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Ji L, Duffy M, Chen B, Majbri A, Trentacosta CJ, Thomason M. Whole Brain MRI Assessment of Age and Sex-Related R2* Changes in the Human Fetal Brain. Hum Brain Mapp 2025; 46:e70073. [PMID: 39844450 PMCID: PMC11754245 DOI: 10.1002/hbm.70073] [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: 07/29/2024] [Revised: 10/16/2024] [Accepted: 10/28/2024] [Indexed: 01/24/2025] Open
Abstract
Iron in the brain is essential to neurodevelopmental processes, as it supports neural functions, including processes of oxygen delivery, electron transport, and enzymatic activity. However, the development of brain iron before birth is scarcely understood. By estimating R2* (1/T2*) relaxometry from a sizable sample of fetal multiecho echo-planar imaging (EPI) scans, which is the standard sequence for functional magnetic resonance imaging (fMRI), across gestation, this study investigates age and sex-related changes in iron, across regions and tissue segments. Our findings reveal that brain R2* levels significantly increase throughout gestation spanning many different regions, except the frontal lobe. Furthermore, females exhibit a faster rate of R2* increase compared to males, in both gray matter and white matter. This sex effect is particularly notable within the left insula. This work represents the first MRI examination of iron accumulation and sex differences in developing fetal brains. This is also the first study to establish R2* estimation methodology in fetal multiecho functional MRI.
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Affiliation(s)
- Lanxin Ji
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Mark Duffy
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Bosi Chen
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Amyn Majbri
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | | | - Moriah Thomason
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
- Department of Population HealthNew York University School of MedicineNew YorkNew YorkUSA
- Neuroscience InstituteNew York University School of MedicineNew YorkNew YorkUSA
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Calixto C, Taymourtash A, Karimi D, Snoussi H, Velasco-Annis C, Jaimes C, Gholipour A. Advances in Fetal Brain Imaging. Magn Reson Imaging Clin N Am 2024; 32:459-478. [PMID: 38944434 PMCID: PMC11216711 DOI: 10.1016/j.mric.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2024]
Abstract
Over the last 20 years, there have been remarkable developments in fetal brain MR imaging analysis methods. This article delves into the specifics of structural imaging, diffusion imaging, functional MR imaging, and spectroscopy, highlighting the latest advancements in motion correction, fetal brain development atlases, and the challenges and innovations. Furthermore, this article explores the clinical applications of these advanced imaging techniques in comprehending and diagnosing fetal brain development and abnormalities.
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Affiliation(s)
- Camilo Calixto
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA.
| | - Athena Taymourtash
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Spitalgasse 23, Wien 1090, Austria
| | - Davood Karimi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Haykel Snoussi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Clemente Velasco-Annis
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Camilo Jaimes
- Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA; Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02215, USA
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
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3
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Desrosiers J, Caron-Desrochers L, René A, Gaudet I, Pincivy A, Paquette N, Gallagher A. Functional connectivity development in the prenatal and neonatal stages measured by functional magnetic resonance imaging: A systematic review. Neurosci Biobehav Rev 2024; 163:105778. [PMID: 38936564 DOI: 10.1016/j.neubiorev.2024.105778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/28/2024] [Accepted: 06/17/2024] [Indexed: 06/29/2024]
Abstract
The prenatal and neonatal periods are two of the most important developmental stages of the human brain. It is therefore crucial to understand normal brain development and how early connections are established during these periods, in order to advance the state of knowledge on altered brain development and eventually identify early brain markers of neurodevelopmental disorders and diseases. In this systematic review (Prospero ID: CRD42024511365), we compiled resting state functional magnetic resonance imaging (fMRI) studies in healthy fetuses and neonates, in order to outline the main characteristics of typical development of the functional brain connectivity during the prenatal and neonatal periods. A systematic search of five databases identified a total of 12 573 articles. Of those, 28 articles met pre-established selection criteria based determined by the authors after surveying and compiling the major limitations reported within the literature. Inclusion criteria were: (1) resting state studies; (2) presentation of original results; (3) use of fMRI with minimum one Tesla; (4) a population ranging from 20 weeks of GA to term birth (around 37-42 weeks of PMA); (5) singleton pregnancy with normal development (absence of any complications known to alter brain development). Exclusion criteria were: (1) preterm studies; (2) post-mortem studies; (3) clinical or pathological studies; (4) twin studies; (5) papers with a sole focus on methodology (i.e. focused on tool and analysis development); (6) volumetric studies; (7) activation map studies; (8) cortical analysis studies; (9) conference papers. A risk of bias assessment was also done to evaluate each article's methodological rigor. 1877 participants were included across all the reviewed articles. Results consistently revealed a developmental gradient of increasing functional brain connectivity from posterior to anterior regions and from proximal-to-distal regions. A decrease in local small-world organization shortly after birth was also observed; small-world characteristics were present in fetuses and newborns, but appeared weaker in the latter group. Also, the posterior-to-anterior gradient could be associated with earlier development of the sensorimotor networks in the posterior regions while more complex higher-order networks (e.g. attention-related) mature later in the anterior regions. The main limitations of this systematic review stem from the inherent limitations of functional imaging in fetuses, mainly: unevenly distributed populations and limited sample sizes; fetal movements in the womb and other imaging obstacles; and a large voxel resolution when imaging a small brain. Another limitation specific to this review is the relatively small number of included articles compared to very a large search result, which may have led to relevant articles having been overlooked.
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Affiliation(s)
- Jérémi Desrosiers
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; School of Psychoeducation, University of Montreal, QC, Canada
| | - Laura Caron-Desrochers
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Psychology, University of Montreal, QC, Canada
| | - Andréanne René
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Psychology, University of Montreal, QC, Canada
| | - Isabelle Gaudet
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Health Sciences, Université du Québec à Chicoutimi, QC, Canada
| | - Alix Pincivy
- Sainte-Justine University Health Center and Research Center Libraries, Montreal, QC, Canada
| | - Natacha Paquette
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Psychology, University of Montreal, QC, Canada
| | - Anne Gallagher
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Psychology, University of Montreal, QC, Canada.
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4
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Wu Y, De Asis-Cruz J, Limperopoulos C. Brain structural and functional outcomes in the offspring of women experiencing psychological distress during pregnancy. Mol Psychiatry 2024; 29:2223-2240. [PMID: 38418579 PMCID: PMC11408260 DOI: 10.1038/s41380-024-02449-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 01/19/2024] [Accepted: 01/23/2024] [Indexed: 03/01/2024]
Abstract
In-utero exposure to maternal psychological distress is increasingly linked with disrupted fetal and neonatal brain development and long-term neurobehavioral dysfunction in children and adults. Elevated maternal psychological distress is associated with changes in fetal brain structure and function, including reduced hippocampal and cerebellar volumes, increased cerebral cortical gyrification and sulcal depth, decreased brain metabolites (e.g., choline and creatine levels), and disrupted functional connectivity. After birth, reduced cerebral and cerebellar gray matter volumes, increased cerebral cortical gyrification, altered amygdala and hippocampal volumes, and disturbed brain microstructure and functional connectivity have been reported in the offspring months or even years after exposure to maternal distress during pregnancy. Additionally, adverse child neurodevelopment outcomes such as cognitive, language, learning, memory, social-emotional problems, and neuropsychiatric dysfunction are being increasingly reported after prenatal exposure to maternal distress. The mechanisms by which prenatal maternal psychological distress influences early brain development include but are not limited to impaired placental function, disrupted fetal epigenetic regulation, altered microbiome and inflammation, dysregulated hypothalamic pituitary adrenal axis, altered distribution of the fetal cardiac output to the brain, and disrupted maternal sleep and appetite. This review will appraise the available literature on the brain structural and functional outcomes and neurodevelopmental outcomes in the offspring of pregnant women experiencing elevated psychological distress. In addition, it will also provide an overview of the mechanistic underpinnings of brain development changes in stress response and discuss current treatments for elevated maternal psychological distress, including pharmacotherapy (e.g., selective serotonin reuptake inhibitors) and non-pharmacotherapy (e.g., cognitive-behavior therapy). Finally, it will end with a consideration of future directions in the field.
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Affiliation(s)
- Yao Wu
- Developing Brain Institute, Children's National Hospital, Washington, DC, 20010, USA
| | | | - Catherine Limperopoulos
- Developing Brain Institute, Children's National Hospital, Washington, DC, 20010, USA.
- Department of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, 20010, USA.
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5
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Arichi T. Characterizing Large-Scale Human Circuit Development with In Vivo Neuroimaging. Cold Spring Harb Perspect Biol 2024; 16:a041496. [PMID: 38438187 PMCID: PMC11146311 DOI: 10.1101/cshperspect.a041496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Large-scale coordinated patterns of neural activity are crucial for the integration of information in the human brain and to enable complex and flexible human behavior across the life span. Through recent advances in noninvasive functional magnetic resonance imaging (fMRI) methods, it is now possible to study this activity and how it emerges in the living fetal brain across the second half of human gestation. This work has demonstrated that functional activity in the fetal brain has several features in keeping with highly organized networks of activity, which are undergoing a highly programmed and rapid sequence of development before birth, in which long-range connections emerge and core features of the mature functional connectome (such as hub regions and a gradient organization) are established. In this review, the findings of these studies are summarized, their relationship to the known changes in developmental neurobiology is considered, and considerations for future work in the context of limitations to the fMRI approach are presented.
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Affiliation(s)
- Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, New Hunt's House, Guy's Campus, London SE1 1UL, United Kingdom
- Children's Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London SE1 7EH, United Kingdom
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6
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Karolis VR, Fitzgibbon SP, Cordero-Grande L, Farahibozorg SR, Price AN, Hughes EJ, Fetit AE, Kyriakopoulou V, Pietsch M, Rutherford MA, Rueckert D, Hajnal JV, Edwards AD, O'Muircheartaigh J, Duff EP, Arichi T. Maturational networks of human fetal brain activity reveal emerging connectivity patterns prior to ex-utero exposure. Commun Biol 2023; 6:661. [PMID: 37349403 PMCID: PMC10287667 DOI: 10.1038/s42003-023-04969-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 05/23/2023] [Indexed: 06/24/2023] Open
Abstract
A key feature of the fetal period is the rapid emergence of organised patterns of spontaneous brain activity. However, characterising this process in utero using functional MRI is inherently challenging and requires analytical methods which can capture the constituent developmental transformations. Here, we introduce a novel analytical framework, termed "maturational networks" (matnets), that achieves this by modelling functional networks as an emerging property of the developing brain. Compared to standard network analysis methods that assume consistent patterns of connectivity across development, our method incorporates age-related changes in connectivity directly into network estimation. We test its performance in a large neonatal sample, finding that the matnets approach characterises adult-like features of functional network architecture with a greater specificity than a standard group-ICA approach; for example, our approach is able to identify a nearly complete default mode network. In the in-utero brain, matnets enables us to reveal the richness of emerging functional connections and the hierarchy of their maturational relationships with remarkable anatomical specificity. We show that the associative areas play a central role within prenatal functional architecture, therefore indicating that functional connections of high-level associative areas start emerging prior to exposure to the extra-utero environment.
