Relating the mechanical properties of atherosclerotic calcification to radiographic density: A nanoindentation approach

Calcification morphology can determine atherosclerotic plaque stability and is associated with increased failures rates for endovascular interventions. Computational efforts have sought to elucidate the relationship between calcification and plaque rupture in addition to predicting tissue response during aggressive revascularisation techniques. However, calcified material properties are currently estimated and may not reflect real tissue conditions. The objective of this study is to correlate calcification mechanical properties with three radiographic density groups obtained from corresponding Computed Tomography (CT) images. Seventeen human plaques extracted from carotid (n = 10) and peripheral lower limb (n = 7) arteries were examined using micro-computed tomography (mu CT), simultaneously locating the calcified deposits within their internal structure and quantifying their densities. Three radiographic density groups were defined based on the sample density distribution: (A) 130-299.99 Hounsfield Units (HU), (B) 300-449.99 HU and (C) >450 HU. Nanoindentation was employed to determine the Elastic Modulus (E) and Hardness (H) values within the three density groups. Results reveal a clear distinction between mechanical properties with respect to radiographic density groups (p < 0.0005). No significant differences exist in the density-specific behaviours observed between carotid and peripheral samples. Previously defined calcification classifications indicate an association with specific radiographic density patterns. Scanning Electron Microscopy (SEM) examination revealed that density group A regions consist of both calcified and non-calcified tissues. Further research is required to define the radiographic thresholds which identify varying degrees of tissue calcification. This study demonstrates that the mechanical properties of fully mineralised atherosclerotic calcification emulate that of bone tissues (17-25 GPa), affording computational models with accurate material parameters. (C) 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.