Reader Comments
Post a new comment on this article
Post Your Discussion Comment
Please follow our guidelines for comments and review our competing interests policy. Comments that do not conform to our guidelines will be promptly removed and the user account disabled. The following must be avoided:
- Remarks that could be interpreted as allegations of misconduct
- Unsupported assertions or statements
- Inflammatory or insulting language
Thank You!
Thank you for taking the time to flag this posting; we review flagged postings on a regular basis.
closeAuthor Summary
Posted by nvelezde on 26 Sep 2013 at 17:20 GMT
Clinical relapses in multiple sclerosis (MS) are a serious condition that contributes to significant morbidity in the clinical population. They reflect acute focal inflammatory events in the central nervous system that affect signal conduction by damaging myelinated axons. Such inflammatory events are evident in T1-weighted post-contrast magnetic resonance imaging as contrast enhancing lesions (CEL). CELs have an important role as a biomarker, since they are four to ten times more frequently compared with clinically defined relapses. The CEL dynamic is currently considered unpredictable, and as a result, significant uncertainty faces both patients and clinicians in managing this disease. Our work addresses this key issue describing the formation /resolution of CELs by applying mathematical modeling techniques. This modeling effort has the potential to alleviate the uncertainty associated with relapsing-remitting MS disease progression. We were able to characterize the relapsing-remitting CEL dynamic and to quantify the inter-patient variability. It was found that the historical pattern of relapses enhances significantly the ability to predict future course. Moreover, the analyses suggested that steroid treatments for the punctual treatment of the clinical relapses helps resolve older CELs yet does not affect newly appearing active lesions in that month. This model could potentially be used to indicate the likelihood of relapse and be used for design of future longitudinal studies and clinical trials, as well as for the evaluation of new therapies.