EPIQ Series Diagnostic Ultrasound System, Affiniti Series Diagnostic Ultrasound System
Philips Medical Systems • Radiology • 09/08/2021
Device Purpose
The Philips EPIQ and Affiniti Series Diagnostic Ultrasound Systems are enhanced with the "Auto Measure" software feature, which aims to streamline adult transthoracic echocardiography. This feature employs an AI/ML-enabled algorithm to provide semi-automated, editable 2D and Doppler measurements, intending to improve workflow efficiency while maintaining clinician oversight and control over the final diagnostic data.
Summary
The Philips EPIQ and Affiniti Series Diagnostic Ultrasound Systems are established, reusable medical devices designed for a wide array of high-resolution general imaging applications, including interventional radiology, cardiology, vascular studies, obstetrics, and gynecology, as well as fluid flow analysis. These systems are intended for use by trained healthcare professionals across various clinical settings and can be used for applications such as abdominal, cardiac (adult, fetal, pediatric), vascular, obstetric, gynecological, musculoskeletal, and small organ imaging. This documentation details the introduction of the "Auto Measure" software-only feature, designed to enhance the existing capabilities of these ultrasound platforms by automating certain measurement tasks. The "Auto Measure" feature leverages an AI/ML-enabled algorithm to provide semi-automated functionality for a subset of 2D and Doppler measurements. This tool is specifically applied during adult transthoracic echocardiography (TTE) when an electrocardiogram (ECG) is simultaneously acquired. The algorithm generates measurements that are editable, allowing clinicians to review, accept, modify, or reject them, thereby integrating automated assistance with essential clinical oversight. Performance data from a Performance Validation Study and comprehensive software verification and validation confirmed that the Auto Measure feature meets its design requirements and performance claims, offering functionality comparable to existing manual measurement techniques but with the added benefit of automation and the potential for improved workflow efficiency.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. What specific 2D and Doppler measurements are included in the "Auto Measure" feature's semi-automated functionality for adult transthoracic echocardiography?; How was the AI/ML algorithm for "Auto Measure" trained and validated, particularly concerning dataset diversity and performance benchmarks against expert manual measurements?; What is the typical time-saving or efficiency gain observed when using "Auto Measure" for TTE compared to purely manual measurements in a clinical workflow?; Are there any known limitations or specific patient populations/cardiac conditions where the "Auto Measure" algorithm's accuracy might be reduced or require more significant manual editing?; How does the "Auto Measure" feature integrate with existing Picture Archiving and Communication Systems (PACS) and reporting workflows, including the process for accepting, editing, or rejecting its outputs in the patient record?
Risk Classification
ESL AnalysisFDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Authorized before §524B enforcement
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Powered by SBOMator™Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.
Supply Chain BOM Evidence
Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.
Analysis:
• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.
• Evidence of ML-BOM, SaaSBOM detected in AI-generated device summary.
• This device was authorized before §524B took effect. Cybersecurity evidence requirements were less prescriptive at the time.
• Postmarket cybersecurity monitoring plan not clearly documented in AI-generated device summary.
• Not detected in AI-generated device summary: SBOM, HBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.
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