Distensibility measurements along carotid atherosclerotic plaques: how can we improve the mechanical modeling of atherosclerosis?

Motivation Biomechanical modeling of atherosclerotic plaques is emerging as a useful tool to provide markers of plaque vulnerability. However, the success of this modeling effort depends on the accurate estimation of local mechanical properties along the diseased vessel wall. Recent studies in healthy carotid bifurcations reported differences in wall distensibility between common and internal carotid arteries, suggesting that current computational models of carotid atherosclerosis could be improved by accounting for these segmental differences in mechanical properties. Furthermore, the compositional variability among plaques may also have an effect on distensibility values; in this case, comprehensive characterization of the wall in terms of distensibility in addition to plaque burden and composition along the entire bifurcation may improve the performance of biomechanical models. Objective We sought to test the hypotheses that (1) in diseased arteries, distensibility changes as the carotid arteries bifurcate and (2) specific plaque components may alter the distensibility along the afflicted vessel wall. CINE magnetic resonance imaging (MRI) of human carotid atherosclerotic arteries was used to measure vessel wall distensibility, whereas a subsequent multi-contrast MRI protocol was used to characterize vessel wall morphology and composition. Methods Twenty five participants with a wide range of carotid stenosis were recruited. Informed consent was obtained prior to subject participation. The study protocol and consent forms were reviewed and approved by the institutional review board. Morphology and Composition: The subjects’ carotid bifurcations were imaged axially using a 3.0 T clinical whole-body scanner (Philips Achieva, R2.6.1, Best, The Netherlands) with a 8-channel custom-designed carotid coil. The imaging protocol included a standardized combination of black and bright blood sequences to characterize the vessel wall morphology and composition (Figure 1). Custom designed analysis software (CASCADE) was used to register and segment the images. Lumen and outer wall boundaries were outlined for each imaged slice. Lipid-rich necrotic core and calcification boundaries were also outlined if detected following histology-validated imaging criteria. Plaque burden was characterized by the normalized wall index (NWI=wall area/total vessel area) and the maximum wall thickness (MWT). When lipid-rich necrotic core and calcification were detected, their percentage of the wall was computed (pNC and pCA, respectively).