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You S, De Leon Barba A, Cruz Tamayo V, Yun HJ, Yang E, Grant PE, Im K. Automatic cortical surface parcellation in the fetal brain using attention-gated spherical U-net. Front Neurosci 2024; 18:1410936. [PMID: 38872945 PMCID: PMC11169851 DOI: 10.3389/fnins.2024.1410936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 05/20/2024] [Indexed: 06/15/2024] Open
Abstract
Cortical surface parcellation for fetal brains is essential for the understanding of neurodevelopmental trajectories during gestations with regional analyses of brain structures and functions. This study proposes the attention-gated spherical U-net, a novel deep-learning model designed for automatic cortical surface parcellation of the fetal brain. We trained and validated the model using MRIs from 55 typically developing fetuses [gestational weeks: 32.9 ± 3.3 (mean ± SD), 27.4-38.7]. The proposed model was compared with the surface registration-based method, SPHARM-net, and the original spherical U-net. Our model demonstrated significantly higher accuracy in parcellation performance compared to previous methods, achieving an overall Dice coefficient of 0.899 ± 0.020. It also showed the lowest error in terms of the median boundary distance, 2.47 ± 1.322 (mm), and mean absolute percent error in surface area measurement, 10.40 ± 2.64 (%). In this study, we showed the efficacy of the attention gates in capturing the subtle but important information in fetal cortical surface parcellation. Our precise automatic parcellation model could increase sensitivity in detecting regional cortical anomalies and lead to the potential for early detection of neurodevelopmental disorders in fetuses.
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Affiliation(s)
- Sungmin You
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Anette De Leon Barba
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Valeria Cruz Tamayo
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Pediatrics, Harvard Medical School, Boston, MA, United States
| | - Edward Yang
- Department of Radiology, Boston Children’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
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Pediatrics, Harvard Medical School, Boston, MA, United States
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Kwon H, You S, Yun HJ, Jeong S, De León Barba AP, Lemus Aguilar ME, Vergara PJ, Davila SU, Grant PE, Lee JM, Im K. The role of cortical structural variance in deep learning-based prediction of fetal brain age. Front Neurosci 2024; 18:1411334. [PMID: 38846713 PMCID: PMC11153753 DOI: 10.3389/fnins.2024.1411334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 05/10/2024] [Indexed: 06/09/2024] Open
Abstract
Background Deep-learning-based brain age estimation using magnetic resonance imaging data has been proposed to identify abnormalities in brain development and the risk of adverse developmental outcomes in the fetal brain. Although saliency and attention activation maps have been used to understand the contribution of different brain regions in determining brain age, there has been no attempt to explain the influence of shape-related cortical structural features on the variance of predicted fetal brain age. Methods We examined the association between the predicted brain age difference (PAD: predicted brain age-chronological age) from our convolution neural networks-based model and global and regional cortical structural measures, such as cortical volume, surface area, curvature, gyrification index, and folding depth, using regression analysis. Results Our results showed that global brain volume and surface area were positively correlated with PAD. Additionally, higher cortical surface curvature and folding depth led to a significant increase in PAD in specific regions, including the perisylvian areas, where dramatic agerelated changes in folding structures were observed in the late second trimester. Furthermore, PAD decreased with disorganized sulcal area patterns, suggesting that the interrelated arrangement and areal patterning of the sulcal folds also significantly affected the prediction of fetal brain age. Conclusion These results allow us to better understand the variance in deep learning-based fetal brain age and provide insight into the mechanism of the fetal brain age prediction model.
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Affiliation(s)
- Hyeokjin Kwon
- Department of Electronic Engineering, Hanyang University, Seoul, Republic of Korea
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
| | - Sungmin You
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Boston, MA, United States
| | - Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Boston, MA, United States
- Department of Pediatrics, Harvard Medical School, Boston, MA, United States
| | - Seungyoon Jeong
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Boston, MA, United States
| | - Anette Paulina De León Barba
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
| | | | - Pablo Jaquez Vergara
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
| | - Sofia Urosa Davila
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
| | - P. Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Boston, MA, United States
- Department of Pediatrics, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Jong-Min Lee
- Department of Electronic Engineering, Hanyang University, Seoul, Republic of Korea
- Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea
- Department of Artificial Intelligence, Hanyang University, Seoul, Republic of Korea
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Boston, MA, United States
- Department of Pediatrics, Harvard Medical School, Boston, MA, United States
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3
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Tarui T, Gimovsky AC, Madan N. Fetal neuroimaging applications for diagnosis and counseling of brain anomalies: Current practice and future diagnostic strategies. Semin Fetal Neonatal Med 2024; 29:101525. [PMID: 38632010 PMCID: PMC11156536 DOI: 10.1016/j.siny.2024.101525] [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: 04/19/2024]
Abstract
Advances in fetal brain neuroimaging, especially fetal neurosonography and brain magnetic resonance imaging (MRI), allow safe and accurate anatomical assessments of fetal brain structures that serve as a foundation for prenatal diagnosis and counseling regarding fetal brain anomalies. Fetal neurosonography strategically assesses fetal brain anomalies suspected by screening ultrasound. Fetal brain MRI has unique technological features that overcome the anatomical limits of smaller fetal brain size and the unpredictable variable of intrauterine motion artifact. Recent studies of fetal brain MRI provide evidence of improved diagnostic and prognostic accuracy, beginning with prenatal diagnosis. Despite technological advances over the last several decades, the combined use of different qualitative structural biomarkers has limitations in providing an accurate prognosis. Quantitative analyses of fetal brain MRIs offer measurable imaging biomarkers that will more accurately associate with clinical outcomes. First-trimester ultrasound opens new opportunities for risk assessment and fetal brain anomaly diagnosis at the earliest time in pregnancy. This review includes a case vignette to illustrate how fetal brain MRI results interpreted by the fetal neurologist can improve diagnostic perspectives. The strength and limitations of conventional ultrasound and fetal brain MRI will be compared with recent research advances in quantitative methods to better correlate fetal neuroimaging biomarkers of neuropathology to predict functional childhood deficits. Discussion of these fetal sonogram and brain MRI advances will highlight the need for further interdisciplinary collaboration using complementary skills to continue improving clinical decision-making following precision medicine principles.
