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Calixto C, Machado-Rivas F, Cortes-Albornoz MC, Karimi D, Velasco-Annis C, Afacan O, Warfield SK, Gholipour A, Jaimes C. Characterizing microstructural development in the fetal brain using diffusion MRI from 23 to 36 weeks of gestation. Cereb Cortex 2024; 34:bhad409. [PMID: 37948665 PMCID: PMC10793585 DOI: 10.1093/cercor/bhad409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/09/2023] [Accepted: 10/10/2023] [Indexed: 11/12/2023] Open
Abstract
We utilized motion-corrected diffusion tensor imaging (DTI) to evaluate microstructural changes in healthy fetal brains during the late second and third trimesters. Data were derived from fetal magnetic resonance imaging scans conducted as part of a prospective study spanning from 2013 March to 2019 May. The study included 44 fetuses between the gestational ages (GAs) of 23 and 36 weeks. We reconstructed fetal brain DTI using a motion-tracked slice-to-volume registration framework. Images were segmented into 14 regions of interest (ROIs) through label propagation using a fetal DTI atlas, with expert refinement. Statistical analysis involved assessing changes in fractional anisotropy (FA) and mean diffusivity (MD) throughout gestation using mixed-effects models, and identifying points of change in trajectory for ROIs with nonlinear trends. Results showed significant GA-related changes in FA and MD in all ROIs except in the thalamus' FA and corpus callosum's MD. Hemispheric asymmetries were found in the FA of the periventricular white matter (pvWM), intermediate zone, and subplate and in the MD of the ganglionic eminence and pvWM. This study provides valuable insight into the normal patterns of development of MD and FA in the fetal brain. These changes are closely linked with cytoarchitectonic changes and display indications of early functional specialization.
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Affiliation(s)
- Camilo Calixto
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Fedel Machado-Rivas
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Maria C Cortes-Albornoz
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Davood Karimi
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Clemente Velasco-Annis
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Onur Afacan
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA 02115, United States
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
| | - Camilo Jaimes
- Department of Radiology, Harvard Medical School, Boston, MA 02115, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, United States
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Mallela AN, Deng H, Gholipour A, Warfield SK, Goldschmidt E. Heterogeneous growth of the insula shapes the human brain. Proc Natl Acad Sci U S A 2023; 120:e2220200120. [PMID: 37279278 PMCID: PMC10268209 DOI: 10.1073/pnas.2220200120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 04/13/2023] [Indexed: 06/08/2023] Open
Abstract
The human cerebrum consists of a precise and stereotyped arrangement of lobes, primary gyri, and connectivity that underlies human cognition [P. Rakic, Nat. Rev. Neurosci. 10, 724-735 (2009)]. The development of this arrangement is less clear. Current models explain individual primary gyrification but largely do not account for the global configuration of the cerebral lobes [T. Tallinen, J. Y. Chung, J. S. Biggins, L. Mahadevan, Proc. Natl. Acad. Sci. U.S.A. 111, 12667-12672 (2014) and D. C. Van Essen, Nature 385, 313-318 (1997)]. The insula, buried in the depths of the Sylvian fissure, is unique in terms of gyral anatomy and size. Here, we quantitatively show that the insula has unique morphology and location in the cerebrum and that these key differences emerge during fetal development. Finally, we identify quantitative differences in developmental migration patterns to the insula that may underlie these differences. We calculated morphologic data in the insula and other lobes in adults (N = 107) and in an in utero fetal brain atlas (N = 81 healthy fetuses). In utero, the insula grows an order of magnitude slower than the other lobes and demonstrates shallower sulci, less curvature, and less surface complexity both in adults and progressively throughout fetal development. Spherical projection analysis demonstrates that the lenticular nuclei obstruct 60 to 70% of radial pathways from the ventricular zone (VZ) to the insula, forcing a curved migration to the insula in contrast to a direct radial pathway. Using fetal diffusion tractography, we identify radial glial fascicles that originate from the VZ and curve around the lenticular nuclei to form the insula. These results confirm existing models of radial migration to the cortex and illustrate findings that suggest differential insular and cerebral development, laying the groundwork to understand cerebral malformations and insular function and pathologies.
