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Updated: May 31, 2025
Evaluation of Left Ventricular Structure and Function using 3D Echocardiography
Published on: October 28, 2020
CardiacField: computational echocardiography for automated heart function estimation using two-dimensional
Chengkang Shen1, Hao Zhu1, You Zhou1,2
1School of Electronic Science and Engineering, Nanjing University, Nanjing 210023, China.
Insights
CardiacField uses 2D echocardiography to precisely estimate heart function, offering an easy-to-use solution for healthcare practitioners to assess ejection fraction (EF) with accuracy comparable to advanced methods.
Area of Science:
- Computational imaging
- Cardiovascular diagnostics
- Medical artificial intelligence
Background:
- Accurate heart function estimation is crucial for cardiovascular disease management.
- Two-dimensional echocardiography (2DE) has limitations including required expertise and lack of 3D data.
- Existing methods can be complex and prone to variability.
Purpose of the Study:
- To introduce CardiacField, an automated system for precise left ventricular (LV) and right ventricular (RV) ejection fraction (EF) estimation using 2DE.
- To evaluate the usability and performance of CardiacField among novice users and compare it to expert interpretations and deep learning (DL) tools.
Main Methods:
- Developed an implicit neural representation network to reconstruct 3D cardiac volumes from multi-view 2DE images.
- Implemented automatic segmentation for LV and RV areas to calculate EF.
- Assessed accuracy against expert readings and 2D DL models in 127 patients.
Main Results:
- CardiacField processed 2D echocardiograms into 3D heart models in under 2 minutes.
- Achieved a Mean Absolute Error (MAE) of [specific MAE value] for LVEF and [specific MAE value] for RVEF.
- Demonstrated usability among novice users across various ultrasound machines.
Conclusions:
- CardiacField provides accurate EF estimations for LV and RV function comparable to 3D echocardiography.
- The system utilizes a simple apical ring scan with a cost-effective 2DE probe.
- Offers an accessible tool for non-cardiovascular specialists to assess cardiac function.
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.
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