age and correlates significantly with gestational age at birth (r=0.49,p<0.0001). In the underlying white matter, fractional anisotropy of local white matter regions correlated significantly with gestational age at birth at term equivalent age (for the genu of the corpus callosum r=0.26,p=0.02 and for the splenium r=0.52,p<0.001) and in addition the fractional anisotropy in these local regions varies according to location. Finally, we demonstrate that connectivity measurements from tractography correlate significantly and specifically with the sulcation ratio of the overlying cortical surface at term equivalent age in a subgroup of 20 infants (r={0.67,0.61,0.86}, p={0.004,0.01,0.00002}) for tract systems emanating from the left and right corticospinal tracts and the corpus callosum respectively). Combined, these results suggest a close relationship between the cortical surface phenotype and underlying white matter structure assessed by diffusion weighted MRI. The spatial surface pattern may allow inference on the connectivity and developmental trajectory of the underlying white matter complementary to diffusion imaging and this result may guide the development of biomarkers of functional outcome.
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Affiliation(s)
- Andrew Melbourne
- Centre for Medical Image Computing (CMIC), University College London, UK.
| | - Giles S Kendall
- Academic Neonatology, EGA UCL Institute for Women's Health, London, UK
| | - M Jorge Cardoso
- Centre for Medical Image Computing (CMIC), University College London, UK
| | - Roxanna Gunny
- Academic Neonatology, EGA UCL Institute for Women's Health, London, UK
| | | | - Neil Marlow
- Academic Neonatology, EGA UCL Institute for Women's Health, London, UK
| | - Sebastien Ourselin
- Centre for Medical Image Computing (CMIC), University College London, UK
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48
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Leigland LA, Budde MD, Cornea A, Kroenke CD. Diffusion MRI of the developing cerebral cortical gray matter can be used to detect abnormalities in tissue microstructure associated with fetal ethanol exposure. Neuroimage 2013; 83:1081-7. [PMID: 23921100 PMCID: PMC3815979 DOI: 10.1016/j.neuroimage.2013.07.068] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2013] [Revised: 07/18/2013] [Accepted: 07/25/2013] [Indexed: 11/23/2022] Open
Abstract
Fetal alcohol spectrum disorders (FASDs) comprise a wide range of neurological deficits that result from fetal exposure to ethanol (EtOH), and are the leading cause of environmentally related birth defects and mental retardation in the western world. One aspect of diagnostic and therapeutic intervention strategies that could substantially improve our ability to combat this significant problem would be to facilitate earlier detection of the disorders within individuals. Light microscopy-based investigations performed by several laboratories have previously shown that morphological development of neurons within the early-developing cerebral cortex is abnormal within the brains of animals exposed to EtOH during fetal development. We and others have recently demonstrated that diffusion MRI can be of utility for detecting abnormal cellular morphological development in the developing cerebral cortex. We therefore assessed whether diffusion tensor imaging (DTI) could be used to distinguish the developing cerebral cortices of ex vivo rat pup brains born from dams treated with EtOH (EtOH; 4.5 g/kg, 25%) or calorie-matched quantities of maltose/dextrin (M/D) throughout gestation. Water diffusion and tissue microstructure were investigated using DTI (fractional anisotropy, FA) and histology (anisotropy index, AI), respectively. Both FA and AI decreased with age, and were higher in the EtOH than the M/D group at postnatal ages (P)0, P3, and P6. Additionally, there was a significant correlation between FA and AI measurements. These findings provide evidence that disruptions in cerebral cortical development induced by EtOH exposure can be revealed by water diffusion anisotropy patterns, and that these disruptions are directly related to cerebral cortical differentiation.
