Combined non-invasive assessment of endothelial shear stress and molecular imaging of inflammation for the prediction of inflamed plaque in hyperlipidaemic rabbit aortas.

Aims: To evaluate the incremental value of low endothelial shear stress (ESS) combined with high-resolution magnetic resonance imaging (MRI)- and computed tomography angiography (CTA)-based imaging for the prediction of inflamed plaque.

Methods And Results: Twelve hereditary hyperlipidaemic rabbits underwent quantitative analysis of plaque in the thoracic aorta with 256-slice CTA and USPIO-enhanced (ultra-small superparamagnetic nanoparticles, P904) 1.5-T MRI at baseline and at 6-month follow-up. Computational fluid dynamics using CTA-based 3D reconstruction of thoracic aortas identified the ESS patterns in the convex and concave curvature subsegments of interest. Subsegments with low baseline ESS exhibited significant increase in wall thickness and plaque inflammation by MRI, in non-calcified plaque burden by CTA, and developed increased plaque size, lipid and inflammatory cell accumulation (high-risk plaque features) at follow-up by histopathology. Multiple regression analysis identified baseline ESS and inflammation by MRI to be independent predictors of plaque progression, while receiver operating curve analysis revealed baseline ESS alone or in combination with inflammation by MRI as the strongest predictor for augmented plaque burden and inflammation (low ESS at baseline: AUC = 0.84, P < 0.001; low ESS and inflammation by molecular MRI at baseline: AUC = 0.89, P < 0.001).

Conclusion: Low ESS predicts progression of plaque burden and inflammation as assessed by non-invasive USPIO-enhanced MRI. Combined non-invasive assessment of ESS and imaging of inflammation may serve to predict plaque with high-risk features.