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Updated: Feb 19, 2026

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
Identification of coronary artery calcification can optimize risk stratification in patients with acute chest pain
Daniel O Bittner1, Richard A P Takx2, Pedro V Staziaki3
1Cardiac MR PET CT Program, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Friedrich-Alexander University Erlangen-Nürnberg (FAU), Department of Cardiology, University Hospital Erlangen, Germany.
Background:
The number of patients presenting to the emergency department (ED) with suspected acute coronary syndrome (ACS) is substantial. We tested whether identification of coronary artery calcium (CAC) can improve the negative predictive value (NPV) of clinical risk assessment for ACS in patients with acute chest pain.
Methods And Results:
We included 826 consecutive patients (mean age: 53±11years; 42% female) without known coronary artery disease (CAD) or initially elevated serum biomarkers, whom underwent non-contrast CT, to assess the CAC score, and CT angiography (CTA), to detect coronary stenosis. We analyzed the diagnostic performance of CAC and the Thrombolysis In Myocardial Infarction (TIMI) risk score for our primary outcomes (ACS and obstructive CAD). No CAC was found in 54% (n=444) of all patients, 63% (n=524) had a TIMI score of 0 and 40% (n=328) had both. The prevalence of obstructive CAD was 16% for ≥50% stenosis and 8.7% for ≥70% stenosis. The incidence of ACS was 7.9%, (MI=11, UAP=54). The NPV of CAC=0 was 99.5% for ACS. The NPV of a combination of TIMI score=0 and no CAC was 89% for any CAD (any plaque or stenosis) and 99.7% for ≥50% stenosis. A 100% NPV was found for ≥70% stenosis and ACS, correctly identifying 328 (40%) patients.
Conclusions:
The exclusion of CAC, in combination with clinical risk assessment, has high clinical value in patients with acute chest pain, as it identifies patients at low risk for ACS and obstructive CAD more accurately as compared to clinical risk assessment alone.
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