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Mohammadi S, Ghaderi S. Advanced magnetic resonance neuroimaging techniques: feasibility and applications in long or post-COVID-19 syndrome - a review. Ann Med Surg (Lond) 2024; 86:1584-1589. [PMID: 38463042 PMCID: PMC10923379 DOI: 10.1097/ms9.0000000000001808] [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: 11/16/2023] [Accepted: 01/29/2024] [Indexed: 03/12/2024] Open
Abstract
Long-term or post-COVID-19 syndrome (PCS) is a condition that affects people infected with SARS‑CoV‑2, the virus that causes COVID-19. PCS is characterized by a wide range of persistent or new symptoms that last months after the initial infection, such as fatigue, shortness of breath, cognitive dysfunction, and pain. Advanced magnetic resonance (MR) neuroimaging techniques can provide valuable information on the structural and functional changes in the brain associated with PCS as well as potential biomarkers for diagnosis and prognosis. In this review, we discuss the feasibility and applications of various advanced MR neuroimaging techniques in PCS, including perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), functional MR imaging (fMRI), diffusion tensor imaging (DTI), and tractography. We summarize the current evidence on neuroimaging findings in PCS, the challenges and limitations of these techniques, and the future directions for research and clinical practice. Although still uncertain, advanced MRI techniques show promise for gaining insight into the pathophysiology and guiding the management of COVID-19 syndrome, pending larger validation studies.
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Affiliation(s)
- Sana Mohammadi
- Department of Medical Sciences, School of Medicine, Iran University of Medical Sciences
| | - Sadegh Ghaderi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
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Vinçon-Leite A, Saitovitch A, Lemaître H, Rechtman E, Boisgontier J, Fillon L, Philippe A, Rio M, Desguerre I, Fabre A, Aljabali K, Boddaert N, Zilbovicius M. Identifying interindividual variability of social perception and associated brain anatomical correlations in children with autism spectrum disorder using eye-tracking and diffusion tensor imaging MRI (DTI-MRI). Cereb Cortex 2024; 34:bhad434. [PMID: 38037470 PMCID: PMC10793563 DOI: 10.1093/cercor/bhad434] [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: 06/22/2023] [Accepted: 10/24/2023] [Indexed: 12/02/2023] Open
Abstract
Even though deficits in social cognition constitute a core characteristic of autism spectrum disorders, a large heterogeneity exists regarding individual social performances and its neural basis remains poorly investigated. Here, we used eye-tracking to objectively measure interindividual variability in social perception and its correlation with white matter microstructure, measured with diffusion tensor imaging MRI, in 25 children with autism spectrum disorder (8.5 ± 3.8 years). Beyond confirming deficits in social perception in participants with autism spectrum disorder compared 24 typically developing controls (10.5 ± 2.9 years), results revealed a large interindividual variability of such behavior among individuals with autism spectrum disorder. Whole-brain analysis showed in both autism spectrum disorder and typically developing groups a positive correlation between number of fixations to the eyes and fractional anisotropy values mainly in right and left superior longitudinal tracts. In children with autism spectrum disorder a correlation was also observed in right and left inferior longitudinal tracts. Importantly, a significant interaction between group and number of fixations to the eyes was observed within the anterior portion of the right inferior longitudinal fasciculus, mainly in the right anterior temporal region. This additional correlation in a supplementary region suggests the existence of a compensatory brain mechanism, which may support enhanced performance in social perception among children with autism spectrum disorder.
