Deep multimodal fusion of image and non-image data in identification of high-risk carotid atheromatous plaque

Cardiovascular diseases remain the leading cause of global mortality, accounting for over 19 million deaths annually according to the World Health Organization.Among these, carotid atherosclerosis, a pathological process characterized by plaque accumulation in the carotid arteries, is a major contributor to ischemic stroke, driven by plaque rupture and thromboembolic events.Traditional diagnostic approaches, which rely on single-modality imaging or clinical data, often fail to capture the complex interplay of morphological, biological, and hemodynamic factors that determine plaque vulnerability.