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Affiliation(s)
- Vyacheslav R Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Sean P Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Lucilio Cordero-Grande
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid & CIBER-BBN, Madrid, Spain
| | - Seyedeh-Rezvan Farahibozorg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Emer J Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Ahmed E Fetit
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK
- UKRI CDT in Artificial Intelligence for Healthcare, Department of Computing, Imperial College London, London, UK
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Maximilian Pietsch
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK
- Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Eugene P Duff
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
- Paediatric Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK
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7
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De Asis-Cruz J, Limperopoulos C. Harnessing the Power of Advanced Fetal Neuroimaging to Understand In Utero Footprints for Later Neuropsychiatric Disorders. Biol Psychiatry 2022; 93:867-879. [PMID: 36804195 DOI: 10.1016/j.biopsych.2022.11.019] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 11/03/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022]
Abstract
Adverse intrauterine events may profoundly impact fetal risk for future adult diseases. The mechanisms underlying this increased vulnerability are complex and remain poorly understood. Contemporary advances in fetal magnetic resonance imaging (MRI) have provided clinicians and scientists with unprecedented access to in vivo human fetal brain development to begin to identify emerging endophenotypes of neuropsychiatric disorders such as autism spectrum disorder, attention-deficit/hyperactivity disorder, and schizophrenia. In this review, we discuss salient findings of normal fetal neurodevelopment from studies using advanced, multimodal MRI that have provided unparalleled characterization of in utero prenatal brain morphology, metabolism, microstructure, and functional connectivity. We appraise the clinical utility of these normative data in identifying high-risk fetuses before birth. We highlight available studies that have investigated the predictive validity of advanced prenatal brain MRI findings and long-term neurodevelopmental outcomes. We then discuss how ex utero quantitative MRI findings can inform in utero investigations toward the pursuit of early biomarkers of risk. Lastly, we explore future opportunities to advance our understanding of the prenatal origins of neuropsychiatric disorders using precision fetal imaging.
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RS-FetMRI: a MATLAB-SPM Based Tool for Pre-processing Fetal Resting-State fMRI Data. Neuroinformatics 2022; 20:1137-1154. [PMID: 35834105 DOI: 10.1007/s12021-022-09592-5] [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] [Accepted: 05/25/2022] [Indexed: 12/31/2022]
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) most recently has proved to open a measureless window on functional neurodevelopment in utero. Fetal brain activation and connectivity maps can be heavily influenced by 1) fetal-specific motion effects on the time-series and 2) the accuracy of time-series spatial normalization to a standardized gestational-week (GW) specific fetal template space.Due to the absence of a standardized and generalizable image processing protocol, the objective of the present work was to implement a validated fetal rs-fMRI preprocessing pipeline (RS-FetMRI) divided into 6 inter-dependent preprocessing modules (i.e., M1 to M6) and designed to work entirely as an extension for Statistical Parametric Mapping (SPM).RS-FetMRI pipeline output analyses on rs-fMRI time-series sampled from a cohort of fetuses acquired on both 1.5 T and 3 T MRI scanning systems showed increased efficacy of estimation of the degree of movement coupled with an efficient motion censoring procedure, resulting in increased number of motion-uncorrupted volumes and temporal continuity in fetal rs-fMRI time-series data. Moreover, a "structural-free" SPM-based spatial normalization procedure granted a high degree of spatial overlap with high reproducibility and a significant improvement in whole-brain and parcellation-specific Temporal Signal-to-Noise Ratio (TSNR) mirrored by functional connectivity analysis.To our knowledge, the RS-FetMRI pipeline is the first semi-automatic and easy-to-use standardized fetal rs-fMRI preprocessing pipeline completely integrated in MATLAB-SPM able to remove entry barriers for new research groups into the field of fetal rs-fMRI, for both research or clinical purposes, and ultimately to make future fetal brain connectivity investigations more suitable for comparison and cross-validation.
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9
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Colenbier N, Marino M, Arcara G, Frederick B, Pellegrino G, Marinazzo D, Ferrazzi G. WHOCARES: WHOle-brain CArdiac signal REgression from highly accelerated simultaneous multi-Slice fMRI acquisitions. J Neural Eng 2022; 19:10.1088/1741-2552/ac8bff. [PMID: 35998568 PMCID: PMC9673276 DOI: 10.1088/1741-2552/ac8bff] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 08/23/2022] [Indexed: 11/12/2022]
Abstract
Objective. To spatio-temporally resolve cardiac signals in functional magnetic resonance imaging (fMRI) time-series of the human brain using neither external physiological measurements nor ad hoc modelling assumptions.Approach. Cardiac pulsation is a physiological confound of fMRI time-series that introduces spurious signal fluctuations in proximity to blood vessels. fMRI alone is not sufficiently fast to resolve cardiac pulsation. Depending on the ratio between the instantaneous heart-rate and the acquisition sampling frequency (1/TR, with TR being the repetition time), the cardiac signal may alias into the frequency band of neural activation so that its removal through spectral filtering techniques is generally not possible. In this paper, we show that it is feasible to temporally and spatially resolve cardiac signals throughout the brain even when cardiac aliasing occurs by combining fMRI hyper-sampling with simultaneous multislice (SMS) imaging. The technique, which we name WHOle-brain CArdiac signal REgression from highly accelerated simultaneous multi-Slice fMRI acquisitions (WHOCARES), was developed on 695 healthy subjects selected from the Human Connectome Project and its performance validated against the RETROICOR, HAPPY and the pulse oxymeter signal regression methods.Main results.WHOCARES is capable of retrieving voxel-wise cardiac signal regressors. This is achieved without employing external physiological recordings nor through ad hoc modelling assumptions. The performance of WHOCARES was, on average, superior to RETROICOR, HAPPY and the pulse oxymeter regression methods.Significance.WHOCARES holds basis for the reliable mapping of cardiac activity in fMRI time-series. WHOCARES can be employed for the retrospective removal of cardiac noise in publicly available fMRI datasets where physiological recordings are not available. WHOCARES is freely available athttps://github.com/gferrazzi/WHOCARES.
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Affiliation(s)
- Nigel Colenbier
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
| | - Marco Marino
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, 3001, Belgium
| | - Giorgio Arcara
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
| | - Blaise Frederick
- Brain Imaging Center, McLean Hospital, 115 Mill St., Belmont, MA, 02478, USA
- Department of Psychiatry, Harvard University Medical School, 25 Shattuck St., Boston, MA, 02115, USA
| | | | - Daniele Marinazzo
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium
| | - Giulio Ferrazzi
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
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10
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Ji L, Hendrix CL, Thomason ME. Empirical evaluation of human fetal fMRI preprocessing steps. Netw Neurosci 2022; 6:702-721. [PMID: 36204420 PMCID: PMC9531599 DOI: 10.1162/netn_a_00254] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 05/09/2022] [Indexed: 11/04/2022] Open
Abstract
Increased study and methodological innovation have led to growth in the field of fetal brain fMRI. An important gap yet to be addressed is optimization of fetal fMRI preprocessing. Rapid developmental changes, imaged within the maternal compartment using an abdominal coil, introduce novel constraints that challenge established methods used in adult fMRI. This study evaluates the impact of (1) normalization to a group mean-age template versus normalization to an age-matched template; (2) independent components analysis (ICA) denoising at two criterion thresholds; and (3) smoothing using three kernel sizes. Data were collected from 121 fetuses (25-39 weeks, 43.8% female). Results indicate that the mean age template is superior in older fetuses, but less optimal in younger fetuses. ICA denoising at a more stringent threshold is superior to less stringent denoising. A larger smoothing kernel can enhance cross-hemisphere functional connectivity. Overall, this study provides improved understanding of the impact of specific steps on fetal image quality. Findings can be used to inform a common set of best practices for fetal fMRI preprocessing.
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Affiliation(s)
- Lanxin Ji
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
| | - Cassandra L. Hendrix
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
| | - Moriah E. Thomason
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
- Department of Population Health, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
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11
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Sobotka D, Ebner M, Schwartz E, Nenning KH, Taymourtash A, Vercauteren T, Ourselin S, Kasprian G, Prayer D, Langs G, Licandro R. Motion correction and volumetric reconstruction for fetal functional magnetic resonance imaging data. Neuroimage 2022; 255:119213. [PMID: 35430359 DOI: 10.1016/j.neuroimage.2022.119213] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 03/21/2022] [Accepted: 04/13/2022] [Indexed: 10/18/2022] Open
Abstract
Motion correction is an essential preprocessing step in functional Magnetic Resonance Imaging (fMRI) of the fetal brain with the aim to remove artifacts caused by fetal movement and maternal breathing and consequently to suppress erroneous signal correlations. Current motion correction approaches for fetal fMRI choose a single 3D volume from a specific acquisition timepoint with least motion artefacts as reference volume, and perform interpolation for the reconstruction of the motion corrected time series. The results can suffer, if no low-motion frame is available, and if reconstruction does not exploit any assumptions about the continuity of the fMRI signal. Here, we propose a novel framework, which estimates a high-resolution reference volume by using outlier-robust motion correction, and by utilizing Huber L2 regularization for intra-stack volumetric reconstruction of the motion-corrected fetal brain fMRI. We performed an extensive parameter study to investigate the effectiveness of motion estimation and present in this work benchmark metrics to quantify the effect of motion correction and regularised volumetric reconstruction approaches on functional connectivity computations. We demonstrate the proposed framework's ability to improve functional connectivity estimates, reproducibility and signal interpretability, which is clinically highly desirable for the establishment of prognostic noninvasive imaging biomarkers. The motion correction and volumetric reconstruction framework is made available as an open-source package of NiftyMIC.
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Affiliation(s)
- Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michael Ebner
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Ernst Schwartz
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Karl-Heinz Nenning
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
| | - Athena Taymourtash
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Tom Vercauteren
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Gregor Kasprian
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Daniela Prayer
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
| | - Roxane Licandro
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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12
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Early magnetic resonance imaging biomarkers of schizophrenia spectrum disorders: Toward a fetal imaging perspective. Dev Psychopathol 2021; 33:899-913. [PMID: 32489161 DOI: 10.1017/s0954579420000218] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
There is mounting evidence to implicate the intrauterine environment as the initial pathogenic stage for neuropsychiatric disease. Recent developments in magnetic resonance imaging technology are making a multimodal analysis of the fetal central nervous system a reality, allowing analysis of structural and functional parameters. Exposures to a range of pertinent risk factors whether preconception or in utero can now be indexed using imaging techniques within the fetus' physiological environment. This approach may determine the first "hit" required for diseases that do not become clinically manifest until adulthood, and which only have subtle clinical markers during childhood and adolescence. A robust characterization of a "multi-hit" hypothesis may necessitate a longitudinal birth cohort; within this investigative paradigm, the full range of genetic and environmental risk factors can be assessed for their impact on the early developing brain. This will lay the foundation for the identification of novel biomarkers and the ability to devise methods for early risk stratification and disease prevention. However, these early markers must be followed over time: first, to account for neural plasticity, and second, to assess the effects of postnatal exposures that continue to drive the individual toward disease. We explore these issues using the schizophrenia spectrum disorders as an illustrative paradigm. However, given the potential richness of fetal magnetic resonance imaging, and the likely overlap of biomarkers, these concepts may extend to a range of neuropsychiatric conditions.
