Evaluation of Early Gadolinium Enhancement (EGE) and Cardiac Functional Parameters in Cine-Magnetic Resonance Imaging (MRI) on Artificial Intelligence in Patients with Acute Myocarditis: A Case-Controlled Observational Study

Medical Science Monitor : International Medical Journal of Experimental and Clinical Research
Wei-Feng YuanFang Tang

Abstract

<strong>BACKGROUND</strong> The diagnosis of myocarditis is challenging, and the treatment is generally delayed due to misdiagnosis or missed diagnosis. Endomyocardial biopsy (EMB) is not a specific or sensitive method. A case-controlled observational study was conducted to evaluate early gadolinium enhancement (EGE) and left ventricular functional parameters on Artificial Intelligence in cine-MRI in patients with acute myocarditis. <strong>MATERIAL AND METHODS</strong> We selected 21 patients with pathologically proven acute myocarditis. We analyzed the EGE findings (total/serial number and location of positive-segments using the 17-segment model according to the American Heart Association) and clinical characteristics (symptoms, arrhythmias in ECG, coronary angiography, and EMB). All patients were divided into positive EGE and negative EGE groups to analyze left ventricular functional parameters (LVEF, FS, LVEDD, LVEDV, LVESV, LVMM, LVSV, CO, and CI) on Artificial Intelligence. <strong>RESULTS</strong> We enrolled 21 patients (11 males) with a mean age of 32.6±9.8 years (range, 16 to 51 years). Abnormalities on EGE were found in 2/3 of patients, involving 41 segments among multiple locations on the myocardium. The differences...Continue Reading

Methods Mentioned

BETA
biopsies
biopsy
X-ray

Software Mentioned

Semi
Automatic
Intelligence Workstation EWS Cardiac Analysis
SPSS
Intelligence
Artificial

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