Risultati per: POCUS in Medicina Generale. Il punto di vista dello specialista

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Abstract 16836: A View-Invariant Deep Learning Model for Estimating Ejection Fraction From Any Valid Echocardiogram Videoclip, Including Point-of-Care Ultrasound (POCUS)

Circulation

Circulation, Volume 148, Issue Suppl_1, Page A16836-A16836, November 6, 2023. Background:Recently, our team developed an end-to-end artificial intelligence (AI) framework that can successfully estimate left ventricular ejection fraction (LVEF) from echocardiogram videos. However, this framework requires specific views (A2C and PLAX), and cannot estimate LVEF for studies from which these views are missing.Goal:To develop a deep learning model to estimate LVEF from any type and number of echocardiogram video(s).Methods:We built a deep learning model for B-mode echocardiogram videos of the left ventricle (A2C, A3C, A4C, or PLAX views), using retrospective transthoracic echocardiography (TTE) data. The model was evaluated with two test datasets: one with random valid (i.e., showing the left ventricle) views, and one with preselected views (both having 433 patients). Later, the model was tested with a prospective patient cohort that had both TTE and point-of-care ultrasound (POCUS) data collected simultaneously (393 patients).Results:On the retrospective TTE test set, we observed excellent performance (five random valid views per study: RMSE of 6.87% and Pearson correlation (PC) of 0.82 on LVEF estimation, and an AUC of 0.96 (95% CI: of 0.94-0.98) on low LVEF classification (

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