Accurate Determination of Blood–Brain Barrier Permeability Using Dynamic Contrast-Enhanced T1-Weighted MRI: A Simulation and in vivo Study on Healthy Subjects and Multiple Sclerosis Patients. Issue 10 (October 2014)

• Record Type: Journal Article
• Authors: Cramer, Stig P; Larsson, Henrik BW
• Is Part Of: Journal of cerebral blood flow & metabolism. Volume 34:Issue 10(2014)
• Page Start: 1655
• Page End: 1665
• Publication Date: 2014-10
• Subjects: blood–brain barrier -- cerebral hemodynamics -- multiple sclerosis -- MRI -- perfusion-weighted MRI; Cerebral circulation -- Periodicals; Brain -- Metabolism -- Periodicals; Brain -- Blood-vessels -- Periodicals; Cerebrovascular disease -- Periodicals; 612.824
• DOI: 10.1038/jcbfm.2014.126
• Languages: English
• ISSNs: 0271-678X

Abstract

Dynamic contrast-enhanced magnetic resonance imaging (DCE–MRI) is increasingly used to estimate permeability in situations with subtle blood–brain barrier (BBB) leakage. However, the method's ability to differentiate such low values from zero is unknown, and no consensus exists on optimal selection of total measurement duration, temporal resolution, and modeling approach under varying physiologic circumstances. To estimate accuracy and precision of the DCE–MRI method we generated simulated data using a two-compartment model and progressively down-sampled and truncated the data to mimic low temporal resolution and short total measurement duration. Model fit was performed with the Patlak, the extended Tofts, and the Tikhonov two-compartment (Tik-2CM) models. Overall, 17 healthy controls were scanned to obtain in vivo data. Long total measurement duration (15 minutes) and high temporal resolution (1.25 seconds) greatly improved accuracy and precision for all three models, enabling us to differentiate values of permeability as low as 0.1 ml/100 g/min from zero. The Patlak model yielded highest accuracy and precision for permeability values <0.3 ml/100 g/min, but for higher values the Tik-2CM performed best. Our results emphasize the importance of optimal parameter setup and model selection when characterizing low BBB permeability.