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Affiliation(s)
- Tomo Tarui
- Pediatric Neurology, Pediatrics, Hasbro Children's Hospital, The Warren Alpert Medical School of Brown University, Providence, RI, USA.
| | - Alexis C Gimovsky
- Maternal Fetal Medicine, Obstetrics and Gynecology, Women & Infants Hospital of Rhode Island, The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Neel Madan
- Neuroradiology, Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Abaci Turk E, Yun HJ, Feldman HA, Lee JY, Lee HJ, Bibbo C, Zhou C, Tamen R, Grant PE, Im K. Association between placental oxygen transport and fetal brain cortical development: a study in monochorionic diamniotic twins. Cereb Cortex 2024; 34:bhad383. [PMID: 37885155 PMCID: PMC11032198 DOI: 10.1093/cercor/bhad383] [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: 06/28/2023] [Revised: 09/25/2023] [Accepted: 09/26/2023] [Indexed: 10/28/2023] Open
Abstract
Normal cortical growth and the resulting folding patterns are crucial for normal brain function. Although cortical development is largely influenced by genetic factors, environmental factors in fetal life can modify the gene expression associated with brain development. As the placenta plays a vital role in shaping the fetal environment, affecting fetal growth through the exchange of oxygen and nutrients, placental oxygen transport might be one of the environmental factors that also affect early human cortical growth. In this study, we aimed to assess the placental oxygen transport during maternal hyperoxia and its impact on fetal brain development using MRI in identical twins to control for genetic and maternal factors. We enrolled 9 pregnant subjects with monochorionic diamniotic twins (30.03 ± 2.39 gestational weeks [mean ± SD]). We observed that the fetuses with slower placental oxygen delivery had reduced volumetric and surface growth of the cerebral cortex. Moreover, when the difference between placenta oxygen delivery increased between the twin pairs, sulcal folding patterns were more divergent. Thus, there is a significant relationship between placental oxygen transport and fetal brain cortical growth and folding in monochorionic twins.
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Affiliation(s)
- Esra Abaci Turk
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
| | - Hyuk Jin Yun
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
| | - Henry A Feldman
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Institutional Centers for Clinical and Translational Research, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
| | - Joo Young Lee
- Department of Pediatrics, Hanyang University College of Medicine, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, South Korea
| | - Hyun Ju Lee
- Department of Pediatrics, Hanyang University College of Medicine, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, South Korea
| | - Carolina Bibbo
- Department of Obstetrics and Gynecology, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115, United States
| | - Cindy Zhou
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
| | - Rubii Tamen
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
| | - Patricia Ellen Grant
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
- Department of Radiology, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
| | - Kiho Im
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
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5
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Murray A, Gough G, Cindrić A, Vučković F, Koschut D, Borelli V, Petrović DJ, Bekavac A, Plećaš A, Hribljan V, Brunmeir R, Jurić J, Pučić-Baković M, Slana A, Deriš H, Frkatović A, Groet J, O'Brien NL, Chen HY, Yeap YJ, Delom F, Havlicek S, Gammon L, Hamburg S, Startin C, D'Souza H, Mitrečić D, Kero M, Odak L, Krušlin B, Krsnik Ž, Kostović I, Foo JN, Loh YH, Dunn NR, de la Luna S, Spector T, Barišić I, Thomas MSC, Strydom A, Franceschi C, Lauc G, Krištić J, Alić I, Nižetić D. Dose imbalance of DYRK1A kinase causes systemic progeroid status in Down syndrome by increasing the un-repaired DNA damage and reducing LaminB1 levels. EBioMedicine 2023; 94:104692. [PMID: 37451904 PMCID: PMC10435767 DOI: 10.1016/j.ebiom.2023.104692] [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: 02/02/2023] [Revised: 06/15/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND People with Down syndrome (DS) show clinical signs of accelerated ageing. Causative mechanisms remain unknown and hypotheses range from the (essentially untreatable) amplified-chromosomal-instability explanation, to potential actions of individual supernumerary chromosome-21 genes. The latter explanation could open a route to therapeutic amelioration if the specific over-acting genes could be identified and their action toned-down. METHODS Biological age was estimated through patterns of sugar molecules attached to plasma immunoglobulin-G (IgG-glycans, an established "biological-ageing-clock") in n = 246 individuals with DS from three European populations, clinically characterised for the presence of co-morbidities, and compared to n = 256 age-, sex- and demography-matched healthy controls. Isogenic human induced pluripotent stem cell (hiPSCs) models of full and partial trisomy-21 with CRISPR-Cas9 gene editing and two kinase inhibitors were studied prior and after differentiation to cerebral organoids. FINDINGS Biological age in adults with DS is (on average) 18.4-19.1 years older than in chronological-age-matched controls independent of co-morbidities, and this shift remains constant throughout lifespan. Changes are detectable from early childhood, and do not require a supernumerary chromosome, but are seen in segmental duplication of only 31 genes, along with increased DNA damage and decreased levels of LaminB1 in nucleated blood cells. We demonstrate that these cell-autonomous phenotypes can be gene-dose-modelled and pharmacologically corrected in hiPSCs and derived cerebral organoids. Using isogenic hiPSC models we show that chromosome-21 gene DYRK1A overdose is sufficient and necessary to cause excess unrepaired DNA damage. INTERPRETATION Explanation of hitherto observed accelerated ageing in DS as a developmental progeroid syndrome driven by DYRK1A overdose provides a target for early pharmacological preventative intervention strategies. FUNDING Main funding came from the "Research Cooperability" Program of the Croatian Science Foundation funded by the European Union from the European Social Fund under the Operational Programme Efficient Human Resources 2014-2020, Project PZS-2019-02-4277, and the Wellcome Trust Grants 098330/Z/12/Z and 217199/Z/19/Z (UK). All other funding is described in details in the "Acknowledgements".
