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Imaging immunomodulatory treatment responses in a multiple sclerosis mouse model using hyperpolarized 13C metabolic MRI.
Guglielmetti, Caroline; Cordano, Christian; Najac, Chloé; Green, Ari J; Chaumeil, Myriam M.
Afiliación
  • Guglielmetti C; Department of Physical Therapy and Rehabilitation Science, University of California San Francisco, San Francisco, CA, USA. caroline.guglielmetti@ucsf.edu.
  • Cordano C; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA. caroline.guglielmetti@ucsf.edu.
  • Najac C; Department of Neurology, Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, CA, USA.
  • Green AJ; Department of Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, Leiden, The Netherlands.
  • Chaumeil MM; Department of Neurology, Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, CA, USA.
Commun Med (Lond) ; 3(1): 71, 2023 May 22.
Article en En | MEDLINE | ID: mdl-37217574
Magnetic resonance imaging (MRI) is widely used in the clinic to diagnose multiple sclerosis (MS), which affects the central nervous system and leads to a range of disabling symptoms. However, MRI is often not capable of detecting how well a patient responds to therapies, in particular those targeting the immune system. We questioned whether an advanced MRI method called hyperpolarized 13C MRS could help. Using a mouse model for MS, we showed that hyperpolarized 13C MRS can detect response to two therapies used in the clinic, namely fingolimod and dimethyl fumarate when conventional MRI could not. We also showed that this method is sensitive to the immune response. As hyperpolarized 13C MRS is becoming available in many centers worldwide, it could be used to evaluate existing and new treatments for people living with MS, improving care and quality of life.

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Commun Med (Lond) Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Commun Med (Lond) Año: 2023 Tipo del documento: Article