Abstract
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Objectives Pts with multi-vessel coronary disease (MVD) are at increased risk for cardiac events, but are not always easily identified. 82Rb PET data are acquired at rest & during vasodilator stress. This study was conducted to determine which PET parameters are most effective in identifying pts with MVD.
Methods We retrospectively analyzed data for 106 pts (age = 70±13; 66 males) who had rest/regadenoson-stress CT attenuation-corrected 82Rb PET and angiography. PET data were analyzed by Emory Cardiac Toolbox algorithms, which computed ejection fractions (EF), LV volumes at end-diastole and end-systole (EDV & ESV), & perfusion scores. Myocardial blood flow (MBF) was assessed using a 2 compartment model. LV dyssychrony was quantified as bandwidth (BW) of contraction phase. Pts with MVD were defined as those with ≥ 70% stenosis in 2-3 vessels, assessed visually by the angiographer. Strength of association to detect pts with MVD (versus 0-1 vessel CAD) was assessed by univariate and multivariate logistic regression.
Results Among the 106 pts, 32 had MVD. All parameters were associated with MVD. Stress values tended to be more strongly predictive than rest values, but BW was the only variable for which stress was significantly more predictive than rest values (see Table). Stress variables most strongly associated with MVD were phase BW, perfusion score & EF. The combination of these three had an accuracy of 83% for identifying MVD (χ2 = 33.7, p < 0.0001). The most effective rest parameter was the combination of EDV, ESV and perfusion scores (χ2 = 16.6, p < 0.0001), for which accuracy was lower (71%, p = 0.05) than that of stress parameters.
Conclusions A combination of stress parameters appears more effective than rest parameters at identifying patients with MVD who may be at higher risk for cardiac events.