Tailoring MRI as the Fan Favorite Measure for Progressive MS

Article

Magnetic Resonance Imaging (MRI) has long been the immediate go-to for “proof-of-concept†outcome measures in relapse-remitting multiple sclerosis (RRMS). After all, why fix what isn’t broken?

Magnetic Resonance Imaging (MRI) has long been the immediate go-to for “proof-of-concept” outcome measures in relapse-remitting multiple sclerosis (RRMS). After all, why fix what isn’t broken?

MRI’s early success in small baseline-to-treatment trials aimed to reduce the incidence of “contrast-enhancing lesions” predicting its efficacy in phase 3 trials, which focus on clinical outcomes.

However, progressive MS is a different playing field, with no existing proof-of-concept trial design or successful large phase 3 studies.

Nonetheless, experts have come forward with promising imaging-based approaches like measurement of atrophy and MRI signal-intensity changes that could be consistent with repair.

Daniel S. Reich, MD, Johns Hopkins University, at the Americas Committee for Treatment and research in Multiple Sclerosis (ACTRIMS) 2016 Forum, discussed three potential uses of MRI in progressive MS often considered “off the beaten track”:

1. That MRI might be more useful as a method for enriching progressive MS studies than as an outcome measure per se

2. That outcome measures for proof-of-concept trials should favor sensitivity over biological specificity

3. That screening of new therapeutics for potential testing in progressive MS should be done initially in early active disease.

Reich argued that unlike the situation in RRMS, progressive MS couldn’t be advantageous to a nonspecific set of outcome measures. He suggested MRI methods should be tailored to the anticipated goals of specific therapies: prevention of neuronal loss, repair of damaged tissue, or the reduction of compartmentalized inflammation).

To better understand targeted therapies, Reich proposes further exploration of parallel studies using the same therapies in similar imaging methods, but in preclinical models.

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