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Affiliation(s)
- Aoife Murray
- Faculty of Medicine and Dentistry, Blizard Institute, Queen Mary University of London, London, UK; The London Down Syndrome Consortium (LonDownS), London, UK.
| | - Gillian Gough
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Ana Cindrić
- Glycoscience Research Laboratory, Genos Ltd., Zagreb, Croatia
| | - Frano Vučković
- Glycoscience Research Laboratory, Genos Ltd., Zagreb, Croatia
| | - David Koschut
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Disease Intervention Technology Laboratory (DITL), Institute of Molecular and Cellular Biology (IMCB), Agency for Science, Technology and Research (A∗STAR), Singapore
| | - Vincenzo Borelli
- Department of Medical and Surgical Sciences, Alma Mater Studiorum University of Bologna, Italy
| | - Dražen J Petrović
- Glycoscience Research Laboratory, Genos Ltd., Zagreb, Croatia; Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ana Bekavac
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ante Plećaš
- Faculty of Veterinary Medicine, Department of Anatomy, Histology and Embryology, University of Zagreb, Zagreb, Croatia
| | - Valentina Hribljan
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Reinhard Brunmeir
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Julija Jurić
- Glycoscience Research Laboratory, Genos Ltd., Zagreb, Croatia
| | | | - Anita Slana
- Glycoscience Research Laboratory, Genos Ltd., Zagreb, Croatia
| | - Helena Deriš
- Glycoscience Research Laboratory, Genos Ltd., Zagreb, Croatia
| | - Azra Frkatović
- Glycoscience Research Laboratory, Genos Ltd., Zagreb, Croatia
| | - Jűrgen Groet
- Faculty of Medicine and Dentistry, Blizard Institute, Queen Mary University of London, London, UK; The London Down Syndrome Consortium (LonDownS), London, UK
| | - Niamh L O'Brien
- Faculty of Medicine and Dentistry, Blizard Institute, Queen Mary University of London, London, UK; The London Down Syndrome Consortium (LonDownS), London, UK
| | - Hong Yu Chen
- Institute of Molecular and Cell Biology (IMCB), A∗STAR, Singapore
| | - Yee Jie Yeap
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Frederic Delom
- Faculty of Medicine and Dentistry, Blizard Institute, Queen Mary University of London, London, UK
| | - Steven Havlicek
- Laboratory of Neurogenetics, Genome Institute of Singapore, A∗STAR, Singapore
| | - Luke Gammon
- Faculty of Medicine and Dentistry, Blizard Institute, Queen Mary University of London, London, UK
| | - Sarah Hamburg
- The London Down Syndrome Consortium (LonDownS), London, UK
| | - Carla Startin
- The London Down Syndrome Consortium (LonDownS), London, UK; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Division of Psychiatry, University College London, London, UK; School of Psychology, University of Roehampton, London, UK
| | - Hana D'Souza
- The London Down Syndrome Consortium (LonDownS), London, UK; Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Dinko Mitrečić
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Mijana Kero
- Department of Medical Genetics, Children's Hospital Zagreb, Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ljubica Odak
- Department of Medical Genetics, Children's Hospital Zagreb, Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Božo Krušlin
- Department of Pathology, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Željka Krsnik
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ivica Kostović
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Jia Nee Foo
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Laboratory of Neurogenetics, Genome Institute of Singapore, A∗STAR, Singapore
| | - Yuin-Han Loh
- Institute of Molecular and Cell Biology (IMCB), A∗STAR, Singapore
| | - Norris Ray Dunn
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Institute of Molecular and Cell Biology (IMCB), A∗STAR, Singapore
| | - Susana de la Luna
- ICREA, Genome Biology Programme (CRG), Universitat Pompeu Fabra (UPF), CIBER of Rare Diseases, Barcelona, Spain
| | - Tim Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Ingeborg Barišić
- Department of Medical Genetics, Children's Hospital Zagreb, Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Michael S C Thomas
- The London Down Syndrome Consortium (LonDownS), London, UK; Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Andre Strydom
- The London Down Syndrome Consortium (LonDownS), London, UK; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Division of Psychiatry, University College London, London, UK
| | - Claudio Franceschi
- Department of Medical and Surgical Sciences, Alma Mater Studiorum University of Bologna, Italy; Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia
| | - Gordan Lauc
- Glycoscience Research Laboratory, Genos Ltd., Zagreb, Croatia; Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | | | - Ivan Alić
- Faculty of Medicine and Dentistry, Blizard Institute, Queen Mary University of London, London, UK; Faculty of Veterinary Medicine, Department of Anatomy, Histology and Embryology, University of Zagreb, Zagreb, Croatia.
