Ultra-sensitive molecular MRI of cerebrovascular cell activation enables early detection of chronic central nervous system disorders
Open accessAbstract
Since endothelial cells can be targeted by large contrast-carrying particles, molecular imaging of cerebrovascular cell activation is highly promising to evaluate the underlying inflammation of the central nervous system (CNS). In this study, we aimed to demonstrate that molecular magnetic resonance imaging (MRI) of cerebrovascular cell activation can reveal CNS disorders in the absence of visible lesions and symptoms. To this aim, we optimized contrast carrying particles targeting vascular cell adhesion molecule-1 and MRI protocols through both in vitro and in vivo experiments. Although, pre-contrast MRI images failed to reveal the ongoing pathology, contrast-enhanced MRI revealed hypoperfusion-triggered CNS injury in vascular dementia, unmasked amyloid-induced cerebrovascular activation in Alzheimer's disease and allowed monitoring of disease activity during experimental autoimmune encephalomyelitis. Moreover, contrast-enhanced MRI revealed the cerebrovascular cell activation associated with known risk factors of CNS disorders such as peripheral inflammation, ethanol consumption, hyperglycemia and aging. By providing a dramatically higher sensitivity than previously reported methods and molecular contrast agents, the technology described in the present study opens new avenues of investigation in the field of neuroinflammation.
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AntiVCAM-1 iron oxide microparticles have been used in animal models to detect endothelial activation and/or inflammation by MRI.
“like antiVCAM-1 iron oxide microparticles to detect endothelial activation and/or inflammation by MRI (417)”
From Blood-Brain Barrier: From Physiology to Disease and Back (2019) · cites this paper as [417]
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Self-citation
- Authors
- Montagne, A., Gauberti, M., Macrez, R., Jullienne, A., Briens, A., Raynaud, J.-S., Louin, G., Buisson, A., Haelewyn, B., Docagne, F., Defer, G., Vivien, D., & Maubert, E.
- Affiliations
- Inserm (FR)
- Guerbet (France) (FR)
- Corresponding author
- Vivien, Denis
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-11
- Volume
- 63
- Issue
- 2
- Pages
- 760-770
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1965461188
- Cited by
- 70
- References
- 19
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 5 · 2022: 8 · 2021: 6 · 2020: 6 · 2019: 4 · 2018: 13 · 2017: 3 · 2016: 6 · 2015: 6 · 2014: 4 · 2013: 5
- FWCI
- 3.62
- Type
- journal article
- Language
- en
- Open access
- green
- zenodo.org
- Licence
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
- Funders
- Institut National de la Santé Et de la Recherche Médicale (INSERM)
- Conseil Régional de Basse-Normandie (CRBN)
- Guerbet
- CRBN
- INSERM
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Neurology › Barrier Structure and Function Studies
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- molecular MRI, VCAM-1, contrast media, neuroinflammation, vascular dementia, Alzheimer's disease, amyloid, experimental autoimmune encephalomyelitis, hypoperfusion, peripheral inflammation, ethanol consumption, hyperglycemia, aging
- MeSH terms
- Animals, Central Nervous System Diseases, Ferric Compounds, Immunohistochemistry, Magnetic Resonance Imaging, Male, Mice, Inbred C57BL, Blotting, Western, Reverse Transcriptase Polymerase Chain Reaction, Endothelial Cells, Mice, Metal Nanoparticles, Molecular Imaging, Real-Time Polymerase Chain Reaction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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