Abstract 16875: Measurement of Atherosclerotic Inflammation with FDG-PET Imaging Improves Cardiovascular Risk Stratification
Background: FDG uptake correlates with cardiovascular (CV) events. Here we test the hypothesis that aortic inflammation measured with FDG-PET-CT imaging provides added value to Framingham risk score (FRS).
Methods: We screened consecutive clinical data (n= 6,109) for patients with no prior CVD, active cancer, or chronic inflammatory conditions who had clinical follow-up data for up to 5 years after an index FDG-PET. From the 229 (median age[IQR],60[47,68], 38% males) meeting these criteria, 42 had CV events (incident ischemic stroke, TIA, ACS, carotid or coronary revascularization) and 187 did not during the follow-up. FRS 10 year % probability of CHD was calculated. FDG uptake was measured (ascending aorta) and reported as target-to-background ratio (TBR) while blinded to clinical data. Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) were used to compare FRS with and without TBR for CV event prediction.
Results: Patients in the highest TBR tertile were substantially more likely to experience CV events (HR[95%CI], 4.85[1.89,12], p=0.001) compared to the lowest tertile after adjusting for FRS, BMI, statin, and diabetes. Further, addition of TBR (tertiles) to FRS variables resulted in an improvement in patient net reclassification, (NRI[95% CI]=26.89%[10%, 47%) across risk categories (<10, 10-20, >20) compared to their initially calculated risk. Adding TBR (tertiles) to FRS variables further improved discrimination of CV risk, (IDI=5.56%[0.27%, 11%]).
Conclusions: FDG-PET measured aortic plaque inflammation improves risk discrimination and reclassification. These preliminary data support prospective follow-up studies to evaluate imaging plaque inflammation for CVD risk assessment.
- © 2011 by American Heart Association, Inc.