ARTERIAL IMAGING Accuracy of Quantitative MR Vessel Wall Imaging Applying a Semi-Automated Gradient Detection Algorithm—A Validation Study

Magnetic resonance imaging (MRI) is uniquely suited to study the pathophysiology of arteriosclerosis. So far, magnetic resonance (MR) measurements of vessel dimensions have mainly been done by manual tracing of vessel wall contours. However, such data postprocessing is very time-consuming and has limited accuracy due to difficulties in precise tracing of the thin vessel wall. Purpose: To assess the accuracy and reproducibility of quantitative vascular MR imaging applying a data analysis method based on (1) vessel wall unwrapping, followed by (2) a gradient detection algorithm for MR data postprocessing. Vascular MR imaging studies were done both in vessel phantoms and in healthy volunteers (n=29) on a clinical 1.5 T MR scanner. A dark blood double-inversion turbo spin echo sequence with fat suppression was applied, with proton-density-weighted and breath-hold acquisition for aortic imaging and T2-weighted acquisition for carotid imaging. Intraobserver and interobserver variabil-ity were systematically evaluated by two independent observers. A repeat study within 10 days of the first MRI was performed in 10 of these subjects for assessmen