PURPOSE

Identification of rupture-prone plaques in coronary arteries is a major clinical challenge. Fibrous cap thickness and wall shear stress are two relevant image-based risk factors, but these two parameters are generally computed and analyzed separately. Accordingly, combining these two parameters can potentially improve the identification of at-risk regions. Therefore, the purpose of this study is to investigate the feasibility of the fusion of wall shear stress and fibrous cap thickness of coronary arteries in patient data.

METHODS

Fourteen patients were included in this pilot study. Imaging of the coronary arteries was performed with optical coherence tomography and with angiography. Fibrous cap thickness was automatically quantified from optical coherence tomography pullbacks using a contour segmentation approach based on fast marching. Wall shear stress was computed by applying computational fluid dynamics on the 3D volume reconstructed from two angiograms. The two parameters then were co-registered using anatomical landmarks such as side branches.

RESULTS

The two image modalities were successfully co-registered, with a mean (±SD) error corresponding to [Formula: see text] of the length of the analyzed region. For all the analyzed participants, the average thinnest portion of each fibrous cap was [Formula: see text], and the average WSS value at the location of the fibrous cap was [Formula: see text]. A unique index was finally generated for each patient via the fusion of fibrous cap thickness and wall shear stress measurements, to translate all the measured parameters into a single risk map.

CONCLUSION

The introduced risk map integrates two complementary parameters and has potential to provide valuable information about plaque vulnerability.