TY - JOUR
T1 - Increased pericardial fat volume measured from noncontrast CT predicts myocardial ischemia by SPECT
AU - Tamarappoo, Balaji
AU - Dey, Damini
AU - Shmilovich, Haim
AU - Nakazato, Ryo
AU - Gransar, Heidi
AU - Cheng, Victor Y.
AU - Friedman, John D.
AU - Hayes, Sean W.
AU - Thomson, Louise E.J.
AU - Slomka, Piotr J.
AU - Rozanski, Alan
AU - Berman, Daniel S.
N1 - Funding Information:
This work was supported by a grant from the National Institute of Biomedical Imaging and Bioengineering ( R21EB006829 to Dr. Dey), the Eisner , Glazer , and Lincy Foundations (to Dr. Berman). The authors have reported that they have no relationships to disclose. Drs. Tamarappoo and Dey contributed equally to this work.
PY - 2010/11
Y1 - 2010/11
N2 - 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.
AB - 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.
KW - Abbreviations and Acronyms
KW - CAD
KW - CCS
KW - CT
KW - MACE
KW - PFV
KW - SPECT
KW - TFV
KW - computed tomography
KW - coronary artery disease
KW - coronary calcium score
KW - major adverse cardiac event(s)
KW - pericardial fat volume
KW - single-photon emission computed tomography
KW - thoracic fat volume
UR - http://www.scopus.com/inward/record.url?scp=78249252033&partnerID=8YFLogxK
U2 - 10.1016/j.jcmg.2010.07.014
DO - 10.1016/j.jcmg.2010.07.014
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C2 - 21070997
AN - SCOPUS:78249252033
SN - 1936-878X
VL - 3
SP - 1104
EP - 1112
JO - JACC: Cardiovascular Imaging
JF - JACC: Cardiovascular Imaging
IS - 11
ER -