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13
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The Fetal Functional Connectome Offers Clues for Early Maturing Networks and Implications for Neurodevelopmental Disorders. J Neurosci 2020; 40:4436-4438. [PMID: 32493796 DOI: 10.1523/jneurosci.0260-20.2020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 04/18/2020] [Accepted: 04/21/2020] [Indexed: 11/21/2022] Open
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14
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Thomas MSC, Ojinaga Alfageme O, D'Souza H, Patkee PA, Rutherford MA, Mok KY, Hardy J, Karmiloff-Smith A. A multi-level developmental approach to exploring individual differences in Down syndrome: genes, brain, behaviour, and environment. RESEARCH IN DEVELOPMENTAL DISABILITIES 2020; 104:103638. [PMID: 32653761 PMCID: PMC7438975 DOI: 10.1016/j.ridd.2020.103638] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 03/18/2020] [Accepted: 03/20/2020] [Indexed: 05/06/2023]
Abstract
In this article, we focus on the causes of individual differences in Down syndrome (DS), exemplifying the multi-level, multi-method, lifespan developmental approach advocated by Karmiloff-Smith (1998, 2009, 2012, 2016). We evaluate the possibility of linking variations in infant and child development with variations in the (elevated) risk for Alzheimer's disease (AD) in adults with DS. We review the theoretical basis for this argument, considering genetics, epigenetics, brain, behaviour and environment. In studies 1 and 2, we focus on variation in language development. We utilise data from the MacArthur-Bates Communicative Development Inventories (CDI; Fenson et al., 2007), and Mullen Scales of Early Learning (MSEL) receptive and productive language subscales (Mullen, 1995) from 84 infants and children with DS (mean age 2;3, range 0;7 to 5;3). As expected, there was developmental delay in both receptive and expressive vocabulary and wide individual differences. Study 1 examined the influence of an environmental measure (socio-economic status as measured by parental occupation) on the observed variability. SES did not predict a reliable amount of the variation. Study 2 examined the predictive power of a specific genetic measure (apolipoprotein APOE genotype) which modulates risk for AD in adulthood. There was no reliable effect of APOE genotype, though weak evidence that development was faster for the genotype conferring greater AD risk (ε4 carriers), consistent with recent observations in infant attention (D'Souza, Mason et al., 2020). Study 3 considered the concerted effect of the DS genotype on early brain development. We describe new magnetic resonance imaging methods for measuring prenatal and neonatal brain structure in DS (e.g., volumes of supratentorial brain, cortex, cerebellar volume; Patkee et al., 2019). We establish the methodological viability of linking differences in early brain structure to measures of infant cognitive development, measured by the MSEL, as a potential early marker of clinical relevance. Five case studies are presented as proof of concept, but these are as yet too few to discern a pattern.
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Affiliation(s)
- Michael S C Thomas
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London WC1E 7HX, United Kingdom.
| | - Olatz Ojinaga Alfageme
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London WC1E 7HX, United Kingdom; Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas's Hospital, London, SE1 7EH, United Kingdom
| | - Hana D'Souza
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London WC1E 7HX, United Kingdom; Department of Psychology & Newnham College, University of Cambridge, Cambridge CB3 9DF, United Kingdom
| | - Prachi A Patkee
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas's Hospital, London, SE1 7EH, United Kingdom
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas's Hospital, London, SE1 7EH, United Kingdom
| | - Kin Y Mok
- Department of Neurodegenerative Disease, Institute of Neurology, University College London, United Kingdom
| | - John Hardy
- Department of Neurodegenerative Disease, Institute of Neurology, University College London, United Kingdom
| | - Annette Karmiloff-Smith
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London WC1E 7HX, United Kingdom
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15
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Deprez M, Price A, Christiaens D, Lockwood Estrin G, Cordero-Grande L, Hutter J, Daducci A, Tournier JD, Rutherford M, Counsell SJ, Cuadra MB, Hajnal JV. Higher Order Spherical Harmonics Reconstruction of Fetal Diffusion MRI With Intensity Correction. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:1104-1113. [PMID: 31562073 DOI: 10.1109/tmi.2019.2943565] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
We present a novel method for higher order reconstruction of fetal diffusion MRI signal that enables detection of fiber crossings. We combine data-driven motion and intensity correction with super-resolution reconstruction and spherical harmonic parametrisation to reconstruct data scattered in both spatial and angular domains into consistent fetal dMRI signal suitable for further diffusion analysis. We show that intensity correction is essential for good performance of the method and identify anatomically plausible fiber crossings. The proposed methodology has potential to facilitate detailed investigation of developing brain connectivity and microstructure in-utero.
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16
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Andescavage N, You W, Jacobs M, Kapse K, Quistorff J, Bulas D, Ahmadzia H, Gimovsky A, Baschat A, Limperopoulos C. Exploring in vivo placental microstructure in healthy and growth-restricted pregnancies through diffusion-weighted magnetic resonance imaging. Placenta 2020; 93:113-118. [PMID: 32250735 PMCID: PMC7153576 DOI: 10.1016/j.placenta.2020.03.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 02/19/2020] [Accepted: 03/05/2020] [Indexed: 02/07/2023]
Abstract
INTRODUCTION Gross and microstructural changes in placental development can influence placental function and adversely impact fetal growth and well-being; however, there is a paucity of invivo tools available to reliably interrogate in vivo placental microstructural development. The objective of this study is to characterize invivo placental microstructural diffusion and perfusion in healthy and growth-restricted pregnancies (FGR) using non-invasive diffusion-weighted imaging (DWI). METHODS We prospectively enrolled healthy pregnant women and women whose pregnancies were complicated by FGR. Each woman underwent DWI-MRI between 18 and 40 weeks gestation. Placental measures of small (D) and large (D*) scale diffusion and perfusion (f) were estimated using the intra-voxel incoherent motion (IVIM) model. RESULTS We studied 137 pregnant women (101 healthy; 36 FGR). D and D* are increased in late-onset FGR, and the placental perfusion fraction, f, is decreased (p < 0.05 for all). DISCUSSION Placental DWI revealed microstructural alterations of the invivo placenta in FGR, particularly in late-onset FGR. Early and reliable identification of placental pathology in vivo may better guide future interventions.
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Affiliation(s)
- Nickie Andescavage
- Division of Neonatology, Children's National Hospital, 111 Michigan Ave, NW, Washington, DC, 20010, USA; Department of Pediatrics, George Washington University School of Medicine, 2300 Eye St. NW, Washington, DC, 20052, USA
| | - Wonsang You
- Division of Diagnostic Imaging & Radiology, Children's National Hospital, 111 Michigan Ave, NW, Washington, DC, 20010, USA
| | - Marni Jacobs
- Division of Biostatistics & Study Methodology, George Washington University School of Medicine, 2300 Eye St. NW, Washington, DC, 20052, USA; Department of Pediatrics, George Washington University School of Medicine, 2300 Eye St. NW, Washington, DC, 20052, USA
| | - Kushal Kapse
- Division of Diagnostic Imaging & Radiology, Children's National Hospital, 111 Michigan Ave, NW, Washington, DC, 20010, USA
| | - Jessica Quistorff
- Division of Diagnostic Imaging & Radiology, Children's National Hospital, 111 Michigan Ave, NW, Washington, DC, 20010, USA
| | - Dorothy Bulas
- Division of Diagnostic Imaging & Radiology, Children's National Hospital, 111 Michigan Ave, NW, Washington, DC, 20010, USA; Department of Radiology, George Washington University School of Medicine, 2300 Eye St. NW, Washington, DC, 20052, USA
| | - Homa Ahmadzia
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, George Washington University School of Medicine, 2300 Eye St. NW, Washington, DC, 20052, USA
| | - Alexis Gimovsky
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, George Washington University School of Medicine, 2300 Eye St. NW, Washington, DC, 20052, USA
| | - Ahmet Baschat
- Department of Gynecology and Obstetrics, Johns Hopkins Center for Fetal Therapy, 600 North Wolfe Street, Nelson 228, Baltimore, MD, 21287, USA
| | - Catherine Limperopoulos
- Division of Diagnostic Imaging & Radiology, Children's National Hospital, 111 Michigan Ave, NW, Washington, DC, 20010, USA; Department of Pediatrics, George Washington University School of Medicine, 2300 Eye St. NW, Washington, DC, 20052, USA; Department of Radiology, George Washington University School of Medicine, 2300 Eye St. NW, Washington, DC, 20052, USA.
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Abstract
Developmental pathoconnectomics is an emerging field that aims to unravel the events leading to and outcome from disrupted brain connectivity development. Advanced magnetic resonance imaging (MRI) technology enables the portrayal of human brain connectivity before birth and has the potential to offer novel insights into normal and pathological human brain development. This review gives an overview of the currently used MRI techniques for connectomic imaging, with a particular focus on recent studies that have successfully translated these to the in utero or postmortem fetal setting. Possible mechanisms of how pathologies, maternal, or environmental factors may interfere with the emergence of the connectome are considered. The review highlights the importance of advanced image post processing and the need for reproducibility studies for connectomic imaging. Further work and novel data-sharing efforts would be required to validate or disprove recent observations from in utero connectomic studies, which are typically limited by low case numbers and high data drop out. Novel knowledge with regard to the ontogenesis, architecture, and temporal dynamics of the human brain connectome would lead to the more precise understanding of the etiological background of neurodevelopmental and mental disorders. To achieve this goal, this review considers the growing evidence from advanced fetal connectomic imaging for the increased vulnerability of the human brain during late gestation for pathologies that might lead to impaired connectome development and subsequently interfere with the development of neural substrates serving higher cognition.
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18
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Functional Connectome of the Fetal Brain. J Neurosci 2019; 39:9716-9724. [PMID: 31685648 PMCID: PMC6891066 DOI: 10.1523/jneurosci.2891-18.2019] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 08/22/2019] [Accepted: 10/01/2019] [Indexed: 01/05/2023] Open
Abstract
Large-scale functional connectome formation and reorganization is apparent in the second trimester of pregnancy, making it a crucial and vulnerable time window in connectome development. Here we identified which architectural principles of functional connectome organization are initiated before birth, and contrast those with topological characteristics observed in the mature adult brain. A sample of 105 pregnant women participated in human fetal resting-state fMRI studies (fetal gestational age between 20 and 40 weeks). Connectome analysis was used to analyze weighted network characteristics of fetal macroscale brain wiring. We identified efficient network attributes, common functional modules, and high overlap between the fetal and adult brain network. Our results indicate that key features of the functional connectome are present in the second and third trimesters of pregnancy. Understanding the organizational principles of fetal connectome organization may bring opportunities to develop markers for early detection of alterations of brain function.SIGNIFICANCE STATEMENT The fetal to neonatal period is well known as a critical stage in brain development. Rapid neurodevelopmental processes establish key functional neural circuits of the human brain. Prenatal risk factors may interfere with early trajectories of connectome formation and thereby shape future health outcomes. Recent advances in MRI have made it possible to examine fetal brain functional connectivity. In this study, we evaluate the network topography of normative functional network development during connectome genesis in utero Understanding the developmental trajectory of brain connectivity provides a basis for understanding how the prenatal period shapes future brain function and disease dysfunction.
