Accepted for/Published in: JMIR Research Protocols
Date Submitted: Nov 30, 2022
Date Accepted: Jan 24, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Clinical validation of an artificial intelligence-based tool for automatic estimation of left ventricular ejection fraction and strain in echocardiography: Protocol for a two-phase prospective cohort study
ABSTRACT
Background:
Echocardiography (ECHO) is a type of ultrasound for examining cardiac function and morphology, with functional parameters of the left ventricle (LV), such as the ejection fraction (EF) and global longitudinal strain (GLS), being important indicators. Estimation of LV-EF and LV-GLS is performed either manually or semi-automatically by cardiologists and requires a non-negligible amount of time, while estimation accuracy depends on scan quality and the clinician’s experience in ECHO, leading to considerable measurement variability.
Objective:
The aim of this study is to externally validate the clinical performance of a trained AI-based tool that automatically estimates LV-EF and LV-GLS from transthoracic ECHO scans and to produce preliminary evidence regarding its utility.
Methods:
This is a prospective cohort study conducted in two phases. ECHO scans will be collected from 12O subjects referred for ECHO examination based on routine clinical practice in the Hippokration General Hospital, Thessaloniki, Greece. During the first phase, 60 scans will be processed by 15 cardiologists of different experience levels and the AI-based tool to determine whether the latter is non-inferior in LV-EF and LV-GLS estimation accuracy (primary outcomes) compared to cardiologists. Secondary outcomes include the time required for estimation and Bland-Altman plots and intra-class correlation coefficients to assess measurement reliability for both the AI and cardiologists. In the second phase, the rest of the scans will be examined by the same cardiologists with and without the AI-based tool to primarily evaluate whether the combination of the cardiologist and the tool is superior to the cardiologist alone in terms of LV function diagnosis correctness, accounting for the level of ECHO experience. Secondary outcomes include time to diagnosis and the system usability scale score. Reference LV-EF and LV-GLS measurements and LV function diagnoses will be provided by a panel of three expert cardiologists.
Results:
Recruitment started in September 2022 and data collection is ongoing. Results of the first phase are expected to be available by summer 2023, while the study will conclude in May 2024, with the end of the second phase.
Conclusions:
This study will provide external evidence regarding the clinical performance and utility of the AI-based tool based on prospective data collected in real-world clinical scenarios. The study protocol may be useful to investigators conducting similar research. Clinical Trial: -
Citation
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