SPATIAL ORGANIZATION OF DISTURBED FLOW AFTER CAROTID ENDARTERECTOMY AND CAROTID ARTERY STENTING.

OBJECTIVE

Carotid endarterectomy (CEA) and carotid artery stenting (CAS) create distinct postoperative geometries. Conventional wall shear stress (WSS)-derived biomarkers quantify disturbed-flow magnitude but not its spatial organisation. We evaluated whether spatial organisation provides complementary haemodynamic information after CEA and CAS.

METHODS

In this retrospective, patient-specific computational fluid dynamics study, nine carotid geometries (three healthy, three post-CEA, three post-CAS) were reconstructed from computed tomography angiography. Identical pulsatile boundary conditions were applied to isolate morphological effects. Time-averaged WSS (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP) were computed. Regions of adverse flow were defined using percentile thresholds (P90, P95, and P99). Spatial organisation was quantified by total area at risk, largest connected hotspot area, hotspot number, and the Spatial Dominance Index (SDI), defined as the largest hotspot area divided by total area at risk.

RESULTS

ECAP, OSI, and RRT colocalised with low TAWSS, and spatial descriptors were consistent across biomarkers. Healthy carotids showed the most focal pattern (SDI approximately 0.22; 8-12 hotspots). CEA had the largest total area at risk and largest hotspot but retained relatively high dominance (SDI 0.16-0.17; 48-75 hotspots). The Roadsaver-treated CAS geometries had the smallest total area at risk but the most fragmented pattern, with smaller hotspots and the lowest dominance (SDI 0.09-0.12; 39-70 hotspots). These patterns persisted across P90-P99 thresholds.

CONCLUSION

Spatial organisation distinguished carotid revascularisation strategies beyond biomarker magnitude. CEA largely preserved a focal, dominant pattern, whereas the Roadsaver-treated CAS geometries showed fragmented, distributed disturbed flow. The simple, dimensionless SDI may complement established WSS-derived biomarkers in patient-specific haemodynamic assessment.