3 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.

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