New publication in Magnetic Resonance in Medicine Journal
Publication year: May 2021
"Sources of systematic error in DCE-MRI estimation of low-level blood-brain barrier leakage"
Authors: Cameron Manning ,Michael Stringer, Ben Dickie, Una Clancy, Maria C. Valdés Hernandez, Stewart J. Wiseman, Daniela Jaime Garcia, Eleni Sakka, Walter H. Backes, Michael Ingrisch, Francesca Chappell, Fergus Doubal, Craig Buckley, Laura M. Parkes, Geoff J. M. Parker, Ian Marshall, Joanna M. Wardlaw, Michael J. Thrippleton.
Dynamic contrast-enhanced (DCE) -MRI with Patlak model analysis is increasingly used to quantify low-level blood-brain barrier (BBB) leakage in studies of pathophysiology. We aimed to investigate systematic errors due to physiological, experimental, and modeling factors influencing quantification of the permeability-surface area product PS and blood plasma volume vp, and to propose modifications to reduce the errors so that subtle differences in BBB permeability can be accurately measured.
Simulations were performed to predict the effects of potential sources of systematic error on conventional PS and vp quantification: restricted BBB water exchange, reduced cerebral blood flow, arterial input function (AIF) delay and error. The impact of targeted modifications to the acquisition and processing were evaluated, including: assumption of fast versus no BBB water exchange, bolus versus slow injection of contrast agent, exclusion of early data from model fitting and correction. The optimal protocol was applied in a cohort of recent mild ischaemic stroke patients.
Simulation results demonstrated substantial systematic errors due to the factors investigated (absolute PS error ≤ 4.48 × 10−4 min−1). However, these were reduced (≤0.56 × 10−4 min−1) by applying modifications to the acquisition and processing pipeline. Processing modifications also had substantial effects on in-vivo normal-appearing white matter PS estimation (absolute change ≤ 0.45 × 10−4 min−1).
Measuring subtle BBB leakage with DCE-MRI presents unique challenges and is affected by several confounds that should be considered when acquiring or interpreting such data. The evaluated modifications should improve accuracy in studies of neurodegenerative diseases involving subtle BBB breakdown.