Abstract
Key points The blood–brain barrier (BBB) is an important and dynamic structure which contributes to homeostasis in the central nervous system.BBB permeability changes occur in health and disease but measurement of BBB permeability in humans is not straightforward.Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) can be used to model the movement of gadolinium contrast into the brain, expressed as the influx constant K i.Here evidence is provided that K i as measured by DCE‐MRI behaves as expected for a marker of overall BBB leakage.These results support the use of DCE‐MRI for in vivo studies of human BBB permeability in health and disease. Blood–brain barrier (BBB) leakage can be measured using dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) as the influx constant K i. To validate this method we compared measured K i with biological expectations, namely (1) higher K i in healthy individual grey matter (GM) versus white matter (WM), (2) GM/WM cerebral blood volume (CBV) ratio close to the histologically established GM/WM vascular density ratio, (3) higher K i in visibly enhancing multiple sclerosis (MS) lesions versus MS normal appearing white matter (NAWM), and (4) higher K i in MS NAWM versus healthy individual NAWM. We recruited 13 healthy individuals and 12 patients with MS and performed whole‐brain 3D DCE‐MRI at 3 T. K i and CBV were calculated using Patlak modelling for manual regions of interest (ROI) and segmented tissue masks. K i was higher in control GM versus WM (P = 0.001). CBV was higher in GM versus WM (P = 0.005, mean ratio 1.9). K i was higher in visibly enhancing MS lesions versus MS NAWM (P = 0.002), and in MS NAWM versus controls (P = 0.014). Bland–Altman analysis showed no significant difference between ROI and segmentation methods (P = 0.638) and an intra‐class correlation coefficient showed moderate single measure consistency (0.610). K i behaves as expected for a compound marker of permeability and surface area. The GM/WM CBV ratio measured by this technique is in agreement with the literature. This adds evidence to the validity of K i measured by DCE‐MRI as a marker of overall BBB leakage.
Highlights
The blood–brain barrier (BBB) is important for the maintenance of a stable microenvironment in the central nervous system (CNS), and in the regulation of solute and cellular traffic between systemic and CNS compartments (Abbott et al 2010)
The relapsing–remitting MS (RRMS) group was older (P = 0.01, Student’s t test), and age was factored into all further analyses comparing groups, since BBB permeability increases with age (Elwood et al 2017)
It is higher in control grey matter (GM) compared to control white matter (WM), higher in multiple sclerosis (MS) normal appearing white matter (NAWM) compared to control WM and higher in contrast-enhancing lesions (CELs) compared to NAWM
Summary
The blood–brain barrier (BBB) is important for the maintenance of a stable microenvironment in the central nervous system (CNS), and in the regulation of solute and cellular traffic between systemic and CNS compartments (Abbott et al 2010). Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a newer technique which can measure all levels of BBB leakiness, including levels invisible to conventional imaging (Cramer et al 2014). To achieve this high sensitivity, the brain is scanned continuously for a period of time (e.g. 15 min) to acquire kinetic data capturing the periods before, during and after contrast injection. One would expect a higher Ki in areas with a higher vascular surface area available for tracer exchange The latter phenomenon can be utilized as one of several ways to validate Ki derived from DCE-MRI in healthy control individuals, since it has been histologically established that vascular density in the grey matter (GM) is higher than in white matter (WM) (Lierse & Horstmann, 1965). Assuming a very simple vascular architecture model comprising cylindrical vessels with constant radius, it can be seen that both S and CBV scale with vessel density, and CBV should predict Ki
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