| | - Dean Nižetić
- Faculty of Medicine and Dentistry, Blizard Institute, Queen Mary University of London, London, UK; The London Down Syndrome Consortium (LonDownS), London, UK; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
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Fukami-Gartner A, Baburamani AA, Dimitrova R, Patkee PA, Ojinaga-Alfageme O, Bonthrone AF, Cromb D, Uus AU, Counsell SJ, Hajnal JV, O’Muircheartaigh J, Rutherford MA. Comprehensive volumetric phenotyping of the neonatal brain in Down syndrome. Cereb Cortex 2023; 33:8921-8941. [PMID: 37254801 PMCID: PMC10350827 DOI: 10.1093/cercor/bhad171] [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: 01/17/2023] [Revised: 04/28/2023] [Accepted: 04/29/2023] [Indexed: 06/01/2023] Open
Abstract
Down syndrome (DS) is the most common genetic cause of intellectual disability with a wide range of neurodevelopmental outcomes. To date, there have been very few in vivo neuroimaging studies of the neonatal brain in DS. In this study we used a cross-sectional sample of 493 preterm- to term-born control neonates from the developing Human Connectome Project to perform normative modeling of regional brain tissue volumes from 32 to 46 weeks postmenstrual age, accounting for sex and age variables. Deviation from the normative mean was quantified in 25 neonates with DS with postnatally confirmed karyotypes from the Early Brain Imaging in DS study. Here, we provide the first comprehensive volumetric phenotyping of the neonatal brain in DS, which is characterized by significantly reduced whole brain, cerebral white matter, and cerebellar volumes; reduced relative frontal and occipital lobar volumes, in contrast with enlarged relative temporal and parietal lobar volumes; enlarged relative deep gray matter volume (particularly the lentiform nuclei); and enlargement of the lateral ventricles, amongst other features. In future, the ability to assess phenotypic severity at the neonatal stage may help guide early interventions and, ultimately, help improve neurodevelopmental outcomes in children with DS.
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Affiliation(s)
- Abi Fukami-Gartner
- 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, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, United Kingdom
| | - Ana A Baburamani
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, United Kingdom
| | - Prachi A Patkee
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Olatz Ojinaga-Alfageme
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London WC1E 7HX, United Kingdom
| | - Alexandra F Bonthrone
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Alena U Uus
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Jonathan O’Muircheartaigh
- 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, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, United Kingdom
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, United Kingdom
| | - Mary A Rutherford
- 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, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, United Kingdom
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7
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de Matos K, Cury C, Chougar L, Strike LT, Rolland T, Riche M, Hemforth L, Martin A, Banaschewski T, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Paillère Martinot ML, Artiges E, Nees F, Papadopoulos Orfanos D, Lemaitre H, Paus T, Poustka L, Hohmann S, Millenet S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Frouin V, Bach Cuadra M, Colliot O, Couvy-Duchesne B. Temporo-basal sulcal connections: a manual annotation protocol and an investigation of sexual dimorphism and heritability. Brain Struct Funct 2023; 228:1459-1478. [PMID: 37358662 DOI: 10.1007/s00429-023-02663-6] [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: 01/31/2023] [Accepted: 06/07/2023] [Indexed: 06/27/2023]
Abstract
The temporo-basal region of the human brain is composed of the collateral, the occipito-temporal, and the rhinal sulci. We manually rated (using a novel protocol) the connections between rhinal/collateral (RS-CS), collateral/occipito-temporal (CS-OTS) and rhinal/occipito-temporal (RS-OTS) sulci, using the MRI of nearly 3400 individuals including around 1000 twins. We reported both the associations between sulcal polymorphisms as well with a wide range of demographics (e.g. age, sex, handedness). Finally, we also estimated the heritability, and the genetic correlation between sulcal connections. We reported the frequency of the sulcal connections in the general population, which were hemisphere dependent. We found a sexual dimorphism of the connections, especially marked in the right hemisphere, with a CS-OTS connection more frequent in females (approximately 35-40% versus 20-25% in males) and an RS-CS connection more common in males (approximately 40-45% versus 25-30% in females). We confirmed associations between sulcal connections and characteristics of incomplete hippocampal inversion (IHI). We estimated the broad sense heritability to be 0.28-0.45 for RS-CS and CS-OTS connections, with hints of dominant contribution for the RS-CS connection. The connections appeared to share some of their genetic causing factors as indicated by strong genetic correlations. Heritability appeared much smaller for the (rarer) RS-OTS connection.
