BACKGROUND: Quantification of myocardial ischemia and necrosis might ameliorate prognostic models and lead to improved patient management. However, no standardized consensus on how to assess and quantify these parameters has been established. The aim of this study was to quantify these variables by cardiac magnetic resonance imaging (CMR) and to establish possible incremental implications in cardiovascular risk prediction. METHODS: This study is a retrospective analysis of patients with known or suspected coronary artery disease (CAD) referred for adenosine perfusion CMR was performed. Myocardial ischemia and necrosis were assessed and quantified using an algorithm based on standard first-pass perfusion imaging and late gadolinium enhancement (LGE). The combined primary endpoint was defined as cardiac death, non-fatal myocardial infarction, and stroke. RESULTS: 845 consecutive patients were enrolled into the study. During the median follow-up of 3.64 [1.03; 10.46] years, 61 primary endpoints occurred. Patients with primary endpoint showed larger extent of ischemia (10.7 ± 12.25% vs. 3.73 ± 8.29%, p < 0.0001) and LGE (21.09 ± 15.11% vs. 17.73 ± 10.72%, p < 0.0001). A risk prediction model containing the extent of ischemia and LGE proved to be superior in comparison to all other models (χ² increase: from 39.678 to 56.676, integrated discrimination index: 0.3851, p = 0.0033, net reclassification index: 0.11516, p = 0.0071). The ben-eficial effect of revascularization tended to be higher in patients with greater extents of ischemia, though statistical significance was not reached. CONCLUSIONS: Quantification of myocardial ischemia and LGE was shown to significantly improve existing risk prediction models and might thus lead to an improvement in patient management.
BACKGROUND: Quantification of myocardial ischemia and necrosis might ameliorate prognostic models and lead to improved patient management. However, no standardized consensus on how to assess and quantify these parameters has been established. The aim of this study was to quantify these variables by cardiac magnetic resonance imaging (CMR) and to establish possible incremental implications in cardiovascular risk prediction. METHODS: This study is a retrospective analysis of patients with known or suspected coronary artery disease (CAD) referred for adenosine perfusion CMR was performed. Myocardial ischemia and necrosis were assessed and quantified using an algorithm based on standard first-pass perfusion imaging and late gadolinium enhancement (LGE). The combined primary endpoint was defined as cardiac death, non-fatal myocardial infarction, and stroke. RESULTS: 845 consecutive patients were enrolled into the study. During the median follow-up of 3.64 [1.03; 10.46] years, 61 primary endpoints occurred. Patients with primary endpoint showed larger extent of ischemia (10.7 ± 12.25% vs. 3.73 ± 8.29%, p < 0.0001) and LGE (21.09 ± 15.11% vs. 17.73 ± 10.72%, p < 0.0001). A risk prediction model containing the extent of ischemia and LGE proved to be superior in comparison to all other models (χ² increase: from 39.678 to 56.676, integrated discrimination index: 0.3851, p = 0.0033, net reclassification index: 0.11516, p = 0.0071). The ben-eficial effect of revascularization tended to be higher in patients with greater extents of ischemia, though statistical significance was not reached. CONCLUSIONS: Quantification of myocardial ischemia and LGE was shown to significantly improve existing risk prediction models and might thus lead to an improvement in patient management.
Entities:
Keywords:
cardiac magnetic resonance imaging; coronary artery disease; prognosis and outcomes; quantification of ischemia and necrosis; risk stratification