Objectives: Patients with type II diabetes are at increased risk of cognitive impairment. The retinal and renal complications of diabetes follow microvascular damage permitting small arterioles to leak, hence the cerebral damage might also follow loss of blood-brain barrier (BBB) integrity. Magnetic resonance (MR) brain imaging with intravenous gadolinium (Gd) diethylenetriamine pentaacetic acid (Gd-DTPA) was used to identify increased BBB permeability. Methods: Ten well controlled type II diabetic patients aged 65-70 years and 10 controls underwent MR brain imaging with fluid attenuated inversion recovery (FLAIR); T1 weighted (T1W) volumetric imaging before; and T1W volumetric imaging at 5, 15, 30, 45, 60, and 90 minutes after intravenous Gd-DTPA. The T1W image before Gd-DTPA was subtracted from the images at each time point after Gd-DTPA. Net signal intensity was plotted against time for different brain regions. White matter hyperintensities were scored from the FLAIR image. Results: The signal intensity/time curves showed that brain signal intensity increased more in the diabetic group than controls during the first 15 minutes after Gd-DTPA, particularly in the basal ganglia (p=0.018). Signal intensity in controls peaked at five minutes and diabetics at 15 minutes. Subjects with more white matter hyperintensities had greater signal increase after Gd-DTPA, whether diabetic or not (p=0.001). Conclusions: Increased BBB permeability with MR imaging was detected in patients with type II diabetes or white matter hyperintensities. Increased permeability of the BBB might account for some of the cerebral effects of type II diabetes, and so possibly also for the effect of other conditions that affect the microvasculature (like hypertension), on the brain.
White matter hyperintensities are frequent on neuroimaging of older people and are a key feature of cerebral small vessel disease. They are commonly attributed to chronic hypoperfusion, although whether low cerebral blood flow is cause or effect is unclear. We systematically reviewed studies that assessed cerebral blood flow in small vessel disease patients, performed meta-analysis and sensitivity analysis of potential confounders. Thirty-eight studies (n = 4006) met the inclusion criteria, including four longitudinal and 34 cross-sectional studies. Most cerebral blood flow data were from grey matter. Twenty-four cross-sectional studies (n = 1161) were meta-analysed, showing that cerebral blood flow was lower in subjects with more white matter hyperintensity, globally and in most grey and white matter regions (e.g. mean global cerebral blood flow: standardised mean difference-0.71, 95% CI -1.12, -0.30). These cerebral blood flow differences were attenuated by excluding studies in dementia or that lacked age-matching. Four longitudinal studies (n = 1079) gave differing results, e.g., more baseline white matter hyperintensity predated falling cerebral blood flow (3.9 years, n = 575); cerebral blood flow was low in regions that developed white matter hyperintensity (1.5 years, n = 40). Cerebral blood flow is lower in subjects with more white matter hyperintensity cross-sectionally, but evidence for falling cerebral blood flow predating increasing white matter hyperintensity is conflicting. Future studies should be longitudinal, obtain more white matter data, use better age-correction and stratify by clinical diagnosis.
Purpose:To study pulsatile fluid flow in a physiologically realistic model of the human carotid bifurcation, and to derive wall shear stress (WSS) vectors. Materials and Methods:WSS vectors were calculated from time-resolved 3D phase-contrast (PC) MRI measurements of the velocity field. The technique was first validated with sinusoidal flow in a straight tube, and then used in a model of a healthy human carotid bifurcation. Velocity measurements in the inflow and outflow regions were also used as boundary conditions for computational fluid dynamics (CFD) calculations of WSS, which were compared with those derived from MRI alone. Results:The straight tube measurements gave WSS results that were within 15% of the theoretical value. WSS results for the phantom showed the main features expected from fluid dynamics, notably the low values in the bulb region of the internal carotid artery, with a return to ordered flow further downstream. MRI was not able to detect the high WSS values along the divider wall that were predicted by the CFD model. Otherwise, there was good general agreement between MRI and CFD.Conclusion: This is the first report of time-resolved WSS vectors estimated from 3D-MRI data. The technique worked well except in regions of disturbed flow, where the combination with CFD modeling is clearly advantageous.
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