Multiple sclerosis (MS) is an immune-mediated disease in which inflammatory lesions form in the brain. In many active MS lesions, the blood-brain barrier (BBB) is disrupted and blood flows into white matter; this disruption may be related to morbidity and disability. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows quantitative study of blood flow and permeability dynamics throughout the brain. This technique involves a subject being imaged sequentially during a study visit as an intravenously administered contrast agent flows into the brain. In regions where flow is abnormal, such as white matter lesions, this allows the quantification of the BBB damage. A DCE-MRI sequence acquired at a single visit is a spatiotemporal process that consists of MR intensity observed at millions of voxels (space) using multiple MRI scans over a period of 15-160 minutes in the scanner (time). In our study, we observe 15 patients who undergo DCE-MRI periodically throughout a year. The longitudinal nature of the study arises from the multiple visits where MRI is conducted for each subject. In this paper, we are interested in designing and studying spatiotemporal parameters of interest that cannot be obtained by visual inspection. Examples of such parameters are the rate and maximum intensity observed in regions of interest. We use functional principal component analysis (FPCA) and semiparametric techniques for this quantification of BBB disruption at each visit. The longitudinal evolution of maps of such parameters provides a useful clinical tool for quantification and visualization of BBB abnormalities. Using these techniques we found evidence of subtle enhancement in a chronic white matter lesion, which is previously undocumented using DCE-MRI in MS.
Shinohara, Russell T.; Crainiceanu, Ciprian M.; Caffo, Brian S.; and Reich, Daniel S., "LONGITUDINAL ANALYSIS OF SPATIOTEMPORAL PROCESSES: A CASE STUDY OF DYNAMIC CONTRAST-ENHANCED MAGNETIC RESONANCE IMAGING IN MULTIPLE SCLEROSIS" (September 2011). Johns Hopkins University, Dept. of Biostatistics Working Papers. Working Paper 231.