EPIQ Series Diagnostic Ultrasound System; Affiniti Series Diagnostic Ultrasound System

Philips Ultrasound's R-Trigger AI algorithm represents a significant advancement by enabling critical transthoracic echocardiography applications to function without reliance on an ECG signal, leveraging artificial intelligence to directly identify the R-wave peak from ultrasound data. This innovative approach was rigorously validated through comprehensive non-clinical testing and an extensive retrospective data analysis, demonstrating high agreement with ECG-based triggering and ensuring continued safe and effective clinical performance.

Philips Ultrasound LLC has introduced the R-Trigger AI algorithm as a new software feature for its EPIQ and Affiniti Series Diagnostic Ultrasound Systems. This innovation is designed to detect the R-wave peak, serving as a critical input for existing transthoracic echocardiography (TTE) clinical applications like AutoStrain and AutoMeasure, which traditionally relied on an ECG signal. The primary purpose of this update is to enhance workflow by enabling these applications to function effectively even when an ECG signal is unavailable or unusable, all without requiring any hardware modifications to the ultrasound systems. The R-Trigger software, along with the updated systems, underwent comprehensive non-clinical verification testing to ensure continued safe and effective performance. A key part of its validation involved a retrospective data analysis study, evaluating the AI algorithm's accuracy in detecting R-wave timestamps and its subsequent impact on the clinical outputs of AutoMeasure and AutoStrain. This extensive study, which analyzed over 7,000 cardiac clips from nearly 4,000 diverse subjects, demonstrated a high degree of agreement between the AI-based R-trigger and the conventional ECG-based R-trigger, confirming the software modification meets its intended use and poses no new safety or effectiveness concerns.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. What specific patient populations or clinical scenarios might benefit most from the R-Trigger AI algorithm's ability to function without an ECG signal?; How does the R-Trigger AI algorithm handle artifact or noisy ultrasound data compared to a clean ECG signal, and what are its limitations in such challenging cases?; Were there any specific types of cardiac pathologies or anatomical variations where the AI-based R-trigger showed reduced agreement with the ECG-based method during the retrospective study?; What is the potential impact of the R-Trigger AI algorithm on diagnostic confidence and inter-operator variability in echocardiography studies performed without ECG?; Are there plans for prospective, multi-center clinical trials to further validate the R-Trigger AI algorithm's performance and clinical utility in a real-world setting?