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Affiliation(s)
- Alice Vinçon-Leite
- Institut Imagine, UMR 1163, INSERM U1299, Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris Cité, 75015 Paris, France
- Department for Autism, SATORI, Henri Guérin Hospital, Pierrefeu du Var 83390, France
| | - Ana Saitovitch
- Institut Imagine, UMR 1163, INSERM U1299, Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris Cité, 75015 Paris, France
| | - Herve Lemaître
- Institut des Maladies Neurodégénératives, CNRS UMR 5293, Université de bordeaux, Centre Broca Nouvelle-Aquitaine, Bordeaux, France
| | - Elza Rechtman
- Department of Environmental Medicine and Public Health, Icahn School of Medecine at Mount Sinai, New York, NY 10029, United States
| | - Jennifer Boisgontier
- Institut Imagine, UMR 1163, INSERM U1299, Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris Cité, 75015 Paris, France
| | - Ludovic Fillon
- Institut Imagine, UMR 1163, INSERM U1299, Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris Cité, 75015 Paris, France
| | - Anne Philippe
- Developmental Brain Disorders Laboratory, Imagine Institute, Université Paris Cité, 75015 Paris, France
| | - Marlène Rio
- Service de Médecine Génomique des Maladies Rares, Hôpital Necker-Enfants Malades, APHP-Centre, Paris, France. Laboratoire de génétique des troubles du neurodéveloppement, Institut Imagine, Université de Paris, 75015 Paris, France
| | - Isabelle Desguerre
- Paediatric Neurology Department, Necker-Enfants malades University Hospital, Assistance Publique Hôpitaux de Paris, Paris Cité University, 75015 Paris, France
| | - Aurélie Fabre
- Institut Imagine, UMR 1163, INSERM U1299, Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris Cité, 75015 Paris, France
| | - Khawla Aljabali
- Institut Imagine, UMR 1163, INSERM U1299, Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris Cité, 75015 Paris, France
| | - Nathalie Boddaert
- Institut Imagine, UMR 1163, INSERM U1299, Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris Cité, 75015 Paris, France
| | - Monica Zilbovicius
- Institut Imagine, UMR 1163, INSERM U1299, Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris Cité, 75015 Paris, France
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Feng Y, Chandio BQ, Thomopoulos SI, Chattopadhyay T, Thompson PM. Variational Autoencoders for Generating Synthetic Tractography-Based Bundle Templates in a Low-Data Setting. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-6. [PMID: 38083771 DOI: 10.1109/embc40787.2023.10340009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
White matter tracts generated from whole brain tractography are often processed using automatic segmentation methods with standard atlases. Atlases are generated from hundreds of subjects, which becomes time-consuming to create and difficult to apply to all populations. In this study, we extended our prior work on using a deep generative model - a Convolutional Variational Autoencoder - to map complex and data-intensive streamlines to a low-dimensional latent space given a limited sample size of 50 subjects from the ADNI3 dataset, to generate synthetic population-specific bundle templates using Kernel Density Estimation (KDE) on streamline embeddings. We conducted a quantitative shape analysis by calculating bundle shape metrics, and found that our bundle templates better capture the shape distribution of the bundles than the atlas data used in the original segmentation derived from young healthy adults. We further demonstrated the use of our framework for direct bundle segmentation from whole-brain tractograms.
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Estrada KA, Govindaraj S, Abdi H, Moraglia LE, Wolff JJ, Meera SS, Dager SR, McKinstry RC, Styner MA, Zwaigenbaum L, Piven J, Swanson MR. Language exposure during infancy is negatively associated with white matter microstructure in the arcuate fasciculus. Dev Cogn Neurosci 2023; 61:101240. [PMID: 37060675 PMCID: PMC10130606 DOI: 10.1016/j.dcn.2023.101240] [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: 10/30/2022] [Revised: 04/04/2023] [Accepted: 04/04/2023] [Indexed: 04/17/2023] Open
Abstract
Decades of research have established that the home language environment, especially quality of caregiver speech, supports language acquisition during infancy. However, the neural mechanisms behind this phenomenon remain under studied. In the current study, we examined associations between the home language environment and structural coherence of white matter tracts in 52 typically developing infants from English speaking homes in a western society. Infants participated in at least one MRI brain scan when they were 3, 6, 12, and/or 24 months old. Home language recordings were collected when infants were 9 and/or 15 months old. General linear regression models indicated that infants who heard the most adult words and participated in the most conversational turns at 9 months of age also had the lowest fractional anisotropy in the left posterior parieto-temporal arcuate fasciculus at 24 months. Similarly, infants who vocalized the most at 9 months also had the lowest fractional anisotropy in the same tract at 6 months of age. This is one of the first studies to report significant associations between caregiver speech collected in the home and white matter structural coherence in the infant brain. The results are in line with prior work showing that protracted white matter development during infancy confers a cognitive advantage.
