Voluson SWIFT; Voluson SWIFT+
GE Medical Systems Ultrasound & Primary Care Diagnostic, LLC • Radiology • 06/20/2023
Device Purpose
The Voluson SWIFT and SWIFT+ are advanced diagnostic ultrasound systems focused on OB/GYN applications with real-time 3D/4D imaging, employing a range of imaging modes and transducer technologies. These systems integrate new software features, including AI-powered tools like Auto-Caliper for follicular assessment, to improve image quality, diagnostic capabilities, and workflow efficiency in clinical practice.
Summary
The Voluson SWIFT and Voluson SWIFT+ are general-purpose diagnostic ultrasound systems primarily designed for qualified healthcare professionals to perform ultrasound imaging, measurement, display, and analysis of the human body and fluids. These systems are specialized for obstetrics and gynecology (OB/GYN) applications, featuring real-time 3D/4D acquisition capabilities, and are built on a mobile console with a full touch monitor, digital acquisition, processing, display, networking, and DICOM functionalities. They support a variety of transducers, including linear, curved linear, and matrix phased array types, for a wide range of clinical applications such as fetal/obstetrics, abdominal, pediatric, small organs, cephalic (neonatal and adult), cardiac, peripheral vascular, musculoskeletal, transrectal, and transvaginal imaging. The systems incorporate numerous imaging modes, including B-mode, M-mode, Anatomical M-Mode, Pulsed Wave (PW) and Continuous Wave (CW) Doppler, Color Doppler, Power Doppler, HD-Flow, Harmonic Imaging, 3D/4D imaging, Elastography, and B-Flow. Significant software enhancements include features such as Shadow Reduction, Autolive, RadiantFlow, Volume with color, Spine Trace, Fractional Limb Volume, Timer for Biophysical Profile (BPP), Fetal Heart Support, SonoPelvic Floor, an AI-driven Auto-Caliper tool, Reminders, and software download capabilities. The Auto-Caliper feature, specifically for 2D caliper placement on follicles, was developed using AI trained on 223 datasets and verified on 67 volumes, demonstrating a success rate of 70% or higher when evaluated by clinical experts comparing AI-generated placements to manual measurements.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. What is the specific clinical impact of the "Auto-Caliper" AI feature on workflow efficiency and measurement consistency in follicular assessment compared to manual methods?; How does the "RadiantFlow" feature quantitatively improve the visualization and assessment of low-velocity blood flow in complex fetal or gynecological vascular structures over traditional Color Doppler?; What are the performance metrics of the "Spine Trace" and "Fractional Limb Volume" tools across varying fetal gestational ages and in the presence of common imaging artifacts?; Can the "SonoPelvic Floor" feature provide standardized, reproducible measurements for pelvic floor muscle assessment, and how does its diagnostic accuracy compare to existing clinical evaluation methods?; Beyond the 70% success rate for follicle identification, what is the measurement accuracy (e.g., mean absolute difference, Bland-Altman analysis) of the "Auto-Caliper" feature compared to expert sonographer measurements?
Risk Classification
ESL AnalysisFDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Authorized before §524B enforcement
Learn how Parasoft automates IEC 62304 compliance testing →Cybersecurity Evidence
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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