How to standardize the measurement of left ventricular ejection fraction.
Kenya KusunoseRobert ZhengHirotsugu YamadaMasataka SataPublished in: Journal of medical ultrasonics (2001) (2021)
Despite recent advances in imaging for myocardial deformation, left ventricular ejection fraction (LVEF) is still the most important index for systolic function in daily practice. Its role in multiple fields (e.g., valvular heart disease, myocardial infarction, cancer therapy-related cardiac dysfunction) has been a mainstay in guidelines. In addition, assessment of LVEF is vital to clinical decision-making in patients with heart failure. However, notable limitations to LVEF include poor inter-observer reproducibility dependent on observer skill, poor acoustic windows, and variations in measurement techniques. To solve these problems, methods for standardization of LVEF by sharing reference images among observers and artificial intelligence for accurate measurements have been developed. In this review, we focus on the standardization of LVEF using reference images and automated LVEF using artificial intelligence.
Keyphrases
- artificial intelligence
- left ventricular
- ejection fraction
- deep learning
- aortic stenosis
- machine learning
- big data
- hypertrophic cardiomyopathy
- heart failure
- cardiac resynchronization therapy
- cancer therapy
- acute myocardial infarction
- convolutional neural network
- mitral valve
- left atrial
- high resolution
- transcatheter aortic valve replacement
- social media
- aortic valve
- healthcare
- primary care
- physical activity
- drug delivery
- oxidative stress
- coronary artery disease
- optical coherence tomography
- quality improvement