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Updated: Jul 27, 2025
In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Diagnostic performance of clinical likelihood models of obstructive coronary artery disease to predict myocardial
Laust Dupont Rasmussen1, Line Emilie Brøgger Albertsen1, Louise Nissen1
1Department of Cardiology, Gødstrup Hospital, Hospitalsparken 15, Herning DK-7400, Denmark.
Insights
The coronary artery calcium score-weighted (CACS-CL) model significantly improved the diagnosis of myocardial perfusion defects (MPDs) in patients with suspected coronary artery disease compared to traditional clinical likelihood (CL) models.
Area of Science:
- Cardiology
- Medical Imaging
- Diagnostic Accuracy
Background:
- Clinical likelihood (CL) models for coronary artery disease (CAD) typically rely on coronary stenosis as a reference standard.
- A reference standard for myocardial perfusion defects (MPDs) may be more appropriate for assessing CAD.
- Existing models like the European Society of Cardiology pre-test probability (ESC-PTP) have limitations in accurately stratifying risk.
Purpose of the Study:
- To evaluate the diagnostic performance of the 2019 ESC-PTP, risk-factor-weighted CL (RF-CL), and coronary artery calcium score-weighted CL (CACS-CL) models for identifying MPDs.
- To compare the ability of these models to classify patients into low-risk categories for obstructive CAD and MPDs.
Main Methods:
- A cohort of 3374 symptomatic stable chest pain patients underwent coronary computed tomography angiography (CCTA) and myocardial perfusion imaging (MPI).
- MPDs were defined by CCTA findings of suspected stenosis combined with stress-perfusion abnormalities in at least two segments.
- ESC-PTP, RF-CL, and CACS-CL models were calculated using varying combinations of age, sex, symptom typicality, risk factors, and CACS.
Main Results:
- The prevalence of MPDs in the study population was 6.5% (219/3374).
- RF-CL and CACS-CL models classified significantly more patients into a low CL (<5%) category for obstructive CAD compared to ESC-PTP (54.1% and 32.5% vs. 12.0%, respectively).
- The CACS-CL model demonstrated superior discrimination for MPDs (AUC 0.88) compared to ESC-PTP (AUC 0.74), while RF-CL showed similar performance (AUC 0.73).
Conclusions:
- The RF-CL and CACS-CL models enhance the down-classification of patients to a very low-risk group.
- These advanced models, particularly CACS-CL, offer improved diagnostic accuracy for MPDs in patients with suspected obstructive CAD.
- Utilizing MPDs as a reference standard and incorporating CACS improves risk stratification for coronary artery disease.
Aims:
Clinical likelihood (CL) models are designed based on a reference of coronary stenosis in patients with suspected obstructive coronary artery disease. However, a reference standard for myocardial perfusion defects (MPDs) could be more appropriate. We aimed to investigate the ability of the 2019 European Society of Cardiology pre-test probability (ESC-PTP), the risk-factor-weighted (RF-CL) model, and coronary artery calcium score-weighted (CACS-CL) model to diagnose MPDs.
Methods And Results:
Symptomatic stable de novo chest pain patients (n = 3374) underwent coronary computed tomography angiography and subsequent myocardial perfusion imaging by single-photon emission computed tomography, positron emission tomography, or cardiac magnetic resonance. For all modalities, MPD was defined as coronary computed tomography angiography with suspected stenosis and stress-perfusion abnormality in ≥2 segments. The ESC-PTP was calculated based on age, sex, and symptom typicality, and the RF-CL and CACS-CL additionally included a number of risk factors and CACS. In total, 219/3374 (6.5%) patients had an MPD. Both the RF-CL and the CACS-CL classified substantially more patients to low CL (<5%) of obstructive coronary artery disease compared with the ESC-PTP (32.5 and 54.1 vs. 12.0%, P < 0.001) with preserved low prevalences of MPD (<2% for all models). Compared with the ESC-PTP [area under the receiver-operating characteristic curve (AUC) 0.74 (0.71-0.78)], the discrimination of having an MPD was higher for the CACS-CL model [AUC 0.88 (0.86-0.91), P < 0.001], while it was similar for the RF-CL model [AUC 0.73 (0.70-0.76), P = 0.32].
Conclusion:
Compared with basic CL models, the RF-CL and CACS-CL models improve down classification of patients to a very low-risk group with a low prevalence of MPD.
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