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Affiliation(s)
- Arka N. Mallela
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA15213
| | - Hansen Deng
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA15213
| | - Ali Gholipour
- Department of Radiology, Harvard Medical School, Boston, MA02115
- Department of Radiology, Boston Children’s Hospital, Boston, MA02115
| | - Simon K. Warfield
- Department of Radiology, Harvard Medical School, Boston, MA02115
- Department of Radiology, Boston Children’s Hospital, Boston, MA02115
| | - Ezequiel Goldschmidt
- Department of Radiology, Harvard Medical School, Boston, MA02115
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA94143
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Ma Y, Bruce IP, Yeh CH, Petrella JR, Song AW, Truong TK. Column-based cortical depth analysis of the diffusion anisotropy and radiality in submillimeter whole-brain diffusion tensor imaging of the human cortical gray matter in vivo. Neuroimage 2023; 270:119993. [PMID: 36863550 PMCID: PMC10037338 DOI: 10.1016/j.neuroimage.2023.119993] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 02/22/2023] [Accepted: 02/25/2023] [Indexed: 03/04/2023] Open
Abstract
High-resolution diffusion tensor imaging (DTI) can noninvasively probe the microstructure of cortical gray matter in vivo. In this study, 0.9-mm isotropic whole-brain DTI data were acquired in healthy subjects with an efficient multi-band multi-shot echo-planar imaging sequence. A column-based analysis that samples the fractional anisotropy (FA) and radiality index (RI) along radially oriented cortical columns was then performed to quantitatively analyze the FA and RI dependence on the cortical depth, cortical region, cortical curvature, and cortical thickness across the whole brain, which has not been simultaneously and systematically investigated in previous studies. The results showed characteristic FA and RI vs. cortical depth profiles, with an FA local maximum and minimum (or two inflection points) and a single RI maximum at intermediate cortical depths in most cortical regions, except for the postcentral gyrus where no FA peaks and a lower RI were observed. These results were consistent between repeated scans from the same subjects and across different subjects. They were also dependent on the cortical curvature and cortical thickness in that the characteristic FA and RI peaks were more pronounced i) at the banks than at the crown of gyri or at the fundus of sulci and ii) as the cortical thickness increases. This methodology can help characterize variations in microstructure along the cortical depth and across the whole brain in vivo, potentially providing quantitative biomarkers for neurological disorders.
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Affiliation(s)
- Yixin Ma
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Medical Physics Graduate Program, Duke University, Durham, NC, United States
| | - Iain P Bruce
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Department of Neurology, Duke University, Durham, NC, United States
| | - Chun-Hung Yeh
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan
| | - Jeffrey R Petrella
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Medical Physics Graduate Program, Duke University, Durham, NC, United States; Department of Radiology, Duke University, Durham, NC, United States
| | - Allen W Song
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Medical Physics Graduate Program, Duke University, Durham, NC, United States; Department of Radiology, Duke University, Durham, NC, United States.
| | - Trong-Kha Truong
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Medical Physics Graduate Program, Duke University, Durham, NC, United States; Department of Radiology, Duke University, Durham, NC, United States.
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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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5
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Peterson BS, Liu J, Dantec L, Newman C, Sawardekar S, Goh S, Bansal R. Using tissue microstructure and multimodal MRI to parse the phenotypic heterogeneity and cellular basis of autism spectrum disorder. J Child Psychol Psychiatry 2022; 63:855-870. [PMID: 34762311 PMCID: PMC9091058 DOI: 10.1111/jcpp.13531] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/08/2021] [Indexed: 01/11/2023]
Abstract
BACKGROUND Identifying the brain bases for phenotypic heterogeneity in Autism Spectrum Disorder (ASD) will advance understanding of its pathogenesis and improve its clinical management. METHODS We compared Diffusion Tensor Imaging (DTI) indices and connectome measures between 77 ASD and 88 Typically Developing (TD) control participants. We also assessed voxel-wise associations of DTI indices with measures of regional cerebral blood flow (rCBF) and N-acetylaspartate (NAA) to understand how tissue microstructure associates with cellular metabolism and neuronal density, respectively. RESULTS Autism Spectrum Disorder participants had significantly lower fractional anisotropy (FA) and higher diffusivity values in deep white matter tracts, likely representing ether reduced myelination by oligodendrocytes or a reduced density of myelinated axons. Greater abnormalities in these measures and regions were associated with higher ASD symptom scores. Participant age, sex and IQ significantly moderated these group differences. Path analyses showed that reduced NAA levels accounted significantly for higher diffusivity and higher rCBF values in ASD compared with TD participants. CONCLUSIONS Reduced neuronal density (reduced NAA) likely underlies abnormalities in DTI indices of white matter microstructure in ASD, which in turn are major determinants of elevated blood flow. Together, these findings suggest the presence of reduced axonal density and axonal pathology in ASD white matter. Greater pathology in turn accounts for more severe symptoms, lower intellectual ability, and reduced global efficiency for measures of white matter connectivity in ASD.
