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Static CT Myocardial Perfusion Imaging: Image Quality, Artifacts Including Distribution and Diagnostic Performance Compared to Rb PET

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Date 2022 Jan 4
PMID 34981241
Citations 1
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Abstract

Background: Rubidium-82 positron emission tomography (Rb PET) MPI is considered a noninvasive reference standard for the assessment of myocardial perfusion in coronary artery disease (CAD) patients. Our main goal was to compare the diagnostic performance of static rest/ vasodilator stress CT myocardial perfusion imaging (CT-MPI) to stress/ rest Rb PET-MPI for the identification of myocardial ischemia.

Methods: Forty-four patients with suspected or diagnosed CAD underwent both static CT-MPI and Rb PET-MPI at rest and during pharmacological stress. The extent and severity of perfusion defects on PET-MPI were assessed to obtain summed stress score, summed rest score, and summed difference score. The extent and severity of perfusion defects on CT-MPI was visually assessed using the same grading scale. CT-MPI was compared with PET-MPI as the gold standard on a per-territory and a per-patient basis.

Results: On a per-patient basis, there was moderate agreement between CT-MPI and PET-MPI with a weighted 0.49 for detection of stress induced perfusion abnormalities. Using PET-MPI as a reference, static CT-MPI had 89% sensitivity (SS), 58% specificity (SP), 71% accuracy (AC), 88% negative predictive value (NPV), and 59% positive predictive value (PPV) to diagnose stress-rest perfusion deficits on a per-patient basis. On a per-territory analysis, CT-MPI had 73% SS, 65% SP, 67% AC, 90.8% NPV, and 34% PPV to diagnose perfusion deficits.

Conclusions: CT-MPI has high sensitivity and good overall accuracy for the diagnosis of functionally significant CAD using Rb PET-MPI as the reference standard. CT-MPI may play an important role in assessing the functional significance of CAD especially in combination with CCTA.

Citing Articles

Low-dose quantitative CT myocardial flow measurement using a single volume scan: phantom and animal validation.

Hubbard L, Molloi S J Med Imaging (Bellingham). 2023; 10(5):056002.

PMID: 37915404 PMC: 10617548. DOI: 10.1117/1.JMI.10.5.056002.

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