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Acta Physiol Hung ; 102(2): 206-15, 2015 Jun.
Article in English | MEDLINE | ID: mdl-26100310

ABSTRACT

UNLABELLED: Tissue level myocardial perfusion is one of the most important prognostic factors after successful recanalisation of the occluded coronary artery in patients suffering acute ST elevation myocardial infarction (STEMI). The primary objective of the present study was to examine the relationship between videodensitometric myocardial perfusion parameters as assessed on coronary angiograms directly following successful recanalization therapy and magnetic resonance imaging (MRI)-derived myocardial tissue loss late after STEMI. The study comprised 29 STEMI patients. Videodensitometric parameter G(max)/T(max) was calculated to characterize myocardial perfusion, derived from the plateau of grey-level intensity (G(max)), divided by the time-to-peak intensity (Tmax). Myocardial loss index (MLI) was assessed by cardiac MRI following 376 ± 254 days after PCI. RESULTS: Significant correlations could be demonstrated between MLI and G(max) (r = 0.36, p = 0.05) and G(max)/T(max) (r = 0.40, p = 0.03) using vessel masking. Using receiver operating characteristic curve analysis, G(max)/T(max) < 2.17 predicted best MLI = 0.3, 0.4, 0.5 and 0.6 with good sensitivity and specificity data, while G(max)/T(max) < 3.25 proved to have a prognostic role in the prediction of MLI = 0.7. CONCLUSIONS: Selective myocardial tissue level perfusion quantitative measurement method is feasible and can serve as a good predictor of myocardial tissue loss following STEMI and revascularization therapy.


Subject(s)
Angiography, Digital Subtraction , Coronary Angiography , Coronary Circulation , Densitometry , Myocardial Infarction/diagnosis , Myocardial Perfusion Imaging/methods , Myocardium/pathology , Aged , Feasibility Studies , Female , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Myocardial Infarction/physiopathology , Myocardial Infarction/therapy , Percutaneous Coronary Intervention , Predictive Value of Tests , Radiographic Image Interpretation, Computer-Assisted , Registries , Treatment Outcome , Video Recording
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