A Novel MRA-Based Framework for Segmenting the Cerebrovascular System and Correlating Cerebral Vascular Changes to Mean Arterial Pressure

Blood pressure (BP) changes with age are widespread, and systemic high blood pressure (HBP) is a serious factor in developing strokes and cognitive impairment. A non-invasive methodology to detect changes in human brain's vasculature using Magnetic Resonance Angiography (MRA) data and correlation of cerebrovascular changes to mean arterial pressure (MAP) is presented. MRA data and systemic blood pressure measurements were gathered from patients (n = 15, M = 8, F = 7, Age = 49.2 +/- 7.3 years) over 700 days (an initial visit and then a follow-up period of 2 years with a final visit.). A novel segmentation algorithm was developed to delineate brain blood vessels from surrounding tissue. Vascular probability distribution function (PDF) was calculated from segmentation data to correlate the temporal changes in cerebral vasculature to MAP calculated from systemic BP measurements. A 3D reconstruction of the cerebral vasculature was performed using a growing tree model. Segmentation results recorded 99.9% specificity and 99.7% sensitivity in identifying and delineating the brain's vascular tree. The PDFs had a statistically significant correlation to MAP changes below the circle of Willis (p-value = 0.0007). This non-invasive methodology could be used to detect alterations in the cerebrovascular system by analyzing MRA images, which would assist clinicians in optimizing medical treatment plans of HBP.