1
|
Jeong D, Jung S, Yoon YE, Jeon J, Jang Y, Ha S, Hong Y, Cho J, Lee SA, Choi HM, Chang HJ. Artificial intelligence-enhanced automation for M-mode echocardiographic analysis: ensuring fully automated, reliable, and reproducible measurements. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024; 40:1245-1256. [PMID: 38652399 DOI: 10.1007/s10554-024-03095-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 03/25/2024] [Indexed: 04/25/2024]
Abstract
To enhance M-mode echocardiography's utility for measuring cardiac structures, we developed and evaluated an artificial intelligence (AI)-based automated analysis system for M-mode images through the aorta and left atrium [M-mode (Ao-LA)], and through the left ventricle [M-mode (LV)]. Our system, integrating two deep neural networks (DNN) for view classification and image segmentation, alongside an auto-measurement algorithm, was developed using 5,958 M-mode images [3,258 M-mode (LA-Ao), and 2,700 M-mode (LV)] drawn from a nationwide echocardiographic dataset collated from five tertiary hospitals. The performance of view classification and segmentation DNNs were evaluated on 594 M-mode images, while automatic measurement accuracy was tested on separate internal test set with 100 M-mode images as well as external test set with 280 images (140 sinus rhythm and 140 atrial fibrillation). Performance evaluation showed the view classification DNN's overall accuracy of 99.8% and segmentation DNN's Dice similarity coefficient of 94.3%. Within the internal test set, all automated measurements, including LA, Ao, and LV wall and cavity, resonated strongly with expert evaluations, exhibiting Pearson's correlation coefficients (PCCs) of 0.81-0.99. This performance persisted in the external test set for both sinus rhythm (PCC, 0.84-0.98) and atrial fibrillation (PCC, 0.70-0.97). Notably, automatic measurements, consistently offering multi-cardiac cycle readings, showcased a stronger correlation with the averaged multi-cycle manual measurements than with those of a single representative cycle. Our AI-based system for automatic M-mode echocardiographic analysis demonstrated excellent accuracy, reproducibility, and speed. This automated approach has the potential to improve efficiency and reduce variability in clinical practice.
Collapse
Affiliation(s)
- Dawun Jeong
- Department of Internal Medicine, Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine, Seoul, South Korea
- CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, South Korea
| | - Sunghee Jung
- CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, South Korea
- Ontact Health Inc, Seoul, South Korea
| | - Yeonyee E Yoon
- Ontact Health Inc, Seoul, South Korea.
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, Seoul National University Bundang Hospital, Gumi-Ro 173, Bundang-Gu, Seongnam, Gyeonggi-Do, 13620, South Korea.
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.
| | | | | | - Seongmin Ha
- CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, South Korea
- Ontact Health Inc, Seoul, South Korea
- Graduate School of Biomedical Engineering, Yonsei University College of Medicine, Seoul, South Korea
| | - Youngtaek Hong
- CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, South Korea
- Ontact Health Inc, Seoul, South Korea
| | | | | | - Hong-Mi Choi
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, Seoul National University Bundang Hospital, Gumi-Ro 173, Bundang-Gu, Seongnam, Gyeonggi-Do, 13620, South Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
| | - Hyuk-Jae Chang
- CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, South Korea
- Ontact Health Inc, Seoul, South Korea
- Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Yonsei University Health System, Seoul, South Korea
| |
Collapse
|