Conducting a retrospective analysis of electronic health records is a challenging task that requires many resources and tools. Increasingly, database resources that are acquired through the clinical care for thousands of patients include longitudinal, research-quality magnetic resonance imaging (MRI). The clinical notes, demographic data, and images obtained from such databases provide an abundance of information for researchers studying neurological diseases. However, these resources come with the informatics challenges of collecting and organizing these retrospective data. As a case study, we led a study based at The Penn Comprehensive Multiple Sclerosis (MS) Center at the University of Pennsylvania to collect over ten thousand MRI studies. We utilized NeuroConductor-based tools in R to organize the information obtained and create an analytic dataset. This is a key step in facilitating the use of these data to answer important questions about MS.