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Afacan O, Estroff JA, Yang E, Barnewolt CE, Connolly SA, Parad RB, Mulkern RV, Warfield SK, Gholipour A. Fetal Echoplanar Imaging: Promises and Challenges. Top Magn Reson Imaging 2019; 28:245-254. [PMID: 31592991 PMCID: PMC6788763 DOI: 10.1097/rmr.0000000000000219] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Fetal magnetic resonance imaging (MRI) has been gaining increasing interest in both clinical radiology and research. Echoplanar imaging (EPI) offers a unique potential, as it can be used to acquire images very fast. It can be used to freeze motion, or to get multiple images with various contrast mechanisms that allow studying the microstructure and function of the fetal brain and body organs. In this article, we discuss the current clinical and research applications of fetal EPI. This includes T2*-weighted imaging to better identify blood products and vessels, using diffusion-weighted MRI to investigate connections of the developing brain and using functional MRI (fMRI) to identify the functional networks of the developing brain. EPI can also be used as an alternative structural sequence when banding or standing wave artifacts adversely affect the mainstream sequences used routinely in structural fetal MRI. We also discuss the challenges with EPI acquisitions, and potential solutions. As EPI acquisitions are inherently sensitive to susceptibility artifacts, geometric distortions limit the use of high-resolution EPI acquisitions. Also, interslice motion and transmit and receive field inhomogeneities may create significant artifacts in fetal EPI. We conclude by discussing promising research directions to overcome these challenges to improve the use of EPI in clinical and research applications.
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Affiliation(s)
- Onur Afacan
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Judy A. Estroff
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Edward Yang
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Carol E. Barnewolt
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Susan A. Connolly
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Richard B. Parad
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- Department of Pediatric Newborn Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Robert V. Mulkern
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Simon K. Warfield
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Ali Gholipour
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
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20
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Baburamani AA, Patkee PA, Arichi T, Rutherford MA. New approaches to studying early brain development in Down syndrome. Dev Med Child Neurol 2019; 61:867-879. [PMID: 31102269 PMCID: PMC6618001 DOI: 10.1111/dmcn.14260] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/28/2019] [Indexed: 12/19/2022]
Abstract
Down syndrome is the most common genetic developmental disorder in humans and is caused by partial or complete triplication of human chromosome 21 (trisomy 21). It is a complex condition which results in multiple lifelong health problems, including varying degrees of intellectual disability and delays in speech, memory, and learning. As both length and quality of life are improving for individuals with Down syndrome, attention is now being directed to understanding and potentially treating the associated cognitive difficulties and their underlying biological substrates. These have included imaging and postmortem studies which have identified decreased regional brain volumes and histological anomalies that accompany early onset dementia. In addition, advances in genome-wide analysis and Down syndrome mouse models are providing valuable insight into potential targets for intervention that could improve neurogenesis and long-term cognition. As little is known about early brain development in human Down syndrome, we review recent advances in magnetic resonance imaging that allow non-invasive visualization of brain macro- and microstructure, even in utero. It is hoped that together these advances may enable Down syndrome to become one of the first genetic disorders to be targeted by antenatal treatments designed to 'normalize' brain development. WHAT THIS PAPER ADDS: Magnetic resonance imaging can provide non-invasive characterization of early brain development in Down syndrome. Down syndrome mouse models enable study of underlying pathology and potential intervention strategies. Potential therapies could modify brain structure and improve early cognitive levels. Down syndrome may be the first genetic disorder to have targeted therapies which alter antenatal brain development.
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Affiliation(s)
- Ana A Baburamani
- Centre for the Developing BrainDepartment of Perinatal Imaging and HealthSchool of Biomedical Engineering & Imaging SciencesKing's College LondonKing's Health PartnersSt Thomas’ HospitalLondonUK
| | - Prachi A Patkee
- Centre for the Developing BrainDepartment of Perinatal Imaging and HealthSchool of Biomedical Engineering & Imaging SciencesKing's College LondonKing's Health PartnersSt Thomas’ HospitalLondonUK
| | - Tomoki Arichi
- Centre for the Developing BrainDepartment of Perinatal Imaging and HealthSchool of Biomedical Engineering & Imaging SciencesKing's College LondonKing's Health PartnersSt Thomas’ HospitalLondonUK,Department of BioengineeringImperial College LondonLondonUK,Children's NeurosciencesEvelina London Children's HospitalLondonUK
| | - Mary A Rutherford
- Centre for the Developing BrainDepartment of Perinatal Imaging and HealthSchool of Biomedical Engineering & Imaging SciencesKing's College LondonKing's Health PartnersSt Thomas’ HospitalLondonUK
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21
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Vasung L, Abaci Turk E, Ferradal SL, Sutin J, Stout JN, Ahtam B, Lin PY, Grant PE. Exploring early human brain development with structural and physiological neuroimaging. Neuroimage 2019; 187:226-254. [PMID: 30041061 PMCID: PMC6537870 DOI: 10.1016/j.neuroimage.2018.07.041] [Citation(s) in RCA: 98] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 07/16/2018] [Accepted: 07/16/2018] [Indexed: 12/11/2022] Open
Abstract
Early brain development, from the embryonic period to infancy, is characterized by rapid structural and functional changes. These changes can be studied using structural and physiological neuroimaging methods. In order to optimally acquire and accurately interpret this data, concepts from adult neuroimaging cannot be directly transferred. Instead, one must have a basic understanding of fetal and neonatal structural and physiological brain development, and the important modulators of this process. Here, we first review the major developmental milestones of transient cerebral structures and structural connectivity (axonal connectivity) followed by a summary of the contributions from ex vivo and in vivo MRI. Next, we discuss the basic biology of neuronal circuitry development (synaptic connectivity, i.e. ensemble of direct chemical and electrical connections between neurons), physiology of neurovascular coupling, baseline metabolic needs of the fetus and the infant, and functional connectivity (defined as statistical dependence of low-frequency spontaneous fluctuations seen with functional magnetic resonance imaging (fMRI)). The complementary roles of magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS) are discussed. We include a section on modulators of brain development where we focus on the placenta and emerging placental MRI approaches. In each section we discuss key technical limitations of the imaging modalities and some of the limitations arising due to the biology of the system. Although neuroimaging approaches have contributed significantly to our understanding of early brain development, there is much yet to be done and a dire need for technical innovations and scientific discoveries to realize the future potential of early fetal and infant interventions to avert long term disease.
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Affiliation(s)
- Lana Vasung
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Esra Abaci Turk
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Silvina L Ferradal
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Jason Sutin
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Jeffrey N Stout
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Banu Ahtam
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Pei-Yi Lin
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
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22
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Graph theoretical modeling of baby brain networks. Neuroimage 2019; 185:711-727. [DOI: 10.1016/j.neuroimage.2018.06.038] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Revised: 05/22/2018] [Accepted: 06/11/2018] [Indexed: 11/20/2022] Open
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23
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Gaspar AS, Nunes RG, Ferrazzi G, Hughes EJ, Hutter J, Malik SJ, McCabe L, Baruteau KP, Rutherford MA, Hajnal JV, Price AN. Optimizing maternal fat suppression with constrained image-based shimming in fetal MR. Magn Reson Med 2019; 81:477-485. [PMID: 30058204 PMCID: PMC6282825 DOI: 10.1002/mrm.27375] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 05/02/2018] [Accepted: 05/03/2018] [Indexed: 12/21/2022]
Abstract
PURPOSE Echo planar imaging (EPI) is the primary sequence for functional and diffusion MRI. In fetal applications, the large field of view needed to encode the maternal abdomen leads to prolonged EPI readouts, which may be further extended due to safety considerations that limit gradient performance. The resulting images become very sensitive to water-fat shift and susceptibility artefacts. The purpose of this study was to reduce artefacts and increase stability of EPI in fetal brain imaging, balancing local field homogeneity across the fetal brain with longer range variations to ensure compatibility with fat suppression of the maternal abdomen. METHODS Spectral Pre-saturation with Inversion-Recovery (SPIR) fat suppression was optimized by investigating SPIR pulse frequency offsets. Subsequently, fetal brain EPI data were acquired using image-based (IB) shimming on 6 pregnant women by (1) minimizing B0 field variations within the fetal brain (localized IB shimming) and (2) with added constraint to limit B0 variation in maternal fat (fat constrained IB shimming). RESULTS The optimal offset for the SPIR pulse at 3 Tesla was 550 Hz. Both shimming approaches had similar performances in terms of B0 homogeneity within the brain, but constrained IB shimming enabled higher fat suppression efficiency. CONCLUSION Optimized SPIR in combination with constrained IB shimming can improve maternal fat suppression while minimizing EPI distortions in the fetal brain.
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Affiliation(s)
- Andreia S. Gaspar
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
- Institute for Systems and Robotics/Department of Bioengineering, Instituto Superior TécnicoUniversidade de LisboaLisbonPortugal
- Instituto de Biofísica e Engenharia BiomédicaFaculdade de Ciências da Universidade de LisboaCampo GrandeLisbonPortugal
| | - Rita G. Nunes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
- Institute for Systems and Robotics/Department of Bioengineering, Instituto Superior TécnicoUniversidade de LisboaLisbonPortugal
- Instituto de Biofísica e Engenharia BiomédicaFaculdade de Ciências da Universidade de LisboaCampo GrandeLisbonPortugal
| | - Giulio Ferrazzi
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
| | - Emer J. Hughes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
| | - Shaihan J. Malik
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
| | - Laura McCabe
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
| | - Kelly P. Baruteau
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUnited Kingdom
| | - Mary A. Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
| | - Joseph V. Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
| | - Anthony N. Price
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUnited Kingdom
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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: 2.2] [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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Hong CCH, Fallon JH, Friston KJ, Harris JC. Rapid Eye Movements in Sleep Furnish a Unique Probe Into Consciousness. Front Psychol 2018; 9:2087. [PMID: 30429814 PMCID: PMC6220670 DOI: 10.3389/fpsyg.2018.02087] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 10/10/2018] [Indexed: 01/07/2023] Open
Abstract
The neural correlates of rapid eye movements (REMs) in sleep are extraordinarily robust; including REM-locked multisensory-motor integration and accompanying activation in the retrosplenial cortex, the supplementary eye field and areas encompassing cholinergic basal nucleus (Hong et al., 2009). The phenomenology of REMs speaks to the notion that perceptual experience in both sleep and wakefulness is a constructive process - in which we generate predictions of sensory inputs and then test those predictions through actively sampling the sensorium with eye movements. On this view, REMs during sleep may index an internalized active sampling or 'scanning' of self-generated visual constructs that are released from the constraints of visual input. If this view is correct, it renders REMs an ideal probe to study consciousness as "an exclusively internal affair" (Metzinger, 2009). In other words, REMs offer a probe of active inference - in the sense of predictive coding - when the brain is isolated from the sensorium in virtue of the natural blockade of sensory afferents during REM sleep. Crucially, REMs are temporally precise events that enable powerful inferences based on time series analyses. As a natural, task-free probe, (REMs) could be used in non-compliant subjects, including infants and animals. In short, REMs constitute a promising probe to study the ontogenetic and phylogenetic development of consciousness and perhaps the psychopathology of schizophrenia and autism, which have been considered in terms of aberrant predictive coding.
