Image-based assessment of uncertainty in quantification of carotid lumen.

Measurements of the vessel lumen diameter are often used to determine the degree of atherosclerotic disease in carotid arteries. However, quantification results vary with imaging technique and acquisition settings. We aim at providing a tool that quantifies the lumen diameter on different image datasets and gives an estimate of quantification uncertainties, so that they can be taken into consideration when evaluating and comparing measurements. For the segmentation of the vessel lumen, we present an algorithm using ray-casting techniques and partial volume correction. We furthermore propose a scheme for the analysis and exploration of the lumen diameter. Finally, we present a clinically relevant application scenario, in which we explore agreement between lumen diameter estimations in corresponding computed tomography angiography, contrast-enhanced magnetic resonance angiography, time-of-flight, and subtraction images of carotid vessels with severe carotid atherosclerotic plaques.