Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

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.

Wei-Feng Yuan | Xin-Xiang Zhao | Fu-Bi Hu | Chen Bai | Fang Tang
Medical science monitor : international medical journal of experimental and clinical research | 2019

BACKGROUND 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. MATERIAL AND METHODS 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. RESULTS 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 in LVEF (40.2±10.2% vs. 51.3±3.6%), LVESV (69.0±16.1ml vs. 52.5±10.6ml) and LVSV (42.6±11.4 vs. 52.8±2.8 ml) on Artificial Intelligence was statistically significant between the positive EGE and negative EGE groups (p<0.05). CONCLUSIONS Our results suggest a significant role of EGE on the basis of Lake Louise criteria in evaluating patients with clinical suspicion of acute myocarditis. Parameters, including LVEF, LVESV, and LVSV, on Artificial Intelligence, may be useful independent predictors for capillary leakage and microcirculatory disturbance in myocarditis.

Pubmed ID: 31378779

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

None found

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


American Heart Association (tool)

RRID:SCR_007210

The American Heart Association (AHA) publishes medical scientific statements on various cardiovascular disease and stroke topics. AHA volunteer scientists and healthcare professionals write the papers. The statements are supported by scientific studies published in recognized journals and have a rigorous review and approval process. Scientific statements generally include a review of data available on a specific subject, an evaluation on its relationship to overall cardiovascular disease science, and often an American Heart Association position on the basis of that evaluation. The American Heart Association sponsors accredited scientific conferences and professional development seminars to disseminate new and emerging scientific knowledge and stimulate discussion on future research and the application of knowledge. Keywords: Heart, Cardiovascular, Disease, Stroke, Volunteer, Scientist, Healthcare, Development, Knowledge,

View all literature mentions