Multiple Sclerosis (MS) is a common neurological disability in young adults, affecting approximately 400,000 people in the United States alone. It is traditionally regarded as a white matter disease, but MRI assessment of white matter abnormalities does not correlate with clinical findings. Recent histopathologic studies suggest that extensive cortical gray matter damage is present in patients with longstanding disease. It has therefore become a critical goal to study the role of cortical lesions in clinical disability and disease progression. In vivo patient studies are, however, hampered by the low sensitivity of magnetic resonance imaging for cortical damage. New and advanced magnetic resonance imaging techniques have improved cortical lesion detection, but only a fraction of cortical lesions are visible. Nevertheless, it has become clear that the high spatial resolution and image contrast provided by ultra-high magnetic field imaging is necessary for further improvements in the visualization of cortical lesions. In this proposal, we will pursue two aims. First, we will measure MRI tissue parameters for cortical and white matter lesions and normal appearing cortex and white matter at 7 Tesla. We will use these parameters in computer simulations to optimize 7 Tesla MRI sequences for cortical lesion imaging. Secondly, we will image MS patients with longstanding disease as well as age-matched controls with the optimized sequences developed in the first goal. Image data will be assessed for their overall visual quality, tissue signal-to-noise, and contrast-to-noise. Currently, no gold standard measures for cortical lesion localization exist, thus lesion count rates and distributions comparable to previously published histopathologic findings will be considered the benchmark during the MRI method development phase. Accurate imaging of cortical demyelination in patients would constitute a breakthrough in MS research. Cortical lesion imaging will allow assessment of cortical contributions to clinical disability and disease progression, and may serve as a surrogate marker for measuring disease burden and treatment efficacy.