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Affiliation(s)
- Kevin de Matos
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, 75013, Paris, France
- CIBM Center for Biomedical Imaging, Vaud, Switzerland
- Radiology Department, Lausanne University and University Hospital, Lausanne, Switzerland
| | - Claire Cury
- CNRS, Inria, Inserm, IRISA UMR 6074, Empenn ERL U-1228, University of Rennes, 35000, Rennes, France
| | - Lydia Chougar
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, 75013, Paris, France
- Service de neuroradiologie, AP-HP, Pitié-Salpêtrière, Paris, France
| | - Lachlan T Strike
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD, 4072, Australia
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Thibault Rolland
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, 75013, Paris, France
| | - Maximilien Riche
- Department of Neurosurgery, AP-HP, La Pitié-Salpêtrière Hospital, Sorbonne University, 75013, Paris, France
| | - Lisa Hemforth
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, 75013, Paris, France
| | - Alexandre Martin
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, 75013, Paris, France
- Inria Sophia Antipolis, Morpheme Project, Paris, France
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, 05405, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Berlin Institute of Health, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Brunswick, Berlin, Germany
| | - Jean-Luc Martinot
- INSERM U 1299 "Trajectoires développementales & psychiatrie", CNRS, Institut National de la Santé et de la Recherche Médicale, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, University Paris-Saclay, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- INSERM U 1299 "Trajectoires développementales & psychiatrie", CNRS, AP-HP, Institut National de la Santé et de la Recherche Médicale, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, University Paris-Saclay, Gif-sur-Yvette, France
- Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
| | - Eric Artiges
- INSERM U 1299 "Trajectoires développementales & psychiatrie", CNRS, Institut National de la Santé et de la Recherche Médicale, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, University Paris-Saclay, Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, 68159, Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Herve Lemaitre
- NeuroSpin, CEA, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
- UMR 5293, CNRS, CEA, Institut des Maladies Neurodégénératives, Université de Bordeaux, 33076, Bordeaux, France
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Université de Montréal and Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, ON, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Department of Psychiatry and Neuroscience, Centre for Population Neuroscience and Stratified Medicine (PONS), Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Berlin Institute of Health, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Department of Psychiatry and Neuroscience, Centre for Population Neuroscience and Stratified Medicine (PONS), Charité Universitätsmedizin Berlin, Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Vincent Frouin
- NeuroSpin, CEA, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Vaud, Switzerland
- Radiology Department, Lausanne University and University Hospital, Lausanne, Switzerland
| | - Olivier Colliot
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, 75013, Paris, France
| | - Baptiste Couvy-Duchesne
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, 75013, Paris, France.
- Institute for Molecular Biosciences, The University of Queensland, St Lucia, QLD, 4062, Australia.
- ARAMIS Team, Pitié-Salpêtrière Hospital, Institut du Cerveau, 75013, Paris, France.
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8
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Watson LA, Meharena HS. From neurodevelopment to neurodegeneration: utilizing human stem cell models to gain insight into Down syndrome. Front Genet 2023; 14:1198129. [PMID: 37323671 PMCID: PMC10267712 DOI: 10.3389/fgene.2023.1198129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/09/2023] [Indexed: 06/17/2023] Open
Abstract
Down syndrome (DS), caused by triplication of chromosome 21, is the most frequent aneuploidy observed in the human population and represents the most common genetic form of intellectual disability and early-onset Alzheimer's disease (AD). Individuals with DS exhibit a wide spectrum of clinical presentation, with a number of organs implicated including the neurological, immune, musculoskeletal, cardiac, and gastrointestinal systems. Decades of DS research have illuminated our understanding of the disorder, however many of the features that limit quality of life and independence of individuals with DS, including intellectual disability and early-onset dementia, remain poorly understood. This lack of knowledge of the cellular and molecular mechanisms leading to neurological features of DS has caused significant roadblocks in developing effective therapeutic strategies to improve quality of life for individuals with DS. Recent technological advances in human stem cell culture methods, genome editing approaches, and single-cell transcriptomics have provided paradigm-shifting insights into complex neurological diseases such as DS. Here, we review novel neurological disease modeling approaches, how they have been used to study DS, and what questions might be addressed in the future using these innovative tools.