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Affiliation(s)
- Bradley S. Peterson
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
| | - Jiaqi Liu
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | - Louis Dantec
- École Polytechnique Universitaire de Marseille, France
| | | | - Siddhant Sawardekar
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | | | - Ravi Bansal
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
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Dimitrova R, Pietsch M, Ciarrusta J, Fitzgibbon SP, Williams LZJ, Christiaens D, Cordero-Grande L, Batalle D, Makropoulos A, Schuh A, Price AN, Hutter J, Teixeira RP, Hughes E, Chew A, Falconer S, Carney O, Egloff A, Tournier JD, McAlonan G, Rutherford MA, Counsell SJ, Robinson EC, Hajnal JV, Rueckert D, Edwards AD, O'Muircheartaigh J. Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age. Neuroimage 2021; 243:118488. [PMID: 34419595 PMCID: PMC8526870 DOI: 10.1016/j.neuroimage.2021.118488] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 07/16/2021] [Accepted: 08/19/2021] [Indexed: 11/27/2022] Open
Abstract
INTRODUCTION The dynamic nature and complexity of the cellular events that take place during the last trimester of pregnancy make the developing cortex particularly vulnerable to perturbations. Abrupt interruption to normal gestation can lead to significant deviations to many of these processes, resulting in atypical trajectory of cortical maturation in preterm birth survivors. METHODS We sought to first map typical cortical micro- and macrostructure development using invivo MRI in a large sample of healthy term-born infants scanned after birth (n = 259). Then we offer a comprehensive characterization of the cortical consequences of preterm birth in 76 preterm infants scanned at term-equivalent age (37-44 weeks postmenstrual age). We describe the group-average atypicality, the heterogeneity across individual preterm infants, and relate individual deviations from normative development to age at birth and neurodevelopment at 18 months. RESULTS In the term-born neonatal brain, we observed heterogeneous and regionally specific associations between age at scan and measures of cortical morphology and microstructure, including rapid surface expansion, greater cortical thickness, lower cortical anisotropy and higher neurite orientation dispersion. By term-equivalent age, preterm infants had on average increased cortical tissue water content and reduced neurite density index in the posterior parts of the cortex, and greater cortical thickness anteriorly compared to term-born infants. While individual preterm infants were more likely to show extreme deviations (over 3.1 standard deviations) from normative cortical maturation compared to term-born infants, these extreme deviations were highly variable and showed very little spatial overlap between individuals. Measures of regional cortical development were associated with age at birth, but not with neurodevelopment at 18 months. CONCLUSION We showed that preterm birth alters cortical micro- and macrostructural maturation near the time of full-term birth. Deviations from normative development were highly variable between individual preterm infants.
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Affiliation(s)
- Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Maximilian Pietsch
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Judit Ciarrusta
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Sean P Fitzgibbon
- Centre for Functional MRI of the Brain (FMRIB), Welcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Logan Z J Williams
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Daan Christiaens
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Department of Electrical Engineering, ESAT/PSI, KU Leuven, Belgium
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BBN, Madrid, Spain
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Antonios Makropoulos
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Andreas Schuh
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Rui Pag Teixeira
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Olivia Carney
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Alexia Egloff
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - J-Donald Tournier
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom; South London and Maudsley NHS Foundation Trust, 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
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Emma C Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom; Faculty of Informatics and Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom.