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Affiliation(s)
- Katiana A Estrada
- Department of Psychological Sciences, Purdue University, West Lafayette, IN 47906, USA; Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Sharnya Govindaraj
- Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Hervé Abdi
- Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Luke E Moraglia
- Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Jason J Wolff
- Department of Educational Psychology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Shoba Sreenath Meera
- Department of Speech Pathology and Audiology, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, India
| | - Stephen R Dager
- Department of Radiology, University of Washington, Seattle, WA 98195, USA
| | - Robert C McKinstry
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63130, USA
| | - Martin A Styner
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Lonnie Zwaigenbaum
- Department of Pediatrics, University of Alberta, Edmonton AB T6G 2R3, Canada
| | - Joseph Piven
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Meghan R Swanson
- Department of Psychology, The University of Texas at Dallas, Richardson, TX 75080, USA.
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Feng Y, Chandio BQ, Thomopoulos SI, Chattopadhyay T, Thompson PM. Variational Autoencoders for Generating Synthetic Tractography-Based Bundle Templates in a Low-Data Setting. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.24.529954. [PMID: 36909490 PMCID: PMC10002615 DOI: 10.1101/2023.02.24.529954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
Abstract
White matter tracts generated from whole brain tractography are often processed using automatic segmentation methods with standard atlases. Atlases are generated from hundreds of subjects, which becomes time-consuming to create and difficult to apply to all populations. In this study, we extended our prior work on using a deep generative model a Convolutional Variational Autoencoder - to map complex and data-intensive streamlines to a low-dimensional latent space given a limited sample size of 50 subjects from the ADNI3 dataset, to generate synthetic population-specific bundle templates using Kernel Density Estimation (KDE) on streamline embeddings. We conducted a quantitative shape analysis by calculating bundle shape metrics, and found that our bundle templates better capture the shape distribution of the bundles than the atlas data used in the original segmentation derived from young healthy adults. We further demonstrated the use of our framework for direct bundle segmentation from whole-brain tractograms.
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Donovan SM, Abrams SA, Azad MB, Belfort MB, Bode L, Carlson SE, Dallas DC, Hettinga K, Järvinen K, Kim JH, Lebrilla CB, McGuire MK, Sela DA, Neu J. Summary of the joint National Institutes of Health and the Food and Drug Administration workshop titled "exploring the science surrounding the safe use of bioactive ingredients in infant formula: Considerations for an assessment framework". J Pediatr 2022; 255:30-41.e1. [PMID: 36463938 PMCID: PMC10121942 DOI: 10.1016/j.jpeds.2022.11.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 10/20/2022] [Accepted: 11/18/2022] [Indexed: 12/03/2022]
Affiliation(s)
- Sharon M Donovan
- Department of Food Science and Human Nutrition, University of Illinois, Urbana, IL
| | - Steven A Abrams
- Department of Pediatrics Dell Medical School, The University of Texas at Austin, Austin, TX
| | - Meghan B Azad
- Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, Canada; Manitoba Interdisciplinary Lactation Centre (MILC), Children's Hospital Research Institute of Manitoba, Winnipeg, Canada
| | - Mandy B Belfort
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Lars Bode
- Department of Pediatrics and Mother-Milk-Infant Center of Research Excellence (MOMI CORE), University of California, San Diego, La Jolla, CA
| | - Susan E Carlson
- Department of Dietetics and Nutrition, Kansas University Medical Center and The University of Kansas, Kansas City, KS
| | - David C Dallas
- Department of Nutrition, Oregon State University, Corvallis, OR
| | - Kasper Hettinga
- Department of Food Sciences and Agrotechnology, Wageningen University, Wageningen, Netherlands
| | - Kirsi Järvinen
- Department of Pediatrics, Golisano Children's Hospital and University of Rochester School of Medicine and Dentistry, Rochester, NY
| | - Jae H Kim
- Perinatal Institute, Department of Pediatrics, Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, OH
| | | | | | - David A Sela
- Department of Food Science, University of Massachusetts, Amherst, Amherst, MA
| | - Josef Neu
- Department of Pediatrics, University of Florida, Gainesville, FL.
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