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9
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de Vareilles H, Rivière D, Mangin JF, Dubois J. Development of cortical folds in the human brain: An attempt to review biological hypotheses, early neuroimaging investigations and functional correlates. Dev Cogn Neurosci 2023; 61:101249. [PMID: 37141790 DOI: 10.1016/j.dcn.2023.101249] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/28/2023] [Accepted: 04/21/2023] [Indexed: 05/06/2023] Open
Abstract
The folding of the human brain mostly takes place in utero, making it challenging to study. After a few pioneer studies looking into it in post-mortem foetal specimen, modern approaches based on neuroimaging have allowed the community to investigate the folding process in vivo, its normal progression, its early disturbances, and its relationship to later functional outcomes. In this review article, we aimed to first give an overview of the current hypotheses on the mechanisms governing cortical folding. After describing the methodological difficulties raised by its study in fetuses, neonates and infants with magnetic resonance imaging (MRI), we reported our current understanding of sulcal pattern emergence in the developing brain. We then highlighted the functional relevance of early sulcal development, through recent insights about hemispheric asymmetries and early factors influencing this dynamic such as prematurity. Finally, we outlined how longitudinal studies have started to relate early folding markers and the child's sensorimotor and cognitive outcome. Through this review, we hope to raise awareness on the potential of studying early sulcal patterns both from a fundamental and clinical perspective, as a window into early neurodevelopment and plasticity in relation to growth in utero and postnatal environment of the child.
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Affiliation(s)
- H de Vareilles
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, CNRS, Gif-sur-Yvette, France.
| | - D Rivière
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, CNRS, Gif-sur-Yvette, France
| | - J F Mangin
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, CNRS, Gif-sur-Yvette, France
| | - J Dubois
- Université Paris Cité, NeuroDiderot, Inserm, Paris, France; Université Paris-Saclay, NeuroSpin-UNIACT, CEA, Gif-sur-Yvette, France
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10
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Yun HJ, Lee HJ, Lee JY, Tarui T, Rollins CK, Ortinau CM, Feldman HA, Grant PE, Im K. Quantification of sulcal emergence timing and its variability in early fetal life: Hemispheric asymmetry and sex difference. Neuroimage 2022; 263:119629. [PMID: 36115591 PMCID: PMC10011016 DOI: 10.1016/j.neuroimage.2022.119629] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 08/07/2022] [Accepted: 09/12/2022] [Indexed: 12/25/2022] Open
Abstract
Human fetal brains show regionally different temporal patterns of sulcal emergence following a regular timeline, which may be associated with spatiotemporal patterns of gene expression among cortical regions. This study aims to quantify the timing of sulcal emergence and its temporal variability across typically developing fetuses by fitting a logistic curve to presence or absence of sulcus. We found that the sulcal emergence started from the central to the temporo-parieto-occipital lobes and frontal lobe, and the temporal variability of emergence in most of the sulci was similar between 1 and 2 weeks. Small variability (< 1 week) was found in the left central and postcentral sulci and larger variability (>2 weeks) was shown in the bilateral occipitotemporal and left superior temporal sulci. The temporal variability showed a positive correlation with the emergence timing that may be associated with differential contributions between genetic and environmental factors. Our statistical analysis revealed that the right superior temporal sulcus emerged earlier than the left. Female fetuses showed a trend of earlier sulcal emergence in the right superior temporal sulcus, lower temporal variability in the right intraparietal sulcus, and higher variability in the right precentral sulcus compared to male fetuses. Our quantitative and statistical approach quantified the temporal patterns of sulcal emergence in detail that can be a reference for assessing the normality of developing fetal gyrification.
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Affiliation(s)
- Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Hyun Ju Lee
- Department of Pediatrics, Hanyang University College of Medicine, Seoul 04763, Korea (the Republic of)
| | - Joo Young Lee
- Department of Pediatrics, Hanyang University College of Medicine, Seoul 04763, Korea (the Republic of)
| | - Tomo Tarui
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA 02115, United States
| | - Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63130, United States
| | - Henry A Feldman
- Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States; Institutional Centers for Clinical and Translational Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - P Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States; Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States.
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11
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Stagni F, Bartesaghi R. The Challenging Pathway of Treatment for Neurogenesis Impairment in Down Syndrome: Achievements and Perspectives. Front Cell Neurosci 2022; 16:903729. [PMID: 35634470 PMCID: PMC9130961 DOI: 10.3389/fncel.2022.903729] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 04/19/2022] [Indexed: 12/17/2022] Open
Abstract
Down syndrome (DS), also known as trisomy 21, is a genetic disorder caused by triplication of Chromosome 21. Gene triplication may compromise different body functions but invariably impairs intellectual abilities starting from infancy. Moreover, after the fourth decade of life people with DS are likely to develop Alzheimer’s disease. Neurogenesis impairment during fetal life stages and dendritic pathology emerging in early infancy are thought to be key determinants of alterations in brain functioning in DS. Although the progressive improvement in medical care has led to a notable increase in life expectancy for people with DS, there are currently no treatments for intellectual disability. Increasing evidence in mouse models of DS reveals that pharmacological interventions in the embryonic and neonatal periods may greatly benefit brain development and cognitive performance. The most striking results have been obtained with pharmacotherapies during embryonic life stages, indicating that it is possible to pharmacologically rescue the severe neurodevelopmental defects linked to the trisomic condition. These findings provide hope that similar benefits may be possible for people with DS. This review summarizes current knowledge regarding (i) the scope and timeline of neurogenesis (and dendritic) alterations in DS, in order to delineate suitable windows for treatment; (ii) the role of triplicated genes that are most likely to be the key determinants of these alterations, in order to highlight possible therapeutic targets; and (iii) prenatal and neonatal treatments that have proved to be effective in mouse models, in order to rationalize the choice of treatment for human application. Based on this body of evidence we will discuss prospects and challenges for fetal therapy in individuals with DS as a potential means of drastically counteracting the deleterious effects of gene triplication.