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Scherrer B, Prohl AK, Taquet M, Kapur K, Peters JM, Tomas-Fernandez X, Davis PE, M Bebin E, Krueger DA, Northrup H, Y Wu J, Sahin M, Warfield SK. The Connectivity Fingerprint of the Fusiform Gyrus Captures the Risk of Developing Autism in Infants with Tuberous Sclerosis Complex. Cereb Cortex 2021; 30:2199-2214. [PMID: 31812987 DOI: 10.1093/cercor/bhz233] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 09/05/2019] [Accepted: 09/12/2019] [Indexed: 12/13/2022] Open
Abstract
Tuberous sclerosis complex (TSC) is a rare genetic disorder characterized by benign tumors throughout the body; it is generally diagnosed early in life and has a high prevalence of autism spectrum disorder (ASD), making it uniquely valuable in studying the early development of autism, before neuropsychiatric symptoms become apparent. One well-documented deficit in ASD is an impairment in face processing. In this work, we assessed whether anatomical connectivity patterns of the fusiform gyrus, a central structure in face processing, capture the risk of developing autism early in life. We longitudinally imaged TSC patients at 1, 2, and 3 years of age with diffusion compartment imaging. We evaluated whether the anatomical connectivity fingerprint of the fusiform gyrus was associated with the risk of developing autism measured by the Autism Observation Scale for Infants (AOSI). Our findings suggest that the fusiform gyrus connectivity captures the risk of developing autism as early as 1 year of age and provides evidence that abnormal fusiform gyrus connectivity increases with age. Moreover, the identified connections that best capture the risk of developing autism involved the fusiform gyrus and limbic and paralimbic regions that were consistent with the ASD phenotype, involving an increased number of left-lateralized structures with increasing age.
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Affiliation(s)
- Benoit Scherrer
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115 USA
| | - Anna K Prohl
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115 USA
| | - Maxime Taquet
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115 USA
| | - Kush Kapur
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115 USA
| | - Jurriaan M Peters
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115 USA
| | - Xavier Tomas-Fernandez
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115 USA
| | - Peter E Davis
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115 USA
| | - Elizabeth M Bebin
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, 35233 USA
| | - Darcy A Krueger
- Department of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229 USA
| | - Hope Northrup
- Department of Pediatrics, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030 USA
| | - Joyce Y Wu
- Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095 USA
| | - Mustafa Sahin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115 USA
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115 USA
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On the use of multicompartment models of diffusion and relaxation for placental imaging. Placenta 2021; 112:197-203. [PMID: 34392172 DOI: 10.1016/j.placenta.2021.07.302] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 04/27/2021] [Accepted: 07/27/2021] [Indexed: 12/14/2022]
Abstract
Multi-compartment models of diffusion and relaxation are ubiquitous in magnetic resonance research especially applied to neuroimaging applications. These models are increasingly making their way into the world of placental imaging. This review provides a framework for their motivation and implementation and describes some of the outstanding questions that need to be answered before they can be routinely adopted.
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Dubois J, Alison M, Counsell SJ, Hertz‐Pannier L, Hüppi PS, Benders MJ. MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances. J Magn Reson Imaging 2021; 53:1318-1343. [PMID: 32420684 PMCID: PMC8247362 DOI: 10.1002/jmri.27192] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 04/24/2020] [Accepted: 04/24/2020] [Indexed: 01/04/2023] Open
Abstract
In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Jessica Dubois
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Marianne Alison
- University of ParisNeuroDiderot, INSERM,ParisFrance
- Department of Pediatric RadiologyAPHP, Robert‐Debré HospitalParisFrance
| | - Serena J. Counsell
- Centre for the Developing BrainSchool of Biomedical Engineering & Imaging Sciences, King's College LondonLondonUK
| | - Lucie Hertz‐Pannier
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Petra S. Hüppi
- Division of Development and Growth, Department of Woman, Child and AdolescentUniversity Hospitals of GenevaGenevaSwitzerland
| | - Manon J.N.L. Benders
- Department of NeonatologyUniversity Medical Center Utrecht, Utrecht UniversityUtrechtthe Netherlands
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10
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Story L, Davidson A, Patkee P, Fleiss B, Kyriakopoulou V, Colford K, Sankaran S, Seed P, Jones A, Hutter J, Shennan A, Rutherford M. Brain volumetry in fetuses that deliver very preterm: An MRI pilot study. NEUROIMAGE-CLINICAL 2021; 30:102650. [PMID: 33838546 PMCID: PMC8045030 DOI: 10.1016/j.nicl.2021.102650] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 03/10/2021] [Accepted: 03/26/2021] [Indexed: 11/17/2022]
Abstract
Fetuses that subsequently deliver very preterm have a reduction in cortical and extra cerebrospinal fluid volumes. If such alterations commence antenatally this suggests a role for earlier administration of neuroprotective agents.