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Affiliation(s)
- Charles C.-H. Hong
- Patuxent Institution, Correctional Mental Health Center — Jessup, Jessup, MD, United States
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins Hospital, Baltimore, MD, United States
| | - James H. Fallon
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA, United States
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States
| | - Karl J. Friston
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom
| | - James C. Harris
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins Hospital, Baltimore, MD, United States
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Jarvis DA, Griffiths PD. Current state of MRI of the fetal brain in utero. J Magn Reson Imaging 2018; 49:632-646. [PMID: 30353990 DOI: 10.1002/jmri.26316] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 08/10/2018] [Accepted: 08/10/2018] [Indexed: 12/25/2022] Open
Abstract
In this article we provide an overview of fetal brain development, describe the range of more common fetal neuropathology, and discuss the relevance of in utero MR (iuMR). Although ultrasonography remains the mainstay of fetal brain imaging, iuMR imaging is both feasible and safe, but presents several challenges. We discuss those challenges, the techniques employed to overcome them, and new approaches that may extend the clinical applicability of fetal iuMR. Level of Evidence: Technical Efficacy Stage. J. Magn. Reson. Imaging 2019;49:632-646.
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Affiliation(s)
- Deborah A Jarvis
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Paul D Griffiths
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
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Hayat TTA, Rutherford MA. Neuroimaging perspectives on fetal motor behavior. Neurosci Biobehav Rev 2018; 92:390-401. [PMID: 29886176 DOI: 10.1016/j.neubiorev.2018.06.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 05/22/2018] [Accepted: 06/01/2018] [Indexed: 12/19/2022]
Abstract
We are entering a new era of understanding human development with the ability to perform studies at the earliest time points possible. There is a substantial body of evidence to support the concept that early motor behaviour originates from supraspinal motor centres, reflects neurological integrity, and that altered patterns of behaviour precede clinical manifestation of disease. Cine Magnetic Resonance Imaging (cineMRI) has established its value as a novel method to visualise motor behaviour in the human fetus, building on the wealth of knowledge gleaned from ultrasound based studies. This paper presents a state of the art review incorporating findings from human and preclinical models, the insights from which, we propose, can proceed a reconceptualisation of fetal motor behaviour using advanced imaging techniques. Foremost is the need to better understand the role of the intrauterine environment, and its inherent unique set of stimuli that activate sensorimotor pathways and shape early brain development. Finally, an improved model of early motor development, combined with multimodal imaging, will provide a novel source of in utero biomarkers predictive of neurodevelopmental disorders.
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Affiliation(s)
- Tayyib T A Hayat
- Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
| | - Mary A Rutherford
- Centre for the Developing Brain, Perinatal Imaging & Health, Imaging Sciences & Biomedical Engineering Division, King's College London, London, United Kingdom
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Pinsard B, Boutin A, Doyon J, Benali H. Integrated fMRI Preprocessing Framework Using Extended Kalman Filter for Estimation of Slice-Wise Motion. Front Neurosci 2018; 12:268. [PMID: 29755312 PMCID: PMC5932184 DOI: 10.3389/fnins.2018.00268] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Accepted: 04/06/2018] [Indexed: 11/13/2022] Open
Abstract
Functional MRI acquisition is sensitive to subjects' motion that cannot be fully constrained. Therefore, signal corrections have to be applied a posteriori in order to mitigate the complex interactions between changing tissue localization and magnetic fields, gradients and readouts. To circumvent current preprocessing strategies limitations, we developed an integrated method that correct motion and spatial low-frequency intensity fluctuations at the level of each slice in order to better fit the acquisition processes. The registration of single or multiple simultaneously acquired slices is achieved online by an Iterated Extended Kalman Filter, favoring the robust estimation of continuous motion, while an intensity bias field is non-parametrically fitted. The proposed extraction of gray-matter BOLD activity from the acquisition space to an anatomical group template space, taking into account distortions, better preserves fine-scale patterns of activity. Importantly, the proposed unified framework generalizes to high-resolution multi-slice techniques. When tested on simulated and real data the latter shows a reduction of motion explained variance and signal variability when compared to the conventional preprocessing approach. These improvements provide more stable patterns of activity, facilitating investigation of cerebral information representation in healthy and/or clinical populations where motion is known to impact fine-scale data.
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Affiliation(s)
- Basile Pinsard
- Unité de Neuroimagerie Fonctionelle, Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada.,UMR7371 Laboratoire d'Imagerie Biomédicale, Paris, France.,Sorbonne Universités, Paris, France
| | - Arnaud Boutin
- Unité de Neuroimagerie Fonctionelle, Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada.,Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Julien Doyon
- Unité de Neuroimagerie Fonctionelle, Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada.,Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Habib Benali
- UMR7371 Laboratoire d'Imagerie Biomédicale, Paris, France.,Sorbonne Universités, Paris, France.,PERFORM Center, Concordia University, Montreal, QC, Canada
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Batalle D, Edwards AD, O'Muircheartaigh J. Annual Research Review: Not just a small adult brain: understanding later neurodevelopment through imaging the neonatal brain. J Child Psychol Psychiatry 2018; 59:350-371. [PMID: 29105061 PMCID: PMC5900873 DOI: 10.1111/jcpp.12838] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/04/2017] [Indexed: 12/27/2022]
Abstract
BACKGROUND There has been a recent proliferation in neuroimaging research focusing on brain development in the prenatal, neonatal and very early childhood brain. Early brain injury and preterm birth are associated with increased risk of neurodevelopmental disorders, indicating the importance of this early period for later outcome. SCOPE AND METHODOLOGY Although using a wide range of different methodologies and investigating diverse samples, the common aim of many of these studies has been to both track normative development and investigate deviations in this development to predict behavioural, cognitive and neurological function in childhood. Here we review structural and functional neuroimaging studies investigating the developing brain. We focus on practical and technical complexities of studying this early age range and discuss how neuroimaging techniques have been successfully applied to investigate later neurodevelopmental outcome. CONCLUSIONS Neuroimaging markers of later outcome still have surprisingly low predictive power and their specificity to individual neurodevelopmental disorders is still under question. However, the field is still young, and substantial challenges to both acquiring and modeling neonatal data are being met.
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Affiliation(s)
- Dafnis Batalle
- Centre for the Developing BrainSchool of Imaging Sciences & Biomedical EngineeringKing's College LondonLondonUK
| | - A. David Edwards
- Centre for the Developing BrainSchool of Imaging Sciences & Biomedical EngineeringKing's College LondonLondonUK
| | - Jonathan O'Muircheartaigh
- Centre for the Developing BrainSchool of Imaging Sciences & Biomedical EngineeringKing's College LondonLondonUK
- Department of NeuroimagingInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
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Hubs in the human fetal brain network. Dev Cogn Neurosci 2018; 30:108-115. [PMID: 29448128 PMCID: PMC5963507 DOI: 10.1016/j.dcn.2018.02.001] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2017] [Revised: 02/02/2018] [Accepted: 02/02/2018] [Indexed: 11/21/2022] Open
Abstract
Network analysis has identified highly connected regions, or hubs, in the human brain. Whether network hubs emerge in utero has yet to be examined. We found that fetal hubs were located in both primary and association cortices. Interestingly, hubs were identified close to fusiform facial and Wernicke’s areas. These putative hubs may be points of vulnerability in fetal brain development.
Advances in neuroimaging and network analyses have lead to discovery of highly connected regions, or hubs, in the connectional architecture of the human brain. Whether these hubs emerge in utero, has yet to be examined. The current study addresses this question and aims to determine the location of neural hubs in human fetuses. Fetal resting-state fMRI data (N = 105) was used to construct connectivity matrices for 197 discrete brain regions. We discovered that within the connectional functional organization of the human fetal brain key hubs are emerging. Consistent with prior reports in infants, visual and motor regions were identified as emerging hub areas, specifically in cerebellar areas. We also found evidence for network hubs in association cortex, including areas remarkably close to the adult fusiform facial and Wernicke areas. Functional significance of hub structure was confirmed by computationally deleting hub versus random nodes and observing that global efficiency decreased significantly more when hubs were removed (p < .001). Taken together, we conclude that both primary and association brain regions demonstrate centrality in network organization before birth. While fetal hubs may be important for facilitating network communication, they may also form potential points of vulnerability in fetal brain development.
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Seshamani S, Blazejewska AI, Mckown S, Caucutt J, Dighe M, Gatenby C, Studholme C. Detecting default mode networks in utero by integrated 4D fMRI reconstruction and analysis. Hum Brain Mapp 2018; 37:4158-4178. [PMID: 27510837 DOI: 10.1002/hbm.23303] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2015] [Revised: 05/03/2016] [Accepted: 06/20/2016] [Indexed: 11/05/2022] Open
Abstract
Recently, there has been considerable interest, especially for in utero imaging, in the detection of functional connectivity in subjects whose motion cannot be controlled while in the MRI scanner. These cases require two advances over current studies: (1) multiecho acquisitions and (2) post processing and reconstruction that can deal with significant between slice motion during multislice protocols to allow for the ability to detect temporal correlations introduced by spatial scattering of slices into account. This article focuses on the estimation of a spatially and temporally regular time series from motion scattered slices of multiecho fMRI datasets using a full four-dimensional (4D) iterative image reconstruction framework. The framework which includes quantitative MRI methods for artifact correction is evaluated using adult studies with and without motion to both refine parameter settings and evaluate the analysis pipeline. ICA analysis is then applied to the 4D image reconstruction of both adult and in utero fetal studies where resting state activity is perturbed by motion. Results indicate quantitative improvements in reconstruction quality when compared to the conventional 3D reconstruction approach (using simulated adult data) and demonstrate the ability to detect the default mode network in moving adults and fetuses with single-subject and group analysis. Hum Brain Mapp 37:4158-4178, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Sharmishtaa Seshamani
- Department of Pediatrics, Radiology and Bioengineering, Biomedical Image Computing Group, University of Washington, Seattle, Washington, 98195.
| | - Anna I Blazejewska
- Department of Pediatrics, Biomedical Image Computing Group, University of Washington, Seattle, Washington, 98195
| | - Susan Mckown
- Department of Radiology, University of Washington, Seattle, Washington, 98195
| | - Jason Caucutt
- Department of Pediatrics, Radiology, Bioengineering, Institute of Translational Health Sciences, University of Washington, Seattle, Washington, 98195
| | - Manjiri Dighe
- Department of Radiology, University of Washington, Seattle, Washington, 98195
| | - Christopher Gatenby
- Department of Radiology, University of Washington, Seattle, Washington, 98195
| | - Colin Studholme
- Departments of Pediatrics, Bioengineering and Radiology, Biomedical Image Computing Group, University of Washington, Seattle, Washington, 98195
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Kuklisova-Murgasova M, Lockwood Estrin G, Nunes RG, Malik SJ, Rutherford MA, Rueckert D, Hajnal JV. Distortion Correction in Fetal EPI Using Non-Rigid Registration With a Laplacian Constraint. IEEE TRANSACTIONS ON MEDICAL IMAGING 2018; 37:12-19. [PMID: 28207387 DOI: 10.1109/tmi.2017.2667227] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Geometric distortion induced by the main B0 field disrupts the consistency of fetal echo planar imaging (EPI) data, on which diffusion and functional magnetic resonance imaging is based. In this paper, we present a novel data-driven method for simultaneous motion and distortion correction of fetal EPI. A motion-corrected and reconstructed T2 weighted single shot fast spin echo (ssFSE) volume is used as a model of undistorted fetal brain anatomy. Our algorithm interleaves two registration steps: estimation of fetal motion parameters by aligning EPI slices to the model; and deformable registration of EPI slices to slices simulated from the undistorted model to estimate the distortion field. The deformable registration is regularized by a physically inspired Laplacian constraint, to model distortion induced by a source-free background B0 field. Our experiments show that distortion correction significantly improves consistency of reconstructed EPI volumes with ssFSE volumes. In addition, the estimated distortion fields are consistent with fields calculated from acquired field maps, and the Laplacian constraint is essential for estimation of plausible distortion fields. The EPI volumes reconstructed from different scans of the same subject were more consistent when the proposed method was used in comparison with EPI volumes reconstructed from data distortion corrected using a separately acquired B0 field map.
