Abstract
Introduction: Echocardiography is widely used because of its portability, high temporal resolution, absence of radiation, and due to the low-costs. Over the past years, echocardiography has been recommended by the European Society of Cardiology in most cardiac diseases for both diagnostic and prognostic purposes. These recommendations have led to an increase in number of performed studies each requiring diligent processing and reviewing. The standard work pattern of image analysis including quantification and reporting has become highly resource intensive and time consuming. Existence of a large number of datasets with digital echocardiography images and recent advent of AI technology have created an environment in which artificial intelligence (AI) solutions can be developed successfully to automate current manual workflow.Methods and Results: We report on published AI solutions for echocardiography analysis on methods' performance, characteristics of the used data and imaged population. Contemporary AI applications are available for automation and advent in the image acquisition, analysis, reporting and education. AI solutions have been developed for both diagnostic and predictive tasks in echocardiography. Left ventricular function assessment and quantification have been most often performed. Performance of automated image view classification, image quality enhancement, cardiac function assessment, disease classification, and cardiac event prediction was overall good but most studies lack external evaluation.Conclusion: Contemporary AI solutions for image acquisition, analysis, reporting and education are developed for relevant tasks with promising performance. In the future major benefit of AI in echocardiography is expected from improvements in automated analysis and interpretation to reduce workload and improve clinical outcome. Some of the challenges have yet to be overcome, however, none of them are insurmountable.
Highlights
Echocardiography is widely used because of its portability, high temporal resolution, absence of radiation, and due to the low-costs
The results demonstrated superior performance compared to individual echocardiographic indices early-to-late diastolic transmitral velocity ratio, e’, and strain (p = 0.04)
We summarize eleven studies on the development of artificial intelligence (AI) in the field of routine echocardiography
Summary
Echocardiography is widely used because of its portability, high temporal resolution, absence of radiation, and due to the low-costs. Echocardiography is the most commonly performed noninvasive cardiac procedure It is the recommended imaging modality for most cardiac diseases for diagnostic and prognostic purposes by the European Society of Cardiology [1,2,3,4,5,6,7]. They are often overloaded with routine tasks inherent to echocardiographic exams and sometimes miss very specialized expertise It takes years of education and experience for a technician or cardiologist to become an expert in detecting perceptual cues in echocardiography clips and automatically integrating this information into a clinical differentiation based upon pattern recognition without overt statistical reasoning. Volume of exams is rising due to new diagnostic assessments and therapeutic options leading to a further increase in expert workload [11,12,13]
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