Background Infants born preterm are at increased risk of neurological complications resulting in significant morbidity and mortality. The exact mechanism and the impact of antenatal factors has not been fully elucidated, although antenatal infection/inflammation has been implicated in both the aetiology of preterm birth and subsequent neurological sequelae. It is therefore hypothesized that processes driving preterm birth are affecting brain development in utero. This study aims to compare MRI derived regional brain volumes in fetuses that deliver < 32 weeks with fetuses that subsequently deliver at term. Methods Women at high risk of preterm birth, with gestation 19.4–32 weeks were recruited prospectively. A control group was obtained from existing study datasets. Fetal MRI was performed on a 1.5 T or 3 T MRI scanner: T2-weighted images were obtained of the fetal brain. 3D brain volumetric datsets were produced using slice to volume reconstruction and regional segmentations were produced using multi-atlas approaches for supratentorial brain tissue, lateral ventricles, cerebellum cerebral cortex and extra-cerebrospinal fluid (eCSF). Statistical comparison of control and high-risk for preterm delivery fetuses was performed by creating normal ranges for each parameter from the control datasets and then calculating gestation adjusted z scores. Groups were compared using t-tests. Results Fetal image datasets from 24 pregnancies with delivery < 32 weeks and 87 control pregnancies that delivered > 37 weeks were included. Median gestation at MRI of the preterm group was 26.8 weeks (range 19.4–31.4) and control group 26.2 weeks (range 21.7–31.9). No difference was found in supra-tentorial brain volume, ventricular volume or cerebellar volume but the eCSF and cerebral cortex volumes were smaller in fetuses that delivered preterm (p < 0.001 in both cases). Conclusion Fetuses that deliver preterm have a reduction in cortical and eCSF volumes. This is a novel finding and needs further investigation. If alterations in brain development are commencing antenatally in fetuses that subsequently deliver preterm, this may present a window for in utero therapy in the future.
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Affiliation(s)
- Lisa Story
- Department of Women and Children's Health, King's College London, UK.
| | - Alice Davidson
- Centre for the Developing Brain, King's College London, London, UK
| | - Prachi Patkee
- Centre for the Developing Brain, King's College London, London, UK
| | - Bobbi Fleiss
- Centre for the Developing Brain, King's College London, London, UK; School of Health and Biomedical Sciences, RMIT University, Bundoora 3083, VIC, Australia; Université de Paris, NeuroDiderot, Inserm, F-75019 Paris, France
| | | | - Kathleen Colford
- Centre for the Developing Brain, King's College London, London, UK; Centre for Medical Engineering, King's College London, London, UK
| | | | - Paul Seed
- Department of Women and Children's Health, King's College London, UK
| | - Alice Jones
- Centre for the Developing Brain, King's College London, London, UK; Queen Mary University Medical School, UK
| | - Jana Hutter
- Centre for the Developing Brain, King's College London, London, UK; School of Health and Biomedical Sciences, RMIT University, Bundoora 3083, VIC, Australia
| | - Andrew Shennan
- Department of Women and Children's Health, King's College London, UK
| | - Mary Rutherford
- Centre for the Developing Brain, King's College London, London, UK
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Reymbaut A, Caron AV, Gilbert G, Szczepankiewicz F, Nilsson M, Warfield SK, Descoteaux M, Scherrer B. Magic DIAMOND: Multi-fascicle diffusion compartment imaging with tensor distribution modeling and tensor-valued diffusion encoding. Med Image Anal 2021; 70:101988. [PMID: 33611054 DOI: 10.1016/j.media.2021.101988] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 01/25/2021] [Accepted: 01/29/2021] [Indexed: 01/05/2023]
Abstract
Diffusion tensor imaging provides increased sensitivity to microstructural tissue changes compared to conventional anatomical imaging but also presents limited specificity. To tackle this problem, the DIAMOND model subdivides the voxel content into diffusion compartments and draws from diffusion-weighted data to estimate compartmental non-central matrix-variate Gamma distributions of diffusion tensors. It models each sub-voxel fascicle separately, resolving crossing white-matter pathways and allowing for a fascicle-element (fixel) based analysis of microstructural features. Alternatively, specific features of the intra-voxel diffusion tensor distribution can be selectively measured using tensor-valued diffusion-weighted acquisition schemes. However, the impact of such schemes on estimating brain microstructural features has only been studied in a handful of parametric single-fascicle models. In this work, we derive a general Laplace transform for the non-central matrix-variate Gamma distribution, which enables the extension of DIAMOND to tensor-valued encoded data. We then evaluate this "Magic DIAMOND" model in silico and in vivo on various combinations of tensor-valued encoded data. Assessing uncertainty on parameter estimation via stratified bootstrap, we investigate both voxel-based and fixel-based metrics by carrying out multi-peak tractography. We demonstrate using in silico evaluations that tensor-valued diffusion encoding significantly improves Magic DIAMOND's accuracy. Most importantly, we show in vivo that our estimated metrics can be robustly mapped along tracks across regions of fiber crossing, which opens new perspectives for tractometry and microstructure mapping along specific white-matter tracts.
