This study aimed to assess the vulnerability of carotid atherosclerotic plaques using the combination of radiomics nomogram and clinical high-risk factors. Texture features were extracted from high-resolution multi-contrast magnetic resonance imaging. Radscore was applied to build a diagnostic model with the consideration of hrMRI texture features and patient demography to assess the power in differentiating vulnerable and stable lesions. The radscore showed a better diagnostic performance. The combination model of texture and clinical information had the best performance in assessing lesion vulnerability. This study demonstrated that hrMRI texture features provided incremental value for the carotid atherosclerotic vulnerability assessment.
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