A large number of surgeries are conducted for carotid stenosis, which is typically based on degree of luminal stenosis. This approach has many limitations – two-thirds of carotid plaque thromboembolism is thought to result from non-significant stenosis and the a large number of surgeries need to be performed to prevent a single stroke in the setting of high-grade carotid stenosis. Understanding plaque pathology may assist in risk stratification. A previously described histopathological scheme classified carotid plaques as thin fibrous cap atheroma (with lipid-rich necrotic core and presumed to be at increased risk of rupture), pathological intimal thickening and fibrous cap atheroma (both of which are more fibrous and more stable). A biomechanical stress analysis to distinguish vulnerable plaques from stable ones (based on plaque morphology, tissue properties, and hemodynamics) can be performed with carotid MRI, but its efficacy has not been established. In this manuscript, Gijsen et al performed both histological classification and peak cap stress computation of carotid plaque sections from patients who underwent endarterectomy for >70% stenosis.


Carotid plaque sections from 34 patients were obtained for histopathological analysis and numerical MRI simulation. Fibrous cap thickness was measured and peak cap stress (in kilopascals) was computed. The authors found that that sections classified as pathological intimal thickening had the lowest stress and that those with thin fibrous cap atheroma had the highest peak cap stress. However, there was significant discordance between classifications – 64% of the thin fibrous cap atheromas had high peak cap stress (high-risk) and 56% of the cross sections not classified as a thin fibrous cap atheromas had low peak cap stress (low-risk). MRI-based stress computation was imprecise and underestimated peak cap stress. Within the low-stress group, however, there actually was consistent agreement between histological classification and peak cap stress measurement by MRI.

This study suggests that MRI-based identification of low-risk carotid plaques may be possible. Evaluation of additional features – such as intraplaque hemorrhage, inflammation, and calcification – may further improve identification of stable carotid plaques. The practical utility of this would be to identify individuals who may not benefit from surgical intervention. However, this concept would need to be tested in a clinical trial to evaluate its efficacy and value.