Subtle blood-brain barrier leakage rate and spatial extent: Considerations for dynamic contrast-enhanced MRI.

Abstract

Dynamic contrast-enhanced (DCE) MRI can be used to measure blood-brain barrier (BBB) leakage. In neurodegenerative disorders such as small vessel disease and dementia, the leakage can be very subtle and the corresponding signal can be rather noisy. For these reasons, an optimized DCE-MRI measurement and study design is required. To this end, a new measure indicative of the spatial extent of leakage is introduced and the effects of scan time and sample size are explored. Dual-time resolution DCE-MRI was performed in 16 patients with early Alzheimer's disease (AD) and 17 healthy controls. The leakage rate (Ki ) and volume fraction of detectable leaking tissue (vL ) to quantify the spatial extent of BBB leakage were calculated in cortical gray matter and white matter using noise-corrected histogram analysis of leakage maps. Computer simulations utilizing realistic Ki histograms, mimicking the strong effect of noise and variation in Ki values, were performed to understand the influence of scan time on the estimated leakage. The mean Ki was very low (order of 10-4 min-1 ) and highly influenced by noise, causing the Ki to be increasingly overestimated at shorter scan times. In the white matter, the Ki was not different between patients with early AD and controls, but was higher in the cortex for patients, reaching significance after 14.5 min of scan time. To detect group differences, vL proved more suitable, showing significantly higher values for patients compared with controls in the cortex after 8 minutes of scan time, and in white matter after 15.5 min. Several ways to improve the sensitivity of a DCE-MRI experiment to subtle BBB leakage were presented. We have provided vL as an attractive and potentially more time-efficient alternative to detect group differences in subtle and widespread blood-brain barrier leakage compared with leakage rate Ki . Recommendations on group size and scan time are made based on statistical power calculations to aid future research.