Description (from grant):    

We are currently unable to predict accurately the course of MS in individual patients. In ongoing efforts to improve care, we have been developing a multi-faceted approach to readily monitor (through state of the art high-resolution retinal and brain imaging) and predict (through imaging and patient specific factors including genetic profiles) disease severity and progression in order to guide individualized therapeutic decision-making among patients with MS. There is a great clinical need in MS for predictive tools (imaging markers) such as those being developed by the P41 given the expanding number of increasingly more effective and potent treatments that may be associated with serious and potentially life-threatening complications. We have over the past 20 years benefitted greatly from MRI tools provided to us by Dr. van Zijl and his team, allowing us to probe deeper into the mechanisms of different types of MS. Most recently, we are studying central vein information with quantitative susceptibility mapping at 7T. We are looking forward to adding the proposed new biomarker packages once they are developed. However, we need to keep the older information regarding T1, T2, magnetic susceptibility and white matter and gray matter mapping. We are therefore especially excited about the propose development of fingerprinting tools that should allow us to get more information per time unit as we need to keep our scan time within a one hour period, while gathering physiologic (CBF, CBV, OEF from TRD1) and metabolic (especially glutamate imaging from TRD2) and tissue microstructure (TRD3) information and the possibility of multi-observable assessment using deep learning (TRD4).