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Updated: Aug 5, 2026
Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography
Published on: October 28, 2020
Agreement of AI-assisted semi-automated right ventricular function analysis using 3D transthoracic echocardiography
Noriko Shiokawa1,2, Masaki Izumo3,4, Yukio Sato1,2
1Ultrasound Center, St. Marianna University Hospital, Kawasaki, Japan.
Background:
Advances in three-dimensional (3D) transthoracic echocardiography (TTE) with artificial intelligence (AI) enable AI-assisted semi-automated right ventricular (RV) function analysis, including two-dimensional (2D) measurements. However, data on the agreement of these semi-automated analyses in routine clinical practice remain limited. This study evaluates the agreement of AI-based 3D TTE semi-automated measurements compared to manual 2D TTE measurements.
Methods:
We enrolled 201 patients who underwent both 2D and 3D TTE between July and November 2023. AI-assisted semi-automated measurements of right ventricular morphology and functional parameters were performed using 3D Auto RV software. While echocardiographic images were acquired manually by the operators in a conventional manner, the AI-assisted analysis was applied specifically during the post-acquisition offline processing stage.
Results:
The feasibility of RV measurement using the AI-based software was 84.8% (201/237) among patients with available 3D datasets, and the overall applicability was 67.4% (201/298) across all consecutive patients undergoing routine echocardiography. Among the 201 analyzed cases, fully automated analysis without manual correction was feasible in 10.9% (22/201), while the remaining 89.1% required manual adjustments of the endocardial borders to ensure clinical accuracy. Time for analysis was significantly shorter with the AI-assisted semi-automated method compared to the manual 2D method (30% reduction, p < 0.001).
Conclusions:
AI-based 3D TTE semi-automated measurement has the potential to enhance the efficiency and reproducibility of RV function assessment, reducing examiner workload and improving clinical workflow.
