Key result
Advanced multimodal carotid imaging improves stroke risk stratification by prioritizing plaque phenotyping over luminal stenosis.
Why the study?
Carotid stenosis alone fails to capture plaque biology and features that strongly influence vulnerability and clinical outcomes in ischemic stroke.
Design
Review
Supports plaque phenotyping in carotid risk assessment; extends traditional stenosis-based models with multimodal data.
Carotid atherosclerosis is a major cause of ischemic stroke, historically managed according to luminal stenosis severity. However, stenosis alone fails to capture plaque biology, as features such as intraplaque hemorrhage (IPH), lipid-rich necrotic core, fibrous cap rupture, ulceration, and perivascular inflammation strongly influence vulnerability and clinical outcomes. Advances in imaging have shifted the focus from lumen quantification to multimodal plaque phenotyping. Ultrasound, computed tomography angiography (CTA), magnetic resonance imaging (MRI), digital subtraction angiography, photon-counting CT (PCCT), and positron emission tomography (PET) provide complementary morphological and biological information, while contrast-enhanced ultrasound, radiomics, and artificial intelligence (AI) enhance risk stratification beyond conventional parameters. MRI remains the reference for detecting IPH, while CTA and PCCT improve lumen and tissue characterization. PET tracers further interrogate inflammatory and calcification pathways. Emerging frameworks such as Plaque-Reporting and Data System aim to standardize reporting and integrate multimodal biomarkers. The future of carotid imaging lies in precision medicine, combining advanced imaging, AI, and molecular biology to optimize individualized stroke prevention strategies.
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Saba et al. (2026) studied this question. Advanced multimodal carotid imaging improves stroke risk stratification by shifting focus from luminal stenosis to comprehensive plaque phenotyping.
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