A PREDICTIVE METHOD FOR HUMAN CAROTID PLAQUE RUPTURE USING IN VIVO SERIAL MRI WITH FOLLOW-UP SCAN SHOWING ACTUAL RUPTURE AND MRI-BASED 3D MODELS WITH FLUID-STRUCTURE INTERACTIONS

摘要

It has been hypothesized that mechanical risk factors may be used to predict future atherosclerotic plaque rupture. Much progress has been made in computational modeling, medical imaging, and mechanical analysis for atherosclerotic plaque vulnerability assessment in recent years [1-2]. However, truly predictive methods to predict plaque rupture are currently lacking in the literature and practice. In this paper, we introduce a procedure using computational and statistical models based on serial magnetic resonance imaging (MRI) to quantify sensitivity and specificity of mechanical predictors and their combinations to identify the best candidate for rupture prediction. Serial MRI of carotid plaque from a patient with follow-up scan showing ulceration (rupture) was acquired and the actual appearance of ulceration was used as "gold standard" and validation for the predictive method.