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Affiliation(s)
| | | | - Guillaume Gilbert
- MR Clinical Science, Philips Healthcare Canada, Markham, ON L6C 2S3, Canada
| | - Filip Szczepankiewicz
- Department of Clinical Sciences, Lund University, 22184, Lund, Sweden; Random Walk Imaging AB, 22224, Lund, Sweden
| | - Markus Nilsson
- Department of Clinical Sciences, Lund University, 22184, Lund, Sweden
| | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital, Boston, MA 02115, United States
| | | | - Benoit Scherrer
- Department of Radiology, Boston Children's Hospital, Boston, MA 02115, United States
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12
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Lee P, Kim HR, Jeong Y. Detection of gray matter microstructural changes in Alzheimer's disease continuum using fiber orientation. BMC Neurol 2020; 20:362. [PMID: 33008321 PMCID: PMC7532608 DOI: 10.1186/s12883-020-01939-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 09/23/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND This study aimed to investigate feasible gray matter microstructural biomarkers with high sensitivity for early Alzheimer's disease (AD) detection. We propose a diffusion tensor imaging (DTI) measure, "radiality", as an early AD biomarker. It is the dot product of the normal vector of the cortical surface and primary diffusion direction, which reflects the fiber orientation within the cortical column. METHODS We analyzed neuroimages from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, including images from 78 cognitively normal (CN), 50 early mild cognitive impairment (EMCI), 34 late mild cognitive impairment (LMCI), and 39 AD patients. We then evaluated the cortical thickness (CTh), mean diffusivity (MD), which are conventional AD magnetic resonance imaging (MRI) biomarkers, and the amount of accumulated amyloid and tau using positron emission tomography (PET). Radiality was projected on the gray matter surface to compare and validate the changes with different stages alongside other neuroimage biomarkers. RESULTS The results revealed decreased radiality primarily in the entorhinal, insula, frontal, and temporal cortex with further progression of disease. In particular, radiality could delineate the difference between the CN and EMCI groups, while the other biomarkers could not. We examined the relationship between radiality and other biomarkers to validate its pathological evidence in AD. Overall, radiality showed a high association with conventional biomarkers. Additional ROI analysis revealed the dynamics of AD-related changes as stages onward. CONCLUSION Radiality in cortical gray matter showed AD-specific changes and relevance with other conventional AD biomarkers with high sensitivity. Moreover, radiality could identify the group differences seen in EMCI, representative of changes in early AD, which supports its superiority in early diagnosis compared to that possible with conventional biomarkers. We provide evidence of structural changes with cognitive impairment and suggest radiality as a sensitive biomarker for identifying early AD.
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Affiliation(s)
- Peter Lee
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro 291, Yuseong-gu, Daejeon, 34141, Republic of Korea
- KI for Health Science and Technology, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Hang-Rai Kim
- KI for Health Science and Technology, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Yong Jeong
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro 291, Yuseong-gu, Daejeon, 34141, Republic of Korea.
