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Updated: May 9, 2026

In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Diagnostic accuracy of low-dose myocardial perfusion imaging in a real-world setting
Mathieu Perrin1, Marine Claudin1, Karim Djaballah2
1Université de Lorraine, CHRU-Nancy, Department of Nuclear Medicine and Nancyclotep Imaging Platform, Nancy, F-54000, France.
Background:
This large-scale study analyzes factors affecting the diagnostic accuracy of low-dose myocardial perfusion imaging and correlation with coronary angiography in a real-world practice.
Methods:
We compared data extracted from routine reports of (i) low-dose [99mTc]sestamibi stress-MPI performed with no attenuation correction and predominantly exercise stress testing and (ii) the corresponding coronary angiography.
Results:
We considered 1070 pairs of coronary angiography/stress-MPI results reported by 11 physicians. Mean MPI effective dose was 4.5 ± 2.1 mSv. The extent of MPI-ischemia was predictive of >70% but not 50%-70% coronary stenoses. A positive test was associated with a sensitivity of 74.7% (413/553) and a specificity of 53.2% (275/517) for >70% stenosis detection. Positive predictive values were lower in patients with left bundle branch block or pacemakers (LBBB/PM) (45.6% vs 64.7%, P = .006) and markedly higher for patients with MPI-ischemia ≥3 segments or associated with ST-segment depression (75.0% (165/220)) as compared to those with <3 segments MPI-ischemia, MPI-infarction or isolated ST-segment depression (57% (248.0/435), P < .001). Negative predictive values were lower for patients with previous coronary artery disease (CAD) history (58.3%), male (61.0%), and elderly patients (59.6%) (vs 72.1%, 79.2%, and 72.4%, respectively, all P < .05).
Conclusions:
Routine results from low-dose stress-MPI, predominantly associated with exercise stress testing and uncorrected for attenuation, correlate with real-world coronary angiography results. However, this correlation is lower than that achieved with conventional study designs and affected by the definition of significant CAD and context variables (LBBB/PM, CAD history, sex, and age). Better consideration of these interacting factors could improve patient monitoring.
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