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Affiliation(s)
- Lindsey A. Leigland
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR
| | - Matthew D. Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI
| | - Anda Cornea
- Oregon National Primate Research Center, Oregon Health & Science University, Portland, OR
| | - Christopher D. Kroenke
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR
- Oregon National Primate Research Center, Oregon Health & Science University, Portland, OR
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49
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Paydar A, Fieremans E, Nwankwo JI, Lazar M, Sheth HD, Adisetiyo V, Helpern JA, Jensen JH, Milla SS. Diffusional kurtosis imaging of the developing brain. AJNR Am J Neuroradiol 2013; 35:808-14. [PMID: 24231848 DOI: 10.3174/ajnr.a3764] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Diffusional kurtosis imaging is an extension of DTI but includes non-Gaussian diffusion effects, allowing more comprehensive characterization of microstructural changes during brain development. Our purpose was to use diffusional kurtosis imaging to measure age-related microstructural changes in both the WM and GM of the developing human brain. MATERIALS AND METHODS Diffusional kurtosis imaging was performed in 59 subjects ranging from birth to 4 years 7 months of age. Diffusion metrics, fractional anisotropy, and mean kurtosis were collected from VOIs within multiple WM and GM structures and subsequently analyzed with respect to age. Diffusional kurtosis tractography images at various stages of development were also generated. RESULTS Fractional anisotropy and mean kurtosis both showed age-related increases in all WM regions, reflecting progression of diffusional anisotropy throughout development, predominantly in the first 2 years of life (eg, 70% and 157% increase in fractional anisotropy and mean kurtosis, respectively, from birth to 2 years for the splenium). However, mean kurtosis detected continued microstructural changes in WM past the fractional anisotropy plateau, accounting for more delayed isotropic changes (eg, 90% of maximum fractional anisotropy was reached at 5 months, whereas 90% of maximum mean kurtosis occurred at 18 months for the external capsule). Mean kurtosis may also provide greater characterization of GM maturation (eg, the putamen showed no change in fractional anisotropy but an 81% change in mean kurtosis from birth to 4 years 7 months). CONCLUSIONS Mean kurtosis detects significant microstructural changes consistent with known patterns of brain maturation. In comparison with fractional anisotropy, mean kurtosis may offer a more comprehensive evaluation of age-related microstructural changes in both WM and GM and is potentially a valuable technique for studying brain development.
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Affiliation(s)
- A Paydar
- From the Department of Radiology (A.P., E.F., J.I.N., M.L., H.D.S., V.A., S.S.M.), Center for Biomedical Imaging, New York University School of Medicine, New York, New York
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50
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Dean JM, McClendon E, Hansen K, Azimi-Zonooz A, Chen K, Riddle A, Gong X, Sharifnia E, Hagen M, Ahmad T, Leigland LA, Hohimer AR, Kroenke CD, Back SA. Prenatal cerebral ischemia disrupts MRI-defined cortical microstructure through disturbances in neuronal arborization. Sci Transl Med 2013; 5:168ra7. [PMID: 23325800 DOI: 10.1126/scitranslmed.3004669] [Citation(s) in RCA: 130] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Children who survive preterm birth exhibit persistent unexplained disturbances in cerebral cortical growth with associated cognitive and learning disabilities. The mechanisms underlying these deficits remain elusive. We used ex vivo diffusion magnetic resonance imaging to demonstrate in a preterm large-animal model that cerebral ischemia impairs cortical growth and the normal maturational decline in cortical fractional anisotropy (FA). Analysis of pyramidal neurons revealed that cortical deficits were associated with impaired expansion of the dendritic arbor and reduced synaptic density. Together, these findings suggest a link between abnormal cortical FA and disturbances of neuronal morphological development. To experimentally investigate this possibility, we measured the orientation distribution of dendritic branches and observed that it corresponds with the theoretically predicted pattern of increased anisotropy within cases that exhibited elevated cortical FA after ischemia. We conclude that cortical growth impairments are associated with diffuse disturbances in the dendritic arbor and synapse formation of cortical neurons, which may underlie the cognitive and learning disabilities in survivors of preterm birth. Further, measurement of cortical FA may be useful for noninvasively detecting neurological disorders affecting cortical development.
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Affiliation(s)
- Justin M Dean
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Evelyn McClendon
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Kelly Hansen
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Aryan Azimi-Zonooz
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Kevin Chen
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Art Riddle
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Xi Gong
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Elica Sharifnia
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Matthew Hagen
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Tahir Ahmad
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Lindsey A Leigland
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, USA.,Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - A Roger Hohimer
- Department of Obstetrics and Gynecology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Christopher D Kroenke
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, USA.,Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - Stephen A Back
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA.,Department of Neurology, Oregon Health & Science University, Portland, OR 97239, USA
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