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Updated: May 22, 2026

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
Coronary calcium score as an adjunct to nuclear myocardial perfusion imaging for risk stratification before
Jelena R Ghadri1, Michael Fiechter, Katja Veraguth
1Department of Radiology, Cardiac Imaging, University Hospital Zurich, Zurich, Switzerland.
Unlabelled:
The purpose of this study was to evaluate the added value of coronary artery calcium score (CACS) as an adjunct to myocardial perfusion imaging (MPI) with SPECT for cardiac risk stratification before noncardiac surgery. SPECT MPI is a well-established and widely used tool for preoperative risk stratification before noncardiac surgery. The potential added value of combining SPECT MPI with CACS is unknown.
Methods:
We included 326 consecutive patients who were referred for SPECT MPI for preoperative cardiac risk assessment before elective noncardiac surgery. All patients underwent an additional low-dose CT scan for CACS and SPECT MPI. Patients were followed up for 40 d after their index surgical procedure, and the occurrence of major adverse cardiovascular events (MACE), including death, myocardial infarction, revascularization, stroke, and sudden cardiac death, was registered.
Results:
Postoperative MACE occurred in 30 patients (9%). Cumulative MACE rate was highest in patients with abnormal SPECT and high CACS (22%), defined by a cutoff value CACS of 1,314 or more, and lowest in patients with normal SPECT MPI findings and low CACS (5%) (CACS < 1,314). A CACS score of 1,314 or more was independently associated with a higher MACE rate in patients with normal (12% vs. 5%) or abnormal perfusion (22% vs. 12%, P < 0.05 for all intergroup comparisons).
Conclusion:
SPECT MPI findings and CACS are strong preoperative risk predictors. CACS allows further risk stratification, indicating very low risk when CACS less than 1,314 is associated with normal SPECT MPI findings. Conversely, in patients with abnormal SPECT MPI findings, a CACS of 1,314 or more confers an added value for predicting adverse outcomes.
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