ABSTRACT
Blood pressure (BP) changes with age are widespread, and systemic high blood pressure (HBP) can significantly contribute to the occurrence of cognitive impairment, as well as strokes. This paper presents a new methodology, which is considered non-invasive. It uses Magnetic Resonance Angiography (MRA) imaging and correlation of cerebrovascular changes to mean arterial pressure (MAP), in order to quantify changes in the cerebral vasculature. Patients (n = 15, M = 8, F = 7, and age = 49.2 ± 7.3 years) were asked to make doctor visits over a period of 700 days (an initial visit and then a follow-up period of 2 years with a final visit) to have their systemic BP measurements as well as MRA images taken. To separate the vasculature of the brain from its surrounding tissue, a new segmentation algorithm was devised. 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. The model of a growing tree was used to reconstruct a 3D representation of the cerebral vasculature. The previously described algorithm was 99.9% specific and 99.7% sensitive in the identification and delineation of the brain’s vasculature. A significant correlation was detected between the PDF and MAP variations below the circle of Willis (P = 0.0007). The methodology described in this paper has shown success in optimizing the medical management of HBP, as it was able to quantify the variations in the cerebral vasculature, as well as the pressure of cerebral perfusion, through the non-invasive method of analyzing MRA images.