- KI for Health Science and Technology, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
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Abstract
Despite notable advances in the care and survival of preterm infants, a significant proportion of preterm neonates will have life-long cognitive, behavioral, and motor deficits, and robustly effective neuroprotective strategies are still missing. These therapies must target the pathophysiologic mechanisms observed in contemporaneous infants and rely on modern epidemiology, imaging, and experimental models and assessment techniques. Two drugs, magnesium sulfate and caffeine, are already in use in several units, and although their targets are apnea of prematurity and myometrial contractility (respectively), they do offer improved odds of positive outcomes. Nevertheless, these drugs have limited efficacy, and NICU-to-NICU administration varies greatly. As such, there is an obvious need for additional specific neurotherapeutic strategies to further enhance the outcome of this very fragile population of neonates. The chapter reviews these issues, highlights bottlenecks that need to be solved for meaningful progress in the field, and proposes future innovative avenues for intervention, including delayed interventions.
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Affiliation(s)
- Bobbi Fleiss
- NeuroDiderot, INSERM, Université Paris Diderot, Sorbonne Paris Cité, Paris, France; Division of Imaging Sciences and Biomedical Engineering, Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Pierre Gressens
- NeuroDiderot, INSERM, Université Paris Diderot, Sorbonne Paris Cité, Paris, France; Division of Imaging Sciences and Biomedical Engineering, Centre for the Developing Brain, King's College London, London, United Kingdom.
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14
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Neuroinflammation in preterm babies and autism spectrum disorders. Pediatr Res 2019; 85:155-165. [PMID: 30446768 DOI: 10.1038/s41390-018-0208-4] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Revised: 09/25/2018] [Accepted: 09/25/2018] [Indexed: 12/23/2022]
Abstract
Genetic anomalies have a role in autism spectrum disorders (ASD). Each genetic factor is responsible for a small fraction of cases. Environment factors, like preterm delivery, have an important role in ASD. Preterm infants have a 10-fold higher risk of developing ASD. Preterm birth is often associated with maternal/fetal inflammation, leading to a fetal/neonatal inflammatory syndrome. There are demonstrated experimental links between fetal inflammation and the later development of behavioral symptoms consistent with ASD. Preterm infants have deficits in connectivity. Most ASD genes encode synaptic proteins, suggesting that ASD are connectivity pathologies. Microglia are essential for normal synaptogenesis. Microglia are diverted from homeostatic functions towards inflammatory phenotypes during perinatal inflammation, impairing synaptogenesis. Preterm infants with ASD have a different phenotype from term born peers. Our original hypothesis is that exposure to inflammation in preterm infants, combined with at risk genetic background, deregulates brain development leading to ASD.
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15
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Pecheva D, Kelly C, Kimpton J, Bonthrone A, Batalle D, Zhang H, Counsell SJ. Recent advances in diffusion neuroimaging: applications in the developing preterm brain. F1000Res 2018; 7. [PMID: 30210783 PMCID: PMC6107996 DOI: 10.12688/f1000research.15073.1] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/17/2018] [Indexed: 12/13/2022] Open
Abstract
Measures obtained from diffusion-weighted imaging provide objective indices of white matter development and injury in the developing preterm brain. To date, diffusion tensor imaging (DTI) has been used widely, highlighting differences in fractional anisotropy (FA) and mean diffusivity (MD) between preterm infants at term and healthy term controls; altered white matter development associated with a number of perinatal risk factors; and correlations between FA values in the white matter in the neonatal period and subsequent neurodevelopmental outcome. Recent developments, including neurite orientation dispersion and density imaging (NODDI) and fixel-based analysis (FBA), enable white matter microstructure to be assessed in detail. Constrained spherical deconvolution (CSD) enables multiple fibre populations in an imaging voxel to be resolved and allows delineation of fibres that traverse regions of fibre-crossings, such as the arcuate fasciculus and cerebellar–cortical pathways. This review summarises DTI findings in the preterm brain and discusses initial findings in this population using CSD, NODDI, and FBA.
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Affiliation(s)
- Diliana Pecheva
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Christopher Kelly
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Jessica Kimpton
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Alexandra Bonthrone
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Hui Zhang
- Department of Computer Science & Centre for Medical Image Computing, University College London, London, UK
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
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16
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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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17
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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: 134] [Impact Index Per Article: 22.3] [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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18
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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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