ArticleNeuroImage. Clinical2015
Detection of demyelination in multiple sclerosis by analysis of [Formula: see text] relaxation at 7 T.
Article in NeuroImage. Clinical, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
13 citing papers in PubMed, 23 citations in OpenAlex.
- Preparation and In vitro/In vivo Evaluation of Fingolimod hydrochloride Loaded Polymeric Mixed Nano-Micelles for Treatment of Multiple Sclerosis.Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology · 2025Article
- Deep learning-based super-resolution of structural brain MRI at 1.5 T: application to quantitative volume measurement.Magma (New York, N.Y.) · 2024Article
- The use of 7T MRI in multiple sclerosis: review and consensus statement from the North American Imaging in Multiple Sclerosis Cooperative.Brain communications · 2024Review
- Advances in differential diagnosis of cerebrovascular diseases in magnetic resonance imaging: a narrative review.Quantitative imaging in medicine and surgery · 2023Review
- Elevated IL-38 Serum Levels in Newly Diagnosed Multiple Sclerosis and Systemic Sclerosis Patients.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2021Article
- Multi-compartment analysis of the complex gradient-echo signal quantifies myelin breakdown in premanifest Huntington's disease.NeuroImage. Clinical · 2021Article
- Article
- Influence of 7T GRE-MRI Signal Compartment Model Choice on Tissue Parameters.Frontiers in neuroscience · 2020Article
- White matter intercompartmental water exchange rates determined from detailed modeling of the myelin sheath.Magnetic resonance in medicine · 2019Article
- Review
- Insights from Ultrahigh Field Imaging in Multiple Sclerosis.Neuroimaging clinics of North America · 2017Review
- Exploring the origins of echo-time-dependent quantitative susceptibility mapping (QSM) measurements in healthy tissue and cerebral microbleeds.NeuroImage · 2017Article
- Contributions to magnetic susceptibility of brain tissue.NMR in biomedicine · 2017Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Multiple sclerosis (MS) is a relatively common cause of inflammatory demyelinating lesions of the central nervous system. In an attempt to detect and characterize ongoing demyelination in MS patient brains, we used a novel magnetic resonance imaging (MRI) technique, involving the fitting of a three-component model to the [Formula: see text] relaxation behavior at high-field (7 T). This model allowed estimation of the amount of myelin water (and thus indirectly myelin content), axonal water, and interstitial water. In this study, 25 relapsing-remitting MS patients underwent a 7 T MRI from which 12 gadolinium-enhancing lesions, 61 non-enhancing lesions, and their corresponding contralateral normal appearing white matter (NAWM) regions were analyzed. In both enhancing and non-enhancing lesions, the amplitude of myelin water was significantly decreased, and interstitial and axonal water were increased relative to the contralateral NAWM. Longer relaxation time [Formula: see text] of interstitial and axonal water, and lower frequency shift of axonal water, were also observed in both enhancing and non-enhancing lesions when compared to the contralateral NAWM. No significant difference was found between enhancing lesions and non-enhancing lesions. These findings suggest that the fitting of a three-component model to the [Formula: see text] decay curve in MS lesions may help to quantify myelin loss.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.