Increased Pericardial Fat Volume Measured From Noncontrast CT Predicts Myocardial Ischemia by SPECT

Objectives We evaluated the association between pericardial fat and myocardial ischemia for risk stratification. Background Pericardial fat volume (PFV) and thoracic fat volume (TFV) measured from noncontrast computed tomography (CT) performed for calculating coronary calcium score (CCS) are associa...

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Published in:JACC. Cardiovascular imaging 2010-11, Vol.3 (11), p.1104-1112
Main Authors: Tamarappoo, Balaji, PhD, MD, Dey, Damini, PhD, Shmilovich, Haim, MD, Nakazato, Ryo, MD, Gransar, Heidi, MSc, Cheng, Victor Y., MD, Friedman, John D., MD, Hayes, Sean W., MD, Thomson, Louise E.J., MD, Slomka, Piotr J., PhD, Rozanski, Alan, MD, Berman, Daniel S., MD
Format: Article
Language:English
Subjects:
Adipose Tissue - diagnostic imaging
Aged
Cardiovascular
Case-Control Studies
Chi-Square Distribution
Exercise Test
Female
Humans
Image Interpretation, Computer-Assisted
Logistic Models
Male
Middle Aged
Myocardial Ischemia - diagnostic imaging
Myocardial Ischemia - etiology
Odds Ratio
Pericardium - diagnostic imaging
Predictive Value of Tests
Registries
Risk Assessment
Risk Factors
ROC Curve
Tomography, Emission-Computed, Single-Photon
Tomography, X-Ray Computed
Vasodilator Agents
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Summary:Objectives We evaluated the association between pericardial fat and myocardial ischemia for risk stratification. Background Pericardial fat volume (PFV) and thoracic fat volume (TFV) measured from noncontrast computed tomography (CT) performed for calculating coronary calcium score (CCS) are associated with increased CCS and risk for major adverse cardiovascular events. Methods From a cohort of 1,777 consecutive patients without previously known coronary artery disease (CAD) with noncontrast CT performed within 6 months of single photon emission computed tomography (SPECT), we compared 73 patients with ischemia by SPECT (cases) with 146 patients with normal SPECT (controls) matched by age, gender, CCS category, and symptoms and risk factors for CAD. TFV was automatically measured. Pericardial contours were manually defined within which fat voxels were automatically identified to compute PFV. Computer-assisted visual interpretation of SPECT was performed using standard 17-segment and 5-point score model; perfusion defect was quantified as summed stress score (SSS) and summed rest score (SRS). Ischemia was defined by: SSS − SRS ≥4. Independent relationships of PFV and TFV to ischemia were examined. Results Cases had higher mean PFV (99.1 ± 42.9 cm3 vs. 80.1 ± 31.8 cm3 , p = 0.0003) and TFV (196.1 ± 82.7 cm3 vs. 160.8 ± 72.1 cm3 , p = 0.001) and higher frequencies of PFV >125 cm3 (22% vs. 8%, p = 0.004) and TFV >200 cm3 (40% vs. 19%, p = 0.001) than controls. After adjustment for CCS, PFV and TFV remained the strongest predictors of ischemia (odds ratio [OR]: 2.91, 95% confidence interval [CI]: 1.53 to 5.52, p = 0.001 for each doubling of PFV; OR: 2.64, 95% CI: 1.48 to 4.72, p = 0.001 for TFV). Receiver operating characteristic analysis showed that prediction of ischemia, as indicated by receiver-operator characteristic area under the curve, improved significantly when PFV or TFV was added to CCS (0.75 vs. 0.68, p = 0.04 for both). Conclusions Pericardial fat was significantly associated with myocardial ischemia in patients without known CAD and may help improve risk assessment.
ISSN:1936-878X
1876-7591
DOI:10.1016/j.jcmg.2010.07.014