Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis.
Journal:
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
PMID:
38556134
Abstract
BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and the peak late (A) transmitral flow velocity, is the first step to defining the grade of diastolic dysfunction. Doppler echocardiography (echo) is the preferred imaging technique for diastolic function assessment, while cardiovascular magnetic resonance (CMR) is less established as a method. Previous four-dimensional (4D) Flow-based studies have looked at the E/A ratio proximal to the mitral valve, requiring manual interaction. In this study, we compare an automated, deep learning-based and two semi-automated approaches for 4D Flow CMR-based E/A ratio assessment to conventional, gold-standard echo-based methods.
Authors
Keywords
Aged
Automation
Blood Flow Velocity
Chronic Disease
Deep Learning
Diastole
Echocardiography, Doppler
Female
Humans
Image Interpretation, Computer-Assisted
Magnetic Resonance Imaging, Cine
Male
Middle Aged
Mitral Valve
Myocardial Ischemia
Predictive Value of Tests
Reproducibility of Results
Ventricular Dysfunction, Left
Ventricular Function, Left