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Updated: Jan 3, 2026
Author Spotlight: Advancing Cardiovascular Imaging - Introducing the Spatially Weighted Calcium Score for Early Disease Detection
Published on: September 22, 2023
Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary
Mirthe Dekker1,2, Farahnaz Waissi1,2, Ingrid E M Bank3
1Department of Vascular Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
Insights
Adding coronary artery calcium (CAC) scores to myocardial perfusion imaging (MPI) significantly improves the detection of obstructive coronary artery disease (CAD). This combined approach enhances diagnostic accuracy, reducing false negatives in patients without prior revascularization.
Area of Science:
- Cardiology
- Medical Imaging
- Artificial Intelligence
Background:
- Myocardial perfusion imaging (MPI) is a key noninvasive test for diagnosing obstructive coronary artery disease (CAD).
- Coronary artery calcium (CAC) scoring is a validated predictor of cardiovascular events.
- Simultaneous CAC scoring during MPI has not been previously explored.
Purpose of the Study:
- To evaluate if automatically derived CAC scores during MPI enhance diagnostic accuracy for obstructive CAD.
- To assess the incremental value of CAC scores when added to MPI and clinical predictors.
Main Methods:
- 150 patients with suspected obstructive CAD underwent 82Rb PET/CT MPI and coronary angiography.
- CAC scores were automatically computed from low-dose CT scans using deep learning software.
- Obstructive CAD was defined by >70% stenosis or fractional flow reserve (FFR) ≤0.80.
Main Results:
- 58% of patients had obstructive CAD; 74% were male.
- The addition of CAC scores to MPI significantly improved diagnostic accuracy (AUC increased from 0.87 to 0.91, p=0.025).
- The MPI + CAC approach reduced false negatives from 14 to 4, while increasing false positives from 11 to 28.
Conclusions:
- Simultaneously collected CAC scores improve the detection of obstructive CAD.
- This combined approach offers enhanced diagnostic performance in patients without prior coronary revascularization.
Background:
Myocardial perfusion imaging (MPI) is an accurate noninvasive test for patients with suspected obstructive coronary artery disease (CAD) and coronary artery calcium (CAC) score is known to be a powerful predictor of cardiovascular events. Collection of CAC scores simultaneously with MPI is unexplored.
Aim:
We aimed to investigate whether automatically derived CAC scores during myocardial perfusion imaging would further improve the diagnostic accuracy of MPI to detect obstructive CAD.
Methods:
We analyzed 150 consecutive patients without a history of coronary revascularization with suspected obstructive CAD who were referred for 82Rb PET/CT and available coronary angiographic data. Myocardial perfusion was evaluated both semi quantitatively as well as quantitatively according to the European guidelines. CAC scores were automatically derived from the low-dose attenuation correction CT scans using previously developed software based on deep learning. Obstructive CAD was defined as stenosis >70% (or >50% in the left main coronary artery) and/or fractional flow reserve (FFR) ≤0.80.
Results:
In total 58% of patients had obstructive CAD of which seventy-four percent were male. Addition of CAC scores to MPI and clinical predictors significantly improved the diagnostic accuracy of MPI to detect obstructive CAD. The area under the curve (AUC) increased from 0.87 to 0.91 (p: 0.025). Sensitivity and specificity analysis showed an incremental decrease in false negative tests with our MPI + CAC approach (n = 14 to n = 4), as a consequence an increase in false positive tests was seen (n = 11 to n = 28).
Conclusion:
CAC scores collected simultaneously with MPI improve the detection of obstructive coronary artery disease in patients without a history of coronary revascularization.
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