4 years ago

Prediction of disease activity in models of multiple sclerosis by molecular magnetic resonance imaging of P-selectin [Neuroscience]

Prediction of disease activity in models of multiple sclerosis by molecular magnetic resonance imaging of P-selectin [Neuroscience]
Antoine Philippe Fournier, Gilles Defer, Aurelien Quenault, Sara Martinez de Lizarrondo, Denis Vivien, Maxime Gauberti, Fabian Docagne, Richard Macrez

New strategies for detecting disease activity in multiple sclerosis are being investigated to ameliorate diagnosis and follow-up of patients. Today, although magnetic resonance imaging (MRI) is widely used to diagnose and monitor multiple sclerosis, no imaging tools exist to predict the evolution of disease and the efficacy of therapeutic strategies. Here, we show that molecular MRI targeting the endothelial adhesion molecule P-selectin unmasks the pathological events that take place in the spinal cord of mice subjected to chronic or relapsing experimental autoimmune encephalomyelitis. This approach provides a quantitative spatiotemporal follow-up of disease course in relation to clinical manifestations. Moreover, it predicts relapse in asymptomatic mice and remission in symptomatic animals. Future molecular MRI targeting P-selectin may be used to improve diagnosis, follow-up of treatment, and management of relapse/remission cycles in multiple sclerosis patients by providing information currently inaccessible through conventional MRI techniques.

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.