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Nunes RG, Ferrazzi G, Price AN, Hutter J, Gaspar AS, Rutherford MA, Hajnal JV. Inner-volume echo volumar imaging (IVEVI) for robust fetal brain imaging. Magn Reson Med 2017; 80:279-285. [PMID: 29115686 DOI: 10.1002/mrm.26998] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 10/17/2017] [Accepted: 10/18/2017] [Indexed: 11/08/2022]
Abstract
PURPOSE Fetal functional MRI studies using conventional 2-dimensional single-shot echo-planar imaging sequences may require discarding a large data fraction as a result of fetal and maternal motion. Increasing the temporal resolution using echo volumar imaging (EVI) could provide an effective alternative strategy. Echo volumar imaging was combined with inner volume (IV) imaging (IVEVI) to locally excite the fetal brain and acquire full 3-dimensional images, fast enough to freeze most fetal head motion. METHODS IVEVI was implemented by modifying a standard multi-echo echo-planar imaging sequence. A spin echo with orthogonal excitation and refocusing ensured localized excitation. To introduce T2* weighting and to save time, the k-space center was shifted relative to the spin echo. Both single and multi-shot variants were tested. Acoustic noise was controlled by adjusting the amplitude and switching frequency of the readout gradient. Image-based shimming was used to minimize B0 inhomogeneities within the fetal brain. RESULTS The sequence was first validated in an adult. Eight fetuses were scanned using single-shot IVEVI at a 3.5 × 3.5 × 5.0 mm3 resolution with a readout duration of 383 ms. Multishot IVEVI showed reduced geometric distortions along the second phase-encode direction. CONCLUSIONS Fetal EVI remains challenging. Although effective echo times comparable to the T2* values of fetal cortical gray matter at 3 T could be achieved, controlling acoustic noise required longer readouts, leading to substantial distortions in single-shot images. Although multishot variants enabled us to reduce susceptibility-induced geometric distortions, sensitivity to motion was increased. Future studies should therefore focus on improvements to multishot variants. Magn Reson Med 80:279-285, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Rita G Nunes
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.,Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal.,Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Giulio Ferrazzi
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Anthony N Price
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Jana Hutter
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Andreia S Gaspar
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.,Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal.,Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Mary A Rutherford
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
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Keunen K, Counsell SJ, Benders MJ. The emergence of functional architecture during early brain development. Neuroimage 2017; 160:2-14. [DOI: 10.1016/j.neuroimage.2017.01.047] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Revised: 12/22/2016] [Accepted: 01/18/2017] [Indexed: 01/12/2023] Open
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Caballero-Gaudes C, Reynolds RC. Methods for cleaning the BOLD fMRI signal. Neuroimage 2017; 154:128-149. [PMID: 27956209 PMCID: PMC5466511 DOI: 10.1016/j.neuroimage.2016.12.018] [Citation(s) in RCA: 355] [Impact Index Per Article: 44.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 12/05/2016] [Accepted: 12/08/2016] [Indexed: 01/13/2023] Open
Abstract
Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has rapidly become a popular technique for the investigation of brain function in healthy individuals, patients as well as in animal studies. However, the BOLD signal arises from a complex mixture of neuronal, metabolic and vascular processes, being therefore an indirect measure of neuronal activity, which is further severely corrupted by multiple non-neuronal fluctuations of instrumental, physiological or subject-specific origin. This review aims to provide a comprehensive summary of existing methods for cleaning the BOLD fMRI signal. The description is given from a methodological point of view, focusing on the operation of the different techniques in addition to pointing out the advantages and limitations in their application. Since motion-related and physiological noise fluctuations are two of the main noise components of the signal, techniques targeting their removal are primarily addressed, including both data-driven approaches and using external recordings. Data-driven approaches, which are less specific in the assumed model and can simultaneously reduce multiple noise fluctuations, are mainly based on data decomposition techniques such as principal and independent component analysis. Importantly, the usefulness of strategies that benefit from the information available in the phase component of the signal, or in multiple signal echoes is also highlighted. The use of global signal regression for denoising is also addressed. Finally, practical recommendations regarding the optimization of the preprocessing pipeline for the purpose of denoising and future venues of research are indicated. Through the review, we summarize the importance of signal denoising as an essential step in the analysis pipeline of task-based and resting state fMRI studies.
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Affiliation(s)
| | - Richard C Reynolds
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, USA
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Jakab A, Tuura R, Kellenberger C, Scheer I. In utero diffusion tensor imaging of the fetal brain: A reproducibility study. NEUROIMAGE-CLINICAL 2017; 15:601-612. [PMID: 28652972 PMCID: PMC5477067 DOI: 10.1016/j.nicl.2017.06.013] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Revised: 01/25/2017] [Accepted: 06/08/2017] [Indexed: 02/06/2023]
Abstract
Our purpose was to evaluate the within-subject reproducibility of in utero diffusion tensor imaging (DTI) metrics and the visibility of major white matter structures. Images for 30 fetuses (20-33. postmenstrual weeks, normal neurodevelopment: 6 cases, cerebral pathology: 24 cases) were acquired on 1.5 T or 3.0 T MRI. DTI with 15 diffusion-weighting directions was repeated three times for each case, TR/TE: 2200/63 ms, voxel size: 1 ∗ 1 mm, slice thickness: 3-5 mm, b-factor: 700 s/mm2. Reproducibility was evaluated from structure detectability, variability of DTI measures using the coefficient of variation (CV), image correlation and structural similarity across repeated scans for six selected structures. The effect of age, scanner type, presence of pathology was determined using Wilcoxon rank sum test. White matter structures were detectable in the following percentage of fetuses in at least two of the three repeated scans: corpus callosum genu 76%, splenium 64%, internal capsule, posterior limb 60%, brainstem fibers 40% and temporooccipital association pathways 60%. The mean CV of DTI metrics ranged between 3% and 14.6% and we measured higher reproducibility in fetuses with normal brain development. Head motion was negatively correlated with reproducibility, this effect was partially ameliorated by motion-correction algorithm using image registration. Structures on 3.0 T had higher variability both with- and without motion correction. Fetal DTI is reproducible for projection and commissural bundles during mid-gestation, however, in 16-30% of the cases, data were corrupted by artifacts, resulting in impaired detection of white matter structures. To achieve robust results for the quantitative analysis of diffusivity and anisotropy values, fetal-specific image processing is recommended and repeated DTI is needed to ensure the detectability of fiber pathways.
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Key Words
- AD, axial diffusivity
- CCA, corpus callosum agenesis
- CV, coefficient of variation
- Connectome
- DTI, diffusion tensor imaging
- Diffusion tensor imaging
- FA, fractional anisotropy
- Fetal brain connectivity
- Fetal diffusion MRI
- GW, gestational week
- MD, mean diffusivity
- Prenatal development
- RD, radial diffusivity
- ROI, region of interest
- SSIM, structural similarity index
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Affiliation(s)
- András Jakab
- Center for MR-Research, University Children's Hospital, Zürich, Switzerland; Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
| | - Ruth Tuura
- Center for MR-Research, University Children's Hospital, Zürich, Switzerland
| | | | - Ianina Scheer
- Department of Diagnostic Imaging, University Children's Hospital, Zürich, Switzerland
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Turk EA, Luo J, Gagoski B, Pascau J, Bibbo C, Robinson JN, Grant PE, Adalsteinsson E, Golland P, Malpica N. Spatiotemporal alignment of in utero BOLD-MRI series. J Magn Reson Imaging 2017; 46:403-412. [PMID: 28152240 DOI: 10.1002/jmri.25585] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Accepted: 11/22/2016] [Indexed: 11/12/2022] Open
Abstract
PURPOSE To present a method for spatiotemporal alignment of in-utero magnetic resonance imaging (MRI) time series acquired during maternal hyperoxia for enabling improved quantitative tracking of blood oxygen level-dependent (BOLD) signal changes that characterize oxygen transport through the placenta to fetal organs. MATERIALS AND METHODS The proposed pipeline for spatiotemporal alignment of images acquired with a single-shot gradient echo echo-planar imaging includes 1) signal nonuniformity correction, 2) intravolume motion correction based on nonrigid registration, 3) correction of motion and nonrigid deformations across volumes, and 4) detection of the outlier volumes to be discarded from subsequent analysis. BOLD MRI time series collected from 10 pregnant women during 3T scans were analyzed using this pipeline. To assess pipeline performance, signal fluctuations between consecutive timepoints were examined. In addition, volume overlap and distance between manual region of interest (ROI) delineations in a subset of frames and the delineations obtained through propagation of the ROIs from the reference frame were used to quantify alignment accuracy. A previously demonstrated rigid registration approach was used for comparison. RESULTS The proposed pipeline improved anatomical alignment of placenta and fetal organs over the state-of-the-art rigid motion correction methods. In particular, unexpected temporal signal fluctuations during the first normoxia period were significantly decreased (P < 0.01) and volume overlap and distance between region boundaries measures were significantly improved (P < 0.01). CONCLUSION The proposed approach to align MRI time series enables more accurate quantitative studies of placental function by improving spatiotemporal alignment across placenta and fetal organs. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:403-412.
