What is the relationship between myocardial perfusion imaging and coronary artery disease risk factors and markers of inflammation?
The treatment of coronary artery disease (CAD) is clinically measured by monitoring changes in venous lipids and inflammatory markers. There is currently no established quantified relationship between coronary flow reserve and markers of inflammatory CAD. A total of 120 men and women underwent quantified measurement of coronary blood flow using SPECT imaging at baseline and 1 year later. They had fasting venous blood work obtained at baseline and 1 year later. These markers of lipids and inflammation included, total cholesterol, low-density lipoprotein cholesterol, very low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, lipoprotein-a, homocysteine, fibrinogen, C-reactive protein, and interleukin-6. Regression analysis reveals no general statistical relationship between these markers and coronary blood flow as measured by myocardial perfusion imaging. However, when changes in indices are considered and changes in risk factors are compared with changes in ischemia, blood factor based estimates yield an adjusted R2 = 0.31, R = 0.57, P < .0001. Initial levels of coronary ischemia cannot be diagnostically inferred from baseline values in lipid and inflammatory markers of coronary artery disease. When change in coronary blood flow is quantified using SPECT imaging, 6 independent underlying blood factors provided statistically useful information in identifying changes in coronary blood flow. Although the relationship of changes is statistically significant ( P < .0001), quantification of coronary blood flow by SPECT imaging provides physiologic status information, which cannot be inferred from fasting markers of lipids and inflammation status.
Fleming
Richard M
RM
Critical Care and Cardiology, Department of Internal Medicine, Sierra Nevada Veterans Affairs Health Care System, Reno, Nevada 89502-2597, USA. rmfmd7@ hotmail.com
Harrington
Gordon M
GM
D000328:Adult; D015415:Biomarkers / Q000097:blood; D003324:Coronary Artery Disease / Q000097:blood / Q000150:complications / Q000000981:diagnostic imaging* / Q000209:etiology / Q000503:physiopathology; D003326:Coronary Circulation; D005260:Female; D005500:Follow-Up Studies; D053805:Fractional Flow Reserve, Myocardial; D006801:Humans; D007249:Inflammation / Q000097:blood* / Q000150:complications; D018836:Inflammation Mediators / Q000097:blood*; D008055:Lipids / Q000097:blood*; D008297:Male; D008875:Middle Aged; D017202:Myocardial Ischemia / Q000097:blood / Q000000981:diagnostic imaging / Q000209:etiology* / Q000503:physiopathology; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D015899:Tomography, Emission-Computed, Single-Photon
D015415:Biomarkers; D018836:Inflammation Mediators; D008055:Lipids