The cerebral and spinal vasculature possesses several unique properties: it is composed of relatively small vessels, it has a highly connected network architecture, and, due to the confined space around the brain, disruptions in flow (rupture, shunting, or blockage) can cause a clinical impact quickly. These features apply across various pathological conditions that alter the distribution of blood through the cerebral vasculature, such as aneurysm, intracranial atherosclerotic disease (ICAD) and arteriovenous malformation (AVM) as well as others. Neurovascular disease is a leading cause of mortality due to stroke in the United States and encompasses a broad range of pathologies including but not limited to cerebral arteriovenous malformation, intracranial atherosclerotic disease, intracranial aneurysms and other neurovascular abnormalities. Novel modalities for assessing disease states in patients with these pathologic conditions are constantly being developed and the understanding of risk factors, disease progression, and effective therapy is rapidly evolving. Neurovascular imaging is at the forefront of this progress. The identification of new predictive biomarkers regarding the risk of rupture, progression, or recurrence will improve prognosis and treatment planning. In this study, there will be evaluation of the various types of brain lesions and different treatment options that have been used by the treating physicians and, grade outcome based on the standard of care MRI imaging. This can help the Investigators stratify the treatment routes, that are better than the other by assessing the mortality and morbidity rates. Investigators are evaluating intracranial lesions and their treatment outcomes can help analyze which standard of care treatment is better than the others at a setting like Northwestern.
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Primary Outcome
Timeframe: one year - We are not using clinical endpoints, it is a developmental and pilot feasibility study of novel MRI applications to assess MR OEF/CVR, using quantitative MR PWI as marker of disease severity]