CardiacField: Computational Echocardiography for Automated Heart Function Estimation Using Two-dimensional Echocardiography Probes

Overview

Journal Eur Heart J Digit Health

Publisher Oxford University Press

Date 2025 Jan 23

PMID 39846074

Authors

Chengkang Shen

Hao Zhu

You Zhou

Yu Liu

Si Yi

Lili Dong

Weipeng Zhao

David J Brady

Xun Cao

Zhan Ma

Yi Lin

Affiliations

Soon will be listed here.

Abstract

Aims: Accurate heart function estimation is vital for detecting and monitoring cardiovascular diseases. While two-dimensional echocardiography (2DE) is widely accessible and used, it requires specialized training, is prone to inter-observer variability, and lacks comprehensive three-dimensional (3D) information. We introduce CardiacField, a computational echocardiography system using a 2DE probe for precise, automated left ventricular (LV) and right ventricular (RV) ejection fraction (EF) estimations, which is especially easy to use for non-cardiovascular healthcare practitioners. We assess the system's usability among novice users and evaluate its performance against expert interpretations and advanced deep learning (DL) tools.

Methods And Results: We developed an implicit neural representation network to reconstruct a 3D cardiac volume from sequential multi-view 2DE images, followed by automatic segmentation of LV and RV areas to calculate volume sizes and EF values. Our study involved 127 patients to assess EF estimation accuracy against expert readings and two-dimensional (2D) video-based DL models. A subset of 56 patients was utilized to evaluate image quality and 3D accuracy and another 50 to test usability by novice users and across various ultrasound machines. CardiacField generated a 3D heart from 2D echocardiograms with <2 min processing time. The LVEF predicted by our method had a mean absolute error (MAE) of , while the RVEF had an MAE of .

Conclusion: Employing a straightforward apical ring scan with a cost-effective 2DE probe, our method achieves a level of EF accuracy for assessing LV and RV function that is comparable to that of three-dimensional echocardiography probes.

Citing Articles

Reinventing 3D echocardiography: could AI-powered 3D reconstruction from 2D echocardiographic views serve as a viable alternative to 3D probes?.

Tokodi M, Kovacs A Eur Heart J Digit Health. 2025; 6(1):3-4.

PMID: 39846072 PMC: 11750183. DOI: 10.1093/ehjdh/ztae078.

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