Biomechanical index for predicting the risk of acute coronary syndrome

Background: A patient-specific biomechanical model for quantifying the stress state within coronary atherosclerotic lesions for the noninvasive prediction of acute coronary syndrome (ACS) has not been established. Methods: Sixty-nine patients with clearly documented ACS and available coronary computed tomographic angiography (cCTA) acquired between 1 month and 2 years before the development of ACS were included. In 63 culprit and 146 nonculprit lesions, lumen geometry, the presence of adverse plaque characteristics (APC), and hemodynamic parameters were evaluated using previously described methods. A novel biomechanical metric, denoted as the Cap Vulnerability Index (CVI), was calculated from cCTA data using computational solid and fluid mechanics and compared to anatomic, plaque and hemodynamics variables for the ability to discriminate culprit from nonculprit lesions. Results: Culprit lesions had a greater diameter stenosis, lesion length, more adverse plaque and hemodynamic characteristics and a greater CVI. Among all parameters evaluated, CVI had the highest AUC (0.75), was the strongest independent predictor for ACS and was comparable to previously described statistical models combining anatomy, plaque and hemodynamic variables. Conclusions: Noninvasive biomechanical assessment of coronary plaques using computational solid and fluid mechanics may improve identification of culprit lesions for ACS and simplify the interpretation of risk factors for individual lesions.