Highly Aggressive Multiple Sclerosis

Multiple Sclerosis Severity Estimation and Progression Prediction Based on Machine Learning Techniques

The aim of the study is to address the Multiple Sclerosis (MS) severity estimation problem based on EDSS score and the prediction of the disease's progression with the application of Machine Learning (ML) approaches. Several ML techniques are implemented. The data are provided by the Neurology Clinic of the University Hospital of Ioannina and were collected in the framework of the ProMiSi project. The features recorded are grouped into: general demographic information, MS clinical related data, results of special tests, treatment, and comorbidities. The records from 30 patients are utilized and are recorded in three time points. The ML methods provided quite high results with 94.87% accuracy for the MS severity estimation and 83.33% for the disease's progression prediction.

Predictive MRI Biomarkers in MS—A Critical Review

Background and Objectives: In this critical review, we explore the potential use of MRI measurements as prognostic biomarkers in multiple sclerosis (MS) patients, for both conventional measurements and more novel techniques such as magnetization transfer, diffusion tensor, and proton spectroscopy MRI. Materials and Methods: All authors individually and comprehensively reviewed each of the aspects listed below in PubMed, Medline, and Google Scholar. Results: There are numerous MRI metrics that have been proven by clinical studies to hold important prognostic value for MS patients, most of which can be readily obtained from standard 1.5T MRI scans. Conclusions: While some of these parameters have passed the test of time and seem to be associated with a reliable predictive power, some are still better interpreted with caution. We hope this will serve as a reminder of how vast a resource we have on our hands in this versatile tool—it is up to us to make use of it.

Multiple sclerosis

Multiple sclerosis is a chronic, unpredictable, and disabling disease. Significant advances have been made in recent years supporting an earlier, more accurate, diagnosis and have led to more than 15 disease-modifying therapies approved by the Food and Drug Administration for relapsing forms of multiple sclerosis. Disease-modifying therapies are now being classified into categories based on level of efficacy. Strategies to use disease-modifying therapies earlier and in a more customizable manner are also emerging. A clinical case study will be used throughout this pearl to review the disease-modifying therapies and use patient-specific factors to develop and provide recommendations on therapeutic strategies for individuals with relapsing forms of multiple sclerosis.