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Affiliation(s)
- Esra Abaci Turk
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.,Madrid-MIT M+Vision Consortium in RLE, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Jie Luo
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.,Madrid-MIT M+Vision Consortium in RLE, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Borjan Gagoski
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.,Department of Radiology, Harvard Medical School, Boston Children's Hospital, Boston, MA, United States
| | - Javier Pascau
- Madrid-MIT M+Vision Consortium in RLE, Massachusetts Institute of Technology, Cambridge, MA, United States.,Instituto de Investigación Sanitaria Gregorio Marañón, CIBERSAM, Madrid, Spain.,Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Spain
| | - Carolina Bibbo
- Maternal and Fetal Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Julian N Robinson
- Maternal and Fetal Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States
| | - Elfar Adalsteinsson
- Madrid-MIT M+Vision Consortium in RLE, Massachusetts Institute of Technology, Cambridge, MA, United States.,Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States.,Harvard-MIT Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Polina Golland
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States.,Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Norberto Malpica
- Madrid-MIT M+Vision Consortium in RLE, Massachusetts Institute of Technology, Cambridge, MA, United States.,Medical Image Analysis and Biometry Laboratory, Universidad Rey Juan Carlos, Madrid, Spain
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38
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Huijbers W, Van Dijk KRA, Boenniger MM, Stirnberg R, Breteler MMB. Less head motion during MRI under task than resting-state conditions. Neuroimage 2016; 147:111-120. [PMID: 27919751 DOI: 10.1016/j.neuroimage.2016.12.002] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Revised: 11/24/2016] [Accepted: 12/01/2016] [Indexed: 10/20/2022] Open
Abstract
Head motion reduces data quality of neuroimaging data. In three functional magnetic resonance imaging (MRI) experiments we demonstrate that people make less head movements under task than resting-state conditions. In Experiment 1, we observed less head motion during a memory encoding task than during the resting-state condition. In Experiment 2, using publicly shared data from the UCLA Consortium for Neuropsychiatric Phenomics LA5c Study, we again found less head motion during several active task conditions than during a resting-state condition, although some task conditions also showed comparable motion. In the healthy controls, we found more head motion in men than in women and more motion with increasing age. When comparing clinical groups, we found that patients with a clinical diagnosis of bipolar disorder, or schizophrenia, move more compared to healthy controls or patients with ADHD. Both these experiments had a fixed acquisition order across participants, and we could not rule out that a first or last scan during a session might be particularly prone to more head motion. Therefore, we conducted Experiment 3, in which we collected several task and resting-state fMRI runs with an acquisition order counter-balanced. The results of Experiment 3 show again less head motion during several task conditions than during rest. Together these experiments demonstrate that small head motions occur during MRI even with careful instruction to remain still and fixation with foam pillows, but that head motion is lower when participants are engaged in a cognitive task. These finding may inform the choice of functional runs when studying difficult-to-scan populations, such as children or certain patient populations. Our findings also indicate that differences in head motion complicate direct comparisons of measures of functional neuronal networks between task and resting-state fMRI because of potential differences in data quality. In practice, a task to reduce head motion might be especially useful when acquiring structural MRI data such as T1/T2-weighted and diffusion MRI in research and clinical settings.
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Affiliation(s)
- Willem Huijbers
- German Centre for Neurodegenerative Diseases (DZNE), Department of Population Health Sciences, Bonn, Germany; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States.
| | - Koene R A Van Dijk
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
| | - Meta M Boenniger
- German Centre for Neurodegenerative Diseases (DZNE), Department of Population Health Sciences, Bonn, Germany
| | - Rüdiger Stirnberg
- German Centre for Neurodegenerative Diseases (DZNE), Department of MR Physics, Bonn, Germany
| | - Monique M B Breteler
- German Centre for Neurodegenerative Diseases (DZNE), Department of Population Health Sciences, Bonn, Germany
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39
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van den Heuvel MI, Thomason ME. Functional Connectivity of the Human Brain in Utero. Trends Cogn Sci 2016; 20:931-939. [PMID: 27825537 DOI: 10.1016/j.tics.2016.10.001] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2016] [Revised: 09/29/2016] [Accepted: 10/04/2016] [Indexed: 12/23/2022]
Abstract
The brain is subject to dramatic developmental processes during the prenatal period. Nevertheless, information about the development of functional brain networks during gestation is scarce. Until recently it has not been possible to probe function in the living human fetal brain. Advances in functional MRI have changed the paradigm, making it possible to measure spontaneous activity in the fetal brain and to cross-correlate functional signals to attain information about neural connectional architecture across human gestation. We summarize the earliest MRI studies of fetal neural functional connectivity and highlight unique challenges and limitations inherent in the technique. In addition, we discuss future directions to unlock the potential of fetal brain functional MRI research.
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Affiliation(s)
- Marion I van den Heuvel
- Merrill Palmer Skillman Institute for Child and Family Development, Wayne State University, Detroit, MI, USA; Perinatology Research Branch, National Institute of Child Health and Human Development (NICHD)/National Institutes of Health (NIH)/Department of Health and Human Services (DHHS), Detroit, MI, USA
| | - Moriah E Thomason
- Merrill Palmer Skillman Institute for Child and Family Development, Wayne State University, Detroit, MI, USA; Perinatology Research Branch, National Institute of Child Health and Human Development (NICHD)/National Institutes of Health (NIH)/Department of Health and Human Services (DHHS), Detroit, MI, USA; Department of Pediatrics, Wayne State University School of Medicine, Detroit, MI, USA.
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40
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Blazejewska AI, Seshamani S, McKown SK, Caucutt JS, Dighe M, Gatenby C, Studholme C. 3D in utero quantification of T2* relaxation times in human fetal brain tissues for age optimized structural and functional MRI. Magn Reson Med 2016; 78:909-916. [PMID: 27699879 DOI: 10.1002/mrm.26471] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2016] [Revised: 08/21/2016] [Accepted: 08/29/2016] [Indexed: 11/05/2022]
Abstract
PURPOSE Maximization of the blood oxygen level-dependent (BOLD) functional MRI (fMRI) contrast requires the echo time of the MR sequence to match the T2* value of the tissue of interest, which is expected to be higher in the fetal brain compared with the brain of a child or an adult. METHODS T2* values of the cortical plate/cortical gray matter tissue in utero in healthy fetuses from mid-gestation onward (20-36 gestational weeks) were measured using 3D T2* maps calculated from 2D dual-echo T2*-weighted data corrected for between-slice motion and reconstructed in 1.0 mm3 isotropic resolution from a sequence of multiple time points, together with 1.0 mm3 isotropic resolution T2-weighted structural data. RESULTS Mean T2* relaxation times of the cortical tissue were about twice as high as those reported previously in adults. In a supporting experiment applying single seed analysis, default mode and auditory networks appeared better localized and less noisy while using an echo time of 100 ms versus 43 ms. The results of the previous study reporting a trend for T2* values to decrease with fetal age were reproduced and extended to include cortical tissues and subjects in earlier gestation (20-26 gestational weeks). CONCLUSION The first measurement of T2* values in fetal cortical tissues suggested the appropriate echo time range for fetal BOLD fMRI protocol optimization to be 130-190 ms. Magn Reson Med 78:909-916, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Anna I Blazejewska
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
| | | | - Susan K McKown
- Department of Radiology, University of Washington, Seattle, Washington, USA
| | - Jason S Caucutt
- Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Manjiri Dighe
- Department of Radiology, University of Washington, Seattle, Washington, USA
| | | | - Colin Studholme
- Department of Pediatrics, University of Washington, Seattle, Washington, USA.,Department of Bioengineering, University of Washington, Seattle, Washington, USA
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41
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Marami B, Scherrer B, Afacan O, Erem B, Warfield SK, Gholipour A. Motion-Robust Diffusion-Weighted Brain MRI Reconstruction Through Slice-Level Registration-Based Motion Tracking. IEEE TRANSACTIONS ON MEDICAL IMAGING 2016; 35:2258-2269. [PMID: 27834639 PMCID: PMC5108524 DOI: 10.1109/tmi.2016.2555244] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
This work proposes a novel approach for motion-robust diffusion-weighted (DW) brain MRI reconstruction through tracking temporal head motion using slice-to-volume registration. The slice-level motion is estimated through a filtering approach that allows tracking the head motion during the scan and correcting for out-of-plane inconsistency in the acquired images. Diffusion-sensitized image slices are registered to a base volume sequentially over time in the acquisition order where an outlier-robust Kalman filter, coupled with slice-to-volume registration, estimates head motion parameters. Diffusion gradient directions are corrected for the aligned DWI slices based on the computed rotation parameters and the diffusion tensors are directly estimated from the corrected data at each voxel using weighted linear least squares. The method was evaluated in DWI scans of adult volunteers who deliberately moved during scans as well as clinical DWI of 28 neonates and children with different types of motion. Experimental results showed marked improvements in DWI reconstruction using the proposed method compared to the state-of-the-art DWI analysis based on volume-to-volume registration. This approach can be readily used to retrieve information from motion-corrupted DW imaging data.
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Affiliation(s)
- Bahram Marami
- Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA 02115 USA
| | - Benoit Scherrer
- Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA 02115 USA
| | - Onur Afacan
- Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA 02115 USA
| | - Burak Erem
- Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA 02115 USA
| | - Simon K. Warfield
- Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA 02115 USA
| | - Ali Gholipour
- Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA 02115 USA
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42
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You W, Evangelou IE, Zun Z, Andescavage N, Limperopoulos C. Robust preprocessing for stimulus-based functional MRI of the moving fetus. J Med Imaging (Bellingham) 2016; 3:026001. [PMID: 27081665 DOI: 10.1117/1.jmi.3.2.026001] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Accepted: 03/03/2016] [Indexed: 11/14/2022] Open
Abstract
Fetal motion manifests as signal degradation and image artifact in the acquired time series of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) studies. We present a robust preprocessing pipeline to specifically address fetal and placental motion-induced artifacts in stimulus-based fMRI with slowly cycled block design in the living fetus. In the proposed pipeline, motion correction is optimized to the experimental paradigm, and it is performed separately in each phase as well as in each region of interest (ROI), recognizing that each phase and organ experiences different types of motion. To obtain the averaged BOLD signals for each ROI, both misaligned volumes and noisy voxels are automatically detected and excluded, and the missing data are then imputed by statistical estimation based on local polynomial smoothing. Our experimental results demonstrate that the proposed pipeline was effective in mitigating the motion-induced artifacts in stimulus-based fMRI data of the fetal brain and placenta.
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Affiliation(s)
- Wonsang You
- Children's National Medical Center , Department of Diagnostic Imaging and Radiology, 111 Michigan Avenue N.W., Washington, DC 20852, United States
| | - Iordanis E Evangelou
- Children's National Medical Center, Department of Diagnostic Imaging and Radiology, 111 Michigan Avenue N.W., Washington, DC 20852, United States; George Washington University, School of Medicine and Health Sciences, Department of Radiology, 2300 Eye Street N.W., Washington, DC 20037, United States
| | - Zungho Zun
- Children's National Medical Center , Department of Diagnostic Imaging and Radiology, 111 Michigan Avenue N.W., Washington, DC 20852, United States
| | - Nickie Andescavage
- Children's National Medical Center, Department of Fetal and Transitional Medicine, 111 Michigan Avenue N.W., Washington, DC 20852, United States; Children's National Medical Center, Department of Neonatology, 111 Michigan Avenue N.W., Washington, DC 20852, United States; George Washington University, School of Medicine and Health Sciences, Department of Pediatrics, 2300 Eye Street N.W., Washington, DC 20037, United States
| | - Catherine Limperopoulos
- Children's National Medical Center, Department of Diagnostic Imaging and Radiology, 111 Michigan Avenue N.W., Washington, DC 20852, United States; George Washington University, School of Medicine and Health Sciences, Department of Radiology, 2300 Eye Street N.W., Washington, DC 20037, United States; Children's National Medical Center, Department of Fetal and Transitional Medicine, 111 Michigan Avenue N.W., Washington, DC 20852, United States; George Washington University, School of Medicine and Health Sciences, Department of Pediatrics, 2300 Eye Street N.W., Washington, DC 20037, United States
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43
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Kozberg M, Hillman E. Neurovascular coupling and energy metabolism in the developing brain. PROGRESS IN BRAIN RESEARCH 2016; 225:213-42. [PMID: 27130418 DOI: 10.1016/bs.pbr.2016.02.002] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
In the adult brain, increases in local neural activity are almost always accompanied by increases in local blood flow. However, many functional imaging studies of the newborn and developing human brain have observed patterns of hemodynamic responses that differ from adult responses. Among the proposed mechanisms for the observed variations is that neurovascular coupling itself is still developing in the perinatal brain. Many of the components thought to be involved in actuating and propagating this hemodynamic response are known to still be developing postnatally, including perivascular cells such as astrocytes and pericytes. Both neural and vascular networks expand and are then selectively pruned over the first year of human life. Additionally, the metabolic demands of the newborn brain are still evolving. These changes are highly likely to affect early postnatal neurovascular coupling, and thus may affect functional imaging signals in this age group. This chapter will discuss the literature relating to neurovascular development. Potential effects of normal and aberrant development of neurovascular coupling on the newborn brain will also be explored, as well as ways to effectively utilize imaging techniques that rely on hemodynamic modulation such as fMRI and NIRS in younger populations.