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Affiliation(s)
- Fiorenza Stagni
- Department for Life Quality Studies, University of Bologna, Rimini, Italy
| | - Renata Bartesaghi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- *Correspondence: Renata Bartesaghi,
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12
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Akiyama S, Madan N, Graham G, Samura O, Kitano R, Yun HJ, Craig A, Nakamura T, Hozawa A, Grant E, Im K, Tarui T. Regional brain development in fetuses with Dandy-Walker malformation: A volumetric fetal brain magnetic resonance imaging study. PLoS One 2022; 17:e0263535. [PMID: 35202430 PMCID: PMC8870580 DOI: 10.1371/journal.pone.0263535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 01/20/2022] [Indexed: 11/18/2022] Open
Abstract
Dandy-Walker malformation (DWM) is a common prenatally diagnosed cerebellar malformation, characterized by cystic dilatation of the fourth ventricle, upward rotation of the hypoplastic vermis, and posterior fossa enlargement with torcular elevation. DWM is associated with a broad spectrum of neurodevelopmental abnormalities such as cognitive, motor, and behavioral impairments, which cannot be explained solely by cerebellar malformations. Notably, the pathogenesis of these symptoms remains poorly understood. This study investigated whether fetal structural developmental abnormalities in DWM extended beyond the posterior fossa to the cerebrum even in fetuses without apparent cerebral anomalies. Post-acquisition volumetric fetal magnetic resonance imaging (MRI) analysis was performed in 12 fetuses with DWM and 14 control fetuses. Growth trajectories of the volumes of the cortical plate, subcortical parenchyma, cerebellar hemispheres, and vermis between 18 and 33 weeks of gestation were compared. The median (interquartile range) gestational ages at the time of MRI were 22.4 (19.4–24.0) and 23.9 (20.6–29.2) weeks in the DWM and control groups, respectively (p = 0.269). Eight of the 12 fetuses with DWM presented with associated cerebral anomalies, including hydrocephalus (n = 3), cerebral ventriculomegaly (n = 3), and complete (n = 2) and partial (n = 2) agenesis of the corpus callosum (ACC); 7 presented with extracerebral abnormalities. Chromosomal abnormalities were detected by microarray analysis in 4 of 11 fetuses with DWM, using amniocentesis. Volumetric analysis revealed that the cortical plate was significantly larger in fetuses with DWM than in controls (p = 0.040). Even without ACC, the subcortical parenchyma, whole cerebrum, cerebellar hemispheres, and whole brain were significantly larger in fetuses with DWM (n = 8) than in controls (p = 0.004, 0.025, 0.033, and 0.026, respectively). In conclusion, volumetric fetal MRI analysis demonstrated that the development of DWM extends throughout the brain during the fetal period, even without apparent cerebral anomalies.
