Key result
CEA maintains higher spatial dominance of disturbed flow than CAS, closer to healthy carotids.
Why the study?
Conventional wall shear stress-derived biomarkers quantify the magnitude of disturbed flow after carotid endarterectomy and carotid artery stenting, but it was unknown whether quantifying spatial organisation provides complementary haemodynamic information.
Does spatial organisation of disturbed flow (measured by the Spatial Dominance Index and hotspot metrics) provide complementary haemodynamic information to distinguish between carotid endarterectomy, carotid artery stenting, and healthy carotid geometries?
Observational (n=9)
Does spatial organisation of disturbed flow (measured by the Spatial Dominance Index and hotspot metrics) provide complementary haemodynamic information to distinguish between carotid endarterectomy, carotid artery stenting, and healthy carotid geometries?
Answers are grounded in this paper and cite their sources.
Spatial organisation of disturbed flow, quantified by the dimensionless Spatial Dominance Index, distinguishes post-CEA focal flow patterns from post-CAS fragmented flow patterns beyond conventional wall shear stress biomarker magnitude.
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.
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Soudah et al. (2026) conducted an observational in Carotid artery stenosis / carotid revascularization (post-CEA and post-CAS) (n=9). Carotid endarterectomy (CEA) and Roadsaver-treated carotid artery stenting (CAS) vs. Healthy carotid geometries (and comparison between CEA and CAS) was evaluated on Spatial Dominance Index (SDI), defined as the largest connected hotspot area divided by total area at risk. Carotid endarterectomy retained higher spatial dominance of disturbed flow than Roadsaver-treated carotid artery stenting, while healthy carotids had SDI ~0.22.
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