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Static CT myocardial perfusion imaging: image quality, artifacts including distribution and diagnostic performance compared to 82Rb PET.
- Source :
-
European Journal of Hybrid Imaging . 1/4/2022, Vol. 6 Issue 1, p1-18. 18p. - Publication Year :
- 2022
-
Abstract
- Background: Rubidium-82 positron emission tomography (82Rb 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 82Rb PET-MPI for the identification of myocardial ischemia. Methods: Forty-four patients with suspected or diagnosed CAD underwent both static CT-MPI and 82Rb 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 82Rb 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 25103636
- Volume :
- 6
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- European Journal of Hybrid Imaging
- Publication Type :
- Academic Journal
- Accession number :
- 154457635
- Full Text :
- https://doi.org/10.1186/s41824-021-00118-x