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Affiliation(s)
- M Kozberg
- Columbia University, New York, NY, United States.
| | - E Hillman
- Columbia University, New York, NY, United States; Kavli Institute for Brain Science, Columbia University, New York, NY, United States; Mortimer B. Zuckerman Institute for Mind Brain and Behavior, Columbia University, New York, NY, United States.
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44
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Abstract
OBJECTIVES Clinical neuroscience is increasingly turning to imaging the human brain for answers to a range of questions and challenges. To date, the majority of studies have focused on the neural basis of current psychiatric symptoms, which can facilitate the identification of neurobiological markers for diagnosis. However, the increasing availability and feasibility of using imaging modalities, such as diffusion imaging and resting-state fMRI, enable longitudinal mapping of brain development. This shift in the field is opening the possibility of identifying predictive markers of risk or prognosis, and also represents a critical missing element for efforts to promote personalized or individualized medicine in psychiatry (i.e., stratified psychiatry). METHODS The present work provides a selective review of potentially high-yield populations for longitudinal examination with MRI, based upon our understanding of risk from epidemiologic studies and initial MRI findings. RESULTS Our discussion is organized into three topic areas: (1) practical considerations for establishing temporal precedence in psychiatric research; (2) readiness of the field for conducting longitudinal MRI, particularly for neurodevelopmental questions; and (3) illustrations of high-yield populations and time windows for examination that can be used to rapidly generate meaningful and useful data. Particular emphasis is placed on the implementation of time-appropriate, developmentally informed longitudinal designs, capable of facilitating the identification of biomarkers predictive of risk and prognosis. CONCLUSIONS Strategic longitudinal examination of the brain at-risk has the potential to bring the concepts of early intervention and prevention to psychiatry.
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45
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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: 0.7] [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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46
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An exploration of task based fMRI in neonates using echo-shifting to allow acquisition at longer TE without loss of temporal efficiency. Neuroimage 2015; 127:298-306. [PMID: 26708014 DOI: 10.1016/j.neuroimage.2015.12.025] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2015] [Revised: 11/03/2015] [Accepted: 12/15/2015] [Indexed: 11/22/2022] Open
Abstract
Optimal contrast to noise ratio of the BOLD signal in neonatal and foetal fMRI has been hard to achieve because of the much longer T2(⁎) values in developing brain tissue in comparison to those in the mature adult brain. The conventional approach of optimizing fMRI sequences would suggest matching the echo time (TE) and the T2(⁎) of the neonatal and foetal brain. However, the use of a long echo time would typically increase the minimum repetition time (TR) resulting in inefficient sampling. Here we apply the concept of echo shifting to task based neonatal fMRI in order to achieve an improved contrast to noise ratio and efficient data sampling at the same time. Echo shifted EPI (es-EPI) is a modification of a standard 2D-EPI sequence which enables echo times longer than the time between consecutive excitations (TE>TS=TRNS, where NS is the number of acquired slices and TS the inter-slice repetition time). The proposed method was tested on neonatal subjects using a passive sensori-motor task paradigm. Dual echo EPI datasets with an identical readout structure to es-EPI were also acquired and used as control data to assess BOLD activation. From the results of the latter analysis, an average increase of 78±41% in contrast to noise ratio was observable when comparing late to short echoes. Furthermore, es-EPI allowed the acquisition of data with an identical contrast to the late echo, but more efficiently since a higher number of slices could be acquired in the same amount of time.
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47
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Jakab A, Pogledic I, Schwartz E, Gruber G, Mitter C, Brugger PC, Langs G, Schöpf V, Kasprian G, Prayer D. Fetal Cerebral Magnetic Resonance Imaging Beyond Morphology. Semin Ultrasound CT MR 2015; 36:465-75. [DOI: 10.1053/j.sult.2015.06.003] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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48
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Allievi AG, Arichi T, Tusor N, Kimpton J, Arulkumaran S, Counsell SJ, Edwards AD, Burdet E. Maturation of Sensori-Motor Functional Responses in the Preterm Brain. Cereb Cortex 2015; 26:402-413. [PMID: 26491066 PMCID: PMC4677983 DOI: 10.1093/cercor/bhv203] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Preterm birth engenders an increased risk of conditions like cerebral palsy and therefore this time may be crucial for the brain's developing sensori-motor system. However, little is known about how cortical sensori-motor function matures at this time, whether development is influenced by experience, and about its role in spontaneous motor behavior. We aimed to systematically characterize spatial and temporal maturation of sensori-motor functional brain activity across this period using functional MRI and a custom-made robotic stimulation device. We studied 57 infants aged from 30 + 2 to 43 + 2 weeks postmenstrual age. Following both induced and spontaneous right wrist movements, we saw consistent positive blood oxygen level–dependent functional responses in the contralateral (left) primary somatosensory and motor cortices. In addition, we saw a maturational trend toward faster, higher amplitude, and more spatially dispersed functional responses; and increasing integration of the ipsilateral hemisphere and sensori-motor associative areas. We also found that interhemispheric functional connectivity was significantly related to ex-utero exposure, suggesting the influence of experience-dependent mechanisms. At term equivalent age, we saw a decrease in both response amplitude and interhemispheric functional connectivity, and an increase in spatial specificity, culminating in the establishment of a sensori-motor functional response similar to that seen in adults.
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Affiliation(s)
| | - Tomoki Arichi
- Department of Bioengineering.,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, UK
| | - Nora Tusor
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, LondonSE1 7EH, UK
| | - Jessica Kimpton
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, LondonSE1 7EH, UK
| | - Sophie Arulkumaran
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, LondonSE1 7EH, UK
| | - Serena 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, LondonSE1 7EH, UK
| | - A David Edwards
- Department of Bioengineering.,Division of Brain Sciences, Department of Medicine, Imperial College of Science, Technology and Medicine, London SW7 2AZ, UK.,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, UK
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49
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Tocchio S, Kline-Fath B, Kanal E, Schmithorst VJ, Panigrahy A. MRI evaluation and safety in the developing brain. Semin Perinatol 2015; 39:73-104. [PMID: 25743582 PMCID: PMC4380813 DOI: 10.1053/j.semperi.2015.01.002] [Citation(s) in RCA: 87] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Magnetic resonance imaging (MRI) evaluation of the developing brain has dramatically increased over the last decade. Faster acquisitions and the development of advanced MRI sequences, such as magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI), perfusion imaging, functional MR imaging (fMRI), and susceptibility-weighted imaging (SWI), as well as the use of higher magnetic field strengths has made MRI an invaluable tool for detailed evaluation of the developing brain. This article will provide an overview of the use and challenges associated with 1.5-T and 3-T static magnetic fields for evaluation of the developing brain. This review will also summarize the advantages, clinical challenges, and safety concerns specifically related to MRI in the fetus and newborn, including the implications of increased magnetic field strength, logistics related to transporting and monitoring of neonates during scanning, and sedation considerations, and a discussion of current technologies such as MRI conditional neonatal incubators and dedicated small-foot print neonatal intensive care unit (NICU) scanners.
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Affiliation(s)
- Shannon Tocchio
- Pediatric Imaging Research Center, Department of Radiology Children’s Hospital of Pittsburgh of UPMC, Pittsburgh, PA University of Pittsburgh Medical Center, Pittsburgh, PA
| | - Beth Kline-Fath
- Department of Radiology Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Emanuel Kanal
- Director, Magnetic Resonance Services; Professor of Neuroradiology; Department of Radiology, University of Pittsburgh Medical Center (UPMC)
| | - Vincent J. Schmithorst
- Pediatric Imaging Research Center, Department of Radiology Children’s Hospital of Pittsburgh of UPMC, Pittsburgh, PA University of Pittsburgh Medical Center, Pittsburgh, PA
| | - Ashok Panigrahy
- Pediatric Imaging Research Center, Department of Radiology Children׳s Hospital of Pittsburgh of UPMC, University of Pittsburgh Medical Center, Pittsburgh, PA.
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50
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Gholipour A, Estroff JA, Barnewolt CE, Robertson RL, Grant PE, Gagoski B, Warfield SK, Afacan O, Connolly SA, Neil JJ, Wolfberg A, Mulkern RV. Fetal MRI: A Technical Update with Educational Aspirations. CONCEPTS IN MAGNETIC RESONANCE. PART A, BRIDGING EDUCATION AND RESEARCH 2014; 43:237-266. [PMID: 26225129 PMCID: PMC4515352 DOI: 10.1002/cmr.a.21321] [Citation(s) in RCA: 77] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Fetal magnetic resonance imaging (MRI) examinations have become well-established procedures at many institutions and can serve as useful adjuncts to ultrasound (US) exams when diagnostic doubts remain after US. Due to fetal motion, however, fetal MRI exams are challenging and require the MR scanner to be used in a somewhat different mode than that employed for more routine clinical studies. Herein we review the techniques most commonly used, and those that are available, for fetal MRI with an emphasis on the physics of the techniques and how to deploy them to improve success rates for fetal MRI exams. By far the most common technique employed is single-shot T2-weighted imaging due to its excellent tissue contrast and relative immunity to fetal motion. Despite the significant challenges involved, however, many of the other techniques commonly employed in conventional neuro- and body MRI such as T1 and T2*-weighted imaging, diffusion and perfusion weighted imaging, as well as spectroscopic methods remain of interest for fetal MR applications. An effort to understand the strengths and limitations of these basic methods within the context of fetal MRI is made in order to optimize their use and facilitate implementation of technical improvements for the further development of fetal MR imaging, both in acquisition and post-processing strategies.
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Affiliation(s)
- Ali Gholipour
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Judith A Estroff
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Carol E Barnewolt
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Richard L Robertson
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - P Ellen Grant
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Borjan Gagoski
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Onur Afacan
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Susan A Connolly
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Jeffrey J Neil
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Adam Wolfberg
- Boston Maternal Fetal Medicine, Boston, Massachusetts, USA
| | - Robert V Mulkern
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts, USA
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