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Artificial Intelligence Improves Apical Four-Chamber Window Quality in Experienced but Not Novice Users
Jacob Lenning1, Corey L Garrison1, Aaron R Mahoney1
1Emergency Medicine, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, USA.
Cureus
|March 23, 2026
Summary
Artificial intelligence (AI) in point-of-care ultrasound (POCUS) prolonged acquisition times for novice users but improved image quality for experienced users. AI assistance in POCUS cardiac imaging requires consideration of user experience level for optimal integration.
Area of Science:
- Medical Ultrasound
- Artificial Intelligence in Medicine
- Cardiology
Background:
- Current point-of-care ultrasound (POCUS) machines integrate artificial intelligence (AI) for cardiac window acquisition assistance.
- Previous research primarily assessed AI's utility for novice POCUS users.
- This study investigates AI's immediate impact on acquisition time and image quality for apical four-chamber (A4C) views across user experience levels.
Purpose of the Study:
- To evaluate the effect of AI assistance on the acquisition time and image quality of A4C cardiac ultrasound windows.
- To compare these effects between novice and experienced POCUS users.
Main Methods:
- Fourteen novice and 10 experienced emergency medicine residents acquired A4C views with and without AI assistance on standardized patients.
- Acquisition times were compared using the Mann-Whitney U test.
- Image quality was assessed based on the visibility of essential structures, correct imaging plane, and proper probe placement using Chi-square analysis.
Main Results:
- AI assistance significantly increased acquisition time for novice users (136 seconds vs. 75 seconds, p < .01) but not for experienced users (98 seconds vs. 66 seconds, p = .18).
- Experienced users were more likely to achieve all image quality criteria than novices.
- For experienced users, AI assistance improved the visibility of essential structures (p = .06) and the correctness of the imaging plane (p = .03), but not probe placement.
Conclusions:
- AI assistance in POCUS A4C view acquisition leads to longer acquisition times in novice users and shows a similar trend in experienced users.
- AI improves image quality for experienced users, particularly in achieving correct imaging planes and visualizing structures, but not for novices.
- Medical educators should tailor the integration of AI POCUS features based on learner experience to optimize both education and clinical practice.