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Affiliation(s)
- Shizuko Akiyama
- Mother Infant Research Institute, Tufts Medical Center, Boston, Massachusetts, United States of America
- * E-mail: (SA); (TT)
| | - Neel Madan
- Radiology, Tufts Medical Center, Boston, Massachusetts, United States of America
| | - George Graham
- Obstetrics and Gynecology, Tufts Medical Center, Boston, Massachusetts, United States of America
| | - Osamu Samura
- Obstetrics and Gynecology, Jikei University School of Medicine, Tokyo, Japan
| | - Rie Kitano
- Mother Infant Research Institute, Tufts Medical Center, Boston, Massachusetts, United States of America
| | - Hyuk Jin Yun
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, Massachusetts, United States of America
| | - Alexa Craig
- Pediatric Neurology, Maine Medical Center, Portland, Oregan, United States of America
| | - Tomohiro Nakamura
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Atsushi Hozawa
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, Massachusetts, United States of America
| | - Kiho Im
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, Massachusetts, United States of America
| | - Tomo Tarui
- Mother Infant Research Institute, Tufts Medical Center, Boston, Massachusetts, United States of America
- Pediatric Neurology, Tufts Children’s Hospital, Boston, Massachusetts, United States of America
- * E-mail: (SA); (TT)
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13
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Hong J, Yun HJ, Park G, Kim S, Ou Y, Vasung L, Rollins CK, Ortinau CM, Takeoka E, Akiyama S, Tarui T, Estroff JA, Grant PE, Lee JM, Im K. Optimal Method for Fetal Brain Age Prediction Using Multiplanar Slices From Structural Magnetic Resonance Imaging. Front Neurosci 2021; 15:714252. [PMID: 34707474 PMCID: PMC8542770 DOI: 10.3389/fnins.2021.714252] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 09/08/2021] [Indexed: 11/23/2022] Open
Abstract
The accurate prediction of fetal brain age using magnetic resonance imaging (MRI) may contribute to the identification of brain abnormalities and the risk of adverse developmental outcomes. This study aimed to propose a method for predicting fetal brain age using MRIs from 220 healthy fetuses between 15.9 and 38.7 weeks of gestational age (GA). We built a 2D single-channel convolutional neural network (CNN) with multiplanar MRI slices in different orthogonal planes without correction for interslice motion. In each fetus, multiple age predictions from different slices were generated, and the brain age was obtained using the mode that determined the most frequent value among the multiple predictions from the 2D single-channel CNN. We obtained a mean absolute error (MAE) of 0.125 weeks (0.875 days) between the GA and brain age across the fetuses. The use of multiplanar slices achieved significantly lower prediction error and its variance than the use of a single slice and a single MRI stack. Our 2D single-channel CNN with multiplanar slices yielded a significantly lower stack-wise MAE (0.304 weeks) than the 2D multi-channel (MAE = 0.979, p < 0.001) and 3D (MAE = 1.114, p < 0.001) CNNs. The saliency maps from our method indicated that the anatomical information describing the cortex and ventricles was the primary contributor to brain age prediction. With the application of the proposed method to external MRIs from 21 healthy fetuses, we obtained an MAE of 0.508 weeks. Based on the external MRIs, we found that the stack-wise MAE of the 2D single-channel CNN (0.743 weeks) was significantly lower than those of the 2D multi-channel (1.466 weeks, p < 0.001) and 3D (1.241 weeks, p < 0.001) CNNs. These results demonstrate that our method with multiplanar slices accurately predicts fetal brain age without the need for increased dimensionality or complex MRI preprocessing steps.
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Affiliation(s)
- Jinwoo Hong
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Gilsoon Park
- USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States
| | - Seonggyu Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Yangming Ou
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Computational Health Informatics Program, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Lana Vasung
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, United States
| | - Emiko Takeoka
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, United States
| | - Shizuko Akiyama
- Center for Perinatal and Neonatal Medicine, Tohoku University Hospital, Sendai, Japan
| | - Tomo Tarui
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, United States
| | - Judy A Estroff
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Patricia Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
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Hong J, Yun HJ, Park G, Kim S, Laurentys CT, Siqueira LC, Tarui T, Rollins CK, Ortinau CM, Grant PE, Lee JM, Im K. Fetal Cortical Plate Segmentation Using Fully Convolutional Networks With Multiple Plane Aggregation. Front Neurosci 2020; 14:591683. [PMID: 33343286 PMCID: PMC7738480 DOI: 10.3389/fnins.2020.591683] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 11/04/2020] [Indexed: 01/14/2023] Open
Abstract
Fetal magnetic resonance imaging (MRI) has the potential to advance our understanding of human brain development by providing quantitative information of cortical plate (CP) development in vivo. However, for a reliable quantitative analysis of cortical volume and sulcal folding, accurate and automated segmentation of the CP is crucial. In this study, we propose a fully convolutional neural network for the automatic segmentation of the CP. We developed a novel hybrid loss function to improve the segmentation accuracy and adopted multi-view (axial, coronal, and sagittal) aggregation with a test-time augmentation method to reduce errors using three-dimensional (3D) information and multiple predictions. We evaluated our proposed method using the ten-fold cross-validation of 52 fetal brain MR images (22.9-31.4 weeks of gestation). The proposed method obtained Dice coefficients of 0.907 ± 0.027 and 0.906 ± 0.031 as well as a mean surface distance error of 0.182 ± 0.058 mm and 0.185 ± 0.069 mm for the left and right, respectively. In addition, the left and right CP volumes, surface area, and global mean curvature generated by automatic segmentation showed a high correlation with the values generated by manual segmentation (R 2 > 0.941). We also demonstrated that the proposed hybrid loss function and the combination of multi-view aggregation and test-time augmentation significantly improved the CP segmentation accuracy. Our proposed segmentation method will be useful for the automatic and reliable quantification of the cortical structure in the fetal brain.
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Affiliation(s)
- Jinwoo Hong
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Hyuk Jin Yun
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Gilsoon Park
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
| | - Seonggyu Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Cynthia T. Laurentys
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Leticia C. Siqueira
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Tomo Tarui
- Mother Infant Research Institute, Tufts Medical Center, Tufts University School of Medicine, Boston, MA, United States
- Department of Pediatrics, Tufts Medical Center, Tufts University School of Medicine, Boston, MA, United States
| | - Caitlin K. Rollins
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Cynthia M. Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, United States
| | - P. Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
| | - Kiho Im
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
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